Groundwater Vulnerability Assessment Methods Research Articles

Оценка уязвимости карстовых подземных вод к загрязнению на основных массивах Горного Крыма с использованием региональной методики

Introduction. Assessment of groundwater vulnerability to contamination is an effective tool for scientific substantiation of the sanitary protection zones for drinking water sources. Karst ground waters of the Mountain Crimea form the main resources for water supply in the Crimean Peninsula. This study has a purpose to perform the assessme nt and mapping of karst ground waters resource vulnerability to contamination on such representative massifs of the Crimean Mountains as Chatyrdag, Dolgorukovsky, Karabi and Ay-Petri . Materials and methods. Assessment of karst ground waters vulnerability is conducted by use of Mountain -Crimean method. It has been developed on the base of some wide-tested European methods (COP-method and Slovene approach) with methodological modification and adaptation to regional conditions of the Mountain Crimea. The input data for assessment is spatial information about ground waters vulnerability factors: protective layers in vadose zone, flow concentration by streams, sinkholes and caves, precipitation regime etc. The collected spatial information was converted into attributed geo data layers, which were subsequently subjected to overlay operations in Arc GIS 10 software according to assessment scheme. Results. According to the assessment results, approximately 34 and 14% of the Chatyrdag massif area gained the category of high and very high vulnerability, on the Karabi massif – 14 and 17%, on the Dolgorukovsky massif – 14 and 2%, on the Ay-Petri massif – 19 and 7% of total area respectively. The result ing vulnerability maps demonstrate significant mosaics and contrast, which is associated with discrete distribution of protective covers and high differentiation of ground water recharge conditions within the catchments of karst massifs. Discussion. Analysis of the resulting vulnerability maps have revealed that the leading factors determining areas of high and very high vulner ability of karst waters are runoff concentration factors, while the factors of protective cover mainly determine the areas with low vulnerability. The zones of high vulnerability on the Chatyrdag and Karabi massifs are mainly coincide with areas of high density of karst forms (sinkholes and caves), while high vulnerability zones of the Ay-Petri and Dolgorukovsky massifs are predominantly associated with areas near permanent and temporary watercourses. In general, the obtained maps of groundwater vulnerability are quite consistent with the known data on the hydro-geological conditions of the assessed massifs. Conclusions. The identified differences in the area ratio and spatial distribution of ground waters vulnerability categories between the assessed massifs are a consequence of local geological, geo-morphological and hydrological features. The obtained results confirm high applicability of the Mountain-Crimean regional method for groundwater vulnerability assessment, at least for the karst massifs of the Mountain Crimea. Suggestions for practical application and direction for future research. The produced groundwater vulnerability maps create a scientific basis for delineation of water protection zones, assessing the risks of groundwater pollution and developing the territorial planning schemes within studied areas. The next stage of study is an assessment of groundwater source vulnerability for individual karst springs used in water supply.

Enhancing groundwater vulnerability assessment: Comparative study of three machine learning models and five classification schemes for Cuddalore district

Most of the groundwater vulnerability assessment methods using machine learning are binary classification. This study attempts multi-class classification models to map the groundwater vulnerability against Nitrate contamination. Further, the significance of the number of classes used in the multi-class classification is studied by considering three and five classes. Three machine learning models, namely Random Forest, Extreme Gradient Boosting and CART, with two classification schemes, were developed for the present study. The parameters used in the conventional DRASTIC method and with an additional parameter, Landuse, have been employed for the study. Evaluation metrics such as Accuracy, Kappa, Positive Predictive Value, Negative Predictive Value, and Area Under the Curve of the Receiver Operating Characteristic (AUC-ROC) were compared among all six models to select the optimal one. Based on the model evaluation metrics and consistent distribution of area among the classes Random Forest model with a three-class classification with an AUC of 0.95 is considered optimum for the selected objective. This study highlights the importance of the data classification process and the selection of the number of classes for ML model prediction in assessing groundwater vulnerability. Leveraging the effectiveness of the Geographic Information system and advanced machine learning techniques, the proposed approach offers valuable insights for enhanced groundwater management and contamination mitigation strategies.

Implementation and evaluation of different techniques to modify DRASTIC method for groundwater vulnerability assessment: a case study from Bouficha aquifer, Tunisia.

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.

