Surface Energy Balance System Research Articles

Higher temporal evapotranspiration estimation with improved SEBS model from geostationary meteorological satellite data

Evapotranspiration (ET) is a key variable in hydrologic cycle that directly affects the redistribution of precipitation and surface balance. ET measurements with high temporal resolution are required for coupling with models of highly dynamic processes, e.g., hydrological and land surface processes. The Haihe River Basin is the focus of China’s industrial base and it is one of the three major grain-producing regions within the country. However, this area is facing serious water resource shortages and water pollution problems. The present study used geostationary satellite remote sensing data, in situ meteorological observations, and the surface energy balance system (SEBS) model with a new kB−1 parameterization to estimate 3-hourly and daily energy and water fluxes in the Haihe River Basin. The results of the SEBS model were validated with point-scale data from five observation flux towers. Validation showed that 3-hourly and daily ET derived from the SEBS model performed well (R2 = 0.67, mean bias = 0.027 mm/h, RMSE = 0.1 mm/h). Moreover, factors influencing ET were also identified based on the results of this study. ET varies with land cover type and physical and chemical properties of the underlying surface. Furthermore, ET is also controlled by water availability, radiation, and other atmospheric conditions. It was found that ET had strong correlation with the normalized difference vegetation index (NDVI). Specifically, daily ET fluctuated with the NDVI when the NDVI was <0.29, and ET increased rapidly as the NDVI increased from 0.29 to 0.81. For NDVI values >0.81, indicating a state of saturation, the rate of increase of ET slowed. This research produced reliable information that could assist in sustainable management of the water resources and in improved understanding of the hydrologic cycle of the Haihe River Basin.

Optimization of a remote sensing energy balance method over different canopy applied at global scale

Parameterization methods which calculate turbulent heat and water fluxes with thermal remote sensing data were evaluated in the revised remote sensing surface energy balance system (SEBS) model (Chen et al., 2013). The model calculates sensible heat (H) based on the Monin-Obukhov similarity theory (MOST) and determines latent heat (LE) as the residual of energy balance. We examined the uncertainties of H and LE in the SEBS model due to five key parameters at the local station point scale. Observations at 27 flux towers located in seven land cover types (needle-leaf forest, broadleaf forest, shrub, savanna, grassland, cropland, and sparsely vegetated land) and an artificial intelligence particle swarm optimization (PSO) algorithm was combined to calibrate the five parameters (leaf drag coefficient, leaf heat transfer coefficients, roughness length for soil, and two parameters for ground heat calculation) in the SEBS model. The root-mean-square error at the site scale was reduced by 9 Wm−2 for H, and 92 Wm−2 for LE, and their correlation coefficients were increased by 0.07 (H) and 0.11 (LE) after using the calibrated parameters. The updated model validation was further conducted globally for the remotely sensed evapotranspiration (ET) calculations. Overestimation of SEBS global ET was significantly improved by using the optimized values of the parameters. The results suggested PSO was able to consistently locate the global optimum of the SEBS model, and appears to be capable of solving the ET model optimization problem.

Comparison of two remote sensing models for estimating evapotranspiration: algorithm evaluation and application in seasonally arid ecosystems in South Africa

Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration (ET) models in recent years, important information gaps still exist on the accuracy of the models particularly in arid and semi-arid environments. In this study, we evaluated the Penman-Monteith based MOD16 and the modified Priestley-Taylor (PT-JPL) models at the daily time step against three measured ET datasets. We used data from two summer and one winter rainfall sites in South Africa. One site was dominated by native broad leaf and the other by fine leafed deciduous savanna tree species and C4 grasses. The third site was in the winter rainfall Cape region and had shrubby fynbos vegetation. Actual ET was measured using open-path eddy covariance systems at the summer rainfall sites while a surface energy balance system utilizing the large aperture boundary layer scintillometer was used in the Cape. Model performance varied between sites and between years with the worst estimates (R2<0.50 and RMSE>0.80 mm/d) observed during years with prolonged mid-summer dry spells in the summer rainfall areas. Sensitivity tests on MOD16 showed that the leaf area index, surface conductance and radiation budget parameters had the largest effect on simulated ET. MOD16 ET predictions were improved by: (1) reformulating the emissivity expressions in the net radiation equation; (2) incorporating representative surface conductance values; and (3) including a soil moisture stress function in the transpiration sub-model. Implementing these changes increased the accuracy of MOD16 daily ET predictions at all sites. However, similar adjustments to the PT-JPL model yielded minimal improvements. We conclude that the MOD16 ET model has the potential to accurately predict water use in arid environments provided soil water stress and accurate biome-specific parameters are incorporated.

