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

Autor: T. Sabzevari, Mohammad Hadi Fattahi, T. Derikvand, M. Tarahi
Rok vydání: 2021
Předmět:
Zdroj: Stochastic Environmental Research and Risk Assessment. 36:51-66
ISSN: 1436-3259
1436-3240
DOI: 10.1007/s00477-021-02068-z
Popis: 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 (RB). 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%.
Databáze: OpenAIRE
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