Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers

Visual MODFLOW, solute transport modeling, and remote sensing techniques for adapting aquifer potentiality under reclamation and climate change impacts in coastal aquifer

Global environmental changes, such as climate change and reclamation alterations, significantly influence hydrological processes, leading to hydrologic nonstationarity and challenges in managing water availability and distribution. This study introduces a conceptual underpinning for the rational development and sustainability of groundwater resources. As one of the areas intended for the development projects within the Egyptian national plan for the reclamation of one and a half million acres; hundreds of pumping wells were constructed in the Moghra area to fulfill the reclamation demand. This study investigates the long-term impacts of exploiting the drilled pumping wells under climate change. The approach is to monitor the groundwater levels and the salinity values in the Moghra aquifer with various operational strategies and present proposed sustainable development scenarios. The impact of global warming and climate change is estimated for a prediction period of 30 years by using satellite data, time series geographical analysis, and statistical modeling. Using MODFLOW and Solute Transport (MT3DMS) modules of Visual MODFLOW USGS 2005 software, a three-dimensional (3D) finite-difference model is created to simulate groundwater flow and salinity distribution in the Moghra aquifer with the input of forecast downscaling (2020-2050) of main climatic parameters (PPT, ET, and Temp). The optimal adaptation-integrated scenario to cope with long-term groundwater withdrawal and climate change impacts is achieved when the Ministry of Irrigation and Water Resources (MWRI) recommends that the maximum drawdown shouldn't be more significant than 1.0 m/ year. In this scenario, 1,500 pumping wells are distributed with an equal space of 500 m, a pumping rate of 1,200 m3/day and input the forecast of the most significant climatic parameters after 30 years. The output results of this scenario revealed a drawdown level of 42 m and a groundwater salinity value of 16,000 mg/l. Climate change has an evident impact on groundwater quantity and quality, particularly in the unconfined coastal aquifer, which is vulnerable to saltwater intrusion and pollution of drinking water resources. The relationship between climate change and the hydrologic cycle is crucial for predicting future water availability and addressing water-related issues.

Harnessing machine learning for assessing climate change influences on groundwater resources: A comprehensive review

Climate change is a major concern for a range of environmental issues including water resources especially groundwater. Recent studies have reported significant impact of various climatic factors such as change in temperature, precipitation, evapotranspiration, etc. on different groundwater variables. For this, a range of tools and techniques are widely used in the literature including advanced machine learning (ML) and artificial intelligence (AI) approaches. To the best of the authors' knowledge, this review is one of the novel studies that offers an in-depth exploration of ML/AI models for evaluating climate change impact on groundwater variables. The study primarily focuses on the efficacy of various ML/AI models in forecasting critical groundwater parameters such as levels, discharge, storage, and quality under various climatic pressures like temperature and precipitation that influence these variables. A total of 65 research papers were selected for review from the year 2017-2023, providing an up-to-date exploration of the advancements in ML/AI methods for assessing the impact of climate change on various groundwater variables. It should be noted that the ML/AI model performance depends on the data attributes like data types, geospatial resolution, temporal scale etc. Moreover, depending on the research aim and objectives of the different studies along with the data availability, various sets of historical/observation data have been used in the reviewed studies Therefore, the reviewed studies considered these attributes for evaluating different ML/AI models. The results of the study highlight the exceptional ability of neural networks, random forest (RF), decision tree (DT), support vector machines (SVM) to perform exceptionally accurate in predicting water resource changes and identifying key determinants of groundwater level fluctuations. Additionally, the review emphasizes on the enhanced accuracy achieved through hybrid and ensemble ML approaches. In terms of Irish context, the study reveals significant climate change risks posing threats to groundwater quantity and quality along with limited research conducted in this avenue. Therefore, the findings of this review can be helpful for understanding the interplay between climate change and groundwater variables along with the details of the various tools and techniques including ML/AI approaches for assessing the impacts of climate changes on groundwater.

A proposed methodology to evaluate the influence of climate change on drinking water treatments and costs

Drinking water (DW) production treatments can be affected by climate change, in particular intense rainfall events, having an impact on the availability and quality of the water source. The current study proposes a methodology for the evaluation of the costs of the different treatment steps for surface water (SW) and groundwater (GW), through the analysis and quantification of the main cost items. It provides the details to count for strong variations in the key quality parameters of inlet water following severe rainfalls (namely turbidity, iron, manganese, and E. coli). This methodology is then applied to a large drinking water treatment plant (DWTP) in Italy, which treats both SW, around 70 %, and GW, around 30%. It discusses the overall DW production costs (from 7.60 c€/m3 to 10.43 c€/m3) during the period 2019-2021 and analyzes the contributions of the different treatment steps in water and sludge trains. Then it focuses on the effects on the treatments of significant variations in SW turbidity (up to 1863 NTU) due to intense rainfalls, and on the daily costs of DW with respect to the average (baseline) costs evaluated on the annual basis. It emerges that, when SW has low turbidity levels, the energy-based steps have the biggest contribution on the costs (final pumping 22 % for SW and 10 % for GW, withdrawal 15 % and 14 %, respectively), whereas at very high turbidity levels, sludge greatly increases, and its treatment and disposal costs become significant (up to 14 % and 50 %). Efforts are being made to adopt the best strategies for the management of DWTPs in these adverse conditions, with the aim to guarantee potable water and optimize water production costs. A mitigation measure consists of increasing GW withdrawal up to the authorized flow rate, thus reducing SW withdrawal. In this context, the study is completed by discussing the potential upgrading of the DWTP by only treating GW withdrawn from riverbank filtration. The DW production cost would be 7.76 c€/m3, which is lower than that seen for the same year (2021) with the current plant configuration (8.32 c€/m3).

