Modelling soil erosion from a watershed using cubic splines
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ORIGINAL PAPER
Modelling soil erosion from a watershed using cubic splines Sarita Gajbhiye Meshram 1,2 & P. L. Powar 2 & Vijay P. Singh 3,4
Received: 16 June 2016 / Accepted: 14 February 2017 # Saudi Society for Geosciences 2017
Abstract Erosion in a watershed exhibits spatial and temporal variability, and its determination is fundamental to determining sediment yield which is a key to proper watershed management. In this study, we propose a relationship between the curve number (SCS 1956) and Sediment Yield Index (SYI) using cubic splines. The method is illustrated with a case study of one watershed of Narmada Basin located in Mandla district of Madhya Pradesh, India. Cubic splines are found to perform satisfactorily with Nash efficiency of 63.64%, absolute prediction error of 2.64%, integral square error of 1.22%, coefficient of correlation of 93.78% and degree of agreement of 0.99%. The relation between observed and computed SYI values is correlated with a coefficient of determination (R2) of 0.87. Such a relationship can be used to determine SYI from the available CN value, which may be quite useful in field applications.
* Sarita Gajbhiye Meshram [email protected] P. L. Powar [email protected] Vijay P. Singh [email protected] 1
Department of Water Resources Development & Management, Indian Institute of Technology, Roorkee, Uttrakhand, India
2
Department of Mathematics and Computer Science, R. D. University, Jabalpur, Madhya Pradesh, India
3
Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843-2117, USA
4
Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843-2117, USA
Keywords Watershed . Runoff curve number . Sediment Yield Index (SYI) . Cubic spline
Introduction Soil, water and vegetation are essential natural resources, and their management is fundamental to the maintenance of ecosystem and economic development. Efficient utilization of water and proper treatment of soil are therefore essential. In India, about 175 M/ha area, which constitutes about 53% of the aggregate geographical area, is subjected to land degradation due to soil erosion. It is estimated that 5334 million tons of soil is eroded annually, which is a matter of serious concern for agricultural productivity (Sebestain et al. 1995). Soil erosion entails detachment and transport of soil particles. Although wind and glaciers also cause soil erosion in some areas, water is the primary agent causing soil erosion. In watershed planning and management, erosion is generally considered as an essential component of management strategies (Sharma et al. 2014b). There are many soil erosion prediction models (physically, conceptual or empirical) that have been employed in different parts of the world (Nazzareno and Sergio 2009). Although physically based models have proven very useful as a research tool, they are of limited use in field, especially in developing countries like India, because of their large data requirements. It is not possible to coll
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