Explore the vast range of titles available.

Many major cities worldwide have inevitably experienced excessive groundwater pumping due to growing demands for freshwater in urban development. To mitigate land subsidence problems during urbanization, various regulations have been adopted to control groundwater usage. This study examines the transition in the post‐subsidence stage, especially in metropolitan areas, to adaptively adjust subsidence prevention strategies for effective groundwater management. Taking the Taipei Basin as an example, historical data reveals significant subsidence of more than 2 m during early urban development, with subsidence hazards largely mitigated over decades. However, the rising groundwater level poses a risk to the stability of engineering excavations. In this study, 29 X‐band Cosmo‐Skymed constellation (CSK) images were utilized with the Persistent Scatterer InSAR (PSInSAR/PSI) technique to monitor surface displacements during the construction of the Mass Rapid Transit system. Correlating groundwater levels helps identify the heterogeneous hydrogeological environment, and the potential groundwater capacity is assessed. PSI time‐series reveal that approximately 2 cm of recoverable land displacements correspond to groundwater fluctuations in the confined aquifer, indicative of the typically elastic behavior of the resilient aquifer system. The estimated groundwater storage variation is about 1.6 million cubic meters, suggesting this potential groundwater capacity could provide available water resources with proper management. Additionally, engineering excavation safety can be ensured with lowered groundwater levels. This study emphasizes the need to balance groundwater resource use with urban development by adjusting subsidence prevention and control strategies to achieve sustainable water management in the post‐subsidence stage. Plain Language Summary Groundwater is used as an important freshwater resource in global urban development, but over‐exploitation often leads to subsidence problems. Once land subsidence situation is under controlled, attention turns to how to balance urban development with environmental protection. This study takes a metropolitan area in a post‐subsidence period as an example and uses satellite technique to estimate potential groundwater volumes. It suggests that with proper management, groundwater resources can be fully utilized and related engineering disasters can be prevented. Key Points Integrating InSAR and numerical model for transient‐like state groundwater level mapping Quantifying changes in potential groundwater storage as available freshwater resources Efficient groundwater utilization for achieving sustainability in post‐subsidence stages

Groundwater, as the largest storage of liquid freshwater on Earth and a major component of the water cycle, is critical for supporting surface water flow, ecosystems as well as water and food security. Human dependence on groundwater has increased sharply over recent decades, contributing to wealth creation and poverty alleviation. However, anthropogenic activities, including groundwater abstraction and climate change, have modified groundwater dynamics, leading to groundwater level (GWL) changes. We analysed 20 year time series of GWLs in 47 countries distributed across a range of climatic, geographic, hydrogeological and socioeconomic contexts worldwide. Using different indicators based on three time series analysis methods, we show that almost one third of the GWLs trends are declining—thus reflecting overexploitation of groundwater—while GWLs are rising in 18% of wells—not always indicating a recovery but also the consequence of human impact on the environment. Globally, GWLs show a mix of declining and rising trends, however, at regional scale, patterns and hotspots are evident. We also explored the associated impacts of GWL change on humans and ecosystems, by reviewing 28 case study examples. We show that both rising and falling GWLs have substantial impacts on water and food security, ecosystems, infrastructure and socioeconomic wellbeing. Our findings underscore an urgent need for expanding monitoring programmes, protecting groundwater, and defining acceptable impacts to determine sustainable groundwater usage and minimise impacts of GWL change.

Few studies have examined the impact of climate change on groundwater resources worldwide, especially in developing countries. The objective of this study is to review the effects of climate change on groundwater resources in Iran in order to assess the present conditions and challenges and future directions. To this end, the related studies, especially the peer-reviewed national and international articles, were surveyed. Only the responses of 40 aquifers have been estimated toward climate change in Iran, such that a large gap occurs in this perspective. This is in reference to the alluvial aquifers, and even fewer studies have evaluated the impact of climate change on hard-rock and karst groundwater systems despite their being highly vulnerable to the existing stresses. The conducted studies are primarily small-scale, and inadequate research has been conducted on the effect of climate change on aquifers at national and even regional scales. The impact of climate change on groundwater quality and coastal aquifers has not hitherto been adequately assessed. An ever-increasing temperature and ever-decreasing precipitation over the country have been forecasted, resulting in induced stresses on aquifers, including the decline of groundwater level, storage and recharge. If the current managerial approaches are maintained, the failure threshold of most aquifers will certainly be exceeded, making the looming crisis of water in Iran even worse. Finally, it is recommended to reevaluate the groundwater management policies across the country thoroughly and, thence, propose and execute the new adaptation strategies.

