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.     

Comparison of the Penman‐Monteith method and regional calibration of the Hargreaves equation for actual evapotranspiration using SWAT-simulated results in the Seolma-cheon basin,South Korea

ABSTRACT

The Hargreaves method provides reference evapotranspiration (ET_o) 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 ET_o 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 (K_ET) 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     

Spatial distribution and temporal variation of reference evapotranspiration in arid and semi‐arid regions of Iran

Analysis of spatial and temporal variations of reference evapotranspiration (ET_o) 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 ET_o 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 ET_o increased from January to July and deceased from July to December at almost all stations. Additionally, higher annual ET_o 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 ET_o series, ET_o generally increased, significantly so in six (～30%) of the stations. Analysis of the impacts of meteorological variables on the temporal trends of ET_o indicated that the increasing trend of ET_o was most likely due to a significant increase in minimum air temperature, while decreasing trend of ET_o was mainly caused by a significant decrease in wind speed. At the sites where increasing ET_o 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 ET_o 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.     

Seasonal climate patterns and their influence on calibration of the Hargreaves-Samani equation

Abstract

Annual patterns in climate parameters were studied to evaluate how these influence the quality of reference evapotranspiration (ETo) estimates obtained from the Hargreaves-Samani (HS) equation, since the method only uses the measured temperature directly. The work evaluates how these patterns can be used to improve the HS ETo estimates. Ten-year moving averages from a set of California Irrigation Management Information System (CIMIS) stations were used to evaluate the relationships between solar radiation (R_s), temperature (T) and ETo. The results indicate that T treads behind solar radiation and its value peaks some 25 days later. Thus, the main irrigation season in the Mediterranean climate (1 May–30 September) can be divided into three phases: increasing R_s and T; decreasing R_s with increasing T; and decreasing R_s and T. Non-univocal annual cycles were observed between R_s and T, ETo and R_s, and ETo and T. These annual patterns result in important seasonal changes in the ratio between the HS and Penman-Monteith (FAO PM) ETo estimates. The changes are particularly important during the irrigation season, where the FAO PM initially calculates greater ETo values than the HS methodology, and from the end of May to early September, where the HS equation overestimates the ETo values (by 17 mm, or 3%). These patterns obtained from 2000–2009 data were used to calibrate and improve HS ETo estimates at new sites for the 2010–2011 period. Calibration based on the proposed seasonal region-wide FAO PM/HS ETo ratios improved both the bias (decreased from 0.40 to 0.36 mm d^-1) and r² (increased from 0.67 to 0.87) of the ETo estimates for the irrigation season. The proposed methodology can be easily applied to other regions, even when the existing weather stations are sparse.

Editor Z.W. Kundzewicz     

Evaluation of actual evapotranspiration measured by large-scale weighing lysimeters in a humid alpine meadow,northeastern Qinghai-Tibetan Plateau

The accurate estimation of evapotranspiration (ET) is essential for assessing water availability and requirements of regional-scale terrestrial ecosystems, and for understanding the hydrological cycle in alpine ecosystems. In this study, two large-scale weighing lysimeters were employed to estimate the magnitude and dynamics of actual evapotranspiration in a humid alpine Kobresia meadow from January 2018 to December 2019 on the northeastern Qinghai-Tibetan Plateau (QTP). The results showed that daily ET_a averaged 2.24 ± 0.10 mm day ⁻¹ throughout the study period, with values of 3.89 ± 0.14 and 0.81 ± 0.06 mm day⁻¹ during the growing season and non-growing season, respectively. The cumulative ET_a during the study period was 937.39 mm, exceeding precipitation (684.20 mm) received at the site during the same period by 37%, suggesting that almost all precipitation in the lysimeters was returned to the atmosphere by evapotranspiration. Furthermore, the cumulative ET_a (805.04 mm) was almost equal to the maximum potential evapotranspiration estimated by the FAO-56 reference evapotranspiration (ET₀) (801.94 mm) during the growing season, but the cumulative ET_a (132.25 mm) was 113.72% less than the minimum equilibrium ET_eq) (282.86 mm) during the non-growing season due to the limited surface moisture in frozen soil. The crop coefficient (K_c) also showed a distinct seasonal pattern, with a monthly average of 1.01 during the growing season. Structural equation model (SEM) and boosted regression tree (BRT) show that net radiation and air temperature were the most important factors affecting daily ET_a during the whole study period and growing season, but that non-growing season ET_a was dominated by soil water content and net radiation. The daily K_c was dominated by net radiation. Furthermore, both ET_a and K_c were also affected by aboveground biomass.     

