Accurate Estimation Of Evapotranspiration Research Articles

Determination of crop and soil evaporation coefficients for estimating evapotranspiration in a paddy field

Accurate estimation of evapotranspiration is important in efficient water management for improving water use efficiency. In order to obtain evapotranspiration and evaporation beneath the canopy using the Food and Agriculture Organization (FAO) method, pan evaporation was used instead of reference evapotranspiration calculated by the Penman-Monteith equation with detailed meteorological data. The total crop coefficient and soil evaporation coefficient were determined using actual measured daytime evapotranspiration and evaporation by the Bowen ratio energy balance and lysimeter, respectively, in a rice paddy field in Japan. The average evapotranspiration was 5.3 mm/d, 4.4 mm/d, 7.4 mm/d and 6.3 mm/d and crop coefficient was 0.79, 1.18, 1.01 and 0.86 for the initial stage, development stage, middle-season stage and late-season stage, respectively. The evaporation was low and almost constant with an average value around 0.77 mm/d when the leaf area index (LAI) reached 3. The proposed average crop coefficients for different growing stages were applied to estimate daytime evapotranspiration and found suitable. A simple soil water evaporation coefficient model was developed using leaf area index for practical use and it was found that it could accurately estimate evaporation. Keywords: evapotranspiration, evaporation, paddy field, lysimeter, leaf area index (LAI), Bowen ratio energy balance DOI: 10.25165/j.ijabe.20171004.2290 Citation: Yan H F, Zhang C, Oue H, Peng G J, Darko R O. Determination of crop and soil evaporation coefficients for estimating evapotranspiration in a paddy field. Int J Agric & Biol Eng, 2017; 10(4): 130–139.

Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images

A study was carried out to estimate the actual evapotranspiration (ET) over a 1074 km2 of the humid area of Perak State (Malaysia), where water and evaporation cycle deeply influences the climate, natural resources and human living aspects. Images from both Terra and Aqua platforms of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor were used for ET estimation by employing the Surface Energy Balance Algorithm for Land (SEBAL) model. As a part of the accuracy assessment process, in-situ measurements on soil temperature and reference ET (ET0) were recorded at the time of satellite overpass. In order to enhance the accuracy of the generated ET maps, MODIS images were subjected to sub-pixel analysis by assigning weights for different land surface cover (urban, agriculture and multi-surface areas) reflections. The weighting process was achieved by integrating ET from pure pixels with the respective site-specific ET0 of each land cover. The enhanced SEBAL model estimated ET exhibited a good correlation with the in-situ measured Penman-Montieth ET0, with R2 values for the Aqua and the Terra platforms of 0.67 and 0.73, respectively. However, the correlation of the non-enhanced ET maps resulted in R2 values of 0.61 and 0.68 for the Aqua and the Terra platforms, respectively. Hence, the results of this study revealed the feasibility of employing the sub-pixel analysis method for an accurate estimation of ET over large areas. Keywords: evapotranspiration, sub-pixel analysis, MODIS image, MODIS sensor, remote sensing, land surface cover DOI: 10.3965/j.ijabe.20171002.2890 Citation: Hassaballa A A, Matori A, Al-Gaadi K A, Tola E H, Madugundu R. Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images. Int J Agric & Biol Eng, 2017; 10(2): 103–113.

Subirrigation System Performance and Evaluation in the Red River Valley of the North

Abstract. Using a subsurface drainage system, subirrigation (SI) applies water below the ground surface and raises the phreatic water to within or near the root zone. SI is relatively new to the Red River Valley (RRV) of the North in eastern North Dakota (ND) and west central Minnesota (MN). In 2011, two SI field sites in the RRV were installed and have shown promising results in optimal water management and increasing agricultural production. Unlike a surface irrigation system, SI supplies water below the ground surface over a long duration; water loss is generally through crop transpiration; and SI leads to negligible water loss via wind, surface runoff and evaporation. Therefore, a new method was developed to evaluate the SI system performance. Water application efficiency (Ea) was calculated through the soil moisture changes in the root zone before and after the SI application with known amounts of SI, precipitation, and evapotranspiration (ET). Uniformity coefficient (UC) and distribution efficiency of low quarter (DULQ) were estimated from the total depth of water stored in the root zone. The SI system performance in 2014 and 2015 showed that the Ea was over 100% in 2014 and 78% for the ND 2015 site-year. The Ea values were high, indicating that the SI system either performed better than typical surface irrigation systems with minimal water loss, or the SI system and/or the methods need improvement in accurate ET estimation to help close the water budget. The UCs were 67% to 86%, and the DULQs were 48% to 78%, much lower than typical sprinkler and surface irrigation systems, possibly due to the unique SI flow path. Overall, the evaluation indicated that a SI system is effective as a water supply, but the uniformity needs to be improved with a longer SI duration or smaller flow rate or an alternative SI system design. Keywords: Red River Valley of the North, Subirrigation, Uniformity, Water use efficiency.