Spatiotemporal patterns of groundwater over South Korea

Understanding the large-scale spatiotemporal pattern of multi-depth groundwater levels is critical to develop water management plans and policies for sustainable ecological and social prosperity, which are still lacking. Here, we investigate three major spatiotemporal modes of groundwater levels from ∼200 groundwater monitoring stations over the southern Korean Peninsula (2009-2020), using the Cyclostationary empirical orthogonal function analysis. The first two major modes are associated with the seasonality of recharge and discharge and groundwater use during the 2016/17 drought, which explained half of the total variance. The third major mode indicated a decreasing trend of deep groundwater levels over the western Korean Peninsula, where key administrative and authority offices have been relocated via balanced national land development policies. Furthermore, at least three million Koreans over this region likely experience groundwater depletion by the 2080s. Observational evidence of emerging groundwater depletion suggests a window of opportunity for pre-emptive groundwater management plans.

Seasonality of hydrogeochemical evolutions and isotopic variabilities (δ18O, δ2H and d-excess) in the surface water as well as groundwater from tropical central-south Mexico

Due to adverse impact of the global warming on hydrological resources, we intended to document the hydrogeochemical evolutions of surface and groundwater at tropical central-south Mexico in terms of seasonality of rock-water interaction, precipitation/evaporation variation and moisture source by evaluating the major ion chemistry in Piper and Gibbs plots, Durov diagram and through estimation of the chloro-alkaline indices as well as assessing the stable isotope compositions (δ18O and δ2H) in samples from different seasons of a year. Surface water of the Lake Coatetelco shifted from mostly Ca-Mg-HCO3 facies in wet summer-autumn to Na-HCO3-Cl facies in the dry spring due to elevated Na, Cl and HCO3. Greater evaporation in spring led to a maximum δ18O enrichment of ca.7‰ compared to the other seasons, and much depleted deuterium excess (-40.92‰ to -39.20‰). Interaction of the lake water with subsurface carbonate lithologies, and comparable isotopic compositions reflected the enhanced interaction between the surface water body and aquifers in the wet autumn. Effect of seasonality, however, was unclear on the groundwater facies, and its heterogenous composition (Ca-Mg-HCO3, Na-HCO3-Cl and Na-HCO3) reflected the interactions with different lithologies. Fractionations in isotope compositions of the groundwater were caused from recharge at different elevations, seasonality of moisture sources and moisture recycling. The water-mineral saturation index was an efficient proxy of seasonality as the lake water and groundwater (avg SIcalcite > 0.5) of the dry autumn were saturated with calcite. This vital information about carbonate precipitation, pCO2 and chemical facies would be useful for the better interpretation of paleoclimate archives in this region.

How Human Activities Affect Groundwater Storage

Despite the recognized influence of natural factors on groundwater, the impact of human activities remains less explored because of the challenges in measuring such effects. To address this gap, our study proposes an approach that considers carbon emissions as an indicator of human activity intensity and quantifies their impact on groundwater storage. The combination of carbon emission data and groundwater storage data for 17,152 grid cells over 16 years in 4 typical basins shows that they were generally negatively correlated, whereas both agriculture and aviation had positive impacts on groundwater storage. The longest impact from aviation and agriculture can even persist for 7 years. Furthermore, an increase of 1 Yg CO2/km2 per second in emissions from petroleum processing demonstrates the most pronounced loss of groundwater storage in the Yangtze River Basin (approximately 4.1 mm). Moreover, regions characterized by high-quality economic development tend to have favorable conditions for groundwater storage. Overall, our findings revealed the substantial role of human activities in influencing groundwater dynamics from both temporal and spatial aspects. This study fills a crucial gap by exploring the relationship between human activities and groundwater storage through the introduction of a quantitative modeling framework based on carbon emissions. It also provides insights for facilitating empirical groundwater management planning and achieving optimal emission reduction levels.

A global dataset of terrestrial evapotranspiration and soil moisture dynamics from 1982 to 2020

Quantifying terrestrial evapotranspiration (ET) and soil moisture dynamics accurately is crucial for understanding the global water cycle and surface energy balance. We present a novel, long-term dataset of global ET and soil moisture derived from the newly developed Simple Terrestrial Hydrosphere model, version 2 (SiTHv2). This ecohydrological model, driven by multi-source satellite observations and hydrometeorological variables from reanalysis data, provides daily global ET-related estimates (e.g., total ET, plant transpiration, soil evaporation, intercepted evaporation) and three-layer soil moisture dynamics at a 0.1° spatial resolution. Validation with in-situ measurements and comparisons with mainstream global ET and soil moisture products demonstrate robust performance of SiTHv2 in both magnitude and temporal dynamics of ET and soil moisture at multiple scales. The comprehensive water path characterization in the SiTHv2 model makes this seamless dataset particularly valuable for studies requiring synchronized water budget and vegetation response to water constraints. With its long-term coverage and high spatiotemporal resolution, the SiTHv2-derived ET and soil moisture product will be suitable to support analyses related to the hydrologic cycle, drought assessment, and ecosystem health.

