The temporal trends of reference evapotranspiration and its sensitivity to key meteorological variables in the Yellow River Basin,China

The temporal trends of reference evapotranspiration (ET_ref) reflect the combined effects of radiometric and aerodynamic variables, such as global solar radiation (R_s), wind speed, relative humidity and air temperature. The temporal trends of annual ET_ref 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 ET_ref were detected using the detrended method and then sensitivity coefficients of ET_ref to meteorological variables were determined. For ET_ref, 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 ET_ref in the upper, middle and whole basins. For the whole basin, the increasing trend of ET_ref 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 R_s and wind speed reduced ET_ref. The spatial distribution of sensitivity coefficients addressed that the sensitive regions for ET_ref response to the changes of the four meteorological variables are different in the YRB. The sensitive region lay in the upper basin for R_s, 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, R_s was the most sensitive variable for ET_ref, followed by relative humidity, air temperature and wind speed in the basin scale. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatiotemporal variations and abrupt changes of potential evapotranspiration and its sensitivity to key meteorological variables in the Wei River basin,China

Evapotranspiration is an important component of hydrological cycle and a key input to hydrological models. Therefore, analysis of the spatiotemporal variation of potential evapotranspiration (PET) will help a better understanding of climate change and its effect on hydrological cycle and water resources. In this study, the Penman–Monteith method was used to estimate PET in the Wei River basin (WRB) in China based on daily data at 21 meteorological stations during 1959–2008. Spatial distribution and temporal trends of annual and seasonal PET were analysed by using the Spline interpolation method and the Mann–Kendall test method. Abrupt changes were detected by using the Pettitt test method. In order to explore the contribution of key meteorological variables to the variation of PET, the sensitivity coefficients method was employed in this study. The results showed that: (1) mean annual and seasonal PET in the WRB was generally decreasing from northeast to southwest. Summer and spring made the major contributions to the annual values; (2) annual and seasonal PET series in most part of the WRB exhibited increasing trends; (3) abrupt changes appeared in 1993 for annual and spring PET series for the entire basin, while summer value series was detected in the late 1970s. (4) Relative humidity was the most sensitive variable for PET in general for the WRB, followed by wind speed, air temperature and solar radiation. In the headwater and outlet of the WRB, relative humidity and air temperature were the most sensitive variables to PET, while relative humidity and wind speed were more influential in most part of the middle‐lower region. Copyright © 2011 John Wiley & Sons, Ltd.     

Hydrological responses to climate shifts for a minimally disturbed mountainous watershed in northwestern China

Much attention has been focused on investigating the effects of precipitation and temperature changes on runoff; however, the influence of wind speed, relative humidity and total solar radiation on hydrological components needs to be studied further. Hydrological responses to climate variations in a minimally disturbed mountainous watershed in the period 1971–2012 are identified and evaluated by statistical analysis and hydrological simulation. The results indicate that the impact of climate component changes on the hydrological process cannot be discounted. The temperature and relative humidity exhibit significant upward trends, while the wind speed exhibits a clear downward trend. The potential and actual evapotranspiration dramatically increased, but the observed pan evaporation substantially decreased. The surface water, soil water, baseflow and water yield are positively correlated with precipitation and relative humidity but negatively correlated with the temperature, wind speed and solar radiation.     

Spatiotemporal variation and driving forces of reference evapotranspiration in Jing River Basin,northwest China

