Stream Network Modeling Using Remote Sensing Data in an Alpine Cold Catchment

The hydrological information derived from a digital elevation model is very important in distributed modeling. As part of alpine research on stream network modeling using remote sensing data the northeast Tibetan Plateau, three (DEM) datasets were obtained for purpose features, mainly including channel network, watershed extent and terrain character. sources include airborne light detection ranging (LiDAR) with point spacing 1 m, High Mountain Asia (HMA) DEM Shuttle Radar Topography Mission (SRTM) DEM. Mapping was conducted each datasets. modeled networks different DEMs verified against actual mapped field. results show that LiDAR most accurate representation SRTM overestimated basin hypsometry relative to at lowest elevation, while HMA underestimated highest elevation. This may be because, compared DEM, has higher initial density, accuracy resolution. It can seen have great potential application hydrologic water resource management small catchments.