Groundwater Potential Assessment Using Integrated Geospatial and Analytic Hierarchy Process Techniques (AHP) in Chemoga Watershed, Upper Blue Nile Basin, Ethiopia

Air Soil and Water Research, Journal Year: 2025, Volume and Issue: 18

Published: Jan. 1, 2025

Groundwater is an invaluable natural resource that sustains human life and supports the economic development of nations. However, its unsustainable utilization has emerged as a critical issue, particularly in developing countries. This study investigates groundwater potential Chemoga watershed to address these challenges. Conventional assessments have typically relied on labor-intensive time-consuming field surveys, which are resource-demanding often fail provide accurate estimates due inherent complexity systems. In response, this research utilizes geospatial analytic hierarchy process (AHP) techniques assess Watershed, aiming overcome Eight biophysical environmental factors: geology, slope, rainfall, land use/land cover (LULC), soil type, elevation, lineament density, drainage density were selected for analysis using Saaty’s AHP methodology. Data was gathered from satellite imagery, existing thematic maps, local water offices, national meteorological agencies. The integration maps performed through weighted overlay ArcGIS 10.8, resulted delineation zones (GWPZ). model validated by cross-referencing generated GWPZ with data dug wells boreholes. results reveal five zones: very high (0.73%), (24.39%), moderate (43.38%), poor (31.25%), (0.25%). most suitable south, southeast, southwest watershed, near Debre Markos Town. These high-potential significant 81.5% match ground truth shallow wells. findings crucial insights decision-makers, enabling formulation more effective management strategies. By identifying cost-effective well sites, contributes ensuring sustainable supply

Language: Английский

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Geospatial and Multi-Criteria Analysis for Identifying Groundwater Potential Zones in the Oltu Basin, Turkey

Water, Journal Year: 2025, Volume and Issue: 17(2), P. 240 - 240

Published: Jan. 16, 2025

This study was conducted to determine potential groundwater storage areas in the semi-arid Oltu Basin northeastern Turkey. The of basin analyzed by evaluating eight geographical factors: lithology, linear density, soil depth, land use, precipitation, geomorphology, slope, and drainage density. These factors were classified weighted using remote sensing, information systems (GIS), analytic hierarchy process (AHP). obtained data modeled ArcGIS software, a map created. results show that there is high close stream bed, while low mountainous steeply sloped regions. provides significant findings for sustainable water resource management region future resources planning.

Language: Английский

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Groundwater potential mapping in arid and semi-arid regions of Kurdistan region of Iraq: A geoinformatics-based machine learning approach

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: unknown, P. 101337 - 101337

Published: Sept. 1, 2024

Language: Английский

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Unleashing the Untapped Potential: Groundwater Exploration in a Watershed Environment of North‐East India Using MCDA‐AHP Techniques

Hydrological Processes, Journal Year: 2025, Volume and Issue: 39(1)

Published: Jan. 1, 2025

ABSTRACT The contemporary era is marked by the faster exploitation of groundwater resources due to combined effects burgeoning population and rapid industrialisation. This study tries delineate potential zones (GWPZs) in a fragile agriculturally dominant watershed North‐East India using GIS‐based multi‐criteria decision analysis (MCDA) approach Analytical Hierarchy Process (AHP) technique. has undertaken 10 influencing factors: geomorphology, geology, land use/land cover (LU/LC), drainage density, rainfall, soil texture, slope, lineament topographic wetness index (TWI) normalised difference water (NDWI). Suitable weights for parameters are assigned according their relative importance association with storage based on pairwise comparison matrix (PCM). Four GWPZs respective coverages namely poor (3.39%), moderate (24.98%), good (33.36%) excellent (38.27%) categories found. central southern parts area covering portion Udalguri, Sonitpur Darrang districts Assam have porous geological settings floodplains, indicating high potentiality. In contrast, northern part hard rugged terrain lacks storage. Incorporating socio‐economic aspect, particularly number villages or without access suitable groundwater, significantly enhances study's utility. outcome cross‐verified well data obtained from Central Groundwater Board (CGWB) field which validated receiver operating characteristics (ROC) curve resulting an accuracy 72.9%. Hence, this inquiry implications both regional global significance will assist stakeholders authorities creating roadmap sustainable effective use.

