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Environmental Earth Sciences

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01.10.2022 | Thematic Issue

Integration of group method of data handling (GMDH) algorithm and population-based metaheuristic algorithms for spatial prediction of potential groundwater

verfasst von: Sahar Amiri-Doumari, Ahmadreza Karimipour, Seyed Nader Nayebpour, Javad Hatamiafkoueieh

Erschienen in: Environmental Earth Sciences | Ausgabe 20/2022

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Abstract

Potable water scarcity is a worldwide issue that can be addressed by looking for new regions with adequate groundwater. The study used a combination of three metaheuristic optimization algorithms (particle swarm optimization (PSO), grey wolf optimizer (GWO), and ant colony optimization (ACO)) and a group method of data handling (GMDH) algorithm to delineate groundwater potential zones in Boroujen, Iran. The spatial datasets were created using twelve conditioning factors and spring data (429 locations). The mentioned dataset was divided into two training (70%) and validation (30%) groups. The weights generated from the frequency ratio (FR) method were utilized as modeling inputs. The groundwater potential maps were created using the GMDH, GMDH-PSO, GMDH-GWO, and GMDH-ACO algorithms. With an area under the receiver operating characteristic curve (AUC-ROC) of 87.4%, the GMDH-PSO algorithm outperformed the GMDH-GWO, GMDH-ACO, and GMDH algorithms, which had AUC-ROC values of 85.1%, 83.3% and 80.3%, respectively. Furthermore, the regression relief (Rrelief) method revealed that rainfall, land use/cover, and altitude play a greater role in groundwater assessment. The findings of this research could help with groundwater resource management and groundwater investment planning for long-term sustainability.

Vorheriger Artikel Delineation of kaolinised and aquifer formations using electrical resistivity tomography (ERT) and induced polarization (IP) techniques

Nächster Artikel Environmental fragility as an indicator of the risk of contamination by human action in watersheds used for public supply in western Paraná, Brazil

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Titel: Integration of group method of data handling (GMDH) algorithm and population-based metaheuristic algorithms for spatial prediction of potential groundwater
verfasst von: Sahar Amiri-Doumari
Ahmadreza Karimipour
Seyed Nader Nayebpour
Javad Hatamiafkoueieh
Publikationsdatum: 01.10.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Environmental Earth Sciences / Ausgabe 20/2022
Print ISSN: 1866-6280
Elektronische ISSN: 1866-6299
DOI: https://doi.org/10.1007/s12665-022-10593-5

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