Relative Evapotranspiration Research Articles

Impact of water stress on Mediterranean oak savanna grasslands productivity: Implications for on-farm grazing management

This study analyzes the productivity of grasslands in a Mediterranean oak-savanna ecosystem, focusing on its linkages with water availability. In these water-controlled ecosystems, grassland environmental preservation and sustainable management depend on quantitatively understanding these links. Productivity and water stress were modeled in southern Spain (2001–2018), integrating meteorological information and MODIS sensor data into a light-use efficiency model and a surface energy balance. The results provided valuable insights into how grasslands behaved during droughts at different spatiotemporal scales. During the most significant droughts, 2004/2005 and 2011/2012, aerial biomass production was reduced by 42 % and 67 %, respectively. The spatial analysis identified the central east side of the region, with low slopes and moderate tree cover, as the most productive area. The biomass production time series classification identified four distinct trends, all showing shifted relationships with similar slopes between production and anomalies of relative evapotranspiration. The seasonal analysis highlighted the importance of autumn, accounting for nearly 30 % of the annual biomass production, which was essential in years with spring water deficits. The proposed methodology provides on-farm grassland production curves depending on water availability (max-mean-min range with a mean error of 15.5 %). Together with weather forecast data, this could help farmers decide on the optimal level of management intensification and stocking rate. Although the regional specificity may limit the study’s direct applicability, this scheme offers valuable metrics that could be adapted to other areas under water scarcity conditions.

Improving the evapotranspiration estimation by coupling soil moisture and atmospheric variables in the relative evapotranspiration parameterization

Accurate monthly evapotranspiration (ET) estimation is essential for many forest, climate, and hydrological applications, as well as for some agricultural uses. In this study, the relationship between ET and relative evapotranspiration (F) using land surface, and atmospheric variables was assessed with 17 FLUXNET sites data in savanna, cropland, and forest land covers, distributed all over the world. A sigmoid (Fs) and a logarithmic (Fl) F expression were included in Walker et al.’s (2019a,b) equations to evaluate their impact on the accuracy of ET estimations. The new parameterizations of ET outperformed the original expression, showing root mean square errors lower than 24% of the mean observed ET. The results presented here suggest that atmospheric parameters, coupled with land explanatory variables included in F estimates, produce more precise ET estimations. In addition, Soil Moisture Active Passive (SMAP) products were used to obtain global maps of ET and compared with Global Landsurface Evaporation Amsterdam Methodology (GLEAM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 products, displaying the flexibility of these new parametrizations with different sources of data.

Exploring evapotranspiration stress in China: A blending approach employing multi-source remote sensing proxies

Study regionChina Study focusAn effective evapotranspiration stress assessment system requires reliable estimates actual evapotranspiration (ETa), and potential evapotranspiration (ETp), and should consider multiple influencing indicators. This study explores the consistency of multiple evaporation reanalysis datasets across mainland China and fuses them with multi-model ensemble method. To address the uncertainty inherent in the traditional evapotranspiration stress index (ESI) that only considers the ETa and ETp relationship, we employ Pearson Correlation Analysis and a Random Forest-based Boruta Algorithm to propose new evapotranspiration stress proxies blending multiple remote sensing indicators, named as MESI-P and MESI-B, respectively. Then, we verified their performance in depicting vegetation production capacity based on Solar-Induced Chlorophyll Fluorescence (SIF) and Gross Primary Productivity (GPP). New hydrological insights for the regionThe patterns of ETa from GLDAS, GLEAM, and Harvard Dataverse in China show consistent, but their threshold values differ. The synthesized ETa obtained after using a multi-model ensemble (MME) method is more adaptable in China, with a range of 0.45–1485.31 mm and an increase of 11.34 mm/10a. Following the same pattern as GLDAS and CRU, the synthetic ETp experiences an increasing trend (11.24 mm/10a) during 2000–2019. Compared with the traditional ESI, the MESI-P and MESI-B proposed in this study have superior signal convergence with ETa, SIF, and GPP due to the higher correlation coefficients (＞0.95) in China. Furthermore, during the calculation of MESI-B, soil moisture and solar radiation are identified as dominate factor in Northwest and Southern China respectively.

