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1.
Ozgur Kisi 《水文研究》2008,22(14):2449-2460
The potential of three different artificial neural network (ANN) techniques, the multi‐layer perceptrons (MLPs), radial basis neural networks (RBNNs) and generalized regression neural networks (GRNNs), in modelling of reference evapotranspiration (ET0) is investigated in this paper. Various daily climatic data, that is, solar radiation, air temperature, relative humidity and wind speed from two stations, Pomona and Santa Monica, in Los Angeles, USA, are used as inputs to the ANN techniques so as to estimate ET0 obtained using the FAO‐56 Penman–Monteith (PM) equation. In the first part of the study, a comparison is made between the estimates provided by the MLP, RBNN and GRNN and those of the following empirical models: The California Irrigation Management Information System (CIMIS) Penman (1985), Hargreaves (1985) and Ritchie (1990). In this part of the study, the empirical models are calibrated using the standard FAO‐56 PM ET0 values. The estimates of the ANN techniques are also compared with those of the calibrated empirical models. Mean square errors, mean absolute errors and determination coefficient statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it is found that the MLP and RBNN techniques could be employed successfully in modelling the ET0 process. In the second part of the study, the potential of ANN techniques and the empirical methods in ET0 estimation using nearby station data is investigated. Among the models, the calibrated Hargreaves model is found to perform better than the others. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
2.
《水文科学杂志》2013,58(5):918-928
Abstract This study investigates the accuracy of support vector machines (SVM), which are regression procedures, in modelling reference evapotranspiration (ET0). The daily meteorological data, solar radiation, air temperature, relative humidity and wind speed from three stations, Windsor, Oakville and Santa Rosa, in central California, USA, are used as inputs to the support vector machines to reproduce ET0 obtained using the FAO-56 Penman-Monteith equation. A comparison is made between the estimates provided by the SVM and those of the following empirical models: the California Irrigation Management System (CIMIS) Penman, Hargreaves, Ritchie and Turc methods. The SVM results were also compared with an artificial neural networks method. Root mean-squared errors, mean-absolute errors, and determination coefficient statistics are used as comparing criteria for the evaluation of the models' performances. The comparison results reveal that the support vector machines could be employed successfully in modelling the ET0 process. 相似文献
3.
The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET0). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET0. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET0. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET0, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four-input PCE models for Isparta and Antalya, respectively. 相似文献
4.
ABSTRACTThe Hargreaves method provides reference evapotranspiration (ETo) estimates when only air temperature data are available, although it requires previous local calibration for an acceptable performance. This method was evaluated using the data from 71 meteorological stations in the Seolma-cheon basin (8.48 km2), South Korea, comparing daily estimates against those from the Penman‐Monteith (PM) method, which was used as the standard. To estimate reference ETo more exactly, considering the climatological characteristics in South Korea, parameter regionalization of the Hargreaves equation is carried out. First, the modified Hargreaves equation is presented after an analysis of the relationship between solar radiation and temperature. Second, parameter (KET) optimization of the regional calibration of the Hargreaves equation (RCH) is performed using the PM method and the modified equation at 71 meteorological stations. Next, an application was carried out to evaluate the evapotranspiration methods (PM, original Hargreaves and RCH) in the SWAT (Soil and Water Assessment Tool) model by comparing these with the measured actual evapotranspiration (AET) in the basin. The SWAT model was calibrated using 3 years (2007–2009) of daily streamflow at the watershed outlet and 3 years (2007–2009) of daily AET measured at a mixed forest. The model was validated with 3 years (2010‐2012) of streamflow and AET. RCH will contribute to a better understanding of evapotranspiration of an ungauged watershed in areas where meteorological information is scarce.
EDITOR D. Koutsoyiannis ASSOCIATE EDITOR Not assigned 相似文献
5.
