Surface Energy Balance System Model Research Articles

Connectivity of evapotranspiration processes in a Brazilian dryland reservoir using remote sensing

Understanding the combined open water reservoir evaporation and riparian vegetation transpiration (evapotranspiration) is important for water resource management in semiarid regions like the Brazilian Dryland region. Existing research has explored reductions in open water evaporation due to riparian vegetation transpiration, but evidence for this interdependence in this region is not well understood. The aim of this study was to estimate the connectivity (impact and maximum distance of action) between riparian vegetation and its transpiration and reservoir evaporation, as well as the ratio of the volume losses by transpiration and evaporation, using Landsat 5 and 8 in a Brazilian Dryland environment. Evaporation and transpiration were estimated using the Surface Energy Balance System for Water and the Surface Energy Balance System models, respectively, from 1985 to 2020. A Class A Pan and the Penman-Monteith equation were used, for reference reservoir evaporation and vegetation transpiration, respectively. The occurrence of riparian vegetation was associated with the Normalized Difference Vegetation Index. Both models performed well, with root mean square error ≤ 0.80 mm/day. The riparian vegetation transpiration demonstrated a high negative correlation (R²>0.7) with evaporation, suggesting the vegetation acts to reduce evaporation (average of 30 %) up to a maximum distance of 90 m from the reservoir shoreline. This is explained by the adjacent riparian vegetation-induced reduction in radiation inputs due to shading at the reservoir margin, a lowering of wind speeds and increases in air humidity from transpiration. The ratio of riparian vegetation transpiration to reservoir evaporation within a buffer of 150 m is approximately equal. Combined riparian vegetation and reservoir evapotranspiration equates to the daily water supply for ∼275,000 people. The paper explains and quantifies the connectivity between riparian vegetation transpiration and reservoir evaporation, thereby providing a model for improved reservoir water balance estimates, which can aid regional water resources planning, development, and management.

Ecological Water Requirement of Vegetation and Water Stress Assessment in the Middle Reaches of the Keriya River Basin

Desert oases are vital for maintaining the ecological balance in arid regions’ inland river basins. However, fine-grained assessments of water stress in desert oasis ecosystems are limited. In our study, we aimed to evaluate the water stress in desert oasis ecosystems in the middle reaches of the Keriya River Basin, with a specific focus on their ecological functions and optimizing water resource management. We hypothesized that evapotranspiration has significant effects on ecological water consumption. First, we estimated the actual evapotranspiration (ET) and potential evapotranspiration (PET) based on the SEBS (surface energy balance system) model and remote sensing downscaling model. Then, the ecological water requirement (EWR) and ecological water stress (EWS) index were constructed to evaluate the ecological water resource utilization. Finally, we explored the influencing factors and proposed coping strategies. It was found that regions with higher ET values were mainly concentrated along the Keriya River and its adjacent farmland areas, while the lower values were observed in bare land or grassland areas. The total EWR exhibited the sequence of grassland > cropland > forest, while the EWR per unit area followed the opposite order. The grassland’s EWS showed a distinct seasonal response, with severe, moderate, and mild water shortages and water plenitude corresponding to spring, summer, autumn, and winter, respectively. In contrast, the land use types with the lowest EWS were water areas that remained in a state of water plentitude grade (0.08–0.20) throughout the year. Temperature and vegetation index were identified as the primary influencing factors. Overall, this study provides a reliable method for evaluating the EWR and EWS values of basin scale vegetation, which can serve as a scientific basis for formulating water resource management and regulation policies in the region.

Multi-scale spatial analysis of satellite-retrieved surface evapotranspiration in Beijing, a rapidly urbanizing region under continental monsoon climate.

