Can satellite land surface temperature data be used similarly to ground discharge measurements for distributed hydrological model calibration?

This study proposes a new methodology for the calibration of distributed hydrological models at basin scale by constraining an internal model variable using satellite data of land surface temperature. The model algorithm solves the system of energy and mass balances in terms of a representative equilibrium temperature that governs the fluxes of energy and mass over the basin domain. This equilibrium surface temperature, which is a critical model state variable, is compared to operational satellite land surface temperature calibrating soil hydraulic parameters and vegetation variables differently in each pixel minimizing the errors. This procedure is also compared to the traditional calibration using only discharge measurements. The distributed energy water balance model, Flash–flood Event–based Spatially–distributed rainfall–runoff Transformation - Energy Water Balance model (FEST-EWB) is used to test this approach. This methodology is applied to the Upper Yangtze River basin (China) using MODIS land surface temperature retrieved from satellite data in the framework of NRSCC-ESA DRAGON-2 Programme. The calibration procedure based on land surface temperature seems to outperform the calibration based on discharge with lower relative error and higher Nash-Sutcliffe efficiency index on cumulated volume