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poster - International Conference of Agricultural Engineering

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Agriculture is still by far the greatest consumer <strong>of</strong> water in the region, and is well<br />

above the world average. More than 80% <strong>of</strong> water resources are allocated to<br />

irrigation, with relatively high losses that exceed 50%. With the intensification <strong>of</strong><br />

water stress and the limited potential for additional water supply, in recent years<br />

great emphasis has been given to improving water use efficiency. In the agricultural<br />

sector, this has been expressed as “more crop and higher value per drop” (FAO,<br />

2000). In the last decade the EU Commission produced several documents<br />

addressing the integration <strong>of</strong> environmental concerns into the agricultural policy.<br />

Particularly was highlighted the needs <strong>of</strong> reliable indicators to monitor, measure and<br />

evaluate the real impact <strong>of</strong> proposed innovation on the environmental sustainability.<br />

Although the need is evident, still are missing practical indicators that farmers and<br />

water authorities can use to achieve their goals by taking note <strong>of</strong> and controlling<br />

changes occurring on-farm and on-irrigation district. Benchmarking tools and<br />

performance indicators can be efficient used for this purpose.<br />

Benchmarking may be defined as the identification and application <strong>of</strong> organisation<br />

specific best practices with the goal <strong>of</strong> improving competitiveness, performance and<br />

efficiency. It is a continuous process that involves (a) internal assessment <strong>of</strong> the<br />

organisation, (b) comparing it with the best practices <strong>of</strong> more successful similar<br />

businesses in the market, (c) determining performance gap between current practice<br />

and best practice, and (d) selecting best practices, tailoring them to fit the<br />

organisation and implementing them. Guidelines for benchmarking in the irrigation<br />

sector were proposed recently (Malano et al., 2004; Farmani et al., 2003).<br />

Performance assessment is based on performance indicators that are specifically<br />

identified to enable the comparison and to monitor progress towards closing the<br />

identified performance gap. Comparison between performance indicators is widely<br />

used in irrigation systems, very much as a tool for water management policies.<br />

Previous applications and checks have shown that performance indicators and<br />

benchmarking can be successfully applied using the common general guidelines,<br />

taking into account the special features <strong>of</strong> every zone, because not all irrigation<br />

zones <strong>of</strong> the world are similar. The core <strong>of</strong> any benchmarking exercise is data<br />

collection. In order to enable comparison between irrigation districts, data used for<br />

benchmarking need to be consistent and comparable.<br />

In the present paper a first set <strong>of</strong> data including both historic and pilot (experimental)<br />

data is presented and relative performance indicators were calculated.<br />

2. Materials and Methods<br />

2.1. Data collection<br />

The core <strong>of</strong> any benchmarking exercise is data collection. In order to enable<br />

comparison between irrigation districts, data used for benchmarking need to be<br />

consistent and comparable. There are three types <strong>of</strong> data collection:<br />

• data collected for day-to-day management, operation and maintenance <strong>of</strong> the<br />

irrigation systems, such as pumping costs, reservoir and canal level, flow<br />

rate, etc.<br />

• data collected for benchmarking and comparison with other systems.<br />

• data collected as part <strong>of</strong> the diagnostic process within the benchmarking<br />

exercise to identify causes <strong>of</strong> performance.<br />

To enable irrigation districts with different levels <strong>of</strong> data available to participate in the<br />

benchmarking process, a range <strong>of</strong> benchmarking indicators will be proposed.<br />

2.2. Performance indicators

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