As one of the important components of hydrological cycle, evapotranspiration spatial distribution is of great significance to regional water resources planning and rational utilization. This research used Surface Energy Balance System model to estimate the daily evapotranspiration (ET) in Beijing based on Landsat 8 observations. Results showed that the daily ET in Beijing ranged from 3.469 to 5.474mm/day. ET is known to decrease with the increase of land surface temperature (LST) and to increase with the increase of Normalized Difference Vegetation Index (NDVI). NDVI primarily decreased from the northwest to the southeast. When the NDVI value was 0.4-0.6, the average ET peaked at 4.88mm/day, and then slightly decreased by 3.7%. The coefficient of determination of NDVI (0.95) was much greater than that of LST (0.30) upon linear fitting, showing LST was not the main factor controlling ET in Beijing. In contrast to the linear fitting results, the spatial correlation between LST and ET is more significant than that between NDVI and ET in the global bivariate spatial analysis, where the absolute value of global bivariate Moran's I of LST (0.51) was higher than that of NDVI (0.21) at a resolution of 150m. And the univariate spatial autocorrelation indices of LST, ET, and NDVI equaled 0.84, 0.65, and 0.51, respectively. Furthermore, the complex spatial distribution pattern of variables could significantly affect the correlation analysis results. Local bivariate spatial analysis showed that over 60% of the Beijing area had a significant correlation, of which the negative correlation area of LST accounted for about 85%, and the positive correlation area of NDVI accounted for 74%. By improving the correlation analysis accuracy, the regional conditions for the establishment of correlation analysis results were clarified from the overall correlation analysis results.

Estimating evapotranspiration using earth observation data: A comparison between hydrological and energy balance modelling approaches

• Earth observation data is a useful alternate data source to hydrological models. • The spatial resolution of satellite data affects the accuracy of evapotranspiration. • The Surface Energy Balance System model outperformed the ACRU model. • Hydrological models should be developed to allow actual evapotranspiration input. Hydrological models are often applied to acquire estimates of evapotranspiration ( ET a ) using quality inputs of reference evapotranspiration ( ET 0 ). However, their application may be limited by the need for good quality long-term data inputs. In data scarce regions, the use of satellite-earth observation data as inputs to these models may provide a potential solution to overcome data acquisition challenges associated with conventional data collection approaches. In this study, the Agricultural Catchments Research Unit (ACRU) hydrological model was applied to estimate the ET a using both in-situ and satellite-derived estimates of ET 0 as inputs to the model. The simulated ET a estimates were then evaluated through comparisons against field-based measurements of ET a acquired from an Eddy Covariance system ( EC ET ), as well as from the application of the Surface Energy Balance System (SEBS) model. The results of these investigations demonstrated that the meteorologically-based ACRU ET a simulations marginally outperformed the satellite-based ACRU ET a simulations. While these results highlight the influence which the quality of ET 0 inputs may have on the accuracy of the ACRU derived ET a estimates, the concurrent application and evaluation of SEBS demonstrated that alternate approaches to hydrological modelling, may be better suited for ET a estimation in certain instances.

Estimation of evapotranspiration using all-weather land surface temperature and variational trends with warming temperatures for the River Source Region in Southwest China

• All-weather LST is used to overcome satellite TIR LST missing in cloudy conditions. • Estimation scheme for all-weather evapotranspiration (AWET) is proposed. • Response of AWET to the warming temperatures exhibits a spatiotemporal heterogeneity. Land surface temperature (LST) derived from satellite thermal infrared (TIR) remote sensing is widely used in estimating land surface evapotranspiration (ET) through energy balance theory. However, as satellite TIR remote sensing is frequently affected by clouds, the derived LST with spatial missing makes it impossible to estimate seamless ET for large areas. In this study, based on the all-weather LST (AWLST) generated through the synergistic use of TIR and passive microwave (PMW) remote sensing, we propose an estimation scheme of all-weather ET (AWET) for the River Source Region of Southwest China (RSR-SC) with complex environmental characteristics of frequent clouds and fog. Specifically, the parameters of the Surface Energy Balance System (SEBS), which have high impact on the model results, are first accurately determined by a global sensitivity analysis. Second, the parametric calculation schemes of turbulent exchange, such as surface roughness heights for momentum ( z 0m ) and heat ( z 0h ) transfer, and soil heat flux ( G 0 ) of the SEBS model are refined. Third, the daily ET temporal upscaling method is developed. Then a long-term AWET product for the RSR-SC is generated. Comparison against ground measurements from 12 eddy covariance (EC) sites indicates a good accuracy of the AWET product: the mean absolute percent error (MAPE) and root mean square error (RMSE) of the daily ET estimates are 36 % and 0.88 mm/d, respectively. From aspects of temporal variation of daily ET, monthly spatiotemporal distribution patterns, interannual variation of different land covers and spatial distribution comparison with other ET products, the generated AWET exhibits to be realistic, reflecting relatively subtle variations. Further investigation indicates that the response of surface ET to the warming temperatures exhibits the spatial heterogeneity of the change trend. This study highlights the importance of estimating daily AWET at a MODIS-like scale using AWLST data to significantly benefit water resource monitoring and conduct runoff prediction over large areas and watershed scales.

