Groundwater vulnerability assessment using an improved DRASTIC method in GIS

Recognizing the vulnerable areas for contamination is a feasible way to protect groundwater resources. The main contribution of the paper is developing a hybrid statistical decision-making model for evaluating the vulnerability of Shiraz aquifer, southern Iran, with modified DRASTIC (depth to the water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity) by using the genetic algorithm (GA), the analytical hierarchy process (AHP) method, and factorial analysis (FA). First, considering the variation of the uncertain parameters, 32 scenarios were defined to perform factorial analysis. Then using the AHP method and GA, DRASTIC parameters were rated and weighted in all scenarios. To achieve the optimal weights for parameters, the objective function in GA was maximizing the correlation coefficient between the vulnerability index and the nitrate concentration. The single and interactive effects of parameters on groundwater vulnerability were analyzed by factorial analysis. The results revealed that the net recharge had the highest single effect, and the resulted effect between net recharge and hydraulic conductivity was the most significant interactive effect on the objective function. Besides, the variation of aquifer media does not change the objective function. The application of the proposed method leads to a precise groundwater vulnerability map. This research provides valuable knowledge for assessing groundwater vulnerability and enables decision-makers to apply groundwater vulnerability information in future water resources management plans.

Groundwater resources are essential for drinking water, irrigation, and the economy mainly in semiarid environments where rainfall is limited. Currently, unpredictable rainfall due to climate change and pollution on the Earth’s surface directly affects groundwater resources. In this area, most people depend on groundwater resources for irrigation and drinking purposes, and every summer, most of the area depends on groundwater in a semiarid environment. Hence, we selected two popular methods, the analytical hierarchy process (AHP) and multiple influence factor (MIF) methods, which can be applied to map groundwater potential zones. Nine thematic layers, such as land use and land cover (LULC), geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps, were selected for this study using remote sensing and geographic information system (GIS) techniques. These layers are integrated in ArcGIS 10.5 software with the help of the AHP and MIF methods. The map of the groundwater potential zones in the study area revealed four classes, i.e., poor, moderate, good, and very good, based on the AHP and MF methods. The groundwater potential zone area is 241.50 (ha) Poor, 285.64 (ha) moderate, 408.31 (ha) good, and 92.75 (ha) very good using the AHP method. Similarly, the MIF method revealed that the groundwater potential classes were divided into four classes: 351.29 (ha) poor, 511.18 (ha), moderate, 123.95 (ha) good, and 41.78 (ha) very good. The results were compared to determine which methods are best for planning water and land resource development in specific areas that have basaltic rock and drought conditions. Both groundwater potential zone maps were validated with water yield data. The receiver operating characteristic (ROC) curve and area under the curve (AUC) model results are found to be 0.80 (good) and 0.93 (excellent) using the MIF and AHP methods, respectively; hence, the AHP method is best for delineation of groundwater potential zone maps and groundwater resource planning. The present study’s framework and the results will be valuable for improving the efficiency of irrigation, conserving rainwater and maintaining the ecosystem in India.

Groundwater vulnerability assessment has nowadays evolved into an essential tool towards proper groundwater protection and management, while the DRASTIC method is included among the most widely applied vulnerability assessment methods. However, the high uncertainty of the DRASTIC method mainly associated with the subjectivity in assigning parameters ratings and weights has driven many researchers to apply various methods for improving its efficiency. In this context, in the present study, different techniques were implemented with the aim of modifying the DRASTIC framework and thus enhancing its performance for groundwater vulnerability assessment in the Bouficha aquifer, Tunisia. In a first stage, the land use type (L) was incorporated as an additional parameter in the typical DRASTIC framework, thus taking into consideration the impact of anthropogenic activities on groundwater vulnerability. Subsequently, the rating and weighting systems of the developed DRASTIC-L framework were modified through the application of statistical methods (DRASTIC-L-SA) and genetic algorithms (GA) (DRASTIC-L-GA) in an attempt to investigate and compare both linear and nonlinear modifications. To evaluate the various vulnerability frameworks, correlation between vulnerability values and nitrate concentrations, expressed as Spearman's rank correlation coefficient (ρ) and Correlation Index (CI), was examined. The results revealed that the DRASTIC-L-GA framework developed by applying a fully GA-based optimization procedure provided the highest values in terms of the performance metrics used, making it the most suitable for the study area. In addition, the aquifer under study was found to be less vulnerable to pollution when employing the typical DRASTIC framework instead of the modified ones, leading to the conclusion that the former substantially underestimates pollution potential in the study area.

