Soil Conservation Service Curve Number Scs Cn Method Current Applications Remaining Challenges And Future Perspectives

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Soil Conservation Service Curve Number (SCS-CN) Method Current Applications, Remaining Challenges, and Future Perspectives

Soil Conservation Service Curve Number (SCS-CN) Method Current Applications, Remaining Challenges, and Future Perspectives
Author :
Publisher : MDPI
Total Pages : 172
Release :
ISBN-10 : 9783036508207
ISBN-13 : 3036508201
Rating : 4/5 (201 Downloads)

Book Synopsis Soil Conservation Service Curve Number (SCS-CN) Method Current Applications, Remaining Challenges, and Future Perspectives by : Konstantinos X. Soulis

Download or read book Soil Conservation Service Curve Number (SCS-CN) Method Current Applications, Remaining Challenges, and Future Perspectives written by Konstantinos X. Soulis and published by MDPI. This book was released on 2021-06-04 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probably, the most well-documented, and at the same time, simple conceptual method for predicting runoff depth from rainfall depth is the Soil Conservation Service curve number (SCS-CN) method. This Special Issue presents the latest developments in the SCS-CN methodology, including, but not limited to, novel applications, theoretical and conceptual studies broadening the current understanding, studies extending the method’s application in other geographical regions or other scientific fields, substantial evaluation studies, and ultimately, key advancements towards addressing the key remaining challenges, such as: improving the SCS-CN method runoff predictions without sacrificing its current level of simplicity; moving towards a unique generally accepted procedure for CN determination from rainfall-runoff data; improving the initial abstraction estimation; investigating the integration of SCS-CN method in long-term continuous hydrological models and the implementation of various soil moisture accounting systems; extending and adopting the existing CNs documentation in a broader range of regions, land uses and climatic conditions; and utilizing novel modeling, geoinformation systems, and remote sensing techniques to improve the performance and the efficiency of the method.


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