2022 年 32 巻 S 号 p. 151-154
Floods in arid areas provide fertile soil and water resources, enabling agricultural production. Likewise, large floods will cause enormous human and economic damage. The Pech River, our study site, is a tributary of the Kunar River, which runs through eastern Afghanistan. The main source of the river discharge moisturizing the towns on the foothills is melted snow in the upper mountainous areas. Its maximum discharge changes depending on the amount of snowfall in winter. Therefore, it is necessary to predict the peak discharge in spring in advance and provide an appropriate flood warnings system. In this study, we tried to predict the peak discharge based on the fluctuation of snow cover area, temperature, and rainfall of the upper reaches of the Pech River. First, the boundary of the river catchment was identified based on the Digital Elevation Model (DEM) of 30 m mesh acquired by Advanced Land Observing Satellite (ALOS). Next, the Snow cover distribution data between 2008 and 2018 at weekly intervals was downloaded from the National Snow & Ice Data Center (NSIDC) database, and the catchment area was extracted. Daily observed temperature and precipitation data were expected as the parameter explaining the snow melting process in spring. We tried to reproduce the discharge of the Pech River using Artificial Neural Network (ANN). The temporal variation of the discharge was not linear to snow cover area, but ANN could reproduce it.