Groundwater vulnerability to pollution refers to the ease with which pollutants reach groundwater, in other words indicating the level of ease of an area to experience pollution. At present, the theme is one of the themes that attracts many researchers because pollution is more frequent in an area. The purpose of this study is to assess groundwater vulnerability in the study area for pollution using the GOD method and conduct a study of 3 groundwater vulnerability assessments, to determine the most appropriate assessment to be applied in the study area. The method used to determine groundwater vulnerability to pollution is GOD, which uses three parameters to assess the vulnerability of groundwater, namely aquifer type, rock type above aquifer and groundwater level. Furthermore, the results of the vulnerability assessment using the GOD method are compared with the vulnerability assessment according to the SINTACS and DRASTIC methods that have been carried out before in this area. The results showed that the variation of groundwater vulnerability index values in the study area according to the GOD method was from 0.35 to 0.63. Locations that are classified as medium vulnerability are generally located in the limestone Sentolo Formation, while locations that are classified as high vulnerability class are located in the volcanic rock of Yogyakarta Formation. Noting the results of determining groundwater vulnerability from the three methods, it can be said that the three methods are suitable for assessing groundwater vulnerability in the study area. However, looking at the distribution pattern of the level of pollution, the DRASTIC method can provide more detailed results related to the level of vulnerability.

The assessment of groundwater vulnerability to contamination has become an important element for landuse planning and groundwater resource management. This study aims at estimating groundwater vulnerability using an integration of Geographic Information System (GIS) and DRASTIC method in the Kumasi Metropolitan Assembly (KMA). The groundwater vulnerability map was prepared using index and overlay analysis with the aid of Arc GIS 10. The DRASTIC Index (DI) computed ranged between 70 and 164 as the lowest and highest contamination potential respectively. The eastern and western flanks and north-west tip of KMA are underlain by the granites which bear water due to the combined effect of weathering and fracturing and are dominated by "Very High", "High" and "Moderate" vulnerability based on the vulnerability index computed. The "Low" and "Very Low" vulnerability are located at the northern, central and southern parts of KMA which are underlain by phyllites. These suggest that boreholes located in the Birimian metasedimentary units which comprise mainly phyllites would be less likely to be vulnerable to contamination than those located in the intrusive rocks dominated by the granites. Keywords: Groundwater Vulnerability, Soil Media, Hydraulic Conductivity, Overlay Analysis

Assessment and validation of groundwater vulnerability to nitrate based on a modified DRASTIC model: A case study in Jilin City of northeast China

Remote sensing (RS) and Geographic Information System (GIS) are potential tools for competent planning and administration of essential groundwater resources. In this study, a typical methodology is proposed to delineate groundwater target zones using integrated RS, GIS and Analytical Hierarchy Process (AHP) method. The developed methodology is confirmed by a case study in Karur district of Tamil Nadu, Southern India. Seven thematic layers, viz., Lithology, Lineament Density, Geomorphology, Slope, Post– Monsoon Water Level, Drainage Density and Landuse/Land cover were considered in this study. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their virtual significance in groundwater incidence. The assigned weights of the thematic layers and their features were then normalized by using AHP. Finally, the selected seven thematic maps were incorporated by weighted linear combination method in a GIS environment to produce a groundwater targeting map. Thus, five groundwater targeting zones were identified and demarcated in the study area, viz., ‘very good’, ‘good’, ‘moderate’, ‘poor’ and ‘very poor’. The groundwater targeting map was finally verified using the well discharge data and the result was found acceptable. The ultimate result depicts the favorable groundwater targeting zones in the study area and can be helpful in better planning and managing of groundwater resources particularly in hard rock terrains.

