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<strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong> <strong>through</strong> <strong>the</strong> <strong>GEOSS</strong><br />
<strong>Architecture</strong><br />
Engineering Report<br />
<strong>GEOSS</strong> <strong>Architecture</strong> Implementation Pilot (AIP)<br />
<strong>Drought</strong> and Water Working Group<br />
Content developed by <strong>the</strong> GEO <strong>Architecture</strong> Implementation Pilot<br />
Licensed under a Creative Commons Attribution 3.0 License<br />
Version 2.0
Content developed by <strong>the</strong> GEO <strong>Architecture</strong> Implementation Pilot<br />
Licensed under a Creative Commons Attribution 3.0 License
Architectural Implementation Pilot, Phase 3 Version: 2.0<br />
<strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> and European <strong>Drought</strong><br />
Observatory-Water SBA Engineering Report<br />
Date: 11/Feb/2011<br />
Revision History<br />
Version Date Editor and<br />
Content<br />
providers<br />
1.0 17/Dec/2010 W. Pozzi<br />
Comments<br />
1.4 03/Jan/2011 C. Fugazza Revision to semantics-related sections<br />
1.4 05/Jan/2011 M.J. Brewer Revision to <strong>Global</strong> <strong>Drought</strong> Monitor Portal<br />
1.4 07/Jan/2011 M. Santoro, S.<br />
Nativi<br />
1.8 18/Jan/2011 B. Lee<br />
System <strong>Architecture</strong> for <strong>the</strong> Discovery<br />
Augmentation Component<br />
1.9 25/Jan/2011 W. Pozzi Incorporation of GEO Ontology Registry<br />
2.0 4/Feb/2011 M. Enenkel Updating GLOWASIS<br />
2.0 10/Feb/2011 M.J. Brewer Review of NIDIS and GDMP sections<br />
2.0 11/Feb/2011 W.Pozzi Release<br />
Document Contact Information<br />
If you have questions or comments regarding this document, you can contact:<br />
Name Organization Contact Information<br />
W.Pozzi GEO AIP Water and <strong>Drought</strong> Working Group &<br />
IGWCO<br />
Page 3<br />
Will.pozzi@gmail.com<br />
M. Santoro Italy National Research Council santoro@imaa.cnr.it<br />
C. Fugazza Joint Research Center (JRC) cristiano.fugazza@jrc.ec.euro<br />
pa.eu<br />
J.Vogt JRC/European <strong>Drought</strong> Observatory (EDO) jürgen.vogt@jrc.ec.europa.<br />
eu<br />
S. Nativi Italy National Research Council nativi@cnr.it<br />
M. Brewer US National Integrated <strong>Drought</strong> Information<br />
System (NIDIS)/NOAA<br />
R. Heim US National Oceanic and Atmospheric<br />
Administration (NOAA)<br />
J. Sheffield Princeton University
Architectural Implementation Pilot, Phase 3 Version: 2.0<br />
<strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> and European <strong>Drought</strong><br />
Observatory-Water SBA Engineering Report<br />
Date: 11/Feb/2011<br />
S. Niemeyer EDO<br />
D. Cripe GEO Secretariat Scientific Officer for Water dcripe@geosec.org<br />
K. Korporal Environment Canada<br />
A. Howard Agriculture and Agri-Food Canada<br />
B. Lloyd-<br />
Hughes<br />
J. Lieberman<br />
University College London<br />
W. Wagner Technical University Wien<br />
Michael<br />
Piasecki<br />
Consortium of Universities for <strong>the</strong> Advancement<br />
of Hydrologic Science (CUAHSI)/City College of<br />
New York (CCNY)<br />
L. Nunez Republic of Argentina Servicio Meteorologic<br />
Nacional <strong>Drought</strong> Monitor<br />
L. Bettio Australia Bureau of Meteorology<br />
M. Nicholson Australia Bureau of Agricultural and Resource<br />
Economics and Sciences (ABARES)<br />
B. Trewin Australia Bureau of Meteorology<br />
B. Lee CSIRO<br />
W. Sonntag US Environmental Protection Agency<br />
V. Guidetti European Space Agency<br />
R. Lawford IGWCO lawford@umbc.edu<br />
B. Hofer EDO/JRC<br />
D. Magni EDO/JRC<br />
L. Di George Mason University<br />
Eugene Yu George Mason University<br />
C. Yang George Mason University<br />
M. Doubkova Technical University of Vienna<br />
M. Enenkel Technical University of Vienna<br />
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Table of Contents<br />
A. <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong> and <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Community of Practice 8<br />
1.1 Scope of this document 8<br />
1.2 Importance of <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> as a Critical Earth Concern and a<br />
Prime Activity for GEO 9<br />
1.3 Identification of Starting Conditions Fostering <strong>Drought</strong> is not Straightforward 9<br />
1.3.1 Description of <strong>the</strong> Water Cycle 10<br />
1.4 What are <strong>the</strong> User Requirements for an effective <strong>Drought</strong> <strong>Monitoring</strong> and<br />
Forecasting Information System? 11<br />
2. <strong>Drought</strong> <strong>Monitoring</strong> Components and Tools found in Hydrometeorology <strong>Drought</strong><br />
<strong>Monitoring</strong> <strong>Service</strong>s within <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Community of Practice 13<br />
2.1 European <strong>Drought</strong> Observatory 13<br />
2.1.1 European <strong>Drought</strong> Observatory Portal Characteristics: “Drill Down” Capability 13<br />
2.1.2 Importance of Soil Moisture for <strong>Monitoring</strong> Agricultural <strong>Drought</strong> 13<br />
2.1.3 EDO-deployed Meteorological <strong>Drought</strong> Indicator: Standardized Precipitation<br />
Index 15<br />
2.1.4 Hydrologic <strong>Drought</strong> Indicator 15<br />
2.2 USA National Integrated <strong>Drought</strong> Information System 16<br />
2.3 Government of Canada <strong>Drought</strong> Coverage 18<br />
2.4 Commonwealth of Australia <strong>Drought</strong> <strong>Monitoring</strong> 18<br />
2.4.1 Commonwealth of Australia Water Availability Project 18<br />
2.5 Africa Continental <strong>Drought</strong> <strong>Monitoring</strong> 19<br />
2.5.1 Princeton Experimental African <strong>Drought</strong> Monitor 19<br />
2.6 New Projects Permitting Fur<strong>the</strong>r Development of <strong>the</strong> <strong>Global</strong> <strong>Drought</strong><br />
<strong>Monitoring</strong> <strong>Service</strong> 21<br />
2.6.1 European Framework (EF) <strong>Drought</strong> Early Warning System for Africa--<br />
DEWFORA 21<br />
2.6.2 GLOWASIS (<strong>Global</strong> Water Scarcity Information <strong>Service</strong>) 21<br />
2.6.3 Satellite Application Facility on Support to Operational Hydrology and Water<br />
Management (H-SAF) 24<br />
2.7 South American Continent 26<br />
2.7.1 Republic of Argentina Servicio Meteorologic Nacional <strong>Drought</strong> <strong>Monitoring</strong> 26<br />
3. Capturing User Requirements for <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor and its<br />
Interoperability with <strong>the</strong> <strong>Global</strong> Earth Observation System of Systems (<strong>GEOSS</strong>) 30<br />
3.1 Assessment of <strong>Drought</strong> Vulnerability and Susceptibility 30<br />
3.2 Capturing User Requirements and Implementation of <strong>Architecture</strong> to Design of<br />
<strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor 31<br />
3.2.1 Portal Requirements: Drill-down capability 31<br />
3.2.2 Top-down versus bottom-up Design 31<br />
3.2.3 Soil Moisture and Agricultural <strong>Drought</strong> <strong>Monitoring</strong> Requirement 32<br />
3.2.4 Republication of information to help decision makers facilitate drought decision<br />
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making 32<br />
3.2.5 Hydrologic <strong>Drought</strong> <strong>Monitoring</strong> for Semi-Arid Areas and Meeting Hydrologic<br />
<strong>Drought</strong> User Requirement <strong>through</strong> Semantics 32<br />
3.3 Developing an Architectural Diagram for <strong>the</strong> GEO <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong><br />
<strong>Service</strong> 33<br />
3.4 Semantic Development Activities within GEO: <strong>the</strong> Data Integration and<br />
Analysis System (DIAS) Contribution from Japan 36<br />
3.4.1 Adding Advanced Search and Discovery using Semantics 39<br />
4. <strong>Global</strong> Implementation of <strong>the</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong> <strong>through</strong> <strong>GEOSS</strong> 40<br />
4.1 Components of <strong>the</strong> System <strong>Architecture</strong> of <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong><br />
Portal 40<br />
4.2 Actors 41<br />
4.3 Capturing User Requirements for <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor Portal <strong>through</strong><br />
<strong>the</strong> GDMP Scenario 41<br />
4.3.1 Display of Selection Bar for <strong>Drought</strong> Indices, Processing to Derive Dehydration<br />
and <strong>Drought</strong> Severity, and <strong>Drought</strong> Map Republication 42<br />
4.3.2 Layout and Organization of <strong>the</strong> GDMP within <strong>the</strong> NIDIS GIS Server 43<br />
4.3.3 Implementation of Advanced Search and Discovery in <strong>the</strong> GDMP 44<br />
4.4 Support of Increased <strong>Global</strong> Coverage within <strong>the</strong> web-based, real-time GDMP<br />
server 44<br />
4.5 Integration of GDMP with <strong>GEOSS</strong> <strong>Architecture</strong> 44<br />
4.6 Remote Sensing Soil Moisture Integration 45<br />
4.7 Adding Water Usage Information Layers, including Agriculture 45<br />
5. Advanced Search and Discovery Capability within <strong>the</strong> European <strong>Drought</strong><br />
Observatory 49<br />
5.1 Components of <strong>the</strong> European <strong>Drought</strong> Observatory 49<br />
5.1.1 European <strong>Drought</strong> Observatory user access 49<br />
5.1.2 Organization and layout of <strong>the</strong> EDO map server page (scenario step 01—<br />
continued) 50<br />
5.1.3 Selection of <strong>Drought</strong> Indices 50<br />
5.1.4 Processing Step by Running <strong>Drought</strong> Indicators over a Selected Spatial Domain 51<br />
5.1.5 Automated Email Alerts and <strong>Drought</strong> Triggers 51<br />
5.1.6 Context and pre-conditions 52<br />
5.2 Implementation of <strong>the</strong> European Regional <strong>Drought</strong> Semantic-enhanced<br />
<strong>Monitoring</strong> and Information System 52<br />
5.2.1 Advanced Semantic Search 54<br />
5.3 Euro<strong>GEOSS</strong> Deployment of <strong>the</strong> Foundation Vocabularies 55<br />
5.4 Fine Tuning <strong>the</strong> Foundation Vocabularies for SBA Application—Specialized<br />
<strong>Drought</strong> Vocabulary 55<br />
5.4.1 Water Ontology-enablement within <strong>the</strong> DAC Semantics 56<br />
5.5 How <strong>the</strong> Euro<strong>GEOSS</strong> Discover Augmentation Component supports semantic<br />
searches 56<br />
5.6 Operation of <strong>the</strong> Water Ontology within <strong>the</strong> Euro<strong>GEOSS</strong> Discovery<br />
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Augmentation Component 58<br />
5.6.1 Searching for Concepts/Terms 58<br />
5.6.2 Multilingual Concepts/Terms 58<br />
5.6.3 European <strong>Drought</strong> Observatory (Client) Query 59<br />
5.6.4 WPS Request 59<br />
5.7 Use of Euro<strong>GEOSS</strong> Semantic Discovery within <strong>the</strong> European <strong>Drought</strong><br />
Observatory (Returning back to <strong>the</strong> Scenario) 59<br />
5.8 Interoperability Arrangements with <strong>GEOSS</strong> 59<br />
5.9 Post Deployment Activities 60<br />
5.9.1 Ontology Engineering 60<br />
6. Evaluating How <strong>the</strong> Advanced Semantic Euro<strong>GEOSS</strong> Search and Discovery System<br />
Works 61<br />
7. <strong>Drought</strong> Metadata for fostering interoperability between EDO and EU national<br />
drought monitors 62<br />
8. Range of Issues Covered by <strong>the</strong> Water Working Group 64<br />
9. References 65<br />
10. Euro<strong>GEOSS</strong> <strong>Drought</strong> Vocabulary Keywords 70<br />
11. Euro<strong>GEOSS</strong> Water Societal Benefit Area Keywords 72<br />
12. Acknowledgments 72<br />
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<strong>Drought</strong> <strong>Monitoring</strong> and Water Activities within <strong>the</strong><br />
Group on Earth Observations (GEO)<br />
A. <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong> and <strong>the</strong><br />
<strong>Global</strong> <strong>Drought</strong> Community of Practice<br />
1.1 Scope of this document<br />
This is an overview and documentation of <strong>the</strong> drought monitoring service as implemented<br />
<strong>through</strong> <strong>the</strong> Group on Earth Observations System of Systems (<strong>GEOSS</strong>) and <strong>the</strong> European<br />
<strong>Drought</strong> Observatory implementation of advanced semantic search capability <strong>through</strong> <strong>the</strong><br />
Euro<strong>GEOSS</strong> Discovery Broker tools. A key deliverable is <strong>the</strong> specification of a set of tools that<br />
will access information published <strong>through</strong> a distributed water data infrastructure. The<br />
development of <strong>the</strong> specification of <strong>the</strong>se tools includes: 1) capturing user requirements <strong>through</strong><br />
expressing <strong>the</strong> GEO Water Societal Benefit Area users within a “scenario,” that is, who might<br />
use <strong>the</strong> GEO <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong> and <strong>the</strong> types of data and functionality that<br />
<strong>the</strong>se users require or expect; 2)Design of a system architecture and <strong>the</strong> enabling framework for<br />
this at <strong>the</strong> component level; 3) integration of this system architecture within <strong>the</strong> <strong>Global</strong> Earth<br />
Observation System of System (<strong>GEOSS</strong>) architecture and its components; and 4)<br />
implementation. The development efforts of <strong>the</strong> GEO <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> Portal have<br />
involved multiple parties, including <strong>the</strong> Architectural Implementation Pilot (AIP) Water and<br />
<strong>Drought</strong> Working Group, <strong>through</strong> <strong>the</strong> GEO <strong>Architecture</strong> and Data Committee level; <strong>the</strong><br />
Scientific Officer for Water of <strong>the</strong> GEO Secretariat (<strong>through</strong> <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong><br />
Initiative); drought task activities of <strong>the</strong> Integrated <strong>Global</strong> Water Cycle Observations (IGWCO)<br />
Community of Practice; Princeton University Land Surface Hydrology Group, USA National<br />
Integrated <strong>Drought</strong> Information System (NIDIS), <strong>the</strong> European <strong>Drought</strong> Observatory, Italian<br />
National Research Council, <strong>the</strong> Joint Research Centre, <strong>the</strong> University College of London, <strong>the</strong><br />
Technical University of Vienna, Canadian Group on Earth Observations (CGEO), Argentina<br />
Servicio Meteorologico Nacional, Australia Bureau of Agricultural and Resource Economics and<br />
Sciences (ABARES), and <strong>the</strong> Australia Bureau of Meteorology.<br />
This report is divided into two sections to increase its accessibility. The first section<br />
explains why certain portal Information Technology (IT) capabilities (“user requirements”) were<br />
selected for implementation and deployment within <strong>the</strong> global drought monitoring service. The<br />
first section deals with development of a web-based, real-time Geographic Information System<br />
GIS server with a distributed database federation, used for hydrologic alerts in drought<br />
conditions, a prototype global drought early warning system. The second section explains why<br />
certain advanced search capabilities (including “semantic” search and discovery)—again, user<br />
requirements—were developed for implementation within <strong>the</strong> European <strong>Drought</strong> Observatory<br />
and <strong>the</strong> Euro<strong>GEOSS</strong> discovery broker. These technologies can also be eventually migrated for<br />
implementation within <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> Portal (GDMP), combining with<br />
concurrent semantic components being built within <strong>the</strong> <strong>Global</strong> Earth Observation System of<br />
System <strong>through</strong> <strong>the</strong> Data Integration and Analysis System (DIAS), <strong>the</strong> Japanese Aerospace<br />
Exploration Agency (JAXA) contribution to GEO, and <strong>the</strong> Euro<strong>GEOSS</strong> European Union<br />
contribution.<br />
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1.2 Importance of <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> as a Critical Earth Concern and a<br />
Prime Activity for GEO<br />
Given current concerns with <strong>the</strong> increasing frequency and magnitude of droughts in many<br />
regions of <strong>the</strong> world, especially in <strong>the</strong> light of expected climate change, drought monitoring and<br />
dissemination of early warning information in a timely fashion is a critical concern. The<br />
European Union experienced intense drought and heat waves in 2003, Argentina in 2008/2009,<br />
sou<strong>the</strong>ast Australia in 2009, while, at <strong>the</strong> same time, <strong>the</strong> Intergovernmental Panel on Climate<br />
Change (IPCC) climate projections for <strong>the</strong> 21 st century suggests an increased frequency of severe<br />
droughts in continental USA and Mexico, Mediterranean Basin, parts of nor<strong>the</strong>rn China,<br />
Sou<strong>the</strong>rn Africa, Australia, and parts of South America. In addition, current agricultural<br />
production is being maintained by multiple crop cycles over <strong>the</strong> course of a single year in India<br />
and China, for example, and drought is exhausting secondary supplies of groundwater , as <strong>the</strong><br />
drought exhausts surface water supplies, creating a dependency upon <strong>the</strong> groundwater sources<br />
needed to maintain <strong>the</strong>se multiple crop cycles.<br />
<strong>Drought</strong>s and famine are inseparable from one ano<strong>the</strong>r: droughts lower agricultural<br />
production. Current agricultural monitoring efforts, such as <strong>the</strong> European Union (EU)<br />
<strong>Monitoring</strong> of Agricultural Resources with Remote Sensing (MARS Food-Sec), <strong>the</strong> USA<br />
Department of Agriculture (USDA) Foreign Agricultural <strong>Service</strong>, and <strong>the</strong> Famine Early Warning<br />
System (FEWSNET) have developed methodologies for estimating <strong>the</strong> impact of drought upon<br />
agricultural production, such as <strong>the</strong> Food and Agricultural Organization (FAO) Water<br />
Requirements Satisfaction Index (WRSI)(as renamed <strong>Global</strong> Water Satisfaction Index by MARS<br />
and GeoWRSI by FEWSNET). The MARS convention implies that a WRSI or GWSI of 50<br />
represents a famine condition (actual evapotranspiration of half <strong>the</strong> plant water requirement).<br />
Advances in Land Surface Modeling, as in more sophisticated representation of soil<br />
water process, including linkage of groundwater with surface water, is just one way in which<br />
new technologies are available to upgrade <strong>the</strong> more schematic soil water balances incorporated<br />
within WRSI. Additional new technologies are coming online with respect to satellite-based soil<br />
moisture sensors. Standardization of global meteorological datasets has permitted <strong>the</strong> running<br />
Land Surface Models and distributed hydrological models in near-real-time (NRT). IT<br />
infrastructure and informatics methodologies, combined with all <strong>the</strong>se scientific advances, have<br />
now created <strong>the</strong> opportunity to develop a more up-to-date, comprehensive, useful-to-decision<br />
making drought monitoring capability. Additional advances in web-based, real-time (RT)<br />
Geographic Information Systems (GIS) with supporting distributed databases (Wangmutitakul,<br />
et. al., 2003; Wang 2005; Chalainanont, et. al. 2007 or web map services in time-critical<br />
applications (Zhang and Li 2005; Ozdilik and Seker).<br />
The role that GEO plays in this process is to provide a rich collaborative environment,<br />
fostering collaboration among <strong>the</strong> USA, Canada, European Community, Asia, Australia, and<br />
South America.<br />
1.3 Identification of Starting Conditions Fostering <strong>Drought</strong> is not straightforward<br />
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The American Meteorological Society Glossary defines “drought” as “a period of<br />
abnormally dry wea<strong>the</strong>r sufficiently long enough to cause a serious hydrological imbalance.”<br />
Agricultural drought is defined as “conditions that result in adverse crop responses, usually<br />
because plants cannot meet potential transpiration as a result of high atmospheric demand and/or<br />
limited soil moisture.” Hydrologic drought is defined “prolonged period of below-normal<br />
precipitation, causing deficiencies in water supply, as measured by below-normal streamflow,<br />
lake and reservoir levels, groundwater levels, and depleted soil moisture.” The definition of<br />
agricultural drought stipulates that soil moisture monitoring is <strong>the</strong> methodology of choice for<br />
monitoring drought afflicting agriculture. The definition of hydrologic drought stipulates that<br />
monitoring of streamflow (including baseflow), groundwater levels, and soil moisture may be<br />
necessary in order to monitor hydrologic droughts. Indeed, <strong>the</strong> complexities of water cycle<br />
processes found in semiarid terrain, particularly processes in <strong>the</strong> vadose zone, may be critical in<br />
identifying drought’s early stages. <strong>Global</strong> drought monitoring capability includes <strong>the</strong> capability<br />
to monitor drought in many diverse semiarid conditions. The definition of <strong>the</strong> different types of<br />