Modified DRASTIC method for groundwater vulnerability assessment in areas with diverse Quaternary deposits

Abstract The DRASTIC method is one of the most widely used groundwater vulnerability assessment techniques. In areas where the main useful aquifers are covered with an extra layer of diverse sediments, a further modification of the DRASTIC method is required for a more precise vulnerability estimation. In this article, the DRASTIC method was improved in areas characterized by a layer of diverse Quaternary deposits remarkably influencing the infiltration conditions. Three parameters were modified: (1) the D-parameter was adjusted to consider the overlying Quaternary deposits that, in some cases, make the aquifer confined, (2) the S-parameter was replaced by the Quaternary sediment-type parameter to assess the hydraulic characteristics of the highly variable deposits, and (3) the I-parameter was replaced by the thickness of the Quaternary deposits parameter to describe the distance from the ground surface to the main useful aquifer. The original and modified DRASTIC methodology was applied in an area with glacial sediments in Central Estonia. Comparing the results using the original and the modified DRASTIC method to a former Estonian groundwater vulnerability method showed that the DRASTIC method was significantly improved and could, thus, be successfully applied in other areas characterized by a heterogenous Quaternary sediment cover.

A Review on Process-Based Groundwater Vulnerability Assessment Methods

The unreasonable development and pollution of groundwater have caused damage to the groundwater system and environmental problems. To prevent this, the concept of “groundwater vulnerability” was proposed, and various evaluation methods were developed for groundwater protection. However, with changing climatic conditions and human activities, groundwater vulnerability is now emphasizing physical processes. This study aims to review and analyze the principles and applications of process-based groundwater vulnerability methods to achieve the source protection of groundwater resources. It introduces the assessment method and elaborates on pollutant migration processes and numerical simulation technology. Relevant articles from the past 30 years are reviewed to show the evolution of process-based groundwater vulnerability assessment. The study also discusses current research trends and proposes future development paths. It concludes that process-based groundwater vulnerability assessment will become the mainstream method, and modern technologies such as artificial intelligence will be necessary to solve challenges and achieve sustainable development.

Comparison of GIS-Based Intrinsic Groundwater Vulnerability Assessment Methods: DRASTIC and SINTACS

The possibility of contaminants percolating and diffusing into the groundwater system is referred to as groundwater vulnerability. When groundwater once gets polluted it is very difficult to process/clean it so, measures must be taken to assess the vulnerability of the groundwater for effective groundwater conservation and management planning. This study aims to evaluate and map the vulnerability of Raipur city using the SINTACS and DRASTIC models and to compare their effectiveness between them. To assess the hydrogeological setting and evaluate aquifer vulnerability, each model includes seven environmental parameters (aquifer hydrogeologic features, effective infiltration, topographic slope, soil media, water table depth, unsaturated conditions, and hydraulic conductivity). The parameter data sets are evaluated in a Geographical Information system (GIS) environment to get the vulnerability index (VI), the index is categorized into five classes that show low to high vulnerability. The area under the low class for DRASTIC and SINTACS is 26.14% and 20.34% respectively whereas for the highly vulnerable class it is 15.54% and 22.54% respectively of the total area. By comparing the 15-groundwater sample value of nitrate concentration on the two vulnerability maps it was found that the SINTACS method result was shown to be significantly associated with the nitrate concentration with an accuracy of 86.7 percent.

Comparison of DRASTIC and DRASTICL groundwater vulnerability assessments of the Burdekin Basin, Queensland, Australia

In the Burdekin Basin, Queensland, Australia, groundwater contamination due to agricultural activities has led to concerns over its impacts on globally significant ecosystems such as the Great Barrier Reef. An appropriate method for groundwater vulnerability assessment is essential for the sustainable use of this groundwater resource and its longer-term environmental management. The aim of this study is to apply and assess the suitability of the standard DRASTIC index-based method for groundwater vulnerability assessment of the Burdekin Basin. The intrinsic groundwater vulnerability is calculated in ArcGIS, using data for the period 2010 to 2021. The results are compared to available water quality data. The calculated DRASTIC scores are found to be only weakly correlated with water quality parameters, including the nitrate concentration (R = 0.07), which should behave as a proxy measure of groundwater vulnerability. To address this, a modified DRASTICL method containing a land use parameter is also implemented, to assess the specific groundwater vulnerability. The correlation between DRASTICL scores and nitrate levels (R = 0.2) is more significant but is still relatively weak. From this study, it is recommended that alternative methods be developed to assess groundwater vulnerability in the Burdekin Basin, and other comparable aquifer systems.