Evaluation of crop coefficients, water productivity, and water balance components for wine grapes irrigated at different deficit levels by a sub-surface drip

Accurate estimation of evapotranspiration (ET) and its partitioning into transpiration and evaporation is fundamental for improving water management practices in water-limited environments and under deficit irrigation conditions. This investigation was conducted to estimate the water balance and ET components of subsurface drip (SDI) irrigated Chardonnay wine grapes for two seasons (2010–2011 and 2011–2012) using a numerical model (HYDRUS-2D). Treatments involved the application of different volumes [51% (I1), 64% (I2), 77% (I3), and 92% (I4) of normal application] of water for irrigation. A modified version of the FAO-56 dual crop coefficient approach was used to generate daily transpiration and evaporation as inputs to the HYDRUS-2D model. The calibrated and validated model produced estimates of actual evapotranspiration (ETCact), actual transpiration (Tpact), and actual evaporation (Esact), and deep percolation under varied irrigation applications. The model-simulated values were then used to estimate actual crop coefficients (Kcact and Kcbact), and water productivity of wine grape under different deficit irrigation conditions.Seasonal ETCact simulated by HYDRUS-2D for different treatments varied between 239 and 382mm. However, seasonal evaporation accounted for 44–59% of seasonal ETCact losses in different treatments. The modelled daily transpiration rate in I4 treatment (Tp4act) varied from 0.11–2.74mm/day. Deep percolation accounted for 35–40% of the total water applied by rainfall and irrigation. The mean value of actual crop coefficient (Kcact) estimated by HYDRUS-2D simulated ETCact over the two seasons was 0.27, which matched with other investigations. Similarly, values of Kcbact for initial, mid and end stages were 0.13, 0.27 and 0.14, respectively. Monthly values of evaporation coefficient (Ke) ranged from 0.1 to 0.32, with a mean value of 0.18. Water productivity with respect to ET losses (WPETC) ranged from 5.9 to 6.2kg/m3 of water use. However, water productivity for transpiration (WPTC) almost doubled as compared to WPETC in all treatments. The impact of deficit irrigation on berry juice composition (Brix, pH and titratable acidity) was lower than the inter-seasonal variability. These results can help develop better irrigation management strategies for SDI irrigated wine grapes under water scarce conditions.

Integrating genetic algorithm and support vector machine for modeling daily reference evapotranspiration in a semi-arid mountain area

Accurate estimation of evapotranspiration is vitally important for management of water resources and environmental protection. This study investigated the accuracy of integrating genetic algorithm and support vector machine (GA-SVM) models using climatic variables for simulating daily reference evapotranspiration (ET0). The developed GA-SVM models were tested using the ET0 calculated by Penman–Monteith FAO-56 (PMF-56) equation in a semi-arid environment of Qilian Mountain, northwest China. Eight models were developed using different combinations of daily climatic data including maximum air temperature (Tmax), minimum air temperature (Tmin), wind speed (U2), relative humidity (RH), and solar radiation (Rs). The accuracy of the models was evaluated using root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (r). The results indicated that the GA-SVM models successfully estimated ET0 with those obtained by the PMF-56 equation in the semi-arid mountain environment. The model with input combinations of Tmin, Tmax, U2, RH, and Rs had the smallest value of the RMSE and MAE as well as higher value of r (0.995) compared to other models. Relative to the performance of support vector machine (SVM) models and feed-forward artificial neural network models, it was found that the GA-SVM models proved superior for simulating ET0.

