Saltwater intrusion prediction in coastal aquifers utilizing a weighted-average heterogeneous ensemble of prediction models based on Dempster-Shafer theory of evidence

Roy, Dilip Kumar, and Datta, B. (2020) Saltwater intrusion prediction in coastal aquifers utilizing a weighted-average heterogeneous ensemble of prediction models based on Dempster-Shafer theory of evidence. Hydrological Sciences Journal, 65 (9). pp. 1555-1567.

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Abstract

Accurate and meaningful prediction of saltwater intrusion in coastal aquifers requires appropriate prediction tools. Artificial intelligence-based prediction models and their ensembles have been a better choice for mimicking the complex and nonlinear seawater intrusion progressions in coastal aquifers. This study utilizes a weighted-average ensemble of 'heterogeneous' prediction models to predict the saltwater intrusion progression in a coastal aquifer study area. The Dempster-Shafer theory of evidence is employed to calculate the weights of five different prediction model algorithms. Corresponding weights for individual prediction models are utilized in developing the ensemble prediction. Ensemble prediction performance for salinity intrusion in coastal aquifers in this effort is evaluated using several descriptive metrics. The values of the descriptive metrics suggest that the ensemble model performs in the same way as the best model in the ensemble. The methodology is evaluated for an illustrative coastal aquifer study area exposed to pumping-induced saltwater intrusion.

Item ID: 63304
Item Type: Article (Research - C1)
ISSN: 2150-3435
Keywords: saltwater intrusion, coastal aquifer, prediction model, Dempster-Shafer theory, heterogeneous ensemble
Copyright Information: © 2020 IAHS
Date Deposited: 27 May 2020 07:34
FoR Codes: 40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering @ 100%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180399 Fresh, ground and surface water systems and management not elsewhere classified @ 100%
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