poster - International Conference of Agricultural Engineering

More documents

Recommendations

Info

BELLOMARINO, S. A.; PARKER, R. M.; CONLAN, X. A.; BARNETT, N. W.; ADAMS, M. J. (2010). Partial least squares and principal components analysis of wine vintage by high performance liquid chromatography with chemiluminescence detection. Analytica Chimica Acta, v. 678, p. 34-38. CASTIGLIONI, S.; CASTELLARIN, A.; MONTANARI, A. (2009). Prediction of low-flow indices in ungauged basins through physiographical space-based interpolation. Journal of Hydrology, v. 378, p. 272-280. ENGELAND, K.; HISDAL, H. (2009). A comparison of low flow estimates in ungauged catchments using regional regression and the HBV-Model. Water Resources Management, v. 23, p. 2567-2586. HAIDER, S.; PARKINSON, G. N.; NEIDLE, S. (2008). Molecular dynamics and principal components analysis of Human Telomeric Quadruplex Multimers. Biophysical Journal, v. 95, p. 296-311. HATVANI, G. I.; KOVÁCS, J.; KOVÁCS, I. S.; JAKUSCH, P.; KORPONAI, J. (2011). Analysis of long-term water quality changes in the Kis-Balaton Water Protection System with time series, cluster analysis and Wilk’s lambda distribution. Ecological Engineering, v. 37, p. 629-635. INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE. (2010). Available in: < http://www.ibge.gov.br/home/>. In july 2010. KAHYA, E.; KALAYCI, S.; PIECHOTA, T. C. (2008). Streamflow regionalization: case study of Turkey. Journal of Hydrologic Engineering, v. 13. MARQUES, F.A.; SILVA, D. D.; RAMOS, M. M.; PRUSKI, F. F. (2009). Sistema multi-usuário para gestão de recursos hídricos. Revista Brasileira de Recursos Hídricos, v. 14, n. 4, p. 51-69. MELCHIORE, C.; MATTEUCCI, M.; AZZONI, A.; ZANCHI, A. (2008). Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology, v. 94, p. 379-400. MEZER, A.; YOVEL, Y.; PASTERNAK, O.; GORFINE, T.; ASSAF, Y. (2009). Cluster Analysis of resting-state fMRI time series. NeuroImage, v. 45, p. 1117-1125. MINAS GERAIS, Governo do Estado. (2010) Redes e bacias hidrográficas ottocodificadas de Minas Gerais. Belo Horizonte, Base vetorial. DVD. MWALE, D.; GAN, T. Y.; DEVITO, K. J.; SILINS, U.; MENDOZA, C.; PETRONE, R. (2010).Regionalization of Runoff Variability of Alberta, Canada, by Wavelet, Independent Component, Empirical Orthogonal Function, and Geographical Information System Analysis. Journal of Hydrologic Engineering, v. 16. PIRES, J. C. M.; SOUSA, S. I. V.; PEREIRA, M. C.; FERRAZ, M. C. M.; MARTINS, F. G. (2008). Management of air quality monitoring using principal component and cluster analysis: Part II – CO, NO 2 and O 3 . Atmospheric Environment, v. 42, p. 1261-1274. PLANO INTEGRADO DE RECURSOS HÍDRICOS DA BACIA DO RIO DOCE - PIRH. (2010). Available in: . In march, 2010. PRICE, A. L.; PATTERSON, N. J.; PLENGE, R. M.; WEINBLATT, M. E.; SHADICK, N. A.; REICH, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics, v. 38, p. 904–909. REID, M. K.; SPENCER, K. L. (2009). Use of principal components analysis (PCA) on estuarine sediment datasets: The effect of data pre-treatment. Environmental Pollution, v. 157, p. 2275-2281. RIBEIRO, C. B. M.; MARQUES F. A.; SILVA D. D. (2005). Estimativa e regionalização de vazões mínimas de referência para a bacia do rio Doce. Engenharia na Agricultura. Viçosa – MG, v.13, n. 2, p. 103-107. SAMUEL, J.; COULIBALY, P.; METCALFE, R. A. (2011). Estimation of Continuous Streamflow in Ontario Ungauged Basins: Comparison of Regionalization Methods. Journal of Hydrologic Engineering, v. 16. SOUSA, H. T., PRUSKI, F. F, SOUSA, J. F., BOF, L. H. N., CECON, P.R. (2008). Sistema Computacional para Regionalização de Vazões – SisCoRV 1.0. Universidade Federal de Viçosa - UFV, Viçosa-MG. WILKS, D. S. (2006). Statistical Methods in the Atmospheric Sciences. Academic Press, 630 p. USA. 6
