The determination of soil characteristics is important in the simulation of rainfall runoff using a distributed FLO-2D model in catchment analysis. Digital maps acquired using remote sensing techniques have been widely used in modern hydrology. However, the determination of a representative parameter with spatial scaling mismatch is difficult. In this investigation, the FLO-2D rainfall-runoff model is utilized in the Yongdam catchment to test sensitivity based on three different methods (mosaic, arithmetic, and predominant) that describe soil surface characteristics in real systems. The results show that the mosaic method is costly, but provides a reasonably realistic description and exhibits superior performance compared to other methods in terms of both the amount and time to peak flow.

The real-time monitoring of surface vegetation is essential for the management of droughts, vegetation growth, and water resources. The availability of land cover maps based on remotely collected data makes the monitoring of surface vegetation easier. The vegetation index in an area is likely to be proportional to meteorological elements there such as air temperature and precipitation. This study investigated relationship between vegetation index based on Moderate Resolution Image Spectroradiometer (MODIS) and ground-measured meteorological elements at the Yongdam catchment station. To do this, 16-day averaged data were used. It was found that the vegetation index is well correlated to air temperature but poorly correlated to precipitation. The study provides some intuition and guidelines for the study of the droughts and ecologies in the future.