scholarly journals Evaluation of the groundwater recharge potential using GIS multi-criteria data analysis: a case study from district of Itabira, Minas Gerais, southeastern Brazil

2020 ◽  
Vol 42 ◽  
pp. e84
Author(s):  
José Augusto Costa Gonçalves ◽  
Pedro Henrique Rodrigues Pereira ◽  
Eliane Maria Vieira
Keyword(s):  
Multicriteria Analysis ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Minas Gerais ◽  
Water Infiltration ◽  
Southeastern Brazil ◽  
Aquifer Recharge ◽  
Thematic Maps ◽  
Groundwater Exploitation ◽  
Very High

Knowledge about the groundwater potential is an important tool to sustainably manage groundwater exploitation. In this context, based on the Geographic Information Systems (GIS) and multicriteria analysis by the Analytic Hierarchy Process (AHP), this study had the objective of mapping the groundwater potential of the district of Itabira, Minas Gerais, which is one of the largest mining regions in Brazil. The evaluation of the regional groundwater potential was based on thematic maps of land use and cover, soil, geology, slope, lineament density, and drainage density. From the evaluation of these parameters and their classes, weights were assigned by the AHP method, according to the influence of each one with regard to favoring water infiltration and aquifer recharge. The thematic maps were integrated in a GIS environment, generating a groundwater map of the district divided into five classes of groundwater potential (very low, low, moderate, high, and very high). In about 64% of the territory the potential for groundwater occurrence was very low to low and from moderate to very high in about 36%. The groundwater potential map showed that 64.42% of the district of Itabira has very low to low potential indices, mainly due to a number of regional characteristics that make aquifer infiltration and recharge difficult and occur in large areas of the territory.

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.

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.

Mapping of Groundwater potential zones in Lingasugur Taluk in North-eastern part of Karnataka, India using Remote Sensing, GIS and multi-criteria data analysis

2021 ◽  
Vol 14 (12) ◽  
pp. 13-22
Author(s):  
Ajgaonkar Swanand ◽  
S. Manjunatha
Keyword(s):  
Remote Sensing ◽  
Groundwater Resources ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Groundwater Exploration ◽  
Geographical Information ◽  
Groundwater Potential Zones ◽  
Thematic Maps ◽  
North Eastern

Groundwater research has evolved tremendously as presently it is the need of society. Remote Sensing (RS) and Geographical Information System (GIS) are the main methods in finding the potential zones for the groundwater. They help in assessing, exploring, monitoring and conserving groundwater resources. A case study was conducted to find the groundwater potential zones in Lingasugur taluk, Raichur District, Karnataka State, India. Ten thematic maps were prepared for the study area such as geology, hydrogeomorphology, land use/ land cover, soil type, NDVI, NDWI, slope map, lineament density, rainfall and drainage density. A weighted overlay superimposed method was used after converting all the thematic maps in raster format. Thus from analysis, the classes in groundwater potential were made as very good, moderate, poor and very poor zones covering an area of 10.1 sq.km., 169.25 sq.km., 1732.31 sq.km. and 53.66 sq.km. respectively. By taking the present study into consideration, the future plans for urbanization, recharge structures and groundwater exploration sites can be decided.

scholarly journals Groundwater Prospect Zonation Using Frequency Ratio Model For Banganga River Basin, India

2019 ◽  
Vol 8 (6) ◽  
pp. 806-814
Keyword(s):  
River Basin ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Groundwater Prospect ◽  
Land Use Land Cover ◽  
Well Location ◽  
High Zone ◽  
Gis Methods ◽  
The Right ◽  
Very High