Today, scientists are deeply concerned by the vulnerability of groundwater reservoirs to pollution. Relatively simple overlay and index methods can be used to produce groundwater vulnerability maps in geographic information system. In addition, this study deals with contamination from nonpoint sources. In this study, two such models, DRASTIC and GOD, were applied in the Jijel Plain area of northeast Algeria and compared with measured groundwater nitrate concentrations. This showed that results from DRASTIC were better than GOD, 69% correlation with nitrate compared to 56%. DRASTIC was better able to identify vulnerable zones along the river valleys. The DRASTIC model was then modified using the nitrate concentrations to optimize the rating score given within each parameter range and sensitivity analysis to change the weighting given for each parameter. These combined changes gave a final Pearson's correlation of 83% with nitrate. This showed that recharge, aquifer type, and topography were the key factors in controlling vulnerability to nitrate pollution.

Objectives: This study aims at the vulnerability assessment of groundwater in Raipur and Naya Raipur, Chhattisgarh, India, and to identify areas where vulnerability of groundwater to contamination is the most. Methods: A vulnerability map has been developed using SINTACS model in order to identify areas where vulnerability of groundwater to contamination is the most. In this analysis, vulnerability index is calculated by considering different hydrogeological parameters such as water table depth, net recharge, unsaturated conditions, soil media, aquifer media, hydraulic conductivity and topographic slope. All the parameters used in this study have been prepared, classified, weighted and integrated in a Geographic Information System (GIS) environment. Findings: The value of vulnerability index estimated lies between 121 to 176.Further, result shows that out of total area, 0.26% of the area indicates very low vulnerability 11.58% indicates low vulnerability 81.35% indicates moderate vulnerability and 6.81% of area indicates high vulnerability. It means majority of the study area exhibit moderate vulnerability. The study produces an effective tool for local authorities who manage and monitor the ground water resources. Novelty: This paper deals with a new approach towards vulnerability assessment. Instead of the conventional statistical methods, this work uses the SINTACS method which is a much improved method and hence provides much more probable values of vulnerability indices than those obtained from DRASTIC methods.

GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea)

Rapid population growth integrated with poor governance and urban planning is highly challenging resulting key for the selection of unsuitable landfill sites, particularly in developing counties. Therefore, the aim of this study is to investigate the suitable solid waste landfill sites in the capital of the country as a case study, by the integration of Geographical Information System (GIS) with fuzzy logic, analytical hierarchy process (AHP), and weighted linear combination (WLC) method based on multi-criteria decision-making (MCDM). We chose thirteen (13) criteria (9 factors and 4 constraints) and grouped them into two main categories (environmental and socioeconomic) to achieve the objectives. The AHP was employed to evaluate the relative importance of the factors followed by standardization of criteria factors based on fuzzy set theory. Subsequently, all criteria factors were combined based on AHP and fuzzy logic-WLC method in order to obtain land suitability map. Finally, the sites were identified by the intersection of two combined suitability index layers. The obtained results depicted that the integration of fuzzy logic, AHP, and WLC technique with GIS can produce satisfactory results for the suitable locations of solid waste landfill sites over complex topographic regions. Overall, the land suitability obtained based on fuzzy-WLC is more refined and smooth because of its better segregation and its potential to consider full tradeoff between factors and average risk. The AHP was identified (47km2) as high suitable while fuzzy-WLC generated 36km2 as suitable area. Finally, the intersection of both suitability index map shows numerous suitable landfill sites available in Islamabad city; however, the surface areas of the sites are small at individual level (less than 15ha).