The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links ra with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates.The present study investigates the influence of ra and its relation to LST uncertainties on the performance of three structurally different SEB models. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE, the energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019.Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low ra (high wind speeds) and caused a slight underestimation of LE at the water-limited sites. The impact of ra on the LE residual error was found to be of the same magnitude as the influence of LST uncertainties in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for the mesic forest ecosystems indicated minor dependency on ra for modelling LE (VIP < 0.4), which was due to a higher roughness length and lower LST resulting in the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of ra.

An improved remote sensing based approach for predicting actual Evapotranspiration by integrating LiDAR

Spatially distributed information of actual Evapotranspiration (ET) is essentially required for various applications in agriculture, as well as studies related to water balance. An Energy Balance model that uses optical and thermal remote sensing datasets is appropriate for the spatially distributed estimation of ET, which is primarily controlled by local environmental conditions. In this study, we use the Surface Energy Balance System (SEBS), which is an Energy Balance model, to estimate an improved actual ET, by integrating canopy height information obtained from ICESat/GLAS, the first space-borne LiDAR satellite. Our model estimates latent heat flux (LE) as a residual of energy balance, while sensible heat flux (H) is estimated based on Monin–Obukhov similarity theory. The spatial variability of H and LE estimated from Landsat TM/ETM+ images were compared with eddy covariance (EC) based in situ flux tower observations, in order to document the SEBS model uncertainties in three forest sites in the East and Southeast Asian ecosystem. We identified that canopy height (hc) is one of the critical parameters that can induce uncertainties in SEBS model estimations. Therefore, hc obtained from LiDAR was introduced in parameterization of the roughness length for momentum transfer (z0m). In situ based hc obtained from flux tower stations, and the normalized difference vegetation index based formulation of hc proposed by Su (2001), were also introduced in the SEBS z0m parameterization. Root mean square error of LiDAR integrated SEBS (SEBSLiDar) for estimated H values reduced by (20, 45, and 23)% compared to Landsat integrated SEBS (SEBSLandsat), and (18, 7, and 9)% compared to In situ integrated SEBS (SEBSInsitu) at the three selected forest sites (SMC, QYZ, and SMF), respectively, while the mean coefficient of determination values for the estimated LE improved by (9.09 and 5.88)% compared to SEBSLandsat and SEBSInsitu, respectively, with reference to ground-based flux tower observations. Our analysis reveals that LiDAR-based parameterization of z0m can significantly increase the accuracy of estimated roughness lengths within an ET model, which can therefore improve the accuracy of the estimated turbulent heat fluxes. SEBSLiDAR was further evaluated for the spatially distributed mapping of actual ET. We have observed that ET estimated by SEBSLandsat overestimated in forest sites compared to EC observations; however, LiDAR-integrated SEBS marginally improved the accuracy of ET, thereby leading to an improvement in the mean correlation value of 0.87 and mean normalized standard deviation value of 0.93 approaching unity based on Taylor diagram, which more closely approximates the actual ground-based measurements. The proposed methodology overcomes the current limitation in the energy balance models in estimating roughness lengths, by providing accurate formulation of hc by specifically incorporating LiDAR measurements in areas of tall vegetation canopies. The operational improvement in roughness lengths by next-generation SEBSLiDAR model provides an opportunity to improve the estimation accuracy of water and energy fluxes, specifically ET. Overall, our proposed SEBSLiDAR model provides a benchmark that is useful to policy makers and water resource managers in devising a plan for sustainable use of water resources in the East Asian region, as well as other similar ecosystems.

