Groundwater Level Drop Research Articles

Evaluating machine learning models in predicting GRI drought indicators (case study: Ajabshir area)

Examining the condition of groundwater resources and the impact of droughts is valuable for effective water resources management. Today, machine learning (ML) models are recognized as one of the useful tools in time series predictions. In this study, the groundwater condition of one of the most important aquifers in northwest Iran was investigated using MODFLOW, followed by estimating the groundwater resource index (GRI) utilizing the multivariate adaptive regression spline (MARS) and least squares support vector regression (LSSVR) for a period between 2001 and 2019. Meteorological and hydrological drought indicators along with precipitation and flow rate were used as input variables for prediction. The simulation results revealed a groundwater level decrease since the aquifer withdrawal amount is more than the recharge amount. Besides, results showed that there is a limited interaction between surface water and groundwater resources, mainly caused by the decrease in the river flow and aquifer groundwater level drop. Both ML models performed well in GRI estimation, using groundwater flow, streamflow drought index, standardized precipitation index, and runoff as input variables. The performance of the MARS model with RMSE, MAE, and NSE error evaluation criteria of 0.37, − 0.19, and 0.83, respectively, exerted slightly better results than LSSVR with RMSE, MAE, and NSE of 0.48, − 0.06, and 0.80, respectively. The findings reveal the appropriate performance of both models in forecasting drought indicators, highlighting the necessity of using ML models in hydrology and drought prediction problems.

Risk assessment of land subsidence based on GIS in the Yongqiao area, Suzhou City, China.

This study focuses on the Yongqiao District in Suzhou City, Anhui Province, China, aiming to analyze the current situation of ground settlement and its influencing factors in the area. The selected risk indices include settlement rate, cumulative settlement amount, groundwater level drop funnel, thickness of loose sediment layer, thickness of soft soil layer, and the number of groundwater extraction layers. Additionally, vulnerability indices such as population density, building density, road traffic, and functional zoning are considered. An evaluation index system for assessing land Subsidence risk was established. The risk evaluation of land Subsidence was conducted using the Hierarchical analysis-composite index method and ArcGIS spatial analysis, The evaluation results show that the area of higher risk area is about 2.82 km2, accounting for 0.96% of the total area, mainly distributed in the area of Jiuli village, Sanba Street. The middle risk area is distributed around the higher area, with an area of about 9.18 km2, accounting for 3.13% of the total area. The lower risk areas were distributed in most of the study area, covering an area of 222.24 km2, accounting for 75.82% of the total area. The low risk assessment area is mainly distributed in Bianhe Street and part of Zhuxianzhuang Town, with an area of about 58.88 km2, accounting for 20.09% of the total area. The findings of this study are not only crucial for informing local policies and practices related to land use planning, infrastructure development, and emergency response but also enhance our understanding of the complexities of land Subsidence processes and their interactions with human activities, informing future research and practice in environmental risk assessment and management.

Sustainability analysis of single vs. multiple adaptation strategies in tackling the adverse impacts of climate change on groundwater resources using water-food-energy nexus approach

Research has shown that groundwater level has decreased in the last few decades worldwide. In future periods, due to global warming and the change in the amount and regime of precipitation, the intensity of groundwater level drop in various parts of the world will increase. This study aims to investigate both single and multiple adaptation strategies to obtain sustainable groundwater resources. At first, the system dynamics model of the Alborz province as the study area, which is located in the center of Iran and includes three aquifers, was developed considering socio-economic, hydrology, agriculture, and energy subsystems. Then, the system was calibrated during an observation period using behavior repetition and extreme conditions tests. Next, the temperature and precipitation data obtained from 16 AOGCM-AR6 models under the SSP2-4.5 scenario were downscaled in the region. The ensemble mean values of temperature and precipitation showed an increase of 1.8 °C in temperature and a 3.5% decrease in precipitation in the period of 2021–2050 compared to the 1985–2014 period. The introduction of downscaled climate scenarios to the developed system dynamics model revealed a sharp drop in the groundwater of the aquifers until 2050. Different adaptation strategies based on water demand management in the agricultural, domestic, and industrial sectors were determined for all three aquifers based on consulting with decision-makers and evaluated using the system dynamics model. Evaluating sustainability indices showed the insignificant effectiveness of each adaptation strategy individually for each aquifer. Meanwhile, the combination of adaptation strategies will not only increase the sustainability of the water systems of the region but will also cause the groundwater level of all aquifers to rise. The framework introduced in this research can be used in most surface and groundwater resource systems to determine the most efficient solutions to adapt to the effects of climate change.

