scholarly journals Integrated remote sensing and GIS techniques to delineate groundwater potential area of Chamchamal basin, Sulaymaniyah, NE Iraq

2021 ◽  
Vol 48 (3) ◽  
Author(s):  
Diary A.Mohammed Al-Manmi ◽  
◽  
Sarkhel H. Mohammed ◽  
Péter Szűcs ◽  
◽  
...  
Keyword(s):  
Drainage Density ◽  
Groundwater Potential ◽  
Thematic Map ◽  
Hydrogeological Characteristics ◽  
Verification Process ◽  
Hierarchy Process ◽  
Favorable Area ◽  
Potential Area ◽  
Relative Standing ◽  
Southwest Part

Groundwater management in the semi-arid areas is a crucial issue and requires more scientific study and techniques. Groundwater potential areas for part of the Chamchamal basin are determined using two techniques, the analytical hierarchy process (AHP) and a geographic information system (GIS). Several Input factors were used to produce a thematic map, including geology, structure, drainage density, land-use/landcover, slope steepness, lineament density, and hydrogeology. Based on the relative importance, the layers are ranked which control the groundwater potential areas. The factor classified into several zones builds upon the hydrogeological characteristics and the classes weighted based on the relative standing to the potential area of groundwater. The output of the analysis showed that there are four zones of groundwater potential, good, moderate, poor, and very poor. The zones cover 10.4, 38.7, 43.93, and 6.96% of the area, respectively. Furthermore, the results showed that the southwest part of the area is the most favorable area for groundwater existence. While the center and some parts of the northeast characterized by low groundwater potential zones. To verify the final potential zones, the yield rates of 38 wells are used. The verification process verified that the categories of groundwater potential areas are closed to the results obtained from (AHP) and (GIS).

Identification of Groundwater Potential Zones using AHP and Geospatial Techniques in Western Part of Cuddapah Basin, Andhra Pradesh, India

2020 ◽  
Vol 3 (2) ◽  
pp. 60-71
Author(s):  
Ramachandra M. ◽  
Raghu Babu K. ◽  
Rajasekhar M. ◽  
Pradeep Kumar B.
Keyword(s):  
Andhra Pradesh ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Water Levels ◽  
Geographical Information ◽  
Cuddapah Basin ◽  
Groundwater Potential Zones ◽  
Lineament Density ◽  
Geospatial Techniques ◽  
Hierarchy Process

Present study is carried out for delineation of Groundwater Potential Zones (GWPZ) in Western part of Cuddapah basin, Southern India using Remote Sensing (RS), Geographical Information System (GIS) and Analytical Hierarchy Process (AHP). Various categorized thematic maps: geology, geomorphology (GM), slope, soils, lineament density (LD), drainage density (DD) and gorundwater levels fluctuations (GWLF) were used for mapping and delineation of GWPZs. Suitable and normalized weights were assigned based on AHP to identify GWPZ. The GWPZ map was categorized into five GWPZs types: very poor, poor, moderate, good and very good. About 1.48% (6.05 km2) area is classified in ‘very good’, 25.95% (106.07 km2) in ‘good’, 47.11% (192.53 km2) in ‘moderate’, 22.12% (90.38 km2) in ‘poor’ and 3.34% (13.66 km2) in ‘very poor’ category. The acquired outcomes were validated with water levels fluctuations in pre- and post-monsoon seasons. GIS-based multi-criteria decision making approach is useful for preparation of precise and reliable data. The AHP approach, with the aptitudes of the geospatial data, various data bases can be combined to create conceptual model for identification and estimation of GWPZs.

Groundwater Potentiality Mapping in Viruthachalam Taluk, Tamil Nadu, India: AHP and GIS Approaches

2021 ◽  
Vol 5 (1) ◽  
pp. 24-33
Author(s):  
Muthukumarasamy Ranganathan ◽  
Bagyaraj M. ◽  
Mukesh M. ◽  
Zubairul Islam ◽  
Daniel Tekley Gebremedhin ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Daily Basis ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Gis And Remote Sensing ◽  
Distance Weighting ◽  
Potential Groundwater ◽  
Micro Level ◽  
Hierarchy Process ◽  
Inverse Distance

