Surface runoff estimation of Sind river basin using integrated SCS-CN and GIS techniques

Rainfall and runoff are the significant hydrologic component in the water resources assessment. Numerous methods are available to estimate runoff from rainfall; however, the SCS-CN method remains the most popular and frequently used method as runoff curve number (CN) is a crucial factor of the SCS-C...

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Autores principales: Abanish Kumar, Shruti Kanga, Ajay Kumar Taloor, Suraj Kumar Singh, Bojan Đurin
Formato: article
Lenguaje:EN
Publicado: KeAi Communications Co., Ltd. 2021
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Acceso en línea:https://doaj.org/article/6960b2a9192a40e4adfd86814a2114b9
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Sumario:Rainfall and runoff are the significant hydrologic component in the water resources assessment. Numerous methods are available to estimate runoff from rainfall; however, the SCS-CN method remains the most popular and frequently used method as runoff curve number (CN) is a crucial factor of the SCS-CN method and depends on land use/land cover (LULC), soil type, and antecedent soil moisture (AMC). Besides this, various parameters, such as Hydrological Soil Characteristics (HSG), precipitation (P), Potential Maximum Retention (PMR), Antecedent Moisture Condition (AMC), Weighted Curve Number (WCN), are the mandatory inputs to the SCS-CN model. In the results, the daily runoff from the Sind river basin for ten years, i.e., 2005 to 2014, has been used. As a result, the average annual surface runoff calculated for the Sind river basin is 133.71 mm. The total average volume of runoff is 35.04 × 10 8 m 3, representing 17.21% of the total average annual rainfall.