Spatial Interpolation of Sediment Yield Estimated from Reservoir Siltation Data of India
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RESEARCH PAPER
Spatial Interpolation of Sediment Yield Estimated from Reservoir Siltation Data of India Y. C. Jabbar1 · S. M. Yadav1 Received: 20 April 2018 / Accepted: 16 May 2020 © Shiraz University 2020
Abstract Estimation of design sediment yield (SY) on a long-term basis is necessary to allocate adequate reservoir dead storage space. Incompetence of the distributed SY models with the input data (of spatial and temporal scale) leads to an error in model results. Therefore, prudent management of the calibration and validation process of SY predicting model is essential. The absence of the observed SY data brings indeterminacy in the validation process. However, a reference value for validation can be determined with spatial interpolation of the observed regional SY. In the present study, 161 spatially distributed Indian reservoirs were analyzed. Considering SY computed from these reservoirs as sampling values, inverse distance weighting and various Kriging interpolation methods were used to generate 25 interpolated datasets. Optimization of interpolation parameters is carried out by an exhaustive cross-validation process, and the best-interpolated surface is identified. Comparing the observed and predicted SY, the coefficient of determination is found to be 0.78, with the index of agreement being 0.88. This obtained surface model was utilized to generate a sediment yield contour map for India. Keywords Inverse distance weighting · Variogram · Kriging · Reservoir sedimentation · Sediment yield
1 Introduction Sediment yield (SY) of a catchment can be defined as the delivery of sediment load from a delineated catchment area to a particular location within a definite period of time. Prediction of design SY is critical to the useful life of the reservoir. Fixing the level at which the spillway gates and flushing gates are to be installed depends on the SY rate. Direct measurement (stream measurement) and quantification of reservoir trap sediments will provide information about the sediment produced and delivered by a catchment (Bussi et al. 2013; Jabbar and Yadav 2019a, b; Van Rompaey et al. 2003; Verstraeten and Poesen 2002). However, both Electronic supplementary material The online version of this article (https://doi.org/10.1007/s40996-020-00420-x) contains supplementary material, which is available to authorized users. * Y. C. Jabbar [email protected]; [email protected] 1
S. M. Yadav [email protected]; [email protected]
Department of Civil Engineering, S. V. National Institute of Technology, Surat, Gujarat 395007, India
the observation techniques (i.e., stream gauging and quantification of reservoir trap sediments) have their drawbacks and benefits. In stream gauging, the bed load is not observed as there are practical limitations for measuring bed load. A high temporal resolution of suspended sediment data is required for a fair SY assessment (Walling 1977). The need for high temporal resolution data can be sufficed by linking sediment rating curve (SRC) to the flow duration curve
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