A system dynamics approach for sustainable groundwater management considering climate change, inter-organizational relationships, and domestic water saving

This article uses system dynamic modeling to examine the relationship between water allocation from the Ilam dam and groundwater fluctuation, as well as the effects of climate change, changes in inter-organizational relationships, and water demand management on water allocation and groundwater level fluctuations. The results showed that agricultural water allocation has a direct effect on groundwater level fluctuations. In the first scenario, which examined the effects of climate change, the comparison of three climate change scenarios (SSP126, SSP245, and SSP585) was carried out. The results illustrated that with temperature increasing and precipitation decreasing occurred in SSP585, the groundwater drawdown increases about 0.8 m more than SSP126. The second scenario examined the effects of changes in inter-organizational relationships. Based on the results of centrality measures in the social network analysis method, it was found that the organizational power of the stakeholder organization in the agriculture sector is greater than the ones in the environment sector. This causes the allocation to the agriculture sector to be prioritized over the environment. This scenario was analyzed by assuming a change in organizational power and giving priority to the water allocation of the environmental sector. The results showed that environmental needs (maximum 0.3 MCM) were almost entirely met in the second scenario, compared to the basic scenario. Also, the decrease in agricultural water allocation has led to an increase in groundwater usage by farmers, resulting in a 20 cm drop in groundwater levels. Therefore, regarding the sustainable management of water resources, directing attention towards alternative livelihoods for farmers can contribute to environmental water rights and the remediation of aquifers. The third scenario examined the effects of water demand management. The results showed that saving 20–25% of water in the domestic sector can reduce 40–50 cm maximum groundwater drawdown which align with sustainable groundwater management.

Analysis on the spatiotemporal evolutions of groundwater hydrochemistry and water quality caused by over-extraction and seawater intrusion in eastern coastal China

The over-extraction of groundwater has resulted in seawater intrusion and the southward migration of the saltwater interface, gradually deteriorating the groundwater quality in the Weibei Plain. In this research, groundwater samples were gathered from 46 monitoring wells for shallow groundwater during the years 2006, 2011, 2016, and 2021. The hydrochemical features of regional groundwater and the factors influencing the issue were subjected to statistical analysis. Additionally, the assessment of spatiotemporal variations in groundwater quality was conducted using the customized entropy-weighted water quality index (EWQI) method. The relationship between groundwater over-extraction and the southward intrusion of the saltwater interface was compared and analyzed. The results of this paper revealed that the Weibei Plain has been in a state of long-term over-extraction of groundwater from 2000 to 2021, with an average annual over-extraction of 118.49 million m3. The groundwater depression cone areas in the northern part of the study area increased from 3,247.37 to 4,581.34 km2 from 2006 to 2021, with the center of the cone experiencing a drop in groundwater level from −22 to −85 m. The saltwater interface shifted southward by 711.71 km2 from 2006 to 2021. In groundwater, the high concentrations of TH, TDS, and Cl− were primarily related to the seawater intrusion, while higher concentrations of NO3− were mainly determined by frequent agricultural production, industrial wastewater, and domestic sewage discharges. The groundwater hydrochemical types in the study area transitioned from predominantly HCO3·Ca-Mg type in 2006 to HCO3-Na type and SO4·Cl-Ca·Mg type in 2021 due to seawater intrusion. The results of PCA and HCA show the effects of seawater intrusion, human activities, and rock weathering on groundwater hydrochemistry. The evaluation results based on the EWQI revealed that the average value of the samples in 2021 was 101.36, which belonged to Class IV water quality standards, representing the poorest water quality among the 4 years. The southward migration of the saltwater interface led to the deterioration of groundwater quality in the groundwater depression cone areas, which gradually worsened from 2006 to 2021. The maximum increase in EWQI value was 174.68 during the period, shifting from Class III water quality to Class V water quality. Groundwater quality remained relatively better in the western and southern regions which were less affected or unaffected by seawater intrusion. The results of the study can provide a certain reference value for the sustainable management of groundwater resources and the management of groundwater pollution and seawater intrusion in the Weifang City area in the future.