Sensitivity analysis of land and water productivities predicted with an empirical and a process-based root water uptake function

Rootzone hydraulic conditions govern root water uptake and transpiration under drought stress. Process-based approaches to predict the soil water status are advocated for an improved simulation of soil hydrology and crop yield. We investigated the sensitivity to system parameters in root water uptake simulation using a process-based function (MFlux) and an empirical function (Feddes) embedded in the SWAP hydrological model, applied to irrigated pasture scenarios in New Zealand. Data from two locations and three soils were used to simulate 42 growing seasons. The sensitivity analysis of both Feddes and MFlux parameters was performed for a rainfed and two irrigated scenarios, one triggering irrigation based on relative evapotranspiration (I–ETr), the other based on common practice using total available water (I–TAW). Results confirm that some parameters of the MFlux function are more sensitive than those from the Feddes function and both functions support the I–ETr criterion to optimize the water use in grazed pastures in New Zealand.

Farm-level Hydroeconomic Analysis of Alternative Water Tariff Charges Using a Hybrid Solution Method

This paper's main objective is to develop a farm-level water programming model to realistically model extensive margin and intensive margin responses resulting from deficit irrigation to the implementation of volumetric water charges. The highly complex programming model that uses the FAO56 water budget calculations to simulate crop water use while using relative evapotranspiration to estimate crop yield is solved using a hybrid procedure. The hybrid solution procedure uses a genetic algorithm to simplify the optimization model by fixing the irrigation schedule of each crop and then solving for the optimal water allocation amongst crops subject to water constraints. The area-based charges results showed that when irrigation application efficiency is low, irrigators could apply more water per hectare to sustain high crop yields without being held accountable if water quotas are exceeded. In contrast, irrigators with higher application efficiency could use less water than the area-based estimated water use. The results also showed that volumetric water charges cause both intensive margin and extensive margin responses. The conclusion of whether a volumetric-based water charging system will be better than area-based water charges is not straightforward because of differentiated impacts on profitability and hydrology. While irrigators will use irrigation water more efficiently and adopt more efficient irrigation technologies, their changed behavior could impact the hydrology of the water system through reduced return flows.

Assessment on irrigation system performance of sugarcane farm using remote sensing at lower Omo basin, Ethiopia

This study was aimed at assessing the irrigation system performance at Omo Kuraz Sugar Cane Development Project using data from remote sensing and meteorological stations. To analyze the distribution of evapotranspiration over the treatment area, the SEBAL (Surface Energy Balance Algorithm) model was used to evaluate the evapotranspiration (ET) rate for sugarcane at the lower Omo River Basin. Surface energy balance algorithm input like NDVI, Land surface temperature, TOA albedo and emissivity was calculated from Land Lat 8 image using the ENVI software. The data were collected from the farm site meteorology station, and the calculated evapotranspiration rate was one of the inputs into irrigation system performance indicators model, along with actual field data gathered from irrigation delivery schedule, root depth of crop at each growth stage, soil moisture before and after irrigation, and water diverted to the field. The four pillars of irrigation system performance are over all consumed ratio, depleted fraction, evaporative fraction, and relative evapotranspiration. This study also examined system performance using four standard indicators; namely, adequacy, efficiency, reliability, and equity. These indicators were calculated using the SEBAL algorithm and data were classified based on satellite and irrigation application. The findings of this study revealed that the irrigation system performed poorly with all treatment fields being below the target performance indicator values (overall water consumption ratio, ep; depleted fraction, DF; evaporative fraction, ᴧ and relative evapotranspiration, RET). The calculated crop water requirements using the SEBAL model and satellite data were not consistent with applied water. The findings from this study also showed that irrigation system performance indicator parameters were limited due to excessive water applied to the field. The study also revealed an acceptable range of RET (0.8, 0.9); however, the irrigation system's reliability was poor according to the results of field observations at the experimental site. This observation was due to the field receiving an excessive amount of water. These results and observations suggest that the irrigation agronomist should schedule irrigation water application based on crop water requirements to manage poor irrigation system performance. Key words: Irrigation system performance, SEBAL model, Remote sensing, Landsat 8, lower Omo Basin

