Tool For Groundwater Management Research Articles

Development and Application of a New Exponential Model for Hydraulic Conductivity with Depth of Rock Mass

Hydraulic conductivity generally decreases with depth in the Earth’s crust. The hydraulic conductivity–depth relationship has been assessed through mathematical models, enabling predictions of hydraulic conductivity in depths beyond the reach of direct measurements. However, it is observed that beyond a certain depth, hydraulic conductivity tends to stabilize; this phenomenon cannot be effectively characterized by the previous models. Thus, these models may make inaccurate predictions at deeper depths. In this work, we introduce an innovative exponential model to effectively assess the conductivity–depth relationship, particularly addressing the stabilization at greater depths. This model, in comparison with an earlier power-like model, has been applied to a globally sourced dataset encompassing a range of lithologies and geological structures. Results reveal that the proposed exponential model outperforms the power-like model in correctly representing the stabilized conductivity, and it well captures the fast stabilization effect of multiple datasets. Further, the proposed model has been utilized to analyze three distinct groups of datasets, revealing how lithology, geological stabilization, and faults impact the conductivity–depth relationship. The hydraulic conductivity decays to the residual hydraulic conductivity in the order (fast to slow): metamorphic rocks, sandstones, igneous rock, mudstones. The mean hydraulic conductivity in stable regions is roughly an order of magnitude lower than unstable regions. The faults showcase a dual role in both promoting and inhibiting hydraulic conductivity. The new exponential model has been successfully applied to a dataset from a specific engineering site to make predictions, demonstrating its practical usage. In the future, this model may serve as a potential tool for groundwater management, geothermal energy collection, pollutant transport, and other engineering projects.

Groundwater pricing strategies for Indian cities - a case of Kanpur

ABSTRACT In the cities of the Indo-Gangetic basin, over the years, urban residents have been relying on groundwater due to its universal availability and reliability clubbed with inadequate municipal water supply. The study aims at using groundwater pricing as a tool for groundwater management in Indian cities giving due importance to the spatial dynamics of groundwater resources. It focuses on Kanpur city, where half the city depends directly on groundwater resources for meeting their requirements, making the aquifers susceptible to low yield and facing the risk of irreversible over-exploitation in the coming future. Spatial analysis using Geographical Information System (GIS) has been carried out for economic evaluation of the resource by assessing the criticality of groundwater resources. This is further incorporated into a differential pricing structure with an aim to curb over-exploitation. We have also proposed specific pricing strategies that are better suited and easily implementable in Kanpur city.

Decision Support System for Sustainable Exploitation of the Eocene Aquifer in the West Bank, Palestine

Groundwater is a crucial resource for water supply and irrigation in many parts of the world, especially in the Middle East. The Eocene aquifer, located in the northern part of the West Bank, Palestine, is threatened by unsustainable groundwater abstractions and on-ground pollution. Analysis and management of this aquifer are challenging because of limited data availability. This research contributes to the long-term sustainability of the aquifer by model-based design of future abstraction strategies considered within an uncertainty analysis framework. The methodology employed started with development of a single-layer steady-state MODFLOW groundwater model of the area, followed by uncertainty analysis of model parameters using Monte Carlo simulations. The same model was afterwards coupled with a Successive Linear Programming (SLP) optimization algorithm, implemented in the Groundwater Management tool (GWM) of the United States Geological Survey (USGS). The purpose of optimization was deriving five optimal abstraction strategies, each aiming to maximize groundwater abstraction, subject to different constraints regarding groundwater depletion. Given the uncertainty of model parameters, the sensitivity and reliability of these optimal strategies were then tested. Sensitivity was checked for two optimal strategies by performing re-optimization with different values of uncertain model parameters (one at a time). Reliability of the five strategies was tested by analyzing the extent of constraints’ violation for each strategy when varying the uncertain parameters using Monte Carlo simulations. Finally, the model was used for determining capture zones of wells for the five optimal abstraction strategies, land-use in these capture zones, and the associated estimates of on-ground nitrogen loading. The developed strategies were then deployed in a web-based decision support application (named Groundwater Decision Support System—GDSS), together with other relevant information. Users can analyze results of different optimal strategies in terms of groundwater level variations and total water balance results, and test consequences of uncertain parameters. Capture zones of wells for different abstraction strategies, together with land-use and on-ground nitrogen loading in these capture zones, are also presented. Results show that critical uncertain parameters are recharge, hydraulic conductivity, and conductance at key boundary condition locations. Optimal abstraction strategies results indicate that an increase in total abstractions could be between 5% and 20% from the current level (estimated at about 56 × 106 m3/year, which is about 74% of estimated annual recharge). The uncertain parameters, however, are impacting the sensitivity and the reliability of the optimal strategies to variable degrees. Recharge and hydraulic conductivity are the most critical uncertain parameters regarding sensitivity of the optimal strategies, while reliability is also impacted by the level of abstraction proposed in a given strategy (number, locations, and abstraction rates of new wells). The main novelty and contribution of this research is in combining modelling, uncertainty analysis, and optimization techniques in a comprehensive decision support system for the area of the Eocene aquifer, characterized with limited data availability.

