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2022 | OriginalPaper | Chapter

15. Curve Numbers Computation Using Observed Rainfall-Runoff Data and RS and GIS-Based NRCS-CN Method for Direct Surface Runoff Estimation in Tilaiya Catchment

Authors : Ravindra Kumar Verma, Ashish Pandey, Surendra Kumar Mishra

Published in: Geospatial Technologies for Land and Water Resources Management

Publisher: Springer International Publishing

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Abstract

Natural Resource Conservation Services-Curve Number (NRCS-CN) method is commonly used in hydrologic and geological sciences for surface runoff estimation in ungauged watersheds for various hydrological applications because it requires very few parameters in comparison with other hydrological methods. Curve Number (CN) is one of the most sensitive parameters of the method because it accounts for most of the watershed runoff producing response characteristics. Therefore, this study aims to compute different CNs to estimate surface runoff in the Tilaiya catchment of the Barakar river basin, Jharkhand, in eastern India. For this, firstly, two approaches were applied to compute CNs values for different antecedent soil moisture conditions: (i) from observed rainfall-runoff (PQ) events data (CNPQ), (ii) GIS-based NRCS-CN method (CNRS) using RS inputs in the observed period 2001–2010, and secondly, surface runoff was estimated by applying the computed CNs values at daily and event scale. As a result of calculating the datasets of CNs values for the years, 2001–2010 shows a large variability of CN. On the other hand, the GIS-based NRCS-CN method of estimating CNs presented in this study shows the characteristics of the catchment and actual rainfall. Estimated runoff using the CNPQ exhibited better results than fixed values applied in the GIS-based NRCS-CN method and could be used for planning, developing, and managing the water resource in the Tilaiya catchment.

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Metadata
Title
Curve Numbers Computation Using Observed Rainfall-Runoff Data and RS and GIS-Based NRCS-CN Method for Direct Surface Runoff Estimation in Tilaiya Catchment
Authors
Ravindra Kumar Verma
Ashish Pandey
Surendra Kumar Mishra
Copyright Year
2022
DOI
https://doi.org/10.1007/978-3-030-90479-1_15

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