Application of Artificial Neural Network Approach for Estimating Reference Evapotranspir

The process of evapotranspiration (ET) is a vital part of the water cycle. Exact estimation of the value of ET is necessary for designing irrigation systems and water resources management. Accurate estimation of ET is essential in agriculture, its over-estimation leads to cause the waste of valuable water resources and its underestimation leads to the plant moisture stress and decrease in the crop yield. The well known Penman-Monteith (PM) equation always performs the highest accuracy results of estimating reference Evapotranspiration (ET0) among the existing methods is without any discussion. However, the equation requires climatic data that are not always available particularly for a developing country. ET0 is a complex process which is depending on a number of interacting meteorological factors, such as temperature, humidity, wind speed, and radiation. The lack of physical understanding of ET0 process and unavailability of all appropriate data results in imprecise estimation of ET0. Over the past two decades, artificial neural networks (ANNs) have been increasingly applied in modeling of hydrological processes because of their ability in mapping the input–output relationship without any understanding of physical process. This paper investigates for the first time in the semiarid environment of Junagadh, the potential of an artificial neural network (ANN) for estimating ET0 with limited climatic data set.

Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

Abstract. The Tibetan Plateau (TP) plays a major role in regional and global climate. The understanding of latent heat (LE) flux can help to better describe the complex mechanisms and interactions between land and atmosphere. Despite its importance, accurate estimation of evapotranspiration (ET) over the TP remains challenging. Satellite observations allow for ET estimation at high temporal and spatial scales. The purpose of this paper is to provide a detailed cross-comparison of existing ET products over the TP. Six available ET products based on different approaches are included for comparison. Results show that all products capture the seasonal variability well with minimum ET in the winter and maximum ET in the summer. Regarding the spatial pattern, the High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) ET demonstrator dataset is very similar to the LandFlux-EVAL dataset (a benchmark ET product from the Global Energy and Water Cycle Experiment), with decreasing ET from the south-east to north-west over the TP. Further comparison against the LandFlux-EVAL over different sub-regions that are decided by different intervals of normalised difference vegetation index (NDVI), precipitation, and elevation reveals that HOLAPS agrees best with LandFlux-EVAL having the highest correlation coefficient (R) and the lowest root mean square difference (RMSD). These results indicate the potential for the application of the HOLAPS demonstrator dataset in understanding the land–atmosphere–biosphere interactions over the TP. In order to provide more accurate ET over the TP, model calibration, high accuracy forcing dataset, appropriate in situ measurements as well as other hydrological data such as runoff measurements are still needed.

Evaluation of FAO-56 Penman-Monteith Model with Limited Data and the Valiantzas Models for Estimating Grass-Reference Evapotranspiration in Sahelian Conditions

Accurate determination of grass-reference evapotranspiration (ETo) is very important for agricultural, hydrological, and environmental studies, especially under increasing water scarcity and climate mitigation conditions. The FAO-56 Penman-Monteith (FAO-PM) model is renowned for being the most accurate model; however, it requires a full climate data set that is not always available at all weather stations, especially in most of the developing countries. Thus, using ETo models that require a reduced set of climate data continues to be an important alternative in such cases. The objectives of this study were to (1) evaluate the FAO-56 Penman-Monteith equation to estimate ETo with limited climate data, and (2) evaluate two of the latest ETo equations developed by Valiantzas. Climatic variables, including maximum and minimum air temperature, maximum and minimum relative humidity, solar radiation, and wind speed were collected from eight weather stations across Burkina Faso. The results showed that when solar radiation data were missing, solar radiation estimation from maximum and minimum daily air temperatures generated accurate estimates of ETo, with regression slope from 0.98 to 1.04, root mean squared error (RMSE) less than 0.60 mm/day, and low mean biased error (MBE) within the range of −0.18–0.02 mm/day. In the case of lacking relative humidity data, the RMSE and MBE varied from 0.07 to 0.47 mm/day and from −0.45 to 0.22 mm/day, respectively, and the regression slope varied from 0.90 to 1.14, and the coefficient of determination (R2) ranged from 0.77 to 0.92. In the case of missing wind speed, the method that used long-term average wind speed (ETo-um) resulted in the best estimates, especially for lower ETo rates (ETo<6 mm/day) as compared to the method (ETo-w2) that adopted the default wind speed of 2 m/s. Indeed the ETo-w2 method overestimated ETo from 4 to 35%. With the ETo-um method, RMSE varied from 0.43 to 0.57 mm/day and the MBE varied from −0.05 to 0.04 mm/day whereas the (ETo-w2) method had the RMSE ranging from 0.59 to 2.11 mm/day and the MBE ranging from 0.26 to 1.90 mm/day. The FAO-PM equation had the least accurate performance when only temperature data is available. The Valiantzas 1 equation that uses only air temperature and relative humidity data was not suitable and is not recommended for use in Burkina Faso climatic conditions. The Valiantzas 2 equation with full climatic data resulted in good ETo estimates relative to the FAO-PM ETo with full data under the Burkina Faso climate conditions; however, the FAO-PM equation is recommended because of limitations of the Valiantzas 2 equation under limited data conditions.