Evaluating the accuracy of satellite-derived evapotranspiration estimates acquired during conditions of water stress

ABSTRACT Surface energy balance models such as the surface energy balance system (SEBS) assume that the influence of soil moisture and biophysical parameters on evapotranspiration (ET), are implicitly encompassed in model input variables such as the land surface temperature. This simplification may generally be suitable for environments in which the available energy constrains ET but may prove to be inadequate during suboptimal environmental conditions. To address this limitation, the SEBSESF approach was proposed to better represent the influence of environmental stress on surface energy fluxes, using an empirically derived calibration factor to adjust the evaporative fraction previously determined in SEBS. SEBSESF was evaluated by comparing the modelled ET estimates against Eddy Covariance ET measurements (ECET) at two sites, with contrasting environmental conditions. Comparisons between ECET and modelled ET indicated that the implementation of SEBSESF resulted in an improved correlation between ECET and modelled ET estimates, as well as an increase in the percentage of modelled ET estimates within an acceptable accuracy range (± 15 to 30%). Overall, the results of the study demonstrate how potential improvements in the mapping of ET within arid and semi-arid environments can be achieved by accounting for environmental stress. This in turn provides an opportunity to better understand and quantify energy and water fluxes, using satellite-based ET estimation approaches.

SENSITIVITY OF ACTUAL EVAPOTRANSPIRATION ESTIMATION USING THE SEBS MODEL TO VARIATION OF INPUT PARAMETERS (LST, DSSF, AERODYNAMICS PARAMETERS, LAI, FVC)

Abstract. Actual Evapotranspiration (AET) is a key component of the water and energy balance and hydrological regime of catchments. A land surface energy balance system model (SEBS) was used to estimate the AET of the 160100-km² Medjerda river basin in Northern Tunisia. This model uses satellite data in combination with meteorological data. In this study, we investigated the sensitivity of the AET model output to five major input variables: the 30-minute Downward Surface Shortwave solar radiation fluxes (DSSF), and Land Surface Temperatures (LST), the roughness height for momentum transfer z0m, and the influence of the spatial resolution of satellite-based Leaf Area Index (LAI) and fraction of Vegetation Cover (FVC) estimates. The DSSF product was validated using a comparison to solar radiation estimates by the Angstrom formula based on in-situ station data. Gaps in the 15-min satellite-based land surface temperature time series were filled using a sinusoidal model on pixels containing meteorological stations. One-half to two standard deviations of the errors of the regression curves were applied to analyse the sensitivity of the SEBS output. Two methods to estimate the near surface aerodynamic parameter z0m were applied and compared. Maps of LAI and FVC derived from two sensors alternatively applied as an input to the SEBS model. A sensitivity analysis, performed in the first decade of May 2010, showed that SEBS model parameterization is quite sensitive in the forestland cover type. The difference can be up to 0.3 mm day−1. For agricultural land areas, representing an important percentage of the Medjerda basin, AET estimations based on the SEBS model proved to be used to satisfy the actual evapotranspiration estimates.