Vulnerability methods in hard rock formation as a basis for groundwater risk assessment – from resource to source

Groundwater in a hard rock formation is most endangered at places where a potential source can discharge contaminants that can reach the saturated zone of an aquifer. In these circumstances, an essential tool for groundwater protection is the contamination risk map. This map is based on the integration of two maps: a hazards map, i.e., map of potential sources of contamination and a vulnerability map. The selection of a proper vulnerability method is an important task since the resulting vulnerability map can significantly impact the final risk of contamination map. The most appropriate method for groundwater vulnerability assessment was considered in the case study of Tara National park, in Western Serbia. The four commonly used methods were applied to assess the intrinsic vulnerability maps: DRASTIC, EPIK, PI and COP. All the applied methods resulted in different vulnerability maps in assessing the degree of vulnerability, consequently influencing the groundwater contamination risk maps. The applied research presents an example of how contamination risk should be assessed in a specific area. Comparison of the results obtained for the area of Tara National Park indicates the preference of the PI method as a well-balanced method, taking into account all the specifics of the study area. A detailed analysis of the assessed risks in the catchments of the existing sources was also conducted to indicate probable sources of contamination and confirm the degree of accuracy of the created vulnerability and risk maps. The conducted research emphasizes the necessity to adopt a clear conceptual hydrogeological model and to apply several methods simultaneously to determine the optimal one for each individual area.

An evaluation of groundwater vulnerability assessment methods in a rapidly urbanizing city: evidence from Dakar, Senegal

In rapidly growing cities in the tropics, unregulated urban development presents a major risk to groundwater quality. Here, we assess the vulnerability of an unconfined aquifer of Quaternary sands in the Thiaroye area of Dakar (Senegal) to contamination using four GIS-based indices (DRASTIC, DRASTIC_N, SINTACS, SI). Our correlation of assessed vulnerability to observed impact is semi-quantitative, relating observed groundwater quality, based on nitrate concentrations and tryptophan-like fluorescence to vulnerability degrees (i.e. coincidence rates). We show that considerably more of the Thiaroye area has a “very high vulnerability” according to SI (36%) relative to DRASTIC (5%) and SINTACS (9%); “high vulnerability” is estimated using DRASTIC_N (100%), DRASTIC (66%) and SINTACS (69%). Single-parameter sensitivity tests show that groundwater depth, soil, topography, land use and redox parameters strongly influence assessments of groundwater vulnerability. Correlation with observed nitrate concentrations reveals aquifer vulnerability is better represented by SI (coincidence rates of 56%) relative to DRASTIC_N (43%), SINTACS (38%) and DRASTIC (34%). The underestimation of groundwater vulnerability in Dakar using DRASTIC, DRASTIC_N and SINTACS is attributed to their reliance on an assumed capacity of the unsaturated zone to attenuate surface or near-surface contaminant loading, which in the low-income (Thiaroye) area of Dakar is thin and affords limited protection. The inclusion of a land-use parameter in SI improves the characterization of groundwater vulnerability in this low-income, rapidly urbanizing area of Dakar.

A Comparative Study of Groundwater Vulnerability Assessment Methods

Recently, methods have emerged to assess the vulnerability of groundwater to pollution, which has been adopted by many countries that depend on groundwater as an important and supportive resource for surface water to protect groundwater and monitor and control its pollution. Assessment methods adopt vulnerability maps and compare them with the real-life pollution map of the region. The study was conducted in Al-Teeb area, which is located in the northeast of Missan province, south of Iraq. This area is about 2450 km2. This study applied four models DRASTIC, GOD, SINTACS and Modified DRASTIC of vulnerability maps are analyzed using GIS technique and compared with the reality map which represent the nitrate concentration map as a basic comparison map; in order to choose the closest one with respect to the realistic acting. The results showed that 80.29 % of study area is classified under low vulnerability in DRASTIC method and moderate vulnerability in GOD, SINTACS and MD-DRASTIC which are covered 54.12 %, 83.18 % and 72.35 % of study area respectively. Pearson's correlation coefficient was used to compare the four methods with the nitrate concentration map, where the correlation value for DRASTIC, GOD, SINTACS and MD-DRASTIC was 73.05, 49.79, 83.23 and 87.94 %, respectively. So, the MD-DRASTIC is represented the best technique for evaluating vulnerability map in the study area which can be recommended.