Assessment of Irrigation Performance by Using Remote Sensing Techniques in Naryanpur Command Area, India

Assessment of irrigation performance for any irrigation scheme becomes necessary to know about effectiveness in terms of its operational management and socio-economic impacts. This study will focus on the performance assessment parameters computed using meteorological, optical datasets, and ground measurements for the Narayanpur Command Area. Net crop area is calculated for both Kharif and Rabi seasons using Optical Datasets for 2018-19. Atmospherically calibrated Sentinel 2 MSI images were used to identify major crop types by using supervised algorithms. Actual and Potential Evapotranspiration was also computed from meteorological datasets for the same duration. The surface Energy Balance algorithm was used for calculating potential Evapotranspiration. Crop water stress index and crop coefficient were computed and multiplied with potential evapotranspiration for getting actual evapotranspiration. It was observed that the actual evapotranspiration for both Kharif and Rabi crops varied from 700 mm to 1550 mm. The temporal scale for each growth stage was evaluated to analyse operational performance based on the growth phase of major crops grown in the Narayanpur command area. For performance assessment, depleted fraction, relative evapotranspiration, and relative water supply index were calculated. Most of the growth stages' depleted fractions varied from 0.6 to 0.9 and relative evapotranspiration varied from 0.7 to 0.92. The relative water supply for Kharif was estimated as 1.05 and for Rabi, it was 0.69.

Evapotranspiration characteristics and soil water balance of alfalfa grasslands under regulated deficit irrigation in the inland arid area of Midwestern China

Drought has been a major limiting factor affecting agricultural production in the world. Accurately quantitative analysis of the dynamic changes of evapotranspiration and soil water balance is very important for effectively managing water resources and improving water use efficiency under water scarcity. Soil water balance for perennial forage is more complex than the annuals due to stronger roots and periodic evapotranspiration. The objective was to explore the evapotranspiration characteristics and soil water balance of alfalfa (Medicago sativa L.) grasslands under border irrigation at different stand ages and irrigation treatments. A 3-yr field experiment with a full irrigation and 6 regulated deficit irrigation treatments was conducted, and growth-related indicators, soil evaporation and soil water dynamics were observed regularly. Daily evapotranspiration and soil water balance were computed using a modified dual-Kc model which is able to simulate evaporation and transpiration separately. The results showed that soil water simulated by the model and the measured value were in good agreement, and regression coefficients were higher than 0.6 and close to 1.0 in most cuts. The change trend of root zone water under deficit irrigation at single growth stages was similar to that under full irrigation. Under irrigation, the transpiration was the main water loss of alfalfa grasslands. The daily actual evapotranspiration of alfalfa in the 1st cut was higher than 8.0 mm d−1 and even over 15.0 mm d−1 at the middle and later growth stages. In contrast, in the 2nd and 3rd cut, it was always less than 10.0 mm d−1. The daily actual evapotranspiration decreased significantly and immediately after cutting, and daily actual transpiration was reduced to less than 1.0 mmd−1. The change trend of daily actual evapotranspiration under deficit irrigation at single growth stages was also similar to that under full irrigation. The seasonal evapotranspiration could reach 800 mm and was reduced by deficit irrigation. The average proportion of soil evaporation to total evapotranspiration was 18%. With the decrease of irrigation amount, the evapotranspiration, transpiration and irrigation water compensation decreased, while evaporation remained relatively stable and the ratio of evaporation to evapotranspiration increased. A lower relative evapotranspiration deficit (0.041) was obtained under moderate deficit irrigation at the budding stage than those in other deficit cases (0.086 or over). In conclusion, in the arid and semi-arid areas, deficit irrigation could be applied to alfalfa grassland at the budding stage in alfalfa production.

