首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 31 毫秒
1.
ABSTRACT

In 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   

2.
Groundwater is sensitive to the climate change and agricultural activities in arid and semi‐arid areas. Over the past several decades, human activities, such as groundwater extraction for irrigation, have resulted in aquifer overdraft and disrupted the natural equilibrium in these areas. Regional groundwater simulation is important to determine appropriate groundwater management policies, and numerical simulation has become the most popular method. However, most groundwater models were developed with static boundary conditions. In this research, the Minqin oasis, an arid region located in northwest China, was selected as the study area. An artificial neural network (ANN) was developed to simulate effects of weather conditions, agricultural activities and surface water on groundwater level in a dynamic boundary of the domain. Subsequently, a groundwater numerical model, named ANN‐FEFLOW model, was developed, with a dynamic boundary condition defined by the ANN model. The verifying results showed that the model has higher precision, with a root mean square error (RMSE) of 0·71 m, relative error (RE) of 17·96% and R2 of 0·84 relative to the great groundwater change. Furthermore, the groundwater model has higher precision than the conventional groundwater model with static boundary condition, particularly in the area near the dynamic boundary. This study demonstrated that dynamic boundaries can improve the precision of the regional groundwater model in an arid area and that ANN can provide higher accuracy prediction capability for groundwater levels with dynamic boundary. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

3.
Evaluating performances of four commonly used evaporation estimate methods, namely; Bowen ratio energy balance (BREB), mass transfer (MT), Priestley–Taylor (PT) and pan evaporation (PE), based on 4 years experimental data, the most effective and the reliable evaporation estimates model for the semi‐arid region of India has been derived. The various goodness‐of‐fit measures, such as; coefficient of determination (R2), index of agreement (D), root mean square error (RMSE), and relative bias (RB) have been chosen for the performance evaluation. Of these models, the PT model has been found most promising when the Bowen ratio, β is known a priori, and based on its limited data requirement. The responses of the BREB, the PT, and the PE models were found comparable to each other, while the response of the MT model differed to match with the responses of the other three models. The coefficients, β of the BREB, µ of the MT, α of the PT and KP of the PE model were estimated as 0·07, 2·35, 1·31 and 0·65, respectively. The PT model can successfully be extended for free water surface evaporation estimates in semi‐arid India. A linear regression model depicting relationship between daily air and water temperature has been developed using the observed water temperatures and the corresponding air temperatures. The model helped to generate unrecorded water temperatures for the corresponding ambient air temperatures. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

4.
M. Z. Iqbal 《水文研究》2008,22(23):4609-4619
Oxygen and deuterium isotopes in precipitation were analysed to define local isotopic trends in Iowa, US. The area is far inland from an oceanic source and the observed averages of δ18O and δ D are ? 6·43‰ and ? 41·35‰ for Ames, ? 7·53‰ and ? 51·33‰ for Cedar Falls, and ? 6·01‰ and ? 38·19‰ for Iowa City, respectively. Although these data generally follow global trends, they are different when compared to a semi‐arid mid‐continental location in North Platt, Nebraska. The local meteoric water lines of Iowa are δ D = 7·68 δ18O + 8·0 for Ames, δ D = 7·62 δ18O + 6·07 for Cedar Falls, and δ D = 7·78 δ18O + 8·61 for Iowa City. The current Iowa study compares well with a study conducted in Ames, Iowa, 10 years earlier. The differences between Iowa and Nebraska studies are attributed to a variable climate across the northern Great Plains ranging from sub‐humid in the east to semi‐arid in the west. Iowa being further east in the region is more strongly influenced by a moist sub‐humid to humid climate fed by the tropical air stream from the Gulf of Mexico. The average d‐excess values are 10·06‰ for Ames, 8·92‰ for Cedar Falls and 9·92‰ for Iowa City. Eighty seven percent of the samples are within the global d‐excess range of 0‰ and 20‰. The results are similar to previous studies, including those by National Atmospheric Deposition Programs and International Atomic Energy Agency. It appears that the impact of recycled water or secondary evaporation on δ18O values of area precipitation is minimal. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