To properly manage the groundwater resources, it is necessary to analyze the impact of groundwater withdrawal on the groundwater level. In this study, a Long Short-Term Memory (LSTM) network was used to evaluate the groundwater level prediction performance and analyze the impact of the change in the amount of groundwater withdrawal from the pumping wells on the change in the groundwater level in the nearby monitoring wells located in Jeju Island, Korea. The Nash–Sutcliffe efficiency between the observed and simulated groundwater level was over 0.97. Therefore, the groundwater prediction performance of LSTM was remarkably high. If the groundwater level is simulated on the assumption that the future withdrawal amount is reduced by 1/3 of the current groundwater withdrawal, the range of the maximum rise of the groundwater level would be 0.06–0.13 m compared to the current condition. In addition, assuming that no groundwater is taken, the range of the maximum increase in the groundwater level would be 0.11–0.38 m more than the current condition. Therefore, the effect of groundwater withdrawal on the groundwater level in this area was exceedingly small. The method and results can be used to develop new groundwater withdrawal sources for the redistribution of groundwater withdrawals.

Estimating groundwater levels (GWL) with accuracy and reliability, in order to maximize the use of water resources, it is crucial to reduce water consumption. To predict GWL in the Shabestar plain in the north-west of Iran, this case study developed a simulation–optimization hybrid model. For predicting GWL, the HBA (honey badger algorithm) optimizes parameters of ANNs (artificial neural networks) and SVRs (support vector regressions). Results were compared to ANN and SVR models. Datasets for periods of April 2001–March 2022 were utilized to develop and assess precision of the models. The average mutual information (AMI) is utilized to find out the combination of inputs for hybrid and standalone predictive models. In consideration of appropriate goodness-of-fit criteria, the predictive accuracy of models has been evaluated: correlation coefficient ( R ), root mean square error (RMSE), Nash–Sutcliffe model efficiency (NSE), mean absolute error (MAE), and Taylor diagram. Based on testing phase, the HBA-ANN model shows a very good agreement with the measured data ( R  = 0.999, RMSE(m) = 0.012, NSE = 0.999, MAE(m) = 0.012) followed by HBA-SVR ( R  = 0.999, RMSE(m) = 0.063, NSE = 0.977, MAE(m) = 0.046), SVR ( R  = 0.886, RMSE(m) = 0.245, NSE = 0.663, MAE(m) = 0.170) and ANN ( R  = 0.898, RMSE(m) = 0.272, NSE = 0.584, MAE(m) = 0.212). In conclusion, the HBA-ANN and HBA-SVR models can be used to forecast GWL based on outcomes of this study. Groundwater systems can be well estimated using such advanced AI techniques, saving resources, and labour conventionally employed.

Climate change disrupts groundwater levels (GWL) by modifying precipitation patterns, reducing recharge rates, and limiting water availability. Rising temperatures and evolving weather patterns further degrade surface and groundwater quality. These changes exacerbate competition for water resources, heightening allocation challenges and ecological disruptions. Groundwater fluctuations adversely affect ecosystems, causing habitat disturbances and biodiversity loss. This study explores the impacts of climate change on GWL using machine learning techniques to analyze 9,430 time series data points (1993–2021) from Northern China. Four distinct classes of top-performing machine learning models were evaluated. The CNN model demonstrated superior performance, achieving an R² value of 0.9924 and an RMSE of 0.1832, highlighting its efficacy in processing complex patterns. Pearson correlation analysis revealed that Average Annual Precipitation (AAP), Average Soil Moisture (ASM), and Evapotranspiration (EV) positively influence GWL, while Severe Wet Potential (SWP), Severe Drought Potential (SDP), and Temperature (T) exhibit negative correlations. Feature ranking identified AAP as the most critical factor for groundwater recharge, followed by ASM and EV, which also play significant roles in groundwater dynamics. These findings provide a robust understanding of the key drivers influencing groundwater recharge and storage, offering valuable insights to inform sustainable water resource management in the context of climate change. Highlights Climate change alters precipitation, reducing recharge and groundwater availability. Rising temperatures and weather changes impact surface and groundwater quality. Scarcity of groundwater leads to resource competition and allocation challenges. Groundwater fluctuations disrupt ecosystems, biodiversity, and habitats. Machine learning models, especially CNN, predict groundwater levels with high accuracy.

Irrigated areas are major vectors of agricultural development and components of ecosystems. The groundwater level maintains the irrigated areas’ ecology safety and sustainable development. Under the influence of irrational irrigation practices—such as flood irrigation or extreme water saving without consideration of ecological impact—different areas within an irrigation district may experience anomalies in groundwater levels (either too deep or too shallow). It is of great significance to carry out research on water resource allocation and future water-saving strategies, taking into consideration groundwater depths. In this study, a method for the optimal allocation of irrigation water resources that considered groundwater level was used to regulate irrational irrigation practices and to reveal the future direction of water saving. Helan County in Ningxia province, an ecologically fragile and arid irrigated area, was selected as a case study. Multiple scenarios of different water use and different degrees of water-saving were analyzed. The results showed that non-engineering water-saving measures (such as adjusting the planting structure and controlling the amount of irrigation for rice) had better benefits compared to engineering measures (such as efficient water-saving irrigation and channel lining). When implementing only one water-saving measure, the strategy of replacing 75% of the rice area with corn yielded the best results. This approach can reduce the irrigation water shortage rate to 11% and increase by 4.58% the acreage where the groundwater level is reasonable. When multiple water-saving measures are implemented together, the most effective strategy for future water-saving efforts involves the joint implementation of several measures: replacing 75% of the rice area with corn, limiting irrigation for rice to no more than 11.85 thousand m3/ha, adopting high-efficiency water-saving irrigation in 90% of the pump-diverted water irrigation region and 40% of the channel-diverted water irrigation region, and maintaining the channel’s water utilization coefficient at 0.62. This strategy can keep the irrigation water shortage below 3.66% and increase the acreage where the groundwater level is reasonable, by 4.58% per year. The conclusions and research approaches can provide references for the formulation of water-saving measures for irrigated areas’ sustainable development.