Evaluating Irrigation Performance and Water Productivity Using EEFlux ET and NDVI

Southern California’s Imperial Valley (IV) faces serious water management concerns due to its semi-arid environment, water-intensive crops and limited water supply. Accurate and reliable irrigation system performance and water productivity information is required in order to assess and improve the current water management strategies. This study evaluates the spatially distributed irrigation equity, adequacy and crop water productivity (CWP) for two water-intensive crops, alfalfa and sugar beet, using remotely sensed data and a geographical information system for the 2018/2019 crop growing season. The actual crop evapotranspiration (ETa) was mapped in Google Earth Engine Evapotranspiration Flux, using the linear interpolation method in R version 4.0.2. The approx() function in the base R was used to produce daily ETa maps, and then totaled to compute the ETa for the whole season. The equity and adequacy were determined according to the ETa’s coefficient of variation (CV) and relative evapotranspiration (RET), respectively. The crop classification was performed using a machine learning approach (a random forest algorithm). The CWP was computed as a ratio of the crop yield to the crop water use, employing yield disaggregation to map the crop yield, using county-level production statistics data and normalized difference vegetation index (NDVI) images. The relative errors (RE) of the ETa compared to the reported literature values were 7–27% for alfalfa and 0–3% for sugar beet. The average ETa variation was low; however, the spatial variation within the fields showed that 35% had a variability greater than 10%. The RET was high, indicating adequate irrigation; 31.5% of the alfalfa and 12% of the sugar beet fields clustered in the Valley’s central corner were consuming more water than their potential visibly. The CWP showed wide variation, with CVs of 32.92% for alfalfa and 25.4% for sugar beet, signifying a substantial scope for CWP enhancement. The correlation between the CWP, ETa and yield showed that reducing the ETa to approximately 1500 mm for alfalfa and 1200 mm for sugar beet would help boost the CWP without decreasing the yield, which is nearly equivalent to 44.52M cu. m (36,000 acre-ft) of water. The study’s results could help water managers to identify poorly performing fields where water conservation and management could be focused.

Comparison of reference evapotranspiration estimation methods, on days with and without precipitation

Water is gradually becoming scarcer and more expensive. Therefore, any means that aims at a more efficient use of this substance in the most diverse sectors, becomes essential. In this context, the accurate estimation of evapotranspiration is of fundamental importance. With this in mind, the objective of this work was to compare the performance of different methodologies for estimating reference evapotranspiration in relation to the FAO Penman-Monteith method on days with and without precipitation in the region of Cambará do Sul/RS. To achieve this goal, daily data on maximum air temperature (°C), minimum temperature (°C), relative air humidity (%), dew point temperature (°C), wind speed at 2 m high (m s-1), atmospheric pressure (hPa) and global solar radiation (MJ m-2 d-1), were acquired from the automatic weather station located in Cambará do Sul/RS and divided into two sets (days with and without precipitation ). The comparison between the different methodologies and the standard method, for each period mentioned above, took place through a simple linear regression analysis to obtain the regression coefficients a and b and the determination coefficient. Subsequently, Pearson's correlation coefficient, root of the mean square of the error, Willmott index and the Camargo and Sentelhas index were calculated . For the municipality of Cambará do Sul/RS to replace the Penman-Monteith method, we recommend the use of the Penman and Makkink methods, which presented satisfactory performance in all periods analyzed.

Comparison of Three Different Satellite-Based Approaches for Aboveground Biomass Estimation

Effective estimation of crop yield on a regional scale in a short time with low cost would only be possible utilizing remote sensing. Several approaches have been proposed based on remotely sensed data for estimating Aboveground Biomass (AGB). In this study, three satellite-based approaches, including Radiation Use Efficiency (RUE). The soil water atmosphere plant (SWAP) model, and FAO33, were evaluated in the irrigated wheat and barley fields in the Qazvin irrigation network, Iran. To this end, the leaf area index (LAI) and relative evapotranspiration (ETrel) were extracted from the Landsat data and incorporated into the methods. A comparative analysis was undertaken to evaluate the performance of the satellite-based approaches using percent absolute error (PAE). By updating SWAP with satellite-derived LAI and surface incoming solar radiation, the PAE decreased significantly. Results of different Spectral Indices (SIs) in the RUE method showed that NDVI performed best with PAE of 1.52 percent and RMSE of 664.6 kg ha−1. Also, the RUE method with RMSE of 664.6 kg ha−1 had 4.7 and 23.8 lower PAE compared to the SWAP (RMSE = 2221.4 kg ha−1) and FAO33 (RMSE = 4394.2 kg ha−1), respectively. However, this was not the only criteria for a well-performed method, because earlier AGB forecast was only feasible by making use of SWAP since the satellite-derived parameters were only incorporated into the model about one month before the harvest.

Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data

This paper analyses the effect of the spatial assessment scale on irrigation performance indicators in small and medium-scale agriculture. Three performance indicators—adequacy (i.e., sufficiency of water use to meet the crop water requirement), equity (i.e., fairness of irrigation distribution), and productivity (i.e., unit of physical crop production/yield per unit water consumption)—are evaluated in five irrigation schemes for three spatial resolutions—250 m, 100 m, and 30 m. Each scheme has varying plot sizes and distributions, with average plot sizes ranging from 0.2 ha to 13 ha. The datasets are derived from the United Nations Food and Agricultural Organization (FAO) water productivity through open access of remotely sensed–derived data (the Water Productivity Open Access Portal—WaPOR) database. Irrigation indicators performed differently in different aspects; for adequacy, all three resolutions show similar spatial trends for relative evapotranspiration (ET) across levels for all years. However, the estimation of relative ET is often higher at higher resolution. In terms of equity, all resolutions show similar inter-annual trends in the coefficient of variation (CV); higher resolutions usually have a higher CV of the annual evapotranspiration and interception (ETIa) while capturing more spatial variability. For productivity, higher resolutions show lower crop water productivity (CWP) due to higher aboveground biomass productivity (AGBP) estimations in lower resolutions; they always have a higher CV of CWP. We find all resolutions of 250 m, 100 m, and 30 m suitable for inter-annual and inter-scheme assessments regardless of plot size. While each resolution shows consistent temporal trends, the magnitude of the trend in both space and time is smoothed by the 100 m and 250 m resolution datasets. This frequently results in substantial differences in the irrigation performance assessment criteria for inter-plot comparisons; therefore, 250 m and 100 m are not recommended for inter-plot comparison for all plot sizes, particularly small plots (<2 ha). Our findings highlight the importance of selecting the spatial resolution appropriate to scheme characteristics when undertaking irrigation performance assessment using remote sensing.

Spatiotemporal Assessment of Irrigation Performance of the Kou Valley Irrigation Scheme in Burkina Faso Using Satellite Remote Sensing-Derived Indicators

Traditional methods based on field campaigns are generally used to assess the performance of irrigation schemes in Burkina Faso, resulting in labor-intensive, time-consuming, and costly processes. Despite their extensive application for such performance assessment, remote sensing (RS)-based approaches remain very much underutilized in Burkina Faso. Using multi-temporal Landsat images within the Python module for the Surface Energy Balance Algorithm for Land model, we investigated the spatiotemporal performance patterns of the Kou Valley irrigation scheme (KVIS) during two consecutive cropping seasons. Four performance indicators (depleted fraction, relative evapotranspiration, uniformity of water consumption, and crop water productivity) for rice, maize, and sweet potato were calculated and compared against standard values. Overall, the performance of the KVIS varied depending on year, crop, and the crop’s geographical position in the irrigation scheme. A gradient of spatially varied relative evapotranspiration was observed across the scheme, with the uniformity of water consumption being fair to good. Although rice was the most cultivated, a shift to more sweet potato farming could be adopted to benefit more from irrigation, given the relatively good performance achieved by this crop. Our findings ascertain the potential of such RS-based cost-effective methodologies to serve as basis for improved irrigation water management in decision support tools.

Modeling tomato evapotranspiration and yield responses to salinity using different macroscopic reduction functions

