Assessing groundwater artificial recharge suitability in the Mi River basin using GIS, RS, and FAHP: a comprehensive analysis with seasonal variations

Applied Water Science, Journal Year: 2025, Volume and Issue: 15(2)

Published: Jan. 29, 2025

Language: Английский

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Enhancing Groundwater Recharge Assessment in Mediterranean Regions: A Comparative Study Using Analytical Hierarchy Process and Fuzzy Analytical Hierarchy Process Integrated with Geographic Information Systems for the Algiers Watershed

Sustainability, Journal Year: 2025, Volume and Issue: 17(7), P. 3242 - 3242

Published: April 5, 2025

Groundwater recharge is critical for sustainable water management in water-scarce regions like North Algeria, where climate change and urbanization exacerbate resource challenges, particularly the populous Algiers watershed. This study evaluates groundwater potential using Analytical Hierarchy Process (AHP) its fuzzy extension (FAHP), integrated with Geographic Information Systems (GIS), to map zones. Employing open-source data, AHP FAHP assessed factors such as lithology, slope, rainfall, classifying watershed into high, moderate, low Results show identifying 44.01% (528.95 km2) 52.82% (634.93 3.18% (38.14 potential, yielding similar outcomes (44.35%, 52.47%, 3.17%, respectively). Validation borehole drawdown data confirmed a 73.3% accuracy an AUC of 0.72, indicating moderate good reliability. High zones were concentrated central northern areas permeable soils gentle slopes, dominated region, minimal. concludes that both are effective preliminary assessments, favored simplicity, though excels uncertain data. Limited high-resolution hydrogeological highlight need further refinement, yet approach offers replicable framework managing arid, urbanized facing environmental pressures.

Language: Английский

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Evaluation of Groundwater Potential Zones Using GIS‐Based Machine Learning Ensemble Models in the Gidabo Watershed, Ethiopia

Global Challenges, Journal Year: 2024, Volume and Issue: 8(12)

Published: Oct. 16, 2024

Abstract The main objective of this study is to map and evaluate groundwater potential zones (GWPZs) using advanced ensemble machine learning (ML) models, notably Random Forest (RF) Support Vector Machine (SVM). GWPZs are identified by considering essential factors such as geology, drainage density, slope, land use/land cover (LULC), rainfall, soil, lineament density. This combined with datasets used for training validating the RF SVM which consisted 75 sites (boreholes springs), 22 non‐potential (bare lands settlement areas), 20 (water bodies). Each dataset randomly partitioned into two sets: (70%) validation (30%). model's performance evaluated area under receiver operating characteristic curve (AUC‐ROC). AUC model 0.91, compared 0.88 model. Both models classified effectively, but performed slightly better. GWPZ shows that high typically located within water bodies, natural springs, low‐lying regions, forested areas. In contrast, low primarily found in shrubland grassland vital decision‐makers it promotes sustainable use ensures security studied area.

Language: Английский

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Delineating Potential Groundwater Recharge Zones in the Semi‐Arid Eastern Plains of Rajasthan, India

CLEAN - Soil Air Water, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 10, 2024

ABSTRACT Surface and subsurface anomalies, hydrological conditions, dynamic interactions between embedded thematic layers influence groundwater recharge potential (GRP). Conducting a GRP study plays an essential role in promoting the sustainable use of resources amid growing population unplanned urbanization. This focuses on assessing semi‐arid eastern plains Rajasthan by delineating zones (GPZs) using integrated approach involving remote sensing geographical information system (RS‐GIS) technique analytical hierarchy process (AHP) method. Research findings indicate that region dominated fine sand, silt clay, pediment‐pediplain complex, aeolian sand sheet, higher drainage density, cambisols soil, river channels, floodplains, water bodies, soil hydraulic conductivity surface wetness significantly contributed to good region. Additionally, lineaments, hills valleys regulate movement. A strong negative correlation (–0.78) decadal‐mean‐depth fluctuation GPZs frequency classes validates identifying high areas with low mean‐depth fluctuation. Sensitivity analysis highlights geology geomorphology as crucial factors. However, addresses limitations challenges, such data scaling spatial resolution issues due nonlinear pixel fusion algorithms AHP method‐related model interpretation. The current presents convenient for improving resource management hydrogeologically sensitive drought‐prone regions.

Language: Английский

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A Geoinformatics-Based Comparative Study of Multi-Criteria Decision Making Approaches of Groundwater Potential Zoning in Ken Basin, India

Journal of the Indian Society of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 11, 2024

Language: Английский

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