基于GIS和SCS-CN方法的埃塞俄比亚冲洗河流域降雨径流估算

Shimelis Sishah
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引用次数: 4

摘要

了解水文行为是有效流域管理和规划的重要组成部分。降雨产生的径流是水文行为的一个组成部分,是有效水资源规划所必需的。本文采用基于GIS的SCS-CN径流模拟模型对阿瓦什河流域降雨径流进行估算。采用全局曲线数(GCN250)、最大土壤保水量(S)和降雨量作为SCS-CN径流模拟模型的输入。阿瓦什河流域的最终地表径流值是根据年总降雨量和2020年最大土壤保水潜力(S)生成的。研究区径流变化幅度在83.95 mm/年至1416.75 mm/年之间。相反,最近开发的全球曲线数(GCN250)数据使用Pearson相关系数进行测试,作为SCS-CN径流模拟模型的输入。在此过程中,使用GCN250作为模型输入的SCS-CN产生的预测径流与从研究区域的站点测量仪获得的观测径流进行了验证。验证结果表明,预测径流量与实测径流量相关性较好,相关系数为0.9253。从这个角度来看,新的GCN250数据可以作为SCS-CN模型的输入来估计流域水平的降雨径流。此外,对年平均降雨量与地表径流之间的关系进行了相关分析。两变量之间的相关系数为0.9873,呈较强的线性关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rainfall runoff estimation using GIS and SCS-CN method for awash river basin, Ethiopia
Understanding hydrological behavior is an important part of effective watershed management and planning. Runoff resulted from rainfall is a component of hydrological behavior that is needed for efficient water resource planning. In this paper, GIS based SCS-CN runoff simulation model was applied to estimate rainfall runoff in Awash river basin. Global Curve Number (GCN250), Maximum Soil Water Retention (S) and Rainfall was used as an input for SCS-CN runoff simulation model. The final surface runoff values for the Awash river basin were generated on the basis of total annual rainfall and maximum soil water retention potential (S) of the year 2020. Accordingly, a runoff variation that range from 83.95 mm/year to a maximum of 1,416.75 mm/year were observed in the study region. Conversely, recently developed Global Curve Number (GCN250) data was tested with Pearson correlation coefficient to be used as an input for SCS-CN runoff simulation model. In doing so, predicted runoff generated in SCS-CN using GCN250 as a model input was validated with observed runoff obtained from station gauges in the study region. The results of validation show that, predicted runoff was well correlated with observed runoff with correlation coefficient of 0.9253. From this stand point, it is observed that the new GCN250 data can be used as an input for SCS-CN model to estimate rainfall runoff at basin level. Furthermore, correlation analysis was performed to explain the relationship between mean annual rainfall and surface runoff. The relationship between these two variables indicates a strong linear relationship with correlation coefficient of 0.9873.
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