AbstractPlant responses to salinity can be used to manage irrigation with brackish water. This study evaluated effects of brackish water irrigation on tomato (Solanum lycopersicum L.) plants, proposed a new model to describe plant relative evapotranspiration (ET) and relative yield as a function of electrical conductivity of soil saturated paste extract (ECe), and compared the estimations of the new model with four other models (linear model of Mass and Hoffman, and three nonlinear models of van Genuchten, Dirksen, and Homaee). A greenhouse experiment was conducted with five salinity treatments: tap water of EC 0.6, brackish groundwater of EC 2 and 3, and reverse osmosis (RO) of EC 4 and 6 dS m−1. Results indicated no changes in leaf photosynthesis rate (Pn), transpiration rate (Tr), and stomatal conductance (Gs) up to 2 dS m−1 irrigation water salinity. Nonlinear models better described tomato yield and seasonal ET. The proposed new model performed best when compared with four previous models to predict tomato yield and ET responses to salinity. The calculated soil salinity threshold values (ECe*) from the new model were 1.73 dS m−1 for yield and 2.52 dS m−1 for ET. Data from published studies on effects of irrigation water salinity (ECw) on tomato yield and ET were analyzed to validate models. The results showed that the new model was simpler and superior in estimating plant responses to ECw. Tomato is a salt‐sensitive crop, and irrigation with brackish waters adversely influences growth and ET.

Multi-Temporal Variabilities of Evapotranspiration Rates and Their Associations with Climate Change and Vegetation Greening in the Gan River Basin, China

Understanding the spatial-temporal dynamics of evapotranspiration in relation to climate change and human activities is crucial for the sustainability of water resources and ecosystem security, especially in regions strongly influenced by human impact. In this study, a process-based evapotranspiration (ET) model in conjunction with the Global Land Surface Satellite (GLASS) LAI dataset was used to characterize the spatial-temporal pattern of evapotranspiration from 1982 to 2016 over the Gan River basin (GRB), the largest sub-basin of the Poyang Lake catchment, China. The results showed that the actual annual ET (ETa) weakly increased with an annual trend of 0.88 mm year−2 from 1982 to 2016 over the GRB, along with a slight decline in annual potential ET (ETp). On an ecosystem scale; however, only the evergreen broadleaved forest and cropland presented a positive ETa trend, while the rest of the ecosystems demonstrated negative trends of ETa. Both correlation analysis and sensitivity analysis revealed a close relationship between ETa inter-annual variability and energy availability. Attribution analysis illustrated that contributions of climate change and vegetation greening on the ETa trend were −0.48 mm year−2 and 1.36 mm year−2, respectively. Climate change had a negative impact on the ETa trend over the GRB. However, the negative effects have been offset by the positive effects of vegetation greening, which mainly resulted from the large-scale revegetation in forestland and agricultural practices in cropland. It is concluded that large-scale afforestation and agricultural management were the main drivers of the long-term evolution of water consumption over the GRB. This study can improve our understanding of the interactive effects of climate change and human activities on the long-term evolution of water cycles.

Quantitative and qualitative analysis of sugarcane productivity in function of air temperature and water stress

Climate variables can influence the both productivity and quality of the commercial product of sugarcane crop. This study aimed to evaluate the influence of thermal time, negative degree-days and water deficit on productivity and industrial quality of sugarcane for the Goiás Brazilian Savanna region. The data of productivity and industrial quality were obtained in the field (Plant Centro Álcool®) and climate data in the weather station. Thermal time and the accumulation of negative degree-days in cycles showed significant correlations with the yield. The highest (340 mm) and the lowest (158 mm) accumulated water deficit blade not reflected in lower productivity and greater, respectively. Relative evapotranspiration (rET) was equal at 1.0 in more than 50% of the studied period, in which not were found significant correlations between the rET<1 with the productivity and industrial quality. We found significant correlations between rates of degree-days and negative degree-days with productivity rates; however, there was a low correlation between the water deficit rates and productivity. The total recoverable sugars rates and total soluble solids showed maximum accumulation point only in function of degree-day rates. We conclude that the thermal time has greater influence on yield decrease of sugarcane with different harvest cycles, significantly contributing to the accumulation of sugars in the stem.

