Assessment Of Groundwater Resources Research Articles

Deciphering natural and anthropogenic effects on the groundwater chemistry of Nago City, Okinawa Island, Japan

A qualitative assessment of groundwater resources is significant in islands that largely depend on individual aquifers. In Okinawa Island, Japan, limestone aquifers are valuable groundwater reservoirs. However, these aquifers are sensitive to contamination due to high permeability in the conduit network. Although human activity has increased in recent decades, there remains insufficient hydrological information to assess the impact of anthropogenic loading on groundwater quality in Okinawa Island. To address this, we analyzed 4 seepage, 16 river, and 14 shallow (<10 m in depth) groundwater samples to obtain baseline chemistry and anthropogenic impact information on groundwater resources in central Nago City, northern Okinawa Island. We divided the region into three landscape units: lowland (<30 m asl), eastern, and western areas. Except for a limited number of water samples collected in the eastern mountain and coastal section of the lowland, the hydrochemistry was characterized by Ca–HCO3 type, indicating carbonate weathering within limestone-bearing lithology and Quaternary deposits. Divergent water 87Sr/86Sr values (0.707723–0.712102) with lower Sr concentrations (0.1–1.6 μmol/L) in the mountains and convergent values (0.708859–0.709184) with higher Sr concentrations (0.3–17.6 μmol/L) in the lowland suggest that the water–rock interactions in the lowland aquifer composed of Quaternary deposits are mostly responsible for the hydrochemistry of groundwater resources. The local meteoric water line (δD = 6.38 δ18O + 3.36) indicated that the water originates from precipitation, the altitude effect, and evaporation. The δ15N and δ18O in NO3− indicated the addition of manure and septic waste in the lowland aquifer. The results imply that detecting source areas of anthropogenic NO3− prior to serious groundwater pollution is important (regardless of the NO3− concentration), and isotope analyses would aid in developing appropriate action plans to mitigate or prevent future water pollution by NO3− in island regions.

Coupled controls of the infiltration of rivers, urban activities and carbonate on trace elements in a karst groundwater system from Guiyang, Southwest China

Hydrogeochemical processes of trace elements (TEs) are of considerable significance to river water and groundwater resource assessment and utilization in the karst region. Therefore, seven TEs were analyzed to investigate their contents, spatial variations, sources, and controlling factors in Guiyang, a typical karst urban area in southwest China. The results showed that the average content of TEs in river water (e.g., As = 1.44 ± 0.47 μg/L andCo = 0.15 ± 0.06 μg/L) was higher than that of groundwater (e.g., As = 0.51 ± 0.42 μg/L andCo = 0.09 ± 0.05 μg/L). The types of groundwater samples were dominated by Ca/Mg-HCO3 and Ca/Mg-Cl types, while those of the river water samples were Ca-Cl and Ca/Mg-Cl types. Principal component analysis (PCA) and correlation analysis (CA) analyses indicated that As and Mn in the groundwater of the study area were related to river infiltration. The end-member analysis further revealed that river infiltration (As = 0.86–1.81 μg/L, Cl/SO42- = 0.62–0.89) and urban activities (As = 0.21–0.32 μg/L, Cl/SO42- = 0.51–0.89) were two main controlling factors of TEs (e.g., As, Co, and Mn) in the study area. In addition, the ion ratios in river and groundwater samples indicated that the weathering of carbonates was also an important control on the hydrogeochemistry of TEs (e.g., Fe and Mn) in Guiyang waters. This study showed that the trace element (TE) contents of groundwater in the Guiyang area were greatly associated with urban input and river recharge, and provided a new perspective for understanding the geochemical behavior of TEs in urban surface and groundwater bodies, which will help the protection of groundwater in the karst areas of southwest China.