Spatial Uniformity in Sensitivity Coefficient of Reference ET in the Texas High Plains

<abstract> <b><sc>Abstract. </sc></b>Evapotranspiration (ET) is a major component of the agricultural water budget and accurate ET estimations are essential for effective irrigation scheduling. Therefore, it is an important aspect of production agriculture and agricultural research. Potential crop ET can be calculated by multiplying reference ET by an appropriate crop coefficient. Reference ET can be estimated from meteorological data obtained from weather stations sited on a reference crop surface, e.g., grass or alfalfa. However, weather station sensor inaccuracies may propagate measurement errors into the reference ET calculations. A sensitivity analysis of weather variables used in calculating ET (air temperature, wind speed, solar radiation, and relative humidity) can be used to determine relative effects of data inaccuracies on ET estimates, and conversely, the sensor accuracy levels needed for acceptably accurate ET estimates. In this study, sensitivity analyses of weather variables on daily reference ET were conducted using hourly data (1995-2008) from eight weather stations managed by the Texas High Plains ET network in the Texas Panhandle. Sensitivity coefficients were calculated for each of the weather variables. Comparison of the sensitivity coefficients for any one station indicated that reference ET was most sensitive to wind speed followed by air temperature. Comparison of sensitivity coefficients for any one weather variable (e.g., wind speed) across the region showed no significant differences in the sensitivity of reference ET to those variables by location. This indicates that the existing North-South air temperature gradient and variability in local wind circulation patterns have limited influence on the sensitivity of reference ET to individual weather variables. This indicated that a uniform maintenance protocol should be sufficient for weather stations located throughout the Texas High Plains.

A review on evapotranspiration data assimilation based on hydrological models

Accurate estimation of evapotranspiration (ET), especially at the regional scale, is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper, a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET, being a non-state variable, to construct data assimilation relationships are elaborated upon, with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this, a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model (DTVGM), and the ET-soil humidity nonlinear time response relationship of this model. Moreover, the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states, and may be referenced for accurate estimation of regional evapotranspiration.

An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing

An accurate estimation of evapotranspiration (ET) is crucial to better understand the water budget and improve related studies. Satellite remote sensing provides an unprecedented opportunity to map the spatiotemporal distribution of ET. However, ET values from barren or sparsely vegetated areas in arid regions are often assumed to be zero in typical ET products because of their low values. In addition, separating ET into soil evaporation (E-s) and vegetation transpiration (E-c) is difficult. To address these challenges, we developed an ET product (MOD3T) based on a three-temperature model and thermal remote sensing, specifically Moderate Resolution Imaging Spectroradiometer (MODIS) data. MOD3T has a spatial resolution of 1 km and a temporal resolution of 8 days. All input parameters except air temperature were obtained from MODIS datasets. Validation in two adjacent arid river basins in northwestern China showed that the mean absolute errors (mean absolute percent errors) between the MOD3T and flux tower ET were 0.71 mm d(-1) (18.5%) and 0.16 mm d(-1) (24.9%) for a densely vegetated area and sparsely vegetated sandy desert, respectively. The error between the MOD3T and water balance ET was 24 mm y(-1) (8.1%). The E-c/ET or E-s/ET of MOD3T was comparable to the observed stable oxygen and hydrogen isotopes. Unlike the MODIS ET (MOD16), MOD3T could not provide continuous ET values (as 70% of the MOD16 area lacked data) but exhibited relatively low uncertainty, particularly in cold seasons. Therefore, MOD3T can provide ET, E-s and E-c estimates for arid regions within acceptable ranges. (C) 2015 Elsevier B.V. All rights reserved.