Nanofibrous Biomaterial-Based Passive Cooling Paint Structurally Linked by Alkane-Oleate Interactions

Passive radiative cooling materials, which provide cooling without consuming electricity, are widely recognized as an important technology for reducing greenhouse gas emissions and delivering thermal comfort to less industrialized communities. Optimizing thermal and optical properties is of primary importance for these materials, but for real-world utilization, ease of application and scalability also require significant emphasis. In this work, we embed the biomaterial hydroxyapatite, in the form of nanoscale fibers, within an oil-based medium to achieve passive cooling from an easy-to-apply paint-like solution. The chemical structure and bonding behaviors of this mixture are studied in detail using FTIR, providing transferable conclusions for pigment-like passive cooling solutions. By reflecting 95% of solar energy and emitting 92% of its radiative output through the atmospheric transparency window, this composite material realizes an average subambient cooling performance of 3.7 °C in outdoor conditions under a mean solar irradiance of 800 W m-2. The inflammability of the material provides enhanced durability as well as unique opportunities for recycling which promote circular economic practices. Finally, the surface structure can be easily altered to tune bonding behaviors and hydrophobicity, making it an ideal passive cooling coating candidate for outdoor applications.

Emerging trends and spatial shifts of drought potential across global river basins

Droughts have devastating effects on various sectors and are difficult to quantify and track because of the invisible and slow but prevalent propagation. This dilemma is more significant in the case of the complex interactions between land and atmosphere mechanisms, which are inadequately considered in previous drought metrics. Here, we investigate the spatiotemporal variability of the recently devised metric called 'Drought Potential Index (DPI)', which incorporates the antecedent land water storage and current precipitation. Using the spatial weighted centroid method, we elucidate the emerging spatial movement of the DPI within 168 major global river basins and analyze its influential factors. Improved drought detection and performance disparity of DPI as compared with multi-scale (i.e., 1, 3, 6, 9, 12-month) Standardized Precipitation Index, ensemble soil moisture anomaly, and Total Storage Deficit Index corroborate the robustness and improved insights of DPI. Higher increasing trends in DPI are detected over dryland basins (0.39 ± 0.43 %/a) than in the humid zones (0.15 ± 0.34 %/a). Six hotspot basins, namely, Don, Yellow, Haihe, Rio Grande, Sao Francisco, and Ganges river basins, are identified with increasing (2.1-3.5%/a) DPI during 2003-2021. The interannual occurrence of the highest DPI, spatial shifts, and relative contribution of DPI's constituent variables correspond well to the climatic and anthropogenic changes in humid and dry land basins. The absolute latitudinal/longitudinal shifts of ∼2° (as high as ∼3.2/4.9°) in DPI in 30% (47 out of 168 basins) of the global basins highlight the need for analyzing the water scarcity problems from both the perspectives of long-term trends and spatial shifts. Our findings provide a global assessment of the spatiotemporal shifts of drought potential and will be beneficial to understanding the anthropogenic and climatic influences on water resource management under a changing environment.

Development of Groundwater Levels Dataset for Chile since 1970

Access to accurate spatio-temporal groundwater level data is crucial for sustainable water management in Chile. Despite this importance, a lack of unified, quality-controlled datasets have hindered large-scale groundwater studies. Our objective was to establish a comprehensive, reliable nationwide groundwater dataset. We curated over 120,000 records from 640 wells, spanning 1970-2021, provided by the General Water Resources Directorate. One notable enhancement to our dataset is the incorporation of elevation data. This addition allows for a more comprehensive estimation of groundwater elevation. Rigorous data quality analysis was executed through a classification scheme applied to raw groundwater level records. This resource is invaluable for researchers, decision-makers, and stakeholders, offering insights into groundwater trends to support informed, sustainable water management. Our study bridges a crucial gap by providing a dependable dataset for expansive studies, aiding water management strategies in Chile.

Perspectives and pitfalls in preserving subterranean biodiversity through protected areas

Subterranean ecosystems (comprising terrestrial, semi-aquatic, and aquatic components) are increasingly threatened by human activities; however, the current network of surface-protected areas is inadequate to safeguard subterranean biodiversity. Establishing protected areas for subterranean ecosystems is challenging. First, there are technical obstacles in mapping three-dimensional ecosystems with uncertain boundaries. Second, the rarity and endemism of subterranean organisms, combined with a scarcity of taxonomists, delays the accumulation of essential biodiversity knowledge. Third, establishing agreements to preserve subterranean ecosystems requires collaboration among multiple actors with often competing interests. This perspective addresses the challenges of preserving subterranean biodiversity through protected areas. Even in the face of uncertainties, we suggest it is both timely and critical to assess general criteria for subterranean biodiversity protection and implement them based on precautionary principles. To this end, we examine the current status of European protected areas and discuss solutions to improve their coverage of subterranean ecosystems.