Exploration of groundwater potential zones mapping for hard rock region in the Jakham river basin using geospatial techniques and aquifer parameters

Geospatial techniques are useful to understand the groundwater resources assessment, development, and management. Groundwater mapping is essential to counter the excessive withdrawal of groundwater and fulfil the need of drinking, irrigation water in hard rock areas. Currently, the main problem is facing the groundwater level is decreasing due to less rainfall, climate changes and increasing demand, which is under in the hot zones. This results can be more useful for future challenges, sustainable development and demand to Jakham river basin. The main objective of this paper to demarcated the groundwater potential zones (GWPZ) using geospatial techniques for the hard rock region with the reference of aquifer parameters. In this paper, we have used to total eight thematic layers such as geomorphology, land use, soil, topographic elevation, slope, post-monsoon groundwater level (GWL), net recharge, and transmissivity, which are prepared from satellite data and field verification. All thematic layers were integrated for assigning the weights to demarcation of the groundwater potential zones in the RS and GIS environment. The selected thematic layers and features were assigned weightage and normalized by the analytic hierarchy process (AHP) technique. Finally, the thematic layers were systematically integrated using weighted overlay analysis within a GIS environment. We have classified into five GWPZ classes i.e. very high, high, moderate, low, and very low for basin area using GIS, and AHP methods. The study area result indicated that high and moderate zone, which is confined in the central part of the basin, covers 2.43 % and 43.88 % area, respectively. The low (49.21 %) and very low (4.25%) GW potential zone is under the confined aquifer in the high slope and rock outcrops formations near the basin boundary. The final GWPZ map was validated with groundwater level fluctuation data, which illustrates the accuracy of the adopted approach. This unique approach and conclusions of this work may also help to develop the framework and policies for swiftly analyzing groundwater recharge planning, development and locating the artificial recharge structures in the other semi-arid, arid and hard rock regions.

Evaluating potential groundwater recharge in the unsteady state for deep-rooted afforestation in deep loess deposits

Groundwater recharge reduces due to high transpiration from shallow-rooted to deep-rooted afforestation. However, reaching a steady state in recharge process is challenging and no methods are available for assessing potential groundwater recharge under unsteady state. Hence, this study developed a new method to quantify groundwater recharge in the unsteady state by (1) calculating the water age (A2) at maximum root depth (D2) for deep-rooted afforestation using the chloride accumulative age method; (2) determining the soil depth (D1) corresponding to A2 under shallow-rooted vegetation using the multi-year average pore water velocity multiplied by A2; (3) calculating the reduction in groundwater recharge (∆R) from shallow- to deep-rooted afforestation as the depth difference multiplied by the average water content between D1 and D2, divided by stand age. The average groundwater recharge for deep-rooted afforestation is equal to the average annual groundwater recharge under shallow-rooted vegetation minus ∆R. Soil cores with >25 m soil profiles below four land-use types of Hippophae rhamnoides Linn. (H. rhamnoides), Platycladus orientalis (L.) Franco (P. orientalis), Robinia pseudoacacia L. (R. pseudoacacia), and grassland were collected to measure soil water content, root distribution, and chloride and tritium contents. The results revealed that: (1) maximum root depths were 11.0 ± 0.5, 20.2 ± 1.2, and 22.6 ± 0.8 m, with soil water deficits of 373.48, 823.65, and 1847.92 mm under H. rhamnoides, P. orientalis, and R. pseudoacacia, respectively; (2) groundwater recharge following land-use change has not reached a steady state; (3) an average annual groundwater recharge was 89.12 mm yr−1 under grassland, amounting to 16 % of the average annual precipitation; deep-rooted afforestation did not significantly differ, with 83.55, 84.91, and 85.65 mm yr−1 under H. rhamnoides, P. orientalis, and R. pseudoacacia, respectively. This study contributes to a rational assessment of groundwater resources under unsteady state during land-use change.