droughts, particularly hydrological droughts stipulate that monitoring capability of groundwater,<br />
stream flow, soil moisture, snow storage at <strong>the</strong> start of spring meltwater season, and river water<br />
level may be prerequisites or user requirements for an effective global drought monitoring<br />
program. These, in turn, establish user requirements for an information system that support<br />
global and regional drought monitoring.<br />
1.3.1 Description of <strong>the</strong> Water Cycle<br />
The water cycle begins—after evaporation of water over <strong>the</strong> oceans—as rain out over<br />
land <strong>through</strong> which precipitation—if temperatures are low enough—which falls as frozen water<br />
which accumulates on top of <strong>the</strong> surface of land as layers of snow or glacial layers.<br />
Alternatively, precipitation falls—if temperatures are high enough—in its liquid form and<br />
infiltrates into soil (unless <strong>the</strong> soil has a precondition of already being water saturated. This<br />
infiltration and percolation occurs both as flow <strong>through</strong> <strong>the</strong> pores of <strong>the</strong> soil and flow <strong>through</strong><br />
macropores or fractured rock. Drainage may occur from topsoil <strong>through</strong> thick vadose zones in<br />
semi-arid areas, until <strong>the</strong> water reaches layers of saturation of pores with water, called<br />
groundwater. The proximity of groundwater to <strong>the</strong> surface determines whe<strong>the</strong>r water is<br />
exchanged between groundwater, with groundwater discharge occurring into streams or rivers or<br />
groundwater recharge occurring <strong>through</strong> river or streamflow. Fur<strong>the</strong>rmore, semiarid areas may<br />
be characterized by ephemeral flashfloods, making <strong>the</strong> occurrence of such sources of water<br />
difficult to typify statistically. One key difference is that flow of water <strong>through</strong> pores in soil is a<br />
very slow, diffusive process which occurs over much longer time scales—decades or longer—<br />
than <strong>the</strong> more rapid, prompt runoff processes occurring at <strong>the</strong> surface. The point to be made here<br />
is that drought originates as a deficiency of frozen precipitation stored on <strong>the</strong> surface or liquid<br />
precipitation that slowly works its way <strong>through</strong> <strong>the</strong> processes of <strong>the</strong> hydrologic cycle. Some of<br />
<strong>the</strong>se processes and events, such as decline of soil water, occur ra<strong>the</strong>r rapidly and impact <strong>the</strong><br />
growth stage of a crop in agriculture (agricultural drought indicator), while o<strong>the</strong>r processes,<br />
drawdown of groundwater level and lowered discharge of groundwater to river baseflow can<br />
occur over seasonal time scales or longer (hydrologic drought) (Van Lanen et al., 2004).<br />
<strong>Drought</strong> can also exhaust municipal water supplies, both as drops in reservoir levels of<br />
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stored water or declines of water surface elevations within stream and river networks.<br />
Environmental flow requirements are not met, causing environmental impacts as well. Cooling<br />
water for <strong>the</strong>rmal power plants is not available. All of <strong>the</strong>se water cycle processes are often<br />
lumped under <strong>the</strong> generic term hydrologic drought, but <strong>the</strong> actual nature of <strong>the</strong> drought may be<br />
caused by a multiplicity of factors.<br />
Hydrologic droughts can occur <strong>through</strong> groundwater flow or streamflow. Groundwater<br />
droughts can be <strong>the</strong> result of long periods with below average precipitation. Van Lanen &<br />
Tallaksen (2007) have compared different terrains having a slow and a fast responding<br />
groundwater system to conclude <strong>the</strong> effect of <strong>the</strong> groundwater system on <strong>the</strong> frequency and<br />
duration of droughts was larger than <strong>the</strong> effect of different soil types. The groundwater system<br />
has large influence on <strong>the</strong> propagation of droughts <strong>through</strong> <strong>the</strong> hydrological cycle and hence on<br />
drought characterization (Van Lanen & Tallaksen (2008); Wanders, van Lanen, and van Loon<br />
2010). The Total Storage Deficit Index, developed by Yirdaw et al (2008) used NASA Gravity<br />
Recovery and climate Experiment observations to attempt to quantify <strong>the</strong> groundwater role in<br />
hydrologic drought in <strong>the</strong> Canadian prairies. Terrestrial water storage changes can also be<br />
adopted for drought monitoring strategies (Rodell). <strong>Drought</strong> indicators have also been<br />
developed for evapotranspiration (Anderson)<br />
1.3.1.1 Difficulties in Identifying <strong>Drought</strong> Conditions<br />
<strong>Drought</strong> lacks a precise and universally accepted definition. The detection of <strong>the</strong><br />
threshold beyond which a drought episode begins is difficult to determine out of <strong>the</strong> statistical<br />
noise that creates random fluctuations (V. Castillo 2009; Moreira et al 2008). Requirements for<br />
drought detection include methodology that can select drought events from <strong>the</strong> remainder of <strong>the</strong><br />
meteorological or hydrological time series, a truncation level or threshold which divides <strong>the</strong> time<br />
series into “above normal” and “below normal” sections (Dracup et al 1980). The truncation<br />
level can be set to cut <strong>the</strong> series at several places, and “run length” is <strong>the</strong> distance between<br />
successive crossings across <strong>the</strong> threshold; <strong>the</strong> run intensity is <strong>the</strong> average deviation from <strong>the</strong><br />
threshold (van Lanen et al 2008). Probabilistic prediction tools have also been developed.<br />
1.4 What are <strong>the</strong> User Requirements for an effective <strong>Drought</strong> <strong>Monitoring</strong> and<br />
Forecasting Information System?<br />
The integration of drought information (indices and impact indicators) in a<br />
comprehensive framework (composite index and maps) is <strong>the</strong> starting point for developing a<br />
drought monitoring system. Several integrating methodologies have been explored in AIP-3.<br />
<strong>Drought</strong> <strong>Monitoring</strong> may be summarized as a back-end information system, linked to an<br />
application that, in turn, is at <strong>the</strong> back-end of a user accessible portal.<br />
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For example, lack of soil moisture availability is used to define conditions for<br />
agricultural drought, and <strong>the</strong> shortage of ground-based in-situ soil moisture measurement<br />
stations requires estimation of soil moisture over large land tracts using Land Surface Models<br />
(such as <strong>the</strong> NCAR Community Land Model, or <strong>the</strong> ensemble National Land Data Assimilation<br />
System (NLDAS within <strong>the</strong> USA) or distributed hydrological models (such as <strong>the</strong> Variable<br />
Infiltration Capacity VIC model or LISFLOOD). Such models are linked systems of partial<br />
difference equations that ingest multidimensional arrays of near-real-time or real-time<br />
meteorological and precipitation data as functions of time. However, despite <strong>the</strong> fact that such<br />
multi-dimensional data are solved across a lattice of grid cells that emulate spatial locations, <strong>the</strong><br />
output arrays for each respective area have to be geographically registered in order to be<br />
imported into a Geographic Information System (GIS). In short, <strong>the</strong> complex land surface model<br />
and Geographic Information System (GIS) are separate packages (applications). The advantage<br />
of linking toge<strong>the</strong>r <strong>the</strong> Land Surface Models or distributed hydrological models with a GIS is<br />
that <strong>the</strong> soil moisture (as well as o<strong>the</strong>r water budget component and drought indicators) can <strong>the</strong>n<br />
be added toge<strong>the</strong>r or republished as layers within a map, displayed with <strong>the</strong> drought impact<br />
information, such as crops dependent upon green water. The soil moisture may <strong>the</strong>n be<br />
combined with different layers of information within <strong>the</strong> GIS, published as maps, and exchanged<br />
using OGC Web Mapping <strong>Service</strong>s (WMS) among individual national hydrometeorological<br />
service drought monitors and <strong>the</strong> global drought monitor. This is <strong>the</strong> information system behind<br />
<strong>the</strong> application (and <strong>the</strong> front end portal user interface), and this integrates <strong>the</strong> drought<br />
information (indices and impact indicators) with maps of drought severity rankings and<br />
vulnerability or impact factors. The observing system is comprised of <strong>the</strong> ground-based or<br />
satellite-based observations used to derive <strong>the</strong> meteorological and precipitation forcing used in<br />
<strong>the</strong> Land Surface Models or distributed hydrologic models.<br />
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2. <strong>Drought</strong> <strong>Monitoring</strong> Components and Tools found in Hydrometeorology<br />
<strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong>s within <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Community of Practice<br />
This section surveys <strong>the</strong> different types of <strong>Drought</strong> <strong>Monitoring</strong> Systems and why certain<br />
techniques were chosen for a basis of <strong>the</strong> design of <strong>the</strong> global drought monitor portal.<br />
2.1 European <strong>Drought</strong> Observatory<br />
2.1.1 European <strong>Drought</strong> Observatory Portal Characteristics: “Drill Down”<br />
Capability<br />
Within <strong>the</strong> European Community, <strong>the</strong> European <strong>Drought</strong> Observatory (EDO)’s map<br />
server utilizes a common spatial resolution of 20 km, while <strong>the</strong> national EU drought monitor<br />
maps have higher spatial resolution. Common registration of datasets <strong>through</strong> <strong>the</strong> Euro<strong>GEOSS</strong><br />
discovery broker enables <strong>the</strong> highest resolution maps to be exchanged with <strong>the</strong> EDO, since <strong>the</strong><br />
overall system is utilizing a common set of standards. The EDO map server can exchange map<br />
via web services with <strong>the</strong> Ministerio de Medio Ambiente (MARM) in Spain, for example, so that<br />
maps of higher spatial resolution can be republished for <strong>the</strong> benefit of a user query. The design<br />
principles for <strong>the</strong> European <strong>Drought</strong> Implementation (<strong>the</strong> combined Euro<strong>GEOSS</strong> discovery<br />
broker and EDO and national drought monitors within <strong>the</strong> EC) were: 1) decentralized data<br />
holdings but direct linkage and exchange using common format and standards; and 2) a set of<br />
products agreed in common among all partners to be made available and exchanged, such as<br />
Standard Precipitation Index and soil moisture anomaly. Common metadata and registration<br />
<strong>through</strong> <strong>the</strong> Euro<strong>GEOSS</strong> discovery broker make <strong>the</strong> linking of data among river basin, nation,<br />
and regional level possible (as well as interoperable).<br />
2.1.2 Importance of Soil Moisture for <strong>Monitoring</strong> Agricultural <strong>Drought</strong><br />
The EDO currently measures <strong>the</strong> presence of agricultural drought by estimating soil<br />
moisture across <strong>the</strong> European Union, using <strong>the</strong> LISFLOOD model. The LISFLOOD model is<br />
used for forecasting floods, as part of <strong>the</strong> European Flood Alert System (EFAS), and <strong>the</strong> soil<br />
moisture outputs of <strong>the</strong> model are extracted for use in drought monitoring. Continuous<br />
simulations with <strong>the</strong> LISFLOOD model within <strong>the</strong> European Flood Alert System produce daily<br />
soil moisture maps of Europe. Having <strong>the</strong> soil saturated with water is a precondition for flooding,<br />
since any additional liquid precipitation will run off immediately. LISFLOOD is run using<br />
near-‐real-‐time meteorological data, including precipitation, derived from measured and<br />
spatially interpolated meteorological point data provided by <strong>the</strong> MARS-STAT activity of IPSC-<br />
JRC (so called JRC-MARS data). Due to <strong>the</strong> reception via <strong>the</strong> <strong>Global</strong> Telecommunication<br />
System of WMO and fur<strong>the</strong>r processing <strong>the</strong> data are typically one to two days behind <strong>the</strong> current<br />
date. The LISFLOOD model is run twice daily on a Linux cluster. The spatial resolution of<br />
LISFLOOD on <strong>the</strong> pan-European scale is currently at 5 km.<br />
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Daily soil moisture map on is presented in form of soil suction (pF) values of <strong>the</strong> top soil layer<br />
that commonly range between 1.5 for very wet conditions up to 5.0 for very dry soils. 1 The pF<br />
value describes <strong>the</strong> forces necessary for plants to apply in order to extract water from <strong>the</strong> soil for<br />
<strong>the</strong>ir use.<br />
2.1.2.1 Development of <strong>the</strong> Soil Moisture Climatology<br />
The “climatology” for soil moisture has been derived as year-to-year outputs from <strong>the</strong><br />
LISFLOOD model, as having been generated from <strong>the</strong> Re-Analysis data of <strong>the</strong> European Centre<br />
for Medium-Range Wea<strong>the</strong>r Forecasts (ERA-40) that comprise <strong>the</strong> period 1958-2001 (i.e. 44<br />
years), along with updating made available from measured meteorological data from JRC-MARS<br />
from <strong>the</strong> <strong>Global</strong> Telecommunication System of WMO covering 1990 to 2006, i.e. a period of 17<br />
years. (Compare this with <strong>the</strong> Princeton datasets below). Soil moisture anomalies are calculated<br />
from <strong>the</strong> climatology. 2<br />
2.1.2.2 Soil Moisture Anomaly Forecasts prepared from <strong>the</strong> climatology<br />
Soil moisture and soil moisture anomaly forecasts are derived using <strong>the</strong> same modeling<br />
approach but, with <strong>the</strong> exception of using <strong>the</strong> short term meteorological forecasts ra<strong>the</strong>r than<br />
near-real-time meteorology data. In <strong>the</strong> forecasting mode <strong>the</strong> European Flood Alert System<br />
produces information on <strong>the</strong> development of soil moisture in Europe for up to ten days ahead. 3<br />
The anomaly forecast is also made. 4<br />
The trend map of soil moisture describes qualitatively <strong>the</strong> change in soil moisture, currently<br />
between today and <strong>the</strong> seventh day ahead. Orange to red colors indicate drying conditions, while<br />
yellow to green colors predict wetter conditions during <strong>the</strong> next week.<br />
1 http://desert.jrc.ec.europa.eu/action/php/index.php?action=view&id=19<br />
2 http://desert.jrc.ec.europa.eu/action/php/index.php?action=view&id=20<br />
3 http://desert.jrc.ec.europa.eu/action/php/index.php?action=view&id=21<br />
4 http://desert.jrc.ec.europa.eu/action/php/index.php?action=view&id=22<br />
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Figure 1 LISFLOOD forecasted normalized top soil moisture suction (pF) for Europe. The pF<br />
values have been normalized by ECMWF ERA-40 statistics.<br />
2.1.3 EDO-deployed Meteorological <strong>Drought</strong> Indicator: Standardized<br />
Precipitation Index<br />
Precipitation anomalies are expressed <strong>the</strong> monthly Standardized Precipitation Index (SPI)<br />
of <strong>the</strong> last month, a well-known meteorological drought index. Monthly SPI values reflect short<br />
term changes in precipitation as compared to <strong>the</strong> long-term average of <strong>the</strong> respective month.<br />
Positive SPI values indicate greater than median precipitation, and negative values indicate less<br />
than median precipitation (McKee et al. 1993).<br />
2.1.4 Hydrologic <strong>Drought</strong> Indicator<br />
A hydrological drought is described usually by <strong>the</strong> analysis of stream-flow, lake, or<br />
reservoir level data. Opposite to meteorological information, hydrological data are collected<br />
<strong>through</strong>out Europe, but are generally stored locally at <strong>the</strong> national or even regional level, often<br />
with varying formats and qualities less consistent than for meteorological data. Here, after<br />
careful calibration, <strong>the</strong> hydrological model LISFLOOD might contribute to <strong>the</strong> forecasting of<br />
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low flows by predicting discharge as it is already being doing for <strong>the</strong> prediction of flood events<br />
in major pan-European catchment areas.<br />
2.2 USA National Integrated <strong>Drought</strong> Information System 5<br />
The US National Integrated <strong>Drought</strong> Information System (NIDIS) is <strong>the</strong> national drought<br />
early warning system for <strong>the</strong> US. It employs three key tools: 1) <strong>the</strong> US <strong>Drought</strong> Monitor 6 (; 2)<br />
<strong>the</strong> <strong>Drought</strong> Impact Reporter 7 ; and 3) <strong>the</strong> US <strong>Drought</strong> Outlook , and hundreds of supplemental<br />
indicators, services, forecasts, and tools, to provide a snapshot of current drought conditions,<br />
how those conditions are affecting local populations, and whe<strong>the</strong>r <strong>the</strong> drought will continue.<br />
2.2.1.1 USA NIDIS Portal Drill-Down Capability<br />
One interesting feature of <strong>the</strong> NIDIS map server is that one begins with a national map of<br />
drought conditions within <strong>the</strong> USA and <strong>the</strong>n “drills down” to <strong>the</strong> region level and <strong>the</strong>n to <strong>the</strong><br />
basin level.<br />
The first drop down tab is “<strong>Drought</strong> monitor date,” while <strong>the</strong> second is “Zoom to area.” The<br />
third drop down tab is “Zoom to basin,” which currently includes <strong>the</strong> Upper Colorado River<br />
Basin and <strong>the</strong> Lower Colorado River Basin.<br />
Such a “drill down” system—used by both <strong>the</strong> European <strong>Drought</strong> Observatory and <strong>the</strong><br />
USA National Integrated <strong>Drought</strong> Information System portal—can integrate <strong>the</strong> basin scale<br />
drought maps, national scale, continental scale, and global scale and, correspondingly, was<br />
selected for implementation within <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> Portal.<br />
2.2.1.2 Soil Moisture <strong>Monitoring</strong> for Agricultural <strong>Drought</strong><br />
As in <strong>the</strong> case of EDO, <strong>the</strong> USA National Integrated <strong>Drought</strong> Information System<br />
(NIDIS) contains soil moisture and soil moisture anomaly maps. 8<br />
5 http://www.drought.gov/portal/server.pt/community/drought.gov/202<br />
6 http://www.drought.gov/portal/server.pt/community/drought_indicators/us_drought_monitor<br />
7 http://www.drought.gov/portal/server.pt/community/impacts/210<br />
8 http://www.drought.gov/portal/server.pt/community/forecasting/209/soil_moisture/338<br />
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Ensemble soil moisture that is based upon multiple Land Surface Models and distributed<br />
hydrologic models are available from <strong>the</strong> NASA/GSFC National Land Data Assimilation System<br />
(NLDAS) ensemble <strong>Drought</strong> Monitor. 9<br />
The University of Washington experimental US surface water monitor is based on <strong>the</strong><br />
Variable Infiltration Capacity (VIC) distributed hydrologic model. 10<br />
The Center for Climate Prediction (CPC) produces “Leaky Bucket Model” soil moisture. 11<br />
2.2.1.3 Agricultural <strong>Drought</strong> Short Term Forecasting<br />
The US <strong>Drought</strong> Outlook provides an integrated drought forecast, relying heavily on <strong>the</strong><br />
NOAA Climate Forecast System (CFS) and is issued for time-scales out to three months 12 .<br />
The soil moisture anomaly forecasts are based upon <strong>the</strong> NOAA <strong>Global</strong> Forecasting<br />
System (GFS) model; soil moisture anomalies are based upon a 1971-2000 mean climatology. 13<br />
2.2.1.4 Indicators for <strong>Monitoring</strong> Meteorological <strong>Drought</strong><br />
A variety of <strong>Drought</strong> Indicators are made available on <strong>the</strong> NIDIS site. 14 Examples include such<br />
items as Standardized Precipitation Indices and Palmer <strong>Drought</strong> Indices at short time-scales,<br />
2.2.1.5 Agricultural Impacts Estimation<br />
Agricultural impacts are currently tracked by a system utilizing color coding for pasture and<br />
range land in “poor” and “very poor condition” 15<br />
9 http://www.emc.ncep.noaa.gov/mmb/nldas/drought/<br />
10 http://www.hydro.washington.edu/forecast/monitor/<br />
11 http://www.cpc.ncep.noaa.gov/products/Soilmst_<strong>Monitoring</strong>/<br />
12 http://www.drought.gov/portal/server.pt/community/forecasting<br />
13 http://www.cpc.ncep.noaa.gov/soilmst/forecasts.shtml<br />