Groundwater is a hidden global keystone ecosystem

Groundwater is a vital ecosystem of the global water cycle, hosting unique biodiversity and providing essential services to societies. Despite being the largest unfrozen freshwater resource, in a period of depletion by extraction and pollution, groundwater environments have been repeatedly overlooked in global biodiversity conservation agendas. Disregarding the importance of groundwater as an ecosystem ignores its critical role in preserving surface biomes. To foster timely global conservation of groundwater, we propose elevating the concept of keystone species into the realm of ecosystems, claiming groundwater as a keystone ecosystem that influences the integrity of many dependent ecosystems. Our global analysis shows that over half of land surface areas (52.6%) has a medium-to-high interaction with groundwater, reaching up to 74.9% when deserts and high mountains are excluded. We postulate that the intrinsic transboundary features of groundwater are critical for shifting perspectives towards more holistic approaches in aquatic ecology and beyond. Furthermore, we propose eight key themes to develop a science-policy integrated groundwater conservation agenda. Given ecosystems above and below the ground intersect at many levels, considering groundwater as an essential component of planetary health is pivotal to reduce biodiversity loss and buffer against climate change.

Identifying hotspots of water table depth change by coupling trend with time stability analysis in the North China Plain

Many groundwater construction projects such as South-to-North Water Diversion Project (SNWDP) were conducted for controlling groundwater overexploitation in the North China Plain (NCP). However, more insight is required into the magnitude and distribution of water table depth (WTD) in time and space over the NCP. This study evaluated the variability and the hotspots of WTD based on 83 unconfined monitoring wells and took trend, breakpoint, and time stability into consideration. We found the average WTD of unconfined aquifer for the Southern Hebei Plain generally increased continuously from 1998 to 2020 in spite of the operation of the SNWDP since 2014. However, the rise rate of WTD slows down in recent years and the WTD has decreased in certain subregions. We further divided these groundwater wells into five groups: climb accelerating (Group 1), increase decelerating (Group 2), first rise then descend (Group 3), first descend then rise (Group 4), decrease decelerating (Group 5), and reduce accelerating (Group 6). Moreover, we found that the number of wells that divided into Group1 to Group 5 account for 15 %, 41 %, 25 %, 18 %, and 1 % of the total number of observation wells. The breakpoints of all the wells are from 2001 to 2017 and most of the breakpoints were found before 2014, which demonstrates that other groundwater management strategies implemented in the Southern Hebei Plain prior to the operation of the SNWDP plays a crucial part. The hotspots area for group 1 is mainly distributed in the north region of Shijiazhuang City, group 2 is in southern region of piedmont plain, group 3 is in northern region of Baoding and south-west region of Xingtai City, and group 4 is in Cangzhou City and eastern region of Xingtai City. The method and framework of this study can be applied in other regions suffering from groundwater depletion.

Understanding global groundwater-climate interactions

Global warming is emerging as an important predictor of water availability and future water supplies across the world through inducing the frequency and severity in hydrological extremes. These extremes (e.g., drought) have potential impacts on groundwater, environmental flows, as well as increase social inequalities (limited access to water by the poor), among a range of other issues. Understanding the influence of global climate on groundwater systems is thus critical to help reshape global water markets through policies underpinned by the knowledge of climatic processes driving the water cycle and freshwater supply. The main aim of this study is to improve understanding of the influence of climate variability on global groundwater using statistical methods (e.g., multi-linear regression and wavelet analyses). The response of groundwater to climate variability are assessed and the feasibility of identifying climatic hotspots of groundwater-climate interactions are explored (2003-2017). Generally, climate variability plays a major role in the distribution of groundwater recharge, evidenced in the groundwater-rainfall relationship (r ranging from 0.6 to 0.8 with lags of 1-5 months) in several regions (Amazon and Congo basins, West Africa, and south Asia). Some of the areas where no relationship exists coincide with major regional aquifer systems (e.g., Nubian sand stone in north Africa) in arid domains with fossil groundwater. Our results also show that groundwater fluxes across the world are driven by global climate teleconnections. Notable among these climate teleconnections are PDO, ENSO, CAR, and Nino 4 with PDO showing the strongest relationship (r= 0.80) with groundwater in some hotspots (e.g. in South America). The explicit role of the Pacific ocean in regulating groundwater fluxes provides an opportunity to improve the prediction of climate change impact on global freshwater systems. As opposed to remarkably large productive hydrological systems (Amazon and Congo basins), in typically arid domains, groundwater could be restricted during prolonged drought, constraining the persistence of surface water in the maintenance of a healthy surface-groundwater interactions.

Assessment of the sustainability of groundwater utilization and crop production under optimized irrigation strategies in the North China Plain under future climate change

Over-exploitation of groundwater due to intensive irrigation and anticipated climate change pose severe threats to the water and food security worldwide, particularly in the North China Plain (NCP). Limited irrigation has been recognized as an effective way to improve crop water productivity and slow the rapid decline of groundwater levels. Whether optimized limited irrigation strategies could achieve a balance between groundwater pumping and grain production in the NCP under future climate change deserves further study. In this study, an improved Soil and Water Assessment Tool (SWAT) model was used to simulate climate change impacts on shallow groundwater levels and crop production under limited irrigation strategies to suggest optimal irrigation management practices under future climate conditions in the NCP. The simulations of eleven limited irrigation strategies for winter wheat with targeted irrigations at different growth stages and with irrigated or rainfed summer maize were compared with future business-as-usual management. Climate change impacts showed that mean wheat (maize) yield under adequate irrigation was expected to increase by 13.2% (4.9%) during the middle time period (2041-2070) and by 11.2% (4.6%) during the late time period (2071-2100) under three SSPs compared to the historical period (1971-2000). Mean decline rate of shallow groundwater level slowed by approximately 1 m a-1 during the entire future period (2041-2100) under three SSPs with a greater reduction for SSP5-8.5. The average contribution rate of future climate toward the balance of shallow groundwater pumping and replenishment was 62.9%. Based on the simulated crop yields and decline rate of shallow groundwater level under the future climate, the most appropriate limited irrigation was achieved by applying irrigation during the jointing stage of wheat with rainfed maize, which could achieve the groundwater recovery and sustainable food production.

