Remotely sensed land surface temperature, lakes area and water level and ground discharge for hydrological model calibration in the Yangtze river basin

摘要

Distributed hydrological models of energy and mass balance usually need in input many soil and vegetation parameters, which are usually difficult to define. This paper will try to approach this problem performing a parameters calibration based on remote sensing land surface temperature data (LST) as a complementary method to the traditional calibration with ground data. A pixel to pixel calibration procedure of soil hydraulic and vegetation parameters for each pixel of the domain is proposed according to the comparison between observed and simulated land surface temperature. A distributed hydrological model, FEST-EWB, that solves the system of energy and mass balance equations as a function of the representative equilibrium temperature (RET) will be used. RET is comparable to the land surface temperature as retrieved from operational remote sensing data. This equilibrium surface temperature, which is a critical model state variable, is compared to land surface temperature from MODIS. A similar calibration procedure will also be applied performing the traditional calibration using only discharge measurements at different available control cross sections. The effects on river discharge of the Three Gorges dam will be evaluated. The dynamic of the three large lakes (Poyang, Dongting and Taihu), which change considerably their area during the seasons, will also be anlyazed using MERIS data to infer surface area changes and LEGOS altimetry data (Topex/Poseidon, Jason, ENVISAT) for water level. Good correlation has been found between area and water level changes. The FEST-EWB hydrological model is then calibrated and validated against water level data, while lake area changes are used as input data. FEST-EWB is run in for the whole Yangtze River basin at spatial resolution of 0.05° and temporal resolution of 3 hours. Results are provided in terms of hourly evapotranspiration, soil moisture and land surface temperature maps for the period between 2003 to 2006.