One‐dimensional expression to calculate specific yield for shallow groundwater systems with microrelief

Although the importance to account for microrelief in the calculation of specific yields for shallow groundwater systems is well recognized, the microrelief influence is often treated very simplified, which can cause considerable errors. We provide a general one-dimensional expression that correctly represents the effect of a microrelief on the total specific yield that is composed of the soil and surface specific yield. The one-dimensional expression can be applied for different soil hydraulic parameterizations and soil surface elevation frequency distributions. Applying different van Genuchten parameters and a simple linear microrelief model, we demonstrate that the specific yield is influenced by the microrelief not only when surface storage directly contributes to specific yield by (partial) inundation but also when water levels are lower than the minimum surface elevation. Compared with a simplified representation of the soil specific yield, in which a mean soil surface is assumed for the calculation of soil specific yield, the correct representation can lead to lower as well as higher soil specific yields depending on the specific interaction of the soil water retention characteristics and the microrelief. The new equation can be used to obtain more accurate evapotranspiration estimates from water level fluctuations and to account for the effect of microtopographic subgrid variability on simulated water levels of spatially distributed hydrological models. Copyright © 2015 The Authors Hydrological Processes Published by John Wiley & Sons Ltd

Comparison of three evapotranspiration models with eddy covariance measurements for a Populus euphratica Oliv. forest in an arid region of northwestern China

The accurate estimation of evapotranspiration (ET) in arid regions is important for improving the water use efficiency of vegetation. Based on successive observations from May to October of 2014, we estimated the ET of a Populus euphratica Oliv. forest during the growing season in an extremely arid region using the PM (Penman-Monteith), SW (Shuttleworth-Wallace) and SSW (an improved canopy transpiration model) models. Estimated ET values were compared with those of the eddy covariance measurements. Results indicated that the actual ET of the P. euphratica forest was always overestimated by the PM model. The accuracy of the SW model was higher than that of the PM model. However, some data were not easily obtained because of the complicated structure of the SW model. The newly proposed SSW model gave the most accurate ET values, and its accuracy was higher at hourly than at daily time scale. In conclusion, the SSW model is more suitable for sparse vegetation system at large scales in extremely arid regions.

Regional estimation and validation of remotely sensed evapotranspiration in China

Accurate estimates of evapotranspiration (ET) are important to skillful predictions of runoff, soil moisture and crop productivity. In this study, ET was simulated over three years in China by integrating remotely-sensed data with the simulation model SEBS-China. SEBS-China was developed from the Surface Energy Balance System (SEBS) model that is used to estimate atmospheric turbulent heat fluxes and evaporative fraction through satellite-derived radiation fluxes and land surface temperatures coupled with near-surface meteorological variables. Simulated regional ET was first evaluated using experimental data from the Changbai Mountains and five river basins in China. Average annual simulated ET agreed well with the observed data, based on the detailed results through comparative validation. Regional ET derived from SEBS-China was then compared with the simulated ET from the Common Land Model (CoLM). Both of the models simulated regional ET well, with a few overestimated areas such as in the Qinghai–Tibet Plateau, YanShan and South Daxing'anling Mountains. We conclude that more efficient ET estimation can be achieved through combining remotely-sensed information with land surface models.