Buffer zone-based trace elements indicating the impact of human activities on karst urban groundwater

The tanglesome allocation of landscape types at various spatial dimensions is an important component influencing the quality of groundwater environment in karst cities. Trace elements can be used as indicators of the extent of impact on groundwater which is an effective means of tracing groundwater contamination. In this study, we studied the influence of landscape patterns on trace elements in groundwater of typical karst cities in Southwest China (Guiyang City) on a multi-spatial scale by using multivariate statistical analysis. According to the sampling points, buffer zone scales with different radii (500 m, 1000 m, 1500 m, and 4000 m) were established to quantify the land use model. There are suburban and urban differences in trace element content. The city center has higher levels of trace elements compared to suburban areas, especially Li, Ni, Tl, Cu, Sr, Co, As, and Mn. In addition, the outcomes of the multiple linear regression had shown that the size effect of the association from landscape pattern to trace elements varies with different indicators and parameters. The results of redundancy analysis showed an overall change in trace elements was better interpreted by the landscape pattern of the 1500 m-scale buffer. At the same time, at the 1500 m scale, Ni, Tl, Cu, Co, As, Cr, Sr, Li, and Mn were positively correlated with the urban landscape index (4LPI, 4LSI), influenced by urban anthropogenic activities, while Cd, Zn, and Pb were positively correlated with the cropland landscape index (1AI, 1LPI), influenced by agricultural activities. This study indicates that trace elements are a reliable indicator for tracing groundwater contamination. The buffer zone can reflect the extent of urban impacts on groundwater and provide a new and effective analytical tool for groundwater management.

Predicting Groundwater Level Using Climate Change Scenarios in the Southern Part of Mali

Groundwater is mainly demanded in all the activities for the population of the southern part especially in the Koda catchment, the studied area. These resources are affected by various factors especially climate change. Therefore, knowing the impact of projected climate change on groundwater recharge is an important issue for water resources management, especially for those responsible for the Koda catchment. In this work, the impact of climate change on groundwater resources in the study area in Mali, West Africa is investigated. The Hydrogeological modeling was performed using the Gardenia model, and the monthly precipitation and temperature data were used as the Baseline. These data considered the past 30-year period (1987-2016) and the projections for the next 30 years (2021-2050). Projected precipitation and air temperatures, extracted from the Rossby Centre regional Atmospheric climate model (RCA 4) statistically downscaled from the GCM-IHEC-EC-EARTH and the GCM-MPI-M-MPI-ESM-LR under the Representative Concentration Pathways RCP 4.5 and RCP 8.5 and corrected with the Multiscale Quantile Mapping bias correction method, were used as input data to the gardenia model. Potential evapotranspiration (PET) values estimated from Blaney Criddle method and groundwater levels measured in three piezometers were used to calibrate the Gardenia model. The outputs display the reduction of groundwater level in the three piezometers in the Koda catchment for all the two Regional Climate Models (RCMs) during the periods of rainy season from July to October. From the results of GCM IHEC-EC-EARTH, the projected decline in GWL reaches 1.09 m for the RCP 4.5 and it up to 1.26 m for the RCP 8.5 in the study area while the GCM MPI-M-MPI-ESM-LR presentes the decline in groundwater level (GWL) during winter season from about 0.62 m for the RCP 4.5 up to 1.93 m for the RCP 8:5. Both RCMs project a reduction trend of groundwater recharge over time. It is noticeable that this decline is greater in RCP8.5 for all the three piezometers. The results also show that the average groundwater recharge (90 mm) in the future (2021-2050) is lower (180 mm) than that of the current drought (1987-2016), which could lead to severe drought events. The projected impacts of climate change would have a significant impact on groundwater in the period of 2029-2039; this situation could have a negative impact the socioeconomic activities especially on agriculture, which depends on water resources. The results will help also to take some adaptation measures to climate change, the famers could have a possibility to know the period of groundwater recharge where they have more water infiltration therefore, where to seek crops that need less or more water. The study area presents numerous potential of groundwater, the results could be a tool for groundwater management and to determine the favorable sites to implant new boreholes.