Identifying robust adaptive irrigation operating policies to balance deeply uncertain economic food production and groundwater sustainability trade-offs

Increasing irrigation demand has heavily relied on groundwater use, especially in places with highly variable water supplies that are vulnerable to drought. Groundwater management in agriculture is becoming increasingly challenging given the growing effects from overdraft and groundwater depletion worldwide. However, multiple challenges emerge when seeking to develop sustainable groundwater management in irrigated systems, such as trade-offs between the economic revenues from food production and groundwater resources, as well as the broad array of uncertainties in food-water systems. In this study we explore the applicability of Evolutionary Multi-Objective Direct Policy Search (EMODPS) to identify adaptive irrigation policies that water agencies and farmers can implement including operational decisions related to land use and groundwater use controls as well as groundwater pumping fees. The EMODPS framework yields state-aware, adaptive policies that respond dynamically as system state conditions change, for example with variable surface water (e.g., shifting management strategies across wet versus dry years). For this study, we focus on the Semitropic Water Storage district located in the San Joaquin Valley, California to provide broader insights relevant to ongoing efforts to improve groundwater sustainability in the state. Our findings demonstrate that adaptive irrigation policies can achieve sufficiently flexible groundwater management to acceptably balance revenue and sustainability goals across a wide range of uncertain future scenarios. Among the evaluated policy decisions, pumping restrictions and reductions in inflexible irrigation demands from tree crops are actions that can support dry-year pumping while maximizing groundwater storage recovery during wet years. Policies suggest that an adaptive pumping fee is the most flexible decision to control groundwater pumping and land use.

Decline in Iran's groundwater recharge

Groundwater recharge feeds aquifers supplying fresh-water to a population over 80 million in Iran-a global hotspot for groundwater depletion. Using an extended database comprising abstractions from over one million groundwater wells, springs, and qanats, from 2002 to 2017, here we show a significant decline of around -3.8 mm/yr in the nationwide groundwater recharge. This decline is primarily attributed to unsustainable water and environmental resources management, exacerbated by decadal changes in climatic conditions. However, it is important to note that the former's contribution outweighs the latter. Our results show the average annual amount of nationwide groundwater recharge (i.e., ~40 mm/yr) is more than the reported average annual runoff in Iran (i.e., ~32 mm/yr), suggesting the surface water is the main contributor to groundwater recharge. Such a decline in groundwater recharge could further exacerbate the already dire aquifer depletion situation in Iran, with devastating consequences for the country's natural environment and socio-economic development.

Natural radionuclides behaviour in drinking groundwaters from Castilla y León (Spain); radiological implications

Since the coming into force of the European Council Directive 51/2013 EURATOM and its transposition into the Spanish legislation, the presence of radioactive substances in drinking waters must be kept under surveillance to ensure that the health protection requirements are met. Driven by this regulatory framework, in an attempt to know the starting point from which to design surveillance plans, the groundwaters intended for human consumption of Castilla y León (Spain) have been radiologically characterised by using both low-level γ-ray and α-particle spectrometry to determine the activity concentration of the natural radionuclides needed to account for the indicative dose estimation. This extensive research has comprised the radiological characterisation of more than 400 drinking water samples from one of the European Union's largest regions. Furthermore, the gross α and gross β activities have been analysed. Results showed a high geographical variability that can be related to the hydrogeological formations where the groundwaters come from. The uranium isotopes, 234U and 238U, are the main radionuclides present in the analysed drinking waters reaching values up to 2000 mBq/L, in the southwestern and western of Castilla y León, where U-rich minerals are part of the host rock. High 210Pb and 226,228Ra occurrences are found in the low permeability igneous and metasedimentary hydrogeological formations of Salamanca province. From a public health protection point of view, 4.4% of the total drinking water samples from intakes exceeded the Indicative Dose parametric value of 0.1 mSv, which is a not negligible number of samples, being very likely related to granitic and metamorphosed host rock under specific local conditions. This fact highlights the need for research and consideration of special surveillance of the groundwaters from these areas.

Understanding the phenomenon of saltwater intrusion sourced from desalination plants at coastal aquifers