Uncertainty in the supply and demand and a lack of available freshwater resources require a better management plan for sustainable development in agriculturally dependent communities. Therefore, scarce freshwater resources are protected and monitored to prevent contamination. Groundwater is the largest freshwater reservoir, and groundwater zones prone to contamination need to be identified. A precise model that enables the simplification and validation of the assessment process was developed by applying a fuzzy logic technique. A hierarchical fuzzy inference model (HFIM) was developed to better handle the input. The application of the developed model was then compared with the conventional index-based DRASTIC model in the Cuddalore District. The parameters that were found to influence the degree of vulnerability, including the depth of the water table (D), net recharge to the aquifer (R), aquifer media (A), soil properties (S), topography of the area (T), impact of the vadose zone (I), and hydraulic conductivity of the aquifer (C), were considered in the model development. A geographical information system (GIS) framework was utilized to synthesize the DRASTIC model and MATLAB was employed to develop the hierarchical fuzzy inference model. The results obtained from the GIS-DRASTIC model and HFIM were classified into five and seven categories based on their index values, respectively. The models were validated using nitrate concentration (mg/l) data obtained from 40 sampling points in and around the study area. A sensitivity analysis was performed on the models by varying the input from their minimum to maximum values for a selected hydrogeological setting. The results revealed that the HFIM was better at determining groundwater vulnerability levels in the Cuddalore District. It could cope with the uncertainty and nonlinearity of the datasets; the output showed a continuous response to modifications of the input data, which contrasts the DRASTIC model.

Proper site selection for solid waste disposal is a significant issue in the management of solid waste. The present study has been carried out in Debark town, Amhara region, Northwestern Ethiopia, with an analytical hierarchy process (AHP) method and geographic information system (GIS) tools to locate the suitable solid waste disposal sites. In the present study, the following eleven thematic layers such as groundwater level, lithology, land use/land cover, precipitation, soil types, elevation, and slope, distance from the (drainages, springs, lineaments, and roads), and their sub-criteria have been used for the selection of suitable solid waste disposal sites. The above-mentioned thematic factors and their sub-criteria standardized weights and consistency ratios have been calculated and checked using the AHP method. The outcome of this study shows (2 km2 area) 2.50%, (3 km2 area) 3%, and (77 km2 area) 94.5% of the area is highly, moderately, and unsuitable, respectively, for the siting the solid waste disposal site in the present study area. The current study results show the effectiveness of GIS tools and the AHP method in solid waste disposal site selection analysis.

With the rapid development of science and technology, new technology is starting to be used in various fields including education. Education has a very important progress in a nation, because it can optimize individual potential. The educational process in higher education has a big influence on a student's future. However, there are many students who experience difficulties in choosing a college major after graduating from vocational high school (SMK) or senior high school (SMA), because of the complexity in identifying the suitability between interests and study programs. Decision making is a problem that everyone faces, especially in choosing an appropriate college major. There are many factors to consider, and with many options available, the decision-making process can be difficult. To overcome this problem, this research aims to create a decision support system (DSS) using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique For Order By Similarity To Ideal Solution) methods. The AHP method is used to solve complex problems by structuring a hierarchy of criteria and developing weights or priorities. However, when the AHP method is used with many criteria and alternatives, other methods are needed for more effective results. Therefore, a combined method of AHP and TOPSIS was chosen, where AHP focuses on pairwise comparison matrices and consistency analysis, while TOPSIS can measure relative performance and alternative decision making simply and efficiently. The results of research on decision support systems for selecting majors using the AHP and TOPSIS methods show that the application of the combined AHP-TOPSIS method can be used to determine the best alternative in selecting majors by comparing alternatives based on predetermined criteria. In addition, system testing results show that the system functions as expected and meets user needs. With a decision support system for selecting college majors implemented on the website, it can simplify the decision-making process for students and BK teachers in choosing college majors. The results of the calculation of the percentage of system feasibility in blackbox testing show a value of 95.71%, which indicates that this major selection decision support system website can be used.

Identification of groundwater potential recharge zones in a Tunisian anthropogenic coastal region: Insights from multi-criteria decision-making techniques