Comparison of methods for applying the Priestley–Taylor equation at a regional scale

The scenario assumed for this study was that of a region with a complete or first‐order weather station surrounded by a network of second‐order stations, where only monthly air temperature data were available. The objective was to evaluate procedures to estimate the monthly α parameter of the Priestley–Taylor equation in the second‐order stations by adjusting and extrapolating α values determined at the first‐order station. These procedures were applied in two climatic zones of north‐east Spain with semi‐arid continental and semi‐arid Mediterranean climates, respectively. Procedure A assumed α to be constant over each zone for each month (direct extrapolation). Procedure B accounted for differences in vapour pressure deficit and available energy for evapotranspiration between the first‐ and second‐order stations. Procedure C was based on equating the Penman–Monteith (P–M) and Priestley–Taylor (P–T) equations on a monthly basis to solve for α. Methods to estimate monthly mean vapour pressure deficit, net radiation and wind speed were developed and evaluated. A total of 11 automated first‐order weather stations with a minimum period of record of 6 years (ranging from 6 to 10 years) were used for this study. Six of these stations were located in the continental zone and five in the Mediterranean zone. One station in each zone was assumed to be first‐order whereas the remainder were taken as second‐order stations. Monthly α parameters were calibrated using P–M reference crop evapotranspiration (ET₀) values, calculated hourly and integrated for monthly periods, which were taken as ‘true’ values of ET₀. For the extrapolation of monthly α parameters, procedure A was found to perform slightly better than procedure B in the Mediterranean zone. The opposite was true in the continental zone. Procedure C had the worst performance owing to the non‐linearity of the P–M equation and errors in the estimation of monthly available energy, vapour pressure deficit and wind speed. Procedures A and B are simpler and performed better. Overall, monthly P–T ET₀ estimates using extrapolated α parameters and R_n?G values were in a reasonable agreement with P–M ET₀ calculated on an hourly basis and integrated for monthly periods. The methods presented for the spatial extrapolation of monthly available energy, vapour pressure deficit and wind speed from first‐ to second‐order stations could be useful for other applications. Copyright © 2001 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.     

A simple parameterization of bulk canopy resistance from climatic variables for estimating hourly evapotranspiration

This paper examines a model for estimating canopy resistance r_c and reference evapotranspiration ET_o on an hourly basis. The experimental data refer to grass at two sites in Spain with semiarid and windy conditions in a typical Mediterranean climate. Measured hourly ET_o values were obtained over grass during a 4 year period between 1997 and 2000 using a weighing lysimeter (Zaragoza, northeastern Spain) and an eddy covariance system (Córdoba, southern Spain). The present model is based on the Penman–Monteith (PM) approach, but incorporates a variable canopy resistance r_c as an empirical function of the square root of a climatic resistance r* that depends on climatic variables. Values for the variable r_c were also computed according to two other approaches: with the r_c variable as a straight‐line function of r* (Katerji and Perrier, 1983, Agronomie 3 (6): 513–521) and as a mechanistic function of weather variables as proposed by Todorovic (1999, Journal of Irrigation and Drainage Engineering, ASCE 125 (5): 235–245). In the proposed model, the results show that r_c/r_a (where r_a is the aerodynamic resistance) presents a dependence on the square root of r*/r_a, as the best approach with empirically derived global parameters. When estimating hourly ET_o values, we compared the performance of the PM equation using those estimated variable r_c values with the PM equation as proposed by the Food and Agriculture Organization, with a constant r_c = 70 s m^?1. The results confirmed the relative robustness of the PM method with constant r_c, but also revealed a tendency to underestimate the measured values when ET_o is high. Under the semiarid conditions of the two experimental sites, slightly better estimates of ET_o were obtained when an estimated variable r_c was used. Although the improvement was limited, the best estimates were provided by the Todorovic and the proposed methods. The proposed approach for r_c as a function of the square root of r* may be considered as an alternative for modelling r_c, since the results suggest that the global coefficients of this locally calibrated relationship might be generalized to other climatic regions. It may also be useful to incorporate the effects of variable canopy resistances into other climatic and hydrological models. Copyright © 2005 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.     

