Spatial Analysis of Surface Runoff Using SCS-CN Technique Integrated with GIS and Remote Sensing

Jakir Hussain K. N., Vijayakumari Raveendra Channavar, Nagaraj Malappanavar, Varsha Somaraddi Radder, Tejaswini Chandrakar, Jagadeesh B. R, Basavaraj D. B.
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Abstract

The Soil Conservation Service (SCS) Curve Number (CN) method is a widely employed hydrological model for estimating surface runoff in watershed studies. This method utilizes land use, soil characteristics, and hydrologic soil grouping information to assign a CN that represents the potential for surface runoff of a specific area. The paper presents a comprehensive study on surface runoff estimation using the SCS Curve Number method integrated with Geographic Information System (GIS) and remote sensing technologies. The incorporation of GIS enhances the spatial representation and analysis of diverse influencing factors, contributing to more informed decision-making in water resource management. The Loose Coupling Model for Runoff Computation, combining GIS and simulation models, is appropriately employed. The study discusses the methodology, including the Thiessen polygon and the Improved Composite CN Computation Method, showcasing a meticulous approach. Results and discussions are supported by relevant studies, reinforcing the credibility of the research. Overall, the paper provides valuable insights for researchers and practitioners in the field of hydrology and water resource management. Future work in this field could focus on refining the SCS-CN method through improved data integration and model calibration. Additionally, exploring advanced machine learning techniques for enhancing the predictive capabilities of GIS-based surface runoff models could offer valuable insights for sustainable water resource management.
利用 SCS-CN 技术与地理信息系统和遥感技术相结合对地表径流进行空间分析
土壤保持服务(SCS)曲线数(CN)法是一种广泛使用的水文模型,用于估算流域研究中的地表径流。该方法利用土地利用、土壤特性和水文土壤分组信息来分配代表特定区域地表径流潜力的 CN。本文介绍了利用 SCS 曲线数方法并结合地理信息系统(GIS)和遥感技术进行地表径流估算的综合研究。地理信息系统的融入增强了对各种影响因素的空间表示和分析,有助于在水资源管理中做出更明智的决策。本研究适当采用了结合地理信息系统和模拟模型的径流计算松散耦合模型。研究讨论了方法,包括 Thiessen 多边形和改进的复合 CN 计算方法,展示了一种细致的方法。研究结果和讨论得到了相关研究的支持,增强了研究的可信度。总之,论文为水文和水资源管理领域的研究人员和从业人员提供了宝贵的见解。该领域未来的工作重点是通过改进数据集成和模型校准来完善 SCS-CN 方法。此外,探索先进的机器学习技术以提高基于地理信息系统的地表径流模型的预测能力,可为可持续水资源管理提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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