14 http://www.drought.gov/portal/server.pt/community/drought_indicators/223<br />
15<br />
http://www.drought.gov/portal/server.pt/community/impacts/210/tracking_agricultural_impacts/<br />
307<br />
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2.2.1.6 Hydrologic <strong>Monitoring</strong><br />
Hydrologic drought monitoring measures and forecasts <strong>the</strong> amount of water in lakes, rivers, and<br />
aquifers. 16 <strong>Drought</strong> takes longer to show up in hydrological systems than in agriculture,<br />
especially when reservoirs and rivers are managed to balance <strong>the</strong> extremes of wet and dry years.<br />
Snow is a major component of water supply in <strong>the</strong> western United States.<br />
2.3 Government of Canada <strong>Drought</strong> Coverage<br />
Canada in 2004 extended drought mapping coverage from agricultural areas to remainder<br />
of <strong>the</strong> Canada Provinces. Canada does not carry out drought mapping within <strong>the</strong> territories<br />
(Yukon, Northwest territories, and Nunavut north-of-tree line and permafrost underlain areas).<br />
Near-Real-Time monitoring is carried out for 508 of 761 ground-based stations by Agriculture<br />
and Agri-Food Canada (AAFC)(Hadwen2008) which runs a national drought model, in which<br />
Standard Precipitation Index is calculated, soil moisture (as percent of average and difference<br />
from normal), and Palmer <strong>Drought</strong> Severity Index.<br />
2.4 Commonwealth of Australia <strong>Drought</strong> <strong>Monitoring</strong><br />
Water issues are now considered among <strong>the</strong> most important drivers and constraints on natural<br />
resource management in Australia; from environmental hazards like salinity and drought,<br />
<strong>through</strong> to security of urban and rural water supplies. At present, Australia has no<br />
comprehensive, consistent source of information on <strong>the</strong> water balance of its landscapes; that is,<br />
on <strong>the</strong> relationship between rainfall, evaporation, transpiration, soil moisture, runoff and<br />
drainage to ground and surface water. A better understanding of water availability is needed<br />
across <strong>the</strong> entire country and is relevant to <strong>the</strong> implementation of key Australian Government<br />
policies such as Exceptional Circumstances, <strong>the</strong> National Water Initiative, <strong>the</strong> Prime Minister’s<br />
National Plan for Water Security and policies in support of improved natural resource<br />
management.<br />
2.4.1 Commonwealth of Australia Water Availability Project<br />
The Australian Water Availability Project is a partnership established in 2004, between <strong>the</strong><br />
Bureau of Rural Sciences, CSIRO, <strong>the</strong> Bureau of Meteorology and <strong>the</strong> Australian National<br />
University. The project aim is to develop an operational system for estimating soil moisture and<br />
o<strong>the</strong>r components of <strong>the</strong> water balance, at scales ranging from five kilometers (km) to all<br />
Australia, over time-periods ranging from daily to decades. Data from ground-based climate<br />
measurements, remote sensing and models (water, plant and climate) are being combined to<br />
produce maps of historic and current levels of all <strong>the</strong> main components of <strong>the</strong> landscape water<br />
balance, including rainfall, evaporation, transpiration, available soil moisture, runoff, stream<br />
flow and deep drainage. The future challenge is to deliver a fully web operational system,<br />
including underpinning procedures for robust real-time product delivery, continuous<br />
16 http://www.drought.gov/portal/server.pt/community/hydrological_monitoring/224<br />
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improvement and validation, and links to seasonal forecasting of water balance conditions. The<br />
fundamental data derived from this project will help underpin future planning and decisionmaking<br />
on a range of issues including drought management and policy, securing urban and rural<br />
water supplies, salinity, biodiversity management, ecosystem services and sustainable farming.<br />
The real-time web operational system to be developed will help agricultural industries<br />
maintain farm profitability before, during, and after drought events and help water and catchment<br />
managers quantify <strong>the</strong> impact of climate cycles or climate change on surface and groundwater<br />
recharge, vegetation and biodiversity. Additionally, risks to agricultural production may be<br />
assessed by detailed analysis of moisture availability and moisture utilization trends for all<br />
Australia. The Bureau of Rural Science presents Water Balances for Recent Months, Water<br />
Balance Annual Average, Water Maps, Land Use Maps, and Social Data. 17<br />
2.5 Africa Continental <strong>Drought</strong> <strong>Monitoring</strong><br />
Regional African drought monitoring networks have been started at AGRHYMET in<br />
West Africa, <strong>the</strong> Sou<strong>the</strong>rn Africa Development Center <strong>Drought</strong> <strong>Monitoring</strong> Center. The<br />
Princeton Experimental African <strong>Drought</strong> monitor offers pan-Africa coverage.<br />
2.5.1 Princeton Experimental African <strong>Drought</strong> Monitor 18<br />
The Variable Infiltration Capacity (VIC) Model is used to calculate soil moisture. 19 The<br />
Princeton Land Surface Hydrology Group initially developed a meteorological forcing dataset<br />
for global land areas for 1950-2000 to force <strong>the</strong> Variable Infiltration Capacity (VIC) distributed<br />
hydrologic model. The subsequent task during <strong>the</strong> first interim period involved updating <strong>the</strong><br />
global macro scale modeling to near-real-time over Africa. A particular challenge over <strong>the</strong><br />
African continent has been to update <strong>the</strong> forcing dataset (1950-2000) (and <strong>the</strong>nce <strong>the</strong> VIC<br />
simulation) to near-real-time (NRT) using available data streams.<br />
2.5.1.1 Climatology<br />
The 1950-2000 meteorology—<strong>the</strong> climatology—is derived from a blending of reanalysis<br />
(NCEP/NCAR) and gridded observation-based datasets including <strong>the</strong> Climatic Research Unit's<br />
TS2.0 monthly precipitation and temperature dataset, <strong>the</strong> NASA Tropical Rainfall Measurement<br />
Mission (TRMM) 3-hourly precipitation products and <strong>the</strong> NASA Surface Radiation Balance<br />
(SRB) short- and long-wave datasets. In effect, <strong>the</strong> observation datasets are used to spatially<br />
17 http://adl.brs.gov.au/water2010/water_cycle/index.phtml<br />
18<br />
http://hydrology.princeton.edu/~justin/research/project_global_monitor/index_africa.html<br />
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downscale <strong>the</strong> reanalysis, which is available at high temporal resolution, and at <strong>the</strong> same time<br />
remove biases in <strong>the</strong> reanalysis. This work is described in detail in Sheffield et al. (2006).<br />
2.5.1.2 Bridging <strong>the</strong> gap between reanalysis data and real time observing system<br />
data<br />
To bridge <strong>the</strong> data gap between <strong>the</strong> beginning of 2001 and near-real-time, <strong>the</strong>se methods<br />
were extended to blend reanalysis with available observations. Although reanalysis data are<br />
available up to real-time, most observation-based datasets are generally only available some<br />
months of even years behind real-time. Therefore for 2001-realtime we have used a number of<br />
different datasets depending on <strong>the</strong>ir availability. For 2001-2006, we have used <strong>the</strong> recently<br />
updated (to 2006) monthly gridded precipitation and temperature dataset of Willmott and<br />
Matsura. This matches well <strong>the</strong> CRU dataset (used for 1950-2000) over <strong>the</strong>ir overlap period at<br />
large scales. From <strong>the</strong> beginning of 2007, we have used <strong>the</strong> <strong>Global</strong> Precipitation Climatology<br />
Project (GPCP) monthly dataset which is available a few months off real-time. Ongoing work is<br />
looking at <strong>the</strong> differences between <strong>the</strong>se various datasets during <strong>the</strong>ir overlap periods and<br />
methods to ensure temporal consistency. For <strong>the</strong> last few months up to real-time, we are relying<br />
on real-time precipitation products (PERSIANN 20 data from University California Irvine,<br />
TRMMM data from NASA) and gauge telemetry (<strong>Global</strong> Telecommunication System (GTS)<br />
gauge data from NOAA). These products are being downloaded on a daily basis and are<br />
blended into a forcing dataset for VIC over Africa.<br />
Having set <strong>the</strong> initial meteorological forcing into place, <strong>the</strong> VIC simulations have been<br />
run, up until near-real-time, in order to establish operational running. Our immediate objectives<br />
are to finalize <strong>the</strong> data streams for <strong>the</strong> real-time running of <strong>the</strong> VIC model. The rapid timing of<br />
real-time operational monitoring creates problems, such as <strong>the</strong> need to assess whe<strong>the</strong>r input data<br />
are available, as well as developing fall-back methods for when data are unavailable or fail<br />
quality control checks. Fur<strong>the</strong>rmore, <strong>the</strong> real-time meteorological data are likely biased, creating<br />
<strong>the</strong> need to periodically re-run <strong>the</strong> VIC model up to a few months off real-time when <strong>the</strong> longterm<br />
gridded observation-based products (which are our best estimates of precipitation and<br />
temperature) are updated, to avoid a drift in <strong>the</strong> land surface states.<br />
The probability distributions of total column soil moisture and runoff for each grid cell<br />
and each month constitute <strong>the</strong> climatology, against which current conditions can be compared.<br />
The screening tools account for drought areal extent and duration using concepts adapted from<br />
Andreadis et al (2005), which involve a form of spatial cluster analysis to identify drought<br />
patterns from gridded model output. Based on <strong>the</strong> historic analysis, we will establish a set of<br />
severity-area-duration thresholds that can be used to screen evolving droughts. Within <strong>the</strong> real<br />
time monitoring framework, we will monitor where drought thresholds are crossed for ei<strong>the</strong>r soil<br />
moisture or runoff. Once <strong>the</strong> prescribed drought thresholds have been crossed, we will continue<br />
to track drought evolution in time (i.e., in subsequent forecasts), until <strong>the</strong> nowcasts indicate that<br />
20 http://chrs.web.uci.edu/research/satellite_precipitation/activities00.html<br />
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<strong>the</strong> drought has dissipated. <strong>Drought</strong> dissipation will be evaluated in comparison with severityarea-duration<br />
thresholds estimated using an approach similar to <strong>the</strong> one used to establish drought<br />
screening thresholds.<br />
2.6 New Projects Permitting Fur<strong>the</strong>r Development of <strong>the</strong> <strong>Global</strong> <strong>Drought</strong><br />
<strong>Monitoring</strong> <strong>Service</strong><br />
2.6.1 European Framework (EF) <strong>Drought</strong> Early Warning System for Africa--<br />
DEWFORA<br />
Under <strong>the</strong> European Framework, <strong>the</strong> <strong>Drought</strong> Forecasting and Early Warning System for<br />
Africa (DEWFORA) project has been funded to set up a regional drought monitor for Africa.<br />
DEWFORA also includes local and regional pilot projects. This is <strong>the</strong> reason why DEWFORA<br />
is listed in parallel with <strong>the</strong> Princeton African drought monitor.<br />
Figure 2 DEWFORA study regions (Werner et al 2010)<br />
2.6.2 GLOWASIS (<strong>Global</strong> Water Scarcity Information <strong>Service</strong>)<br />
GLOWASIS will combine in-situ, satellite derived and statistical data on water supply<br />
and demand and make <strong>the</strong>m available <strong>through</strong> a public information portal on water scarcity.<br />
Funded under <strong>the</strong> European FP7 framework, <strong>the</strong> overall objective is to pre-validate a GMES<br />
(<strong>Global</strong> <strong>Monitoring</strong> for Environment and Security) <strong>Service</strong> for Water Scarcity information, based<br />
on pilot studies in Europe, Africa and on global level. The main objectives are:<br />
• Assessment of water demand and supply<br />
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• Near real-time reporting on disasters (droughts, floods)<br />
• Medium and long-term forecasting (also with respect to climate change)<br />
• Promotion of new satellite-capabilities (e.g. Sentinel 1)<br />
• Matching new satellite-capabilities to specific user requirements<br />
GLOWASIS will be made interoperable with <strong>the</strong> Water Information System for Europe<br />
(WISE-RTD), linking water demand and supply with existing tools, such as <strong>the</strong> European<br />
<strong>Drought</strong> Observatory (EDO) and PCR-GLOBWB, a global hydrological model (<strong>the</strong> same model<br />
used in DEWFORA), combining complex water cycle variables in a standardized format with<br />
respect to water scarcity information.<br />
Sources of information and data are:<br />
• Already existing GMES (<strong>Global</strong> <strong>Monitoring</strong> for Environment and Security) data, such as<br />
<strong>the</strong> LMCS (Land <strong>Monitoring</strong> Core <strong>Service</strong>) of GEOLAND2,<br />
• in-situ data from GEWEX (<strong>Global</strong> Energy and Water Cycle Experiment) and <strong>Global</strong><br />
Terrestrial Network on Hydrology (GTN-H) initiatives, such as <strong>the</strong> International Soil<br />
Moisture Network,<br />
• statistical databases (e.g. AQUASTAT and SEEAW)<br />
Results of GLOWASIS can be used in research, for practical implementation and<br />
management purposes. Therefore, end-users encompass river basin management organizations<br />
(Rhine, Danube, Elbe, Oder), <strong>the</strong> European Environment Agency, UN-Water, <strong>the</strong> Australian<br />
Bureau of Meteorology, etc. GLOWASIS is coordinated by DELTARES, <strong>the</strong> Ne<strong>the</strong>rlands. The<br />
Institute of Photogrammetry and remote Sensing (IPF) leads one work package (user<br />
requirements) and is involved in all o<strong>the</strong>rs.<br />
As one of IPF’s most successful projects on soil moisture, SHARE will also contribute to<br />
GLOWASIS. The following sub-chapters give an overview about soil moisture products from<br />
ASAR (advanced syn<strong>the</strong>tic aperture radar) and scatterometer sensors.<br />
SHARE is a DUE Tiger Project of <strong>the</strong> European Space Agency, which offers an<br />
operational soil moisture monitoring service. The synergistic use of ENVISAT's ASAR sensor<br />
and scatterometers (on METOP and ERS) allows for frequent, high resolution monitoring of<br />
regional soil moisture dynamics.<br />
An algorithm was developed at IPF to detect surface soil moisture from active microwave<br />
systems. Active sensors are sensitive to soil moisture mainly due to distinct dielectric properties<br />
of water stored in soil. Microwaves of <strong>the</strong> Advanced Syn<strong>the</strong>tic Aperture Radar (ASAR) and <strong>the</strong><br />
advanced scatterometer (ASCAT) cannot penetrate soil deeper than a few centimetres. In case of<br />
ASCAT an algorithm was developed, which models <strong>the</strong> soil water content in deeper layers (<strong>the</strong><br />
soil water index, SWI). It is obtained by filtering surface moisture time series with an<br />
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exponential function (WAGNER et al., 1999). Being able to model <strong>the</strong> profile soil moisture up to<br />
one metre facilitates estimations of infiltration capacities and plant available water (defined as<br />
<strong>the</strong> difference between field capacity and permanent wilting point). This is <strong>the</strong> approach used in<br />
<strong>the</strong> agricultural monitoring and forecasting models cited in section 1.3 above. Flooded soils are<br />
more prone to cause flooding, as noted in section 2.1.2 above.<br />
The two systems to obtain soil moisture data:<br />
• Medium resolution soil moisture from an imaging Advanced Syn<strong>the</strong>tic Aperture Radar<br />
(ASAR) onboard ENVISAT can be operated in global monitoring or wide swath mode. It<br />
was <strong>the</strong> first system to deliver global backscatter measurements in C-Band (5.3 GHz) at a<br />
spatial resolution of one kilometre. Spatial resolutions of 150 meters can be achieved by<br />
SCAN SAR wide-swath mode. In <strong>the</strong> SHARE project, regions on three continents have<br />
been monitored once or twice a week. Soil roughness and vegetation effects of each pixel<br />
are “corrected” by change detection method – <strong>the</strong> subtraction of a reference image from a<br />
SAR image. This way <strong>the</strong> inhomogeneous distribution of soil water in <strong>the</strong> topmost<br />
centimetres of <strong>the</strong> unsaturated zone, where evapotranspiration takes place, can be<br />
considered. The most recent version of <strong>the</strong> ASAR data viewer is online at:<br />
http://www.ipf.tuwien.ac.at/radar/dv/ipfdv/index.php?dataviewer=asar2<br />
• Scatterometers onboard METOP (ASCAT), ERS-1 and ERS-2 (SCAT) are non-imaging<br />
sensors and characterised by higher temporal (1-2 days), but lower spatial resolution.<br />
Change detection works similar to <strong>the</strong> SAR system. ASCAT is a collaboration of<br />
EUMETSAT and IPF. It was declared operational in December 2008 and is now<br />
produced in near real-time by EUMETSAT, using <strong>the</strong> WARP-NRT software. This<br />
software had been prototyped by EUMETSAT and developed by IPF. ASCAT soil<br />
moisture is a Level 2 product delivered in orbit geometry at two different grid spacings:<br />
25 km and 12.5 km. The two products are derived directly and on <strong>the</strong> same grid as <strong>the</strong><br />
equivalent ASCAT Level 1b products (normalized backscatter).Consequently, <strong>the</strong><br />
resolution of <strong>the</strong> soil moisture values is approximately 50km and 35 km.<br />
Thorough validation of ERS scatterometer and ASAR demonstrated a good<br />
correspondence of satellite and in-situ data (DORIGO, 2010). The correlation of ASAR results to<br />
in-situ measurements is slightly weaker than <strong>the</strong> ones of scatterometers on board ERS, mainly<br />
due to its lower radiometric resolution. However, <strong>the</strong> correlation of ASAR and in-situ data<br />
improves significantly when averaged over larger areas (PATHE et al., 20009, MLADENOVA<br />
et al., 2010). ASCAT products are spatially variable with high quality over grassland and<br />
agricultural areas and lower quality in more densely vegetated areas and deserts. The<br />
investigation of soil moisture at medium scale is a critical assess for IPF’s efforts for<br />
downscaling of active and passive sensors. Field studies showed that, despite high spatiotemporal<br />
variability of soil moisture, its correlation to <strong>the</strong> mean soil moisture over a larger area is<br />
significant in <strong>the</strong> temporal domain.<br />
Recent flood events (January 2011) in Eastern Australia affected more than 200 000<br />
people and an area as big as <strong>the</strong> size of France and Germany combined. ASAR observations can<br />
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now be used to increase <strong>the</strong> reliability of information that is fed into models for monitoring and<br />
forecasting. The Australian Commonwealth Scientific and Research Organization (CSIRO)<br />
currently rely on optical data in combination with passive microwave technologies and digital<br />
elevation models. Incorporating ASAR in <strong>the</strong> system would result in several advantages: on one<br />
hand, reliability and accuracy increases <strong>through</strong> higher resolution, while, on <strong>the</strong> o<strong>the</strong>r, cloudindependent<br />
continuous monitoring is possible. Figure 3 illustrates relative soil moisture<br />
saturation on Australia’s Eastern coast during <strong>the</strong> flood events of December 2010.<br />
Figure 3 Relative soil moisture from ASAR onboard ENVISAT during Floods in Australia (25th<br />
of December). Blue colours represent highly saturated soils, while brown stands for extremely<br />
dry soil conditions (IPF, 2010)<br />
2.6.3 Satellite Application Facility on Support to Operational Hydrology and<br />
Water Management (H-SAF)<br />
H-SAF was established by <strong>the</strong> EUMETSAT Council in July 2005. The Development phase<br />
started in September 2005. Within <strong>the</strong> H-SAF framework <strong>the</strong> focus for new satellite products lies<br />
on:<br />
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• Precipitation rate and cumulate precipitation, including liquid/solid discrimination,<br />
• Soil moisture in <strong>the</strong> surface layer and possibly in <strong>the</strong> roots region and<br />
• Snow parameters such as effective cover, wet/dry discrimination and water equivalent.<br />
H-SAF membership includes 11 EUMETSAT member or cooperating States (Austria,<br />
Belgium, Finland, France, Germany, Hungary, Italy, Poland, Romania, Slovakia and Turkey)<br />
and ECMWF. Host of H-SAF is <strong>the</strong> Italian Met <strong>Service</strong>. The algorithms for satellite rainfall<br />
