Groundwater Vulnerability Mapping Research Articles

Assessment of Groundwater Vulnerability to Seawater Intrusion Using GALDIT, SITE and SIVI Methods in Laspias River Coastal Aquifer System, NE Greece

This paper presents the investigation of groundwater vulnerability to seawater intrusion of the aquifer system in the coastal area of Laspias River, NE Greece, for the year 2023, by applying the GALDIT, SITE and SIVI methods, in the context of the groundwater management of the area. The relevant research works include the collection and analysis of data and information regarding the geological and geomorphological environment, as well as the hydrogeological system of the area. The calculation of the GALDIT, SITE and SIVI indices values is described, and the results from the application of the methods are presented, as well as the design of relevant groundwater vulnerability maps of the study area. This paper concludes with findings and proposals useful for the reliable assessment of the hydrogeological regime of the wider study area.

GROUNDWATER VULNERABILITY MAP OF BASARA BASIN, SULAIMANI GOVERNORATE, IRAQI KURDISTAN REGION

The Basara basin which is one of the most promising hydrogeological basin in Iraqi Kurdistan Region, located in north east of Iraq, 25 km west of Sulaimani city, between the 496652 - 537752 East and 3911038 - 3951906 North in Universal Transverse Mercator (UTM) and lie in Zone 38N. The basin has a rectangular shape and covering an area of 571 km². The present hydrogeological investigations have revealed three inhomogeneous and anisotropic water bearing formations: Eocene Karstic Fissured Aquifer (EKFA), Intergranular Aquifer represented by Alluvium and Pliocene (AIA) & (PIA), as well as Miocene Complex Aquifer (MCA).For the first time, not only in Kurdistan but also in Iraq, Groundwater Vulnerability Map has been constructed in this study, using DRASTIC method with the assistance of Geographic Information System (GIS) to show zonation area of high and low groundwater susceptibility to pollution. Accordingly, vulnerability classes of the study area were classified into four classes. Most of the basin shows the highest extension of the zones with very low and low vulnerability zones, in contrast the zones with high vulnerability are distributed mainly in the mountain areas, solely in the eastern Uloblagh and Kuwaik mountains, in addition to that small zones in the farthest northern corner and south western corner of the area have less or no human activity.

Using VES and GIS-Based DRASTIC Analysis to Evaluate Groundwater Aquifer Contamination Vulnerability in Owerri, Southeastern Nigeria

This study assesses groundwater vulnerability in Owerri, Nigeria, using Vertical Electrical Sounding (VES) and Geographic Information System (GIS)-based DRASTIC modeling. The research methodology includes literature review, field survey, geological feature mapping, hydrogeological assessment, geo-electrical sounding, and data interpretation. Owerri, a rapidly developing city with flat topography and a growing population, uses the DRASTIC model to construct a groundwater vulnerability map. The model evaluates the risk of groundwater contamination using seven critical criteria, including depth to water table, net recharge, aquifer media, soil media, topography, vadose zone impact, and hydraulic conductivity. Each parameter was given a weight and rating, and the DRASTIC Index (DI) was calculated by summing the products of the weights and ratings for each factor. The results of the vulnerability assessment indicated that approximately 49% of the study area falls into the high vulnerability category, around 45% is classified as moderate vulnerability, and the remaining 6% is labeled as low vulnerability. The study reveals moderate to high vulnerability zones in Owerri, Nigeria, due to factors like lower slope terrain, permeable aquifer media, and vadose zone impact. The use of VES and GIS-based DRASTIC mapping techniques provides insights into groundwater vulnerability, aiding in sustainable resource management and environmental protection. The findings emphasize the importance of understanding potential risks and the need for effective management strategies to safeguard clean water supplies. Further research and mitigation efforts should focus on highly vulnerable areas.

Advancing groundwater vulnerability assessment in Bangladesh: a comprehensive machine learning approach