Evaluating the contribution of satellite-derived evapotranspiration in the calibration of numerical groundwater models in remote zones using the EEFlux tool

Assessment of groundwater resources is crucial for developing water management practices for its sustainable exploitation, both for current and future needs. Numerical models are useful tools for such purpose. However, the lack of continuous monitoring networks, mainly due to difficult access to some remote locations, poses a challenge in developing and calibrating groundwater models. Remote sensing offers an alternative for acquiring information on hydrological and climatic variables at multiple spatiotemporal scales that has the potential to strengthen groundwater modeling. The aim of this study is to develop a methodology that uses remote sensing products to support model calibration. With this aim, we used the Parameter Estimation software (PEST) to calibrate a hydrogeological model of an unexploited basin located in the arid Chilean Altiplano using observed groundwater levels and evapotranspiration (ET) derived from the Earth Engine Evapotranspiration Flux (EEFlux) tool as observations. Our results show that the best model calibration is achieved using both EEFlux-ET and heads as observations to calibrate the hydraulic properties (normalized root mean square error = 4.1 %). We analyzed the effect of EEFlux-ET on the calibration of these properties and found a direct effect on specific yield parameters, which regulate the fluctuations of the water table over time. Incorporating EEFlux-ET estimates in the calibration resulted in lower values of specific yield across the aquifer. Therefore, incorporating remotely sensed ET as observations in the calibration of the groundwater model contributes to a better simulation of the spatiotemporal head variations in the basin.

Groundwater potential mapping based on long time series remote sensing data in Penghu Islands, China

AbstractIslands are special bodies of land surrounded by seawater. Many islands are facing water shortages as the demand for groundwater increases, thus, highlighting the importance and urgency of the assessment, planning, and management of island groundwater resources. To facilitate the same, the groundwater potential of the Penghu Islands in China was assessed for the first time using remote sensing (RS), geographic information system (GIS), and the analytic hierarchy process (AHP). Long‐term series remote sensing studies were also conducted to monitor the dynamic change in groundwater potential and to identify groundwater potential areas. In this study, the geological environment factors were normalized, and their weight was allocated based on the AHP of RS and GIS. The groundwater potential assessment (GPA) index, established using the weighted comprehensive algorithm, was used to analyse groundwater potential and demarcate groundwater potential zones. Finally, the trend in the spatio‐temporal variation of groundwater potential was analysed using long‐term series remote sensing data. The results from 2015 to 2021 showed that the Penghu Islands can be divided into five groundwater potential zones of different grades, such as 6.3%–8.1% of grade I, 22.2%–24.2% of grade II, 23%–24.4% of grade III, 19.6%–21% of grade IV, and 25.1%–25.5% of grade V. The results of the GPA were verified by comparing them with the abundance of water‐content rock formation in hydrogeologic maps, which yielded correlation coefficients of 78.3%–88.9%. Overall, the groundwater potential zones of different grades in the study area tended to be stable all year‐round, including the zones of grades I and II. The results of this study highlighted the reliability of predicting groundwater potential based on long‐term series remote sensing data and its usability to local personnel in appropriate groundwater resource planning and management.

Role of Snowpack-Hydrometeorological Sensors for Hydrogeological System Comprehension inside an Alpine Closed-Basin.

Groundwater resource assessment and forecasting in mountain areas requires the monitoring of two conditions, local meteorological conditions, and springs’ groundwater parameters. The reliability of the monitoring data and conditions are linked to the technical instrumentation, multiparametric probes, and sensors. This paper presents a set of attractive tools and sensors for springs’ groundwater resource monitoring and assessment in mountain basins. Data from the combination of weather station sensors with spring flow-rate instruments, installed in the alpine Mascognaz basin, can guarantee an entire understanding of how one set of parameters can affect other results, defining consequential cause-and-effect relationships. Since a large part of the Alpine groundwater bodies are exploited for drinking purposes, understanding the evolution of their rechange processes requires making the right economic and instrumental investments aimed at using them according to forecast predictions and sustainable development goals.