Nature-Based Solutions for the Restoration of Groundwater Level and Groundwater-Dependent Ecosystems in a Typical Inland Region in China

The rapid drop in groundwater level and the degradation of groundwater-dependent ecosystems (GDEs) has led to serious imbalances in the development of the socio-ecological system (SES) in Minqin Oasis, northwest China. In this study, the interactions between the elements of the SES were analyzed, and the effects of the implementation of nature-based solutions (NbS) and the resilience of the SES were assessed using the methods of linear trend analysis, correlation, and fuzzy comprehensive evaluation. The results showed that: (i) the most important contributing factor to the increase in groundwater depth (GLD) and the degradation of GDEs was the continuous groundwater extraction for the irrigation of farmland; and (ii) the natural vegetation began to be degraded when the GLD surpassed 5 m; (iii) the initial goal of NbS was achieved, the increase in GLD has been curbed, and the vegetation and the wetland area of Qingtu lake have begun to be restored. The SES resilience index increased by a factor of 1.82 from 2009 to 2017; however, it was still below 0.6, and thus the NbS should be continued in the future. This study provides a reference for the sustainable development of the SES in other similar areas under various environmental challenges.

The influence of the 2022 extreme drought on groundwater hydrodynamics in the floodplain wetland of Poyang Lake using a modeling assessment

The 2022 extreme drought in Poyang Lake (China) caused severe damage to a wide range of sectors. It also emphasized the fact that, even in regions with abundant surface water resources, groundwater resource is still a crucial component of drought management strategies. However, providing up-to-date assessments of groundwater response remains challenging due to the limited data in complex floodplain settings. This study uses a groundwater flow modeling FEFLOW to investigate the influences of the most extreme drought in 2022 on groundwater hydrology in the floodplain wetland of Poyang Lake. Model simulation indicates that the extreme drought led to a significant decrease in floodplain groundwater levels, with a maximum drop of about 5 m. In addition, the extent of the groundwater level drop varies significantly across the floodplain wetland, particularly for the strongest impact (drop > 4 m) occurring in the eastern area of the floodplain. It is expected that the extreme drought accelerates the groundwater discharge rate that is about 3 times than that of the normal year, and thus resulting in a losing condition of the floodplain wetland. On an annual scale, the groundwater discharge of the floodplain wetland in 2022 is estimated to be about 14.5 times than that of a normal year, demonstrating a significant attenuation of groundwater storage under drought environments. The reduction in rainfall combined with the associated low lake level is most likely to exert substantial influences on reduced floodplain groundwater storage. This study is the first attempt to interrogate the response of wetland groundwater to the unpredictable drought event in Poyang Lake, contributing to improved understanding of future water resources allocation and drought resistance strategy.

Assessment of drought conditions and prediction by machine learning algorithms using Standardized Precipitation Index and Standardized Water-Level Index (case study: Yazd province, Iran).