Efeito das condições climáticas na ocorrência de endoparasitos de ovinos

This study evaluated the effect of climatic conditions on the occurrence of Eimeria sp., strongylids and Moniezia sp. by analyzing the excretion of eggs and oocysts in the feces of sheep. In all, 3,509 coproparasitological examinations were performed after the monthly collection of feces of 121 sheep for 29 months. The meteorological data collected were rainfall, insolation, evapotranspiration, relative humidity, and temperature. Principal component analysis was performed to summarize the number of climatic variables. To evaluate the climatic vectors that influenced the variables, Eimeria sp., strongylids and Moniezia sp., a spatial projection of the ordination of vectors on the first two principal components was performed. To evaluate the mean values of the variables, Eimeria sp., strongylids and Moniezia sp., a cluster analysis was performed (k-means clustering), according to the categories. An association of Eimeria sp. and strongylids with relative humidity and rainfall was observed. Moniezia sp. was also related to the minimum temperature. The prevalence of Moniezia sp. was the least affected by relative humidity, rainfall, insolation, and evapotranspiration. The highest counts of endoparasites were observed in the offspring category and in the months of higher rainfall.

Regional evapotranspiration estimates using the relative soil moisture ratio derived from SMAP products

Evapotranspiration (ET) is the main water loss in water balance, particularly in arid and semiarid regions. In the last decades, remote sensing technology has been providing valuable information to monitor ET at large scale. In this study, a modification of the relative evapotranspiration (F) parameter introduced by Venturini et al. (2008) is presented. The surface actual water vapor pressure (es) is estimated incorporating surface texture information and the soil moisture (SM) content, as proposed by Deardorff (1978). The introduction of SM content in es estimation led to a physically meaningful estimation of the traditional F formulation. As a result, the original Venturini et al.’s ET application is simpler, more flexible and robust. The results presented here were calculated from the Soil Moisture Active Passive (SMAP) products with two different spatial resolutions 36 and 3 km, to compute regional ET. The proposed ET model was validated using ground observations from Bowen Ratio stations and Eddy Covariance towers. The ET results with a spatial resolution of 36 km showed good agreement with ground data, with a root mean square error varying from 0.91 to 1.22 mm/d. The recently released SMAP SM product at 3 km produces ET estimates with a root mean square error of 0.63 mm/d for autumn-winter season. The new ET model results were also compared with the well-known ET MYD16A2 product, making evident that the proposed approach outreaches the Moderate Resolution Imaging Spectroradiometer (MODIS) methodology. The preliminary results presented with our simple, flexible, universal and robust ET equation using SMAP SM, are promising.

Variations in Soil Water Content and Evapotranspiration in Relation to Precipitation Pulses within Desert Steppe in Inner Mongolia, China

Neither single nor discontinuous hydrological observation data can truly reflect periodic changes in soil moisture under natural conditions or interrelationships between various water sources. Therefore, in this study, precipitation pulse characteristics and variations in the soil water content (SWC) and actual evapotranspiration (ETa) in relation to pulses are explored through a field multi-water continuous observation system set in desert steppe in Inner Mongolia, China. A comparison between precipitation events in the growing seasons of 2016 and 2017 shows that precipitation events that are greater than 10 mm are the main cause of dramatic interannual precipitation variations in this region. A single small precipitation event has a limited impact on SWC and provides no obvious increase in the SWC within the top 10 cm soil layer. The precipitation interval ratio (P/I) is suitable for comparing water stresses of different drying-wetting cycles, and correlations between soil layers are found to be closer in humid years than in dry years. In this study, three modes of interpulse ETa in the desert steppe are discussed: a stable ETa mode under a water-sufficient condition, an attenuation ETa mode, and a stable ETa mode under extreme drought conditions.

Evapotranspiration estimation using SMAP soil moisture products and bouchet complementary evapotranspiration over Southern Great Plains

Evapotranspiration (ET) is an important water withdrawal in the water balance, particularly in arid and semiarid regions. In this study, a formulation to derive the relative evapotranspiration (β) and ET from in situ and passive microwave data, is presented. The original Komatsu's β equation was modified by introducing a calibration parameter to eliminate the wind speed effects. Then, a simple formulation to estimate mean daily ET was obtained by combining the β parameter, Bouchet's complementary relationship, and Priestley-Taylor's equation. Estimates of β and ET were compared with ground observations in the study area, Southern Great Plains (SGP). These comparisons suggest that β characterizes the relative evapotranspiration behavior in the region. Besides, ET results show a good agreement with ground data, yielding a root mean square error and bias of 28.5 and −6 W/m2, respectively. The proposed approach took advantages of passive microwave images, combining them with ground observations in a simple and robust equation.