Evaluation of Remote Sensing-Based Evapotranspiration Datasets for Improving Hydrological Model Simulation in Humid Region of East China
نویسندگان
چکیده
Conventional calibration methods used in hydrological modelling are based on runoff observations at the basin outlet. However, with only often produces reasonable but poor results for other variables. Multi-variable both and remote sensing-based evapotranspiration (ET) is developed naturally, due to importance of ET its data availability. This study compares two main schemes: (1) (Scheme I) (2) multi-variable II). obtained from three datasets, namely Penman–Monteith–Leuning (PML), FLUXCOM, Global Land Evaporation Amsterdam Model (GLEAM). The aforementioned schemes applied calibrate parameters Distributed Hydrology Soil Vegetation (DHSVM) through ?-dominance non-dominated sorted genetic algorithm II (?-NSGAII). show that all datasets have good performance areal area. DHSVM model calibrated Scheme I acceptable simulation (Kling–Gupta Efficiency, KGE = 0.87), not (KGE < 0.7). simulations can be achieved variables II. value reach 0.87(0.91), 0.72(0.85), 0.75(0.86) (validation) period (FLUXCOM), (GLEAM), respectively. Simultaneously, greatly improved validation periods. Furthermore, incorporating into variants able improve extreme flow (including low high flow). Based improvement simulations, PML utilized drought forecasting, FLUXCOM GLEAM choices flood forecasting.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2022
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs14184546