Drought as a natural phenomenon has always been a serious threat to regions with hot and dry climates. One of the major effects of drought is the drop in groundwater level. This paper focused on the SPI (Standardized Precipitation Index) and SWI (Standardized Water-Level Index) to assess meteorological and hydrological drought, respectively. In the first part, we used different time frames of SPI (3, 6, 12, and 24 months) to investigate drought in Yazd, a dry province in the center of Iran for 29 years (1990-2018). Then, in the second part, the relationship between SPI and SWI was investigated in the three aquifers of Yazd by some rain gauge stations and the closest observation wells to them. In addition to using SPI and SWI, we also used different machine learning (ML) algorithms to predict drought conditions including linear model and six non-linear models of K_Nearest_Neighbors, Gradient_Boosting, Decision_Tree, XGBoost, Random_Forest, and Neural_Net. To evaluate the accuracy of the mentioned models, three statistical indicators including Score, RMSE, and MAE were used. Based on the results of the first part, Yazd province has changed from mild wet to mild drought in terms of meteorological drought (the amount of rainfall according to SPI), and this condition can worsen due to climate change. The models used in ML showed that SPI-6 (score ave = 0.977), SPI-3 (score ave = 0.936), SPI-24 (score ave = 0.571), and SPI-12 (score ave = 0.413) indices had the highest accuracy, respectively. The models of Neural_Net (score ave = 0.964-RMSE ave = 0.020-MAE ave = 0.077) and Gradient_Boosting (score ave = 0.551-RMSE ave = 0.124-MAE ave = 0.248) had the highest and lowest accuracy in prediction of the SPI in all four-time scales. Based on the results of the second part, about the SWI, Random_Forest model (score = 0.929-RMSE = 0.052-MAE = 0.150) and model of Neural_Net (score = 0.755-RMSE = 0.235-MAE = 0.456) had the highest and lowest accuracy, respectively. Also, hydrological drought (reduction of the groundwater level) of the region has been much more severe, and according to the low correlation coefficient of average SPI and SWI (R2 = 0.14), we found that the uncontrolled pumping wells, as a main factor than a shortage of rainfall, have aggravated the hydrological drought, and this region is at risk of becoming a more arid region in the future.

Influence assessment of urban expansion on groundwater level fluctuations in Gandhinagar, Gujarat, India.

Being the state capital of Gujarat, Gandhinagar is snowballing urban population, resulting in overexploitation of groundwater resources and consequent decline in local groundwater level. The key objective of the current research is to understand the impact of urban expansion on the groundwater level of Gandhinagar district for the last 3 decades. Long-term land use/land cover (LULC) alterations using Landsat images (1991-2021) reveal a 234% increase in overall built-up area and it is more prominent in western and southern parts than the eastern part of study area till 2021 due to urban sprawl of adjacent Ahmedabad City. Spatial distribution of groundwater levels exhibits the same pattern of groundwater level drop as that of the urban expansion and the drop of maximum depth of the groundwater level has also observed during study tenure. Rapid population growth indicates inevitable urban densification which may lead to increase in groundwater abstraction and consequent groundwater level depletion of Gandhinagar City in near future. The scenario may be worsened due to the reduction in groundwater recharge area owing to enhancement of impervious surfaces. A negative correlation is established between groundwater level and respective built-up areas from 1991 to 2011. After 2001, groundwater levels in some areas showed a rising trend and the number of those locations have increased from 2001 to 2021, indicating a sufficient supply of surface water, meeting the escalating water demand and subsequent reduction in groundwater abstraction. High fluoride content was found in many groundwater samples collected from Gandhinagar's shallow unconfined aquifer. In lieu of almost unperturbed natural groundwater recharge, built-up expansion, rising population, and over-exploitation result in groundwater level depletion in both shallow and deeper aquifers. To replenish the already depleted groundwater level and for sustainable water supply, an integration of rainwater-surface water-groundwater management plan and sustainable urban management plan is highly required. The future sustainable urban-groundwater management plan of Gandhinagar City must emphasized on the expansion of green and permeable spaces for groundwater recharge, mandatory rainwater harvesting system in every building possible, suitable area demarcation for artificial recharge, and identification of areas which are less prone to groundwater level depletion for city expansion. The outcomes of the present study will help the decision-makers to prepare inclusive and resilient urban management plan to accomplish the 6th and 11th Sustainable Development Goals of United Nations by 2030.