Members of the Gulf Cooperation Council countries Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates rely on desalination to produce water for domestic use. Desalination produces brine that may intrude into the aquifers to pollute the fresh groundwater because of the concentration gradient and groundwater pumping. Modeling the trends of saltwater intrusion needs theoretical understanding and thorough logical experimentation. The objective of this exercise was to understand the phenomenon of saltwater intrusion using an existing set of data analyzed with the convective-diffusion equation and the two-region mobile-immobile solution model. The objective was achieved by optimizing non-measurable solute transport parameters from an existing set of data generated from a series of logical miscible displacements of potassium bromide through sepiolite minerals and curve-fitting simulations. Assumptions included that solute displacements through sepiolite porous media and the related simulations represented the phenomenon of saltwater intrusion under non-equilibrium conditions of porous media mimicking the aquifers. Miscible displacements of potassium bromide were observed from a column of 2.0-2.8 mm aggregates of sepiolite over 4 ranges of concentration and at 11 displacement speeds under saturated vertical flow deionized water and vice versa. Breakthrough curves of both bromide and potassium ions were analyzed by a curve-fitting technique to optimize transport parameters assuming solute movement was governed (i) by the convective-diffusion equation and (ii) the two-region mobile-immobile solution model. Column Peclet numbers from the two analyses were identical for potassium ions but those for bromide ions were c. 60% greater from the two-region model than from the convective-diffusion equation. For the two-region model, dispersion coefficients were well defined and remained unchanged from the convective-diffusion equation for potassium ions but decreased for bromide ions. Retardation factors for bromide ions were approximately the same, but those for potassium ions, though > 1, were poorly defined. In order to design mitigation strategies for avoiding groundwater contamination, this study's findings may help model groundwater pollution caused by the activities of desalination of seawater, which produces concentrated liquid that intrudes into the coastal aquifer through miscible displacement. However, robust saltwater intrusion models may be considered in future studies to confirm the results of the approach presented in this exercise. Field data on the groundwater contamination levels may be collected to compare with simulated trends drawn from the saltwater intrusion models and the curve-fitting technique used in this work. A comparison of the output from the two types of models may help determine the right option to understand the phenomena of saltwater intrusion into coastal aquifers of various characteristics.

Identifying the suitable managed aquifer recharge (MAR) strategy in an overexploited and contaminated river basin

Managed aquifer recharge (MAR) is a promising adaptation measure to reduce vulnerability to climate change and hydrological variability. However, in areas where the basin is highly polluted, densely populated, and intensely cultivated, implementing suitable MAR strategies is a significant challenge. This study used a geographic information system-based multicriteria decision analysis (GIS-MCDA) approach to delineate the MAR potential sites using seven thematic layers describing surface and subsurface features. Further, basin-specific MAR approach was developed using information such as polluted water areas, canal network distribution for water supply, and cropping patterns. The results of this study indicate that only 17% of the area is highly suitable, while 54% and 29% were found moderately suitable and unsuitable for the MAR approach. Since most highly and moderately suitable sites were falling in the agricultural areas, agricultural-based MAR (AgMAR) was considered a preferred option. AquaCrop model for sugarcane was developed considering excess canal water supply during the grand growth stage to understand the AgMAR potential in the study area. It was observed that the potential recharge under normal irrigation scenarios varies from 135.5 to 272 mm/year, which can be increased through AgMAR up to 545 mm/year depending on the water availability for excess irrigations. This study provides an improved understanding of the parameters that should be considered for MAR site selection and post-GIS-MCDA analysis to assess the basin-specific MAR strategy.

From Recharge, to Groundwater, to Discharge Areas in Aquifer Systems in Quebec (Canada): Shaping of Microbial Diversity and Community Structure by Environmental Factors

Groundwater recharge and discharge rates and zones are important hydrogeological characteristics of aquifer systems, yet their impact on the formation of both subterranean and surface microbiomes remains largely unknown. In this study, we used 16S rRNA gene sequencing to characterize and compare the microbial community of seven different aquifers, including the recharge and discharge areas of each system. The connectivity between subsurface and surface microbiomes was evaluated at each site, and the temporal succession of groundwater microbial communities was further assessed at one of the sites. Bacterial and archaeal community composition varied between the different sites, reflecting different geological characteristics, with communities from unconsolidated aquifers being distinct from those of consolidated aquifers. Our results also revealed very little to no contribution of surface recharge microbial communities to groundwater communities as well as little to no contribution of groundwater microbial communities to surface discharge communities. Temporal succession suggests seasonal shifts in composition for both bacterial and archaeal communities. This study demonstrates the highly diverse communities of prokaryotes living in aquifer systems, including zones of groundwater recharge and discharge, and highlights the need for further temporal studies with higher resolution to better understand the connectivity between surface and subsurface microbiomes.

Application and comparison of different statistical methods for the analysis of groundwater levels over time: Response to rainfall and resource evolution in the Piedmont Plain (NW Italy)

Monitoring and analysis of groundwater level (GWL) in space and time is one of the tools used to evaluate the quantitative status of groundwater (GW) resources and identify possible alterations and critical cases due to climate change and variability, anthropogenic influences and other driving factors. In this study, four statistical methodologies (trend, change-point, percentile and non-standardized anomaly analyses) were applied for GWL and rainfall (R) analysis in the Piedmont Plain (western Po Plain, NW Italy). To detect the interannual variations in the GW maximum annual amplitude, the coefficient of variation was also used. The aims of the study were 1) to compare the results of different statistical methods, highlighting their applicability and differences to evaluate the quantitative evolution of GW, 2) to identify the relationship between GWL and R, 3) to investigate the spatiotemporal variation in the GWL of shallow aquifers in the Piedmont Plain, and 4) to describe critical situations of GW depletion. The study highlights that the application of a single method for assessing the shallow GW resource status does not always guarantee a reliable evaluation. For this reason, it is advisable to apply different analysis methods at the same time. Completeness of data and medium to long time series are prerequisites for meaningful analyses. The use of the same time interval is always necessary for comparisons between different monitoring wells and between the results of different statistical analyses. Last, by spatializing the results, it was possible to identify areas characterized by similar GWL behaviour due to hydrological structure, climate variability, land use and the evolution of anthropogenic activities over time. These factors influence vary locally in the Piedmont plain and require local assessments to determine the impact of changes in GWL.