Evapotranspiration is an important component of the hydrological cycle, which integrates atmospheric demands and surface conditions. Research on spatial and temporal variations of reference evapotranspiration (ET_o) enables understanding of climate change and its effects on hydrological processes and water resources. In this study, ET_o was estimated by the FAO‐56 Penman–Monteith method in the Jing River Basin in China, based on daily data from 37 meteorological stations from 1960 to 2005. ET_o trends were detected by the Mann–Kendall test in annual, seasonal, and monthly timescales. Sensitivity coefficients were used to examine the contribution of important meteorological variables to ET_o. The influence of agricultural activities, especially irrigation on ET_o was also analyzed. We found that ET_o showed a decreasing trend in most of the basin in all seasons, except for autumn, which showed an increasing trend. Mean maximum temperature was generally the most sensitive parameter for ET_o, followed by relative humidity, solar radiation, mean minimum temperature, and wind speed. Wind speed was the most dominant factor for the declining trend in ET_o. The more significant decrease in ET_o for agricultural and irrigation stations was mainly because of the more significant decrease in wind speed and sunshine hours, a mitigation in climate warming, and more significant increase in relative humidity compared with natural stations and non‐irrigation stations. Changes in ET_o and the sensitivity coefficient of meteorological variables in relation to ET_o were also affected by topography. Better understanding of ET_o response to climate change will enable efficient use of agricultural production and water resources, which could improve the ecological environment in Jing River Basin. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantifying the impact of climate variables on reference evapotranspiration in Pearl River Basin,China

ABSTRACT

The impact of climate variables on monthly reference evapotranspiration (ET_o) is a critical issue in water resources management and irrigation planning. The spatio-temporal contribution of climate variables to ET_o in the Pearl River Basin (PRB), China, from 1960 to 2016 were calculated based on sensitivity and relative change of each climatic variable. The results show that annual ET_o total decreased by 1.64% and diminished in magnitude from the southeast to the northwest. Sunshine duration, wind speed and relative humidity decreased by 15.5%, 7.4%, and 4.0%, respectively, while average temperature increased by 4.25%. The ET_o showed a positive sensitivity to all variables except relative humidity, which showed a negative sensitivity. Sunshine duration had the highest contribution of ?4.26%, and the overall decrease in ET_o was mainly caused by the declines in sunshine duration and wind speed, which offset the positive impact of rises in average temperature and reduction in relative humidity.     

Projection of glacier runoff in Yarkant River basin and Beida River basin,Western China

Potential changes in glacier area, mass balance and runoff in the Yarkant River Basin (YRB) and Beida River Basin (BRB) are projected for the period from 2011 to 2050 employing the modified monthly degree‐day model forced by climate change projection. Future monthly air temperature and precipitation were derived from the simple average of 17, 16 and 17 General Circulation Model (GCM) projections following the A1B, A2 and B1 scenarios, respectively. These data were downscaled to each station employing the Delta method, which computes differences between current and future GCM simulations and adds these changes to observed time series. Model parameters calibrated with observations or results published in the literature between 1961 and 2006 were kept unchanged. Annual glacier runoff in YRB is projected to increase until 2050, and the total runoff over glacier area in 1970 is projected to increase by about 13%–35% during 2011–2050 relative to the average during 1961–2006. Annual glacier runoff and the total runoff over glacier area in 1970 in BRB is projected to increase initially and then to reach a tipping point during 2011–2030. There are prominent increases in summer, but only small increase in May and October of glacier runoff in YRB, and significant increases during late spring and early summer and significant decreases in July and late summer of glacier runoff in BRB. This study highlights the great differences among basins in their response to future climate warming. The specific runoff from areas exposed after glacier retreat relative to 1970 is projected to general increasing, which must be considered when evaluating the potential change of glacier runoff. Copyright © 2011 John Wiley & Sons, Ltd.     

M5 model tree based modelling of reference evapotranspiration

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.     