COMPARATIVE STUDY OF EVALUATION OF EVAPOTRANSPIRATION METHODS AND CALCULATION OF CROP WATER REQUIREMENTS AT CHASKAMAN COMMAND AREA IN PUNE REGION, INDIA

Accurate estimation of evapotranspiration is necessary step in water resources management. Evapotranspiration varies spatially and temporally. Recently, the Food and Agricultural Organisation has suggested FAO-56 PM method (modified PM method) as a standard method for calculating reference evapotranspiration (ET0), because this method is applicable to all types of season and different climates and gives more accurate result when compared with the physical methods like Lysimeter and Class A Pan. FAO-56 PM method cannot be debated by any other old methods which require less data for calculating ET0. But FAO-56 PM requires very large amount of meteorological data, which is not available at full climate stations. So there is need to find out the next best suitable method after FAO-56 PM method, which will give ETo results nearer to FAO-56 PM method. Here seven different methods are considered for present study, which are radiation based, temperature based and combine parameters based (FAO-56 modified Penman Monteith, FAO-24 Penman Monteith, FAO-56 Hargreaves, Turc, Thornthwaite, Blaney-Criddle, Priestley Taylor are the methods). Chaskaman dam and its left bank canal is selected for this project. The objective of the project work is to calculate daily, monthly and yearly reference ET0 using modified PM equations for ‘left bank canal of Chaskaman dam and its command area’. Further ETc (crop evapotranspiration/crop water requirement) will be calculated for that command area.

Exploring ground-based methods for the validation of remotely sensed evapotranspiration

Accurate estimates of evapotranspiration (ET) are essential when calculating catchment-scale water balances. An open top chamber (OTC), a ground-based method for measuring actual ET, was used to validate modeled ET from earth observation MODIS and agrometeorological data. We studied and compared the modeled ET (ETMODIS of two adjacent, quaternary catchments from the Bushman's River primary catchment, namely P10A and Q91C, representing light and heavy stocking density, respectively. Within each catchment, a relatively homogenous 1 km2 pixel of grassland was selected for intensive study. Mean annual ETMODIS results from 2009 to 2011 showed that P10A (light) was higher by 14 mm than Q91C (heavy). No significant difference was observed between hourly ETMODIS and hourly ETOTC. A good relationship was observed between daily ETMODIS and ETOTC (r2 = 0.7065, p value < 0.01, df = 8) for each 1 km2 pixel during the 2010/11 growing season. This confirmed that the OTC is a useful instrument to determine actual ET over grassland and short shrubland, and may be used in model validation.

Evaluation of irrigation water use efficiency using remote sensing in the middle reach of the Heihe river, in the semi‐arid Northwestern China

AbstractIrrigation of agricultural oases is the main water consumer in semi‐arid and arid regions of Northwestern China. The accurate estimation of evapotranspiration (ET) on the oases is extremely important for evaluating water use efficiency so as to reasonably allocate water resources, particularly in semi‐arid and arid areas. In this study, we integrated the soil moisture information into surface energy balance system (SEBS) for improving irrigated crop water consumption estimation. The new approach fed with the moderate resolution imaging spectro‐radiometer images mapped spatiotemporal ET on the oasis in the middle reach of the Heihe river. The daily ET outputs of the new approach were compared with those of the original SEBS using the eddy correlation observations, and the results demonstrate that the modified SEBS remedied the shortcoming of general overestimating ET without regard to soil water stress. Meanwhile, the crop planting structure and leaf area index spatiotemporal distribution in the studied region were derived from the high‐resolution Chinese satellite HJ‐1/CCD images for helping analyse the pattern of the monthly ET (ETmonthly). The results show that the spatiotemporal variation of ETmonthly is closely related to artificial irrigation and crop growth. Further evaluation of current irrigation water use efficiency was conducted on both irrigation district scale and the whole middle reach of the Heihe river. The results reveal that the average fraction of consumed water on irrigation district scale is 57% in 2012. The current irrigation water system is irrational because only 52% of the total irrigated amount was used to fulfil plant ET requirement and the rest of the irrigation water recharged into groundwater in the oasis in 2012. However, in view of the whole middle reach of the Heihe river, the irrigation water use efficiency could reach to 66% in 2012. But pumping groundwater for reused irrigation wastes mostly energy instead of water. An improved irrigation water allocation system according to actual ET requirement is needed to increase irrigation efficiency per cubic meter water resource in an effort to save both water and energy. Copyright © 2014 John Wiley &amp; Sons, Ltd.