In response to Bangladesh's severe water shortages, this research delves into the intricate dynamics of groundwater vulnerability. Integrating often-overlooked factors such as topography, meteorology, socio-economic conditions, and land use & geology, the study employs advanced Random Forest (RF) modeling. Rigorously analyzing 200 strategically chosen sample points, the research uncovers critical areas like Rajshahi, Nawabganj, Naogaon, and Dhaka, constituting 21% of the land, as highly vulnerable. In contrast, regions like Rangpur, Mymensingh, and Barisal, encompassing 31% of the area, exhibit lower vulnerability. Topographic factors, accounting for 45% of the vulnerability, including aspect, drainage density, and slope, significantly influence susceptibility. Socio-economic elements contribute 22%, particularly population density and industrial activities. The RF model achieves exceptional accuracy (over 90%), emphasizing the complexity of groundwater dynamics. By integrating geological, social, and economic aspects, the study provides actionable insights for nuanced and sustainable management strategies. This research not only unveils a highly accurate groundwater vulnerability map, enriching scientific understanding, but also offers a unique approach by incorporating often-overlooked variables and leveraging machine learning. These insights empower policymakers and urban planners to craft targeted and sustainable groundwater management strategies, ensuring a resilient water supply system for Bangladesh's growing population. Through this work, the aim is to significantly contribute to the scientific community while providing data-driven solutions for the nation's pressing water challenges.

Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer’s highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

Assessing Groundwater Resources Vulnerability with the New DRASTIC-LP: A Case Study in Chiang Mai Province, Thailand

Groundwater vulnerability has gained widespread attention, particularly in Chiang Mai Province, one of Thailand’s fastest-growing cities, which is experiencing rapid development in both economic and social sectors. The expansion of urban communities and the industrial, tourism, and agriculture sectors has resulted in the overutilization of available resources, notably water resources. This overuse, coupled with the adoption of modern technology to boost productivity and meet market demands, has led to an increased reliance on groundwater to supplement surface water sources, providing benefits across all sectors. However, the economic and social growth plays a pivotal role in shaping the diversity of land use, encompassing residential, commercial, industrial, and agricultural activities. These activities, in turn, directly contribute to environmental pollution, particularly in terms of the risk of groundwater contamination in Chiang Mai Province. This study aims to predict the future vulnerabilities of groundwater resources under an ensemble of climate change scenarios and changes in land-use patterns. Chiang Mai Province in northern Thailand is one of the fastest-growing cities and therefore is experiencing rapid urbanization, as well as land-use pattern changes, which was important for the case study. The new DRASTIC model, namely the DRASTIC-LP model, combined with GIS-based techniques and overlay techniques, was used to generate the map of groundwater resource vulnerabilities. A point pollution source (P)-related land-use pattern (L) that represents contamination impacts was considered an additional new DRASTIC parameter. The study’s findings reveal the high reliability and maximum effectiveness of the new DRASTIC-LP model in assessing groundwater vulnerability and contamination-risk areas under a climate change scenario (by MIROC-ESM-CHEM model under RCP.8.5 scenario) and land-use pattern changes (by CA_Markov Chian Model) for both the current year (2020) and the next 50-year period (2021–2070). Furthermore, the new DRASTIC-LP model is employed to trace the movement of pollutants from high- to very high-risk areas based on the groundwater vulnerability and contamination-risk maps. The results highlight that waste disposal dumping sites pose a more critical distribution and movement of pollutants when compared to industrial sites. Additionally, unconsolidated aquifers and cracked consolidated rock aquifers show a potentially higher occurrence of pollutant distribution and movement when compared to consolidated aquifers. Consequently, the study’s outcomes are applied to formulate guidelines for the management and control of groundwater resource contamination. These guidelines serve as valuable tools for decision makers, aiding in pollution prevention and the effective management of contamination risks in groundwater resources.

Groundwater vulnerability mapping of hyper-humid urban aquifers for an improved water management in African megacities, opportunities and limitations in the case of Douala (Cameroon)

Groundwater vulnerability mapping of hyper-humid urban aquifers for an improved water management in African megacities, opportunities and limitations in the case of Douala (Cameroon)

Hydro-chemical based assessment of groundwater vulnerability in the Holocene multi-aquifers of Ganges delta

Determining the degree of high groundwater arsenic (As) and fluoride (F−) risk is crucial for successful groundwater management and protection of public health, as elevated contamination in groundwater poses a risk to the environment and human health. It is a fact that several non-point sources of pollutants contaminate the groundwater of the multi-aquifers of the Ganges delta. This study used logistic regression (LR), random forest (RF) and artificial neural network (ANN) machine learning algorithm to evaluate groundwater vulnerability in the Holocene multi-layered aquifers of Ganges delta, which is part of the Indo-Bangladesh region. Fifteen hydro-chemical data were used for modelling purposes and sophisticated statistical tests were carried out to check the dataset regarding their dependent relationships. ANN performed best with an AUC of 0.902 in the validation dataset and prepared a groundwater vulnerability map accordingly. The spatial distribution of the vulnerability map indicates that eastern and some isolated south-eastern and central middle portions are very vulnerable in terms of As and F− concentration. The overall prediction demonstrates that 29% of the areal coverage of the Ganges delta is very vulnerable to As and F− contents. Finally, this study discusses major contamination categories, rising security issues, and problems related to groundwater quality globally. Henceforth, groundwater quality monitoring must be significantly improved to successfully detect and reduce hazards to groundwater from past, present, and future contamination.

