Analyzing the prediction uncertainty of a distributed hydrological model based on DEM with different spatial resolutions

摘要：

Spatial resolution of a distributed hydrological model is a dominant attribution for model complexity. Lower spatial resolution brings significant decrease of computational consuming but results in higher distortion of hydrological representation. This paper investigated a most efficient spatial resolution by comparing both prediction uncertainties and computing costs. The prediction uncertainty estimation of Geomorphology-based Hydrological Model (GBHM) with four different spatial resolutions in Linken catchment, Jiangxi, China, was performed using Generalized Likelihood Uncertainty Estimation (GLUE) methodology. Parameters for Monte Carlo sampling in GLUE included Slope Shape Factor (SSF), saturated hydraulic conductivity, and roughness both on the hillslope and in the river channel. The results show that prediction uncertainty increases with the simplification of spatial resolution, while the differences between expectations of predicted discharges are little. It suggests moderate spatial resolution being chosen when the prediction uncertainty mostly lies on the parameter uncertainty.

关键词： prediction uncertainty spatial resolution GBHM GLUE distributed hydrological model

作者: Mingliang LI Dawen YANG

作者单位: State Key Laboratory of Hydroscience and Engineering,Department of Hydraulic Engineering,Tsinghua University,Beijing 100084,China

会议类型: 国际会议

会议名称: The Four Conference of Asia Pacific Association of Hydrology and Water Resources(亚太地区水文水资源协会第4届科学大会)

会议地点: 北京

会议语种:英文

页码: 37-41

在线出版日期: 2008-11-03（万方平台首次上网日期，不代表论文的发表时间）