Sensitivity analysis of a Penman–Monteith type equation to estimate reference evapotranspiration in southern Spain

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.     

Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations

ABSTRACT

In this work, the applicability of 12 solar radiation (R_S) estimation models and their impacts on daily reference evapotranspiration (ET_o) 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 ET_o estimates by the calibrated R_S 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 ET_o by the calibrated R_S 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     

The application of multiple linear regression method in reference evapotranspiration trend calculation

Trend analysis of reference evapotranspiration (ET₀), as a key factor in irrigation programming, has an important role in water resources management. Many parameters affect ET₀ and their variations can change its values. In this paper, the effect of temporal variation of meteorological variables including wind speed, temperature, solar radiation and saturation vapor pressure deficit on temporal variations of ET₀ was analyzed. Trend analysis of ET₀ and its more effective meteorological parameters was accomplished in 30 synoptic stations which are located in Iran using Spearman’s Rho test. The multiple linear regressions were also used to determine the relationship between ET₀ trend and the trend of its more effective parameters. Increasing and decreasing trends in ET₀ were obtained at annual and seasonal scales. Many studied stations which had decreasing trend in the annual and seasonal periods have been located in the arid climates while all stations which have been located in humid and very-humid climates, had an increasing trend in annual and seasonal periods. The trend results in studied variables showed that annual and seasonal values of wind speed, temperature and saturation vapor pressure deficit decrease however the values of solar radiation increases in most studied stations. Multiple linear regressions results demonstrated that ET₀ trend can be calculated by the trend of two more effective variables including wind speed and saturation vapor pressure deficit.     

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.     

A comparison of ASCE and FAO-56 reference evapotranspiration for a 15-min time step in humid climate conditions

Many applications in diverse disciplines require estimates of evapotranspiration (ET) at hourly or smaller time steps. The primary objectives of this study were to compare the American Society of Civil Engineers (ASCE) and FAO-56 Penman–Monteith equations for 15-min ET₀ (ET_{0,15-min,ASCE} and ET_0,15-min,FAO) estimations for humid climate conditions and to compare the 24 h sum of ASCE (ET_0,24 h,ASCE) and FAO-56 15-min ET₀ (ET_0,24 h,FAO) with the daily ET₀ (ET_0,d,FAO) computed from the daily FAO-56 equation, which is identical to ASCE daily ET₀ equation. Ten-year, i.e., 1997–2006 continuous 15-min and daily weather data for 11 representative and well-distributed sites throughout Georgia, USA were used. It was evident that during the day, ET_{0,15-min,ASCE} was higher than ET_0,15-min,FAO due to a lower surface resistance parameter value, while at night ET_{0,15-min,ASCE} was lower than ET_0,15-min,FAO due to a higher surface resistance parameter value. The ET_0,15-min,FAO was about 5% less than ET_{0,15-min,ASCE} and ET_0,24 h,FAO was about 5% lower than ET_0,24 h,ASCE. The difference between ET_{0,15-min,ASCE} and ET_0,15-min,FAO during the day and night was highly dependent on wind speed. During the three summer months, i.e., June, July and August, on average, ET_0,24 h,FAO was only 1% higher than ET_0,d,FAO while ET_0,24 h,ASCE was 5% higher than ET_0,d,FAO. For the entire year, ET_0,24 h,FAO was 8% higher than ET_0,d,FAO while ET_0,24 h,ASCE was 13% higher than ET_0,d,FAO. The ET_0,24 h,FAO and ET_0,d,FAO had a better agreement than ET_0,24 h,ASCE and ET_0,d,FAO throughout the year and during the summer months. It is also worth noting that the daily calculations for FAO-56 and ASCE were identical. These results demonstrated that for applications that require 15-min time steps or daily ET₀ for the entire year, the use of ET_0,15-min,FAO and ET_0,24 h,FAO, respectively, will yield more consistent outcomes. The use of ET_0,d,FAO during the summer months can be as accurate as the use of ET_0,24 h,FAO for applications that require daily time steps, such as irrigation scheduling.     