Rate of occurrence of wood degradation in foundations and archaeological sites when groundwater levels are too low

In many places around the world, soils preserve ancient wooden elements. These are related to archaeological objects such as shipwrecks, water wells or tools, but also to piled constructions supporting buildings and waterworks. In countries like the Netherlands, a significant part of the built environment still stands on wooden piles and some have been in function for more than 600 years. For the preservation of this wood, it is essential that it remains waterlogged. Due to climate change, more and longer periods of drought are expected during which groundwater levels drop. Previously waterlogged wood that finds itself above groundwater loses its water protection as oxygen becomes available and wood degrading fungi become active. It is unclear how much time it takes before these detrimental processes start to have an effect. Therefore, to better protect buried wood, an understanding of the degradation processes under dynamic groundwater levels is needed. This includes the conditions under which the fungi become active and when these conditions occur in and around the wood. To address this complex issue, two experiments were conducted: Firstly, under optimal laboratory conditions, the rate of degradation over time by different fungal species in different wood species was determined. Subsequently, the changing conditions in and around wooden piles after lowering the groundwater level were examined in a field experiment. The latter experiment showed that the wood-soil matrix provides long-term protection against degradation. The soil types appear to be an important factor as well as the moisture content of the wood, both determining for how long the protection can be maintained. Together with the degradation speed by fungi, a risk assessment can be made for specific conditions when drought leads to loss of archaeological cultural heritage or to instability of our (monumental) buildings and structures.

Soft computing assessment of current and future groundwater resources under CMIP6 scenarios in northwestern Iran

Excessive use of water resources in combination with climate change threaten to significantly reduce groundwater in arid and semiarid regions. We studied the effects of climate change on the groundwater level for the important Dehgolan Aquifer in northwestern Iran. The water level in this aquifer has dropped by about 35 m during the last 30 years. Soft computing techniques were used together with climate projections in three methodological steps to estimate the groundwater level drop by 2045. Firstly, MODFLOW was used to simulate groundwater flow and movement. Secondly, simulation results, support vector regression (SVR), and least-squares SVR (LSSVR) machine learning models were used to predict groundwater levels for the future 20-year period (2026–2045). The whale optimization algorithm (WOA) was used to improve the prediction results by optimizing the SVR parameters. Thirdly, three climate models of CMIP6 (ACCESS-CM2, BCC-CSM2-MR, and CMCC-ESM2) were used to predict the changes in precipitation for the future period (2026–2045) using SSP 2.6 and SSP 8.5 scenarios. The results showed that the MODFLOW-LSSVR model predicted the groundwater level more accurately than MODFLOW-SVR and MODFLOW-SVR-WOA. The calculation scenario containing previous month groundwater level, monthly aquifer withdrawal, and monthly precipitation had the highest performance in predicting groundwater level with root mean square error (RMSE), mean absolute percentage error (MAPE), and Nash Sutcliffe efficiency (NSE) equal to 0.305 m, 0.014 m, and 0.998, respectively. The results indicate that precipitation may decrease in the future period for the SSP 8.5 scenario (about 6% compared to the reference period 1987–2005). This decrease, along with the continuation of the current aquifer withdrawal, will cause a drop of about 36 m (during 28 years) of the groundwater level (1.3 m per year). The results reveal that the drop could be reduced to 12 m by adopting a 25% reduction in the current aquifer withdrawal. The findings show the necessity of providing a suitable management approach to prevent future aquifer exhaustion due to the continuation of the current withdrawal situation in the region.

Disentangling Shallow Subsidence Sources by Data Assimilation in a Reclaimed Urbanized Coastal Plain, South Flevoland Polder, the Netherlands

AbstractThis research targets disentangling shallow causes of anthropogenically induced subsidence in a reclaimed and urbanized coastal plain. The study area is the city of Almere, in the South Flevoland polder, the Netherlands, which is among the countries' fastest subsiding areas. The procedure consists of integrating Interferometric Synthetic Aperture Radar (InSAR) data with high‐resolution phreatic groundwater and lithoclass models, and a database containing construction details. The InSAR data were derived from Sentinel‐1, one ascending and one descending track, over a period from March 2015 until June 2020. The two main parts of the workflow are isolation of the InSAR points of structures without a pile foundation and a data assimilation procedure. The shrinkage of surficial clay beds by phreatic groundwater level lowering is identified as the main cause of subsidence in the area, with an average contribution of 6 mm per year. The history‐matched physics‐based model predicts that 1 m drop in phreatic groundwater level now translates into 10 mm of subsidence in the next 5 years. Additionally, a groundwater deficiency due to severe dry periods should be considered as an accelerator of subsidence. To ensure a robust network to estimate subsidence, we recommend a consistent monitoring strategy of the phreatic groundwater level.

