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%.

在未经测量的集水区，降雨-径流模型参数的估计非常重要。纳什地貌瞬时单位流量线 (NGIUH) 模型广泛用于预测未测量流域的径流。NGIUH 模型参数根据流域的河网划分进行估计，以获得河序律比。已经提出了使用遥感 (RS) 和地理信息系统 (GIS) 基于地形图和卫星图像来描绘流域河流网络的不同方法。本研究通过对河网图像进行小波图像处理，计算出河网分形维数(D)和主要河流的分形维数(d)。应用剪切波变换来计算分叉比 (R _B）。基于对河网和主要河流长度的分形分析，提出了新的方程来估计 NGIUH 参数。通过计算 Kasilian、Galazchai 和 Heng-Chi 三个流域的洪水过程线来评估所提出的方法。根据结果​​，效率系数 (CE) 为 0.42 和 0.96。峰值流量估计的误差在 0.93-12.91% 的可接受范围内。