Reference evapotranspiration (ET) is an important parameter that needs to be estimated accurately to enhance its utility in numerous applications. Although the widely recommended procedure for calculating this index involves using the FAO Penman–Monteith equation (ETo), the latter’s effectiveness is constrained by its considerable data requirements. To overcome this constraint, alternative methods using the limited data available have to be explored. In this study the ability of the Hargreaves and Samani (ETHS) and Thornthwaite (ETT) equations to estimate ET was investigated using multi-year data (1999–2008) from eight weather stations in the semi-arid Free State Province of South Africa. Results for non-calibrated equations are closely correlated, with ETHS tending to underestimate ET for the July to December period while ETT underestimates ET for all months of the calendar year. Although estimates from calibrated equations are also closely correlated, they have smaller deviations compared to the original equations with the calibrated Hargreaves and Samani equation (ETCHS) estimating reference evapotranspiration better than its calibrated Thornthwaite (ETCT) counterpart. The former’s better performance suggests that in data-scarce areas, the Hargreaves and Samani model is capable of giving results within acceptable ranges of accuracy. 相似文献
6.
Accurate estimation of evapotranspiration (ET) is essential in water resources management and hydrological practices. Estimation of ET in areas, where adequate meteorological data are not available, is one of the challenges faced by water resource managers. Hence, a simplified approach, which is less data intensive, is crucial. The FAO‐56 Penman–Monteith (FAO‐56 PM) is a sole global standard method, but it requires numerous weather data for the estimation of reference ET. A new simple temperature method is developed, which uses only maximum temperature data to estimate ET. Ten class I weather stations data were collected from the National Meteorological Agency of Ethiopia. This method was compared with the global standard PM method, the observed Piche evaporimeter data, and the well‐known Hargreaves (HAR) temperature method. The coefficient of determination (R2) of the new method was as high as 0.74, 0.75, and 0.91, when compared with that of PM reference evapotranspiration (ETo), Piche evaporimeter data, and HAR methods, respectively. The annual average R2 over the ten stations when compared with PM, Piche, and HAR methods were 0.65, 0.67, and 0.84, respectively. The Nash–Sutcliff efficiency of the new method compared with that of PM was as high as 0.67. The method was able to estimate daily ET with an average root mean square error and an average absolute mean error of 0.59 and 0.47 mm, respectively, from the PM ETo method. The method was also tested in dry and wet seasons and found to perform well in both seasons. The average R2 of the new method with the HAR method was 0.82 and 0.84 in dry and wet seasons, respectively. During validation, the average R2 and Nash–Sutcliff values when compared with Piche evaporation were 0.67 and 0.51, respectively. The method could be used for the estimation of daily ETo where there are insufficient data. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
7.
Gene Expression Programming (GEP) was used to develop new mathematical equations for estimating daily reference evapotranspiration (ET ref) for the Kingdom of Saudi Arabia. The daily climatic variables were collected by 13 meteorological stations from 1980 to 2010. The GEP models were trained on 65% of the climatic data and tested using the remaining 35%. The generalised Penman-Monteith model was used as a reference target for evapotranspiration (ET) values, with h c varies from 5 to 105 cm with increment of a centimetre. Eight GEP models have been compared with four locally calibrated traditional models (Hargreaves-Samani, Irmak, Jensen-Haise and Kimberly-Penman). The results showed that the statistical performance criteria values such as determination coefficients (R 2) ranged from as low as 64.4% for GEP-MOD1, where the only parameters included (maximum, minimum, and mean temperature and crop height), to as high as 95.5% for GEP-MOD8 with which all climatic parameters included (maximum, minimum and mean temperature; maximum, minimum and mean humidity; solar radiation; wind speed; and crop height). Moreover, an interesting founded result is that the solar radiation has almost no effect on ET ref under the hyper arid conditions. In contrast, the wind speed and plant height have a great positive impact in increasing the accuracy of calculating ET ref. Furthermore, eight GEP models have obtained better results than the locally calibrated traditional ET ref equations. 相似文献
8.
M5 model tree based modelling of reference evapotranspiration 总被引：1，自引：0，他引：1
This paper investigates the potential of M5 model tree based regression approach to model daily reference evapotranspiration using climatic data of Davis station maintained by California irrigation Management Information System (CIMIS). Four inputs including solar radiation, average air temperature, average relative humidity, and average wind speed whereas reference evapotranspiration calculated using a relation provided by the CIMIS was used as output. To compare the performance of M5 model tree in predicting the reference evapotranspiration, FAO–56 Penman–Monteith equation and calibrated Hargreaves–Samani relation was used. A comparison of results suggests that M5 model tree approach works well in comparison to both FAO–56 and calibrated Hargreaves–Samani relations. To judge the generalization capability of M5 model tree approach, model created by using the Davis data set was tested with the datasets of four different sites. Results from this part of the study suggest that M5 model tree could successfully be employed in modeling the reference evapotranspiration. Further, sensitivity analysis with M5 model tree approach suggests the suitability of solar radiation, average air temperature, average relative humidity, and average wind speed as input parameters to model the reference evapotranspiration Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
9.