A stochastic, daily time-step model for conjunctive water use at local authority level

South Africa has a broadly developed water resource infrastructure, based mainly on surface water, localised groundwater, and limited desalination. The Department of Water and Sanitation projects that increasing requirements will exceed the capacity of the country's bulk water supply systems by 2025. To mitigate water scarcity at a local authority level, more conjunctive water use solutions need to be investigated. A Microsoft Excel 2016 model, estimating supply capacity on a daily basis, was developed for local authorities to better manage their water supply systems. The model utilises synthetically generated stochastic streamflow sequences, based on historical data. Monthly streamflow is disaggregated into daily streamflow and a rainfall-runoff relationship is established to produce synthetic rainfall sequences. Groundwater is modelled using an approach similar to the Aquifer Firm Yield Model. Recharge percentages (rainfall data) are obtained from the Groundwater Resource Assessment Phase 2 project. The Cooper-Jacob model evaluates borehole drawdowns and their effect on surrounding boreholes. Desalination and water reclamation are modelled as one source. The model evaluates and compares the historical, as well as stochastic available yield of a conjunctive use water supply system, for different operational scenarios. The water supply system of Stellenbosch was used as a case study to illustrate the model's functionality.

Development and application of hybrid artificial intelligence models for groundwater potential mapping and assessment

Groundwater potential assessment is essential for optimum utilization and recharge of groundwater resources for the proper development and management of an area. The main aim of this study is to develop an accurate groundwater potential map of the Dak Nong Province (Vietnam) using hybrid artificial intelligence models, which are a combination of Random Forest (RF) and its Ensemble Framework (AdaBoost - ABRF, Bagging - BRF and LogitBoost - LBRF). In this study, twelve conditioning factors, namely topography (aspect, elevation, Topographic Wetness Index - TWI, slope, and curvature), hydrology (infiltration and river density, rainfall, Sediment Transport Index - STI, Stream Power Index - SPI), land use, and soil were used to develop the models. Well, yield data was also utilized to develop and validate potential groundwater zones.&#x0D; One Rule (R) feature selection method was utilized to prioritize the importance of groundwater potential affecting parameters. The results indicated that the Average Merit (AM) of the rainfall factor was the highest (68.039), and river density was the lowest (53,969). Performance evaluation of ML models was done using standard statistical indicators, including Area Under the Receiver Operating Characteristic (ROC) curve (AUC). The results showed that all the four models performed well in the training (AUC ≥ 0.967) and testing (AUC ≥ 0.734) phases, but the performance of the ABRF (AUC=0.992) model is the best in the training phase, whereas LBRF is the best in the testing phase (AUC=0.776). The present model study would be helpful in the proper groundwater potential assessment and management of groundwater resources for sustainable development.

Assessment of Groundwater Resources and Its Sustainability in the St. Martin’s Island, Bangladesh

The St. Martin’s Island, the only offshore coral island in Bangladesh depends on solely groundwater for domestic uses. This study finds that groundwater occurs between 1m and 7m depths within four different aquifer lobes distributed throughout the island. These lobes are formed by deposition of beach sands within bedrock depression and are completely isolated from the influence of sea water. The model simulated groundwater budget for one of the lobes suggests that 11% of total dynamic reserve is used for water supply to local inhabitants and seasonal tourists and the rest is lost due to evapotranspiration and seepage along the boundary of the aquifer. The chemically suitable quality of potable groundwater prevails throughout the island but presence of Escherichia coli in the groundwater samples of the island possesses a great health threat. E. coli is found in 58% and 44% of the groundwater samples during dry and wet season, respectively. The unplanned construction of resorts and their septic tanks within the aquifer are responsible for the pathogenic contamination of groundwater in the St. Martin’s Island. Although currently there is no threat of seawater intrusion, the rise of sea level over the bedrock barrier and storm surge inundation may destroy this resource in near future. The Dhaka University Journal of Earth and Environmental Sciences, Centennial Special Volume June 2022: 63-72

Three-Dimensional Hierarchical Hydrogeological Static Modeling for Groundwater Resource Assessment: A Case Study in the Eastern Henan Plain, China