Evapotranspiration Estimation Using Surface Energy Balance System Model: A Case Study in the Nagqu River Basin

Calculation of actual evapotranspiration (AET) is of vital importance for the study of climate change, ecosystem carbon cycling, flooding, drought, and agricultural water demand. It is one of the more important components in the hydrological cycle and surface energy balance (SEB). How to accurately estimate AET especially for the Tibetan Plateau (TP) with complex terrain remains a challenge for the scientific community. Using multi-sensor remote sensing data, meteorological forcing data, and field observations, AET was derived for the Nagqu river basin of the Northern Tibetan Plateau from a surface energy balance system (SEBS) model. As inputs for SEBS, improved algorithms and datasets for land surface albedo and a cloud-free normalized difference vegetation index (NDVI) were also constructed. The model-estimated AET were compared with results by using the combinatory method (CM). The validation indicated that the model estimates of AET agreed well with the correlation coefficient, the root mean square error, and the mean percentage error of 0.972, 0.052 mm/h, and −10.4%, respectively. The comparison between SEBS estimation and CM results also proved the feasibility of parameterization schemes for land surface parameters and AET.

Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests

Evapotranspiration (ET) is considered a key variable in the understanding of the Amazonian tropical forests and their response to climate change. Remote-Sensing (RS) based evapotranspiration models are presented as a feasible means in order to provide accurate spatially-distributed ET estimates over this region. In this work, the performance of four commonly used ET RS models was evaluated over Amazonia using Moderate Resolution Imaging Spectroradiometer (MODIS) data. RS models included i) Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), ii) Penman-Monteith MODIS operative parametrization (PM-Mu), iii) Surface Energy Balance System (SEBS), and iv) Satellite Application Facility on Land Surface Analysis (LSASAF). These models were forced using two ancillary meteorological data sources: i) in-situ data extracted from Large-Scale Biosphere-Atmosphere Experiment (LBA) stations (scenario I), and ii) three reanalysis datasets (scenario II), including Modern-Era Retrospective analysis for Research and Application (MERRA-2), European Centre for Medium-range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim), and Global Land Assimilation System (GLDAS-2). Performance of algorithms under the two scenarios was validated using in-situ eddy-covariance measurements. For scenario I, PT-JPL provided the best agreement with in-situ ET observations (RMSE = 0.55 mm/day, R = 0.88). Neglecting water canopy evaporation resulted in an underestimation of ET measurements for LSASAF. SEBS performance was similar to that of PT-JPL, nevertheless SEBS estimates were limited by the continuous cloud cover of the region. A physically-based ET gap-filling method was used in order to alleviate this issue. PM-Mu tended to overestimate in-situ ET observations. For scenario II, quality assessment of reanalysis input data demonstrated that MERRA-2, ERA-Interim and GLDAS-2 contain biases that impact model performance. In particular, biases in radiation inputs were found the main responsible of the observed biases in ET estimates. For the region, MERRA-2 tends to overestimate daily net radiation and incoming solar radiation. ERA-Interim tends to underestimate both variables, and GLDAS tends to overestimate daily radiation while underestimating incoming solar radiation. Discrepancies amongst these reanalysis inputs generally explain the observed discrepancies in model spatial and temporal patterns.

Evaluation of Evapotranspiration over a Semiarid Region Using Multiresolution Data Sources

AbstractEvapotranspiration (ET) estimation is important for water management decision tools. In this study, different ET data with varying resolution, accuracy, and functionality were reviewed over a semiarid, data-sparse region in southern Iran. Study results showed that the widely used reanalysis and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets have relatively high uncertainty and underestimated ET over the sparse heterogeneous landscape. On the other hand, fine-resolution ET datasets using Landsat imagery with Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Surface Energy Balance System (SEBS) algorithms, yielded high accuracy. Evaluation of METRIC and SEBS models in estimating seasonal crop water use showed a mean absolute error of 5% and 13%, respectively. The Satellite Application Facility on Climate Monitoring (CMSAF) data were used as radiation input to the models and were found to be a representative data source with daily average RMSE of 70 W m−2. An average crop coefficient Kc was estimated for the region and was obtained as 0.77. The study proposes and applies a hybrid framework that uses reference ET from simple diagnostic models (such as the REF-ET tool) and calculates actual ET by using the satellite-derived regionally and locally representative Kc values. The ET estimates generated with the framework were regionally representative and required low computational resources. The study findings have the potential to provide practical guidance to local farmers and water managers to generate useful and usable decision-making tools, especially for ET assessments in the study region and other data-sparse areas.

