4. Conclusions Sensitivity coefficients <strong>of</strong> reference crop evapotranspiration to mean air temperature, net radiation, Vapor pressure deficit and wind speed were calculated and analyzed by ASCE- Penman-Monteith method in Kerman, Baft, Bam and Jir<strong>of</strong>t (Southeast <strong>of</strong> Iran) using daily dataset. The study results show that on the whole, net radiation is the most and air temperature is the least sensitive meteorological factors for most <strong>of</strong> measurement locations. Our results are not directly comparable to those <strong>of</strong> other sensitivity analyses since the predictions for vegetation surfaces (Beven, 1979; Saxton, 1975) or open-water surfaces (Mc Cuen, 1974) were considered in the other available papers. However, all studies (Mc Cuen, 1974; Saxton, 1975; Coleman and DeCoursey, 1976; Beven, 1979) showed that potential evaporation or evapotranspiration was much more sensitive to radiation and humidity. Therefore, accurate estimation <strong>of</strong> evapotranspiration rates in all the measurement stations depends primarily on the solar radiation. For highest S Rn (0.88), increase <strong>of</strong> 10% in net radiation may cause increase <strong>of</strong> 8.8% in ET o . We can conclude that vapor pressure deficit is the second controlling factor to ET o among the climate variables. The results provide a new approach for ET o estimation in Kerman province, and also can be used as a theoretical basis for future research on the response <strong>of</strong> reference evapotranspiration to climate change. References Ali, M. H., Adham, A. K. M., Rahman, M. M., & Islam, A. K. M. R. (2009). Sensitivity <strong>of</strong> Penman-Monteith estimates <strong>of</strong> reference evapotranspiration to errors in input climatic data. J. Agromet., 11(1), 1-8. Allen, R. G., Jensen, M. E., Wright, J. L., & Burman, R. D. (1989). Operational estimates <strong>of</strong> reference evapotranspiration. Agron. J., 81, 650-662. Allen, R. G., Smith, M., Pereira, L. S., & Perrier, A. (1994). An update for the calculation <strong>of</strong> reference evapotranspiration. ICID Bulletin, 43(2): 35–92. Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage, Paper No. 56, FAO, Rome. Allen, R. G., Walter, I. A., Elliott, L., Itenfisu, D., Brown, P., Jensen, M. E., Mecham, B., Howell, T. A., Snyder, R., Echings, T. S., Sp<strong>of</strong>ford, T., Hattendorf, M., Cuenca, R.H., Wright, J. L., & Martin, D. L. American Society <strong>of</strong> <strong>Agricultural</strong> Engineers. (2000). Issues, requirements and challenges in selecting and specifying a satandardized ET equation. Proceedings <strong>of</strong> the 4th National Irrigation Symposium, St. Joseph, Michigan. Anderton, S., Latron, J., & Gallart, F. (2002). Sensitivity analysis and multi-response, multicriteria evaluation <strong>of</strong> a physically based distributed model. Hydrol. Processes, 16, 333–353. ASCE-EWRI. (2005). The ASCE Standardized Reference Evapotranspiration Equation. Technical Committee report to the Environmental and Water Resources Institute <strong>of</strong> the American Society <strong>of</strong> Civil Engineers from the Task Committee on Standardization <strong>of</strong> Reference Evapotranspiration. ASCE-EWRI, 1801 Alexander Bell Drive, Reston, VA 20191- 4400, 173 p. Beven, K. (1979). A sensitivity analysis <strong>of</strong> the Penman- Monteith actual evapotranspiration estimates. J. Hydrol., 44, 169-190. Blaney, H. F., & Criddle, W. D. (1950). Determining Water Requirements in Irrigated Area from Climatological Irrigation Data, US Department <strong>of</strong> Agriculture, Soil Conservation Service, Techical, Paper No. 96, p. 48. Coleman, G., & DeCoursey, D. G. (1976). Sensitivity and model variance analysis applied to some evaporation and evapotranspiration models. Water Resour. Res., 12 (5), 873–879. Droogers, P., & Allen, R. G. (2002). Estimating reference evapotranspiration under inaccurate data conditions. Irrig. and Drain. Sys., 16, 33–45. Doorenbos, J., & Pruitt,W. O. (1977). Guidelines for Prediction <strong>of</strong> Crop Water Requirements. F.A.O. Irrig. and Drain. Paper No. 24. 2nd ed., FAO, Rome, Italy, 156 pp. 7
