Ken Hiramatsu

Improving the performance of temperature index snowmelt model of SWAT by using MODIS land surface temperature data.

Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R 2) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations.

Impact of Land-Use Change on Flooding Patterns

Recent unplanned and rapid urbanisation of Dhaka has a possibility to induce serious urban flooding in the near future. To evaluate the impacts of land-use changes on flood propagation patterns, we conducted flood inundation simulations using a two-dimensional finite element method with simplified Saint Venant equations. We used as a study site the mid-eastern part of the city of Dhaka, popularly known as “mid-eastern Dhaka”. Two different land-cover datasets were prepared—one showing land use in 1990 and the other for 2011. In addition, complete land-cover change scenarios were also considered. As for the boundary conditions for flood simulations, we first estimated river discharge by constructing a kind of conceptual hydrologic model called a tank model, since we only have water-level data with daily time resolution at the Balu River mouth. Changes in inundation areas, related to these different land-cover patterns, were then evaluated. The study shows that although no significant difference was detected between the results for land use in 1990 and in 2011, under the complete land-use conversion scenarios, with all wetlands converted to other uses, both flood propagation time and flooding area will significantly change. Thus, the simulation results prove that the presence of wetland in land cover reduces flood risk, as compared with other land use. While further validations of flood simulation results are required, our results may provide data useful for proper flood management in achieving urban sustainability.