Spatial distribution and temporal variation of reference evapotranspiration during 1961–2006 in the Yellow River Basin,China

Abstract

To explore the spatial and temporal variations of the reference evapotranspiration (ET_ref) is helpful to understand the response of hydrological processes to climate changes. In this study, ET_ref was calculated by the Penman-Monteith method (P-M method) using air temperature, wind speed, relative humidity and sunshine hours at 89 meteorological stations during 1961–2006 in the Yellow River Basin (YRB), China. The spatial distribution and temporal variations of ET_ref were explored by means of the kriging method, the Mann-Kendall (M-K) method and the linear regression model, and the causes for the variations discussed. The contribution of main meteorological variables to the variations of ET_ref was explored. From the results we found that: (1) the spatial distributions of ET_ref display seasonal variation, with similar spatial patterns in spring, summer and autumn; (2) temporal trends for ET_ref showed large variation in the upper, middle and lower regions of the basin, most of the significant trends (P?=?0.05) were detected in the middle and lower regions, and, in particular, the upward and downward trends were mainly detected in the middle region and lower region of the basin, respectively; and (3) sensitivity analysis identified the most sensitive variable for ET_ref as relative humidity, followed by air temperature, sunshine hours and wind speed at the basin scale.

Citation Yang, Zhifeng, Liu, Qiang & Cui, Baoshan (2011) Spatial distribution and temporal variation of reference evapotranspiration during 1961–2006 in the Yellow River Basin, China. Hydrol. Sci. J. 56(6), 1015–1026.     

Choice between competitive pairs of frequency models for use in hydrology: a review and some new results

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.     

Micrometeorological measurements in Nigeria during the total solar eclipse of 29 March, 2006

The total solar eclipse of 29 March, 2006 which was visible at Ibadan (7.55°N, 4.56°E), south-western Nigeria was utilized to document atmospheric surface-layer effects of the eclipse for the first time in Nigeria. The meteorological parameters measured are global radiation, net radiation, wind speed (at different heights), atmospheric pressure and soil temperature (5, 10 and 30 cm), moisture and heat flux and rainfall. The results revealed remarkable dynamic atmospheric effects. The observations showed that the incoming solar radiation, net radiation and air temperature were significantly affected.There was an upsurge of wind speed just before the first contact of the eclipse followed by a very sharp decrease in wind speed due to the cooling and stabilization of the atmospheric boundary layer. The atmospheric pressure lags the eclipse maximum by 1 h 30 min, while the soil temperature at 5 and 10 cm remain constant during the maximum phase of the eclipse.     

Changes to flow regime on the Niger River at Koulikoro under a changing climate

Abstract

A significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). A t-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level.     

A simple method to combine snow height and meteorological observations to estimate winter precipitation at sub-daily resolution

ABSTRACT

Measuring winter solid and liquid precipitation with high temporal resolution in remote or higher elevation regions is a challenging task because of undercatch and power supply issues. However, the number of micro-meteorological stations and ultrasonic height sensors in mountain regions is steadily increasing. To gain more benefit from such stations, a new simple approach for EStimating SOlid and LIquid Precipitation (ESOLIP) is presented. The method consists of three main steps: (1) definition of precipitation events using micro-meteorological data, (2) quantification of solid and liquid precipitation using wet-bulb temperature and filtered snow height and (3) calculation of fresh snow density. ESOLIP performance was validated using data from a heated rain gauge, snow pillow and daily manual observations both for single precipitation events and over three winter seasons. Results proved ESOLIP as an effective approach for precipitation quantification, where snow height observations and basic meteorological measurements (air temperature, solar radiation, wind speed, relative humidity), but no reliable rain gauges are available.     

An explicit neural network formulation for evapotranspiration

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.     

Deep echo state network: a novel machine learning approach to model dew point temperature using meteorological variables

ABSTRACT

The potential of different models – deep echo state network (DeepESN), extreme learning machine (ELM), extra tree (ET), and regression tree (RT) – in estimating dew point temperature by using meteorological variables is investigated. The variables consist of daily records of average air temperature, atmospheric pressure, relative humidity, wind speed, solar radiation, and dew point temperature (T_dew) from Seoul and Incheon stations, Republic of Korea. Evaluation of the model performance shows that the models with five and three-input variables yielded better accuracy than the other models in these two stations, respectively. In terms of root-mean-square error, there was significant increase in accuracy when using the DeepESN model compared to the ELM (18%), ET (58%), and RT (64%) models at Seoul station and the ELM (12%), ET (23%), and RT (49%) models at Incheon. The results show that the proposed DeepESN model performed better than the other models in forecasting T_dew values.     

