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TR(BR)-4/98-99 : Long term hydrologic simulation using SCS-CN method

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dc.contributor.author Mishra, S. K.
dc.contributor.author Singh, R. D.
dc.date.accessioned 2019-05-24T04:15:43Z
dc.date.available 2019-05-24T04:15:43Z
dc.date.issued 1998
dc.identifier.uri http://117.252.14.250:8080/xmlui/handle/123456789/2562
dc.description.abstract Hydrologic simulation studies provide a useful and important input to water resources planning and watershed management practices. The Soil Conservation Service (SCS, 1956) Curve Number (SCS-CN) method is a widely used event based rainfall-runoff method. In this .report, the SCS-CN method is used for simulating daily rainfall-runoff data of three catchments, viz., Ramganga (area = 3134 sq. km) and Hemavati catchments (area = 600 sq. km) falling in sub-humid regions and Sabarmati catchment (area = 5240 sq. km) falling in the arid region of India. In the model formulation, the daily variation of parameter potential maximum retention is governed by known antecedent moisture condition. Simulation of Ramganga data is performed using data in its primitive form as well as the data perturbed about seasonal means, identified as Case A and Case B, respectively. The usage of perturbed data in Case B parallels the concept of linear perturbation model (LPM) (Nash and Barsi, 1983). The simulation results of Case B exhibit better performance than those of Case A as well as the results of the LPM, in validation period of 6 years. The Case A results exhibit efficiency of 50.073% in calibration and 67.299% in validation in Ramganga application, 72.444 % in calibration and 75.567% in validation in Hemavati application, and 47.693 % in calibration and 59.694% in validation in Sabarmati application. Thus, the simulation model has exhibited better performance on the catchments falling in the sub-humid region than that falling in the arid region. A sensitivity analysis of the model is also performed on the Hemavati data used in validation. The parameters CN, d1, d2, d3, d4are found to be more sensitive than X, NLAG, and bf and, therefore, require careful estimation for field applications. en_US
dc.language.iso en en_US
dc.publisher National Institute of Hydrology en_US
dc.relation.ispartofseries ;TR(BR)-4/98-99
dc.subject Long term hydrologic simulation en_US
dc.subject SCS-CN method en_US
dc.title TR(BR)-4/98-99 : Long term hydrologic simulation using SCS-CN method en_US
dc.type Technical Report en_US


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