A Hybrid Dual-Source Model of Estimating Evapotranspiration over Different Ecosystems and Implications for Satellite-Based Approaches

Accurate estimation of evapotranspiration (ET) and its components is critical to developing a better understanding of climate, hydrology, and vegetation coverage conditions for areas of interest. A hybrid dual-source (H-D) model incorporating the strengths of the two-layer and two-patch schemes was proposed to estimate actual ET processes by considering varying vegetation coverage patterns and soil moisture conditions. The proposed model was tested in four different ecosystems, including deciduous broadleaf forest, woody savannas, grassland, and cropland. Performance of the H-D model was compared with that of the Penman-Monteith (P-M) model, the Shuttleworth-Wallace (S-W) model, as well as the Two-Patch (T-P) model, with ET and/or its components (i.e., transpiration and evaporation) being evaluated against eddy covariance measurements. Overall, ET estimates from the developed H-D model agreed reasonably well with the ground-based measurements at all sites, with mean absolute errors ranging from 16.3 W/m2 to 38.6 W/m2, indicating good performance of the H-D model in all ecosystems being tested. In addition, the H-D model provides a more reasonable partitioning of evaporation and transpiration than other models in the ecosystems tested.

Generalized calibration of the Hargreaves equation for evapotranspiration under different climate conditions

Accurate estimation of evapotranspiration (ETo) is a key factor in weather-based irrigation scheduling methods. To estimate ETo using the Hargreaves equation, just the data on the minimum and maximum temperature and solar radiation are required. However, this procedure cannot offer consistent accuracy for different climate conditions. To attain the accuracy, calibration of the equation constants (C&lt;sub&gt;H&lt;/sub&gt;and E&lt;sub&gt;H&lt;/sub&gt;) for different climate conditions have successfully been attempted by many researchers. Because these calibration procedures are lengthy and location-specific, there is a need of a generalized calibration method to make the Hargreaves equation more pertinent and effective. In this paper, fuzzy logic based calibration method for the Hargreaves equation is proposed and validated. The fuzzy inference system is developed to compute appropriate values of the constants C&lt;sub&gt;H&lt;/sub&gt;and E&lt;sub&gt;H&lt;/sub&gt; on the basis of past data on humidity and wind velocity of a selected location. The underlying relationship between weather conditions and the best values of the constants C&lt;sub&gt;H&lt;/sub&gt;and E&lt;sub&gt;H&lt;/sub&gt; are used to establish a fuzzy rule base. The performance of the method is checked at eight geographically different locations of India with diverse climate conditions. The Mean Absolute Error (MAE) in ETovalues estimated by the calibrated modified Hargreaves equation and the Penman-Monteith (PM) equation is in the range of 0.3220&amp;ndash;1.0325. It is far more lower than if the error is calculated using the original Hargreaves equation. It confirms the correctness of the calibration method for different climate conditions.

Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin

[1] Regional evapotranspiration (ET) can be estimated using diagnostic remote sensing models, generally based on principles of energy balance closure, or with spatially distributed prognostic models that simultaneously balance both energy and water budgets over landscapes using predictive equations for land surface temperature and moisture states. Each modeling approach has complementary advantages and disadvantages, and in combination they can be used to obtain more accurate ET estimates over a variety of land and climate conditions, particularly for areas with limited ground truth data. In this study, energy and water flux estimates from diagnostic Atmosphere-Land Exchange (ALEXI) and prognostic Noah land surface models are compared over the Nile River basin between 2007 and 2011. A second remote sensing data set, generated with Penman-Monteith approach as implemented in the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 ET product, is also included as a comparative technique. In general, spatial and temporal distributions of flux estimates from ALEXI and Noah are similar in regions where the climate is temperate and local rainfall is the primary source of water available for ET. However, the diagnostic ALEXI model is better able to retrieve ET signals not directly coupled with the local precipitation rates, for example, over irrigated agricultural areas or regions influenced by shallow water tables. These hydrologic features are not well represented by either Noah or MOD16. Evaluation of consistency between diagnostic and prognostic model estimates can provide useful information about relative product skill, particularly over regions where ground data are limited or nonexistent as in the Nile basin.