The eddy covariance (EC) method was used in a 30‐month study to quantify evapotranspiration (ET) and vegetation coefficient (KCW) for a wetland on a ranch in subtropical south Florida. To evaluate the errors in ET estimates, the EC‐based ET (ETC‐EC) and the Food and Agricultural Organization (FAO) Penman–Monteith (PM) based ET (ETC‐PM) estimates (with literature crop coefficient, KC) were compared with each other. The ETC‐EC and FAO‐PM reference ET were used to develop KCW. Regression models were developed to estimate KCW using climatic and hydrologic variables. Annual and daily ETC‐EC values were 1152 and 3.27 mm, respectively. The FAO‐PM model underestimated ET by 25% with ETC‐EC being statistically higher than ETC‐PM. The KCW varied from 0.79 (December) to 1.06 (November). The mean KCW for the dry (November–April) season (0.95) was much higher than values reported for wetlands in literature; whereas for the wet (May–October) season, KCW (0.97) was closer to literature values. Higher than expected KCW values during the dry season were due to higher temperature, lower humidity and perennial wetland vegetation. Regression analyses showed that factors affecting the KCW were different during the dry (soil moisture, temperature and relative humidity) and wet (net radiation, inundation and wind speed) seasons. Separate regression models for the dry and wet seasons were developed. Evapotranspiration and KCW from this study, one of the first for the agricultural wetlands in subtropical environment, will help improve the ET estimates for similar wetlands. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
10.
Estimation of daily evapotranspiration (ET) over cloudy regions highly desires models which rely on meteorological data only. Notwithstanding, the conventional crop coefficient (Kc) method requires detailed knowledge of geo/biophysical properties of the coupled land-vegetation system, precipitation, and soil moisture. Six Eddy Covariance (EC) towers in Iowa, California and New Hampshire of the USA (covering corn, soybeans, prairie, and deciduous forest) were selected. Investigation on 6 years (2007–2012) 15-min micrometeorological records of these sites revealed that there is an indubitable strong interaction between relative humidity (RH), reference ET (ETo), and actual ET at different timescales. This allowed to bypass the need for the non-meteorological inputs and express Kc as a second-order polynomial function of RH and ETo, the ambient regression evapotranspiration model (AREM). The coefficients of the empirical function are crop-specific and may require calibration over different soil types. The mean absolute percentage error (MAPE) of the regression against daily EC observations was 17% during the growing season, and 32% throughout the year with root mean square error (RMSE) of 0.74 mm day−1 and coefficient of determination of 0.71. The model was fully operational (MAPE of 34% and RMSE of 0.82 mm day−1) over the four Iowan sites based on inputs from local weather stations and NLDAS-2 forcing data of NASA. AREM was capable of capturing the dynamics of ET at 15-min and daily timescales irrespective of varying complexities associated with biophysical, geophysical and climatological states. 相似文献
11.
ABSTRACTThe performance of eight empirical equations for estimating ETo at 80 weather stations in Iran is evaluated. The equations assessed are Hargreaves (HGS), Trajkovic (TKC), Berti (BTI), Ravazzani (RZI), Irmak (IMK), Turc (TRC) and two Valiantzas methods (VTS1 and VTS2). The FAO56 reference crop Penman-Monteith (PM) equation is used as a baseline to evaluate their performance. Also, a Köppen climate classification map for Iran is developed and the best ETo method for each climate type identified. The updated Köppen climate map shows six climate sub-classes; BWh, BWk, BSh, BSk, Csa and Dsa in Iran with a percentage of land area covered by each sub-class of 43, 17, 7, 9, 11 and 13%, respectively. The best performing ETo equation for each climate class in Iran was HGS for BSh, VTS1 for BWk, and VTS2 for BSk, BWh, Csa and Dsa. 相似文献
12.