A Modified GALDIT Method to Assess Groundwater Vulnerability to Salinization—Application to Rhodope Coastal Aquifer (North Greece)

Aquifer overexploitation in coastal aquifers has led to seawater intrusion that causes severe salinization effects on the groundwater system. The most widespread method for assessing groundwater vulnerability to seawater intrusion, the dominant cause of salinization in coastal aquifers, is the GALDIT method, with numerous applications globally. The present study proposes a modified version of the GALDIT method (GALDIT-Ι) to evaluate the vulnerability of salinization, including its potential additional sources. Both methods have been applied to Rhodope coastal aquifer, an intensively cultivated agricultural area subject to multiple salinization sources. The basic modifications of the proposed GALDIT-I method include different weighting factors and modification of classes for critical parameters, the use of a different indicator (TDS) for the estimation of the Impact factor and, overall, the address of the concept of groundwater salinization instead of seawater intrusion only. The differences in the results of the two methods were significant, as the modified version exhibited a more finite and realistic vulnerability capture, according to the area’s existing hydrogeological and hydrogeochemical knowledge. The original GALDIT method showed an area of nearly 80% as medium vulnerable with very limited spatial deviations. On the other hand, the proposed modified GALDIT method depicted high vulnerability hotspots away from the shoreline, indicating various salinity sources. The validation of the modified method showed that nearly 80% of the sampling points present very good to perfect match between the salinity assessment and the concentration of Cl−, indicating the successful validation of the method. Overall, the GALDIT-I method facilitated groundwater vulnerability assessment to salinization more accurately and exhibited a more discrete spatial assessment, thus, it could be regarded as a promising proactive tool for groundwater management and decision-making.

Improving Results of Existing Groundwater Numerical Models Using Machine Learning Techniques: A Review

This paper presents a review of papers specifically focused on the use of both numerical and machine learning methods for groundwater level modelling. In the reviewed papers, machine learning models (also called data-driven models) are used to improve the prediction or speed process of existing numerical modelling. When long runtimes inhibit the use of numerical models, machine learning models can be a valid alternative, capable of reducing the time for model development and calibration without sacrificing accuracy of detail in groundwater level forecasting. The results of this review highlight that machine learning models do not offer a complete representation of the physical system, such as flux estimates or total water balance and, thus, cannot be used to substitute numerical models in large study areas; however, they are affordable tools to improve predictions at specific observation wells. Numerical and machine learning models can be successfully used as complementary to each other as a powerful groundwater management tool. The machine learning techniques can be used to improve calibration of numerical models, whereas results of numerical models allow us to understand the physical system and select proper input variables for machine learning models. Machine learning models can be integrated in decision-making processes when rapid and effective solutions for groundwater management need to be considered. Finally, machine learning models are computationally efficient tools to correct head error prediction of numerical models.