Estimation of hourly land surface heat fluxes over the Tibetan Plateau by the combined use of geostationary and polar-orbiting satellites

Abstract. Estimation of land surface heat fluxes is important for energy and water cycle studies, especially on the Tibetan Plateau (TP), where the topography is unique and the land–atmosphere interactions are strong. The land surface heating conditions also directly influence the movement of atmospheric circulation. However, high-temporal-resolution information on the plateau-scale land surface heat fluxes has been lacking for a long time, which significantly limits the understanding of diurnal variations in land–atmosphere interactions. Based on geostationary and polar-orbiting satellite data, the surface energy balance system (SEBS) was used in this paper to derive hourly land surface heat fluxes at a spatial resolution of 10 km. Six stations scattered throughout the TP and equipped for flux tower measurements were used to perform a cross-validation. The results showed good agreement between the derived fluxes and in situ measurements through 3738 validation samples. The root-mean-square errors (RMSEs) for net radiation flux, sensible heat flux, latent heat flux and soil heat flux were 76.63, 60.29, 71.03 and 37.5 W m−2, respectively; the derived results were also found to be superior to the Global Land Data Assimilation System (GLDAS) flux products (with RMSEs for the surface energy balance components of 114.32, 67.77, 75.6 and 40.05 W m−2, respectively). The diurnal and seasonal cycles of the land surface energy balance components were clearly identified, and their spatial distribution was found to be consistent with the heterogeneous land surface conditions and the general hydrometeorological conditions of the TP.

Impact of land use and land cover transitions and climate on evapotranspiration in the Lake Naivasha Basin, Kenya

The Lake Naivasha Basin in Kenya has experienced significant land use cover changes (LUCC) that has been hypothesized to have altered the hydrological regime in recent decades. While it is generally recognized that LUCC will impact evapotranspiration (ET), the precise nature of such impact is not very well understood. This paper describes how land use conversions among grassland and croplands have influenced ET in the Lake Naivasha Basin for the period 2003 to 2012. MODIS data products were used in combination with the European Centre for Medium-Range Weather Forecasts (ECMWF) data sets to model ET using the Surface Energy Balance System (SEBS). The results indicate that conversions from grassland to cropland accounted for increases in ET of up to 12% while conversion from cropland back to grasslands (abandonment) reduced ET by ~4%. This suggests that recently cultivated agricultural lands could increase local water demands, while abandonment of the farms could decrease the water loss and eventually increase the water availability. Also, recovery of ET following re-conversion from cropland to grassland might be impeded due to delayed recovery of soil properties since parts of the catchment are continuously being transformed with no ample time given for soil recovery. The annual ET over the 10 years shows an estimated decline from 724 mm to 650 mm (~10%). This decline is largely explained by a reduction in net radiation, an increase in actual vapour pressure whose net effect also led to decrease in the surface-air temperature difference. These findings suggest that in order to better understand LUCC effects on water resources of Lake Naivasha, it is important to take into account the effect of LUCC and climate because large scale changes of vegetation type from grassland to cropland substantially will increase evapotranspiration with implications on the water balance.

A Modeling Framework for Deriving Daily Time Series of Evapotranspiration Maps Using a Surface Energy Balance Model

Surface energy balance models have been one of the most widely used approaches to estimate spatially distributed evapotranspiration (ET) at varying landscape scales. However, more research is required to develop and test an operational framework that can address all challenges related to processing and gap filling of non-continuous satellite data to generate time series of ET at regional scale. In this study, an automated modeling framework was developed to construct daily time series of ET maps using MODIS imagery and the Surface Energy Balance System model. The ET estimates generated from this modeling framework were validated against observations of three eddy-covariance towers in Oklahoma, United States during a two-year period at each site. The modeling framework overestimated ET but captured its spatial and temporal variability. The overall performance was good with mean bias errors less than 30 W m−2 and root mean square errors less than 50 W m−2. The model was then applied for a 14-year period (2001–2014) to study ET variations across Oklahoma. The statewide annual ET varied from 841 to 1100 mm yr−1, with an average of 994 mm yr−1. The results were also analyzed to estimate the ratio of estimated ET to reference ET, which is an indicator of water scarcity. The potential applications and challenges of the ET modeling framework are discussed and the future direction for the improvement and development of similar automated approaches are highlighted.