Estimating water balance components in irrigated agriculture using a combined approach of soil moisture and energy balance monitoring,and numerical modelling

Information on water balance components such as evapotranspiration and groundwater recharge are crucial for water management. Due to differences in physical conditions, but also due to limited budgets, there is not one universal best practice, but a wide range of different methods with specific advantages and disadvantages. In this study, we propose an approach to quantify actual evapotranspiration, groundwater recharge and water inflow, i.e. precipitation and irrigation, that considers the specific conditions of irrigated agriculture in warm, arid environments. This approach does not require direct measurements of precipitation or irrigation quantities and is therefore suitable for sites with an uncertain data basis. For this purpose, we combine soil moisture and energy balance monitoring, remote sensing data analysis and numerical modelling using Hydrus. Energy balance data and routine weather data serve to estimate ET₀. Surface reflectance data from satellite images (Sentinel-2) are used to derive leaf area indices, which help to partition ET₀ into energy limited evaporation and transpiration. Subsequently, first approximations of water inflow are derived based on observed soil moisture changes. These inflow estimates are used in a series of forward simulations that produce initial estimates of drainage and ET_act, which in turn help improve the estimate of water inflow. Finally, the improved inflow estimates are incorporated into the model and then a parameter optimization is performed using the observed soil moisture as the reference figure. Forward simulations with calibrated soil parameters result in final estimates for ET_act and groundwater recharge. The presented method is applied to an agricultural test site with a crop rotation of cotton and wheat in Punjab, Pakistan. The final model results, with an RMSE of 2.2% in volumetric water content, suggest a cumulative ET_act and groundwater recharge of 769 and 297 mm over a period of 281 days, respectively. The total estimated water inflow accounts for 946 mm, of which 77% originates from irrigation.     

Regional impacts of climate change on irrigation water demands

This paper presents an approach to model the expected impacts of climate change on irrigation water demand in a reservoir command area. A statistical downscaling model and an evapotranspiration model are used with a general circulation model (GCM) output to predict the anticipated change in the monthly irrigation water requirement of a crop. Specifically, we quantify the likely changes in irrigation water demands at a location in the command area, as a response to the projected changes in precipitation and evapotranspiration at that location. Statistical downscaling with a canonical correlation analysis is carried out to develop the future scenarios of meteorological variables (rainfall, relative humidity (RH), wind speed (U₂), radiation, maximum (Tmax) and minimum (Tmin) temperatures) starting with simulations provided by a GCM for a specified emission scenario. The medium resolution Model for Interdisciplinary Research on Climate GCM is used with the A1B scenario, to assess the likely changes in irrigation demands for paddy, sugarcane, permanent garden and semidry crops over the command area of Bhadra reservoir, India. Results from the downscaling model suggest that the monthly rainfall is likely to increase in the reservoir command area. RH, Tmax and Tmin are also projected to increase with small changes in U₂. Consequently, the reference evapotranspiration, modeled by the Penman–Monteith equation, is predicted to increase. The irrigation requirements are assessed on monthly scale at nine selected locations encompassing the Bhadra reservoir command area. The irrigation requirements are projected to increase, in most cases, suggesting that the effect of projected increase in rainfall on the irrigation demands is offset by the effect due to projected increase/change in other meteorological variables (viz., Tmax and Tmin, solar radiation, RH and U₂). The irrigation demand assessment study carried out at a river basin will be useful for future irrigation management systems. Copyright © 2012 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.     