Characterization and Productivity of Alluvial Aquifers in Sustainability Oasis Areas: A Case Study of the Tata Watershed (Southeast Morocco)

Groundwater from alluvial aquifers is a critical source of water supply for rural agriculture, particularly in semi-arid and arid regions. Effective management of these aquifers requires an understanding of the factors that influence their water resources. In this study, we present a case study of the Tata watershed in southeastern Morocco, where the economy is heavily dependent on agriculture and relies exclusively on groundwater. We demonstrate the importance of integrating geological, hydrogeological, and geophysical methods to characterize the aquifer and evaluate groundwater productivity. Analysis of 64 data wells tapping into the aquifer revealed significant disparities in flow yields, ranging from 0.05 to 15.50 L per second. The highest yields were found between depths of 12 and 43 m, which correspond to the alluvium and the altered and fractured part of its substrate. The maximum alluvial thickness of 57 m was determined using geo-electrical prospecting. A piezometric map was created to define the recharge zones, which correspond to the lateral contributions of the bordering Georgian limestones, and infiltration of both rain and surface water along the Tata wadi. Since 1987, there has been a continuous drop in groundwater level, which can be attributed to the increase in irrigated areas following financial incentives provided by the Moroccan government to the agricultural sector. A proposal has been made for the construction of a recharge dam to enable the recharge of the alluvial aquifer. This development is expected to serve a dual purpose by mitigating the deleterious impacts of flooding and facilitating the gradual water infiltration of the alluvial aquifer. This case study provides insights into the hydrodynamics of the aquifer and establishes a simplified model of its functioning. These findings have important implications for the management of alluvial aquifers in similar regions.

A Hybrid Coupled Model for Groundwater-Level Simulation and Prediction: A Case Study of Yancheng City in Eastern China

The over-exploitation of groundwater has led to a significant drop in groundwater levels, which may lead to a series of geological disasters and ecological environmental problems such as ground subsidence and ground cracks. Therefore, through studying the dynamic change characteristics of groundwater, we can grasp the dynamic changes in groundwater level over time and invert the hydrogeological parameters, which provides an important basis for the management of groundwater resources. In this study, the confined aquifer III groundwater between 2005 and 2014 in Yancheng City was selected as the research object, and the Back Propagation (BP) neural network, Spatial-temporal Auto Regressive and Moving Average (STARMA) model, and BP-STARMA model were used to predict the spatial and temporal evolution trends of groundwater. In order to compare the prediction effectiveness of the BP-STARMA model, the fitting and prediction accuracies of the three models were measured from the perspectives of time and space. The results of the Relative Squared Error (RSE), Normal Mean Squared Error (NMSE), Root-Mean-Squared Error (RMSE), and Mean Absolute Error (MAE) were used to assess the robustness of the BP-STARMA model. The results showed that the fitting of the RMSE of BP-STARMA model was reduced by 39.92%, 38.35%, 30.25%, 31.55%, and 13.57% compared with the STARMA model, and by 22.2%, 8.7%, 15.9%, 28.5%, and 4.42% compared with the BP neural network model, respectively. Collectively, this shows that the BP-STARMA model has a better spatiotemporal prediction of groundwater level than the STARMA and BP neural network models, is more applicable to spatially continuous time-discrete spatiotemporal sequences, and is more applicable to spatiotemporal sequences that respond to natural geographic phenomena.