Satellite-based analysis of regional evapotranspiration trends in a semi-arid area

ABSTRACTA regional framework for a spatial and temporal distributed assessment of time series trends in the hydrological variable and its related ecological factors of an arid area was presented in this research. To achieve this, we tested the Surface Energy Balance System (SEBS) algorithm for estimating evapotranspiration (ET) in regional scale and the result was further validated by water budget. The ET assessment was applied for the Yinchuan and Weining (YW) Plains (China), the upstream areas of the Yellow River. Moreover, we analysed the recent trends (from year 2001 to 2014) in actual ET, normalized difference vegetation index (NDVI), farmland and wetland using a combination of remote sensing and ground observations. The results illustrated that the yearly ET of 78% areas has no change during the study period and the areas with decreasing ET are larger than the areas with increasing trend. The highest decreasing rate is observed in urban areas and the value is –20 mm year–1, while the rate of increasing trend is especially higher in the wetlands reaching around 60 mm year–1. This phenomenon can be explained by changes in NDVI, farmland and wetland. The distribution and magnitude of NDVI trends shows that the higher NDVI (NDVI > 0.4) area is occupied 56% and the farmland (NDVI > 0.55) covered about 35% of the YW Plains. The increasing trends of mean NDVI is mostly observed in farmland and shrub covers, while the decreasing NDVI areas are mainly wetlands and urban area. The emerging image showed that the greening trend of vegetation and variation of evapotranspiration in the YW Plains are related to land-cover changes and to the adjustment of crop pattern for agriculture. The increasing of wetland area is also believed as a cause related to evapotranspiration change. Such spatiotemporally distributed analysis in regional level is important for water management at this scale, which can be also applied to other similar areas.