estimation used in H-SAF will be considered and tested with respect to requirements of<br />
GLOWASIS.<br />
IPF is again contributing to H-SAF with expertise on soil moisture. The basis for all soil<br />
moisture products in H-SAF is <strong>the</strong> radar scatterometer ASCAT on Metop. The three soil<br />
moisture products that emerged from <strong>the</strong> development phase were:<br />
• Large-scale surface soil moisture derived from ASCAT for <strong>the</strong> H-SAF area (SM-OBS- 1),<br />
• Small-scale surface soil moisture resulting from disaggregation of <strong>the</strong> EUMETSAT CAF<br />
global soil moisture from ASCAT (SM-OBS-2);<br />
• Volumetric soil moisture (SM-ASS-1) for <strong>the</strong> H-SAF area (four soil layers up to a depth of<br />
three metres). SM-ASS-1 is now part of ECMWF’s operational service and not<br />
considered an H-SAF product anymore.<br />
The development of two o<strong>the</strong>r products is planned in <strong>the</strong> current phase:<br />
• A Soil Wetness Index in <strong>the</strong> root zone resulting from assimilation of CAF global ASCAT-<br />
Soil Moisture product in a NWP model (SM-ASS-2) and<br />
• <strong>Global</strong> large-scale surface soil moisture derived from ASCAT for <strong>the</strong> H-SAF area (SM-<br />
OBS-3) as <strong>the</strong> successor of <strong>the</strong> EUMETSAT CAF global soil moisture product.<br />
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2.7 South American Continent<br />
2.7.1 Republic of Argentina Servicio Meteorologic Nacional <strong>Drought</strong> <strong>Monitoring</strong><br />
Figure 4 (a) Hydrological Balance and (b) Precipitation is deducted from potential<br />
evapotranspiration (left) to estimate hydrologic balance difference with <strong>the</strong> previous decade<br />
(Nunez 2010).<br />
The Republic of Argentina SMN assembles maps of <strong>the</strong> hydrologic balance, which are<br />
included within daily, monthly, and decadal bulletins which also include maps of number of<br />
consecutive dry days, and NDVI-based vegetation health. Precipitation exhibits a non-normal<br />
statistical distribution. Argentina uses 1960-1990 as its base “climatology” in determining<br />
“average” conditions out of which drought episodes is detected.<br />
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2.7.1.1 Integration of Republic of Argentina SMN <strong>Drought</strong> Coverage into <strong>the</strong><br />
<strong>Global</strong> <strong>Drought</strong> Monitor<br />
Users should be able to access <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor from anywhere on <strong>the</strong> World<br />
Wide Web and see <strong>the</strong> drought coverage for <strong>the</strong>ir respective countries in <strong>the</strong> form that <strong>the</strong>y see it<br />
and utilize it within <strong>the</strong>ir native countries. Yet, at <strong>the</strong> same time, <strong>the</strong> methodology that is<br />
identifying droughts over Brasil or Paraguay should be able to identify droughts, if <strong>the</strong>y are<br />
present, over Argentina, as well. Hence, some standardization of drought indicators is required,<br />
since one of <strong>the</strong> objectives of <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> is to improve <strong>the</strong> accuracy with which<br />
drought is being recorded all over <strong>the</strong> planet.<br />
One approach is to find a proportional relationship between <strong>the</strong> range of <strong>the</strong><br />
drought indicator used in <strong>the</strong> native country and <strong>the</strong> drought severity range, ei<strong>the</strong>r used by <strong>the</strong><br />
US National <strong>Drought</strong> Mitigation Center or by EDO, as illustrated in Figures 5 and 6. The<br />
drought severity ranking system employed by <strong>the</strong> North American <strong>Drought</strong> Monitor was<br />
developed by <strong>the</strong> USA University of Nebraska Lincoln. This system has a colorized code which<br />
is linked to Standardized Precipitation Index (Figure 5). Figure 5 (a) and (b) compare <strong>the</strong><br />
National <strong>Drought</strong> Mitigation Center drought severity ranking system with <strong>the</strong> drought severity<br />
ranking system employed by <strong>the</strong> European <strong>Drought</strong> Observatory. Eventually, <strong>the</strong> two systems<br />
will have to be linked (or made interoperable).<br />
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Figure 5 (a) <strong>Drought</strong> Severity Ranking System of <strong>the</strong> USA National <strong>Drought</strong> Mitigation Center<br />
(UNL) and (b) <strong>Drought</strong> Severity Ranking System of EDO (Iglesias and Schlickenrieder 2010)<br />
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Figure 6 (a) <strong>Drought</strong> Severity Status (Vargus 2008a) and (b) <strong>Drought</strong> Severity Indicator in<br />
practice (Vargus 2008b)<br />
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B Informatics Section<br />
3. Capturing User Requirements for <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor and its<br />
Interoperability with <strong>the</strong> <strong>Global</strong> Earth Observation System of Systems (<strong>GEOSS</strong>)<br />
A key deliverable is <strong>the</strong> specification of a set of tools that will access information<br />
published <strong>through</strong> a distributed water data infrastructure. The tools in this case are represented<br />
by <strong>the</strong> applications which constitute <strong>the</strong> GEO <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong>. The tools are<br />
specified <strong>through</strong> completion of three phases:<br />
1). Capture of User Requirements—who might use <strong>the</strong> GEO <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong><br />
<strong>Service</strong> and <strong>the</strong> types of data and <strong>the</strong> types of functionality <strong>the</strong>se users might require or expect<br />
2) Design of a System <strong>Architecture</strong>—and associated enabling framework at <strong>the</strong><br />
component level<br />
3) Implementation Plan<br />
The <strong>GEOSS</strong> <strong>Architecture</strong> Implementation Pilot (AIP) task develops infrastructure<br />
components for <strong>the</strong> <strong>GEOSS</strong> Common Infrastructure (GCI) and <strong>the</strong> broader <strong>GEOSS</strong> architecture<br />
as a means of coordinating and deploying cross-disciplinary interoperability, such as <strong>the</strong> display<br />
on top of drought map layers, combined with layers of different water usage and agricultural<br />
water needs. The architectural implementation (AIP) task is envisioned as a way of developing<br />
<strong>the</strong> <strong>GEOSS</strong> informatics capability and architecture <strong>through</strong> pilot projects. The process includes<br />
user interactions; component deployment and interoperability testing; and SBA-focused<br />
demonstrations.<br />
3.1 Assessment of <strong>Drought</strong> Vulnerability and Susceptibility<br />
The first section of this report dealt with drought indicators currently utilized by <strong>the</strong><br />
drought community of practice. Indicators do not correlate well with historic drought impacts,<br />
and <strong>the</strong>y need to be correlated with vulnerability. A direct linear proportionality between <strong>the</strong><br />
severity of <strong>the</strong> drought, as expressed by a drought indicator and <strong>the</strong> observed and recorded<br />
impacts of a drought should not be expected. That is <strong>the</strong> role of <strong>the</strong> drought vulnerability factor<br />
(Iglesias and Schlickenrieder 2010). Values of indicators change with <strong>the</strong> region and social<br />
conditions.<br />
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The same level of drought severity can cause a wide variety of drought impacts due to<br />
different underlying vulnerability of different regions. The multiple disciplinary information<br />
sources that assist decision makers in evaluating drought impacts include information on regional<br />
infrastructures, land use, residential water use, etc, which ei<strong>the</strong>r are impacted by drought or may<br />
mitigate drought severity (such as groundwater availability). Land use information (forage for<br />
pasture animals in agricultural lands), crop type information with crop growing seasons, power<br />
plant locations (for identifying cooling water requirements), groundwater springs (to identify<br />
area of groundwater export) are all different types of data that can be combined toge<strong>the</strong>r as<br />
“layers” within a Geographical Information System. The display of layers, one type of<br />
information on top of o<strong>the</strong>r layers, is <strong>the</strong> basis for <strong>the</strong> integration of multi-disciplinary<br />
information. Several types of multi-disciplinary data integration exist, and several tools were<br />
explored <strong>through</strong> testing for deployment for regional and global drought monitoring.<br />
3.2 Capturing User Requirements and Implementation of <strong>Architecture</strong> to Design<br />
of <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor<br />
3.2.1 Portal Requirements: Drill-down capability<br />
Both <strong>the</strong> European <strong>Drought</strong> Observatory and <strong>the</strong> US NIDIS drought monitoring system<br />
portals support “drill down” capability from continental to national scale and from national scale<br />
to river basin scale. The spatial resolution of <strong>the</strong> drought maps are progressively higher, moving<br />
from global scale to continental scale to national scale and finally to river basin scale. This is not<br />
simply a matter of display preference, since a drought early warning system should be developed<br />
for local scales, particularly in <strong>the</strong> case of small-scale agricultural plots. Although existing<br />
national drought monitoring coverage (at its existing resolution) is incorporated into <strong>the</strong> GDMP,<br />
<strong>the</strong> GDMP is not simply <strong>the</strong> assembly of a collection of web page graphics into one location.<br />
3.2.2 Top-down versus bottom-up Design<br />
There are several possible candidates for designing a global drought monitoring service:<br />
1) a single, top-down system at coarse resolution; or 2) a single, top-down system at fine<br />
resolution; 3) a bottom-up system, or 4) a bottom-up system complemented with some top-down<br />
coverage where coverage is lacking.<br />
One example of a top-down global drought monitor is <strong>the</strong> University of College London<br />
<strong>Global</strong> <strong>Drought</strong> Monitor. 21 Ano<strong>the</strong>r is <strong>the</strong> Beijing Climate Center <strong>Drought</strong> Monitor. 22<br />
21<br />
http://drought.mssl.ucl.ac.uk/drought.html?map=%2Fwww%2Fdrought%2Fweb_pag<br />
es%2Fdrought.map&program=%2Fcgibin%2Fmapserv&root=%2Fwww%2Fdrought2%2F&map_web_imagepath=%2Ftmp<br />
%2F&map_web_imageurl=%2Ftmp%2F&map_web_template=%2Fdrought.html<br />
22 http://bcc.cma.gov.cn/Website/index.php?ChannelID=82&show_product=1<br />
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However, <strong>the</strong>re are good reasons for embarking upon a bottom-up system. A global top<br />
down system can imply that drought is present within a local area, although <strong>the</strong> local area might<br />
be drought-free due to availability of secondary sources of water such as groundwater. Having<br />
participation of members who are familiar with local conditions on <strong>the</strong> ground is invaluable in<br />
setting up a global drought monitoring system. A global network of national<br />
hydrometeorological service and ministry-based drought experts can provide <strong>the</strong> expertise to<br />
carry out retrospective validations of drought forecasts, along with fine tuning of <strong>the</strong> drought<br />
forecasting system, part of <strong>the</strong> life cycle by which “experimental” (research stage product)<br />
becomes “operational.”<br />
<strong>Drought</strong> monitoring and forecasting is intended for applications. For example soil<br />
moisture monitoring and forecasting can support farmers’ activities. Since <strong>the</strong> size of farms may<br />
vary, a drought early warning system is best applied at local scales. This means that a coarsescale<br />
system may not be very valuable for providing decision support. A drill down system is<br />
built upon a combined bottom up-top down system, in which <strong>the</strong> highest resolution drought maps<br />
of <strong>the</strong> system, i.e., those at river basin scale or national scale can be used for drought early<br />
warning applications or used for agricultural support.<br />
3.2.3 Soil Moisture and Agricultural <strong>Drought</strong> <strong>Monitoring</strong> Requirement<br />
Given <strong>the</strong> importance of soil moisture in agricultural drought monitoring, and <strong>the</strong><br />
importance of agriculture in <strong>the</strong> world food problem, remote sensing-based and modeled-based<br />
soil moisture should be utilized within <strong>the</strong> system.<br />
3.2.4 Republication of information to help decision makers facilitate drought<br />
decision making<br />
Integrating toge<strong>the</strong>r multiple disciplinary and cross-disciplinary information, such as<br />
drought severity information and agricultural production data, require different informatics<br />
strategies to carry out such integration. While layers can be added toge<strong>the</strong>r and removed within<br />
a Geographic Information System (GIS), more sophisticated tools are required in order to<br />
assemble all of <strong>the</strong> information in a form that can be immediately used for decision making. As<br />
noted by Lemon et. al (2010): “The ‘Discover, Display, and Download’ Use Case has misled us.<br />
No one simply wants to find, look at, and collect data. To <strong>the</strong> contrary, <strong>the</strong>y all want to do<br />
something with <strong>the</strong> data: subject it to some analysis, make a map, or prepare a basis for making<br />
rapid decisions.” Search and discovery alone will not make <strong>GEOSS</strong> a viable system, valuable to<br />
end users: its information has to be repackaged into a user-friendly form that provides<br />
application knowledge and accelerates decision making.<br />
3.2.5 Hydrologic <strong>Drought</strong> <strong>Monitoring</strong> for Semi-Arid Areas and Meeting<br />
Hydrologic <strong>Drought</strong> User Requirement <strong>through</strong> Semantics<br />
The hydrologic drought indicator user requirement creates a need for assembling<br />
information on water budget components, such as groundwater, streamflow, precipitation, soil<br />
water, snow cover, etc. The sheer volume of information, particularly if assembled over large<br />
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segments of <strong>the</strong> globe, will require some integrative technology in order to accommodate <strong>the</strong><br />
utter complexity of multiple languages, multiple scientific terms within different languages,<br />
differences in place names to describe geographic entities, and multiple variable names within<br />
database schema. These are <strong>the</strong> requirements for a semantic-based information system: datasets<br />
and records have to be registered at <strong>the</strong> level of water budget components, i.e., stores of<br />
groundwater, river water elevation, precipitation, etc, to meet <strong>the</strong> requirements for hydrologic<br />
drought monitoring. This also means, conversely, that a semantic ontology has to include <strong>the</strong>se<br />
concepts, as well, within <strong>the</strong> water ontology, for <strong>the</strong> purposes of organizing information. This<br />
level of detail is a critical requirement.<br />
Several possible methodologies for achieving multidisciplinary interoperability take<br />
advantage of <strong>the</strong> possible integrative power of Semantic Web technologies, developed by Tim<br />
Berners-Lee (Berners-Lee, Hendler, Lassila 2001; Yu(2007).<br />
What, simply put, does <strong>the</strong> semantic web do? It tries to lift <strong>the</strong> burden off <strong>the</strong> user of<br />
having to process huge amounts of information by automating (and making machine readable)<br />
<strong>the</strong> collection and processing of information, so that <strong>the</strong> processing burden may be shifted from<br />
<strong>the</strong> user to <strong>the</strong> machine. Semantic web techniques improve irretrievability of <strong>the</strong> correct<br />
document or resource or dataset by providing semantic annotation <strong>through</strong> Resource Description<br />
Framework (RDF) or RDFS, perhaps combined with an ontology which provides <strong>the</strong> structural<br />
arrangement of <strong>the</strong> resources in context with one ano<strong>the</strong>r, along with possibly including some<br />
simplified artificial intelligence application for sorting or selection.<br />
Semantics can be directly employed within <strong>the</strong> decision support services developed by<br />
GEO, i.e., within <strong>the</strong> software applications and processing of data. For example, SEAMLESS<br />
links toge<strong>the</strong>r application modules (such as used in Delft- Flooding Early Warning System or<br />
FEWS) and component-based applications that can be orchestrated into a workflow run over a<br />
framework, in this case, OpenMI (Rizolli, et. al 2007).<br />
Ano<strong>the</strong>r use of semantics is <strong>the</strong> more traditional search and discovery role. This use<br />
case of semantics is what has been explored within this session of AIP-3, as a test case project<br />
within <strong>the</strong> European Union among <strong>the</strong> architects of <strong>the</strong> Euro<strong>GEOSS</strong> discovery broker, <strong>the</strong> AIP-3<br />
Semantics Working Group, <strong>the</strong> European <strong>Drought</strong> Observatory, and <strong>the</strong> AIP-3 Water and<br />
<strong>Drought</strong> Working Group.<br />
3.3 Developing an Architectural Diagram for <strong>the</strong> GEO <strong>Global</strong> <strong>Drought</strong><br />
<strong>Monitoring</strong> <strong>Service</strong><br />
Figure 6, derived from <strong>the</strong> Australia Water Resources Information System, illustrates<br />
some of <strong>the</strong> components that are prerequisites for <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor Portal (GDMP).<br />
The “system architecture” is a diagram of <strong>the</strong> applications and <strong>the</strong> tools, combined with <strong>the</strong><br />
enabling framework at <strong>the</strong> component level. Figure 6 shows <strong>the</strong> bottom rung of data entering<br />
<strong>through</strong> <strong>the</strong> observing system, as, respectively, “Numeric data” (as in soil moisture generated by<br />
<strong>the</strong> VIC and LISFlood models), or satellite source “Sensor output” originating from space-based<br />
scatterometer soil moisture data. The upper tier illustrates in schematic boxes some additional<br />
components, <strong>the</strong> Open Geospatial Consortium (OGC) geospatial Web Mapping <strong>Service</strong>s (WMS)<br />
exchange of drought maps. The exchange of drought maps among <strong>the</strong> European <strong>Drought</strong><br />
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Observatory, <strong>the</strong> Princeton African <strong>Drought</strong> Monitor, <strong>the</strong> NIDIS Server, <strong>the</strong> University College<br />
London drought monitor, and <strong>the</strong> Argentina SMN drought monitor make <strong>the</strong> functionality of <strong>the</strong><br />
GDMP possible.<br />
In between <strong>the</strong> bottom rung (<strong>the</strong> sensor and model data sources of <strong>the</strong> observing system)<br />
and <strong>the</strong> upper tier (and <strong>the</strong> OGC-supported web service data exchange over <strong>the</strong> WWW) are<br />
additional layers which include controlled vocabularies, dictionaries, ontologies, semantic<br />
mappings, and transfer format and protocols, along with common data models, for data<br />
integration and processing this information at multiple levels, republishing <strong>the</strong> information in a<br />
format immediately available for decision making. This functionality is depicted as schematic<br />
boxes in Figure 8(a), but <strong>the</strong> actual operations are set out below.<br />
This overall strategy is a scalable system that permits integration multiple data stores<br />
(information hubs), along with information of multiple disciplines.<br />
Figure 7 Australia Water Resources Information System (Boston 2010)<br />
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Figures 8 (a) and (b) Commonwealth of Australia Water Resources Information System<br />
(Boston 2010)<br />
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Figure 9 Euro<strong>GEOSS</strong> Broker Discovery Augmentation Component Expansion of<br />
<strong>Drought</strong> (diagram kindly provided by Mattia Santoro)<br />
3.4 Semantic Development Activities within GEO: <strong>the</strong> Data Integration and<br />
Analysis System (DIAS) Contribution from Japan<br />
The DIAS approach is illustrated within Figures 10 and 11. Each GEO Societal Benefit<br />
Area, i.e., Disasters, Water, Sustainable Agriculture, Biodiversity, Health, Energy is represented<br />
by a domain within <strong>the</strong> “application layer.” The overall user requirement is to support crossdisciplinary<br />
or multidisciplinary sharing of information and data. The DIAS system supports <strong>the</strong><br />