Peatland groundwater level in the Indonesian maritime continent as an alert for El Niño and moderate positive Indian Ocean dipole events

In general, it is known that extreme climatic conditions such as El Niño and positive Indian Ocean Dipole (IOD+) cause prolonged drought in Indonesia's tropical peatlands so that groundwater levels (GWL) drop and peat is prone to fire. However, 27 years of GWL measurements in Central Kalimantan peat forests show the opposite condition, where the lowest GWL occurs several weeks before El Niño and after IOD+ reaches its peaks. We show that the dropped sea surface temperature anomaly induced by anomalously easterly winds along the southern Java-Sumatra occurs several weeks before the GWL drop to the lowest value. Local rainfall decreased, and GWL dropped sharply by 1.0 to 1.5 m, during the super El Niño events in 1997/98 and 2015, as well as remarkable events of IOD+ in 2019. It is suggested that the tropical peatland ecohydrological system (represented by the GWL), El Niño Southern Oscillation (ENSO), and IOD+ are teleconnected. Hence, monitoring GWL variability of peatland over the IMC is a possibility an alert for extreme climate events associated with El Niño and/or moderate IOD+.

Evolution of salinity in the Gaza Strip over the last five decades deduced from field data

Gaza coastal aquifer has been exposed to severe overexploitation to meet the human needs for water supply. This exploitation has resulted in lowering of the groundwater level to by more than 15 m below mean sea level in the south and around 5 m in the north. Groundwater level drop has exposed the aquifer to seawater intrusion and inland saline upconing in the central south and south-east of the Gaza Strip.We developed five cross sections based on wells drilled over the past five decades representing aquifer stratigraphy in the five governorates (North, Gaza, Deir El Balah, Khan Younis and Rafah) of the Gaza Strip. Those cross sections have been used to map the chloride concentration over the past five decades (years 1972, 1980, 1990, 2000, 2010, 2017 and 2021).The results show three main sources of aquifer salinity: (1) seawater intrusion, (2) lateral inflow from Eocene rocks in the east and/or from agricultural return flow as a result of using treated wastewater for irrigation in Israel close to the eastern border and (3) upconing due to fossil marine salt water trapped at the bottom of the aquifer. The clay layers which are subdividing the aquifer have caused a difference in sub-aquifer level chloride difference. Before the year 2000, the public water supply wells were placed far away from the sea and no seawater intrusion was noticed especially in the south of Gaza Strip (Khan Younis and Rafah governorates), while afterwards public water supply wells appeared within 2 km from the Mediterranean Sea. From then on, seawater intrusion has been taking place due to heavy groundwater abstraction. Also, lateral inflow with chloride concentrations of more than 1,000 mg/l is well noticed during the different years, related to eastern inflow from Eocene rock formation where the coastal aquifer rests directly on it, 10–15 km from the coast. Inland areas with high chloride contents were observed as a result of upconing from deep saline groundwater. Cumulative Distribution Function (CDF) curves were created for all wells in each cross section and showed a remarkable shrinkage of freshwater percentage in the aquifer.

Application of the gleization soil layer to assess centurial drops in shallow groundwater levels across the southeastern coast of China

Groundwater is a critical resource for global sustainable development, but it is often poorly monitored and managed. The gleization soil layer is the Critical Zone between the pedosphere and underground hydrosphere. It records the groundwater table fluctuation for an extended period, providing an ideal opportunity to evaluate shallow groundwater level dynamics. The present work applies the gleization soil layer to explore centurial changes and the complex interactions of factors affecting (climate, parent material, economic development, and land use) in shallow groundwater levels across the southeastern coast of China using GIS and regression analysis, based on 249 soil profiles collected from 2010 to 2012. The results showed approximately 60% drops in shallow groundwater level over a century, and deep groundwater level mostly appeared in north plain and coastal delta regions. Climate dominates the changes in groundwater level for the long term (34.0%). Still, the development of the economic belts mitigated its influences and played a more important role (26.1%) than climate (20.8%) on current. Land use and parent material also contributed to shallow groundwater level dynamics. The shallow groundwater level change across different land uses was more likely to occur in a subtropical climate and Delta with Sediments and Alluvial deposits. We concluded that the Huanghuai plain and Yangtze River Delta's shallow groundwater level dynamics would slow down due to the regulation of water conservancy facilities and groundwater protection policies. However, shallow groundwater level in Pearl River Delta would decline continuously due to the emerging economy and urbanization. Overall, this work is the first to investigate the coastal centurial drop in shallow groundwater level through the gleization soil layer. It provides a possible approach for filling in gaps in groundwater level data and highlights the different contributions of climate and economic growth to the groundwater level over time.