Is Imaging Analysis Quantifying the Impacts of Solute Transport? A New Approach to Assess Wetting Front Map under Trickle Irrigation El-Sayed E. Omran 1 *, Gamal M. ElMasry 2 and Mohamed A. Rashad 2 1 Soil and Water Department, Faculty of Agriculture, Suez Canal University, Egypt. 2 Agricultural Engineering Department, Faculty of Agriculture, Suez Canal University, Egypt. * Corresponding author. E-mail: e.omran@scuegypt.edu.eg Abstrat To investigate solute transport in soils, detailed information about the spatial distribution of solutes is required. Many attempts have been made to determine wetting pattern under trickle irrigation using sophisticated mathematical and numerical models. These methods require detailed information concerning soil physical properties besides too complicated calculations for routine use. This study was carried out to investigate the feasibility of using image-analysis technique to derive soil wetting area and depth and to develop an image processing algorithm to derive soil wetting front map. A digital image analysis technique is proposed as a potential alternative method for visualizing and quantifying flow patterns in soils with a high spatial resolution. The method was applied in two soil types (sandy and sandy clay loam). The results of the proposed method showed that the image analysis technique gives reasonably good estimates of the wetting front map (depth and area). This potential approach to characterize flow patterns allows an objective comparison of soil infiltration patterns in the field. This proposed method could be generalized to quantify and easily derive soil flow patterns which are an important issue for precision irrigation farming and agricultural management. Key words: solute transport, image analysis, trickle irrigation, precision irrigation. Introduction Agricultural management, soil remediation and groundwater protection require ways of quantifying solute transport processes. Soil heterogeneity is responsible for the difficulty in predicting the movement of mass (solids, liquids and gases) in field situations at most scales [Lin & Zhou, 2008; Jamieson et al., 2002]. Solute transport in the unsaturated zone which is difficult to predict remains an important research topic in soil science [Vanderborght et al., 2002 and Omran, 2008]. The concern is mainly about the impact of solute transport on the water use efficiency. One of the methods that can provide high water use efficiency is trickle irrigation but only if the system is designed to meet the soil and plant conditions [Phene, 1995; Cook et al., 2006]. One of the pre-requisites for better trickle irrigation design is more information about the moisture distribution patterns. Trickle irrigation involves applying low quantity of water at low pressure via an emitter. The wetted-soil volume under a point source trickle systems must be known to determine the total number of emitters required to wet a specific volume of soil to meet plant water requirements [Ainechee et al., 2009]. The volume of wetted soil and its shape is primarily a function of the soil texture and structure, application rate, and number of emitters. So, it is essential to know the effect of the water application technique (discharge rate, continuous or intermittent application) on the amounts of water distributed to the various