Application of the APLIS Method for Groundwater Vulnerability Assessment in Rote Island Karst Areas

The karst area on Rote Island dominates more than 60% of the Island. The land surface conditions in karst areas are generally dry, while below the subsurface is the potential for abundant water resources. This study aims to assess groundwater vulnerability using the APLIS (Altitude, Pendiete/Slope, Lithology, Infiltration, and Soils) method that will integrate with Geographic Information System (GIS) technique. The parameters used are elevation, slope, lithology, infiltration zone, and soil type. Slope and elevation are obtained from DEM maps, the soil is obtained from soil type maps, while lithology and infiltration zone are obtained from geological maps. The lithology and the infiltration zone in APLIS method analysis have a high role in determining the level of groundwater vulnerability. The groundwater vulnerability in Rote Island was divided into four classes: very low in the Northeast, low in the South, moderate in the East and North, and high in the East and West part of the Island. It explains that a high level of groundwater vulnerability in Rote Island needs to be used as a groundwater protection zone.

New hybrid evolutionary algorithm for optimizing index-based groundwater vulnerability assessment method

Limited hydrogeological data accessibility leads scholars to improve the robustness of present qualitative groundwater vulnerability assessment methods using mathematical techniques. In the present study, we implemented three GIS-based groundwater vulnerability assessment indices, namely DRASTIC (Depth to water table, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity), SINTACS (Soggicenza, Infiltrazione, Non saturo, Tipologia della copertura, Acquifero, Conducibilità, and Superficie topografica), and GODS (Groundwater confinement, Overlying strata, Depth to groundwater, and Soil media) to assess the groundwater vulnerability levels. Although DRASTIC results showed better performance with respect to the nitrate concentration data from 50 observation wells in the study site, the index is still unreliable due to its inherent drawbacks, including subjectivity. Hybrid PSO-GA method is a successful optimization algorithm gathering the advantages of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) while avoiding their shortcomings. The DRASTIC weighting system is optimized using PSO-GA optimization algorithm. Also, Step-wise Weight Assessment Ratio Analysis (SWARA) as a Multi-Attribute Decision Making (MADM) method is applied for changing ranges of DRASTIC rates and weights. The vulnerability indices obtained from SWARA-SWARA, DRASTIC-PSO-GA, and SWARA-PSO-GA frameworks are evaluated and compared with generic DRASTIC regarding the nitrate concentration dataset by employing Area Under the ROC Curve (AUC) and Grey relational analysis methods. Results show a noticeable improvement of correlation between indices and observed nitrate concentration after modifications and optimizations. The new hybrid SWARA-PSO-GA framework is the most effective framework in assessing the vulnerability of the present study area.

DRASTIC framework improvement using Stepwise Weight Assessment Ratio Analysis (SWARA) and combination of Genetic Algorithm and Entropy.

Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overlay and index groundwater vulnerability assessment methods. The development of a robust groundwater vulnerability assessment framework for precise identification of susceptible zones may contribute to more efficient policies and plans for sustainable managements. To achieve an overall view of the groundwater pollution potential, the DRASTIC framework (Depth to the water table, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and hydraulic Conductivity) can be used for intrinsic vulnerability assessment. However, the unreliability of this index is because of its inherent drawbacks, including the weight and rating assignment subjectivity. To modify the rating range, this study recommended a new DRASTIC modification using a recently introduced Multi-Criteria Decision-Making (MCDM) method, namely the Stepwise Weight Assessment Ratio Analysis (SWARA); in addition, the Entropy and Genetic Algorithm (GA) methods were employed to alter the relative weights of DRASTIC parameters. To improve the DRASTIC index, nitrate concentration data from 50 observation wells in the study site were used. To assess the models' overall performance, the datasets obtained from new observation wells, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were studied. The experiments were carried out in the aquifer of the Qazvin Plain in Iran. The results indicated the higher performance of the modified DRASTIC framework, manifested as an increase in the AUC value from 0.58 for generic DRASTIC to 0.68 for the SWARA-Ent framework and 0.74 for the SWARA-GA framework. The application of the SWARA technique, as an effective MCDM method, resulted in the DRASTIC rating system enhancement. The generic DRASTIC optimization by integrating SWARA and GA provided an effective framework to assess groundwater vulnerability to nitrate contamination in the Qazvin Plain.