西北干旱区河西走廊荒漠绿洲土地覆盖类型与蒸散的关系研究——基于Landsat 8和ZY3数据融合

PDF HTML阅读 XML下载 导出引用 引用提醒 西北干旱区河西走廊荒漠绿洲土地覆盖类型与蒸散的关系研究——基于Landsat 8和ZY3数据融合 DOI: 10.5846/stxb201807161532 作者: 作者单位: 中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室/中国科学院大学。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室/中国科学院大学。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室/中国科学院大学。 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2017YFC0504303）；国家自然科学基金项目（41771041，41501044，41701035） Relationship between land cover type and evapotranspiration on the basis of Landsat 8 and ZY3 data fusion approach for a desert oasis in the middle Hexi corridor area of the arid regions of northwestern China Author: Affiliation: Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, University of Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, University of Chinese Academy of Sciences.,Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, University of Chinese Academy of Sciences. Fund Project: National Key Research and Development Plan（2017YFC0504303）；The National Natural Science Foundation of China （41771041；41501044；41701035） 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:蒸散是地表水热平衡的重要分量，也是陆地生态过程与水文过程之间的重要纽带，尤其在干旱区地-气相互作用、碳循环、水循环等过程所包含的物质与能量交换中占有极其重要的地位。基于Landsat 8遥感影像和资源三号影像（ZY3）的高分辨率植被信息，利用SEBS模型对西北干旱区河西走廊中段临泽绿洲北部区域地表蒸散量进行了估算，并用绿洲内部和绿洲-荒漠过渡带两个通量塔涡动相关数据对模型进行评估，分析了不同土地覆盖类型对蒸散量空间分布的影响。结果表明：（1） SEBS模型模拟值与实测日蒸散值之间拟合效果较好，且在均一地表时（绿洲农田区）估算精度更高（R2=0.96，P < 0.001），RMSE、MAE分别为0.84 mm/d、0.56 mm/d；（2）从季节变化来看蒸散量与作物生长密切相关，夏季灌溉和降雨使得研究区水分充足，植被覆盖度高，蒸散量相应增加，在绿洲地区可达5.95 mm/d，而冬季最小仅为0.52 mm/d；（3）从蒸散量的空间变化来看，水体蒸散值最大，其余依次为农田、防护林、裸地和灌木丛，说明除水体外，随着植被覆盖的增大，蒸散量也逐渐增加。通过ZY3影像的高分辨率植被信息与Landsat 8影像热红外数据融合，提高了SEBS模型对该区域蒸散量的模拟效果，增进了我们对绿洲下垫面与大气间水热交换规律、水文过程、生态-水文相互作用的深入理解。 Abstract:Evapotranspiration is a major component of water and heat exchange in terrestrial ecosystems, as it acts as a critical link between ecological and hydrological processes, particularly for the exchange of mass and energy involved in land surface-air interaction, carbon cycle, and hydrological cycle in arid regions. In this study, we used Landsat 8 remote-sensing images and resources NO.3 (ZY3) images, with high-resolution vegetation information, and surface energy balance system (SEBS) model to estimate surface evapotranspiration (ET) in a desert oasis in the middle Hexi corridor area of the arid regions of northwestern China. We compared the estimated ET values with the measured values by using the eddy covariance method. We also spatially analyzed the effects of land cover types on ET. The main results of this study indicated that (1) the estimated daily ET was consistent with the corresponding measured values, especially for homogeneous underlying surface such as oasis (R2=0.96, P < 0.001) with low values of RMSE (0.84 mm/d) and MAE (0.56 mm/d). (2) In terms of seasonal changes, ET is closely related to phonological period, highest in summer, followed by spring, autumn, and winter (e.g., daily ET was 5.95 mm/d for cropland within the oasis, as opposed to 0.52 mm/d in winter), because of the peaked plant cover and summer rainfall in this study area. (3) With respect to spatial variations in ET, the surface ET for water body was the highest, followed by those for cropland, shelterbelt, bare land, and shrubland; this suggested that evapotranspiration also increases gradually with the increase in plant cover, except for water body. In addition, performance of the SEBS model for estimating ET in this region was fairly good when applying the data fusion of high-resolution vegetation information of ZY3 and thermal infrared data of the Landsat 8 remote-sensing images was performed. All these results have enhanced our understanding of the patterns of water and heat exchange between the underlying surface and atmosphere, which play a key role in hydrological and ecological processes or interaction between ecological and hydrological processes locally in arid desert oasis area. Our findings may provide some scientific insights into the decision-making for rational water utilization by the local government. 参考文献 相似文献 引证文献

A Critical Evaluation on the Role of Aerodynamic and Canopy–Surface Conductance Parameterization in SEB and SVAT Models for Simulating Evapotranspiration: A Case Study in the Upper Biebrza National Park Wetland in Poland

Evapotranspiration (ET) estimation through the surface energy balance (SEB) and soil-vegetation-atmosphere-transfer (SVAT) models are uncertain due to the empirical parameterizations of the aerodynamic and canopy-substrate conductances (gA and gS) for heat and water vapor transfers. This study critically assessed the impact of conductance parameterizations on ET simulation using three structurally different SEB and SVAT models for an ecologically important North-Eastern European wetland, Upper Biebrza National Park (UBNP) in two consecutive years 2015 and 2016. A pronounced ET underestimation (mean bias −0.48 to −0.68 mm day−1) in SEBS (Surface Energy Balance System) was associated with an overestimation of gA due to uncertain parameterization of momentum roughness length and bare soil’s excess resistance to heat transfer (kB−1) under low vegetation cover. The systematic ET overestimation (0.65–0.80 mm day−1) in SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) was attributed to the overestimation of both the conductances. Conductance parameterizations in SEBS and SCOPE appeared to be very sensitive to the general ecohydrological conditions, with a tendency of overestimating gA (gS) under humid (arid) conditions. Low ET bias in the analytical STIC (Surface Temperature Initiated Closure) model as compared to SEBS/SCOPE indicated the critical need for calibration-free conductance parameterizations for improved ET estimation.

Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data

The estimation of land-surface evapotranspiration (ET) at high spatial and temporal resolutions is important for management and planning of agricultural water resources, but available remote sensing data generally have either high spatial resolution or high temporal resolution. To overcome this limitation, we evaluated the use of a data fusion scheme, Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), to determine the surface parameters needed to estimate daily ET at a Landsat-like scale (100 m). In particular, we fused Moderate Resolution Imaging Spectroradiometer (MODIS) data with Landsat Enhanced Thematic Mapper Plus (ETM+) data in analysis of the Heihe River Basin (HRB), an arid region of Northwest China. The surface parameters were then used to drive the revised Surface Energy Balance System (SEBS) model to estimate daily ET at a spatial resolution of 100 m for this an arid irrigation area during the crop growth period (April to October) in 2012. The results showed that the daily ET estimates had a mean absolute percent error (MAPE) of 12% and a root mean square error (RMSE) of 0.81 mm/day relative to ground measurements from 18 eddy covariance (EC) sites in the study area. The validation results indicated good accuracy for land cover types of maize and vegetables, a slight overestimation for residential and wetland sites, and a slight underestimation for orchard site. Our comparison of the input parameter fusion approach (IPFA) and the ET fusion approach (ETFA) with field measurements indicated the IPFA was superior than the ETFA for land surfaces with high spatial heterogeneity. Furthermore, our high spatiotemporal ET estimates indicated that irrigation water efficiencies of the irrigation districts (mean: 70%) and villages (mean: 62%) had large spatial heterogeneity. These results point to the need for calculating ET at a high spatiotemporal resolution for monitoring and improving irrigation water efficiency at local scales. Our findings suggest that the proposed framework of estimating daily ET at a Landsat-like scale using multi-source data may also be applicable to other heterogeneous landscapes by providing a foundation for management of water resources at the basin or finer scales.

Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management, and development-related challenges leading to inequity, inadequacy, and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on a long term basis to identify the existing bottlenecks. Although there are several indicators available for the performance evaluation of the irrigation schemes, we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET), and temporal CV of RET, to assess the equity, adequacy, and reliability of water distribution, respectively, from 2003 to 2013. The ETa was estimated through a surface energy balance system (SEBS) algorithm and the ETa estimates were validated using the advection aridity (AA) method with a R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations, respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that the mean seasonal sub-based RET values during summer (May–September) (0.37 ± 0.06) and winter (October–April) (0.40 ± 0.08) are below the target values (RET ≥ 0.75) during 2003–2013. The CV of the mean ETa, within sub-basins and provinces for the entire study period, has an equitable distribution of water from October–January (0.09 ± 0.04), whereas the highest inequity (0.24 ± 0.08) in water distribution is during early summer. The range of the CV of the mean ETa (0.04–0.06) on a monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of the temporal CV of mean RET highlights the unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for the Shamal sub-basin (552 ± 43 mm) while among the provinces, Kunar experienced the highest ETa (544 ± 39 mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing water distribution plans in future.

Daily Evapotranspiration Estimation at the Field Scale: Using the Modified SEBS Model and HJ-1 Data in a Desert-Oasis Area, Northwestern China

Accurate continuous daily evapotranspiration (ET) at the field scale is crucial for allocating and managing water resources in irrigation areas, particularly in arid and semi-arid regions. The authors integrated the modified perpendicular drought index (MPDI) as an indicator of water stress into surface energy balance system (SEBS) to improve ET estimation under water-limited conditions. The new approach fed with Chinese satellite HJ-1 (environmental and disaster monitoring and forecasting with a small satellite constellation) images was used to map daily ET on the desert-oasis irrigation fields in the middle of the Heihe River Basin. The outputs, including instantaneous sensible heat flux (H) and daily ET from the MPDI-integrated SEBS and the original SEBS model, were compared with the eddy covariance observations. The results indicate that the MPDI-integrated SEBS significantly improved the surface turbulent fluxes in water-limited regions, especially for sparsely vegetated areas. The new approach only uses one optical satellite data and meteorological data as inputs, providing a considerable operational improvement for ET mapping. Moreover, HJ-1 high-resolution data promised continuous daily ET at the field scale, which helps in understanding the corresponding relationships among field, crop, and water consumption. Such detailed ET information can greatly serve water resources management in the study area as well as other arid and semi-arid regions.

