Evaluation of parameter sensitivity for groundwater potential mapping in the mountainous region of Nepal Himalaya

Pathak, Dinesh; Maharjan, Rupendra; Maharjan, N. B.; Shrestha, Surendra; Timilsina, Purushottam

doi:10.1016/j.gsd.2021.100562

Cited by 24 publications

(7 citation statements)

References 48 publications

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“…This curve is a widely used metric for predicting model accuracy in classification issues [100]. In several studies, this method has been used to assess the accuracy of the groundwater potential mapping using a GIS-based AHP method [6,98,[101][102][103][104][105].…”

Section: Validation Of Resultsmentioning

confidence: 99%

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

Uc-Castillo

Cruz

Ramos-Leal

et al. 2022

Water

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Groundwater occurrence in semi-arid regions is variable in space and time due to climate patterns, terrain features, and aquifer properties. Thus, accurate delineation of Groundwater Potential Zones (GWPZs) is essential for sustainable water resources management in these environments. The present research aims to delineate and assess GWPZs in a semi-arid basin of San Luis Potosi (SLP), Mexico, through the integration of Remote Sensing (RS), Geographic Information System (GIS), and Analytic Hierarchy Process (AHP). Seven thematic layers (geology, lineament density, land use and land cover, topographic wetness index (TWI), rainfall, drainage density, and slope) were generated in raster format. After the AHP procedure and rank assignment, the thematic layers were integrated using the raster calculator to obtain the GWPZs map. The results indicated that 68.21% of the area is classified as low groundwater potential, whereas 26.30% is classified as moderate. Validation was done by assessing the water residence time data from 15 wells distributed in the study area. Furthermore, the Receiver Operating Characteristics (ROC) curve was obtained, indicating a satisfactory accuracy prediction (AUC = 0.677). This study provides valuable information for decision-makers regarding the conservation and sustainable management of groundwater resources.

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Section: Validation Of Resultsmentioning

confidence: 99%

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

Uc-Castillo

Cruz

Ramos-Leal

et al. 2022

Water

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“…Then, the consistency ratio was computed as per equation 8 and the computed result was CR = 0.03 which was less than 0.1and the given weights were accepted for further analysis. Groundwater Recharge zone map (GWRZM) was computed after checking all criteria as follows: GWRZM= 44.16Rf + 25.97slo + 14.63LU + 8.11Dd + 4.160Ld +2.52Geo…………… (6) Rainfall, Slope, Land use land cover and drainage density hold the highest value relative to the other parameters. The weights assigned for Rainfall were greater than the weight of others, which influence the process of groundwater recharge than other parameters.…”

Section: Normalized Principal Eigen Vectorsmentioning

confidence: 99%

“…Due to its extensive fieldwork, this technique is has a great application. Both the GIS and RS are now considered essential tools for assessing potential groundwater for further studies, particularly in extended and complicated systems [6] [7].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Groundwater Potential Zone Using Remote Sensing and Geographical Information System: in Kaffa Zone, South Western Ethiopia

Woldegebriel¹,

Amibo

Bayu

2021

SJE

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This study focused on delineating the groundwater potential and recharge area for Kaffa Zone by the method of remote sensing and ArcGIS 10.4 software analysis techniques. There are six main influencing factors (rainfall, slope, land use/cover, lineaments, drainage density, and Lithology) selected for groundwater recharge zone mapping. The thematic maps were scanned, geo-referenced, and classified as suitable for groundwater using ArcGIS 10.4. The methods to assess the potential zone were using weight overlay analysis and hierarchy of analytical process algorithm. The result obtained the potential of ground water were discussed recharge zones into four major categories: very good, good, and moderate and low. This can help for better planning and management the potential resource of groundwater. The results analyzed the groundwater potential that were subdivided in to low, moderate, high, and very high groundwater potentials areas that cover 1664.1,7682.9, 958.27, and 192.78 km2 respectively. The prediction accuracy was checked based on the borehole yield observed and predicted data of respective locations within the selected area. The prediction accuracy obtained (68.42%) reflects that the present study's method was produced significantly reliable and precise results.

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“…We chose those variables, which many researchers have extensively used. In the plain regions, topographic and climatic parameters have been recognized as important variables, while in the mountains, along with topographic, geological variables have been described as critical variables for GWP mapping (Mallick et al 2021c;Al-Djazouli et al 2021;Pathak et al 2021;Namous et al 2021;Al-Abadi et al 2021). For example, drainage density could be a valid variable in flood plains, not in mountainous regions (Bhattacharya et al 2021;Fadhillah et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Novel hybrid models to enhance the efficiency of groundwater potentiality model

et al. 2022

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The present study aimed to create novel hybrid models to produce groundwater potentiality models (GWP) in the Teesta River basin of Bangladesh. Six ensemble machine learning (EML) algorithms, such as random forest (RF), random subspace, dagging, bagging, naïve Bayes tree (NBT), and stacking, coupled with fuzzy logic (FL) models and a ROC-based weighting approach have been used for creating hybrid models integrated GWP. The GWP was then verified using both parametric and nonparametric receiver operating characteristic curves (ROC), such as the empirical ROC (eROC) and the binormal ROC curve (bROC). We conducted an RF-based sensitivity analysis to compute the relevancy of the conditioning variables for GWP modeling. The very high and high groundwater potential regions were predicted as 831–1200 km2 and 521–680 km2 areas based on six EML models. Based on the area under the curve of the ROC, the NBT (eROC: 0.892; bROC: 0.928) model outperforms rest of the models. Six GPMs were considered variables for the next step and turned into crisp fuzzy layers using the fuzzy membership function, and the ROC-based weighting approach. Subsequently four fuzzy logic operators were used to assimilate the crisp fuzzy layers, including AND, OR, GAMMA0.8, and GAMMA 0.9, as well as GAMMA0.9. Thus, we created four hybrid models using FL model. The results of the eROC and bROC curve showed that GAMMA 0.9 operator outperformed other fuzzy operators-based GPMs in terms of accuracy. According to the validation outcomes, four hybrid models outperformed six EML models in terms of performance. The present study will aid in enhancing the efficiency of GPMs in preparing viable planning for groundwater management.

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Evaluation of parameter sensitivity for groundwater potential mapping in the mountainous region of Nepal Himalaya

Cited by 24 publications

References 48 publications

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

Evaluation of Groundwater Potential Zone Using Remote Sensing and Geographical Information System: in Kaffa Zone, South Western Ethiopia

Novel hybrid models to enhance the efficiency of groundwater potentiality model

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