Groundwater is closely related to hydrogeological structure and hydro-lithology, which mainly refers to the spatial distributions and properties of the environment where groundwater occurs. To analyze the constraints of hydrogeological structure and hydro-lithology on regional groundwater resources in the Eastern Henan Plain, China, we reconstructed the three-dimensional (3D) hierarchical models at two scales, hydrogeological structural models and hydro-lithological models, using hydrogeological cross-sections. First, the hydrogeological structural models of four aquifer groups, corresponding to four formations of the Quaternary in the study area, were reconstructed. Second, the hierarchical hydro-lithological model was built using SIS and IK estimation under the constraint of each aquifer group model space, respectively. Compared to global model, the variograms of hierarchical model captured more spatial characteristics of lithology in each aquifer group. The IK hierarchical model presents more continuities, clear boundaries, and realistic geometric shapes of the three lithologies, excluding the banding characteristics of the IK global model. The hierarchical SIS models reproduced the lithology distribution of each aquifer group and captured small changes in the lithology, with the smallest absolute percentage errors (APEs). Third, coupling the SIS hierarchical models and the groundwater levels, the groundwater resource in the study area was estimated to have a total volume of 1.2339 × 104 m3. The shallow groundwater in the study area is mainly concentrated in Hebi City and the Puyang basin of the Yellow River, and deep groundwater is mainly concentrated in the northern Anyang City and Hebi City. Finally, the possible quantities of shallow and deep groundwater recharges were estimated for future groundwater management decision in the study area. The hierarchical hydrogeological model, groundwater resource assessment, and possible groundwater recharge estimation can also provide a basis for groundwater vulnerability, groundwater extraction, and land subsidence assessment.

Geochemical and multivariate assessment of groundwater resources of churachandpur sub-division of Manipur, India

Hydrogeochemical and multivariate assessment of groundwater samples of the Churachandpur sub-division of the state of Manipur was carried out to study its suitability for potable and irrigational uses. The study extensively discusses the underlying hydro-geochemistry using multivariate geostatistical tools for physicochemical parameters of 35 spatially distributed groundwater samples during pre- and post-monsoon seasons. In situ parameters (pH, TDS, DO, EC, salinity, ORP) were assessed in field conditions, and it was found that few samples exceed concentration than the prescribed standards. Both positive and negative ORP values and low DO levels of the samples indicate oxidizing and reducing aquifers due to recent unstable geologic formations. Although the concentration of Cl−, SO42−, and NO3− is well within desirable levels, the concentration of F− and As3+ of a few samples exceeds the prescribed standard. The water quality index of the groundwater samples signifies that more than 50% of samples are unsuitable for potable uses for both seasons. The geochemical analysis indicates that most of the water is Ca–Mg–Cl–HCO3 type followed by Mg–Ca–Cl–HCO3 types in both the seasons and dominated by the rock-weathering geochemical process. Multivariate analysis and geostatistical mapping highlight the spatial variability of water quality parameters and possibilities of the occurrence of geogenic contaminants in the aquifers of the study area.

Aquifer exploitation potential at a riverbank filtration site based on spatiotemporal variations in riverbed hydraulic conductivity

Study regionA riparian zone within the Songhua River Basin in Northeast China, characterized by a continental monsoon semi-humid climate. Study focusRiver infiltration is an important part of groundwater recharge at riverbank filtration (RBF) sites and largely depends on the riverbed hydraulic conductivity (RHC). The influence of river scouring and deposition on RHC is not completely clear, resulting in calculation inaccuracies in the rate of river water infiltration to the aquifer. Thus, the study determined the relationship between RHC and sediment particle size using stepwise regression analysis and a genetic algorithm. A hydrodynamic and sediment transport model (Delft3D) was used to simulate the spatial distribution of sediment particle sizes. A numerical groundwater flow model was also established, using Visual MODFLOW, in which the river boundary was generalized into a third type of boundary condition, and RHC zoning was performed to improve the accuracy of the simulation. New hydrological insightsThe findings showed that accurate prediction of RHC is essential for the assessment of groundwater resources in riparian zones. This is crucial for RBF managers, as they will be able to adjust the pumping rate according to the hydrological conditions of the river to either access more water resources in wet years or avoid a series of ecological and geological problems caused by excessive groundwater exploitation in dry years.