parts of the wetted soil volume [Elmaloglou & Diamantopoulos, 2007]. Water trickling from a point source takes place in the soil and moves downwards and sideways. As a result, three dimensional transient flows occur. There has been much speculation on the shape of the wetted soil volume. One of the important criteria when designing trickle irrigation systems is the geometry of the wetting pattern generated by the emitters [Cook et al., 2006]. Many attempts have been exerted to determine the wetting pattern under trickle irrigation using sophisticated mathematical and
Page 1 and 2:
POSTER SW: SOIL AND WATER ENGINEERI
Page 3 and 4:
Presenter: Jose Euclides Paterniani
Page 5 and 6:
1 Faculdade de Engenharia Agricola
Page 7 and 8:
Matsura Department of hydraulic and
Page 9 and 10:
P-2064 MULTIVARIATE STATISTICAL OF
Page 11 and 12:
temperature-based (e.g., Thornthwai
Page 13 and 14:
two types of reference surfaces rep
Page 15 and 16:
(d) Baft (c) Bam (b) Kerma n (a) Ji
Page 17 and 18:
Estevez, J., Gavilan, P., & Berenge
Page 19 and 20:
2. Materials and Methods 2.1 The hy
Page 21 and 22:
Ia = n × v ec Equation 3 which: Ia
Page 23 and 24:
5. References ALLEN, R.G.; PEREIRA,
Page 25 and 26:
The density analysis was performed
Page 27 and 28:
Figure1 - Relationship between the
Page 29 and 30:
4 Conclusions • The density obtai
Page 31 and 32:
characteristics resulting from of g
Page 33 and 34:
Table1. Morphological characteristi
Page 35 and 36:
Transpiration of Eucalyptus spp see
Page 37 and 38:
The fertilization growth and harden
Page 39 and 40:
Cool, J. B., Rodrigo, G. N., Garcí
Page 41 and 42:
Abstract Agriculture and water sour
Page 43 and 44:
In 1985 and 1986 hygienic protectio
Page 45 and 46:
spring area. It is also prohibited
Page 47 and 48:
Biological Nitrogen Fixation In Gen
Page 49 and 50:
We used a completely randomized in
Page 51 and 52:
5. References AYERS, R.S.; WESTCOT,
Page 53 and 54:
2 However, the cultures are not alw
Page 55 and 56:
4 TABEL 2: Mean values of radiation
Page 57 and 58:
accumulated ETo (mm dia -1 ) 6 900
Page 59 and 60:
only the expansion of agricultural
Page 61 and 62:
FIGURE 2: Content of chlorophyll a,
Page 63 and 64:
Evapotranspiration and Crop Coeffic
Page 65 and 66:
were respectively applied in the fi
Page 67 and 68:
TABLE 1: Irrigation depth and actua
Page 69 and 70:
NUTRIENT RETENTION IN WETLANDS USIN
Page 71 and 72:
Table 2. Daily affluent concentrati
Page 73 and 74:
IMPORTANCE OF DRY GEAR MASS CULTURE
Page 75 and 76:
mobilizing assimilated exerted by c
Page 77 and 78:
This method consists of covering th
Page 79 and 80:
uncovered ones, that mixed the wate
Page 81 and 82:
coliforms and E-coli that might hav
Page 83 and 84:
WATER TREATMENT BY COAGULATION WITH
Page 85 and 86:
in a grinder and passed through a 0
Page 87 and 88:
3.2. Determination of the required
Page 89 and 90:
ANALYSIS OF LEVELS OF LAND DEGRADAT
Page 91 and 92:
This methodology consists of a sequ
Page 93 and 94:
FIGURE 5. A - Area of exploitation
Page 95 and 96:
Water technology improvements and t
Page 97 and 98:
The Multiattribute Utility Theory (
Page 99 and 100:
higher demand than those of scenari
Page 101 and 102:
YIELD AND BEAN SIZE OF COFFEA ARABI
Page 103 and 104:
uniformity of flowering. The irriga
Page 105 and 106:
Table 3 - Analysis of variance for
Page 107 and 108:
SUGARCANE FERTIRRIGATED WITH MINERA
Page 109 and 110:
3. Results and Discussion The value
Page 111 and 112:
espectively, compared to that obser
Page 113 and 114:
Optimal Reservoir Operation Model w
Page 115 and 116:
all periods are computed using Eq.
