Paper
Runoff Prediction in Ungauged Watersheds Using Remote Sensor Datasets
- Authors:
- Jong Pil Kim; Won Kim; Il-Won Jung; Gwangseob Kim
- Abstract
- Runoff prediction in ungauged watersheds is regarded as one of the major issues in contemporary hydrology. This study examined the utility of remote sensor datasets for parameter regionalization. A distributed hydrologic model, the Coupled Routing and Excess Storage (CREST) model, was employed to simulate runoff conditions in the mountainous watersheds over South Korea. In gauged watersheds, the relationships between the optimized parameter set of the hydrologic model and the physiographic properties of the gauged watersheds were investigated using multiple linear regressions. The regression parameters for the ungauged watersheds were then validated and assessed. Results demonstrated that the hydrologic model and the proposed regression equations could acceptably simulate the discharge in both gauged and ungauged watersheds. However, they provided somewhat biased discharge for all the ungauged watersheds. In further studies, these biases should be reduced by investigating other watersheds and finding physiographic properties highly related to the model parameters.
- Keywords
- Runoff Prediction; Ungauged Watersheds; TRMM; Multi-satellite; Regionalization
- StartPage
- 257
- EndPage
- 264
- Doi
- 10.5963/JWRHE0403007