Groundwater Vulnerability Mapping Using the Susceptibility Index (SI) Method and Tritium Isotopes: A Case Study of the Gharb Aquifer in Northwestern Morocco

The Gharb aquifer plays a critical role as a source of drinking water and irrigation in Morocco. However, rapid economic growth and increased use of chemical fertilizers have led to groundwater pollution and land degradation. To address this issue, a vulnerability assessment was conducted using the Susceptibility Index (SI) method. Five parameters including depth to groundwater, effective recharge, slope, soil type, and land use/land cover were considered to evaluate groundwater vulnerability. The vulnerability assessment revealed index values ranging from 31 to 160. The study area was categorized into three zones of relative vulnerability (low, moderate, and high). Spatial analysis demonstrated significant spatial heterogeneity, with moderate vulnerability observed in areas characterized by shallow groundwater and composed primarily of sandstones in the northwest and southwest regions. In the entire study area, the low, medium, and high vulnerability zones covered 3%, 70%, and 26% (101 km2, 2725 km2, and 986 km2), respectively. Furthermore, Tritium isotope analysis and nitrate content were selected and applied as pollution markers to confirm and validate the obtained vulnerability map. The Tritium (3H) content in groundwater reveals a correlation with an R2 value of 0.86 with the degree of vulnerability, while the nitrate concentration in the aquifer’s groundwater showed a correlation with an R2 value of 0.55.

GIS based Groundwater Vulnerability Assessment of Lahore a Metropolitan using Modified DRASTIC Model

The metropolitans of the developing countries are experiencing the hazard of low quality drinking water. Lahore, the heart of Pakistan, has over 12 million population and is going to face the shortage of clean drinking water. The study was designed to create a groundwater vulnerability map of Lahore using modified DRASTIC model. The water table, land use/cover, hydraulic conductivity, vadose zone, soil and aquifer media layers of Lahore aquifer were analyzed using ‘geostatistical analyst’ and ‘spatial analyst’ extensions of ArcGIS software to compute the groundwater vulnerability. The Vulnerability index of modified DRASTIC model ranged from 64 – 144. The spatial variability of modified DRASTIC index were divided into 4 categories, namely, Low, Moderate, High and Very High groundwater vulnerable zones. The modified DRASTIC model revealed that 51.38% areas have low vulnerability, 36.77% areas have moderate vulnerability, 9.48% areas have high vulnerability and 2.37% areas have very high vulnerability to groundwater pollution. The ‘high’ and ‘very high’ vulnerability classes were found in the western parts of Lahore. The results of modified DRASTIC model were validated using the groundwater contamination data of arsenic in the study area. The groundwater arsenic concentrations map also showed higher values in the northwestern parts while in the eastern parts of the study area, the arsenic concentrations had a decreasing trend. In Ravi Town, the arsenic concentrations were positively correlated with modified DRASTIC vulnerability index and inversely correlated with water table depth (p < 0.01). It is recommended that the arsenic removal plants should be installed at all the tubewells with higher arsenic levels (arsenic concentration > 50 ppb) to provide safe drinking water to the citizens of Lahore. It is recommended that the modified DRASTIC model based on geospatial techniques can be applied on other metropolitans of the world for taking preventive measures against massive water pollution.

Modelling Groundwater Vulnerability to Contamination using DRASTIC Model through Geospatial Techniques over Northern Kwazulu-Natal, South Africa

This study models groundwater vulnerability to contamination in three northern district municipalities (Amajuba, Zululand and Umkhanyakude) in KwaZulu Natal province in South Africa using GIS-based DRASTIC model. The method considers seven parameters: depth to water table (D), recharge (R), aquifer media (A), soil media (S), topography (T), impact of the vadose zone (I), and hydraulic conductivity (C). DRASTIC parameter maps are generated in ArcGIS environment and relevant weights assigned. A weighted overlay analysis is then employed to generate the groundwater vulnerability map for the study area. Finally, the groundwater vulnerability map is combined with land use/cover to obtain groundwater pollution risk map. Results indicate that 22, 45, 21 and 12% of the total area are under low, moderate, high, and very high groundwater contamination vulnerable zones, respectively. Low, moderate, high, and very high groundwater pollution risk are found in 23, 40, 27 and 10% of the total area, respectively. These results can be used by environmental managers, spatial planers and other policy makers in formulating integrated and sustainable development plans to ensure optimal groundwater exploitation and conservation in the northern KwaZulu Natal region.