Groundwater Modeling: A Tool for Groundwater Management to Support Urban Water Supply and Food Security

Faisalabad is the 3rd largest city of Pakistan where underlying aquifer mostly contains saline water. Heavy population of the city needs huge quantity of fresh water. Water requirements for the existing Faisalabad city are being met by installation of well-fields along Jhang Branch canal, where groundwater is fresh. The increasing population pressure requires more water and identify more suitable sites for installation of well-field on sustainable basis. It was deemed imperative to elevate the existing well field. The MODFLOW, a numerical groundwater model developed by United States Geological Survey (USGS) for simulation and future prediction of aquifer behavior in response to pumping by various well fields was developed, calibrated and validated satisfactorily. A groundwater decomposition approach was also developed to tune various coefficients used in estimation of inflow and outflow components of groundwater system. The calibrated model was used to predict the future response of aquifer under different scenarios of pumping by existing and future/proposed wellfields. Calibrated flow model revealed that a sink has already been developed at the center of existing well-field of Water and Sanitation Agency (WASA) due to excessive pumpage. Future predictions of model indicate that there is no conspicuous change in regional groundwater flow pattern, even with all the existing tubewells remain in operation. However, the sink in the WASA well field area further deepens, and flow gradients become comparatively steep showing increase in groundwater flow velocity. Depth to watertable has already increased from 12 m in 2005 to 16 m in 2011 in the critical area of WASA well field. Model has predicted that this depth will further increase to 24 m in 2018. It has also been observed that groundwater quality along the river is fresh and becomes saline towards Faisalabad city. Due to pumpage in the freshwater zone model predicts that saline water will rush towards well fields deteriorating the quality of fresh water along Jhang Branch Canal. Therefore, it has been suggested that site for further pumping should be moved towards upstream of Jhang Branch Canal at least up to RD 180-187 and possibly on right side of the canal instead of left side

Simplifying the Groundwater Model Interface to Provide Enhanced Decision Support

AbstractGroundwater modeling can be made more accessible to stakeholders and water managers through interface tools that prepare model inputs and create graphical outputs. An application of this improved modeling technique is presented here, where a model interface tool, called the Groundwater Management Tool (GMT) was developed for the widely used MODFLOW model. The GMT facilitates the evaluation of various water use scenarios for those who have limited time for and/or experience in modifying groundwater model inputs and outputs, yet who need the complexity of a three‐dimensional numerical groundwater model to adequately represent the hydrologic system of interest. The impacts of new pumping wells and altered pumping regimes in existing wells are easily explored through the current version of this interface tool. The modeling technique employed by the GMT provides water managers with the ability to efficiently leverage the decision‐support power and confidence provided by a calibrated groundwater model without the time‐consuming processing of model input and output files, and thereby increases the value and utility provided by the model in supporting water resource management decisions. The purpose of this Technical Note is to highlight an improved modeling approach by combining the power of FloPy with the widely used Microsoft Excel software, to quickly utilize the power of an existing MODFLOW model.

Feasibility of farm-scale infiltration galleries for managed aquifer recharge in an agricultural alluvial aquifer of Northeast Arkansas

Agriculture-heavy alluvial aquifer regions around the world have experienced severe groundwater declines due to irrigation demand. This consequence has been observed in the United States in the latter half of the 20th century, notably in the Central Valley of California and in the Mississippi River Valley. In some portions of the Mississippi River Valley, such as the Cache River Critical Groundwater Area (CRCGA) of northeast Arkansas, drawdown has exceeded 30 m and portends aquifer depletion in the near future. In addition to adopting surface-water storage and irrigation efficiency methods, farm-scale managed aquifer recharge (MAR) with infiltration galleries (IG), gravel-filled trenches designed to move surface water into the aquifer, may be a useful tool for reducing declines. Low-permeability surface deposits, which limit and create significant variation in natural recharge across the region, also control the placement of MAR systems. It is therefore critical to understand the variability of surface deposits, as well as underlying aquifer properties, to best plan the placement, design, and operation of such systems. This study aimed to characterize surface and upper aquifer conditions to assess the feasibility of IG in the central CRCGA. Available well logs were used to interpolate the approximate thickness of surface deposits and identify thinner areas. Approximately 37% of the study area has less than 5 m of confining material at the surface and included 28 existing reservoirs that could act as recharge water sources. Guided by this mapping effort, geophysical and sediment surveys were conducted at selected sites. The upper unsaturated alluvial aquifer of fine silty-sand had estimated hydraulic conductivities of 0.20–2.79 m d−1. These results are promising for the implementation of farm-scale IG in the study region and suggest that small MAR systems could be a useful tool for groundwater management in other agricultural aquifer systems given the proper placement.