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.

Multi-decadal analysis of water resources and agricultural change in a Mediterranean semiarid irrigated piedmont under water scarcity and human interaction

Mediterranean piedmonts are an important hydro-agricultural systems. They constitute the junction between the mountains, where the streamflow is generated, and the surrounding plains, where the water is used. In Morocco, these traditional systems extend largely along the High Atlas Mountains. Yet, changing conditions in the Mediterranean basin as well as recurrent droughts in recent decades remain poorly understood in terms of hydrological and agricultural impacts, particularly in traditional hydro-agro-systems. The combined effects of climate variability and ineffective management of water resource dynamics may lead to increased water scarcity in these regions. The present work aims to assess the effects of climate variability and associated agricultural changes on water resources in a traditional irrigated piedmont of the Moroccan High Atlas. To that end, a trend analysis, together with change points detection, was carried out on annual and monthly precipitation, and streamflow from 1965 to 2018. Then, the standardized precipitation index (SPI) was employed to identify meteorological droughts. Also, groundwater, and spring discharge data were analyzed and discussed from 1973 to 2021. SPI outcomes revealed three major droughts, in 1981-1988, 1999-2008, and 2013-2018. Although the precipitation data showed no significant trend, except for Tahannaout station, the average annual precipitation over the piedmont area decreased by 28%. Similarly, streamflow decreased significantly by almost 40% for all stations, as did the Abainou spring's discharge. Consistent with that, groundwater level has declined dramatically over the past decades in the downstream piedmont. These decreases in water cycle components were tightly aligned with droughts. Yet, irrigation diversions were maintained in both dry and wet periods. Paradoxically, this decrease in water resources was associated with an agricultural transition from seasonal crops (cereals) to perennial crops (olive trees). This conversion is likely to amplify the water shortage, leading to groundwater resources overexploitation to satisfy the growing agricultural demand.

Spatial Characterisation of Vegetation Diversity in Groundwater-Dependent Ecosystems Using In-Situ and Sentinel-2 MSI Satellite Data

Groundwater-Dependent Ecosystems (GDEs) are under threat from groundwater over-abstraction, which significantly impacts their conservation and sustainable management. Although the socio-economic significance of GDEs is understood, their ecosystem services and ecological significance (e.g., biodiversity hotspots) in arid environments remains understudied. Therefore, under the United Nations Sustainable Development Goal (SDG) 15, characterizing or identifying biodiversity hotspots in GDEs improves their management and conservation. In this study, we present the first attempt towards the spatial characterization of vegetation diversity in GDEs within the Khakea-Bray Transboundary Aquifer. Following the Spectral Variation Hypothesis (SVH), we used multispectral remotely sensed data (i.e., Sentinel-2 MSI) to characterize the vegetation diversity. This involved the use of the Rao’s Q to measure spectral diversity from several measures of spectral variation and validating the Rao’s Q using field-measured data on vegetation diversity (i.e., effective number of species). We observed that the Rao’s Q has the potential of spatially characterizing vegetation diversity of GDEs in the Khakea-Bray Transboundary Aquifer. Specifically, we discovered that the Rao’s Q was related to field-measured vegetation diversity (R2 = 0.61 and p = 0.00), and the coefficient of variation (CV) was the best measure to derive the Rao’s Q. Vegetation diversity was also used as a proxy for identifying priority conservation areas and biodiversity hotspots. Vegetation diversity was more concentrated around natural pans and along roads, fence lines, and rivers. In addition, vegetation diversity was observed to decrease with an increasing distance (>35 m) from natural pans and simulated an inverse piosphere (i.e., minimal utilization around the natural water pans). We provide baseline information necessary for identifying priority conservation areas within the Khakea-Bray Transboundary Aquifer. Furthermore, this work provides a pathway for resource managers to achieve SDG 15 as well as national and regional Aichi biodiversity targets.

Chemical Quality and Hydrogeological Settings of the El-Farafra Oasis (Western Desert of Egypt) Groundwater Resources in Relation to Human Uses

In the Egyptian deserts, new land reclamation projects have been recently established to meet the increasing-population growth rate and food demand. These projects mainly depend on the different groundwater aquifers. El-Farafra Oasis is one of the “1.5-million-feddan reclamation project” areas recently established in the Western Desert of Egypt where the only available water source is the world’s largest fossil freshwater reservoir “the Nubian Sandstone Aquifer System (NSAS)”. Groundwater-dependent springs, and their artificial counterpart “drilled wells”, are reliable water systems throughout the world. In the present study, hydrochemical parameters were collected in 2015 from 16 different springs and wells of the El-Farafra Oasis, and analyzed using the different water quality indices. The calculated water quality index (WQI), its correlations with the water quality parameters Gibbs, Piper, US Salinity-Lab Staff and Wilcox diagrams, and Principal Component Analysis (PCA) were used to evaluate the groundwater suitability for human drinking and irrigation purposes. WQI values revealed good-to-excellent groundwater quality for human drinking. In addition, the spring and well water samples investigated showed good indices for irrigation activities. Gibbs and Piper’s diagrams were presented, with most samples falling into the rock-dominance category, and belonging to hydrogeochemical facies determining the following water types: Mg(HCO3)2 type water (37.5% of the samples), no dominant ions (mixed water-type category; Ca/MgCl2) (50% of the samples), and, finally, NaCl water type (the remaining 12.5%). The groundwater chemistry in the study area is mainly controlled by rock-water interactions, particularly the dissolution of carbonate rocks and silicate weathering. The elevated nutrient concentrations, in particular nitrates, are most likely due to agricultural activities, indicating substantial anthropogenic activities in the area studied.

