Integration of Remote Sensing Evapotranspiration into Multi-Objective Calibration of Distributed Hydrology–Soil–Vegetation Model (DHSVM) in a Humid Region of China

• Main Authors: Suli Pan, Li Liu, Zhixu Bai, Yue-Ping Xu
• Format: Article
• Language: English
• Published: MDPI AG 2018-12-01
• Series: Water
• Subjects: remote sensing evapotranspiration; multi-objective calibration; εP-DHSVM; MODIS; SEBAL
• Online Access: https://www.mdpi.com/2073-4441/10/12/1841

This study presents an approach that integrates remote sensing evapotranspiration into multi-objective calibration (i.e., runoff and evapotranspiration) of a fully distributed hydrological model, namely a distributed hydrology&#8315;soil&#8315;vegetation model (DHSVM). Because of the lack of a calibration module in the DHSVM, a multi-objective calibration module using &#949;-dominance non-dominated sorted genetic algorithm II (&#949;-NSGAII) and based on parallel computing of a Linux cluster for the DHSVM (&#949;P-DHSVM) is developed. The module with DHSVM is applied to a humid river basin located in the mid-west of Zhejiang Province, east China. The results show that runoff is simulated well in single objective calibration, whereas evapotranspiration is not. By considering more variables in multi-objective calibration, DHSVM provides more reasonable simulation for both runoff (<i>NS</i>: 0.74% and <i>PBIAS</i>: 10.5%) and evapotranspiration (<i>NS</i>: 0.76% and <i>PBIAS</i>: 8.6%) and great reduction of equifinality, which illustrates the effect of remote sensing evapotranspiration integration in the calibration of hydrological models.