Drought and water scarcity can significantly impair the sustainable development of groundwater resources, a scenario commonly found in aquifers in the Mediterranean region. Water management measures to address these drivers of groundwater depletion are highly relevant, especially considering the increasing severity of droughts under climate change. This study evaluates the potential of managed aquifer recharge (MAR) to offset the adverse effects of drought and water scarcity on groundwater storage. Los Arenales aquifer (central Spain), which was unsustainably exploited for irrigation in the second half of the twentieth century, is employed as a case study. Two neighbouring zones within this aquifer are contrasted, namely, Los Arenales (LA) and Medina del Campo (MC). The primary difference between them in terms of water resources management is the wide-scale implementation of MAR systems in LA since the early 2000s. Several groundwater statistical methods are used. Groundwater-level trend analysis and average piezometric levels show in LA a faster recovery of aquifer storage and less susceptibility to drought compared to MC. On the other hand, standardised precipitation indexes and standardised groundwater level indexes of detrended groundwater-level time series, which do not include the effects of MAR, show that LA can be more negatively affected by drought and groundwater abstraction. The sharper recovery of piezometric levels in LA when considering MAR, and bigger drought impacts observed when the effects of this measure are removed, demonstrate that MAR can effectively alleviate the impacts of water scarcity and drought, providing an adaptation solution to climate change worldwide.

To precisely delineate the transformation dynamics across several temporal and spatial scales in the middle and lower portions of the Songhua River basin in Heilongjiang Province, China, characterized by numerous irrigation zones and frequent transitions from surface water to groundwater. The SWAT-MODLFOW model, developed on the QSWATMOD2 platform, was validated using river runoff data and groundwater level observations. Consequently, the delay of precipitation on groundwater levels and the correlation between surface water and groundwater dynamics in the middle and lower portions of the Songhua River basin were modeled. The findings indicate: (1) The coefficient of calibration and Nash coefficient for monthly runoff during the calibration and validation periods yielded R 2  ≥ 0.86, NSE ≥ 0.87, R 2  ≥ 0.76, and NSE ≥ 0.77, respectively. Furthermore, the discrepancy between the simulated and actual groundwater table values is within 0.6 m, with R² values of 0.97 and 0.98 for the periodic and verification phases, respectively. The simulation outcomes of this test model are satisfactory and fulfill the criteria for scientific research. (2) The groundwater level in the research area typically declines from west-northwest to northeast and from south to east. The groundwater level lag time influenced by precipitation in Jiamusi, Fujin, and Tongjiang cities is around 10.56 days, 10.58 days, and 3.15 days, respectively. (3) The river channels facilitating surface water recharge to groundwater constitute 41.75% of the entire length of the Jiamusi-Tongjiang stretch of the Songhua River, with the annual average recharge representing 50.84% of the total exchanged water. Seasonally, the peak recharge value for each river section occurred in August, while the lowest recharge value was recorded in April. The peak recharge happened in 2009, while the lowest recharge was in 2014. The contribution of groundwater to surface water exhibits significant fluctuations, with seasonal variance between − 52% and 55%, and inter-annual variation between − 35% and 52%.

The rising demand for water in Punjab, fueled by swift urban growth, industrial development, and intensive agricultural practices, has resulted in significant groundwater depletion. In the state, more than 97% of cultivable land is irrigated, with groundwater accounting for approximately 70–75% of the total irrigation water supply. The present study analyzes fluctuations in groundwater levels within the S.A.S. Nagar district over a span of 26 years, from 1995 to 2021, utilizing comprehensive water level data. The findings indicate a significant decrease, with groundwater levels plummeting from 3.6 m in 1995 to 30.7 m in 2021, reflecting an average decline of over 1 m annually. The rate of depletion increased significantly after 1998, largely as a result of a broad transition from canal irrigation to tube wells, which offered farmers more convenient access to water. The findings indicate that 32% of the area exhibits high groundwater potential, whereas merely 3% shows low potential. Furthermore, 8% of the area is categorized as having a high flood risk, while 7% is identified as having a high drought risk. Despite the introduction of initiatives like underground pipeline systems and enhanced rice farming techniques, the groundwater table persists in its decline. The results underscore the critical necessity for revised irrigation policies, enhanced water conservation strategies, and greater public engagement to secure the enduring sustainability of groundwater resources.