Groundwater prospective Zonation mapping and its reasonable improvement are a significant perspective in Banganga River Basin. In the present investigation, the groundwater imminent zones were depicted by receiving a recurrence proportion (FR) model Land use land cover, Geomorphology, Geology, Drainage Density, Lineament Density Aquifer, Slope, well location and water level were the Thematic layers considered for groundwater prospective Zonation mapping. There are 157 spring wells situated in the investigation Study area, of which all wells were considered for evolution rate and staying absolute wells considered for predict rate in the FR model. The last groundwater prospective map was characterized into five zones as Very Low, Low, Medium, High and Very high. Finally, appropriate destinations for Groundwater revitalize for practical groundwater the board were distinguished. The locales were chosen based on profundity of groundwater level, wellspring of spring great areas and inclination from regular spring to select invigorate wells.Groundwater Prospective zone ranging from 2.8068 to 12.3712. It classified into five prospective classes Very low classes cover 904.62 sq km, low zone covers 1220.76 sq km, medium zone covers 1821.46 sq km, High zone covers 2145.55sq km and very High zone covers 2687.57 sqkm.Areas with steeply inclined limestone terrains and younger tough rocks had moderate to weak groundwater potential. The groundwater is mostly not appropriate in the research region for consumption but may be used for irrigation under unique circumstances, on the basis of the chemical analysis. The general findings show that using remote sensing and GIS methods provides strong method for developing groundwater and developing the right exploration scheme.

scholarly journals IDENTIFICATION OF LANDSLIDE SUSCEPTIBILITY ZONATION IN CNG GHAT SECTION, GUDALUR, THE NILGIRIS – USING GIS BASED ANN/MULTI CRITERIA METHOD

2018 ◽  
Vol XLII-5 ◽  
pp. 871-875 ◽  
Author(s):  
S. Prasanna Venkatesh ◽  
S. E. Saranaathan
Keyword(s):  
Landslide Susceptibility ◽  
Field Data ◽  
Satellite Image ◽  
Drainage Density ◽  
Slope Aspect ◽  
Thematic Maps ◽  
Soil Thickness ◽  
Landslide Susceptibility Zonation ◽  
The Nilgiris ◽  
Very High

<p><strong>Abstract.</strong> Among the various natural hazards, landslide is the most widespread and damaging hazard. In recent times, throughout a lot of attention is being drawn to evaluate the risk due to landslides. The invention of remote sensing and GIS have been new vistas in the field of geo scientific studies viz. geomorphological mapping, groundwater potential mapping, disaster management etc. The present study has been undertaken to study different thematic maps like, contour, drainage, slope, aspect, curvature, DEM, DTM, drainage density, drainage intensity, geology, lineament, lineament density, lineament intensity, geomorphology, land use, weathering thickness, run off, soil thickness and buffer maps like road, drainage, lineament etc. in CNG ghat section, Gudalur, The Nilgiris. For this purpose, the satellite image IRS – RS2, LISS III January 2014 used to prepare different thematic maps. The contour, drainage and road network were incorporate from SoI Toposheets. The slope, curvature, aspects and buffer maps were prepared from GIS environments. Based on field studies, above said thematic maps (22 nos.) were prepared and were grouped into 3 categories viz. Geology, Hydrology and Terrain. In each category the input maps were assigned different score as well as each layer has been given different weightage. Finally the categories are analysed through multi – criteria analysis to find out 5 different vulnerability classes. The 5 different land susceptibility zones are classified as very low, low, moderate, high and very high. The percentages of area under different susceptibility classes are 3%, 20%, 51%, 25%, and 1% respectively. The locations of small area major landslides and slip locations were calculated from different years using (2010 and 2014) Trimble GPS in the field. The field data was converted into point layer in GIS and landslide inventory map was prepared. This map was superimposed in landslide susceptibility zonation map. As per field data 0%, 9.25%, 57.5%, 32% and 1.25% Slide points are come under very low, low, moderate, high, very high susceptibility zones respectively.</p>

scholarly journals Soil erosion vulnerability in the verde river basin, southern minas gerais

2014 ◽  
Vol 38 (3) ◽  
pp. 262-269 ◽  
Author(s):  
Vinícius Augusto de Oliveira ◽  
Carlos Rogério de Mello ◽  
Matheus Fonseca Durães ◽  
Antônio Marciano da Silva
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Minas Gerais ◽  
Annual Rainfall ◽  
Southeastern Brazil ◽  
Rainfall Erosivity ◽  
Verde River ◽  
Gis Environment ◽  
Elevation Model ◽  
Very High