organization of information within each of <strong>the</strong>se areas.<br />
Figure 9 illustrates a SBA area, in this case drought, using Euro<strong>GEOSS</strong> (see below). At<br />
<strong>the</strong> center of <strong>the</strong> graph is “drought.” “<strong>Drought</strong>” is linked to “Species impoverishment” (within<br />
<strong>the</strong> Biodiversity cluster) in one node and to “famine” (within <strong>the</strong> Sustainable Agriculture cluster)<br />
as ano<strong>the</strong>r node. The arrangement of concepts for each GEO SBA is <strong>the</strong> ontology for each GEO<br />
SBA. DIAS also separates this conceptual scientific terminology from geographic locations and<br />
place names (Figure 12). The drought lexicon, for example, comprises <strong>the</strong> lexicographic<br />
content. Each ontology or collection of ontologies for each of <strong>the</strong>se areas can be loaded into <strong>the</strong><br />
semantic network dictionary. A semantic network illustrates <strong>the</strong> relationship among concepts.<br />
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Figure 11 Integration of DIAS into Web-based Information System (Koike 2010)<br />
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Figures 12 (a) DIAS cross disciplinary areas (Koike 2010) and (b) DIAS Ontology Development<br />
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<strong>Architecture</strong> (Nagai 2010)<br />
Figure 13 (Nagai 2010)<br />
3.4.1 Adding Advanced Search and Discovery using Semantics<br />
The AIP-3 video 23 , “<strong>Drought</strong>—European” includes a walk<strong>through</strong> demonstrations, in<br />
which users select scientific terms (or “concepts”) and, secondly, <strong>the</strong> geographic region or spatial<br />
domain which is defined within a bounding box. This reflects <strong>the</strong> division into lexicographic and<br />
geographic content which has been cited in Section 3.5. The purpose of <strong>the</strong> semantic enrichment<br />
was to supplement keyword searches, such as used on Google, by adding search capability that<br />
could search <strong>through</strong> concepts; this is tantamount to adding “Semantics.” In o<strong>the</strong>r words, one is<br />
not searching for “drought” as a keyword; one is searching for “drought” as a concept, combined<br />
with search functionality that allows <strong>the</strong> user to select broader or narrower searches within <strong>the</strong><br />
drought field or within allied fields. For example, “water” is a concept which can be broken up<br />
into underlying processes of “evapotranspiration,” “streamflow,” “precipitation,” “soil<br />
moisture,” “snow cover,” and “groundwater.” The stores of water are a subset or part of water,<br />
and this class structure is affected in <strong>the</strong> arrangement of <strong>the</strong> terms within <strong>the</strong> semantic network.<br />
Datasets can be registered to each of <strong>the</strong>se terms, so that queries of “hydrologic drought<br />
indicators” reveal “groundwater” data, “streamflow” data, such as baseflow, and o<strong>the</strong>r water<br />
budget information for a selected area. The Euro<strong>GEOSS</strong> discovery broker has <strong>the</strong> capability to<br />
access <strong>the</strong> GI-Cat registered datasets on groundwater, river discharge, water usage, and o<strong>the</strong>r<br />
data. Search-by-concept is intended to not only improve <strong>the</strong> “hit-or-miss” success rate of recall<br />
of datasets <strong>through</strong> keyword searches alone but also reduce <strong>the</strong> high amounts of irrelevant<br />
returned results in keyword searches.<br />
Figure 8 is a screen capture of <strong>the</strong> search interface in <strong>the</strong> AIP-3 “<strong>Drought</strong>—European”<br />
23 http://www.ogcnetwork.net/pub/ogcnetwork/<strong>GEOSS</strong>/AIP3/pages/Demo.html<br />
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video. Note that <strong>the</strong> interface and tool has not only has a list of scientific terms but also has<br />
<strong>the</strong>se terms “arranged,” so that <strong>the</strong> terms are linked to one ano<strong>the</strong>r. This tool enables a user to go<br />
from <strong>the</strong> general term—“drought”—to an associated term “drought indicator” to specific drought<br />
indicators, such as “meteorological drought indicator,” <strong>the</strong>n to “precipitation” and <strong>the</strong>n to<br />
“Standard Precipitation Index.” Alternative branches are “drought” to “drought indicator” to<br />
“agricultural drought indicator” to “soil moisture” or “drought” to “drought indicator” to<br />
“hydrologic drought indicator” to “groundwater” to “terrestrial water storage change.” Datasets<br />
also have tags to <strong>the</strong> appropriate geographic area, such as “England.”<br />
4. <strong>Global</strong> Implementation of <strong>the</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong> <strong>through</strong> <strong>GEOSS</strong><br />
4.1 Components of <strong>the</strong> System <strong>Architecture</strong> of <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong><br />
Portal<br />
The <strong>Global</strong> <strong>Drought</strong> Monitor utilizes and is designed to have a “drill-down” capability.<br />
One begins at <strong>the</strong> global (and coarsest spatial resolution) and <strong>the</strong>n is directed toward higher<br />
spatial resolution regional maps. The user can follow <strong>the</strong> sequence of events by accompanying<br />
<strong>the</strong> steps while watching <strong>the</strong> “<strong>Drought</strong>—<strong>Global</strong>” video. 24<br />
One begins with a <strong>Global</strong> World Map (a <strong>Global</strong> <strong>Drought</strong> Map, as well), accessible on <strong>the</strong><br />
Graphical User Interface (GUI). The <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> Portal is accessible from <strong>the</strong><br />
World Wide Web. 25<br />
The layout of <strong>the</strong> entry web page (index or home page) includes <strong>the</strong> title bar “”Beyond<br />
<strong>Drought</strong>: <strong>Global</strong> Participation for Better Planning and Response,” underneath of which are four<br />
underlying header tabs, arranged from left to right: “Current Conditions,” “Interactive Maps and<br />
Data,” “Regional <strong>Drought</strong> monitoring,” and “About.”<br />
The “Current Conditions” tab displays <strong>the</strong> “<strong>Global</strong> <strong>Drought</strong> Monitor” of <strong>the</strong> University<br />
College London global drought monitor. 26 As noted in <strong>the</strong> Disclaimer to <strong>the</strong> University College<br />
London <strong>Global</strong> <strong>Drought</strong> Monitor, <strong>the</strong> (UCL) <strong>Global</strong> <strong>Drought</strong> Monitor provides <strong>the</strong> 'overall<br />
drought picture' on a ~100km spatial scale. The maps are not designed to depict local conditions.<br />
As a consequence, <strong>the</strong>re could be water shortages or crop failures within an area not designated<br />
as drought, just as <strong>the</strong>re could be locations with adequate water supplies in an area designated as<br />
'extreme' or 'exceptional' drought.”<br />
24 http://www.ogcnetwork.net/pub/ogcnetwork/<strong>GEOSS</strong>/AIP3/pages/Demo.html<br />
25 http://www.drought.gov/portal/server.pt/community/global_drought<br />
26<br />
http://drought.mssl.ucl.ac.uk/drought.html?map=%2Fwww%2Fdrought%2Fweb_pages%2Fdrou<br />
ght.map&program=%2Fcgibin%2Fmapserv&root=%2Fwww%2Fdrought2%2F&map_web_imagepath=%2Ftmp%2F&map<br />
_web_imageurl=%2Ftmp%2F&map_web_template=%2Fdrought.html<br />
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The differences between <strong>the</strong> second “Interactive Maps and Data” tab and <strong>the</strong> third<br />
“Regional <strong>Drought</strong> <strong>Monitoring</strong>” tab are <strong>the</strong> display of <strong>the</strong> drought zones on <strong>the</strong> Interactive Maps<br />
and Data” tab, while <strong>the</strong> Regional <strong>Drought</strong> <strong>Monitoring</strong>” tab displays highlighted continental<br />
areas. The drought zones that are displayed on <strong>the</strong> “Interactive Maps and Data) map viewer are<br />
not necessarily <strong>the</strong> same drought zones that are displayed on <strong>the</strong> “Current Conditions” first tab.<br />
This is because <strong>the</strong> “Current Conditions” <strong>Global</strong> <strong>Drought</strong> map is largely based upon Standard<br />
Precipitation Index (SPI), while <strong>the</strong> “Interactive Maps and Data” second tab displays drought<br />
coverage for members of <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor and <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong><br />
Community of Practice. The “Current Conditions” calculates drought globally, based upon API<br />
and is a top-down system. The “Interactive Maps and Data” drought displays are integrated<br />
toge<strong>the</strong>r from national coverage in North America, derived from <strong>the</strong> regional European<br />
Community LISFLOOD model application with real time data, or derived from continental scale<br />
coverage for <strong>the</strong> African continent.<br />
The third “Regional <strong>Drought</strong> <strong>Monitoring</strong>” tab 27 displays <strong>the</strong> North American,<br />
European and western Asian, and African continents highlighted in different colors with <strong>the</strong><br />
indent being to allow users to access regional drought portals for additional, higher resolution<br />
drought information. The remainder of <strong>the</strong> terrestrial globe is designated a common color. If<br />
one points <strong>the</strong> mouse and clicks anywhere within <strong>the</strong> Canada, USA, or Mexican spatial domain,<br />
i.e., anywhere within North America, one is redirected to <strong>the</strong> North American <strong>Drought</strong> Monitor. 28<br />
If one points <strong>the</strong> mouse and clicks anywhere within <strong>the</strong> European Community, one is redirected<br />
to <strong>the</strong> European <strong>Drought</strong> Observatory home page. 29 If one points <strong>the</strong> mouse and clicks<br />
anywhere within <strong>the</strong> African continent, one is redirected to <strong>the</strong> Princeton University African<br />
<strong>Drought</strong> Monitor. 30 The remainders of <strong>the</strong> terrestrial continental areas share a common color,<br />
because <strong>the</strong>se areas have yet to be integrated and made interoperable within <strong>the</strong> <strong>Global</strong> <strong>Drought</strong><br />
Monitor Portal (GDMP).<br />
4.2 Actors<br />
While <strong>the</strong> administrative user has been identified above, <strong>the</strong> main actors will be officials<br />
working in <strong>the</strong> national hydrometeorology drought monitoring services, as well as officials<br />
working in national and private relief agencies, such as <strong>the</strong> case for famine relief, countrysponsored<br />
agricultural agencies, and agricultural commodities insurers.<br />
4.3 Capturing User Requirements for <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor Portal <strong>through</strong><br />
27<br />
http://www.drought.gov/portal/server.pt/community/global_drought/314/regional_drought_moni<br />
toring/1097 .<br />
28 http://www.drought.gov/portal/server.pt/community/nadm/303<br />
29 http://edo.jrc.ec.europa.eu/php/index.php?action=view&id=2<br />
30 http://hydrology.princeton.edu/~justin/research/project_global_monitor/<br />
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<strong>the</strong> GDMP Scenario<br />
As noted above, a scenario is <strong>the</strong> listing, step-by-step, of <strong>the</strong> user requirements (for<br />
drought monitoring), showing which <strong>GEOSS</strong> resources and components are utilized within <strong>the</strong><br />
retrieval of drought maps and information (such as soil moisture) for users.<br />
Table 4<br />
Objective: Obtain a <strong>Drought</strong> Overview of a Given Area on <strong>the</strong> Terrestrial Earth, along with<br />
detailed information on affected regions<br />
Step 01: Obtain <strong>Drought</strong> Indices from <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> Monitor<br />
Step 01.1: Obtain <strong>Drought</strong> Indices <strong>through</strong> standard services<br />
Step 01.2: A dedicated WPS processes <strong>the</strong> drought index and calculates <strong>the</strong> drought hazard<br />
Step 02: A dedicated WPS processes <strong>the</strong> drought index and calculates <strong>the</strong> drought hazard<br />
Step 02.1: The WPS retrieves <strong>the</strong> <strong>Drought</strong> Index <strong>through</strong> <strong>the</strong> WCS<br />
Step 02.2: The WPS executes <strong>the</strong> hazard detection model and, where detected, sends an alert to<br />
<strong>the</strong> decision support tool<br />
Step 03: <strong>Drought</strong> Hazard Related Information Discovery<br />
Step 03.1: The decision maker uses <strong>the</strong> decision support tool to submit a query to <strong>the</strong> augmented<br />
search component in order to discover drought hazard related information (datasets)<br />
Step 03.2: The Euro<strong>GEOSS</strong> Broker mediates <strong>the</strong> query request, distributing it to its federated<br />
services<br />
Step 03.3: The Decision maker uses <strong>the</strong> Decision Support System to select one or more drought<br />
hazard related information datasets, among <strong>the</strong> ones returned by <strong>the</strong> query<br />
Presentation of Reachable <strong>Service</strong>s and Alerts<br />
Step 03.4: The Decision Support Tool submits an access request to <strong>the</strong> Euro<strong>GEOSS</strong> Broker in<br />
order to retrieve <strong>the</strong> user-selected drought hazard information datasets<br />
Interact with <strong>Service</strong>s<br />
Step 04: Visualization and Assessment of Information<br />
Step 04.1: The Decision Support Tool displays <strong>the</strong> accessed drought hazard information datasets,<br />
combining <strong>the</strong>m with <strong>the</strong> potential hazard layer<br />
Step 04.2: The decision maker assesses <strong>the</strong> drought hazard impact<br />
4.3.1 Display of Selection Bar for <strong>Drought</strong> Indices, Processing to Derive<br />
Dehydration and <strong>Drought</strong> Severity, and <strong>Drought</strong> Map Republication<br />
The <strong>Global</strong> <strong>Drought</strong> Scenario steps, by <strong>the</strong>mselves, are relatively abstract, and are best<br />
understood by following <strong>the</strong> actual presentation given within <strong>the</strong> videos, “<strong>Drought</strong>—<strong>Global</strong>.” 31<br />
31 http://www.ogcnetwork.net/pub/ogcnetwork/<strong>GEOSS</strong>/AIP3/pages/Demo.html<br />
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Step 01 within <strong>the</strong> European <strong>Drought</strong> Observatory is equivalent to providing with users<br />
<strong>the</strong> ability to select one of multiple drought indicators. EDO makes available to users <strong>the</strong> choice<br />
of Standard Precipitation Index (SPI), Soil Moisture, Soil Moisture Anomaly, and several remote<br />
sensing-based measures of vegetation health, such as fraction of Absorbed Photosyn<strong>the</strong>tic Active<br />
Radiation (fAPAR) in <strong>the</strong> case of EDO and VegDRI in <strong>the</strong> case of NIDIS (over <strong>the</strong> USA). The<br />
GDMP does not yet have <strong>the</strong> extensive development to support independent display of multiple<br />
drought indicators and indices. As noted above, SPI is already being displayed on <strong>the</strong> “Current<br />
Conditions” map.<br />
Step 02 is <strong>the</strong> processing loop of taking <strong>the</strong> selected drought indicator, running <strong>the</strong> indicator over<br />
a selected spatial domain or region, and <strong>the</strong>n returning a republished map which displays <strong>the</strong><br />
level of drought intensity or severity within this area (if drought is present at all). The current<br />
GDMP configuration displays <strong>the</strong> integrated drought severity ranking system of Figure 5 for<br />
North America and <strong>the</strong> integrated drought severity ranking system deployed by EDO for <strong>the</strong><br />
European Community. (A drought severity ranking system is being developed for Africa and is<br />
not yet deployed. The Figure 5 system can be adapted to soil moisture percentiles, which is a<br />
drought indicator within <strong>the</strong> Princeton African <strong>Drought</strong> Monitor system). Under <strong>the</strong> current<br />
system, users would have to drill down to <strong>the</strong> North American <strong>Drought</strong> Monitor and from <strong>the</strong>re<br />
to <strong>the</strong> USA, Canada, or Mexico, in order to select individual drought indicators, such as those on<br />
display on <strong>the</strong> NIDIS portal. <strong>Drought</strong> Indicators are made available on <strong>the</strong> NIDIS site. 32<br />
SPI may not be an adequate drought indicator for semiarid areas, such as areas where<br />
sources of water may be water crossing a national boundary from a snowmelt runoff mountain<br />
zone (like Central Asia), or areas where complicated moisture fluxes within <strong>the</strong> vadose zone may<br />
reverse direction and return back to <strong>the</strong> surface. The North American map currently displays<br />
drought zones using <strong>the</strong> National <strong>Drought</strong> Mitigation Center drought severity ranking system<br />
shown in Figure 5(a), while EDO deploys <strong>the</strong> “indicator” alert system shown in Figure 5(b).<br />
4.3.2 Layout and Organization of <strong>the</strong> GDMP within <strong>the</strong> NIDIS GIS Server<br />
The home page (index page) of <strong>the</strong> NIDIS portal is accessible from <strong>the</strong> World Wide<br />
Web. 33 Underneath <strong>the</strong> NIDIS banner, “US <strong>Drought</strong> Portal” is a list of subcategories: “Home,”<br />
“What is NIDIS,” “Current <strong>Drought</strong>,” “Forecasting,” etc. The URL for “current drought,” 34 <strong>the</strong><br />
URL for “forecasting” 35 show <strong>the</strong> navigation within <strong>the</strong> portal: <strong>the</strong> category item is located in <strong>the</strong><br />
32 http://www.drought.gov/portal/server.pt/community/drought_indicators/223<br />
33 http://www.drought.gov/portal/server.pt/community/drought.gov/202<br />
34 http://www.drought.gov/portal/server.pt/community/current_drought/208<br />
35 http://www.drought.gov/portal/server.pt/community/forecasting/209<br />
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URL path after community, so that <strong>the</strong> path to <strong>the</strong> global drought monitor is analogous. 36<br />
4.3.3 Implementation of Advanced Search and Discovery in <strong>the</strong> GDMP<br />
Advanced semantic-enriched search and discovery is discussed below for <strong>the</strong> European<br />
<strong>Drought</strong> Observatory. Eventual semantic deployment within GDMP would likely be limited to<br />
national drought monitors that are part of GDMP. In addition, <strong>the</strong> information resources built<br />
up by DEWFORA can be incorporated into <strong>the</strong> system, including water cycle component<br />
datasets for Africa. The water usage datasets, such as for <strong>the</strong> Water Information System for<br />
Europe (WISE), and o<strong>the</strong>r areas, from GLOWASIS can also be integrated into <strong>the</strong> system over<br />
time, funding permitting. This type of implementation would require registration of <strong>the</strong> datasets<br />
within GI-Cat, tantamount to <strong>the</strong> addition of ano<strong>the</strong>r drought catalogue (Figure 13). The datasets<br />
would also be registered with <strong>the</strong> concepts of <strong>the</strong> water ontology. More information on<br />
establishing interoperability of Euro<strong>GEOSS</strong> with <strong>GEOSS</strong> is contained in Section 5.8.<br />
4.4 Support of Increased <strong>Global</strong> Coverage within <strong>the</strong> web-based, real-time GDMP<br />
server<br />
The GDMP is a web-based, real time (RT) Geographical Information System (GIS) server,<br />
which is built on top of a distributed database federation and ingests meteorological information<br />
and hydrologic information in real-time, in order to provide alerts, a prototype <strong>Drought</strong> Early<br />
Warning System. An overview of <strong>the</strong> alert system is provided for <strong>the</strong> European <strong>Drought</strong><br />
Observatory in Section 5.1.5.<br />
As mentioned in <strong>the</strong> “<strong>Drought</strong>—<strong>Global</strong>” video, <strong>the</strong> global drought server is integrated<br />
and interoperable with continental drought servers, while <strong>the</strong> national hydrometeorology drought<br />
monitors within <strong>the</strong> continental areas are integrated with and made interoperable with <strong>the</strong><br />
continental drought servers. The European Framework project <strong>Drought</strong> Early Warning System<br />
for Africa (DEWFORA) would be expected to possibly serve as an African continental (pan<br />
Africa) continental drought monitor with intercomparisons being prepared between <strong>the</strong><br />
DEWFORA and Princeton African drought monitors. The meteorological forcing data sets are<br />
being assembled for South America to integrate with real time meteorological observing system<br />
data to create a continental scale system <strong>the</strong>re. The GEO Community of Practice partner, <strong>the</strong><br />