Increasing groundwater storage and maintaining irrigation through managed aquifer recharge

Aquifers providing groundwater for agriculture are in many cases unsustainably managed, resulting in environmental degradation and socioeconomic impacts. In this context, strategies that contribute to recovering groundwater reserves and satisfactorily maintaining irrigation are essential. Los Arenales Aquifer (Spain) experienced a dramatic decline in groundwater level in the last quarter of the 20th century due to intensive agricultural abstractions. We assess whether this aquifer has recovered in recent years and the potential contribution of managed aquifer recharge (MAR). We evaluate the significance of groundwater level trends and their magnitude through the (regional) Mann-Kendall test and the Theil-Sen estimator. We also calculate the average groundwater level and explore factors that could influence the observed trends, such as MAR, land use, agricultural water demand, and water management measures. We also contrast two groundwater management regions located within Los Arenales Aquifer, namely Los Arenales (LA), which has implemented MAR, and Medina del Campo (MC), to obtain further insight into groundwater development. The hydro statistical analyses reveal a continuous drop in groundwater levels of about −1.3 m/year in LA between 1985 and 2001, followed by a consistent recovery. In MC, groundwater levels decrease in two out of three analysis periods. We show that MAR is spatially and temporally correlated with increasing groundwater level trends. Land use, agricultural water demand, and water management measures have remained similar throughout the analysis period or have a limited impact on groundwater use. Furthermore, the only significant water management measure MC differs from LA is MAR. These pieces of evidence point to MAR as the primary mechanism for replenishing Los Arenales Aquifer, showing the potential of this tool to recover stressed aquifers and sustain irrigation in the area and beyond.

Spatial and Temporal Distribution of Groundwater in Open-Pit Coal Mining: A Case Study from Baorixile Coal Mine, Hailaer Basin, China

Groundwater distribution influenced by mining activities is hard to be tracked due to the lack of accurate and real-time monitoring data. To address the groundwater dynamic change data under the mining conditions of open-pit coal mines, a three-dimensional automatic observation network of groundwater was constructed, and this observation network takes open-pit as the center, showing a radioactive distribution, based on hydrogeological conditions, and observes different aquifers. The data was analyzed by integrating hydrology, mining activity, and meteorological data. Analytic hierarchy process was adopted to reveal the underground disturbance influencing factors, and suggestions for groundwater protection were given. The results show that the dynamic variations of the groundwater with time can be divided into 3 types (precipitation affected, unaffected type, and mining affected types). The drainage operation during the open-pit mining triggered the drop of groundwater level, resulting in a cone of depression. The maximum drawdown of the central groundwater level was 60 m. And the disturbance mainly occurred in the mining area where the maximum groundwater disturbance radius was 8 km. Artificial drainage was the main disturbance factor of groundwater, and the range of groundwater level drop within the disturbance radius was closely related to the distance from the open-pit coal mine and the drainage volume. The closer the distance to the mines and the higher the drainage volume led to the deeper the groundwater level drop. This study shows the importance of the three-dimensional observation network of groundwater and provides a good reference for groundwater resources protection and ecological restoration in open-pit coal mines.

Intermittency as an indicator of drought in streamflow and groundwater

AbstractUnder normal precipitation conditions, increasing water demand causes groundwater level to deplete and streamflow to decrease. This results in more frequent intermittency. The so‐called intermittency cycle hypothesis is examined in this study. It is a vicious circle in hydrology making both surface and groundwater resources less efficient in supplying ever‐increasing water demand. To test the hypothesis, a data‐based analysis is applied to Gediz, Kucuk Menderes, and Ergene river basins in western Turkey. Results at basin‐ and station‐scale show no change in precipitation while streamflow fluctuates with a tendency to decrease and groundwater steeply declines. Groundwater is used excessively to meet the drastically increased water demand. With the overuse of groundwater, water table descends, streamflow decreases and intermittency increases. Intermittency ratio of a river is found related to the decrease in streamflow and the drop in groundwater level. It can trigger drought in streamflow and groundwater. It is concluded that intermittency can be taken as a quantitative indicator of drought in streamflow and groundwater.