A physical-based two-source evapotranspiration model with Monin–Obukhov similarity theory

ABSTRACT Accurate quantification of energy budget components and its partitioning between canopy and soil is essential for improving water resource management. During the last few decades, several two-source evapotranspiration (ET) models have been developed by exploiting satellite datasets in conjunction with meteorological observations to estimate fluxes at different spatio-temporal scales. However, the complex parameterization scheme intrinsic to those models as well as the need for a large number of input datasets hampers their applications in a broader hydro-meteorological studies. In this study, we formulated a Leaf Area Index (LAI)-based methodology to develop a Two-Source Surface Energy Balance System (TS-SEBS) based on Monin–Obukhov similarity theory and Su (2002) principles, which uses fewer input datasets from satellite and meteorological observations to obtain fluxes on local as well as regional scales. Specifically, 97 medium-resolution Landsat TM/ETM+ images have been used to validate the TS-SEBS model estimations with (a) Eddy Covariance (EC)-based in-situ flux tower observations and (b) one-source SEBS (Surface Energy Balance System) model estimations in East Asian ecosystems. The mean bias and RMSE were 10.90 and 58.95 Wm−2 for instantaneous net radiation, 35.14, and 63.35 Wm−2 for instantaneous net radiation over the soil, and −25.06 and 45.93 Wm−2 for instantaneous net radiation over the canopy, whereas the ground heat flux showed a mean bias and RMSE of 45.60 and 59.21 Wm−2, respectively, over six selected sites. The results of sensible heat flux (H) for SEBS revealed its underestimation pattern (mean bias value of −20.68 Wm−2), whereas TS-SEBS tended to slightly overestimate values (mean bias value of 2.32 Wm−2) compared with EC observations. The TS-SEBS exhibited relatively better approximations of H (mean RMSE of 57.83 Wm−2) compared with SEBS (mean RMSE of 79.47 Wm−2) by reducing the error by ~27%. In terms of spatially distributed estimation of ET, the TS-SEBS outperformed SEBS with a mean normalized standard deviation value of 1.08 compared with 1.25 for SEBS, a reduction of ~14%. A mean Pearson’s correlation coefficient value >0.73 was obtained for both selected models based on a Taylor diagram, and these statistics more closely approximate the ground-based EC observations. The better performance of TS-SEBS compared with SEBS is due to the incorporation of improved LAI-based formulations in its structural algorithm to partition fluxes between soil and canopy, incorporation of improved wind speed profile extinction coefficient, and separate calculations of aerodynamic resistance for both soil and canopy components. The proposed methodology in the next-generation TS-SEBS model provides an unprecedented opportunity for quantifying improved energy budgets and partitioning fluxes between soil and canopy in an accurate and computationally efficient approach for better plant-soil-atmosphere interaction studies.

Distribution Characteristics of Soil Moisture in the Three Rivers Headwaters Region, China

The change of soil moisture has significant influence on the surface energy distribution and evapotranspiration process and causes the climatic environment changes. It is thus urgent to detect soil moisture facing climate change problems. Based on apparent thermal inertia method, the GLDAS soil moisture of the layer in 0 ~ 10 cm, 10 ~ 40 cm, 40 ~ 100 cm, 100 ~ 200 cm under the ground surface are proceeded for downscaling and the monthly soil moisture are obtained by combination of MODIS data. Statistics of precipitation and temperature of 13 meteorological stations in the Three River Headwater Region (TRHR) are collected to analyze the correlation between soil moisture change and temperature and precipitation. The correlation between soil moisture and evapotranspiration (ET) are analyzed by using the surface energy balance system model to calculate the average evapotranspiration in the study area. The result indicated that (1) Apparent thermal inertia (ATI) is positively correlated with soil depths in the four layers below the surface and has the best correlation with 0 ~ 10 cm soil moisture. Soil moisture increases with soil depth. Soil moisture is lowest under 0 ~ 10 cm depth while highest under 10 ~ 40 cm on average. (2) In terms of spatial distribution of TRHR, soil moisture is higher in the northwest and southeast, but lower in the southwest and northeast than average. The temporal variation of the soil moisture in one year was high in summer and low in winter, and the average annual soil moisture increased with time. (3) Soil moisture is negatively correlated with temperature and positively corre-lated with precipitation. There is a positive correlation between soil moisture and evapotranspiration. The linear regression coefficient of determination R2 is 0.8489.