Asian Water Cycle Initiative <strong>Drought</strong> Working Group (Ichiro Kaihotsu, Hiroshima University) is<br />
developing a regional drought network (with ground-based stations) that may be made<br />
interoperable with <strong>the</strong> GDMP. An expected, possible configuration for <strong>the</strong> continental servers is<br />
depicted in Figures 14 <strong>through</strong> 16.<br />
4.5 Integration of GDMP with <strong>GEOSS</strong> <strong>Architecture</strong><br />
The GDMP is integrated into <strong>GEOSS</strong> via: 1) metadata creation and addition; 2) catalogue<br />
addition (via Euro<strong>GEOSS</strong> and GI-Cat; and 3) utilization of OGC Web Mapping <strong>Service</strong>, via<br />
36 http://www.drought.gov/portal/server.pt/community/global_drought/<br />
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installed Minnesota MapServer (University College London, Princeton, and EDO) and ESRI GIS<br />
Server (NIDIS). Additional web services are slated for installation. See section for more details<br />
in interoperability of Euro<strong>GEOSS</strong> with <strong>GEOSS</strong>.<br />
4.6 Remote Sensing Soil Moisture Integration<br />
Figure 7’s lowest tier displayed both numeric and sensor sources of data originating from<br />
<strong>the</strong> observing system. The numerical models are forced by real-time meteorological data from<br />
<strong>the</strong> observing system. Sections 2.6.2 and 2.6.3 showed how space-based scatterometers could<br />
provide soil profile and root zone soil moisture. These results can be displayed alongside<br />
modeled soil moisture data; direct data assimilation into a common product is also a possibility<br />
or even <strong>the</strong> latter with <strong>the</strong> display of separate inputs. The US National Aeronautics and Space<br />
Administration (NASA) Soil Moisture Active and Passive (SMAP) results can also be added<br />
when <strong>the</strong>y go live and come on line.<br />
4.7 Adding Water Usage Information Layers, including Agriculture<br />
GLOWASIS may provide a basis for incorporating water usage information and data into<br />
<strong>the</strong> GDMP. This would also be a prerequisite for assessing drought vulnerability.<br />
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Figures 14 (a) and (b)<br />
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Figures 15 (a) and (b)<br />
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Figures 16 (a) and (b)<br />
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5. Advanced Search and Discovery Capability within <strong>the</strong> European <strong>Drought</strong><br />
Observatory<br />
A set of tools have been developed for deployment within <strong>the</strong> European <strong>Drought</strong><br />
Observatory, also serving as a contribution to GEO. These technologies provide capability to<br />
integrate water information for <strong>the</strong> Water (and drought) Societal Benefit Area, including possible<br />
deployment within <strong>the</strong> <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> <strong>Service</strong>. This report captures <strong>the</strong> user<br />
requirements for who would be using this system (EDO), what data types would be required, and<br />
<strong>the</strong> type of functionality users would expect. These user requirements are embodied within a<br />
“scenario,” with <strong>the</strong> development of a system architecture providing <strong>the</strong> associated enabling<br />
framework. The GEO Architectural Implementation Pilot (AIP) develops components for <strong>the</strong><br />
<strong>GEOSS</strong> <strong>Architecture</strong> <strong>through</strong> component deployment and subsequent testing, interoperability<br />
testing, followed by Societal Benefit Area (SBA) demonstrations, i.e., demonstrations of a<br />
decision support service, such as <strong>the</strong> global drought monitoring service for <strong>the</strong> Water SBA. GEO<br />
AIP projects are run by framing a “scenario” which expresses and embodies <strong>the</strong> user<br />
requirements, such as GEO tasks.<br />
5.1 Components of <strong>the</strong> European <strong>Drought</strong> Observatory<br />
The European <strong>Drought</strong> Observatory is based upon a loosely-coupled system having as<br />
components: 1) drought indicators; 2) drought climatologies; 3) drought observing systems; 4)<br />
water usage observing system; 5) internet-based and web-based services which make<br />
interoperability and exchange of data and maps possible; 6) common formats among <strong>the</strong> system;<br />
7) user network to verify nowcasts and forecasts; and 8) hardware infrastructure and technical<br />
support staff.<br />
The European Community has identified drought, biodiversity, and forestry as targets for<br />
<strong>GEOSS</strong> activity. This AIP effort has included development of <strong>the</strong> Euro<strong>GEOSS</strong> search<br />
capability. As has been mentioned above (Section 2.1.1), common registration of datasets permit<br />
maps and data to be shared and exchanged among <strong>the</strong> EDO, <strong>the</strong> national drought monitors, such<br />
as MARM and SIA, and <strong>the</strong> river basin authorities, such as Confidercion Hidrografica del Ebro.<br />
In short, joint registration supports interoperability. At <strong>the</strong> same time, some of <strong>the</strong> data retrieval<br />
capabilities of EDO were time series of soil moisture, soil moisture anomalies, and Standardized<br />
Precipitation Index over different time periods. The longer <strong>the</strong> period of observation for<br />
precipitation falling upon a landscape, <strong>the</strong> longer <strong>the</strong> period of time over which water works its<br />
way <strong>through</strong> <strong>the</strong> soil and drains down into groundwater.<br />
5.1.1 European <strong>Drought</strong> Observatory user access 37<br />
The EDO map server is separated from <strong>the</strong> index page. 38<br />
37 http://edo.jrc.ec.europa.eu/php/index.php?action=view&id=36<br />
38 http://edo.jrc.ec.europa.eu/php/index.php?action=view&id=201<br />
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5.1.2 Organization and layout of <strong>the</strong> EDO map server page (scenario step 01—<br />
continued)<br />
The upper left hand column has “European <strong>Drought</strong> Products,” underneath of which are<br />
listed:<br />
1. Soil Moisture;<br />
2. Precipitation;<br />
3. Precipitation from Archive;<br />
4. Remote Sensing Indicators;<br />
5. <strong>Drought</strong>-related products; and<br />
6. Generate Graphs and Time Series<br />
Underneath this list are three tabs:<br />
1. Information from Euro<strong>GEOSS</strong> <strong>Drought</strong> Catalogue;<br />
2. National/International <strong>Drought</strong> Information; and<br />
3. Regional/Local <strong>Drought</strong> Information<br />
Selecting Soil Moisture, number 1 from <strong>the</strong> top panel (button), causes a list to fall down, having<br />
<strong>the</strong> selection:<br />
1. Daily Soil Moisture;<br />
2. Daily Soil Moisture Anomaly;<br />
3. Forecasted Soil Moisture Anomaly;<br />
4. Forecasted Soil Moisture Trend. Etc.<br />
The Euro<strong>GEOSS</strong> drought catalogue box is accessible. 39<br />
5.1.3 Selection of <strong>Drought</strong> Indices<br />
The <strong>Drought</strong> Indices of Step 01 are Standardized Precipitation Index and Soil Moisture<br />
Anomaly (and Soil Moisture). No hydrologic drought indicator is included, although some<br />
remote sensing drought indicators are given. We have not included remote sensing drought<br />
indicators here, in order to reduce <strong>the</strong> length of this report.<br />
Step 01.1 entails “obtaining drought indices <strong>through</strong> standard services”: this step is tantamount to<br />
<strong>the</strong> process of selecting one of <strong>the</strong> drought indicators above, such as daily soil moisture anomaly,<br />
and sending a query to <strong>the</strong> EDO server from a local machine browser window, in order to request<br />
a returned map showing daily conditions calculated for western Euro Asia for that day.<br />
Returning to <strong>the</strong> Euro<strong>GEOSS</strong> drought catalog box above, <strong>the</strong> returned web page contains a given<br />
drought vocabulary (Section 9), along with a <strong>the</strong>saurus button underneath. Pressing <strong>the</strong><br />
<strong>the</strong>saurus button prompts a new button to appear “Add term” with a dialog box popping up<br />
“Select <strong>the</strong>saurus from list ‘SBA_Euro<strong>GEOSS</strong>.” The GEO Societal Benefit Area groupings are<br />
listed, including water.<br />
NOTE: This is an important step which is not included within <strong>the</strong> original scenario. The<br />
implications of this Euro<strong>GEOSS</strong> interface—with respect to semantics—are outlined below in<br />
Section 6.4.<br />
39 http://eurogeoss.unizar.es/Search/Search.html?opener=EDOMapServer<br />
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A returned map is loaded and returned.<br />
5.1.4 Processing Step by Running <strong>Drought</strong> Indicators over a Selected Spatial<br />
Domain<br />
Step 02 is <strong>the</strong> process of processing current daily conditions using <strong>the</strong> drought indicator (“daily<br />
soil moisture anomaly” and <strong>the</strong> display of <strong>the</strong> map within <strong>the</strong> browser on <strong>the</strong> local machine.<br />
Step 02 determines whe<strong>the</strong>r <strong>the</strong>re is a drought over a given spatial domain, as well as <strong>the</strong><br />
severity (ranking) of <strong>the</strong> drought. EDO utilizes a drought severity ranking system,<br />
corresponding to drought of increasing severity: 1) 0-green; 2) 1-yellow; 3) 2-orange; 4) 3-red;<br />
5) 4-brown. This is <strong>the</strong> drought severity ranking system that differs from <strong>the</strong> North American<br />
<strong>Drought</strong> Monitor ranking system, as presented within Figure 5.<br />
The currently displayed drought severity color coding system on <strong>the</strong> EDO map server<br />
system does not yet implement this drought severity ranking system. It current system is<br />
simpler, exhibiting wetter or drier conditions (than average) only: green (indicating wetter<br />
conditions), yellow (indicating normal or 0), and orange for progressively drier, until red. 40<br />
5.1.5 Automated Email Alerts and <strong>Drought</strong> Triggers<br />
Scenario step 02.2<br />
If any area within <strong>the</strong> European Union (including adjacent areas, such as Turkey) is<br />
designated as having drought of a particular severity, an automated email alert can be sent to<br />
decision makers, if <strong>the</strong>y have already signed up to be a recipient for such an alert service. This is<br />
<strong>the</strong> type of automated email alert system used by <strong>the</strong> USA National Oceanic and Atmospheric<br />
Administration (NOAA) Integrated Coral reef Observing Network (ICON), which dispatches<br />
automated emails to alert <strong>the</strong> oceanographic community of possible coral reef bleaching, when<br />
pre-assigned bleaching thresholds are passed. The Euro<strong>GEOSS</strong> broker offers support for <strong>the</strong><br />
GeoRSS alert mechanism.<br />
If, after being notified by email alert of a designated drought ranking, a decision maker<br />
wants to retrieve more information about drought conditions, <strong>the</strong> semantics-supported advanced<br />
search and discovery is set up to make it easier to retrieve <strong>the</strong> information. This is in keeping<br />
with <strong>the</strong> philosophy of tailoring a decision support system to make it easier to utilize<br />
information.<br />
40 http://edo.jrc.ec.europa.eu/php/index.php?action=view&id=201<br />
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5.1.6 Context and pre-conditions<br />
Some of <strong>the</strong> existing <strong>Global</strong> Earth Observation System of System functionality has been<br />
described above. This section will provide fur<strong>the</strong>r documentation of Euro<strong>GEOSS</strong> in providing<br />
components supporting advanced search and discovery. The following datasets and services are<br />
assumed to be available before <strong>the</strong> scenario begins:<br />
• GEO Portal, <strong>through</strong> this portal <strong>the</strong> end user will be able to search, find and access<br />
<strong>the</strong> services which are needed for <strong>the</strong> Scenario execution;<br />
• Euro<strong>GEOSS</strong>/GENESIS Client Application is registered on <strong>the</strong> Components and<br />
<strong>Service</strong>s Registry (CSR) and accessible <strong>through</strong> <strong>the</strong> GEO Portal;<br />
• Euro<strong>GEOSS</strong> Discovery Augmentation Component (DAC) <strong>Service</strong>. This service<br />
federates both semantics (e.g. SKOS repositories) and ISO-compliant geospatial<br />
catalog services. The DAC can be queried using common geospatial constraints (i.e.<br />
what, where, when, etc.). The service exposes a semantics-extended OpenSearch<br />
interface.<br />
• Euro<strong>GEOSS</strong> Discovery Broker <strong>Service</strong>. This is a distributed catalogue which<br />
federates several services (exposing <strong>the</strong>m <strong>through</strong> <strong>the</strong> CSW-ISO interface). Federated<br />
services publish <strong>the</strong> following datasets:<br />
o Environmental datasets (WCS);<br />
o Climate Change datasets (WCS);<br />
• GENESIS Vocabulary <strong>Service</strong>. This repository publishes a SPARQL interface for<br />
navigating <strong>the</strong> aforementioned SKOS-based <strong>the</strong>sauri.<br />
• WPS Client. This is web client for configuring and running data retrieval for graph<br />
construction <strong>through</strong> <strong>the</strong> European <strong>Drought</strong> Observatory<br />
• <strong>GEOSS</strong> Ontology Registry<br />
• <strong>GEOSS</strong> Geographic Gazetteer<br />
• Application (WPS): <strong>the</strong> search interface is designed to be accessible <strong>through</strong> <strong>the</strong><br />
European <strong>Drought</strong> Observatory (EDO) portal interface<br />
• A workflow engine. This component manages all phases of <strong>the</strong> scenario (browse<br />
semantic repository, retrieve concepts of interest, search for resources related to such<br />
concepts, execute WPS)<br />
5.2 Implementation of <strong>the</strong> European Regional <strong>Drought</strong> Semantic-enhanced <strong>Monitoring</strong> and<br />
Information System<br />
The <strong>Drought</strong> Scenario that has been used for AIP-3 was originally introduced within<br />
presentations of Barbara Hofer and Stefan Niemeyer (European <strong>Drought</strong> Observatory),<br />
“Euro<strong>GEOSS</strong> for <strong>Drought</strong>--Linking <strong>the</strong> EDO to Local and <strong>Global</strong> Scales,” at <strong>the</strong> INSPIRE<br />
conference in June 2010 and “<strong>Drought</strong> Data, Metadata, and Interoperability,” at <strong>the</strong> Training<br />
Workshop on <strong>Drought</strong> Risk Assessment for <strong>the</strong> Agricultural Sector in September 2010. These<br />
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identical drought scenarios are also given within Report D.2.1.1 Report on Requirements for<br />
Interdisciplinary Interoperability (L. Vacarri, S. Nativi, and M. Santoro), 2 Nov 2010.<br />
The actual scenario which was used is presented in Table 1 below. This scenario is pretty<br />
abstract, and <strong>the</strong> reader may find viewing this scenario more useful by accompanying <strong>the</strong> reading<br />
with a viewing of <strong>the</strong> video “<strong>Drought</strong>—European.” 41 along with reading this scenario.<br />
The video is actually a “walk<strong>through</strong>,” showing step-by-step how a user interested in<br />
drought will use <strong>the</strong> drought information system, showing <strong>the</strong> implementation of <strong>the</strong> scenario.<br />
The scenario itself in Table 1 is actually <strong>the</strong> user requirements before construction of <strong>the</strong> system,<br />
while <strong>the</strong> video displays <strong>the</strong> components that have been assembled and implemented to meet<br />
<strong>the</strong>se requirements.<br />
The use cases Semantics Enabled Search and Ontology Engine Search have been<br />
developed in conjunction with <strong>the</strong> Semantics WG; fur<strong>the</strong>r details are contained in <strong>the</strong><br />
Euro<strong>GEOSS</strong> Broker documentation and <strong>the</strong> Semantics Working Group Report.<br />
Table 3 European <strong>Drought</strong> Observatory Scenario<br />
European <strong>Drought</strong> Observatory Scenario<br />
Step 01: Obtain <strong>Drought</strong> Indices from European <strong>Drought</strong> Observatory<br />
Step 01.1: Obtain <strong>Drought</strong> Indices <strong>through</strong> Standard <strong>Service</strong>s<br />
Step 02: A dedicated WPS processes <strong>the</strong> drought index and calculates <strong>the</strong> drought hazard<br />
Step 02.1: The WPS retrieves <strong>the</strong> <strong>Drought</strong> Index <strong>through</strong> <strong>the</strong> WCS<br />
Step 02.2: The WPS executes <strong>the</strong> hazard detection model and, where detected, sends an alert to<br />
<strong>the</strong> decision support tool<br />
Step 03: <strong>Drought</strong> Hazard Related Information Discovery<br />
Step 03.1: The decision maker uses <strong>the</strong> decision support tool to submit a query to <strong>the</strong> augmented<br />
search component in order to discover drought hazard related information (datasets)<br />
Use Case: Semantics Enabled Search<br />
Step 03.1.1: The augmented search component submits a query to <strong>the</strong> ontology query engine and<br />
extracts 0,…N terms to be inserted into <strong>the</strong> geospatial query<br />
Specialized Use Case: Ontology Enabled Search<br />
Step 03.1.2: The augmented search component generates one or more geospatial queries based<br />
on <strong>the</strong> user selection as geospatial constraints and/or as keywords from <strong>the</strong> previous step and<br />
41 http://www.ogcnetwork.net/pub/ogcnetwork/<strong>GEOSS</strong>/AIP3/pages/Demo.html<br />
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submits <strong>the</strong> queries to <strong>the</strong> Euro<strong>GEOSS</strong> Broker<br />
Use Case: Discovery: Client Search of Metadata<br />
Step 03.2: The Euro<strong>GEOSS</strong> Broker mediates <strong>the</strong> query request, distributing it to its federated<br />
services<br />
Step 03.3: The Decision maker uses <strong>the</strong> Decision Support System to select one or more drought<br />
hazard related information datasets, among <strong>the</strong> ones returned by <strong>the</strong> query<br />
Presentation of Reachable <strong>Service</strong>s and Alerts<br />
Step 03.4: The Decision Support Tool submits an access request to <strong>the</strong> Euro<strong>GEOSS</strong> Broker in<br />
order to retrieve <strong>the</strong> user-selected drought hazard information datasets<br />
Interact with <strong>Service</strong>s<br />
Step 04: Visualization and Assessment of Information<br />
Step 04.1: The Decision Support Tool displays <strong>the</strong> accessed drought hazard information datasets,<br />
combining <strong>the</strong>m with <strong>the</strong> potential hazard layer<br />
Step 04.2: The decision maker assesses <strong>the</strong> drought hazard impact<br />
5.2.1 Advanced Semantic Search<br />
Scenario Step 03 embodies <strong>the</strong> advanced semantics incorporated into <strong>the</strong> European<br />
<strong>Drought</strong> Implementation.<br />
Upon being notified of a drought alert in an area of interest, <strong>the</strong> decision maker (drought<br />
expert) can go online to consult <strong>the</strong> common Euro<strong>GEOSS</strong> broker-EDO interface. For example,<br />
<strong>the</strong> Euro<strong>GEOSS</strong> broker incorporates both: 1) Discovery Augmentation Component (DAC) and<br />
2) <strong>the</strong> workflow engine, which increases <strong>the</strong> power of search by integrating toge<strong>the</strong>r catalogue<br />
and semantic components. In o<strong>the</strong>r words, <strong>the</strong> workflow engine browses <strong>the</strong> semantic<br />
repositories to retrieve concepts. Once <strong>the</strong> expert drought user has identified a concept of<br />
interest, <strong>the</strong> resources (datasets and services) linked to each of <strong>the</strong>se concepts can be retrieved.<br />
5.2.1.1 Ontology Registration<br />
An ontology is a technology for organizing information which includes <strong>the</strong> organization<br />
of <strong>the</strong> information toge<strong>the</strong>r into relationships that are reminiscent of <strong>the</strong> class structure found in<br />
programming languages. The ontologies are stored within <strong>the</strong> Semantic Network within DIAS,<br />
which preserves this class structure.<br />
5.2.1.2 Geographic Registration<br />
As can be seen in Figure 11, two types of ontological information are developed and<br />
expanded: 1) lexicographic ontologies, i.e., ontologies of scientific disciplines and remote<br />
sensing; and 2) geographic ontologies, as represented by gazetteers. A gazetteer is defined as a<br />
reference for information about places and place names used in conjunction with an atlas (hill et<br />
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al 1999). The gazetteer assembles a correspondence between place names and spatial<br />
information. Each concept (i.e., place) can be uniquely identified by Resource Description<br />
framework via a Universal Resource Identifier (URI). Gazetteers can record a triple (place<br />