A new assessment method for the vulnerability of confined water: W-F&PNN method

At present, groundwater vulnerability assessment is mainly aimed at phreatic aquifer, but in most areas, people draw water from confined aquifer, so it is necessary to assess the vulnerability of confined water. As the existing groundwater vulnerability assessment methods are greatly influenced by subjectivity. The purpose of this study is to put forward W-F&PNN method to avoid subjectivity. Weber-Fechner (W-F) law in psychophysics and Probabilistic Neural Network (PNN) are combined in this paper. W-F law is a theory for describing the people's response to a stimulus, which is used to calculate the cluster center and determine the assessment standard; Probabilistic Neural Network is a widely used algorithm for classification, which is used to classify the vulnerability of confined water. According to the influence factors of confined water, the assessment parameters D3A2C2 were determined, and the vulnerability of confined water in plain area of Xi'an city in 2005 was assessed by W-F&PNN method and were divided into four categories. The vulnerability of confined water gradually reduces from the flood plain, the first terrace, the second terrace, the third terrace, the alluvial fan, to the loess tableland. Results of vulnerability assessment were validated by nitrate concentration in 2016 over the area. The results show that the distribution of vulnerability region is mostly consistent with that of nitrate concentration region. The W-F&PNN method does not assign rate, but calculate the cluster center; and not need to assign weight for parameters, avoiding subjectivity, is a reliable method for groundwater vulnerability assessment and suitable for the area with insufficient data.

Intrinsic groundwater vulnerability assessment by multiparameter methods, a case study of Suva Planina Mountain (SE Serbia)

Karst terrains appear on all continents and karst aquifers produce drinking water for more than 9% of the world’s population while being the most vulnerable to contamination. One of the main challenges in the management of a water supply that depends on groundwater is the possibility of the pollution of the karst aquifer which is usually open toward the surface and is highly permeable. Various environmental problems found in karstic areas demand a completely unconventional approach for this particular environment. To achieve and maintain high-quality groundwater that can be used for a public water supply, an effective prevention program must be designed and implemented. The process of determining the sanitary protection zones (SPZ) has been relying on new technologies, especially the use of a geographic information system (GIS) environment. An assortment of groundwater vulnerability assessment methods has been developed in the GIS environment, as a necessary basis for implementing preventive measures. Suva Planina Mountain is one of the greatest and the highest karst massifs in South-East Serbia. Almost all known karst features are present, and several karst springs exist at the foothill of the mountain. The largest springs have been captured for the water supply. The catchment areas of the springs are not populated and there is no industry, besides grazing and forestry; nevertheless, some limits for human impact must be enacted. This paper is an attempt at using the GIS-overlay spatial modeling technique for groundwater vulnerability assessment of Suva Planina Mountain. Maps of intrinsic vulnerability have been designed by the application of three multi-parameter methods for vulnerability mapping (EPIK, PI, COP). The maps that have been designed for Suva Planina Mountain show the existence of four classes of vulnerability, though in somewhat different arrangements and distribution.

Groundwater vulnerability assessment for the karst aquifer of Tanour and Rasoun springs catchment area (NW-Jordan) using COP and EPIK intrinsic methods

Groundwater vulnerability maps were constructed for the surface water catchment area of Tanour and Rasoun spring (north-west of Jordan) using the COP and EPIK intrinsic groundwater vulnerability assessment methods. Tanour and Rasoun springs are the main water resources for domestic purposes within the study area. A detailed geological survey was carried out, and data of lithology, karst features, precipitation, vegetation and soil cover, etc. were gathered from various sources for the catchment area in order to determine the required parameters for each method. ArcGIS software was used for map preparation. In the resulting COP vulnerability map, spatial distribution of groundwater vulnerability is as follows: (1) high (37%), (2) moderate (34.8%), (3) low (20.1%), and (4) very low (8.1%). In the EPIK vulnerability map, only two out of four vulnerability classes characterize the catchment area: very high vulnerable areas (38.4%) and moderately vulnerable areas (61.6%). Due to limited soil thickness, the low vulnerability class is absent within the catchment. The high percentage of very high to moderately vulnerable areas displayed by both the COP and EPIK vulnerability assessment methods are reflected by different pollution events in Tanour and Rasoun karst springs especially during the winter season. The high sensitivity of the aquifer to pollution can be explained by different factors such as: thin or absent soil cover, the high development of the epikarst and karst network, and the lithology and confining conditions of the aquifer.