Differences and similarities between precipitation patterns of different climates

In recent years water-related issues are increasing globally, some researchers even argue that the global hydrological cycle is accelerating, while the number of meteorological extremities is growing. With the help of large number of available measured data, these changes can be examined with advanced mathematical methods. In the outlined research we were able to collect long precipitation datasets from two different climatical regions, one sample area being Ecuador, the other one being Kenya. Using the methodology of spectral analysis based on the discrete Fourier-transformation, several deterministic components were calculated locally in the otherwise stochastic time series, while by the comparison of the results, also with previous calculations from Hungary, several global precipitation cycles were defined in the time interval between 1980 and 2019. The results of these calculations, the described local, regional, and global precipitation cycles can be a helpful tool for groundwater management, as precipitation is the major resource of groundwater recharge, as well as with the help of these deterministic cycles, precipitation forecasts can be delivered for the areas.

Spatial mapping for Groundwater Vulnerability to Pollution Risk Assessment Using DRASTIC Model in Ponnaiyar River Basin, South India


 
 
 Groundwater is the principle source of drinking water and protection of groundwater quality is an important issue meets out the increasing population and agricultural practices. The present research an attempt made to develop DRASTIC model to understand the groundwater contamination risk in Ponnaiyar River Basin (PRB), Tamil Nadu, India using geographical information system (GIS). GIS have been shown to be useful tools for assessing groundwater pollution hazard. According to Central Ground Water Board reports the PRB categorized by semi-critical groundwater development. In view of the extensive reliance on this basin, contamination of PRB groundwater became an alarming issue. To assess groundwater contamination risk in the PRB the parameters such as Groundwater depth, Net recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and Hydraulic conductivity were selected. Based on the importance of groundwater contamination all the parameters were assigned to rank and weights. Then all the themes were integrated and classified into five categories such as very low (9.33%), low (26.54%), moderate (34.77%), high (22.38%) and very high (6.98) risk. To validate the DRASTIC model, nitrate concentration was selected and found that it is 81.53% accurate which reflects that, DRASTIC model is appropriate to understand groundwater pollution risk assessment. In the GSB groundwater is contaminated mainly due to extensive use of groundwater extraction for agriculture purpose. Groundwater risk index assessment is an effective tool for groundwater management in the PRB.
 
 

Modeling groundwater flow under chaotic urbanization constraints in Kinshasa Capital Region (D.R. Congo)

Groundwater is used as an alternative source of drinking water in the chaotically urbanized African mega city of Kinshasa (DR Congo). However, groundwater abstraction without proper management leads to aquifers mining. The main objective of this study was to better understand the regional groundwater flow regime and to build a groundwater management tool for an area of 2187.36 km2 using Visual MODFLOW Flex. The model's input data were collected from various databases of national agencies and companies in charge of water engineering and management. Large scale steady-state and transient regional model was set up for the period 2000–2014, calibrated and validated to optimize groundwater development scenarios. The recharge in the area is estimated at an average of 236.21 mm/yr and is high in the southwest and less in paved areas and sandy-clayey soils in the east. The calibrated model had Nash-Sutcliffe Efficiency (NSE) coefficient of 0.9 and correlation coefficient of 0.98 and 0.96 for the steady-state and transient state, respectively. The accuracy of the calculated ground water levels was also judged by standard error of estimation which was 0.24 m and root mean squared of 16.8 m. The results for the three (3) scenarios from the baseline, which comprised increasing pumping rates by 10, 25 and 50%, indicated a further decrease in groundwater levels by 0.05m, 0.076m and 0.12 m, respectively. The modeled groundwater flow indicated that the flow direction for the whole study area is mainly from highlands towards lowlands, heading north, where the Congo River is located.

