Ecohydrological Assessment Tool (Ecohat) System And Its New Application Cases

Ecohydrological process model driven by remote sensing data has been international research hotspots in the fields of water resources and water environment, along with the technology development in RS, GIS, and computer. Ecohydrological Assessment Tool (EcoHAT) system is one for simulations of ecohydrological processes. This paper introduces some new application cases of EcoHAT system, discussing the coupling of remote sensing data and the models with physical mechanism. To understand the main issues in fields of water resources and water environment, including water resource evaluation in an ungauged basin, lower soil water simulation at a large scale, simulation of pollution loads from non - point sources, and impact analysis of riparian basin. Spatially, simulation and analysis on water resources and water environment at a large scale has been done through modifying structure of physical models to realize their coupling with remote sensing data. Thus, key parameters of the models will be obtained or determined from public remote sensing products, to reduce the dependence on field monitoring data in traditional methods. For ungauged basin without suitable hydrological models or abundant data, we have constructed a remote sensing data driven distributed hydrological model (RS - DTVGM) coupling with the TRMM and FY - 2 precipitation products and the MODIS LST products, to evaluate water resource. A soil water model with physical mechanism has been coupled with remote sensing data, including the FY - 2 precipitation product, MODIS data and GLDAS data from public platform, to simulate lower layer soil water movement at a large scale in Weihe River. Pollutant loads from non - point sources in a large - scale basin (ENPS - LSB) is estimated and the impacts of riparian is analyzed in Hainan province from 2003 to 2007 by modifying of the model and constructing a riparian model (RIPAM). By comparison with the experiment data, the simulation results are found to be in acceptable differences. Future breakthroughs in scale transformation and interpolation techniques of remote sensing data from multi - source will help improve our understanding in ecohydrological processes.