Sensitivity analysis is crucial in assessing the impact of climatic variables on reference evapotranspiration estimations. The sensitivity of the standardized ASCE–Penman–Monteith evapotranspiration equation for daily estimations to climatic variables has not yet been studied in Spain. Andalusia is located in southern Spain where almost 1 million ha are irrigated under quite different conditions; it has a high inter‐annual variability in rainfall. In this study, sensitivity analyses for this equation were carried out for temperature, relative humidity, solar radiation and wind speed data from 87 automatic weather stations, including coastal and inland locations, from 1999 to 2006. Topography and Mediterranean climate characterize the heterogeneous landscape and vegetation of this region. Simulated random and systematic errors have been added to meteorological data to obtain ET0 deviations and sensitivity coefficients for different time periods. BIAS and SEE (standard error of estimate) have been used to evaluate the effect of both types of errors. The results showed a large degree of daily and seasonal variability, especially for temperature and relative humidity. In general, the effect on ET0 values of introduced random errors was larger than that of systematic errors. ET0 overestimations were produced using positive errors in temperature, solar radiation and wind speed data, while these errors in relative humidity resulted in ET0 underestimations. The sensitivity of ET0 to the same climatic variables showed significant differences among locations. The geographical distribution of sensitivity coefficients across this region was also studied. As an example, during spring months, ET0 equation was more sensitive to temperature in stations located along the Guadalquivir Valley. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
13.
The temporal trends of reference evapotranspiration (ETref) reflect the combined effects of radiometric and aerodynamic variables, such as global solar radiation (Rs), wind speed, relative humidity and air temperature. The temporal trends of annual ETref during 1961–2006 calculated by Penman‐Monteith method were explored and the underlying causes for these trends were analysed in the Yellow River Basin (YRB). The contributions of key meteorological variables to the temporal trend of ETref were detected using the detrended method and then sensitivity coefficients of ETref to meteorological variables were determined. For ETref, positive trends in the upper, middle and whole of YRB, and significant negative trend (P = 0·05) in the lower basin were obtained by the linear fitted model. Significant increasing trend (P = 0·05) in air temperature and decreasing trend in relative humidity were the main causes for the increasing trends of ETref in the upper, middle and whole basins. For the whole basin, the increasing trend of ETref was mainly caused by the significant increase (P = 0·05) in air temperature and to a lesser extent by a decrease in the relative humidity, decreasing trends of Rs and wind speed reduced ETref. The spatial distribution of sensitivity coefficients addressed that the sensitive regions for ETref response to the changes of the four meteorological variables are different in the YRB. The sensitive region lay in the upper basin for Rs, the northwest portion of the middle basin for wind speed, the south portion of YRB for relative humidity and the west portion of the upper basin and the north portion of the middle basin for air temperature. In general, Rs was the most sensitive variable for ETref, followed by relative humidity, air temperature and wind speed in the basin scale. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
14.
Abstract The Blaney-Criddle (BC) temperature-based equation is used in areas where the complete weather data to estimate reference evapotranspiration (ET0) by the Penman-Monteith FAO-56 (PMF-56) standard model is complex. In this study, the BC equation was first tested and calibrated against the ET0 values computed by the PMF-56 method using data from 17 weather stations in arid regions of Iran. Then, geographical information systems (GIS)-based spatially-distributed maps of ET0 were prepared by means of geographic/topographic factors derived from a digital elevation model (DEM) for all months, separately. The results indicate that the original BC equation overestimated PMF-56 ET0 by 4% at the study sites. The BC equation produced closer ET0 estimates to the PMF-56 method after it was calibrated. The error rate of <3% for the spatial modelling approach suggests that the developed ET0 maps are reliable. Editor D. Koutsoyiannis; Associate editor D. Yang Citation Tabari, H., Hosseinzadeh Talaee, P., and Shifteh Some'e, B., 2013. Spatial modelling of reference evapotranspiration using adjusted Blaney-Criddle equation in an arid environment. Hydrological Sciences Journal, 58 (2), 408–420. 相似文献
15.
