Predicting Saltwater Intrusion into Coastal Aquifers Using Support Vector Regression Surrogate Models

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faal Fatemeh; GHAFOURI HAMID REZA; ASHRAFI SEYED MOHAMMAD

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Paper Information

Journal: WATER AND WASTEWATER Year:2020 | Volume:31 | Issue:2 (126) Page(s): 118-129

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Information Journal Paper

Title

Predicting Saltwater Intrusion into Coastal Aquifers Using Support Vector Regression Surrogate Models

Author(s)

faal Fatemeh | GHAFOURI HAMID REZA | ASHRAFI SEYED MOHAMMAD | Issue Writer Certificate

Keywords

Coastal AquifersQ2

Saltwater IntrusionQ1

Surrogate ModelsQ1

Support Vector RegressionQ1

Prediction CapabilityQ1

Abstract

The prediction of the intrusion of saline water into Coastal Aquifers as a result of changing the amount of groundwater extractions is a prerequisite for managing groundwater. This study investigates the capability of different types of Support Vector Regression (SVR) models to predict salinity concentrations at the selected well in the small coastal aquifer under different groundwater abstraction conditions. SVR models were trained and tested using input (random transient pumping from the production wells) derived from Latin Hypercube Sampling and output (salinity concentration at the selected well) datasets. The trained and tested models were then used to predict salinity concentrations at the selected well for new pumping datasets. The models ability for predicting and generalizing compared with commonly used artificial neural network (ANN) model was evaluated using different performance criteria. The results of the performance evaluation of the models showed that the predictive capability of the polynomial SVR model is superior to other models. Also, comparing different performance criteria for all SVR models, except for linear SVR model, proved their acceptable predictive performance. The prediction and generalisation ability of polynomial SVR, recommends using these models to connect to the optimization algorithm for a surrogate model based simulation-optimization approach in sustainable management of Coastal Aquifers.

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APA: Copy

faal, Fatemeh, GHAFOURI, HAMID REZA, & ASHRAFI, SEYED MOHAMMAD. (2020). Predicting Saltwater Intrusion into Coastal Aquifers Using Support Vector Regression Surrogate Models. WATER AND WASTEWATER, 31(2 (126) ), 118-129. SID. https://sid.ir/paper/104047/en

Vancouver: Copy

faal Fatemeh, GHAFOURI HAMID REZA, ASHRAFI SEYED MOHAMMAD. Predicting Saltwater Intrusion into Coastal Aquifers Using Support Vector Regression Surrogate Models. WATER AND WASTEWATER[Internet]. 2020;31(2 (126) ):118-129. Available from: https://sid.ir/paper/104047/en

IEEE: Copy

Fatemeh faal, HAMID REZA GHAFOURI, and SEYED MOHAMMAD ASHRAFI, “Predicting Saltwater Intrusion into Coastal Aquifers Using Support Vector Regression Surrogate Models,” WATER AND WASTEWATER, vol. 31, no. 2 (126) , pp. 118–129, 2020, [Online]. Available: https://sid.ir/paper/104047/en

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