A comparison of methods for assessing groundwater vulnerability in karst aquifers: the case study of Terminio Mt. aquifer (Southern Italy)

The assessment of groundwater vulnerability to pollution is becoming even more important all over the world due to the increase of impacts of human activities on groundwater resources and the related risks to the human health, economics, and the environment. Owing to the variability of methods known for estimating groundwater vulnerability, basically depending on hydrogeological parameters considered and the scale of analysis, the comparison of results of different methods appears straightforward for identifying the best approach in a given hydrogeological condition and reference scale. In such a view, this work attempts to assess the groundwater vulnerability of the Terminio Mt. karst aquifer, by applying four different groundwater vulnerability methods, index-based, and comparing results in order to identify the best performing one in karst environments. The study aquifer, located in the Picentini Mts Regional Park (Campania region, southern Italy) represents a strategic drinking water resource since Roman times and hosts massive groundwater resources which outflow mainly from tapped basal and subordinately perched springs.The peculiar characters of the study karst aquifer, which favour direct infiltration and groundwater recharge processes, as well as the occurrence of industrial, agricultural and grazing activities, make it very vulnerable to groundwater pollution, thus requiring a proper and careful territorial management.Beside the most frequently and generally used methods for assessing groundwater vulnerability, such as the DRASTIC and SINTACS, also DAC and COP methods specifically designed for karst aquifers were applied and mutually compared. Results of SINTACS, DRASTIC and DAC methods show groundwater vulnerability maps of the Terminio Mt. karst aquifer as chiefly characterized by two classes of intrinsic groundwater vulnerability, varying between the medium and high degrees. Furthermore, high and extremely high values of groundwater vulnerability were found in areas controlled by the shallow depth of the water-table. Instead, the COP method resulted as the most effective in identifying the endorheic areas and the related karst morphologies as very high groundwater vulnerability zones, therefore the most suitable in capturing specific hydrogeological features of karst areas that control groundwater pollution and vulnerability.Results obtained will support decision tools aimed at the land use planning and protection of karst aquifers from pollution in karst areas.

Groundwater vulnerability assessment in central Iran: Integration of GIS-based DRASTIC model and a machine learning approach

The study try to evaluate the susceptibility of groundwater. The DRASTIC model was implemented through GIS. Various input variables, such as water table depth, net recharge, aquifer and soil media, topography, vadose zone impact, and hydraulic conductivity, were evaluated within the model to generate a groundwater vulnerability map. Subsequently, machine-learning algorithms (SVM, RF, and GLM) employed using the SDM package in R software to optimize the DRASTIC method. To assess the performance of groundwater pollution risk models, training and validation datasets were evaluated using the ROC curve. The results revealed that approximately 40% of the study area fell within the high vulnerability range, while around 30% exhibited moderate pollution risk. Evaluation of the machine learning models indicated their effectiveness in model development. The RF model demonstrated the highest predictive power, achieving an AUC of 0.98. Additionally, the GLM and SVM algorithms achieved AUC values of approximately 76%. These algorithms can serve as efficient techniques for evaluating and managing groundwater resources. The findings underscored relatively poor groundwater quality in the study area, with excessive aquifer exploitation by the agricultural sector and infiltration of urban sewage and industrial waste identified as the primary causes of groundwater pollution. The implications of these findings are crucial for devising strategies and implementing preventive measures to mitigate water resource vulnerability and associated health risks in central Iran.

Regional characterization of the vulnerability of the unconfined groundwaters in Bulgaria

Groundwater vulnerability to contaminant infiltration from the surface, and to state deterioration, is related to the spatial distribution of rocks with diverse porosities, flow characteristics and unsaturated zone thickness. For the present regional assessment of groundwater vulnerability, it is considered most appropriate to adopt a method based on spatial differences in the geological and tectonic, and related hydrogeological, conditions in Bulgaria. The objective of the present study is to compile a vulnerability map of the unconfined groundwater in the country. This groundwater type is very important for drinking water supply, and it is at the highest risk of contamination. The groundwater on the territory of the Republic of Bulgaria has been divided into seven vulnerability classes, based on the corresponding hydrogeological units. The map is based on the geological map of Bulgaria in scale 1:100 000. It shows that groundwater is of low vulnerability over a large part of the country’s area (57%). Medium to medium-high groundwater vulnerability is defined for approximately 31% of the total area, while high and very high vulnerability are defined for 7% and 5%, correspondingly.

