Performance evaluation of satellite-based approaches for the estimation of daily air temperature and reference evapotranspiration

Different satellite-based radiation (Makkink) and temperature (Hargreaves-Samani, Penman-Monteith temperature, PMT) reference evapotranspiration (ET_o) models were compared with the FAO56-PM method over the Cauvery basin, India. Maximum air temperature (T_max) required in the ET_o models was estimated using the temperature–vegetation index (TVX) and an advanced statistical approach (ASA), and evaluated with observed T_max obtained from automatic weather stations. Minimum air temperature (T_min) was estimated using ASA. Land surface temperature was employed in the ET_o models in place of air temperature (T_a) to check the potency of its applicability. The results suggest that the PMT model with T_a as input performed better than the other ET_o 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 T_max and T_min values (r and RMSE of 0.87 and 2.17°C, and 0.87 and 2.27°C, respectively).     

Effectiveness of introducing crop coefficient and leaf area index to enhance evapotranspiration simulations in hydrologic models

Evapotranspiration (ET) is an essential component of the hydrological cycle and plays a critical role in water resource management. However, ET is often overlooked in order to transform rainfall to runoff for better streamflow simulation. Hydrological models are commonly used to estimate areal actual evapotranspiration (AET) after calibration against observed discharge. However, classical approaches are often inadequate to appropriately simulate other hydrologic components. Hence, it is important to introduce natural heterogeneity to enhance hydrological processes and reduce water balance errors. In this study, the effectiveness of introducing a constant crop coefficient (K_c), flux tower‐based K_c, and leaf area index (LAI) to three hydrological models (Three‐Parametric Hydrologic Model [TPHM], Génie Rural à 4 paramètres Journalier [GR4J], and Catchment hydrologic cycle Assessment Tool [CAT]) is assessed for the simulation of daily streamflow and AET in a mountainous mixed forest watershed (8.54 km²) in South Korea. The results show that the streamflow simulations after introduction of K_c and LAI to the original models are quite similar. However, the effectiveness of the AET estimation was significantly enhanced after introduction of the flux tower‐based K_c and LAI. The information criterion computed to compare the models reveals that the flux tower‐based K_c‐simulated AET demonstrated better agreement with the observed AET. The Pearson's correlation coefficients (R²) of the TPHM (8%), GR4J (55%), and CAT (55%) models also showed improvements that were greater than the constant based K_c simulation. Similarly, the limitations of the three models with respect to capturing seasonal variation as well as high and low flows were enhanced after the introduction of the flux tower‐based K_c, which adequately reproduced hydrological processes with minimum water balance errors and bias. A regression analysis revealed the potential of estimating K_c as a linear function of LAI (R² = 0.84). The results of this study indicate that introduction of K_c and LAI to the conceptual rainfall–runoff models can be considered an effective approach to reduce water balance errors and uncertainties in hydrological models and improve the reliability of climate change studies and water resource management.     

Spatio‐temporal distribution of actual evapotranspiration in the Indus Basin Irrigation System

Strategic planning of optimal water use requires an accurate assessment of actual evapotranspiration (ET_a) 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 ET_a 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 ET_a 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 ET_a 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 ET_a 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, ET_a 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.     

A minimalistic approach for evapotranspiration estimation using the Prophet model

ABSTRACT

This study aimed to evaluate the potential of the recently introduced Prophet model for estimating reference evapotranspiration (ETo). A comparative study was conducted for benchmarking the model results with support vector regression (SVR) and temperature-based empirical models (Thornthwaite and Hargreaves) in southern Japan. The performance of the Prophet, SVR and temperature-based empirical models was evaluated by Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R²). The results indicate that temperature-based Prophet and SVR models have greater accuracy than the empirical models. The Prophet model with sole input of relative humidity, sunshine hours or windspeed showed acceptable accuracy (NSE > 0.80; R² > 0.80), while SVR models with similar inputs showed greater errors. Accuracy improved with increasing number of input parameters, giving excellent performance (NSE > 0.95; R² > 0.95) with all input parameters. Hence, the Prophet model is a new promising approach for modelling ETo with limited input variables.     

Reference crop evapotranspiration determined with a modified Makkink equation

A modified version of the Makkink equation is shown to be a suitable alternative for Penman's formula for the determination of the crop reference evapotranspiration E_ref that is used in the so-called crop factor approach. Makkink's equation requires solar radiation and temperature data only. Since 1987 the Royal Netherlands Meteorological Institute has calculated E_ref with the modified Makkink's formula on a routine base. Using solar radiation derived from geostationary satellites, remotely sensed estimates of crop reference evapotranspiration can be obtained. © 1998 John Wiley & Sons, Ltd.     