Groundwater is the most valuable treasury commodity in the world, yet it is depleted on a daily basis. Hand arrangement is crucial in assembly for delineating a potential groundwater zones. Geographic Information System (GIS) and Remote Sensing (RS) data with Analytical Hierarchy Process (AHP) approach have proven critical for micro level analysis of groundwater potentials. This exploration was authorized in order to locate a prospective groundwater area in the Virutachalam Taluk of Southern India. The Inverse Distance Weightage (IDW) technique was used to determine the groundwater potential precinct by thematic layers of drainage, drainage density, geology, lineament, lineament density, geomorphology, soil, and slopes. Overall, the prospective groundwater zone in the study area was classified as excellent (20.66 %), good (60.29 %), moderate (16.38 %) and poor (2.73 %). This optional analysis offers an excellent possible groundwater zone for patches in the northern and central sections of Kotteri and Kammapuram in Virudhachalam Taluk. The survey revealed that the approach of inverse distance weighting provides an operating mechanism for suggesting groundwater potential zones for clear expansion and groundwater control in not the same hydro-geological settings.

scholarly journals Integration of Delphi Technique and Analytical Hierarchy Process Method in Assessment the Groundwater Potential Influence Criteria: A Case Study of the Ba River Basin

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Tuyet Minh DANG ◽  
Le Tung Duong NGUYEN
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Weight Vector ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Sensitivity Analyses ◽  
Lineament Density ◽  
Analytic Hierarchy ◽  
Study Results ◽  
Hierarchy Process

Water is a boon for all living beings over the world and groundwater is considered one of theindispensable natural sources of potable water. It is necessary to assess and predict the groundwaterpotential to provide insights for decision-makers for proper planning and management of groundwater.The occurrence of groundwater depends on hydrological, ecological, climate, geological, andphysiographical criteria. The purpose of the present study is to choose and attribute scores to all variousfactors that affected groundwater prospects in the Ba river basin. Firstly, the Delphi method was appliedin the expert-based survey to choose six parameters that are considered as influencing factors, namely,lineament density, rainfall, slope, land cover, drainage density, and geology. Then, the weights for thevarious factors were generated using the Analytic Hierarchy Process (AHP) approach which allows thepairwise comparison of criteria influencing the potential areas. The consistency analyses show that thefindings were consistent with a previous study. The consistency and sensitivity analyses showed that theobtained results were coherent, providing the weight vector of the achievable criteria that affect thegroundwater prospect in the study area. The study reveals that lineament density and slope are criteriaaffecting the most prominent groundwater occurrence with 35.1% and 20.1%, respectively. However, theinfluence of other factors (rainfall, land cover, drainage density, and geology) is not visible. These criteriaare assigned to the small weights and do not have a significant influence on the groundwater potential.The study results provide baseline

Integrated Geomorphological, Geospatial and AHP Technique for Groundwater Prospects Mapping in Basaltic Terrain

2018 ◽  
Vol 2 (1) ◽  
pp. 16-27 ◽  
Author(s):  
Vaishnavi Mundalik ◽  
Clinton Fernandes ◽  
Ajaykumar Kadam ◽  
Bhavana Umrikar
Keyword(s):  
Groundwater Resources ◽  
Drainage Density ◽  
Groundwater Potential ◽  
The Sustainable Development ◽  
Thematic Layers ◽  
Groundwater Availability ◽  
Basaltic Terrain ◽  
Thematic Layer ◽  
Increasing Demand ◽  
Gis Environment

Groundwater is an important source of drinking water in rural parts of India. Because of the increasing demand for water, it is essential to identify new sources for the sustainable development of this resource. The potential mapping and exploration of groundwater resources have become a breakthrough in the field of hydrogeological research. In the present paper, a groundwater prospects map is delineated for the assessment of groundwater availability in Kar basin on basaltic terrain, using remote sensing and Geographic Information System (GIS) techniques. Various thematic layers such as geology, slope, soil, geomorphology, drainage density and rainfall are prepared using satellite data, topographic maps and field data. The ranks and weights were assigned to each thematic layer and various categories of those thematic layers using AHP technique respectively. Further, a weighted overlay analysis was performed by reclassifying them in the GIS environment to prepare the groundwater potential map of the study area. The results show that groundwater prospects map classified into three classes low, moderate and high having area 17.12%, 38.26%, 44.62%, respectively. The overlay map with the groundwater potential zones in the study area has been found to be helpful for better planning and managing the resources.