Language: Английский

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Groundwater potential mapping using WetSpass-M and GIS-based multi-criteria decision analysis (MCDA) models in the Chamo Lake basin, Ethiopian rift

Sustainable Water Resources Management, Journal Year: 2025, Volume and Issue: 11(2)

Published: March 17, 2025

Language: Английский

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Assessing Groundwater Potential in the Ziway Lake Watershed Using Geographical Information System, Analytic Hierarchy Process, and Drinking Water Quality Index

Global Challenges, Journal Year: 2025, Volume and Issue: unknown

Published: April 27, 2025

Abstract This study investigates the groundwater potential zones in Ziway Lake watershed of Ethiopia's rift valley using a GIS‐based multi‐criteria decision analysis within Analytical Hierarchy Process (AHP). Environmental factors, including recharge, lithology, elevation, lineament density, and drainage are analyzed. The soil water assessment tool (SWAT) model is applied to estimate recharge for watershed. performance SWAT model, evaluated based on observed streamflow at Katar Meki stations, demonstrates good during calibration validation phases. watershed's classified as Very low (18.01%), Low (17.62%), Moderate (12.05%), High (28.34%), (23.98%). Groundwater integrated with drinking quality index GIS, showing that (39.72%) very high areas have excellent quality. Results show over half has moderate potential, identifying critical sustainable management. findings provide useful guidance key exploration conservation, offering practical approach can be other regions ensure

Language: Английский

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Positive–Unlabeled Learning-Based Hybrid Models and Interpretability for Groundwater Potential Mapping in Karst Areas

Water, Journal Year: 2025, Volume and Issue: 17(10), P. 1422 - 1422

Published: May 9, 2025

Despite the increasing adoption of machine learning and data-driven models for predicting regional groundwater potential (GWP), exploration geoscientists have recognized that these still face various challenges in their predictive precision. For instance, stochastic uncertainty associated with incomplete investigation inventories inherent non-transparency characteristic models, which lack transparency regarding how input features influence outcomes, pose significant challenges. This research constructs a bagging-based framework integrates Positive–Unlabeled samples (BPUL), along ex-post interpretability, to map GWP Lijiang River Basin China, renowned karst region. this purpose, we first aggregated topographic, hydrological, geological, meteorological, land conditional factors. The training were enhanced data from subterranean stream investigated study area, addition conventional such as wells, boreholes, springs. We employed BPUL algorithm four different base learners—Logistic Regression (LR), k-nearest neighbor (KNN), Random Forest (RF), Light Gradient Boosting Machine (LightGBM)—and model validation was conducted regions. findings indicate all exhibit satisfactory performance mapping, hybrid ensemble (RF-BPUL LightGBM-BPUL) achieving higher scores. interpretation SHAP values revealed contribution patterns factors distribution zones, emphasizing lithology, multiresolution index valley bottom flatness (MRVBF), geochemical element calcium oxide (CaO) most impact on enrichment zones. These offer new approaches methodologies in-depth scientific prediction potential.

Language: Английский

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Integrated GIS-Based Approach for Groundwater Potential Mapping in Arid Regions: A Case Study of Kenadsa-Bechar Using AHP and Frequency Ratio Methods

Groundwater for Sustainable Development, Journal Year: 2025, Volume and Issue: unknown, P. 101461 - 101461

Published: May 1, 2025

Language: Английский

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Spatial evaluation of flood susceptibility on a national scale across Ghana using a fuzzy analytic hierarchy process and evidential belief function: an ensemble approach

Acta Geophysica, Journal Year: 2025, Volume and Issue: unknown

Published: May 16, 2025

Language: Английский

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Assessing Recharge Zones for Groundwater Potential in Dera Ismail Khan (Pakistan): A GIS-Based Analytical Hierarchy Process Approach

Water, Journal Year: 2025, Volume and Issue: 17(11), P. 1586 - 1586

Published: May 23, 2025

Groundwater constitutes the primary source of liquid freshwater on Earth and is essential for ecosystems, agriculture, human consumption. However, rising demand, urbanization, climate change have intensified groundwater depletion, particularly in semi-arid regions. Therefore, assessing recharge zones sustainable water resource management vulnerable areas such as Dera Ismail Khan, Pakistan. This study aims to delineate potential (GWPZs), using an integrated approach combining Geographic Information System (GIS), remote sensing (RS), analytical hierarchy process (AHP). Twelve factors were identified a conducted GIS-based AHP determine region. These include land use/land cover (LULC), rainfall, drainage density, soil type, slope, road table depth, indices Normalized Difference Vegetation Index (NDVI), Built-up (NDBI), Moisture Stress (MSI), Worldview Water (WVWI), Land Surface Temperature (LST). The results show that 17.52% 2.03% area “good” “very good” recharge, respectively, while 48.63% has “moderate” potential. Furthermore, gentle slopes (0–2.471°), high shallow depths (20–94 m), densely vegetated (with NDVI) are considered important influencing recharge. Conversely, with steep slopes, temperatures, dense built-up showed “poor” demonstrates effectiveness integrating advanced model context, validated through high-accuracy field data (Kappa = 0.93). methodology offers cost-effective decision support tool planning similar environments.

Language: Английский

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