5.
Tropospheric (ground‐level) ozone has adverse effects on human health and environment. In this study, next day's maximum 1‐h average ozone concentrations in Istanbul were predicted using multi‐layer perceptron (MLP) type artificial neural networks (ANNs). Nine meteorological parameters and nine air pollutant concentrations were utilized as inputs. The total 578 datasets were divided into three groups: training, cross‐validation, and testing. When all the 18 inputs were used, the best performance was obtained with a network containing one hidden layer with 24 neurons. The transfer function was hyperbolic tangent. The correlation coefficient (R), mean absolute error (MAE), root mean squared error (RMSE), and index of agreement or Willmott's Index (d2) for the testing data were 0.90, 8.78 µg/m3, 11.15 µg/m3, and 0.95, respectively. Sensitivity analysis has indicated that the persistence information (current day's maximum and average ozone concentrations), NO concentration, average temperature, PM10, maximum temperature, sunshine time, wind direction, and solar radiation were the most important input parameters. The values of R, MAE, RMSE, and d2 did not change considerably for the MLP model using only these nine inputs. The performances of the MLP models were compared with those of regression models (i.e., multiple linear regression and multiple non‐linear regression). It has been found that there was no significant difference between the ANN and regression modeling techniques for the forecasting of ozone concentrations in Istanbul.  相似文献   

6.
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   

7.
Analysis of spatial and temporal variations of reference evapotranspiration (ETo) is important in arid and semi‐arid regions where water resources are limited. The main aim of this study was to analyse the spatial distribution and the annual, seasonal and monthly trends of the Penman–Monteith ETo for 21 stations in the arid and semi‐arid regions of Iran. Three statistical tests the Mann‐Kendall, Sen's slope estimator and linear regression were used for the analysis. The analysis revealed that ETo increased from January to July and deceased from July to December at almost all stations. Additionally, higher annual ETo values were found in the southeast of the study region and lower values in the northwest of the region. Although the results showed both positive and negative trends in annual ETo series, ETo generally increased, significantly so in six (~30%) of the stations. Analysis of the impacts of meteorological variables on the temporal trends of ETo indicated that the increasing trend of ETo was most likely due to a significant increase in minimum air temperature, while decreasing trend of ETo was mainly caused by a significant decrease in wind speed. At the sites where increasing ETo trends were statistically significant, the rate of increase varied from (+)8·36 mm/year at Mashhad station to (+)31·68 mm/year at Iranshahr station. On average, an increasing trend of (+)4·42 mm/year was obtained for the whole study area during the last four decades. Seasonal and monthly ETo have also tended to increase at the majority of the stations. The greatest numbers of significant trends were observed in winter on the seasonal time‐scale and in September on the monthly time‐scale. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

8.
Fish habitat and aquatic life in rivers are highly dependent on water temperature. Therefore, it is important to understand andto be able to predict river water temperatures using models. Such models can increase our knowledge of river thermal regimes as well as provide tools for environmental impact assessments. In this study, artificial neural networks (ANNs) will be used to develop models for predicting both the mean and maximum daily water temperature. The study was conducted within Catamaran Brook, a small drainage basin tributary to the Miramichi River (New Brunswick, Canada). In total, eight ANN models were investigated using a variety of input parameters. Of these models, four predicted mean daily water temperature and four predicted maximum daily water temperature. The best model for mean daily temperature had eight input parameters: minimum, maximum and mean air temperatures of the current day and those of the preceding day, the day of year and the water level. This model had an overall root‐mean‐square error (RMSE) of 0·96 °C, a bias of 0·26 °C and a coefficient of determination R2 = 0·971. The model that best predicted maximum daily water temperature was similar to the first model but excluded mean daily air temperature. Good results were obtained for maximum water temperatures with an overall RMSE of 1·18 °C, a bias of 0·15 °C and R2 = 0·961. The results of ANN models were similar to and/or better than those observed from the literature. The advantages of artificial neural networks models in modelling river water temperature lie in their simplicity of use, their low data requirement and their good performance, as well as their flexibility in allowing many input and output parameters. Copyright © 2008 Crown in the right of Canada and John Wiley & Sons, Ltd.  相似文献   

9.
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   

10.
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   

11.
Climatic variations over Eastern Asia, including the Tibetan Plateau, were analysed using meteorological data for 32 points in the period 1971 to 2000. Changes in heat and water balances were examined using potential evaporation EP, and a wetness index WI, as suggested by Kondo and Xu ( 1997a,b ). Climate zones, including the humid, semi‐humid, semi‐arid and arid climate types, in Eastern Asia identified by the wetness index matched the vegetation distribution. Average monthly temperatures increased over the 30 years, with the sharpest increase in February. In general, temperature increases were larger in the north than in the south. Air temperature increased by more than 0·05 K yr−1 in northern China. The data showed that diurnal temperature ranges have decreased in recent years. From the Tibetan Plateau, through central China, to southern northeast China, there has been an increase in potential evaporation and pan evaporation, which may be related to both higher temperatures and a lack of surface water. Increasing long‐wave radiation flux is apparent in every month and in the interannual trends. This is in contrast to the solar radiation flux. On the other hand, trends for relative humidity and cloud cover were negative, but positive for water vapour pressure. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

