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Active microwave remote sensing of soil moisture : a case study in Kurukavak Basin

Yılmaz, Musa
Soil moisture condition of a watershed plays a significant role in separation of rainfall into infiltration and surface runoff, and hence is a key parameter for the majority of physical hydrological models. Due to the large difference in dielectric constants of dry soil and water, microwave remote sensing and particularly the commonly available synthetic aperture radar is a potential tool for such studies. The main aim of this study is to produce the distributed soil moisture maps of a catchment from active microwave imagery. For this purpose, nine field trips are performed within a small basin in western Anatolia and point surface soil moisture values are collected with a Time Domain Reflectometer. The field studies are planned to match radar image acquisitions and accomplished over the water year of 2004 - 2005. In this context, first, the Dubois Model, a semi-empirical backscatter model is utilized in the reverse order to develop radar backscatter soil roughness relationship and soil roughness maps of the study area are obtained. Then another relationship is built between radar backscatter and the three governing surface parameters: local incidence angle, soil moisture and soil roughness, which is later used in the soil moisture estimation methods. Depending on land use and vegetation cover condition, surface soil moisture maps of the catchment are produced by Backscatter Correction Factors, Water Cloud Model and Basin Indexes methods. In the last part of the study, the soil moisture maps of the basin are input to a semi-distributed hydrological model, HEC-HMS, as the initial soil moisture condition of a flood event simulation. In order to investigate the contribution of distributed initial soil moisture data on model outputs, simulation of the same flood event is also performed with the lumped initial soil moisture condition. Finally, a comparison between both the distributed and lumped model simulation outputs and with the observed data is carried out.