Spatio-temporal variations of reference crop evapotranspiration and pan evaporation in the West Songnen Plain of China

Abstract

The spatio-temporal variations of reference crop evapotranspiration (ET_ref) reflect the combined effects of meteorological variables, primarily wind speed, relative humidity, net radiation and air temperature. This study investigated the spatial distribution and temporal trends of ET_ref (calculated by the FAO-56 Penman-Monteith equation), pan evaporation (E_pan) and pan coefficient (K_p) in a 140?×?10³ km² semi-humid to semi-arid area in China. The results show that: (i) although the spatial distributions of ET_ref and E_pan are roughly similar and their spatial correlation is high over the growing season, K_p varied considerably in space due to high humidity in the east of the region and low humidity in the southwest; (ii) the monthly variations of ET_ref and E_pan are similar to that of net radiation and opposite to that of relative humidity, while the monthly variation of K_p is similar to that of relative humidity and opposite to that of wind speed, and the long-term trend is slightly increasing for ET_ref and E_pan, while significantly (10% significance level) increasing for K_p; and (iii) generally, the time series of ET_ref and E_pan from 1951 to 2001 could be divided into three phases due to variations of meteorological variables.

Citation Liang, L.-Q., Li, L.-J. & Liu, Q. (2011) Spatio-temporal variations of reference crop evapotranspiration and pan evaporation in the West Songnen Plain of China. Hydrol. Sci. J. 56(7), 1300–1313.     

Estimation of monthly reference evapotranspiration using novel hybrid machine learning approaches

ABSTRACT

In this research, five hybrid novel machine learning approaches, artificial neural network (ANN)-embedded grey wolf optimizer (ANN-GWO), multi-verse optimizer (ANN-MVO), particle swarm optimizer (ANN-PSO), whale optimization algorithm (ANN-WOA) and ant lion optimizer (ANN-ALO), were applied for modelling monthly reference evapotranspiration (ET_o) at Ranichauri (India) and Dar El Beida (Algeria) stations. The estimates yielded by hybrid machine learning models were compared against three models, Valiantzas-1, 2 and 3 based on root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (PCC) and Willmott index (WI). The results of comparison show that the ANN-GWO-1 model with five input variables (T_min, T_max, RH, U_s, R_s) provides better estimates at both study stations (RMSE = 0.0592/0.0808, NSE = 0.9972/0.9956, PCC = 0.9986/0.9978, and WI = 0.9993/0.9989). Also, the adopted modelling strategy can build a truthful expert intelligent system for estimating the monthly ET_o at study stations.     

On the correlation between precipitation and potential evapotranspiration climate change signals for hydrological impact analyses

State-of-the-art hydrological climate impact assessment involves ensemble approaches to address uncertainties. For precipitation, a wide range of climate model runs is available. However, for particular meteorological variables used for the calculation of potential evapotranspiration (ET_o), availability of climate model runs is limited. It is preferred that climate model runs are considered coupled when calculating changes in precipitation and ET_o amounts, in order to preserve the internal physical consistency. This results in constraints on the maximum ensemble size. In this paper, we investigate the correlation between climate change signals of precipitation and ET_o. It is found that, for two medium-sized catchments in Belgium, uncoupling climate model runs used for calculation of change signals of precipitation and ET_o amounts does not result in a significant bias for changes in extreme flow. With these results, future impact studies can be conducted with larger ensemble sizes, resulting in a more complete uncertainty estimation.