Diurnal and seasonal variations of sap flow of Caragana korshinskii in the arid desert region of north‐west China

The aim of this study was to obtain the diurnal and seasonal changes of trunk sap flow in desert‐living Caragana korshinskii so as to understand its water requirement and ecological significance. The experiment was carried out with 15‐year old Caragana korshinskii grown in north‐west China under natural conditions. Heat pulse sensors based on the heat compensation theory were applied to measure the trunk sap flow, and soil moisture content at 0–300 cm layer, using tube‐type time domain reflectometry (Tube‐TDR). The solar radiation, the maximum and minimum air temperatures, relative humidity, wind speed, wind direction and precipitation were measured at a standard automatic weather station. The diurnal and seasonal variations of sap flow rate, the sap velocity at different positions in the trunk and the sap flow rate under different weather conditions were analysed. And the correlation between the sap flow rate and the meteorological factors was also analysed. Results showed that the trunk sap flow varied regularly in the diurnal term and the sap flow velocity decreased with the probe‐inserted depth into the sapwood. Magnitude of sap flow changed considerably between sunny and rainy days. The order of the main meteorological factors affecting the sap flow rate of Caragana korshinskii shrubs were: vapour pressure deficit > solar radiation > air temperature > wind speed. The close correlation between daily sap flow rate and meteorological factors in the whole growing season can be used to estimate the transpiration of Caragana korshinskii. Copyright © 2007 John Wiley & Sons, Ltd.     

长江上游区域蒸发皿蒸发量变化及其对水分循环的影响

利用长江上游最近30年(66个测站)蒸发皿蒸发量和最近50年(90个测站)的7种气象要素,分析了蒸发皿蒸发量的区域变化趋势和影响蒸发皿蒸发量变化的因素;针对7个水文站的年径流量变化,探讨了蒸发皿蒸发量变化后对水分循环的影响.结果表明,长江上游蒸发皿蒸发量的变化可以划分为三个分区,研究区域东西两侧(青藏高原和大巴山一带)为显著减少区,分别命名为RⅠ和RⅡ,中间(云贵高原北部到黄土高原南缘以及由二者包围的四川盆地一带)为显著增大区,命名为RⅢ区.影响区域蒸发皿蒸发量变化的原因各有不同,青藏高原一带(RⅠ区)蒸发皿蒸发量减少的原因可归结于太阳辐射强度和风动力扰动减弱所致.大巴山一带(RⅡ区)减少原因是太阳辐射强度、风动力扰动强度、湿度条件都在显著下降所引起的.云贵高原到四川盆地一带(RⅢ区)蒸发皿蒸发量增加是环境气温强烈升高,导致其上空大气水汽含量显著减少,大气很干燥,引发蒸发过程加强所致.蒸发皿蒸发量发生变化的直接后果就是导致水分循环强弱发生变化,对于RⅠ区,尽管蒸发皿蒸发量减少,由于降水量和径流量增加的作用,这一区域的水分循环有所加强.在RⅡ区,降水量、径流量和蒸发量都在减少,因此RⅡ区水分循环显著减弱.在RⅢ区,降水量和径流量同时减少,而蒸发量增大,水量消耗增大,因此RⅢ区水分循环有减弱趋势.     