Geo-Environmental Approaches for the Analysis and Assessment of Groundwater Resources at the Catchment Scale

Groundwater resources constitute nearly one-third of the globe’s freshwater resources [...]

Groundwater Level Modeling with Machine Learning: A Systematic Review and Meta-Analysis

Groundwater is a vital source of freshwater, supporting the livelihood of over two billion people worldwide. The quantitative assessment of groundwater resources is critical for sustainable management of this strained resource, particularly as climate warming, population growth, and socioeconomic development further press the water resources. Rapid growth in the availability of a plethora of in-situ and remotely sensed data alongside advancements in data-driven methods and machine learning offer immense opportunities for an improved assessment of groundwater resources at the local to global levels. This systematic review documents the advancements in this field and evaluates the accuracy of various models, following the protocol developed by the Center for Evidence-Based Conservation. A total of 197 original peer-reviewed articles from 2010–2020 and from 28 countries that employ regression machine learning algorithms for groundwater monitoring or prediction are analyzed and their results are aggregated through a meta-analysis. Our analysis points to the capability of machine learning models to monitor/predict different characteristics of groundwater resources effectively and efficiently. Modeling the groundwater level is the most popular application of machine learning models, and the groundwater level in previous time steps is the most employed input data. The feed-forward artificial neural network is the most employed and accurate model, although the model performance does not exhibit a striking dependence on the model choice, but rather the information content of the input variables. Around 10–12 years of data are required to develop an acceptable machine learning model with a monthly temporal resolution. Finally, advances in machine and deep learning algorithms and computational advancements to merge them with physics-based models offer unprecedented opportunities to employ new information, e.g., InSAR data, for increased spatiotemporal resolution and accuracy of groundwater monitoring and prediction.

An integrated geochemical and spatiotemporal assessment of groundwater resources within an industrial suburb, Southeastern Nigeria

An integrated geochemical and spatiotemporal assessment of groundwater resources within an industrial suburb, Southeastern Nigeria

Groundwater Suitability for Drinking and Irrigation Using Water Quality Indices and Multivariate Modeling in Makkah Al-Mukarramah Province, Saudi Arabia

Water shortage and quality are major issues in many places, particularly arid and semi-arid regions such as Makkah Al-Mukarramah province, Saudi Arabia. The current work was conducted to examine the geochemical mechanisms influencing the chemistry of groundwater and assess groundwater resources through several water quality indices (WQIs), GIS methods, and the partial least squares regression model (PLSR). For that, 59 groundwater wells were tested for different physical and chemical parameters using conventional analytical procedures. The results showed that the average content of ions was as follows: Na+ &gt; Ca2+ &gt; Mg 2+ &gt; K+ and Cl− &gt; SO42− &gt; HCO32− &gt; NO3− &gt; CO3−. Under the stress of evaporation and saltwater intrusion associated with the reverse ion exchange process, the predominant hydrochemical facies were Ca-HCO3, Na-Cl, mixed Ca-Mg-Cl-SO4, and Na-Ca-HCO3. The drinking water quality index (DWQI) has indicated that only 5% of the wells were categorized under good to excellent for drinking while the majority (95%) were poor to unsuitable for drinking, and required appropriate treatment. Furthermore, the irrigation water quality index (IWQI) has indicated that 45.5% of the wells were classified under high to severe restriction for agriculture, and can be utilized only for high salt tolerant plants. The majority (54.5%) were deemed moderate to no restriction for irrigation, with no toxicity concern for most plants. Agriculture indicators such as total dissolved solids (TDS), potential salinity (PS), sodium absorption ratio (SAR), and residual sodium carbonate (RSC) had mean values of 2572.30, 33.32, 4.84, and −21.14, respectively. However, the quality of the groundwater in the study area improves with increased rainfall and thus recharging the Quaternary aquifer. The PLSR models, which are based on physicochemical characteristics, have been shown to be the most efficient as alternative techniques for determining the six WQIs. For instance, the PLSR models of all IWQs had determination coefficients values of R2 ranging between 0.848 and 0.999 in the Cal., and between 0.848 and 0.999 in the Val. datasets, and had model accuracy varying from 0.824 to 0.999 in the Cal., and from 0.817 to 0.989 in the Val. datasets. In conclusion, the combination of physicochemical parameters, WQIs, and multivariate modeling with statistical analysis and GIS tools is a successful and adaptable methodology that provides a comprehensive picture of groundwater quality and governing mechanisms.

Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model

It is an effective measure to estimate groundwater storage anomalies (GWSA) by combining Gravity Recovery and Climate Experiment (GRACE) data and hydrological models. However, GWSA results based on a single hydrological model and GRACE data may have greater uncertainties, and it is difficult to verify in some regions where in situ groundwater-level measurements are limited. First, to solve this problem, a groundwater weighted fusion model (GWFM) is presented, based on the extended triple collocation (ETC) method. Second, the Shiyang River Basin (SYRB) is taken as an example, and in situ groundwater-level measurements are used to evaluate the performance of the GWFM. The comparison indicates that the correlation coefficient (CC) and Nash-Sutcliffe efficiency coefficient (NSE) are increased by 9–40% and 23–657%, respectively, relative to the original results. Moreover, the root mean squared error (RMSE) is reduced by 9–28%, which verifies the superiority of the GWFM. Third, the spatiotemporal distribution and influencing factors of GWSA in the Hexi Corridor (HC) are comprehensively analyzed during the period between 2003 and 2016. The results show that GWSA decline, with a trend of −2.37 ± 0.38 mm/yr from 2003 to 2010, and the downward trend after 2011 (−0.46 ± 1.35 mm/yr) slow down significantly compared to 2003–2010. The spatial distribution obtained by the GWFM is more reliable compared to the arithmetic average results, and GWFM-based GWSA fully retain the advantages of different models, especially in the southeastern part of the SYRB. Additionally, a simple index is used to evaluate the contributions of climatic factors and human factors to groundwater storage (GWS) in the HC and its different subregions. The index indicates that climate factors occupy a dominant position in the SLRB and SYRB, while human factors have a significant impact on GWS in the Heihe River Basin (HRB). This study can provide suggestions for the management and assessments of groundwater resources in some arid regions.

Assessment of groundwater resources in the process of creating a set of maps of hydrogeological subject at a scale of 1 : 200 000 for the Chelyabinsk region

Assessment of groundwater resources in the process of creating a set of maps of hydrogeological subject at a scale of 1 : 200 000 for the Chelyabinsk region

Assessment of Groundwater and Surface-Water Resources of Gushkara in Purba Bardhaman (West Bengal, India) using the Water Quality Index

Survival of life on earth indispensably depends on water. Population explosion and its consequences resulted in the usable water sources being unusable in many regions. Regular monitoring of water quality becomes necessary to protect public health. The present study aimed to evaluate the water quality status of various water resources of Gushkara (West Bengal, India). The result showed that the status of the water quality index (WQI) of the studied surface-water sources is ‘poor’ or ‘very poor’ (ranges 50.582 - 87.969) whereas the groundwater and municipal water supply are rather safer (ranges 15.804 - 36.210). There is also an indication of faecal coliform contamination in surface-water sites. Overall water quality is better in winter than other two seasons. Some parameters in surface-water crossed the recommended level while some reached near that level. So immediate attention is necessary to rectify the situation.