Comparison of Two Satellite‐Based Evapotranspiration Models of the Nagqu River Basin of the Tibetan Plateau

AbstractEvapotranspiration (ET) is one of the major uncertain components of the energy and water cycle and was derived for the Nagqu River Basin based on remote sensing data and atmospheric surface layer observations under cloudless conditions. Two process‐based models were used to determine the ET: a Priestley‐Taylor (PT)‐based model and a topographical enhanced surface energy balance system (TESEBS) model. Improved broadband albedo, downward shortwave radiation flux, and reconstructed normalized difference vegetation index (NDVI) were coupled into the TESEBS model and PT‐based model to estimate the actual ET. The atmospheric surface layer meteorological data, SPOT Vegetation (VGT) data, and Moderate Resolution Imaging Spectroradiometer data were used as inputs for 10‐day ET calculations. The model‐estimated results were compared with ground truths calculated via the combinatory method. The results indicated that the ET determined by both models well fit the actual ET, with correlation coefficients (R) of 0.88 and 0.82, respectively. However, the TESEBS model showed a better performance than the PT model, with a lower mean bias error (−0.02 mm/hr) and lower root–mean‐square error (0.08 mm/hr). Although the PT model is computationally simple and requires few parameters, the strong weighting of the NDVI may lead to some overestimations, especially during the growing season.

Improvement of Two Evapotranspiration Estimation Models Using a Linear Spectral Mixture Model over a Small Agricultural Watershed

Accurately measuring regional evapotranspiration (ET) is of great significance for studying global climate change, regional hydrological cycles, and surface energy balance. However, estimating regional ET from mixed vegetation types is still challenging. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) and the Surface Energy Balance System (SEBS) models were applied to estimate surface ET in a small agricultural watershed. Landsat8 satellite images were used as input data to the single-source models. The two models were validated at single point and ecosystem scales. The results showed that both models overestimated ET observations in paddy fields and orange groves but underestimated them in dry farmland. The error was mainly caused by the heterogeneity of the mixed pixels. The linear spectral mixture model and a set of equations were introduced to reduce the simulation error. The revised results showed that the relative precision of SEBAL was improved by 9.87% and 10.06%, respectively. This research is expected to provide new ideas for future development of accurate remote-sensing ET estimations on heterogeneous surfaces.

Evaluation of SEBS, SEBAL, and METRIC models in estimation of the evaporation from the freshwater lakes (Case study: Amirkabir dam, Iran)

Evapotranspiration (ET) estimation is of great importance due to its key role in water resource management. Surface energy modeling tools such as Surface Energy Balance Algorithm for Land (SEBAL), Mapping Evapotranspiration with Internalized Calibration (METRIC), and the Surface Energy Balance System (SEBS) can estimate the amount of evapotranspiration for every pixel of the satellite images. The main objective of this research is evaporation investigation from the freshwater bodies using SEBAL, METRIC, and SEBS. For this purpose, the Amirkabir dam reservoir and its nearby agricultural lands in a semi-arid climate were selected and studied from 2011 to 2017 as the study area. The implementations of this study were accomplished on 16 satellite images of Landsat TM5 and OLI. Then, SEBAL, METRIC, and SEBS were implemented on the selected images. Moreover, the corresponding pan evaporate measurements on the reservoir bank were considered as the ground truth data. Regarding to the results, SEBAL is not a reliable method to evaluate freshwater evaporation with the coefficient of determination (R2) of 0.36 and the Root Mean Square Error (RMSE) of 5.1 mm. On the other hand, METRIC with RMSE and R2 of 0.57 and 2.02 mm and SEBS with RMSE and R2 of 0.93 and 0.62 demonstrated a relatively good performance.