Groundwater vulnerability assessment of typical covered karst areas in northern China based on an improved COPK method

Karst in China is characterized by a wide distribution, diverse forms, well-developed features, and excellent preservation, making it a representative example on a global scale. The semi-arid karst in northern China, widely distributed in many provinces, has unique hydrogeological features, including covered karst, weak karst development, thick aquifers, highly interconnected fissure network, and numerous karst springs, making it difficult to directly apply the COP method which is widely used in karst groundwater vulnerability assessment in this area. Additionally, the quality of the karst groundwater in many northern China cities is facing a threat in recent years, making it urgent to evaluate the vulnerability of the karst groundwater. This study aims to develop an improved COPK method for the covered karst groundwater vulnerability assessment modified from the widely used COP method, and to use it in the Baotu Spring basin in Jinan City, as a typical representative of the covered karst area in northern China. The assessment result by the improved COPK method shows that most of the study area exhibits moderate to low karst groundwater vulnerability, and the area with very high to high vulnerability is situated in the Middle Ordovician-Upper Cambrian Chaomidian Formation limestone exposed area. The above results by the improved COPK method are more consistent with the hydrogeological conditions than those by the original COP method. A comparison of nitrate contamination map to the groundwater vulnerability map reveals the more efficient performance of the improved COPK method compared to the original COP method in vulnerability assessment of the typical covered karst areas in northern China. This paper can provide a reference for karst groundwater vulnerability assessment of covered karst areas in northern China, as well as other countries and regions with similar hydrogeological conditions, which can provide valuable support for groundwater pollution control efforts.

Groundwater vulnerability assessment to pollution using GIS-based DRASTIC and GOD methods in Araihazar upazila of Narayanganj district, Bangladesh

A groundwater vulnerability map is a preliminary way to assess the risk of groundwater pollution from a variety of sources and across a range of geological and hydrological contexts. With rapid urbanization and industrialization, the possibility of groundwater contamination has greatly increased in Bangladesh. The focus of this study is on an industrialized peri-urban area in Bangladesh, where the regional aquifer has already been depressurized owing to pumping to fulfill the ascending municipal and industrial water demand of the Dhaka megacity and adjacent areas. Two vulnerability index maps were created utilizing a Geographic Information System (GIS) and the contamination risk indices DRASTIC (Depth to water table (D), Net recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of vadose zone (I) and hydraulic Conductivity of the aquifer (C)) and GOD (Groundwater or hydraulic confinement in the aquifer under consideration (G), Overlying strata in terms of lithological characters that determine the pollutant attenuation capacity (O) and Depth to groundwater (D)). Vulnerabilities varied greatly over the study area. The DRASTIC analysis identified three vulnerability classes: one-fifth of the area exhibited high vulnerability, more than half of the study area showed moderate vulnerability and rest of the area is low in vulnerability. In contrast, GOD analysis was somewhat conservative, showed two classes where vulnerability was negligible in 58% of the study area and low in the rest of the area. The study also generated hot-spot maps of potential surface contamination for each vulnerability map by overlapping the potentially hazardous activity layer which corresponds to areas with higher industrial clusters. Human activities that commonly cause groundwater pollution need to be constrained by utilizing groundwater protection strategies in the identified vulnerable areas to ensure sustainable development.

Modeling assessment of groundwater vulnerability to contamination risk in a typical basement terrain using TOPSIS-entropy developed vulnerability data mining technique

This study involved a comparative analysis in the groundwater vulnerability domain, which is a crucial component of groundwater management decision support systems (DSS). This was achieved by creating models that covered the range of algorithms from the subjective to the data-driven. The study was conducted in a basement complex area. Databases of climatic, remote sensing, and geophysical datasets were created using varieties of data acquisition techniques. The datasets included in this assessment were: rainfall (R), land use (LU), bedrock topography (BT), recharge rate (Re), and slope (S). The slope and rainfall were determined to have the highest (0.78) and lowest (0.01) weighted factors, respectively, using the entropy method. For the development of the TOPSIS-Entropy model algorithm, the weights results were combined with the TOPSIS outranking method. To generate the Groundwater Vulnerability Model map of the study area, the hybrid model was applied to griddled raster layers of the factors. Also, the TOPSIS and Entropy-WLA model algorithms were also explored and used to generate groundwater vulnerability maps. The TOPSIS-Entropy algorithms produced an accuracy of 70%, while TOPSIS and Entropy-WLA produced accuracy of 50 and 47%, respectively. The resulting model maps were validated by using correlation technique on the produced map and the longitudinal conductance map of the study area. The TOPSIS-Entropy, which followed an object-oriented model pattern, demonstrates greater accuracy and has the potential to provide appropriate insights and alternatives to decision-making in the field of groundwater hydrology in the study area and other regions of the world with comparable geology.