scholarly journals Identification of Groundwater Potential Zones Using GIS and Multi-Criteria Decision-Making Techniques: A Case Study Upper Coruh River Basin (NE Turkey)

2021 ◽  
Vol 10 (6) ◽  
pp. 396
Author(s):  
Ümit Yıldırım
Keyword(s):  
Drainage Density ◽  
Groundwater Potential ◽  
High Potential ◽  
Groundwater Potential Zones ◽  
Topographic Wetness Index ◽  
Analytic Hierarchy ◽  
Soil Thickness ◽  
Çoruh River Basin ◽  
Basin Area ◽  
Very High

In this study, geographic information system (GIS)-based, analytic hierarchy process (AHP) techniques were used to identify groundwater potential zones to provide insight to decisionmakers and local authorities for present and future planning. Ten different geo-environmental factors, such as slope, topographic wetness index, geomorphology, drainage density, lithology, lineament density, rainfall, soil type, soil thickness, and land-use classes were selected as the decision criteria, and related GIS tools were used for creating, analysing and standardising the layers. The final groundwater potential zones map was delineated, using the weighted linear combination (WLC) aggregation method. The map was spatially classified into very high potential, high potential, moderate potential, low potential, and very low potential. The results showed that 21.5% of the basin area is characterised by high to very high groundwater potential. In comparison, the very low to low groundwater potential occupies 57.15%, and the moderate groundwater potential covers 21.4% of the basin area. Finally, the GWPZs map was investigated to validate the model, using discharges and depth to groundwater data related to 22 wells scattered over the basin. The validation results showed that GWPZs classes strongly overlap with the well discharges and groundwater depth located in the given area.

Assessment and Modeling of Groundwater Potential Zones by using Geospatial and Decision-making approaches: A case study in Anantapur district, Andhra Pradesh, India

2021 ◽  
Vol 5 (1) ◽  
pp. 34-44
Author(s):  
B. Pradeep Kumar ◽  
K. Raghu Babu ◽  
M. Rajasekhar ◽  
M. Ramachandra
Keyword(s):  
Andhra Pradesh ◽  
Primary Source ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Groundwater Exploration ◽  
Groundwater Potential Zone ◽  
Potential Zone ◽  
Groundwater Potential Zones ◽  
Thematic Layers ◽  
Total Study Area

Freshwater scarcity is a major issue in Rayalaseema region in Andhra Pradesh (India). Groundwater is the primary source of drinking and irrigation water in Anantapur district, Andhra Pradesh, India. Therefore, it is important to identify areas having groundwater potential; however, the current methods of groundwater exploration consume a lot of time and money. Analytic Hierarchy Process (AHP)-based spatial model is used to identify groundwater potential zones in Anantapur using remote sensing and GIS-based decision support system. Thematic layers considered in this study were geology, geomorphology, soils, land use land cover (LULC), lineament density (LD), drainage density (DD), slope, and rainfall. According to Saaty’s AHP, all these themes and individual features were weighted according to their relative importance in groundwater occurrence. Thematic layers were finally combined using ArcGIS to prepare a groundwater potential zone map. The high weighted value area was considered a groundwater prospecting region. Accordingly, the GWPZ map was classified into four categories: very good, good, moderate, and poor. The very good GWPZ area is 77.37 km2 (24.93%) of the total study area. The northeastern and southeastern sections of the study area, as well as some medium patches in the center and western regions, are covered by moderate GWPZs, which cover an area of 53.07 km2 (17.10%). However, the GWP in the study area’s central, southwestern, and northern portions is poor, encompassing an area of approximately 79.31 km2 (25.56%). Finally, RS and GIS techniques are highly effective and useful for identifying GWPZs.

scholarly journals Modeling of Groundwater Potential Using Cloud Computing Platform: A Case Study from Nineveh Plain, Northern Iraq

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3330
Author(s):  
Ali ZA. Al-Ozeer ◽  
Alaa M. Al-Abadi ◽  
Tariq Abed Hussain ◽  
Alan E. Fryar ◽  
Biswajeet Pradhan ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Specific Yield ◽  
Support Vector ◽  
Northern Iraq ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Very High