Page 117 and 118:
(a) Calibration (b) Verification Fi
Page 119 and 120:
Characteristics of Heavy Metal Cont
Page 121 and 122:
2. Materials and Method 2.1. Study
Page 123 and 124:
TABLE 2: Devices for collecting of
Page 125 and 126:
Calibration of Hargreaves Equation
Page 127 and 128:
Relative error (RE): Index of agree
Page 129 and 130:
Stochastic modelling of Contaminant
Page 131 and 132:
widely used for various fields such
Page 133 and 134:
show that Extvalue and Logistic dis
Page 135 and 136:
Efficiency of water and energy use
Page 137 and 138:
Pressure: it was obtained by means
Page 139 and 140:
them cover similar percentages. Dur
Page 141 and 142:
Relationship among compaction, mois
Page 143 and 144:
Cylindrical containers (191mm diame
Page 145 and 146:
Figure 9 High compaction. Bulk dens
Page 147 and 148:
Simulation of water flow with root
Page 149 and 150:
water contents were almost greater
Page 151 and 152:
Operation and Energy Optimization M
Page 153 and 154:
Urmia Salt Lake Urmia FIGURE 1: Gha
Page 155 and 156:
changes have been done in system. F
Page 157 and 158:
Application of Surface Cover and So
Page 159 and 160:
significantly lower than those from
Page 161 and 162:
Choi, J. D., (1997). Effect of Rura
Page 163 and 164:
1.1. Scope and aim The growth of th
Page 165 and 166:
Therefore, the remaining works are
Page 167 and 168:
network makes such volumes unaccept
Page 169 and 170:
Reclaimed wastewater reuse has been
Page 171 and 172:
Fig. 2 shows the monitoring results
Page 173 and 174:
3. Conclusions Reclaimed wastewater
Page 175 and 176:
Q P Ia 2 P Ia S for P≥Ia Q 0
Page 177 and 178:
data P (mm), gauged in 130 pluviogr
Page 179 and 180:
TABLE 2: CN emp values obtained for
Page 181 and 182:
References Chapman, T. G. & Maxwell
Page 183 and 184:
This work, after applying Kennessey
Page 185 and 186:
TABLE 2 - Partial runoff coefficien
Page 187 and 188:
Figure 3 also reports a comparison
Page 189 and 190:
2. Material and Methods The experim
Page 191 and 192:
TABLE 2: Summary of variance analys
Page 193 and 194:
BEZERRA, I. L.; GHEYI, H. R.; FERNA
Page 195 and 196:
2. Materials and Methods The study
Page 197 and 198:
Figure 3. Hourly values of ET estim
Page 199 and 200:
Ortega-Farias, S.O., Cuenca, R.H.,
Page 201 and 202:
2 Material end methods The wastewat
Page 203 and 204:
Queiroz et al. (2004) and (Fonseca
Page 205 and 206:
Reference list CEREDA, M.P. (2001)
Page 207 and 208:
2. Data and Methods 2.1. Methods Ir
Page 209 and 210:
3. Results The water balance model
Page 211 and 212:
Acknowledgments This work was carri
Page 213 and 214:
and the need to reduce costs, it be
Page 215 and 216:
40 mm 65.30 59.00 8.70 8.10 60 mm 6
Page 217 and 218:
REFERENCES BERTRAND, J. P. et al. L
Page 219 and 220:
The mathematical modeling in the wa
Page 221 and 222:
OD (mg L -1 ) OD obs (mg L -1 ) TAB
Page 223 and 224:
OD (mg L -1 ) DBO (mg L -1 ) 8,00 7
Page 225 and 226:
Effect of Rice Straw Mulch on Runof
Page 227 and 228:
mg/L, 14.6 mg/L, and 1.2 mg/L, resp
Page 229 and 230:
1 PAPAYA SEEDLINGS PRODUCTION FROM
Page 231 and 232:
3 into an oven with circulating air
Page 233 and 234:
5 14 12 Stem diameter (mm) 10 8 6 4
Page 235 and 236:
7 Root dry matter (g plant -1 ) 8 7
Page 237 and 238:
CAVALCANTE, L. F.; CORDEIRO, J. C.;
Page 239 and 240:
This document was created with Win2
Page 241 and 242:
extractable and non-extractable bou
Page 243 and 244:
MOD-E and MOD-B, and 65.99% and 80.