《水文科学杂志》2013,58(4):893-904
Abstract An explicit neural network formulation (ENNF) is developed for estimating reference evapotranspiration (ET0) using daily meteorological variables obtained from the California Irrigation Management Information System (CIMIS) database. First, the ENNF is trained and tested using the CIMIS database, and then compared with five conventional ET0 models, as well as the multiple linear regression method. Statistics such as average, standard deviation, minimum and maximum values, and criteria such as mean square error and determination coefficient are used to measure the performance of the ENNF. Daily atmospheric data of four climatic stations in central California are taken into consideration in the model development and those of three other stations are used for comparison purposes. The meteorological variables employed in the formulation are solar radiation, air temperature, relative humidity and wind speed. It is concluded from the results that ENNF offers an alternative ET0 formulation, but that the gain in skill is marginal compared with simpler linear techniques. However, this finding needs to be tested using sites drawn from a wider range of climate regimes. 相似文献
16.
Evapotranspiration (ET) is one of the basic components of the hydrologic cycle and is essential for estimating irrigation water requirements. In this study, an artificial neural network (ANN) model for reference evapotranspiration (ET0) calculation was investigated. ANNs were trained and tested for arid (west), semi‐arid (middle) and sub‐humid (east) areas of the Inner Mongolia district of China. Three or four climate factors, i.e. air temperature (T), relative humidity (RH), wind speed (U) and duration of sunshine (N) from 135 meteorological stations distributed throughout the study area, were used as the inputs of the ANNs. A comparison was conducted between the estimates provided by the ANNs and by multilinear regression (MLR). The results showed that ANNs using the climatic data successfully estimated ET0 and the ANNs simulated ET0 better than the MLRs. The ANNs with four inputs were more accurate than those with three inputs. The errors of the ANNs with four inputs were lower (with RMSE of 0·130 mm d?1, RE of 2·7% and R2 of 0·986) in the semi‐arid area than in the other two areas, but the errors of the ANNs with three inputs were lower in the sub‐humid area (with RMSE of 0·21 mm d?1, RE of 5·2% and R2 of 0·961. For the different seasons, the results indicated that the highest errors occurred in September and the lowest in April for the ANNs with four inputs. Similarly, the errors were higher in September for the ANNs with three inputs. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
17.
Hossein Tabari Parisa Hosseinzadehtalaei Patrick Willems Christopher Martinez 《水文科学杂志》2013,58(3):610-619
ABSTRACTIn this work, the applicability of 12 solar radiation (RS) estimation models and their impacts on daily reference evapotranspiration (ETo) estimates using the Penman‐Monteith FAO-56 (PMF-56) method were tested under cool arid and semi-arid conditions in Iran. The results indicated that the average increase in accuracy of the ETo estimates by the calibrated RS models, quantified by the decrease in RMSE, was 2.8% and 6.4% for semi-arid and arid climates, respectively. Mean daily deviations in the estimated ETo by the calibrated RS equations in semi-arid climates varied from ?0.283?mm/d-1 for the Glover‐McCulloch model to 0.080?mm/d for the El-Sebaii model, with an average of ?0.109?mm/d-1, and in arid climates, they ranged from ?0.522?mm/d-1 for the Samani model to 0.668?mm/d for the El-Sebaii model, with an average of 0.125?mm/d-1.
Editor D. Koutsyiannis; Associate editor Not assigned 相似文献
18.
