Application of the SCS–CN Method Integrated with GIS and Remote Sensing for Watershed Runoff Estimation: A Review
Sudhir Lad *
Department of SWCE, Dr. A. S. G. College of Agricultural Engineering and Technology, M. P. K. V., Rahuri, Maharashtra, India.
Ravindra Bansod
Dr. A. S. G. College of Agricultural Engineering and Technology, M. P. K. V., Rahuri, Maharashtra, India.
Bhaupatil Gavit
M. P. K. V., Rahuri, Maharashtra, India.
Sachin Nandgude
Department of SWCE, Dr. A. S. G. College of Agricultural Engineering and Technology, M. P. K. V., Rahuri, Maharashtra, India.
Shailendra Gadge
Department of Irrigation and Drainage Engineering, M. P. K. V., Rahuri, Maharashtra, India.
Mahesh Patil
Department of Agricultural Statistics, M. P. K. V., Rahuri, Maharashtra, India.
*Author to whom correspondence should be addressed.
Abstract
Accurate estimation of runoff is crucial for watershed planning, soil and water conservation, flood mitigation, and the management of ungauged watersheds. The Soil Conservation Service Curve Number (SCS-CN) method has been extensively used because of its minimal input requirements and its ability to model the spatial influence of land use, soil properties, and hydrologic soil groups. This review compiles applications of the GIS-based SCS-CN method reported for watersheds in semi-arid and monsoon-affected countries such as India, Saudi Arabia, Afghanistan, China, Iraq, and Ethiopia. The reviewed literature employed rainfall data, land-use/land-cover data, soil maps, hydrologic soil groups, digital elevation models, and watershed morphometry to calculate curve numbers and direct runoff. The reported CN values varied substantially, from about 40 under dry conditions to more than 90 under urban, rocky, agricultural, or poorly infiltrating conditions. Runoff estimates ranged from relatively low values in arid catchments to more than 1,300 mm per year in high-rainfall watersheds. Several studies reported high R2 correlations between observed and estimated runoff, typically ranging from 0.73 to 0.98. Important limitations identified in the review include the sensitivity of results to the choice of curve number, antecedent moisture condition, initial abstraction assumption, land-use classification, soil-group assignment, rainfall representation, and the lack of observed discharge data. The overall design of the SCS-CN method and its integration with RS and GIS offer a practical approach to assessing spatial runoff and prioritising watersheds, but the method requires local calibration, uncertainty analysis, and validation against observed rainfall–runoff data.
Keywords: Runoff estimation, SCS-CN method, geographic information system, remote sensing, curve number, hydrologic soil group, antecedent moisture condition, watershed management, ungauged watersheds, rainfall–runoff modelling