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Prediction of Ground Water Level using SVM-WOA Approach: A Case Study

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Title Prediction of Ground Water Level using SVM-WOA Approach: A Case Study
 
Creator Satapathy, Deba Prakash
Sahoo, Sujeet Kumar
 
Subject Groundwater level
OUAT
RBFN
Wilmott index
 
Description 269-277
Reliable and accurate estimation of Groundwater Level (GWL) fluctuations is essential and vital for sustainable water
resources management. Due to uncertainties and interdependencies in hydro-geological processes, GWL prediction is
complex by the fact that fluctuation of GWL is extremely nonlinear and non-stationary. Utilising novel methods for
accurately predicting GWL is of vital significance in arid regions. In present work, Support Vector Machine (SVM), in
combination with Whale Optimisation Algorithm (SVM-WOA), is applied to forecast GWL in Bhubaneswar region (Odisha
University of Agricultural Technology). Three quantitative statistical performance assessment indices, coefficient of
determination (R2), Mean Squared Error (MSE), and Wilmott Index (WI), is used to assess model performances. Based on
the assessment with conventional SVM and RBFN models, the performance of hybrid SVM-WOA model is preeminent.
SVM-WOA is capable of predicting nonlinear behavior of GWLs. Proposed modelling technique can be applied in different
regions for proper management of groundwater resources and provides significant information, at a short time scale, to
estimate variability in groundwater at local level.
 
Date 2023-02-08T05:00:52Z
2023-02-08T05:00:52Z
2023-02
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61356
https://doi.org/10.56042/jsir.v82i2.70212
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.82(02) [February 2023]