Shang Chen Wenzhe Feng Liang He Wei Xiao Hao Feng Qiang Yu Jiandong Liu Jianqiang He 《水文研究》2024,38(2):e15091
Accurately estimated reference evapotranspiration (ET0) is essential to regional water management. The FAO recommends coupling the Penman–Monteith (P-M) model with the Ångström–Prescott (A-P) formula as the standard method for ET0 estimation with missing Rs measurements. However, its application is usually restricted by the two fundamental coefficients (a and b) of the A-P formula. This paper proposes a new method for estimating ET0 with missing Rs by combining machine learning with physical-based P-M models (PM-ET0). The benchmark values of the A-P coefficients were first determined at the daily, monthly, and yearly scales, and further evaluated in Rs and ET0 estimates at 80 national Rs measuring stations. Then, three empirical models and four machine-learning methods were evaluated in estimating the A-P coefficients. Machine learning methods were also used to estimate ET0 (ML-ET0) to compare with the PM-ET0. Finally, the optimal estimation method was used to estimate the A-P coefficients for the 839 regular weather stations for ET0 estimation without Rs measurement for China. The results demonstrated a descending trend for coefficient a from northwest to southeast China, with larger values in cold seasons. However, coefficient b showed the opposite distribution as the coefficient a. The FAO has recommended a larger a but a smaller b for southeast China, which produced the region's largest Rs and ET0 estimation errors. Additionally, the A-P coefficients calibrated at the daily scale obtained the best estimation accuracy for both Rs and ET0, and slightly outperformed the monthly and yearly coefficients without significant difference in most cases. The machine learning methods outperformed the empirical methods for estimating the A-P coefficients, especially for the sites with extreme values. Further, ML-ET0 outperformed the PM-ET0 with yearly A-P coefficients but underperformed those with daily and monthly ones. This study indicates an exciting potential for combining machine learning with physical models for estimating ET0. However, we found that using the A-P coefficients with finer time scales is unnecessary to deal with the missing Rs measurements. 相似文献
19.
AbstractStatistically significant FAO-56 Penman-Monteith (FAO-56 PM) and adjusted Hargreaves (AHARG) reference evapotranspiration (ET0) trends at monthly, seasonal and annual time scales were analysed by using linear regression, Mann-Kendall and Spearman’s Rho tests at the 1 and 5% significance levels. Meteorological data were used from 12 meteorological stations in Serbia, which has a humid climate, for the period 1980–2010. Web-based software for conducting the trend analyses was developed. All of the trends significant at the 1 and 5% significance levels were increasing. The FAO-56 PM ET0 trends were almost similar to the AHARG trends. On the seasonal time scale, for the majority of stations significant increasing trends occurred in summer, while no significant positive or negative trends were detected by the trend tests in autumn for the AHARG series. Moreover, 70% of the stations were characterized by significant increasing trends for both annual ET0 series. Editor Z.W. Kundzewicz; Associate editor S. GrimaldiCitation Gocic, M. and Trajkovic, S., 2013. Analysis of trends in reference evapotranspiration data in a humid climate. Hydrological Sciences Journal, 59 (1), 165–180. 相似文献
20.
Spatio‐temporal distribution of actual evapotranspiration in the Indus Basin Irrigation System 
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下载免费PDF全文 Strategic planning of optimal water use requires an accurate assessment of actual evapotranspiration (ETa) to understand the environmental and hydrological processes of the world's largest contiguous irrigation networks, including the Indus Basin Irrigation System (IBIS) in Pakistan. The Surface Energy Balance System (SEBS) has been used successfully for accurate estimations of ETa in different river basins throughout the world. In this study, we examined the application of SEBS using publically available remote sensing data to assess spatial variations in water consumption and to map water stress from daily to annual scales in the IBIS. Ground‐based ETa was calculated by the advection‐aridity method, from nine meteorological sites, and used to evaluate the intra‐annual seasonality in the hydrological year 2009–2010. In comparison with the advection‐aridity, SEBS computed daily ETa was slightly underestimated with a bias of ?0.15 mm day?1 during the kharif (wet; April–September) season, and it was overestimated with a bias of 0.23 mm day?1 in the rabi (dry; October–March) season. Monthly values of the ETa estimated by SEBS were significantly (P < 0.05) controlled by mean air temperature and rainfall, among other climatological variables (relative humidity, sunshine hours and wind speed). Because of the seasonal (kharif and rabi) differences in the water and energy budget in the huge canal command areas of the IBIS, ETa and rainfall were positively correlated in the kharif season and were negatively correlated during the rabi season. In addition, analysis of the evaporation process showed that mixed‐cropping and rice–wheat dominated areas had lower and higher water consumption rates, respectively, in comparison with other cropping systems in the basin. Basin areas under water stress were identified by means of spatial variations in the relative evapotranspiration, which had an average value of 0.59 and 0.42 during the kharif and the rabi seasons, respectively. The hydrological parameters used in this study provide useful information for understanding hydrological processes at different spatial and temporal scales. Results of this study further suggest that the SEBS is useful for evaluation of water resources in semi‐arid to arid regions over longer periods, if the data inputs are carefully handled. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献