Simulation of the Water Table Elevation in Shallow Unconfined Aquifers by means of the ERA5 Soil Moisture Dataset: The Umbria Region Case Study

AbstractThis paper concerns the simulation of the water table elevation in shallow unconfined aquifers where infiltration is assumed as the main mechanism of recharge. The main aim is to provide a reliable tool for groundwater management that satisfies water supply managers. Such a tool is a candidate as a physically based alternative to the use of empirical methods or general circulation models. It is based on the use of two widely available sets of data: the water table elevation measurements and soil moisture time series. In fact, the former are usually provided by government agencies on public websites whereas the latter are included in the atmospheric global datasets (reanalysis). It is notable that data from reanalysis are accessible to any citizen and organization around the world on an open-access basis (e.g., Copernicus). In the proposed method, the measured water table elevations are correlated quantitatively with the water fluxes toward the aquifer evaluated using the soil moisture data from ERA5 reanalysis (provided by ECMWF) within a Richards equation–based approach. The analysis is executed using data from the Umbria region (Italy) on both a daily and monthly scale. In fact, these are the time intervals of interest for a proper management of groundwater resources. The proposed relationships include both a logarithmic and linear term and point out the possible different regimes of the shallow aquifers with regard to the recharge due to infiltration. These different mechanisms reflect in the different role played by the water fluxes toward the aquifer in terms of water table elevation changes according to the considered time scale.

Analysis of spatio-temporal trend in groundwater elevation data from arsenic affected alluvial aquifers – Case study from Murshidabad district, West Bengal, Eastern India

Fluctuation in groundwater level is a time-dependent stochastic process. It is also a function of various inflow and outflow components to and from the hydrologic system concerned. Depth to water level data are measured through a network of observation wells or hydrograph stations to ascertain the degree of fluctuation in groundwater level at the desired scale, on a long-term basis. Basically, these depths to water level data are point measurements, which can be regarded as random variables furnishing changes in groundwater storage over time. The intrinsic in-homogeneity in aquifer materials introduces variations like jumps, trends, and periodicities in such hydrologic time series data. Thus, trending results from certain gradual, natural and/or anthropogenic interventions in the hydrologic environment and analyses of their trends are imperative for assessment of groundwater level scenario in the area of interest. This in turn, is essential for strategic planning and management for exploitation of the precious groundwater resource in the same area. The area of interest in this article, i.e., Murshidabad is one of the nine arsenic affected districts of West Bengal. Here, contamination persist within, shallow, arseniferous, alluvial aquifers, which are otherwise widely exploited for irrigation purposes. According to many researchers working in this area, over-exploitation of groundwater is the root cause for the plummeting water level and the widespread arsenic contamination as well. The present study intends to detect and analyze the trends persisting in the depth to water level data measured over a period from 1996 to 2016, in Murshidabad district of West Bengal, India, amidst its complex and contrasting hydrogeologic set-up and interpret the results in terms of the hydrologic attributes of the Bengal basin as a whole. The non-parametric Mann–Kendall test and the Sen’s slope estimator have been used to identify the linear trend persisting in the time series pre- and post-monsoon groundwater elevation values. The analysis indicates statistically significant decline in water level across the study area especially during the post-monsoon season. This can be attributed to the recharge–discharge disparity within the hydrologic regime; brought through intense pumping over the study area. Its ill effect being particularly observed in the western part of river Bhagirathi. Findings of such study are crucial for assessment of dynamic groundwater resources of the district and subsequently can be utilized as a decision support tool for groundwater management at micro-level.

Assessment of the Vulnerability to Agricultural Nitrate in Two Highly Diversified Environmental Settings

A significant rise of groundwater pollution has been registered worldwide, where nitrate has been recognized as the most widespread pollutant. In this context, the groundwater vulnerability assessment and more specifically the delineation of “Nitrate Vulnerable Zones” represents a reliable cost-effective tool for groundwater management. In this study, the Agricultural Nitrate Hazard Index (ANHI) method was applied to two case histories in southern Italy: the Lete River catchment and the eastern sector of the Campania Plain. The first area is characterized by agricultural activities and a low anthropic influence while the eastern part of the Campania Plain, around Caserta city, is strongly urbanized and developed on an extensive alluvial plain filled with volcaniclastic deposits. The parametric method applied suggests moderate hazard for the more natural setting highlighting how the intensive crop farming and livestock activities that characterized the area negatively influenced the results. For the eastern part of the Campania Plain, where a strong urbanization and widespread industrial crops are dominant, a low to very low hazard has been identified. The groundwater quality value, in contrast with the methodology results underlines the importance of further risk evaluations based on accurate aquifer characterization. A multiple year assessment based on land use change and climate variation could further highlights the difference between the study areas.