Knowledge of the groundwater potential, especially in an arid region, can play a major role in planning the sustainable management of groundwater resources. In this study, nine machine learning (ML) algorithms—namely, Artificial Neural Network (ANN), Decision Jungle (DJ), Averaged Perceptron (AP), Bayes Point Machine (BPM), Decision Forest (DF), Locally-Deep Support Vector Machine (LD-SVM), Boosted Decision Tree (BDT), Logistic Regression (LG), and Support Vector Machine (SVM)—were run on the Microsoft Azure cloud computing platform to model the groundwater potential. We investigated the relationship between 512 operating boreholes with a specified specific capacity and 14 groundwater-influencing occurrence factors. The unconfined aquifer in the Nineveh plain, Mosul Governorate, northern Iraq, was used as a case study. The groundwater-influencing factors used included elevation, slope, curvature, topographic wetness index, stream power index, soil, land use/land cover (LULC), geology, drainage density, aquifer saturated thickness, aquifer hydraulic conductivity, aquifer specific yield, depth to groundwater, distance to faults, and fault density. Analysis of the contribution of these factors in groundwater potential using information gain ratio indicated that aquifer saturated thickness, rainfall, hydraulic conductivity, depth to groundwater, specific yield, and elevation were the most important factors (average merit > 0.1), followed by geology, fault density, drainage density, soil, LULC, and distance to faults (average merit < 0.1). The average merits for the remaining factors were zero, and thus, these factors were removed from the analysis. When the selected ML classifiers were used to estimate groundwater potential in the Azure cloud computing environment, the DJ and BDT models performed the best in terms of all statistical error measures used (accuracy, precision, recall, F-score, and area under the receiver operating characteristics curve), followed by DF and LD-SVM. The probability of groundwater potential from these algorithms was mapped and visualized into five groundwater potential zones: very low, low, moderate, high, and very high, which correspond to the northern (very low to low), southern (moderate), and middle (high to very high) portions of the study area. Using a cloud computing service provides an improved platform for quickly and cheaply running and testing different algorithms for predicting groundwater potential.

scholarly journals Spatial Prediction of Groundwater Potentiality Mapping Using Machine Learning Algorithms

2021 ◽  
Author(s):  
Sunil Saha ◽  
Amiya Gayen ◽  
Kaustuv Mukherjee ◽  
Hamid Reza Pourghasemi ◽  
M. Santosh
Keyword(s):  
Machine Learning ◽  
Influencing Factors ◽  
Groundwater Resources ◽  
Learning Algorithms ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Machine Learning Algorithms ◽  
Lineament Density ◽  
Dug Wells ◽  
Groundwater Potentiality

Abstract Machine learning techniques offer powerful tools for the assessment and management of groundwater resources. Here, we evaluated the groundwater potential maps (GWPMs) in Md. Bazar Block of Birbhum District, India using four GIS-based machine-learning algorithms (MLA) such as predictive neural network (PNN), decision tree (DT), Naïve Bayes classifier (NBC), and random forest (RF). We used a database of 85 dug wells and one piezometer location identified using extensive field study, and employed 12 influencing factors (elevation, slope, drainage density (DD), topographical wetness index, geomorphology, lineament density, rainfall, geology, pond density, land use/land cover (LULC), geology, and soil texture) for evaluation through GIS. The 85 dug wells and 1 piezometer locations were sub-divided into two classes: 70:30 for training and model validation. The DT, RF, PNN, and NBC MLAs were implemented to analyse the relationship between the dug well locations and groundwater influencing factors to generate GWPMs. The results predict excellent groundwater potential areas (GPA) DT RF of 17.38%, 14.69%, 20.43%, and 13.97% of the study area, respectively. The prediction accuracy of each GWPM was determined using a receiver operating characteristic (ROC) curve. Using the 30% data sets (validation data), accuracies of 80.1%, 78.30%, 75.20%, and 69.2% were obtained for the PNN, RF, DT, and NBC models, respectively. The ROC values show that the four implemented models provide satisfactory and suitable results for GWP mapping in this region. In addition, the well-known mean decrease Gini (MDG) from the RF MLA was implemented to determine the relative importance of the variables for groundwater potentiality assessment. The MDG revealed that drainage density, lineament density, geomorphology, pond density, elevation, and stream junction frequency were the most useful determinants of GWPM. Our approach to delineate the GWPM can aid in the effective planning and management of groundwater resources in this region.

Sign in / Sign up

Export Citation Format

Share Document