长江上游区域蒸发皿蒸发量变化及其对水分循环的影响

利用长江上游最近30年(66个测站)蒸发皿蒸发量和最近50年(90个测站)的7种气象要素,分析了蒸发皿蒸发量的区域变化趋势和影响蒸发皿蒸发量变化的因素;针对7个水文站的年径流量变化,探讨了蒸发皿蒸发量变化后对水分循环的影响.结果表明,长江上游蒸发皿蒸发量的变化可以划分为三个分区,研究区域东西两侧(青藏高原和大巴山一带)为显著减少区,分别命名为RⅠ和RⅡ,中间(云贵高原北部到黄土高原南缘以及由二者包围的四川盆地一带)为显著增大区,命名为RⅢ区.影响区域蒸发皿蒸发量变化的原因各有不同,青藏高原一带(RⅠ区)蒸发皿蒸发量减少的原因可归结于太阳辐射强度和风动力扰动减弱所致.大巴山一带(RⅡ区)减少原因是太阳辐射强度、风动力扰动强度、湿度条件都在显著下降所引起的.云贵高原到四川盆地一带(RⅢ区)蒸发皿蒸发量增加是环境气温强烈升高,导致其上空大气水汽含量显著减少,大气很干燥,引发蒸发过程加强所致.蒸发皿蒸发量发生变化的直接后果就是导致水分循环强弱发生变化,对于RⅠ区,尽管蒸发皿蒸发量减少,由于降水量和径流量增加的作用,这一区域的水分循环有所加强.在RⅡ区,降水量、径流量和蒸发量都在减少,因此RⅡ区水分循环显著减弱.在RⅢ区,降水量和径流量同时减少,而蒸发量增大,水量消耗增大,因此RⅢ区水分循环有减弱趋势.     

Long‐term trend analysis for major climate variables in the Yellow River basin*

Some previous studies have shown that drying‐up of the lower Yellow River resulted from decreasing precipitation and excessive industrial and agricultural consumption of water from the middle and downstream regions of the Yellow River. On the basis of average air temperature, precipitation, and pan evaporation data from nearly 80 gauging stations in the Yellow River basin, the monotonic trends of major climate variables over the past several decades are analysed. The analysis was mainly made for 12 months and the annual means. The isograms for annual and typical months are given in the paper. The result shows that the average temperature in the study area exhibits an increasing trend, mainly because of the increase of temperature in December, January and February. The largest trend is shown in December and the smallest is in August. There are 65 of 77 stations exhibiting a downward trend for annual precipitation. In all seasons except summer, there is a similar trend in the upstream region of the Yellow River, south of latitude 35°N. It is interesting to note that the pan evaporation has decreased in most areas of the Yellow River basin during the past several decades. April and July showed the greatest magnitude of slope, and the area from Sanmenxia to Huayuankou as well as the Yiluo River basin exhibited the strongest declining trend. The conclusion is that the decreasing pan evaporation results from complex changes of air temperature, relative humidity, solar radiation, and wind speed, and both climate change and human activities have affected the flow regime of the Yellow River during the past several decades. Copyright © 2007 John Wiley & Sons, Ltd.     

Long‐term variations and temporal scaling of hydroclimatic time series with focus on the German part of the Elbe River Basin

Long‐term variations and temporal scaling of mean monthly time series of river flow, precipitation, temperature, relative humidity, air pressure, duration of bright sunshine, degree of cloud cover, short wave radiation, wind speed and potential evaporation within or in vicinity of the German part of the Elbe River Basin are analyzed. Statistically significant correlations between the 2–15 year scale‐averaged wavelet spectra of the hydroclimatic variables and the North Atlantic Oscillation‐ and Arctic Oscillation index are found which suggests that such long‐term patterns in hydroclimatic time series are externally forced. The Hurst parameter estimates (H) based on the Detrended Fluctuation Analysis (DFA) indicate persistence for discharge, precipitation, wind speed, air pressure and the degree of cloud cover, all having an annual cycle and a broad low‐frequency distribution. Also, DFA H parameter estimates are higher for discharge than for precipitation. The major long‐term quasi‐periodic variability modes of precipitation detected using Singular Spectrum Analysis coincide with those detected in the discharge time series. Upon subtraction of these low‐frequency quasi‐periodic modes, the DFA H parameter estimates suggest absence of the persistence for both precipitation and discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

Evapotranspiration modelling using support vector machines / Modélisation de l'évapotranspiration à l'aide de ‘support vector machines’

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.