Solute transport model equation for mobile phase in semi-infinite porous media

An analytical solution of one-dimensional solute transport model equation for mobile phase is derived for semi-infinite heterogeneous porous media. The transport equation considers advection, longitudinal dispersion, linear isotherm, and porosity in its formulation. The dispersion is assumed to be Fickian, characterized by a constant dispersion coefficient. Temporally dependent velocity patterns are employed for the prediction of contaminant concentration. The analytical solution is compared with two reported solutions and can be used for benchmarking numerical codesand also as a preliminary predictive tool for groundwater management. Also, the obtained analytical solution of the proposed model may be helpful in the groundwater hydrology areas.

Quantification of Water Sources in a Coastal Gold Mine through an End-Member Mixing Analysis Combining Multivariate Statistical Methods

Mixing calculations have been widely applied to identify sources of groundwater recharge, but these calculations have assumed that the concentrations of end-members are well known. However, the end-members of water remain unclear and are not easily available in practical applications. To better determine end-members and mixing ratios, an end-member mixing analysis combining multivariate statistical methods was used on a large, complex water chemistry dataset collected from the Shashandao gold mine in China. Multivariate statistical methods, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were applied to determine the specific end-members (these two methods verified each other). On the basis of the identified end-members, a maximum likelihood method was then used to estimate the mixing ratios of the water sources. The combined method proposed in this study can help to identify more accurate end-members and deal with uncertainty in end-member concentrations, and it can also adjust the concentrations until the optimal mixing ratios for the calculation are obtained. This method can be a powerful tool for groundwater management and in predicting water inrush in mining operations.

Numerical groundwater flow modeling for managing the Gabes Jeffara aquifer system (Tunisia) in relation with oasis ecosystems

The Gabes Jeffara aquifer system, in southeastern Tunisia, is essentially recharged by rainfall infiltration and by groundwater inflow from the Intercalary Continental aquifer in the northwest. The increase in groundwater pumping for irrigation in recent decades has induced a serious decrease in groundwater levels, depletion of springs and degradation of oasis ecosystems. A multidisciplinary study was carried out to better understand the behavior of oasis ecosystems and aquifer systems and to provide tools and recommendations for water resources management. An important part of the study was devoted to developing a hydrodynamic flow model of the Jeffara aquifer system, which can be used as a future groundwater management tool considering different recharge or exploitation scenarios. This model was built with Processing Modflow, gathering data on geology, hydrogeology, hydrology, rainfall, piezometry, withdrawals and spring flow rates. The model was calibrated in steady state with reference to the piezometric levels measured in 1970 and in transient state for the period 1972–2014, using records from more than 200 wells and piezometers. The analysis of current and future water consumption was carried out with existing data, processed satellite images and farmer surveys. This analysis was used to define water demand scenarios combined with scenarios of decreased groundwater withdrawal, reinforced groundwater recharge and use of alternative water resources. The scenarios tested with the model show that the situation will be critical in less than 25 years without radical measures to reduce groundwater withdrawals by at least 60 MCM/year.

Assessment of Groundwater Pollution Vulnerability Using GIS-Based DRASTIC Model and its Validation Using Nitrate Concentration in Tandula Watershed, Chhattisgarh

Effective management of groundwater resources has now become a global issue and on the other hand industrialization, deforestation and agricultural activities are potential sources of groundwater pollution. Groundwater vulnerability index assessment is an effective tool for groundwater management. In this study DRASTIC model was utilized to evaluate aquifer vulnerability of Tandula watershed, Chhattisgarh, India. Aquifer vulnerability of the study area classified into five categories such as very low (18.68%), low (23.84%), moderate (16.42%), high (23.72%) and very high (17.34%) vulnerability. To validate the DRASTIC model, nitrate concentration was selected and found that it is 82.35% accurate which reflects that, DRASTIC model is appropriate to understand groundwater pollution risk assessment. In the study area groundwater is contaminated mainly due to extensive use of fertilizer for agriculture purpose. Present study will be helpful in proper management and development of available groundwater resource in the study area.