12.
In the present study, the trends in the reference evapotranspiration (ETO) estimated through the Penman‐Monteith method were investigated over the humid region of northeast (NE) India by using the Mann‐Kendall (MK) test after removing the effect of significant lag‐1 serial correlation from the time series of ETO by pre‐whitening. During the last 22 years, ETO has been found to decrease significantly at annual and seasonal time scales for 6 sites in NE India and NE India as a whole. The seasonal decreases in ETO have, however, been more significant in the pre‐monsoon season, indicating the presence of an element of a seasonal cycle. The decreases in ETO are mainly attributed to the net radiation and wind speed, which are also corroborated by the observed trends in these two parameters at almost all the times scales over most of the sites in NE India. The steady decrease in wind speed and decline in net radiation not only balanced the impact of the temperature increases on ETO, but may have actually caused the decreases in ETO over the humid region of northeast India. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

13.
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   

14.
Different satellite-based radiation (Makkink) and temperature (Hargreaves-Samani, Penman-Monteith temperature, PMT) reference evapotranspiration (ETo) models were compared with the FAO56-PM method over the Cauvery basin, India. Maximum air temperature (Tmax) required in the ETo models was estimated using the temperature–vegetation index (TVX) and an advanced statistical approach (ASA), and evaluated with observed Tmax obtained from automatic weather stations. Minimum air temperature (Tmin) was estimated using ASA. Land surface temperature was employed in the ETo models in place of air temperature (Ta) to check the potency of its applicability. The results suggest that the PMT model with Ta as input performed better than the other ETo models, with correlation coefficient (r), averaged root mean square error (RMSE) and mean bias error (MBE) of 0.77, 0.80 mm d?1 and ?0.69 for all land cover classes. The ASA yielded better Tmax and Tmin values (r and RMSE of 0.87 and 2.17°C, and 0.87 and 2.27°C, respectively).  相似文献   

15.
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   

16.
F. Ashkar 《水文科学杂志》2013,58(6):1092-1106
Abstract

The potential is investigated of the generalized regression neural networks (GRNN) technique in modelling of reference evapotranspiration (ET0) obtained using the FAO Penman-Monteith (PM) equation. Various combinations of daily climatic data, namely solar radiation, air temperature, relative humidity and wind speed, are used as inputs to the ANN so as to evaluate the degree of effect of each of these variables on ET0. In the first part of the study, a comparison is made between the estimates provided by the GRNN and those obtained by the Penman, Hargreaves and Ritchie methods as implemented by the California Irrigation Management System (CIMIS). The empirical models were calibrated using the standard FAO PM ET0 values. The GRNN estimates are also compared with those of the calibrated models. Mean square error, mean absolute error and determination coefficient statistics are used as comparison criteria for the evaluation of the model performances. The GRNN technique (GRNN 1) whose inputs are solar radiation, air temperature, relative humidity and wind speed, gave mean square errors of 0.058 and 0.032 mm2 day?2, mean absolute errors of 0.184 and 0.127 mm day?1, and determination coefficients of 0.985 and 0.986 for the Pomona and Santa Monica stations (Los Angeles, USA), respectively. Based on the comparisons, it was found that the GRNN 1 model could be employed successfully in modelling the ET0 process. The second part of the study investigates the potential of the GRNN and the empirical methods in ET0 estimation using the nearby station data. Among the models, the calibrated Hargreaves was found to perform better than the others.  相似文献   

17.
Evaporation dominates the water balance in arid and semi‐arid areas. The estimation of evaporation by land‐cover type is important for proper management of scarce water resources. Here, we present a method to assess spatial and temporal patterns of actual evaporation by relating water balance evaporation estimates to satellite‐derived radiometric surface temperature. The method is applied to a heterogeneous landscape in the Krishna River basin in south India using 10‐day composites of NOAA advanced very high‐resolution radiometer satellite imagery. The surface temperature predicts the difference between reference evaporation and modelled actual evaporation well in the four catchments (r2 = 0·85 to r2 = 0·88). Spatial and temporal variations in evaporation are linked to vegetation type and irrigation. During the monsoon season (June–September), evaporation occurs quite uniformly over the case‐study area (1·7–2·1 mm day?1), since precipitation is in excess of soil moisture holding capacity, but it is higher in irrigated areas (2·2–2·7 mm day?1). In the post‐monsoon season (December–March) evaporation is highest in irrigated areas (2·4 mm day?1). A seemingly reasonable estimate of temporal and spatial patterns of evaporation can be made without the use of more complex and data‐intensive methods; the method also constrains satellite estimates of evaporation by the annual water balance, thereby assuring accuracy at the seasonal and annual time‐scales. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

