Abstract:An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance … Show more
“…Some local differences occur unavoidably due to the inaccuracy of the various mathematical expressions used to compute a complex hydrological process such as ET. Remote sensing ET values reflect more the real world conditions as they are based on observations [33][34][35]42]. The agreement between SWAT and remote sensing data was expressed by means of the correlation coefficient and the bias.…”
Abstract:In this paper, evapotranspiration (ET) and leaf area index (LAI) were used to calibrate the SWAT model, whereas remotely sensed precipitation and other climatic parameters were used as forcing data for the 6300 km 2 Day Basin, a tributary of the Red River in Vietnam. The efficacy of the Sequential Uncertainty Fitting (SUFI-2) parameter sensitivity and optimization model was tested with area specific remote sensing input parameters for every Hydrological Response Units (HRU), rather than with measurements of river flow representing a large set of HRUs, i.e., a bulk calibration. Simulated monthly ET correlations with remote sensing estimates showed an R 2 = 0.71, Nash-Sutcliffe Efficiency NSE = 0.65, and Kling Gupta Efficiency KGE = 0.80 while monthly LAI showed correlations of R 2 = 0.59, NSE = 0.57 and KGE = 0.83 over a five-year validation period. Accumulated modelled ET over the 5-year calibration period amounted to 5713 mm compared to 6015 mm of remotely sensed ET, yielding a difference of 302 mm (5.3%). The monthly flow at two flow measurement stations were adequately estimated (R 2 = 0.78 and 0.55, NSE = 0.71 and 0.63, KGE = 0.59 and 0.75 for Phu Ly and Ninh Binh, respectively). This outcome demonstrates the capability of SWAT model to obtain spatial and accurate simulation of eco-hydrological processes, also when rivers are ungauged and the water withdrawal system is complex.
“…Some local differences occur unavoidably due to the inaccuracy of the various mathematical expressions used to compute a complex hydrological process such as ET. Remote sensing ET values reflect more the real world conditions as they are based on observations [33][34][35]42]. The agreement between SWAT and remote sensing data was expressed by means of the correlation coefficient and the bias.…”
Abstract:In this paper, evapotranspiration (ET) and leaf area index (LAI) were used to calibrate the SWAT model, whereas remotely sensed precipitation and other climatic parameters were used as forcing data for the 6300 km 2 Day Basin, a tributary of the Red River in Vietnam. The efficacy of the Sequential Uncertainty Fitting (SUFI-2) parameter sensitivity and optimization model was tested with area specific remote sensing input parameters for every Hydrological Response Units (HRU), rather than with measurements of river flow representing a large set of HRUs, i.e., a bulk calibration. Simulated monthly ET correlations with remote sensing estimates showed an R 2 = 0.71, Nash-Sutcliffe Efficiency NSE = 0.65, and Kling Gupta Efficiency KGE = 0.80 while monthly LAI showed correlations of R 2 = 0.59, NSE = 0.57 and KGE = 0.83 over a five-year validation period. Accumulated modelled ET over the 5-year calibration period amounted to 5713 mm compared to 6015 mm of remotely sensed ET, yielding a difference of 302 mm (5.3%). The monthly flow at two flow measurement stations were adequately estimated (R 2 = 0.78 and 0.55, NSE = 0.71 and 0.63, KGE = 0.59 and 0.75 for Phu Ly and Ninh Binh, respectively). This outcome demonstrates the capability of SWAT model to obtain spatial and accurate simulation of eco-hydrological processes, also when rivers are ungauged and the water withdrawal system is complex.
“…The use of surface energy balance algorithms based on remote sensing data has been shown to be quite promising for the estimation of actual evapotranspiration on both regional and local scales (LI et al, 2009). The Surface Energy Balance System (SEBS) model was proposed by SU (2002) to estimate atmospheric turbulent fluxes and evaporative fraction using satellite data and ancillary surface and meteorological information.…”
ABSTRACT:The objective of this research was to evaluate the water consumption of irrigated sugarcane areas using the Surface Energy Balance System (SEBS) driven by products derived from Meteosat Second Generation (MSG), SPOT/VEGETATION, Terra/MODIS satellite data and meteorological observations data from Minas Gerais State, Brazil. The actual evapotranspiration from SEBS model (ET-SEBS) was compared against crop evapotranspiration under standard conditions (ETc), which was obtained from weather data based on reference evapotranspiration (ET0) and the crop coefficient (Kc) values from FAO. Results showed that there was a good agreement between ET-SEBS and ETc when sugarcane was at maximum development stage under center pivot irrigation and the Kc value corresponded to 1.25. The ET-SEBS values seem to overestimate water use during sugarcane late stage in areas which the Kc value was 0.7. Increasing Kc to a value equals to 1.25 for sugarcane late stage, the differences between ETc and ET-SEBS decreased; Kc is not so high at that stage, reinforcing ET-SEBS overestimation. In conclusion, the estimation of evapotranspiration using satellite data and SEBS model approach was appropriated to monitor water usage of large sugarcane areas irrigated by center pivots in Minas Gerais State, Brazil.
“…A Surface Energy Balance System (SEBS) for the estimation of atmospheric turbulent fluxes and surface evaporation using satellite earth observation data in the visible, near infra-red and thermal infrared frequency range has been designed for composite terrain with heterogeneous surfaces at a larger scale (Su, 2002). SEBS, applied to many case studies in Europe and Asia (Gokmen et al, 2012;Ma et al, 2014;Wang and Dickinson, 2012), has been shown as one of the most logical and accurate methods in ET estimation (Li et al, 2009). The accuracy of SEBS depends on the land surface physical parameters which is suitable to the study areas (Wood et al, 2003).…”
Accurate estimates of evapotranspiration (ET) are important to skillful predictions of runoff, soil moisture and crop productivity. In this study, ET was simulated over three years in China by integrating remotely-sensed data with the simulation model SEBS-China. SEBS-China was developed from the Surface Energy Balance System (SEBS) model that is used to estimate atmospheric turbulent heat fluxes and evaporative fraction through satellite-derived radiation fluxes and land surface temperatures coupled with near-surface meteorological variables. Simulated regional ET was first evaluated using experimental data from the Changbai Mountains and five river basins in China. Average annual simulated ET agreed well with the observed data, based on the detailed results through comparative validation. Regional ET derived from SEBS-China was then compared with the simulated ET from the Common Land Model (CoLM). Both of the models simulated regional ET well, with a few overestimated areas such as in the Qinghai-Tibet Plateau, YanShan and South Daxing'anling Mountains. We conclude that more efficient ET estimation can be achieved through combining remotely-sensed information with land surface models.
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