names; geographic footprints (locations); and class of described feature or representation of <strong>the</strong><br />
real world geographic entity. The place name is a “handle” to support communication.<br />
5.3 Euro<strong>GEOSS</strong> Deployment of <strong>the</strong> Foundation Vocabularies<br />
Ontologies are created out of scientific vocabularies, controlled vocabularies, where<br />
terminology has accepted meaning. So <strong>the</strong> starting point for <strong>the</strong> vocabularies in Figure 10 would<br />
be general vocabularies, such as:<br />
The GEO SBA ontologies were constructed out of:<br />
• The General Multilingual Environmental Thesaurus (GEMET): 28 of <strong>the</strong> 29 languages<br />
currently provided by <strong>the</strong> EIONET portal.<br />
• The INSPIRE Feature Concept Dictionary and Glossary: 21 of <strong>the</strong> 23 EU official<br />
languages for INSPIRE Themes, monolingual <strong>the</strong> o<strong>the</strong>r terms.<br />
• The ISO 19119 categorisation of spatial data services: 21 of <strong>the</strong> 23 EU official languages.<br />
• The <strong>GEOSS</strong> Societal Benefit Areas: 5 languages.<br />
5.4 Fine Tuning <strong>the</strong> Foundation Vocabularies for SBA Application—Specialized<br />
<strong>Drought</strong> Vocabulary<br />
At <strong>the</strong> start of AIP-3, Pozzi parsed <strong>the</strong> GEMET water <strong>the</strong>saurus, in order to identify <strong>the</strong><br />
extent of drought terminology and concepts contained within it. An extensive, developed<br />
network of drought concepts would be necessary to support <strong>the</strong> presentation graphs in <strong>the</strong> user<br />
interface on <strong>the</strong> EDO portal (Figure 9) and also provide concepts linked to <strong>the</strong> drought data and<br />
information. However, parsing and browsing <strong>the</strong> GEMET <strong>the</strong>saurus for water shows it lacks any<br />
specialized drought vocabulary. 42 Even <strong>the</strong> precipitation it lists only includes chemical<br />
precipitation. 43 Hence, GEMET, by itself, is not adequate to express meteorological drought,<br />
agricultural drought, and hydrologic drought indicators or <strong>the</strong>ir associated water budget<br />
components (groundwater, streamflow, baseflow, snow cover); <strong>the</strong> base <strong>the</strong>saurus must be<br />
supplemented by a water ontology. Pozzi (of <strong>the</strong> Water Working Group), C. Fugazza of <strong>the</strong><br />
AIP-3 Semantics Working Group, and M. Santoro and S. Nativi, <strong>the</strong> Euro<strong>GEOSS</strong> architects,<br />
concurred in developing a water ontology that would include a drought specialization that could<br />
be used for both Euro<strong>GEOSS</strong> (and EDO) and <strong>the</strong> DIAS ontology registration within <strong>the</strong> semantic<br />
42<br />
http://www.eionet.europa.eu/gemet/<strong>the</strong>me_concepts?letter=0&start=390&th=40&langcode=en&<br />
ns=4<br />
43<br />
http://www.eionet.europa.eu/gemet/<strong>the</strong>me_concepts?letter=0&start=270&th=40&langcode=en&<br />
ns=4<br />
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network registry. Such a specialized drought vocabulary or a water ontology would link to<br />
drought indicators and drought and water datasets used in common with <strong>the</strong> European <strong>Drought</strong><br />
Observatory. The Simple Knowledge Organizing System (SKOS) had been used to express this<br />
GEMET data structure, so <strong>the</strong> water ontology, developed in AIP-3, would also be translated into<br />
SKOS data structures and linked to relevant terms in <strong>the</strong> reference <strong>the</strong>sauri as an AIP-4 activity.<br />
5.4.1 Water Ontology-enablement within <strong>the</strong> DAC Semantics<br />
One possible candidate as a foundation water ontology was <strong>the</strong> USA Consortium of<br />
Universities for <strong>the</strong> Advancement of Hydrologic Sciences (CUAHSI) water ontology, version 1.<br />
The CUAHSI water ontology does list water stores of surface and subsurface (soil) water,<br />
<strong>the</strong>reby meeting some of <strong>the</strong> requirements needed in a hydrologic drought indicator. Fugazza<br />
has converted <strong>the</strong> CUAHSI Ontology Web Language (OWL) into SKOS, as an AIP-3<br />
contribution (See AIP-3 Semantics Engineering Report).<br />
5.5 How <strong>the</strong> Euro<strong>GEOSS</strong> Discover Augmentation Component supports semantic<br />
searches<br />
To conclude, <strong>the</strong> Discovery Augmentation Component enables semantics-aware<br />
discovery by matching <strong>the</strong> search patterns entered by <strong>the</strong> end user against a collection of<br />
multilingual, SDI-related <strong>the</strong>sauri: <strong>the</strong>se are controlled vocabularies providing multiple textual<br />
representations for terms and organizing <strong>the</strong>m according to specificity and relatedness. As a<br />
consequence <strong>the</strong> user’s query is first related to a set of language-neutral identifiers (URIs) (like<br />
<strong>the</strong> URIs used for geographic spatial entities, noted above in section 5.2.1.2). These URIs<br />
represent entities in a concept graph that <strong>the</strong> user may navigate for identifying related terms that<br />
are relevant to her search. These data structures are hosted by <strong>the</strong> GENESIS Vocabulary <strong>Service</strong>.<br />
These <strong>the</strong>sauri are provided in <strong>the</strong> Simple Knowledge Organizing System (SKOS)<br />
format, a lightweight ontology for expressing knowledge organization systems (such as<br />
taxonomies, classification schemes etc.), and have been harmonized in <strong>the</strong> context of <strong>the</strong><br />
Euro<strong>GEOSS</strong> project by relating terms from distinct <strong>the</strong>sauri, thus allowing <strong>the</strong> user to move from<br />
one categorization to <strong>the</strong> o<strong>the</strong>r, i.e., one scientific discipline to ano<strong>the</strong>r within a GEO SBA or<br />
from one SBA (water) to ano<strong>the</strong>r SBA (agriculture). Once <strong>the</strong> user has identified an exhaustive<br />
set of terms that are relevant to her query, <strong>the</strong> broker translates <strong>the</strong> corresponding URIs back to a<br />
customizable set of languages and executes multiple queries against <strong>the</strong> catalogs it is federating<br />
(recalling <strong>the</strong> desired datasets).<br />
The Euro<strong>GEOSS</strong> Discovery Augmentation Component (DAC) implements a query<br />
expansion strategy deriving multiple traditional geospatial queries from a single semantic query.<br />
The DAC is able to accept a semantic query and, accessing a configurable set of external<br />
semantic services (e.g. controlled vocabularies, gazetteers, etc.), split it into several geospatial<br />
queries directed to a set of federated traditional/standard services for geospatial resources<br />
discovery. Results are finally combined in a meaningful way and sent back to <strong>the</strong> client.<br />
This framework realizes <strong>the</strong> Separation-of-Concerns pattern assigning specific tasks to<br />
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different components, making <strong>the</strong> architecture flexible and scalable. Moreover, it does not affect<br />
existing geospatial service interfaces implementing a loosely-coupled solution in compliance<br />
with <strong>the</strong> <strong>GEOSS</strong> architectural principles.<br />
The system design for <strong>the</strong> DAC applies <strong>the</strong> well-known principle of Layered <strong>Architecture</strong><br />
(ISO, 1994), as depicted in Figure 11. Functionalities are grouped and layered according to <strong>the</strong>ir<br />
abstraction level. Figure 11 shows <strong>the</strong> three layers of <strong>the</strong> proposed architecture, implementing<br />
each layer on a different distribution tier:<br />
• in <strong>the</strong> Presentation Layer we find components implementing graphic user interfaces<br />
(GUIs);<br />
• <strong>the</strong> Integrated Semantic Layer is composed of components which implement <strong>the</strong> business<br />
logic necessary to integrate semantic and geospatial services;<br />
• The Single Semantic and Geospatial Query Layer provides query functionalities towards<br />
a set of different services (geospatial, semantic, etc.).<br />
Figure 17 – System <strong>Architecture</strong> for <strong>the</strong> DAC System<br />
The DAC clearly falls into <strong>the</strong> integrated semantic layer and makes use of <strong>the</strong> services in<br />
<strong>the</strong> single semantic and query layer in order to implement <strong>the</strong> query expansion strategy.<br />
The choice of service interfaces was mainly driven by <strong>the</strong> need of being as compliant as<br />
possible with widely adopted catalog service specifications to be interoperable with existing<br />
systems. Thus, for <strong>the</strong> interaction between <strong>the</strong> DAC and <strong>the</strong> catalog service, <strong>the</strong> OGC CSW/ISO<br />
AP (Application Profile) interface is used. Among <strong>the</strong> present application profiles of <strong>the</strong> OGC<br />
CSW core specification; this is presently one of <strong>the</strong> most widely implemented. Moreover, this is<br />
<strong>the</strong> INSPIRE compliant catalog service interface. The access to <strong>the</strong> semantic service takes place<br />
<strong>through</strong> SPARQL (<strong>the</strong> Query Language for Resource Description Format (RDF) semantic<br />
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documents, a W3C standard) syntax for queries. However, <strong>the</strong> DAC was conceived to be flexible<br />
and federate also semantic services that use different interfaces.<br />
The DAC shall also provide an interface (towards <strong>the</strong> presentation layer) for being<br />
queried with any combination of semantic, geospatial and free text constraints. At <strong>the</strong> time being<br />
<strong>the</strong>re is no well-recognized standard interface or syntax allowing such combined queries. Hence,<br />
<strong>the</strong> choice was to use <strong>the</strong> lightweight OpenSearch 44 interface. The OpenSearch is a basic<br />
interface, allowing querying a catalogue with a simple free text search. There exist several<br />
extensions of <strong>the</strong> basic OpenSearch syntax; two widely used extensions to submit geospatial<br />
queries are:<br />
• Geo extension: allows to specify a spatial extent/location as constraint in a query;<br />
• Time extension: allows building queries based on time and time spans constraints.<br />
In addition to <strong>the</strong> above extensions, we defined a “Concept-driven” extension to allow <strong>the</strong><br />
discovery of well-defined concepts and relations between concepts form semantic services.<br />
These three extensions form <strong>the</strong> DAC query interface.<br />
A detailed documentation describing <strong>the</strong> “Concept-driven” extension will soon be<br />
published on <strong>the</strong> OpenSearch Web Site. The AIP-3 Engineering Report Best Practices Wiki 45<br />
will be updated as soon as <strong>the</strong> detailed documentation will be available.<br />
5.6 Operation of <strong>the</strong> Water Ontology within <strong>the</strong> Euro<strong>GEOSS</strong> Discovery<br />
Augmentation Component<br />
5.6.1 Searching for Concepts/Terms<br />
Euro<strong>GEOSS</strong> DAC communicates with <strong>the</strong> GENESIS Vocabulary <strong>Service</strong> using SPARQL<br />
interface. According to user’s request <strong>the</strong> Euro<strong>GEOSS</strong> DAC performs different actions:<br />
1. When <strong>the</strong> user has searched for concepts/terms related to a keyword of interest (e.g.<br />
“drought”), <strong>the</strong> Euro<strong>GEOSS</strong> DAC performs a “GetConcepts” request; that is,<br />
Euro<strong>GEOSS</strong> DAC builds a SPARQL query to retrieve from <strong>the</strong> GENESIS<br />
Vocabulary <strong>Service</strong> all concepts/terms containing <strong>the</strong> searched keyword in <strong>the</strong> label<br />
and/or in <strong>the</strong> description. The matching concepts/terms are returned to <strong>the</strong><br />
Euro<strong>GEOSS</strong>/GENESIS Client Application.<br />
2. When <strong>the</strong> user is extending a set of concepts/terms, <strong>the</strong> Euro<strong>GEOSS</strong> DAC<br />
transforms <strong>the</strong> selected relation type (e.g. “more specific concepts”) into formal<br />
SKOS relations (e.g. skos: narrower and skos: narrowMatch). Using <strong>the</strong>se relations<br />
a set of SPARQL queries is executed, and matching concepts/terms are returned to<br />
<strong>the</strong> Euro<strong>GEOSS</strong>/GENESIS Client Application.<br />
5.6.2 Multilingual Concepts/Terms<br />
Each of <strong>the</strong> selected concepts/terms is identified by a URI. The Euro<strong>GEOSS</strong> DAC submits<br />
a SPARQL query to <strong>the</strong> GENESIS Vocabulary <strong>Service</strong> in order to retrieve all available<br />
44 http://www.opensearch.org/Home<br />
45 http://wiki.ieee-earth.org/Best_Practices/<strong>GEOSS</strong>_Transverse_Areas/Data_and_<strong>Architecture</strong><br />
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translations for each of <strong>the</strong> selected concepts/terms.<br />
5.6.3 European <strong>Drought</strong> Observatory (Client) Query<br />
Euro<strong>GEOSS</strong> DAC communicates with <strong>the</strong> Euro<strong>GEOSS</strong> Discovery Broker <strong>through</strong> <strong>the</strong><br />
OGC CSW ISO AP 2.0.2 interface. For each of <strong>the</strong> selected concepts/terms, Euro<strong>GEOSS</strong><br />
DAC creates a query that contains geographic (i.e. <strong>the</strong> envelope characterizing <strong>the</strong> specific<br />
AOI), and multilingual Keywords constraints (i.e. <strong>the</strong> concepts/terms selected <strong>through</strong> <strong>the</strong><br />
Euro<strong>GEOSS</strong>/GENESIS Client Application). This set of queries is submitted to <strong>the</strong><br />
Euro<strong>GEOSS</strong> Discovery Broker. As shown in <strong>the</strong> “<strong>Drought</strong>—Europe” video, <strong>the</strong> user has<br />
identified a geographic area on <strong>the</strong> map interface, while at <strong>the</strong> same time, highlighted and<br />
clicked on a concept. Before sending back <strong>the</strong> results to <strong>the</strong> client, <strong>the</strong> Euro<strong>GEOSS</strong> DAC<br />
groups <strong>the</strong>m according to <strong>the</strong> matched concept/term.<br />
5.6.4 WPS Request<br />
The European <strong>Drought</strong> Observatory (EDO) WPS Client sends an Execute request to <strong>the</strong><br />
WPS Server, including references to <strong>the</strong> input <strong>the</strong>matic layers selected by <strong>the</strong> user (WCS<br />
endpoint and coverage name).<br />
5.7 Use of Euro<strong>GEOSS</strong> Semantic Discovery within <strong>the</strong> European <strong>Drought</strong><br />
Observatory (Returning back to <strong>the</strong> Scenario)<br />
The User Interface to DAC includes two tabs: 1) “Search” and 2) “configuration.” The<br />
process begins with a “Simple Search” text box, in which a user types in <strong>the</strong> overall query item<br />
of interest “drought.” The “Advanced Search” panel becomes active, containing a text string box<br />
in which <strong>the</strong> user types <strong>the</strong> keyword, underneath of which are buttons “Get concepts,” “relation,”<br />
“extend node,” “clean selection,” and “search.” The “Get concepts” button obviously retrieves<br />
<strong>the</strong> concepts, which are <strong>the</strong>n displayed in graph form as nodes on a tree or graph.<br />
The “relation” button, when pressed, offers <strong>the</strong> selection of “more general terms,” “more<br />
specific terms,” “corresponding terms,” and “related terms.” The color coding used in <strong>the</strong> graphs<br />
are: 1) “orange” for more specific, 2) “yellow” for more general, and 3) “green” for<br />
corresponding. For example, “drought indicator” is a “more specific” example of “drought.”<br />
As shown in <strong>the</strong> demonstration video, a user can draw a box around an area of interest on<br />
a map, while simultaneously having entered <strong>the</strong> concept of interest to <strong>the</strong> user. Then <strong>the</strong> search<br />
results will be retrieved. The returning data matches <strong>the</strong> requested concepts. Then <strong>the</strong> selected<br />
datasets can be displayed upon a map server (Scenario Step 04) (see section 6.4)<br />
5.8 Interoperability Arrangements with <strong>GEOSS</strong><br />
We use <strong>the</strong> following service interface:<br />
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OGC CSW ISO AP, published by <strong>the</strong> Euro<strong>GEOSS</strong> Discovery Broker<br />
W3C SPARQL, published by <strong>the</strong> GENESIS SKOS repository<br />
OpenSearch interface (with geo, temporal and semantic extensions), published by<br />
<strong>the</strong> Euro<strong>GEOSS</strong> DAC<br />
Use of <strong>the</strong> <strong>GEOSS</strong> Common Infrastructure (GCI):<br />
The Euro<strong>GEOSS</strong> discovery broker is registered in <strong>the</strong> GCI. It is accessible <strong>through</strong> <strong>the</strong> GEO<br />
Portal using <strong>the</strong> following standard interfaces:<br />
CSW/ISO 2.0.2<br />
CSW/ebRIM-EO 2.0.2<br />
OpenSearch with Geo and Time extensions<br />
5.9 Post Deployment Activities<br />
5.9.1 Ontology Engineering<br />
As noted in Section 5.4.1, <strong>the</strong> CUAHSI version 1 46 water ontology contains <strong>the</strong><br />
subclasses of surface hydrology, subsurface hydrology, atmospheric hydrology, land, water<br />
quality, aquatic biology, and infrastructure subclasses, but it lacks an extensively developed<br />
subsurface water subclass and surface subclassification. CUAHSI is preparing to revise and<br />
update a version 2 release of <strong>the</strong> water ontology, but not in time for AIP-3. Correspondingly,<br />
some development work was undertaken, along with more expected for AIP-4, in preparing a<br />
specialized drought module for <strong>the</strong> CUAHSI water ontology.<br />
A concise overview of <strong>the</strong> documentation for <strong>the</strong>se modules follows. However, a standalone<br />
drought vocabulary was prepared to use within <strong>the</strong> Euro<strong>GEOSS</strong> search tools built into <strong>the</strong><br />
European <strong>Drought</strong> Observatory. This stand-alone drought vocabulary is already operational and<br />
provides <strong>the</strong> tool to test whe<strong>the</strong>r concept-oriented drought searches improve retrieval of drought<br />
information for users—structuring a tool to facilitate <strong>the</strong> user, as in section 3.2.4. The<br />
operational tool and its search results are reviewed in section 6.<br />
The ontology documentation is provided here. Every water domain specialist, drought<br />
specialist, hydraulic engineer, land surface modeler, hydrologist, and ecologist will recognize<br />
two basic equations: <strong>the</strong> surface water equation and <strong>the</strong> surface energy equation. The<br />
“atmospheric hydrology” concept contains subclasses “precipitation” and “radiation” and “wind”<br />
(which creates mechanical turbulence and affects turbulent transfer of water vapor fluxes of<br />
evaporated water back to <strong>the</strong> atmosphere.<br />
A starting point for more comprehensive water ontology is to build upon <strong>the</strong> ALMA<br />
convention. 47 The ALMA convention has also been used in <strong>the</strong> distributed hydrologic model<br />
intercomparison experiments undertaken by <strong>the</strong> EU Water and Climate Change (EU-WATCH). 48<br />
46 http://water.sdsc.edu/hiscentral/startree.html<br />
47 http://web.lmd.jussieu.fr/~polcher/ALMA/<br />
48 http://www.eu-watch.org/templates/dispatcher.asp?page_id=25222765<br />
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FLUXNet controlled vocabulary, <strong>the</strong> surface water budget equation, <strong>the</strong> surface energy budget<br />
equation, and <strong>the</strong> land use classification system of Boston University and <strong>the</strong> University of<br />
Maryland (as modified by GlobeCover Product Specification of MERIS. These provide a<br />
framework in which <strong>the</strong> drought vocabulary module can be included and expanded.<br />
An example of <strong>the</strong> expansion of <strong>the</strong> land module of <strong>the</strong> water ontology is presented in<br />
Figure 18.<br />
Figure 18 Land Surface Module of <strong>the</strong> Water Ontology<br />
6. Evaluating How <strong>the</strong> Advanced Semantic Euro<strong>GEOSS</strong> Search and Discovery<br />
System Works<br />
By <strong>the</strong> end of AIP-3, <strong>the</strong> Euro<strong>GEOSS</strong> search interface had been incorporated into <strong>the</strong><br />
operational European <strong>Drought</strong> Observatory web site, even though <strong>the</strong> water ontology was not<br />
fully functional within <strong>the</strong> Euro<strong>GEOSS</strong> Discovery Augmentation Component. Be that as it may,<br />
a specialized drought vocabulary (section 10) was available and linked to <strong>the</strong> Euro<strong>GEOSS</strong><br />
broker. How effectively does this system retrieve specialized drought datasets, its stated user<br />
objective?<br />
The Euro<strong>GEOSS</strong> <strong>Drought</strong> Catalog page pops up, containing a list of drought terms<br />