Indicative mean transit time estimation from δ18O values as groundwater vulnerability indicator in karst-fissure aquifers

Ideally, groundwater vulnerability assessment should take into account potential contaminant breakthrough curve, characterized by transit time, relative change of contamination concentration (input/output) and duration of overstepped concentration. Still, a majority of groundwater vulnerability assessment methods that tend to be more physically based count only with the value of mean transit time (MTT), the elapsed time when groundwater can exit the aquifer after its recharge. In this paper, indicative values of MTT derived from single δ18O sampling values were used to estimate intrinsic vulnerability of individual springs occurring on the Muranska planina Plateau (Slovakia). For 295 springs sampled within 10 days, δ18O was found in the range between −10.90 and −7.32 ‰, without signs of altitudinal effect. According to International Atomic Energy Agency (IAEA) Global Network of Isotopes in Precipitation (GNIP) stations, significant contrast in precipitation δ18O values was found several weeks before sampling. Indicative MTT value, e maxMTT (estimated longest possible mean transit time), was calculated from sine wave course of monitored precipitation isotopic composition, δ18O value in the spring groundwater sample and altitudes of sampled point and precipitation station. Estimated e maxMTT values suggest that heavier oxygen isotopes in samples probably reflect quick circulation and a more vulnerable environment as influenced by enriched summer precipitation. Depleted δ18O suggests lower vulnerability represented by higher e maxMTT values.

Proposed APLIE method for groundwater vulnerability assessment in karst-phreatic aquifer, Shandong Province, China: a case study

Groundwater vulnerability assessment has become a useful tool to delineate areas for the prevention and control of groundwater pollution. The paper proposed the APLIE method by combining the DRASTIC, PI, COP, European approach with the characteristics of karst-phreatic aquifer in North China in the help of ARCGIS®, which was used to assess the groundwater vulnerability of Dawu water source, Shandong Province, China. Water abundance (A), protective cover (P), types of land use (L), infiltration amount of precipitation (I) and groundwater exploitation (E) were picked up to compose the index system for characterizing the hydrogeology and environmental geology setting and evaluating the aquifer vulnerability. Weights of new index system were reassigned using the analytic hierarchy process method based on the relative importance of indexes. The assessment results indicated that groundwater vulnerability mapping with APLIE method is in better agreement with the current hydrogeological and environment geological understanding of Dawu water source area compared with the results obtained from PI and COP methods. And the exceeding standard subareas of ammonia nitrogen (NH4-N) and electric conductivity in the study area proved the reliability of groundwater vulnerability results. Subareas of vulnerability were portioned by natural breaks based on the spatial platform of ARCGIS®. The integrated vulnerability map showed that the very high and high vulnerability subareas were formed for reasons of highest or higher infiltration amount of precipitation (I), worst or worse protective cover (P), most complex type of land use (L), poor water abundance (A) and over groundwater exploitation (E). Sensitivity analyses showed that infiltration amount of precipitation (I) is the most sensitive factor affecting groundwater vulnerability in the case study. In short, APLIE method was applicable to assess the karst-phreatic vulnerability in the study area with readily available hydrogeological and environment geological data. Hence, the groundwater vulnerability mapping is a promising tool for sensible groundwater resource management and land use planning, which contributes to the development of human survival and sustainable development of groundwater.

Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh–Bonab plain aquifer, Iran

Summary Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh–Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the pollution risk.

지하수 오염 취약성 기법의 비교 적용 연구: 충남 홍성군 금마면 일대에의 적용

In the present study, several groundwater vulnerability assessment methods were applied to an agricultural area of Gumma in Korea. For the groundwater intrinsic vulnerability assessment, the performance of DRASTIC, SINTACS and GOD models was compared and an ensemble approach was suggested. M-DRASTIC and multi-linear regression (MLR) models were applied for the groundwater specific vulnerability assessment to nitrate of the study site. The correlation coefficient between the nitrate concentration and M-DRASTIC index was as low as 0.24. The result of the MLR model showed that the correlation coefficient is 0.62 and the areal extents of livestock farming and upland field are most influential factors for the nitrate contamination of groundwater in the study site.