...
首页> 外文期刊>Stochastic environmental research and risk assessment >Estimating runoff in ungauged catchments by Nash-GIUH model using image processing and fractal analysis
【24h】

Estimating runoff in ungauged catchments by Nash-GIUH model using image processing and fractal analysis

机译:Estimating runoff in ungauged catchments by Nash-GIUH model using image processing and fractal analysis

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Estimation of rainfall-runoff model parameters in ungauged catchments is of significant importance. The Nash geomorphological instantaneous unit hydrograph (NGIUH) model is widely used to predict runoff in ungauged catchments. The NGIUH model parameters are estimated based on the stream network delineation of the catchment to obtain the stream-order-law ratios. Different methods have been presented to delineate stream networks of catchments based on topographic maps and satellite images using remote sensing (RS) and geographic information system (GIS). In this study, the fractal dimension of the stream network (D) and the fractal dimension of the main river (d) were calculated by wavelet image processing of the stream network images. Shearlet transform was applied to compute the bifurcation ratio (R-B). New equations were proposed to estimate the NGIUH parameters based on the fractal analysis of the river network and main river length. The proposed approach was evaluated by computing the flood hydrographs in three catchments of Kasilian, Galazchai and Heng-Chi. Based on results, coefficients of efficiency (CE) were 0.42 and 0.96. The errors in peak discharge estimation were in an acceptable range 0.93-12.91%.

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号