18.
Shallow groundwater plays a key role in agro‐hydrological processes of arid areas. Groundwater often supplies a necessary part of the water requirement of crops and surrounding native vegetation, such as groundwater‐dependent ecosystems. However, the impact of water‐saving irrigation on cropland water balance, such as the contribution of shallow groundwater to field evapotranspiration, requires further investigation. Increased understanding of quantitative evaluation of field‐scale water productivity under different irrigation methods aids policy and decision‐making. In this study, high‐resolution water table depth and soil water content in field maize were monitored under conditions of flood irrigation (FI) and drip irrigation (DI), respectively. Groundwater evapotranspiration (ETg) was estimated by the combination of the water table fluctuation method and an empirical groundwater–soil–atmosphere continuum model. The results indicate that daily ETg at different growth stages varies under the two irrigation methods. Between two consecutive irrigation events of the FI site, daily ETg rate increases from zero to greater than that of the DI site. Maize under DI steadily consumes more groundwater than FI, accounting for 16.4% and 14.5% of ETa, respectively. Overall, FI recharges groundwater, whereas DI extracts water from shallow groundwater. The yield under DI increases compared with that under FI, with less ETa (526 mm) compared with FI (578 mm), and irrigation water productivity improves from 3.51 kg m?3 (FI) to 4.58 kg m?3 (DI) through reducing deep drainage and soil evaporation by DI. These results highlight the critical role of irrigation method and groundwater on crop water consumption and productivity. This study provides important information to aid the development of agricultural irrigation schemes in arid areas with shallow groundwater.  相似文献   

19.
Estimation of reference evapotranspiration (ET0) in urban areas is challenging but essential in arid urban climates. To evaluate ET0 in an urban environment and non-urban areas, air temperature and relative humidity were measured at five different sites across the arid city of Isfahan, Iran, over 4 years. Wind speed and sunshine hours were obtained from an urban surrounding weather station over the same period and used to estimate ET0. Calculated ET0 was compared with satellite-based ET0 retrieved from the MOD16A2 PET product. Although MODIS PET was strongly correlated with the Valiantzas equation, it overestimated ET0 and showed average accuracy (r = 0.93–0.94, RMSE = 1.18–1.28 mm/day, MBE = 0.73–0.84 mm/day). The highest ET0 differences between an urban green space and a non-urban area were 1.1 and 0.87 mm/day, which were estimated by ground measurements and MODIS PET, respectively. The sensitivity of ET0 to wind speed and sunshine hours indicated a significant effect on cumulative ET0 at urban sites compared to the non-urban site, which has a considerable impact on the amount of irrigation required in those areas. Although MODIS PET requires improvement to accurately reflect field level microclimate conditions affecting ET0, it is beneficial to hydrological applications and water resource managers especially in areas where data is limited. In addition, our results indicated that using limited data methods or meteorological data from regional weather stations, leads to incorrect estimation of ET0 in urban areas. Therefore, decision-makers and urban planners should consider the importance of precisely estimating ET0 to optimize management of urban green space irrigation, especially in arid and semi-arid climates such as the city of Isfahan.  相似文献   

20.
Chaolei Zheng  Quan Wang 《水文研究》2014,28(25):6124-6134
Spatial and temporal variations of reference evapotranspiration (ET0) are useful for regional agricultural and water resources management as well as required in most distributed hydrological modelling. In the current study, the Penman–Monteith estimated ET0 in the arid land of Northwestern China has been explicitly explored using the Mann–Kendall test. Most stations in the study region exhibited significant decreasing trend of ET0 (P < 0.05) with only few occasions showing significant increasing trend (P < 0.05), despite the increase of temperature in the entire region. Analysis results revealed that the overall decreasing wind speed contributed most to the decreasing trend of ET0, whereas the contributions of relative humidity and sunshine duration were limited. Temperature played the second important role on determining ET0 trend, but its effect was opposite to that of wind speed and was largely offset by the decreasing wind speed. Furthermore, sensitivity analysis suggested the impact of temperature to ET0 was much larger than formerly reported if its effect on saturated vapour deficit was taken into account. The results obtained in the current study will help for better understanding of the effects of climate changes to water resource management in the arid land of northwest China. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号