Soil erosion is one of the most significant environmental degradation processes. Mapping and assessment of soil erosion vulnerability is an important tool for planning and management of the natural resources. The objective of the present study was to apply the Revised Universal Soil Loss Equation (RUSLE) using GIS tools to the Verde River Basin (VRB), southern Minas Gerais, in order to assess soil erosion vulnerability. A annual rainfall erosivity map was derived from the geographical model adjusted for Southeastern Brazil, calculating an annual value for each pixel. The maps of soil erodibility (K), topographic factor (LS), and use and management of soils (C) were developed from soils and their uses map and the digital elevation model (DEM) developed for the basin. In a GIS environment, the layers of the factors were combined to create the soil erosion vulnerability map according to RUSLE. The results showed that, in general, the soils of the VRB present a very high vulnerability to water erosion, with 58.68% of soil losses classified as "High" and "Extremely High" classes. In the headwater region of VRB, the predominant classes were "Very High" and "Extremely High" where there is predominance of Cambisols associated with extensive pastures. Furthermore, the integration of RUSLE/GIS showed an efficient tool for spatial characterization of soil erosion vulnerability in this important basin of the Minas Gerais state.

scholarly journals Application of Probabilistic and Machine Learning Models for Groundwater Potentiality Mapping in Damghan Sedimentary Plain, Iran

2019 ◽  
Vol 11 (24) ◽  
pp. 3015 ◽  
Author(s):  
Alireza Arabameri ◽  
Jagabandhu Roy ◽  
Sunil Saha ◽  
Thomas Blaschke ◽  
Omid Ghorbanzadeh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Sensitivity Analysis ◽  
Prediction Accuracy ◽  
Goodness Of Fit ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Plain Area ◽  
Groundwater Occurrence ◽  
Groundwater Potentiality ◽  
Very High

Groundwater is one of the most important natural resources, as it regulates the earth’s hydrological system. The Damghan sedimentary plain area, located in the region of a semi-arid climate of Iran, has very critical conditions of groundwater due to massive pressure on it and is in need of robust models for identifying the groundwater potential zones (GWPZ). The main goal of the current research is to prepare a groundwater potentiality map (GWPM) considering the probabilistic, machine learning, data mining, and multi-criteria decision analysis (MCDA) approaches. For this purpose, 80 wells collected from the Iranian groundwater resource department and field investigation with global positioning system (GPS), have been selected randomly and considered as the groundwater inventory datasets. Out of 80 wells, 56 (70%) wells have been brought into play for modeling and 24 (30%) for validation purposes. Elevation, slope, aspect, convergence index (CI), rainfall, drainage density (Dd), distance to river, distance to fault, distance to road, lithology, soil type, land use/land cover (LU/LC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), topographic position index (TPI), and stream power index (SPI) have been used for modeling purpose. The area under the receiver operating characteristic (AUROC), sensitivity (SE), specificity (SP), accuracy (AC), mean absolute error (MAE), and root mean square error (RMSE) are used for checking the goodness-of-fit and prediction accuracy of approaches to compare their performance. In addition, the influence of groundwater determining factors (GWDFs) on groundwater occurrence was evaluated by performing a sensitivity analysis model. The GWPMs, produced by technique for order preference by similarity to ideal solution (TOPSIS), random forest (RF), binary logistic regression (BLR), weight of evidence (WoE) and support vector machine (SVM) have been classified into four categories, i.e., low, medium, high and very high groundwater potentiality with the help of the natural break classification methods in the GIS environment. The very high groundwater potentiality class is covered 15.09% for TOPSIS, 15.46% for WoE, 25.26% for RF, 15.47% for BLR, and 18.74% for SVM of the entire plain area. Based on sensitivity analysis, distance from river, and drainage density represent significantly effects on the groundwater occurrence. validation results show that the BLR model with best prediction accuracy and goodness-of-fit outperforms the other five models. Although, all models have very good performance in modeling of groundwater potential. Results of seed cell area index model that used for checking accuracy classification of models show that all models have suitable performance. Therefore, these are promising models that can be applied for the GWPZs identification, which will help for some needful action of these areas.