Assessing the Spatial Pattern of Irrigation Demand under Climate Change in Arid Area

Studying the pattern of agricultural water demand under climate change has great significance for the regional water resources management, especially in arid areas. In this study, the future pattern of the irrigation demand in Hotan Oasis in Xinjiang Uygur Autonomous Region in Northwest China, including Hotan City, Hotan County, Moyu County and Luopu County, was assessed based on the general circulation models (GCMs) and the Surface Energy Balance System model (SEBS). Six different scenarios were used based on the GCMs of BCC_CSM1.1, HadGEM2-ES and MIROC-ESM-CHEM under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The results showed that the method integrating the GCMs and SEBS to predict the spatial pattern was useful. The irrigation demand of Hotan Oasis will increase in 2021–2040. The annual irrigation demand of Hotan City is higher, with 923.2 and 936.2 mm/a in 2021–2030 and 2031–2040, respectively. The other three regions (Hotan County, Moyu County and Luopu County) are lower in the six scenarios. The annual irrigation demand showed a spatial pattern of high in the middle, low in the northwest and southeast under the six scenarios in 2021–2040. The study can provide useful suggestions on the water resources allocation in different regions to protect water resources security in arid areas.

Estimation of surface energy fluxes in the permafrost region of the Tibetan Plateau based on in situ measurements and the surface energy balance system model

AbstractThe surface energy balance is a key issue in land surface process research and important for studies of climate and hydrology. In this paper, the surface energy fluxes (net radiation, ground heat flux, sensible heat flux and latent heat flux) at the Tanggula (TGL) and Xidatan (XDT) sites were measured and the distributions of the regional surface energy fluxes on the Tibetan Plateau were obtained using a revised surface energy balance system (SEBS) model. The results show that the surface energy fluxes have obvious seasonal variations. At both sites, the sensible heat flux is highest in spring and lowest in summer, and the latent heat flux is highest in summer and lowest in winter. The high elevation, snow cover, freeze–thaw process, precipitation, vegetation and soil texture are important influencing factors for land surface energy fluxes. The time‐phase difference between the net radiation and ground heat flux for bare soils is estimated to be 2–3 hr. The ratio of ground heat flux and net radiation ranged from approximately 0.18 to 0.33, and a parameterization scheme for the remote sensing of ground heat flux over the Tibetan Plateau bare soil in summer is developed. The simulation results of the regional surface energy fluxes show that the distributions of surface parameters, such as vegetation, soil texture and soil moisture content, are important for understanding regional changes in the surface energy fluxes.

Improving Meteorological Input for Surface Energy Balance System Utilizing Mesoscale Weather Research and Forecasting Model for Estimating Daily Actual Evapotranspiration

