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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/14972
Title: Application and analysis of support vector machine based simulation for runoff and sediment yield
Authors: Misra D.
Oommen T.
Agarwal A.
Mishra, Surendra Kumar
Thompson A.M.
Published in: Biosystems Engineering
Abstract: The objective of the study was to use Support Vector Machines (SVM) to simulate runoff and sediment yield from watersheds. Recently, pattern-recognition algorithms such as artificial neural networks (ANN) have gained popularity in simulating rainfall-runoff-sediment yield processes producing comparable accuracy to physics-based models. We have simulated daily, weekly, and monthly runoff and sediment yield from an Indian watershed, with monsoon period data, using SVM, a relatively new pattern-recognition algorithm. Model performance was evaluated using correlation coefficient for evaluating variability, coefficient of efficiency for evaluating efficiency, and the difference of slope of a best-fit line from observed-estimated scatter plots to 1:1 line for evaluating predictability. Time-series data were split into training, calibration and validation sets. The results of SVM were compared to those of ANN. An alternate method, the Multiple Regressive Pattern Recognition Technique (MRPRT), was used for runoff estimation only. The MRPRT did not improve the results significantly compared to SVM, hence, it was not used to simulate sediment yield. We concluded that SVM provided significant improvement in training, calibration and validation as compared to ANN. SVM could be an efficient alternative to ANN, a computationally intensive method, for runoff and sediment yield predictions providing at least comparable accuracy. © 2009 IAgrE.
Citation: Biosystems Engineering (2009), 103(4): 527-535
URI: https://doi.org/10.1016/j.biosystemseng.2009.04.017
http://repository.iitr.ac.in/handle/123456789/14972
Issue Date: 2009
Publisher: Academic Press
ISSN: 15375110
Author Scopus IDs: 35580812700
22951898700
7401480650
55463271000
7404597302
Author Affiliations: Misra, D., Geological Engineering, College of Engineering and Mines, University of Alaska Fairbanks, P.O. Box 755800, Fairbanks, AK 99775, United States
Oommen, T., Tufts University, Department of Civil and Environmental Engineering, 200 College Avenue, Medford, MA 02155, United States
Agarwal, A., National Institute of Hydrology, Roorkee, 247667 Uttaranchal, India
Mishra, S.K., Indian Institute of Technology, Water Resources Development Training Centre, Roorkee, 247667 Uttaranchal, India
Thompson, A.M., Department of Biological Systems Engineering, University of Wisconsin - Madison, 230 Ag. Eng. Building, 460 Henry Mall, Madison, WI 53706, United States
Corresponding Author: Misra, D.; Geological Engineering, College of Engineering and Mines, University of Alaska Fairbanks, P.O. Box 755800, Fairbanks, AK 99775, United States; email: debu.misra@uaf.edu
Appears in Collections:Journal Publications [WR]

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