scholarly journals Assessment of groundwater potential zones using GIS and AHP techniques: a case study of the Lafia district, Nasarawa State, Nigeria

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Stanley Ikenna Ifediegwu
Keyword(s):  
Groundwater Resources ◽  
Pairwise Comparison ◽  
Research Area ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Groundwater Potential Zones ◽  
Thematic Maps ◽  
Borehole Data ◽  
Pairwise Comparison Matrix ◽  
Integrated Method

AbstractIn the Lafia district, rising population has increased the need for groundwater resources for economic growth. Sustainable groundwater resource management demands accurate quantitative assessment, which may be accomplished using scientific theories and innovative methods. In present study, an integrated method has been employed to assess the groundwater potential zones in the Lafia district utilizing remote sensing (RS), geographic information system (GIS), and analytic hierarchy method (AHP). For this aim, eight thematic maps regulating to occurrence and transportation of groundwater (i.e., geology, rainfall, geomorphology, slope, drainage density, soil, land use/land cover and lineament density) were generated and converted into raster format utilizing ArcGIS tool. Weights were assigned to these eight thematic maps based on their importance. Moreover, the final normalized weights of these parameters were calculated adopting pairwise comparison matrix of the AHP. To create the groundwater potential zones (GWPZs) map of the research area, we employed the overlay weighted sum approach to combine the parameters. The map has been divided into four zones (good, moderate, poor and very poor), each of which represents 19.3, 12.9, 57.8, and 10% of the study area. Lastly, the GWPZs map was validated utilizing borehole data obtained from 50 wells scattered throughout the study area to examine the performance of the approach. The validation results demonstrate that the adopted procedure produces highly reliable results that can aid in long-term development and strategic use of groundwater resources in this area.

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 Mapping Groundwater Potential for Irrigation, by Geographical Information System and Remote Sensing Techniques: A Case Study of District Lower Dir, Pakistan

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 669
Author(s):  
Abid Sarwar ◽  
Sajid Rashid Ahmad ◽  
Muhammad Ishaq Asif Rehmani ◽  
Muhammad Asif Javid ◽  
Shazia Gulzar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Table ◽  
Groundwater Potential ◽  
Geographical Information ◽  
Groundwater Potential Zone ◽  
Potential Zone ◽  
Relative Significance ◽  
High Good ◽  
Groundwater Potentiality ◽  
Very High

The changing climate and global warming have rendered existing surface water insufficient, which is projected to adversely influence the irrigated farming systems globally. Consequently, groundwater demand has increased significantly owing to increasing population and demand for plant-based foods especially in South Asia and Pakistan. This study aimed to determine the potential areas for groundwater use for agriculture sector development in the study area Lower Dir District. ArcGIS 10.4 was utilized for geospatial analysis, which is referred to as Multi Influencing Factor (MIF) methodology. Seven parameters including land cover, geology, soil, rainfall, underground faults (liniment) density, drainage density, and slope, were utilized for delineation purpose. Considering relative significance and influence of each parameter in the groundwater recharge rating and weightage was given and potential groundwater areas were classified into very high, high, good, and poor. The result of classification disclosed that the areas of 113.10, 659.38, 674.68, and 124.17 km2 had very high, high, good, and poor potential for groundwater agricultural uses, respectively. Field surveys for water table indicated groundwater potentiality, which was high for Kotkay and Lalqila union councils having shallow water table. However, groundwater potentiality was poor in Zimdara, Khal, and Talash, characterized with a very deep water table. Moreover, the study effectively revealed that remote sensing and GIS could be developed as potent tools for mapping potential sites for groundwater utilization. Furthermore, MIF technique could be a suitable approach for delineation of groundwater potential zone, which can be applied for further research in different areas.

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