Page 245 and 246:
Houot, S., Barriuso, E., Bergheaud,
Page 247 and 248:
measures water content and electric
Page 249 and 250:
As observed, increasing the dischar
Page 251 and 252:
irrigation: a comparison of point a
Page 253 and 254:
field operations (STRECK et al., 20
Page 255 and 256:
3. Results and discussions Table 1
Page 257 and 258:
4. Conclusions It can be concluded
Page 259 and 260:
water maintenance. At the same time
Page 261 and 262:
TABLE 1 Stream discharge for each m
Page 263 and 264:
TABLE 5 Correlation analysis of wat
Page 265 and 266:
turbulent flow energy produced by w
Page 267 and 268:
The numerical model was validated a
Page 269 and 270:
4. Conclusion FIGURE 6: The shape o
Page 271 and 272:
2.1 Case study The Zayandeh-Rud bas
Page 273 and 274:
economic factors. In this is a very
Page 275 and 276:
FIGURE 1. Location of the Wuliangsu
Page 277 and 278:
WT( o C) (a) 30 25 20 15 10 5 0 -5
Page 279 and 280:
(a) (b) (c) (d) (e) (f) (g) (h) (i)
Page 281 and 282: • The effectiveness of the crop c
Page 283 and 284: As evidenced by Rana et al. (2005),
Page 285 and 286: 1.20 1.20 2010 2011 0.90 0.90 K c 0
Page 287 and 288: elationships. There is forest area,
Page 289 and 290: B = ( c − a) A − ( c − d) c
Page 291 and 292: References Choi, W.-J., Lee, S.-M.,
Page 293 and 294: of faecal bacteria (Kummerer, 2004;
Page 295 and 296: FIGURE 1 - Project tasks and links
Page 297 and 298: Oliveira, A.B. & Henriques, M. (201
Page 299 and 300: 1 Introduction To irrigate is to su
Page 301 and 302: the inverter that provides a refere
Page 303 and 304: OLIVEIRA FILHO, D. ; SAMPAIO, R. P.
Page 305 and 306: 1.1 Description of the Study Area T
Page 307 and 308: Refrences: Bruce J.P. (1994). Natur
Page 309 and 310: RE because it has the advantages ov
Page 311 and 312: with L 1 2 com obs J ( k ) = ∑{ f
Page 313 and 314: Relative hydraulic conductivity r 1
Page 315 and 316: surfaces requires information on th
Page 317 and 318: climate. Therefore a special coeffi
Page 319 and 320: FIGURE 2: The relation between K pa
Page 321 and 322: Coagulation using Moringa oleifera
Page 323 and 324: After the assembly of the experimen
Page 325 and 326: For the positive control test, the
Page 327 and 328: MULTIVARIATE STATISTICAL OF PRINCIP
Page 329 and 330: The multiple regression equations w
Page 331: Table 3 - Regression models that be
Page 335 and 336: of the computer. All additional ima
Page 337 and 338: The final enhanced images were segm
Page 339 and 340: image analysis is well suited and f
Page 341 and 342: EVALUATION OF CROP CANOPY EFFECT ON
Page 343 and 344: ∂e ∂e ∂e + u + v ∂t ∂x
Page 345 and 346: 4. Results and discussion 4.1. Spat
Page 347 and 348: Benchmarking of Irrigated Agricultu
Page 349 and 350: Indicators can be thought of as sta
Page 351 and 352: total area is about 13,700 km2. The
show all

poster - International Conference of Agricultural Engineering

Create successful ePaper yourself

Delete template?

Save as template?