Estimation of annual actual evapotranspiration from nonsaturated land surfaces with conventional meteorological data

Land surface evapotranspiration is an important component both in earth surface heat and water bal-ance, on whose budgets weather and climate depend, to a great extent, for their changes are responsible for the formation and variation of vegetation features on the globe. Besides, the evapotranspiration is an im-portant topic of short-term flood forecasting and the estimation of runoff from mountainous sides. As a result, the problem as to the evapotranspiration has been one of the concerns in …     

A simple temperature method for the estimation of evapotranspiration

Accurate estimation of evapotranspiration (ET) is essential in water resources management and hydrological practices. Estimation of ET in areas, where adequate meteorological data are not available, is one of the challenges faced by water resource managers. Hence, a simplified approach, which is less data intensive, is crucial. The FAO‐56 Penman–Monteith (FAO‐56 PM) is a sole global standard method, but it requires numerous weather data for the estimation of reference ET. A new simple temperature method is developed, which uses only maximum temperature data to estimate ET. Ten class I weather stations data were collected from the National Meteorological Agency of Ethiopia. This method was compared with the global standard PM method, the observed Piche evaporimeter data, and the well‐known Hargreaves (HAR) temperature method. The coefficient of determination (R²) of the new method was as high as 0.74, 0.75, and 0.91, when compared with that of PM reference evapotranspiration (ET_o), Piche evaporimeter data, and HAR methods, respectively. The annual average R² over the ten stations when compared with PM, Piche, and HAR methods were 0.65, 0.67, and 0.84, respectively. The Nash–Sutcliff efficiency of the new method compared with that of PM was as high as 0.67. The method was able to estimate daily ET with an average root mean square error and an average absolute mean error of 0.59 and 0.47 mm, respectively, from the PM ET_o method. The method was also tested in dry and wet seasons and found to perform well in both seasons. The average R² of the new method with the HAR method was 0.82 and 0.84 in dry and wet seasons, respectively. During validation, the average R² and Nash–Sutcliff values when compared with Piche evaporation were 0.67 and 0.51, respectively. The method could be used for the estimation of daily ET_o where there are insufficient data. Copyright © 2013 John Wiley & Sons, Ltd.     

A coupled surface resistance model to estimate crop evapotranspiration in arid region of northwest China

The Penman–Monteith (PM) model has been widely used to estimate crop evapotranspiration (ET), but it performs poorly with sparse vegetation. By combining the Jarvis canopy resistance model and the soil resistance model, we have developed a coupled surface resistance model to address this issue. Maize field and vineyard ET, measured by the eddy covariance method during 2007 and 2008, were used to test the estimations produced by the PM model combined with our coupled surface resistance model and Jarvis model, respectively. Results indicate that PM model combined with the coupled surface resistance model produces higher determination coefficient and lower root mean square error when compared with the PM–Jarvis method, either for maize field or for the sparse vineyard, on half‐hourly or daily time scales. Our study confirms that the coupled surface resistance model produces higher accuracy than the Jarvis model and provides a method to calculate resistance parameters for using the PM model to simulate the ET of sparse vegetation. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of potential evapotranspiration over the Yellow River basin: reference crop evaporation or Shuttleworth–Wallace?

Potential evapotranspiration (PET) is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P–M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this paper the Shuttleworth–Wallace (S–W) model is implemented to estimate PET directly in a form that recognizes vegetation diversity and temporal change without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme land cover classification. The spatial and temporal variation of the LAI of vegetation is derived from the composite NOAA‐AVHRR normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S–W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins. A comparison is made between the FAO‐56 method and the S–W model when applied to the Yellow River basin for the whole of the last century. The resulting estimates of RET and PET and their association with vegetation types and leaf area index (LAI) are examined over the whole basin both annual and monthly and at six specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S–W model not only reflects the changes in climate, but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET and/or climatic variables, applying these relationships likely will result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of vegetation. It is concluded that use of the implementation of the S–W model described in this study results in a physically sound estimate of PET that accounts for changing land surface conditions. Copyright © 2006 John Wiley & Sons, Ltd.     