(Section 10), followed by a list of terms representing <strong>the</strong> GEO Societal Benefit Areas (Section<br />
11). As has been noted, <strong>the</strong> list of drought terms contains <strong>the</strong> water budget components, i.e.,<br />
groundwater, discharge, evapotranspiration, low flow, piezometric level, precipitation, snow, soil<br />
moisture, soil moisture deficit, and snow pack.<br />
Clicking <strong>the</strong> groundwater term and hitting <strong>the</strong> search button brings up two pages of<br />
references.<br />
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Highlighting <strong>the</strong> soil moisture term and clicking on <strong>the</strong> search button retrieves: daily soil<br />
moisture per region; daily soil moisture anomaly per region (EDO): humedad del suelo en<br />
Espana, composite drought indicator, forecasted soil moisture trend (EDO); forecasted soil<br />
moisture anomaly (EDO); daily soil moisture anomaly EDO; and daily soil moisture.<br />
Although this is not a direct test utilizing <strong>the</strong> full ontology, <strong>the</strong> results are encouraging in<br />
supporting <strong>the</strong> use of a specialized concept-oriented vocabulary, such as that of drought, in<br />
supporting more effective searches.<br />
7. <strong>Drought</strong> Metadata for fostering interoperability between EDO and EU national<br />
drought monitors<br />
European efforts, independent of AIP, have constructed drought metadata and <strong>the</strong><br />
registration of drought datasets (for Spain),part of <strong>the</strong> metadata creation and registration upper<br />
tier “Catalog” box of <strong>the</strong> Australia Water Resources Information System diagram (Figure 6).<br />
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Figure 19<br />
<strong>Drought</strong> metadata were defined, as documented in D.5.2, Metadata Catalogue for<br />
<strong>Drought</strong> Information (J Nogueras, et. Al. 49<br />
At <strong>the</strong> start of <strong>the</strong> project only two WP5 partners (CNIG and CHE) had metadata<br />
catalogues describing drought related resources toge<strong>the</strong>r with o<strong>the</strong>r types of resources, while<br />
some of <strong>the</strong> o<strong>the</strong>r partners had no metadata available for <strong>the</strong>ir drought related resources <strong>the</strong>y use.<br />
In addition to this, CNIG and CHE catalogues have been included in <strong>the</strong> WP2 broker (GI-Cat),<br />
toge<strong>the</strong>r with this WP5 drought catalogue, so all metadata resources available from WP5 partners<br />
are accessible in a distributed way.<br />
The technology of this catalogue has been developed by <strong>the</strong> Universidad de Zaragoza.<br />
The Euro<strong>GEOSS</strong> drought catalogue has been registered as a service accessible <strong>through</strong> <strong>the</strong><br />
Euro<strong>GEOSS</strong> discovery broker component. 50 Thanks to <strong>the</strong> connection to <strong>the</strong> IOC brokering<br />
framework, Euro<strong>GEOSS</strong> users can discover drought related resources in a distributed way.<br />
49 www.eurogeoss.eu<br />
50 http://217.108.210.73/broker/<br />
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The Euro<strong>GEOSS</strong> discovery broker component is based on GI-Cat software 51 .<br />
8. Range of Issues Covered by <strong>the</strong> Water Working Group<br />
The AIP-3 Call for Participation originally included Water Quality and <strong>Drought</strong><br />
(including Agricultural <strong>Drought</strong>). W. Sonntag and C. Spooner (USA Environmental Protection<br />
Agency), V. Guidetti of <strong>the</strong> European Space Agency (ESA), and J. Lieberman joined to raise<br />
water quality issues with regards to an EO2Heaven project to be based in Africa and beach<br />
closures in <strong>the</strong> Gulf of Maine.<br />
The CSIRO Tasmanian ICT Centre has developed <strong>the</strong> Hydrological Sensor Web (HSW)<br />
based on OGC-SWE standards. Near real-time hydrologic observations and flow forecasting are<br />
published and accessed <strong>through</strong> <strong>the</strong> OGC Sensor Observation <strong>Service</strong> (SOS).<br />
Fig. 18(a) shows <strong>the</strong> generation process of flow forecasting. Firstly, rainfall observations<br />
are collected from different sensor sites, owned by different agencies, and stored in databases.<br />
The observations are published on <strong>the</strong> HWS via SOS. A Kepler workflow obtains rainfall<br />
observations from SOS and generates <strong>the</strong> gridded rainfall surface. A forecast model <strong>the</strong>n<br />
consumes <strong>the</strong> gridded rainfall data and produces flow forecasts. Finally, <strong>the</strong> forecasting results<br />
are published onto <strong>the</strong> HSW <strong>through</strong> SOS. It can be seen that different agencies are involved in<br />
producing flow forecasting results.<br />
For this use case, a provenance information model has been developed which is demonstrated in<br />
Fig. 18(b). Three sets of ontologies have been adopted, which are <strong>the</strong> Sensor Ontology, <strong>the</strong><br />
WaterML2 Ontology and <strong>the</strong> Process Ontology to describe information/ knowledge in <strong>the</strong> sensor<br />
domain, <strong>the</strong> water domain and <strong>the</strong> data processing domain, respectively. Then, <strong>the</strong> Proof Markup<br />
Language (PML) is used to describe <strong>the</strong> generation processes of information products and link<br />
multi-domain ontologies toge<strong>the</strong>r. This allows tracking <strong>the</strong> lifecycle of hydrologic data products,<br />
as well as record-related factors that may impact on data qualities, e.g., sensor setting, model<br />
calibration.<br />
51 http://zeus.pin.uinfi.it/cgi-bin/twiki/view/GIcat<br />
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Figure 10 (a) and (b)<br />
9. References<br />
Agboma, C.O., S. Z. Yirdaw, & K. R. Snelgrove 2009. Intercomparison of <strong>the</strong> Total Storage<br />
Deficit Index (TSDI) over two Canadian Prairie catchments. Journal of Hydrology, 374,<br />
351 – 359<br />
American Meteorological Society Glossary of Meteorology<br />
Anderson, M.C., W. P. Kustas, J.R. Mecikalski, and C. R. Hain, 2009 “A GOES-based drought<br />
product using <strong>the</strong>rmal remote sensing of evapotranspiration, 23 rd Conference on Hydrology,<br />
Session 2, <strong>Drought</strong> Prediction, <strong>Monitoring</strong>, and Mitigation, 17 Jan 2009, American<br />
Meteorological Society<br />
Anderson, M.C., and W. P. Kustas, “Mapping Evapotranspiration and <strong>Drought</strong> at Continental<br />
and Local Scales with a Thermal-based Surface Energy Balance Model”<br />
Page 65
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Date: 11/Feb/2011<br />
Andreadis, K.M., E.A. Clark, A.W. Wood, A.F. Hamlet, and D.P. Lettenmaier, 2005. 20th<br />
Century drought in <strong>the</strong> conterminous United States, J. Hydrometeorology. 6, 985-1001<br />
Berners-Lee, T., J. Hendler, and O. Lassila 2001 “The Semantic Web,” Scientific American,<br />
May, 2001<br />
Boston, T 2010 Australian Water and Climate Networks: <strong>the</strong> Changing Environment of Data<br />
Sharing,” Workshop on Standards-based Frameworks underpinning Linked Information Sharing<br />
Networks, Canberra, 5 Nov 2010<br />
V. Castillo 2009 Brief note on <strong>the</strong> Inter-‐Regional Workshop on Indices and Early Warning<br />
Systems for <strong>Drought</strong>, 8-‐11 December 2009, Lincoln, Nebraska U.S.A.<br />
Dai, A., K. E. Trenberth, & T. Qian, 2004. A global dataset of Palmer <strong>Drought</strong> Severity Index<br />
for 1870 - 2002: Relationship with soil moisture and effects of surface warming. Journal of<br />
Hydrometeorology, 5, 1117 – 1130<br />
Doubkova, M. A. Bartsch, C. Pa<strong>the</strong>, D. Sabel, and W. Wagner The Medium Resolution Soil<br />
Moisture Dataset: Overview of <strong>the</strong> SHARE ESA TIGER Project<br />
Dracup, J. A., K. Seong Lee, and E. G. Paulson 1980 “On <strong>the</strong> Definition of <strong>Drought</strong>s,” Water<br />
Resources Research, 16, 2, 297-302<br />
Euro<strong>GEOSS</strong> 2010, Specification of <strong>the</strong> Euro<strong>GEOSS</strong> Initial Operating Capacity<br />
Fleig, A.K., L. M. Tallaksen, H. Hisdal, & S. Demuth 2006. A global evaluation of streamflow<br />
drought characteristics. Hydrology and Earth System Sciences, 10, 535 – 552<br />
Gibbs, W.J., & J. V. Maher 1967. Rainfall deciles as drought indicators. Australian Bureau of<br />
Meteorology<br />
Hadwen, T. 2008 “The North American <strong>Drought</strong> Monitor—The Canadian Perspective,”<br />
presentation, March 16-18, Canmore, Alberta.<br />
Iglesias, A. and J. Schlickenrieder 2010 “Overview of Indicators,” Mediterranean Joint Process<br />
Water Scarcity and <strong>Drought</strong> Working Group Meeting, Madrid, 17 Feb 2010<br />
Institute of Hydrology. 1980. Low flow studies. Tech. rept. Institute of Hydrology, Wallingford,<br />
UK<br />
International Organization for Standardization 1994, “Information technology—Open systems<br />
interconnection—Basic Reference Model: The Basic Model,” ISO/IEC 7498-1<br />
Jones, D.A., W. Wang, and R. Fawcett 2009 “High quality spatial climate datasets for Australia,”<br />
Australia Meteorologic and Oceanographic Journal, 58, 233-248<br />
Page 66
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Date: 11/Feb/2011<br />
Keyantash, J.A., & J. A. Dracup 2004. An aggregate drought index: Assessing drought severity<br />
based on fluctuations in <strong>the</strong> hydrologic cycle and surface water storage. Water Resources<br />
Research, 40, W09304<br />
Koike, T 2010 “<strong>GEOSS</strong>/AWCI Summary Report, including updates of <strong>the</strong> demonstration<br />
projects,” presentation at <strong>the</strong> 6 th <strong>GEOSS</strong>/AWCI International Coordination Group (ICG)<br />
Meeting, Bali, Indonesia, 13 March 2010<br />
Lawrence, B. 2010 “British Experience with Building Standards-based Networks for Climate<br />
and Environmental Research,” presentation, Standards Based Information Sharing Networks<br />
workshop, Canberra, Australia, 5 Nov 2010<br />
Lemon, D. P. Box, and R. Atkinson 2010 “Towards a National Environmental Information<br />
Repurposing System, presentation, Standards Based Information Sharing Networks workshop,<br />
Canberra, Australia, 5 Nov 2010<br />
Lloyd-Hughes, B. and M. A. Saunders 2002 “A drought climatology for Europe,” International<br />
Journal of Climatology, 22, 1571-1592<br />
Luo, L., J. Sheffield, and E. F. Wood “Towards a global drought monitoring and forecasting<br />
capability,” 33 rd NOAA annual Climate Diagnostics and Prediction Workshop, 20-24 October<br />
2008, Lincoln, NE<br />
Mendicino, G., A Senatore, & P. Versace, 2008. A Groundwater Resource Index for drought<br />
monitoring and forecasting in a Mediterranean climate. Journal of Hydrology, 357, 282 – 302<br />
McKee, T.B., N. J. Doesken, & J. Kleist 1993. The relationship of drought frequency and<br />
duration to time scales. In: Eighth Conference on Applied Climatology. 17-22 January, Anaheim,<br />
California<br />
Moreira,E., C. Coelho, A. Paolo, L. Pereira, and J. Mexia 2008 “SPI-based drought category<br />
prediction using log linear models, Journal of Hydrology 354, 116-130.<br />
Nagai, M. 2009 “Interoperability Arrangements for Geospatial Data,” presentation delivered at<br />
Workshop on Geospatial Information for Developing Countries, December 16, 2009, India<br />
Naresh Kumar, M., C. S. Murthy, M. V. R. Sesha Sai, & P. S. Roy 2009. On <strong>the</strong> use of<br />
Standardized Precipitation Index (SPI) for drought intensity assessment. Meteorological<br />
applications, 16, 381 – 389<br />
Nunez, L. N. “National Meteorological <strong>Service</strong> <strong>Drought</strong> <strong>Monitoring</strong>”<br />
O’ Hagan, R. G., B. Robinson, G. Swan, and D. Kinny 2008 “Web-based Visualization of Water<br />
Information,” Commonwealth of Australia Water for a Healthy Country Flagship Report<br />
C. W. Pa<strong>the</strong>, W., D. Sabel, M. Doubkova, and J. Basara, 2009 "Using ENVISAT ASAR <strong>Global</strong><br />
Mode Data for Surface Soil Moisture Retrieval Over Oklahoma, USA," IEEE Transactions on<br />
Geosciences and Remote Sensing, 2009<br />
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Date: 11/Feb/2011<br />
Peters, E., & H. A. J. van Lanen 2005 Separation of base flow from streamflow using<br />
groundwater levels- illustrated for <strong>the</strong> Pang catchment (UK). Hydrological Processes, 19(4), 921<br />
– 936<br />
Rizolli, Li, Athanasiadis, and Marechal 2007 “Semantic-rich interfaces for Simulation<br />
Interoperability”<br />
Rodell, M. “Remote Sensing of Terrestrial Water Storage and Application to <strong>Drought</strong><br />
monitoring,”<br />
Sabel, D 2006 “Scaling information from ENVISAT ASAR for downscaling of scatterometer<br />
derived soil moisture estimates down to 1 km,” (<strong>the</strong>sis), Technical University of Wien<br />
Shafer, B.A., & L. E. Dezman 1982 Development of a Surface Water Supply Index (SWSI) to<br />
assess <strong>the</strong> severity of drought conditions in snowpack runoff areas (Colorado). Pages 164 – 175<br />
of: Product of 50th Western Snow Conference<br />
Sheffield, J., G. Goteti, F. Wen, and E.F. Wood, 2004 A simulated soil moisture based drought<br />
analysis for <strong>the</strong> USA. J. Geophysical. Res., 109, D24108, doi: 10.1029/2004JD005182.<br />
Sheffield, J., G. Goteti, and E.F. Wood 2006 Development of a 50-yr, high resolution global<br />
dataset of meteorological forcing for land surface modeling, J. Climate, 13, 3088-3111.<br />
Sheffield, J., D.B.Lobell, and E. F. Wood 2010. <strong>Global</strong> <strong>Drought</strong> <strong>Monitoring</strong> and Forecasting,<br />
based on Satellite Data and Land Surface Modeling, American Geophysical Union, Fall Meeting,<br />
abstract #H23B-1189<br />
Sheffield, J., K. M. Andreadis, E. F. Wood, & D. P. Lettenmaier, D.P. 2009. <strong>Global</strong> and<br />
continental drought in <strong>the</strong> second half of <strong>the</strong> twentieth century: Severity-Area-Duration analysis<br />
and temporal variability of large-scale events. Journal of Climate, 22, 1962 – 1981<br />
Sheffield, J., & E. F. Wood 2007. Characteristics of global and regional drought, 1950 - 2000:<br />
Analysis of soil moisture data from off-line simulation of <strong>the</strong> terrestrial hydrologic cycle.<br />
Journal of Geophysical Research, 112, D17115<br />
Stahl, K., & H. Hisdal 2004. “Hydroclimatology,” in L, M. Tallaksen & H. A. J. Lanen, (eds.),<br />
Hydrological <strong>Drought</strong>: Processes and estimation methods for streamflow and groundwater.<br />
Development in water science, no. 48. Elsevier<br />
Svoboda, M 2010 “<strong>Drought</strong>: A global perspective: Efforts towards a <strong>Global</strong> <strong>Drought</strong> Early<br />
Warning System,” presentation at <strong>the</strong> INSPIRE conference, 23-25 June 2010, Krakow, Poland<br />
Tallaksen, L.M, & H. A. J. van Lanen 2004. Hydrological <strong>Drought</strong>: Processes and estimation<br />
methods for streamflow and groundwater. Development in water science, no. 48. Elsevier<br />
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Van Lanen, H. A. J., Z. W. Kundzeciwz, L. M. Talleksen, H. Hisdal, M. Fendekova, and C.<br />
Prudhomme 2008. Indices for Different Types of <strong>Drought</strong>s and Floods at Different Scales. EU<br />
Water and Climate Change (WATCH) Technical report number 11<br />
Vargas, E 2008a “<strong>Drought</strong> Management in Spain,” July 8, Zaragoza<br />
Vargas, E 2008b “New Water Indicator System in Spain,” Thematic EIONET Workshop “Water<br />
Quantity and Use,” Copenhagen, June 10-11<br />
Vischel, T., G. G. S. Pegram, S. Sinclair, W.Wagner, and A. Bartsch, "Comparison of soil<br />
moisture fields estimated by catchment modeling and remote sensing: A case study in South<br />
Africa," Hydrology and Earth System Sciences, vol. 12, pp. 751-767, 2008<br />
Wagner, W., C. Pa<strong>the</strong>, D. Sabel, A. Bartsch, C. Kuener, and K. Scipal “Experimental 1 kilometer<br />
soil moisture products from ENVISAT ASAR for Sou<strong>the</strong>rn Africa,”<br />
W. Wagner, G. Lemoine, and H. Rott, "A Method for Estimating Soil Moisture from ERS<br />
Scatterometer and Soil Data," Remote Sensing of Environment, vol. 70, pp. 191-207, 1999<br />
Wanders, N., H. A. J. van Lannen, A. F. van Loon 2010 Indicators for <strong>Drought</strong> Characterization<br />
on <strong>the</strong> <strong>Global</strong> Scale, European Union Water and Climate Change (EU-WATCH) Technical<br />
Report 24<br />
Werner, M.G.F., H.C. Winsemius, Y.A.Iglesias, Morales, S. Maskey, and D. Love2010<br />
“DEWFORA: <strong>Drought</strong> Forecasting and Early Warning for Africa,” 11 th<br />
WaterNet/WARFSA/GWP-SA symposium, Victoria Falls, Zimbabwe.<br />
Yirdaw, S.Z, K. R. Snelgrove, & C. O. Agboma 2008 GRACE satellite observations of terrestrial<br />
moisture changes for drought characterization in <strong>the</strong> Canadian Prairie. Journal of Hydrology,<br />
356, 84 –92.<br />
Yu, L. (2007) Semantic Web and Semantic Web <strong>Service</strong>s. Chapman and Hall/CRC<br />
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10. Euro<strong>GEOSS</strong> <strong>Drought</strong> Vocabulary Keywords<br />
DMCSEE - <strong>Drought</strong> Management Centre<br />
for Sou<strong>the</strong>ast Europe<br />
<strong>Drought</strong><br />
EDO - European <strong>Drought</strong> Observatory<br />
European drought product<br />
GPCC data<br />
Hydrolog<br />
y<br />
Meteorology<br />
NDWI - Normalized Difference Water<br />
Index<br />
National/multinational drought product<br />
Natural hazard<br />
PDSI<br />
Regional/local drought product<br />
Remote sensing<br />
SPI<br />
Soil<br />
Statistics<br />
alert<br />
anomaly<br />
arid climate, desert climate, dry climate<br />
arid zone, dryland, dry zone<br />
climate<br />
climate change<br />
climate variability<br />
composite drought indicator<br />
cumulative departure from normal or<br />
climatologically expected precipitation<br />
cumulative precipitation deficit<br />
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desertification<br />
discharge<br />
drought control<br />
drought duration<br />
drought early warning<br />
drought end<br />
drought forecast<br />
drought frequency<br />
<strong>Drought</strong><br />
hazard<br />
drought impact<br />
drought index<br />
drought indicator<br />
drought intensity<br />
drought management<br />
drought map<br />
drought mitigation<br />
drought monitoring<br />
drought monitoring system<br />
drought onset<br />
drought overview<br />
drought plan<br />
drought product<br />
drought region<br />
drought resilience<br />
drought risk<br />
drought severity<br />
drought spatial extent<br />
drought status<br />
drought stress<br />
drought threshold
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Dry<br />
season<br />
emergency<br />
evaporation<br />
evapotranspiration<br />
fAPAR - Fraction of Absorbed<br />
Photosyn<strong>the</strong>tically Active Radiation<br />
groundwater<br />
heat stress<br />
hydrological drought<br />
hydrological drought index<br />
hydrological status<br />
low flow<br />
meteorological drought<br />
meteorological drought index<br />
meteorological state<br />
normality<br />
piezometric level<br />
potential evapotranspiration<br />
pre-alert<br />
precipitation<br />
precipitation anomaly<br />
precipitation deficiency (amount, intensity,<br />
timing)<br />
precipitation deficit<br />
precipitation percentile<br />
rainfall<br />
rainfall anomaly<br />
remote sensing product<br />
reservoir<br />
reservoir volume<br />
semiarid climate<br />
semiarid zone<br />
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snow<br />
snow pack<br />
soil moisture<br />
soil moisture deficit<br />
spatial assessment of drought<br />
susceptibility to drought<br />
Time series<br />
trend<br />
type of drought<br />
vegetation productivity<br />
vegetation state index<br />
vulnerability to drought<br />
water deficit<br />
water<br />
runoff<br />
water scarcity<br />
water stored in reservoir<br />
water stress<br />
wea<strong>the</strong>r extremes
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11. Euro<strong>GEOSS</strong> Water Societal Benefit Area Keywords<br />
Biogeochemistry<br />
Climate prediction<br />
<strong>Drought</strong> prediction<br />
Ecosystem<br />
Fisheries and habitat<br />
Flood prediction<br />
Human Health<br />
Impacts of Humans<br />
Land use planning<br />
Management<br />
Production of Food<br />
Resource management<br />
Telecommunications-navigation<br />
Water Cycle<br />
Wea<strong>the</strong>r prediction<br />
12. Acknowledgments<br />
The role of <strong>the</strong> USA National Integrated <strong>Drought</strong> Information System and <strong>the</strong> USA<br />
National Oceanic and Atmospheric Administration (NOAA) is greatly appreciated in<br />
extending manpower and data and services hub capacity towards hosting <strong>the</strong> <strong>Global</strong><br />
<strong>Drought</strong> Monitor Portal. The manpower of <strong>the</strong> European <strong>Drought</strong> Observatory staff in<br />
setting up OGC Web Mapping <strong>Service</strong>-enabled Map Servers on <strong>the</strong> Princeton server and<br />
establishment of interoperability with <strong>the</strong> NIDIS server is also gratefully acknowledged.<br />
The role of <strong>the</strong> Japanese Aerospace Exploration Agency (JAXA) in helping<br />
support <strong>the</strong> GEO Water Community of Practice is acknowledged and appreciated. Such<br />
support was crucial in establishing <strong>the</strong> initial impetuous for setting up <strong>the</strong> global drought<br />
monitor <strong>through</strong> GEO.<br />
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