Abstract
The curve number method was developed by the USDA Natural Resources Conservation Service, which was formerly called the Soil Conservation Service or SCS. It is widely used in hydrological investigations. The present study is an attempt to estimate surface runoff using SCS curve number method coupled with remote sensing and GIS tools. SCS is an empirical formula based on curve numbers that are defined using landuse and hydrological soil groups. In 2016, Muche derived relation between curve number and NDVI considering soil classes. His study utilized 12 years of rainfall and runoff data from four small watersheds in Northeast Kansas on the Konza Prairie Long-Term Ecological Research (LTER). A relationship is developed based on practical tests that used here; for our study area, we have calculated runoff using both methods, i.e., using direct value of curve number and derived NDVI. Nasiri and Alipur (Int J Environ Chem Ecol Geol Geophys Eng 8(5):342–345, 2014) determined curve number using NDVI. Our result shows similar pattern of runoff using both the methods. Therefore, his equation can be used for any soil type. Because natural vegetation type also depends on soil type and urban landuse classes, so it is possible to link CN with NDVI that used in this study. In this study, we used pre-defined soils by FAO. The study area lies in single soil of hydrological soil group C. Usable range of curve number is between 30 and 98 where lower curve number value represents more infiltration and less runoff. Higher value represents more runoff and less infiltration (Fan et al. in Remote Sens 5:1425–1438, 2013). This study attempts to link these values with NDVI. This study used to drive runoff using SCS curve number method using GIS model. The results from both the methods are also validated by taking 400 random sample points and compared runoff value with the observed. It is found that runoff is based on NDVI and without NDVI having relation of r2 = 0.80. This is acceptable for any area for estimation of surface runoff.
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References
Fan F, Deng Y, Hu X, Weng Q (2013) Estimating composite curve number using an improved SCS-CN method with remotely sensed variables in Guangzhou, China. Remote Sens 5(3):1425–1438
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Nasiri A, Alipur H (2014) Determination the curve number catchment by using GIS and remote sensing. Int J Environ Chem Ecol Geol Geophys Eng 8(5):342–345
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Acknowledgements
The authors would like thanks for the support of the sponsor project “Assessment of Climate change and its impact on urban hydrology: Indian Perspective [Project Number = AIC-566-WRC].”
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Singh, L., Khare, D. (2021). Estimation of Surface Runoff Using SCS Curve Number Method Coupled with GIS: A Case Study of Vadodara City. In: Pandey, A., Mishra, S., Kansal, M., Singh, R., Singh, V. (eds) Water Management and Water Governance. Water Science and Technology Library, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-58051-3_14
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