A modified trapezoid framework model for partitioning regional evapotranspiration

While evapotranspiration (ET) is normally measured as one hydrologic component, evaporation (E), and transpiration (T) result from different physical-biological processes. Using a two-source model, a trapezoid framework has been widely applied in recent years. The key to applying the trapezoid framework model is the determination of the dry/wet boundaries of the land surface temperature-fractional vegetation coverage trapezoid (LST-f_c). Although algorithms have been developed to characterize the two boundaries, there remains a significant uncertainty near the wet boundary which scatters in a discrete and uneven manner. It is therefore difficult to precisely locate the wet boundary. To address this problem, a Wet Boundary Algorithm (WBA) was developed in this study with the algorithm applied in the region of Huang-Huai-Hai plain of China, using the Pixel Component Arranging and Comparing Algorithm (PCACA) to retrieve ET from MODerate-resolution Imaging Spectroradiometer (MODIS) Data. The eddy covariance (EC) measurements from Yucheng station was used to verify the modified model where the root mean square error (RMSE) of 17.8 W/m², Bias of −7.2 W/m² for latent heat flux (LE) simulation in 28 cloudless test days. The ratio of transpiration to evapotranspiration (T/ET) varied between 0.48 and 0.81 over the Huang-Huai-Hai plain. The spatial and temporal distribution of ET revealed that agriculture practices have a significant influence on the hydrological cycle, where crop growth promotes the magnitude of ET. Likewise, harvesting activities significantly reduce ET. The proposed WBA algorithm significantly reduces the uncertainty of the trapezoid ET model caused by wet edge positioning. The analysis of the impact of agricultural activities on ET provide a better understanding how human activities change the hydrological cycle at regional scales.     

A distributed approach for estimating catchment evapotranspiration: comparison of the combination equation and the complementary relationship approaches

In large river basins, there may be considerable variations in both climate and land use across the region. The evapotranspiration that occurs over a basin may be drastically different from one part of the region to another. The potential influence of these variations in evapotranspiration estimated for the catchment is weakened by using a spatially based distributed hydrological model in such a study. Areal evapotranspiration is estimated by means of approaches requiring only meteorological data: the combination equation (CE) model and the complementary relationship approach—the complementary relationship areal evapotranspiration (CRAE) and advection–aridity (AA) models. The capability of three models to estimate the evapotranspiration of catchments with complex topography and land‐use classification is investigated, and the models are applied to two catchments with different characteristics and scales for several representative years. Daily, monthly, and annual evapotranspiration are estimated with different accuracy. The result shows that the modified CE model may underestimate the evapotranspiration in some cases. The CRAE and AA models seem to be two kinds of effective alternatives for estimating catchment evapotranspiration. Copyright © 2003 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.     

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.     

Evaluating actual evapotranspiration and impacts of groundwater storage change in the North China Plain

As a critical water discharge term in basin‐scale water balance, accurate estimation of evapotranspiration (ET) is therefore important for sustainable water resources management. The understanding of the relationship between ET and groundwater storage change can improve our knowledge on the hydrological cycle in such regions with intensive agricultural land usage. Since the 1960s, the North China Plain (NCP) has experienced groundwater depletion because of overexploitation of groundwater for agriculture and urban development. Using meteorological data from 23 stations, the complementary relationship areal evapotranspiration model is evaluated against estimates of ET derived from regional water balance in the NCP during the period 1993–2008. The discrepancies between calculated ET and that derived by basin water balance indicate seasonal and interannual variations in model parameters. The monthly actual ET variations during the period from 1960 to 2008 are investigated by the calibrated model and then are used to derive groundwater storage change. The estimated actual ET is positively correlated with precipitation, and the general higher ET than precipitation indicates the contributions of groundwater irrigation to the total water supply. The long term decreasing trend in the actual ET can be explained by declining in precipitation, sunshine duration and wind speed. Over the past ~50 years, the calculated average annual water storage change, represented by the difference between actual ET and precipitation, was approximately 36 mm, or 4.8 km³; and the cumulative groundwater storage depletion was approximately 1700 mm, or 220 km³ in the NCP. The significantly groundwater storage depletion conversely affects the seasonal and interannual variations of ET. Irrigation especially during spring cause a marked increase in seasonal ET, whereas the rapid increasing of agricultural coverage over the NCP reduces the annual ET and is the primary control factor of the strong linear relationship between actual and potential ET. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

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     

Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration

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.