Estevez, J., Gavilan, P., & Berengena, J. (2009). Sensitivity analysis <strong>of</strong> a Penman–Monteith type quation to estimate reference evapotranspiration in southern Spain. Hydrol. Processes, 23, 3342–3353. Gong, L., Xu, C. Y., Chen, D., Halldin, S., & Chen, Y. D. (2006). Sensitivity<strong>of</strong>thePenman- Monteithreference evapotranspirationtokeyclimaticvariablesinthe Changjiang(YangtzeRiver) basin. J. Hydrol., 329, 620- 629 Goyal, R. K. (2004). Sensitivity <strong>of</strong> evapotranspiration to global warming: A case study <strong>of</strong> arid zone <strong>of</strong> Rajasthan (India). Agric. Water Management, 69(1): 1–11. Guitjens, J. C. (1982). Models <strong>of</strong> Alfalfa Yield and Evapotranspiration. Journal <strong>of</strong> the Irrigation and Drainage Division, Proceedings <strong>of</strong> the American Society <strong>of</strong> Civil Engineers, 108(IR3), 212-222. Harbeck, Jr., G. E. (1962). A Practical Field Technique for Measuring Reservoir Evaporation Utilizing Mass-transfer Theory, US Geological Survey, Paper 272-E, 101–105. Hatfield, J. L., Prueger, J. H., & Reicosky, D. C. (1996). Evapotranspiration effects on water quality. In: Proceeding <strong>of</strong> the ASAE <strong>International</strong> <strong>Conference</strong> on Evapotranspiration and Irrigation Scheduling, 3–6 November, San Antonio, TX, 536–546. Hupet, F., & Vanclooster, M. (2001). Effect <strong>of</strong> the sampling frequency <strong>of</strong> meteorological variables on the estimation <strong>of</strong> the reference evapotranspiration. Journal <strong>of</strong> Hydrology, 243, 192-204. Irmak, S., Payero, J. O., Martin, D. L., Irmak, A., & Howell, T. A. (2006). Sensitivity analyses and sensitivity coefficients <strong>of</strong> standardized daily ASCEPenman-Monteith equation. J. Irrig. Drain. Eng., 132(6), 564–578. Itenfisu, D., Elliot, R. L., Allen, R. G., & Walter, I. A. (2003). Comparison <strong>of</strong> reference evapotranspiration calculations as part <strong>of</strong> the ASCE standardization effort. J. Irrig. Drain. Eng., 129 (6), 440–448. Jensen, M. E., Burman, R. D., & Allen, R. G. (eds), (1990). Evapotranspiration and Irrigation Water Requirements. New York: ASCE, 332 pp. Khalili, A., 1997. Integrated water plan <strong>of</strong> Iran. Vol. 4: Meteorological studies, Ministry <strong>of</strong> Power, Iran. Ley, T. W., Hill, R. W., & Jensen, D. T. (1994). Errors in Penman-Wright alfalfa reference evapotranspiration estimates: Effects <strong>of</strong> weather sensor measurement variability. Trans. ASAE, 37(6), 1863-1870. Mc Cuen, R. H. (1973). The role <strong>of</strong> sensitivity analysis in hydrologic modeling. J. Hydrol. 18, 37–53. Meyer, S. J., Hubbard, K. G., & Wilhite, D.A. (1989). Estimating potential evapotranspiration: the effect <strong>of</strong> random and systematic errors. Agric. For. Meteorol., 46, 285–296. Penman, H. L., 1948. Natural evaporation from open water, bare soil and grass. Proceedings <strong>of</strong> the Royal Society <strong>of</strong> London, 193, 120–145. Piper, B. (1989). Sensitivity <strong>of</strong> Penman estimates <strong>of</strong> evaporation to errors in input data. <strong>Agricultural</strong> Water Manage., 15, 279-300. Priestley, C. H. B., & Taylor, R. J. (1972). On the assessment <strong>of</strong> the surface heat flux and evaporation using large-scale parameters. Monthly Weather Review, 100, 81–92. Rana, G., & Katerji, N. (1998). A measurement based sensitivity analysis <strong>of</strong> the Penman- Monteith actual evapotranspiration model for crops <strong>of</strong> different height and in contrasting water status. Theoret. and Appl. Climatol., 60,141-149. Saltelli, A., Chan, K., & Scott, M. (2004). Sensitivity Analysis. John Wiley & Sons Publishers, N. Y. Saxton, K. E. (1975). Sensitivity analysis <strong>of</strong> the combination evapotranspiration equation. Agric. Meterol., 15, 343-353. Smajstrla, A. G., Zazueta, F. S., & Schmidt, G. M. (1987). Sensitivity <strong>of</strong> potential evapotranspiration to four climatic variables in Florida. Soil and Crop Sci. Soc. <strong>of</strong> Florida, 46, 21–26. Thornthwaite, C. W. (1948). An approach toward a rational classification <strong>of</strong> climate. Geograph. Review, 38, 55–94. 8
- 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: (d) Baft (c) Bam (b) Kerma n (a) Ji
- 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 and 332:
Table 3 - Regression models that be
- Page 333 and 334:
Is Imaging Analysis Quantifying the
- 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