Using Surface Energy Balance System (SEBS) to estimate actual evapotranspiration (ET) on a regional scale generally uses gridded meteorological data by interpolating data from meteorological stations with mathematical interpolation. The heterogeneity of underlying surfaces cannot be effectively considered when interpolating meteorological station measurements to gridded data only by mathematical interpolation. This study aims to highlight the improvement of modeled meteorological data from the Weather Research and Forecasting (WRF) mesoscale numerical model which fully considers the heterogeneity of underlying surfaces over the data from mathematical interpolation method when providing accurate meteorological input for SEBS model. Meteorological data at 1 km resolution in the Hotan Oasis were simulated and then were put into SEBS model to estimate the daily actual ET. The accuracy of WRF simulation was evaluated through comparison with data collected at the meteorological station. Results found that the WRF-simulated wind speed, air temperature, relative humidity and surface pressure correlate well with the meteorological stations measurements (R2 are 0.628, 0.8242, 0.8089 and 0.8915, respectively). Comparison between ET calculated using the meteorological data simulated from the WRF (ETa-WRF) and meteorological data interpolated from measurements at met stations (ETa-STA) showed that ETa-WRF could better reflect the ET difference between different land cover, and capture the vegetation growing trend, especially in areas with sparse vegetation, where ETa-STA intends to overestimate. In addition, ETa-WRF has less noise in barren areas compared to ETa-STA. Our findings suggest that WRF can provide more reliable meteorological input for SEBS model than mathematical interpolation method.

Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau

Land surface heat fluxes consist of the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. The estimation of these fluxes is essential to the study of energy transfer in land–atmosphere systems. In this paper, Landsat 7 ETM+ SLC-on data were applied to estimate the land surface heat fluxes on the northern Tibetan Plateau using the SEBS (surface energy balance system) model, in combination with the calculation of field measurements at CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project on the Tibetan Plateau) automatic weather stations based on the combinatory method (CM) for comparison. The root mean square errors between the satellite estimations and the CM calculations for the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux were 49.2 W/m2, 46.3 W/m2, 68.2 W/m2, and 54.9 W/m2, respectively. The results reveal that land surface heat fluxes all present significant seasonal variability. Apart from the sensible heat flux, the satellite-estimated net radiation flux, soil heat flux, and latent heat flux exhibited a trend of summer &gt; spring &gt; autumn &gt; winter. In summer, spring, autumn, and winter, respectively, the median values of the net radiation flux (631.8 W/m2, 583.0 W/m2, 404.4 W/m2, 314.3 W/m2), soil heat flux (40.9 W/m2, 37.9 W/m2, 26.1 W/m2, 20.5 W/m2), sensible heat flux (252.7 W/m2, 219.5 W/m2, 221.4 W/m2, 204.8 W/m2), and latent heat flux (320.1 W/m2, 298.3 W/m2, 142.3 W/m2, 75.5 W/m2) exhibited distinct seasonal diversity. From November to April, the in situ sensible heat flux is higher than the latent heat flux; the opposite is true between June and September, leaving May and October as transitional months. For water bodies, alpine meadows and other main underlying surface types, sensible and latent heat flux generally present contrasting and complementary spatial distributions. Due to the 15–60 m resolution of the Landsat 7 ETM+ data, the distribution of land surface heat fluxes can be used as an indicator of complex underlying surface types over the northern Tibetan Plateau.

Quantifying the contribution of riparian total evaporation to streamflow transmission losses: Preliminary investigations along the Groot Letaba river

The Groot Letaba River, situated in the semi-arid north-eastern region of South Africa is an example of a river system in which the uncertainty associated with transmission losses (TL) has limited the effective management of environmental water requirement (EWR) flows. TL along the river significantly impacts EWR flows, as it is often the case that specified EWR releases are not adequately received further downstream. Due to the limited understanding of the magnitude of TL, as well as the dominant contributing processes to TL within the region, it remains a challenge to operate the river using downstream targets far from the source of operations. In an attempt to address this knowledge gap, detailed characterizations of hydrological processes were performed along the lower reaches of the river, which centred around the estimation of riparian total evaporation and quantifying the rapport between surface and subsurface water flow processes. Riparian total evaporation was estimated using the satellite-based surface energy balance system model, soil water evaporation measurements and open water evaporation estimates. Losses from the river to the adjacent aquifer were determined from the continuous monitoring of the groundwater phreatic surface and characterization of aquifer hydraulic properties. The results of these investigations indicated that present flows within the system are likely to be insufficient to satisfy gazetted median and extreme low flow targets. Overall, the study details key hydrological processes influencing TL along the river. It should, however, be noted that these observations only provide an understanding of the system over a limited observation period.

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.

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.

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.

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.

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

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.