Groundwater vulnerability assessment for drinking water suitability using Fuzzy Shannon Entropy model in a semi-arid river basin

Groundwater protection against geogenic and anthropogenic diffuse pollutants are of preeminent importance for convoying groundwater-dependent hydro-aquatic ecosystems and safeguarding human health by securing a safe and sustainable water security plan. Mapping groundwater vulnerability to pollution represents a topical area of research where traditional models suffer from inherent prejudices. A novel approach to identify groundwater vulnerable zones is thus presented in this study by combining Fuzzy Shannon Entropy (FSE) with a decision support algorithm to replace DRASTIC, GOD and other related methods. We proposed a contemporary “FSE-GVI″ framework for assessing aquifer vulnerability, which for the first time expands and redesigns the seven original geological and hydrogeological parameters with geochemical and anthropogenic factors. Applying such technique weights of 13 geo-environmental and hydrogeological factors (slope, soil, pH, recharge), and anthropogenic factors (land use land cover, population density, groundwater based schemes for irrigation) has been optimized. The computed map has been categorized into very high (10.82%), high (23.20%), moderate (29.29%), low (25.02%) and very low (11.64%).The groundwater of the river basin is rated on a scale of excellent, good, poor, very poor and unfit for consumption. The model is compared to 74 groundwater quality data, and the findings demonstrate an excellent correlation between water quality index (r = 0.84), Total dissolve solids (70%), iron (72%), hardness (85%) and alkalinity levels (75%).The findings of the research reveals 27.3 % of the sampling sites (villages) under poor water quality and 23.21% of very high vulnerable zone which requires competent planning, development, managerial technique to safeguard groundwater resources.

Using appropriate Kappa statistic in evaluating inter-rater reliability. Short communication on “Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques”

In this article, some misuses of Kappa statistic in the original paper [Chemosphere, 307, 135831] are discussed. By using DRASTIC and Analytic Hierarchy Process (AHP) models, the authors have assessed the groundwater vulnerability of Totko, India. High nitrate concentrations in groundwater have been found in highly vulnerable areas, and the accuracy of the models has been assessed through Pearson's correlation coefficient and Kappa coefficient. However, using Cohen's Kappa to estimate the intra-rater reliabilities (IRRs) of the two models is not appropriate on the condition of ordinal categorical variables in five categories in the original paper. We briefly introduce the Kappa statistic and propose to use weighted Kappa to compute IRRs under such conditions. To conclude, we recognize that this does not significantly alter the conclusions of the original paper, but it is necessary to ensure that the appropriate statistical tools are used.

Assessment of groundwater vulnerability by applying the improved DRASTIC model: a case in Guyuan City, Ningxia, China

Groundwater is the main source of production and living in most arid and semi-arid areas, and it plays an increasingly critical role in achieving local urban development. There is a serious issue regarding the contradiction between urban development and groundwater protection. In this study, we used three different models to assess the groundwater vulnerability of Guyuan City, including DRASTIC model, analytical hierarchy process-DRASTIC model (AHP-DRASTIC) and variable weight theory-DRASTIC model (VW-DRASTIC). The groundwater vulnerability index (GVI) of the study area was calculated in ArcGIS. Based on the magnitude of GVI, the groundwater vulnerability was classified into five classes: very high, high, medium, low, and very low using the natural breakpoint method, and the groundwater vulnerability map (GVM) of the study area was drawn. In order to validate the accuracy of groundwater vulnerability, the Spearman correlation coefficient was used, and the results showed that the VW-DRASTIC model performed best among the three models (ρ=0.83). The improved VW-DRASTIC model shows that the variable weight model effectively improves the accuracy of the DRASTIC model, which is more suitable for the study area. Finally, based on the results of GVM combined with the distribution of F- and urban development planning, suggestions were proposed for further sustainable groundwater management. This study provides a scientific basis for groundwater management in Guyuan City, which can be an example for similar areas, particularly in arid and semi-arid areas.