Three Decades of Gross Primary Production (GPP) in China: Variations, Trends, Attributions, and Prediction Inferred from Multiple Datasets and Time Series Modeling

The accurate estimation of gross primary production (GPP) is crucial to understanding plant carbon sequestration and grasping the quality of the ecological environment. Nevertheless, due to the inconsistencies of current GPP products, the variations, trends and short-term predictions of GPP have not been sufficiently well studied. In this study, we explore the spatiotemporal variability and trends of GPP and its associated climatic and anthropogenic factors in China from 1982 to 2015, mainly based on the optimum light use efficiency (LUEopt) product. We also employ an autoregressive integrated moving average (ARIMA) model to forecast the monthly GPP for a one-year lead time. The results show that GPP experienced an upward trend of 2.268 g C/m2 per year during the studied period, that is, an increasing rate of 3.9% per decade since 1982. However, these trend changes revealed distinct heterogeneity across space and time. The positive trends were mainly distributed in the Yellow River and Huaihe River out of the nine major river basins in China. We found that the dynamics of GPP were concurrently affected by climate factors and human activities. While air temperature and leaf area index (LAI) played dominant roles at a national level, the effects of precipitation, downward shortwave radiation (SRAD), carbon dioxide (CO2) and aerosol optical depth (AOD) exhibited discrepancies in terms of degree and scope. The ARIMA model achieved satisfactory prediction performance in most areas, though the accuracy was influenced by both data values and data quality. The model can potentially be generalized for other biophysical parameters with distinct seasonality. Our findings are further verified and corroborated by four widely used GPP products, demonstrating a good consistency of GPP trends and prediction. Our analysis provides a robust framework for characterizing long-term GPP dynamics that shed light on the improved assessment of the environmental quality of terrestrial ecosystems.

A critical appraisal of the status and hydrogeochemical characteristics of freshwater springs in Kashmir Valley

With growing water scarcity, jeopardized by climate change, springs are likely to perform a vital role in meeting the domestic water demand in future. This paper examines the water quality status of Kashmir valley springs in relation to their geographical location, regional hydrogeological conditions, anthropogenic activities and climate change. We analyzed data for 258 springs from the whole Kashmir valley using water quality index (WQI) and geographic information system techniques. WQI ranged from 23 (excellent water) to 537 (water unsuitable for drinking). The WQI indicated that 39.5% of the springs had excellent waters, 47.7% had good water, 5% had poor water, 1.6% had very-poor water, and 6.2% of the springs had water unfit for drinking purposes. The Piper diagram identified Ca-Mg-HCO_3, Ca-Mg-SO_4, and Na-HCO₃ as the most predominant hydro-chemical facies, whereas Gibbs diagram revealed that the water of springs in the study region is mainly controlled by rock weathering dominance. The results of the study offer inputs about the water quality to be used by the concerned departments and agencies at a bigger scale for drinking purposes. Our findings therefore suggest that springs which are in thousands in Kashmir landscape have the potential to offer viable solution to the rising drinking water demand and therefore merit an attention for their protection and management.

Aosta Valley Mountain Springs: A Preliminary Analysis for Understanding Variations in Water Resource Availability under Climate Change

The availability of freshwater resources in mountain areas has been affected by climate change impacts on groundwater storage mechanisms. As a web of complex interactions characterizes climate systems, understanding how water storage conditions have changed in response to climate-driven factors in different Italian contexts is becoming increasingly crucial. In order to comprehend the relationship between changes in weather conditions and water availability in the Aosta Valley region and how their trends have changed over the last decade, a 7-year discharge series of different Aosta Valley springs (Promise, Alpe Perrot, Promiod, Cheserod) and precipitation data are analysed. Precipitation and flow rate trends using the Mann–Kendall and Sen’s slope trend detection tests were also performed. Not all of the Aosta Valley mountain springs detected seem to respond to the climate variation with a decrease in their stored water resources. Unlike Promiod, Alpe Perrot, Cheserod, and Promise springs have experienced an increase in water discharged amount during the detected 7-year period. This behavior occurs despite the available precipitation data for the associated Sant Vincent, Aymaville-Viayes, La Thuile-Villaret, Champdepraz meteorological stations revealing an overall decreasing trend in annual rainfall (mm), with a slight increase in intensity (mm/day) as a result of the reduction in rainfall events (number of rainy days).

Water Availability for Biorefineries in the Contiguous United States and the Implications for Bioenergy Production Distribution

Renewable biofuel production depends on many factors, including feedstock availability, refinery and shipment infrastructure, and in particular, water availability. This study assesses water requirement and availability for mainstream biorefinery technologies in the contiguous United States (CONUS). The assessment is conducted in newly defined spatial units, namely, biorefinery planning boundaries, considering feedstock availability, transportation cost, and refinery capacity requirement for cost-effectiveness. The results suggest that the total biorefinery water use in the CONUS by 2030 will be low compared to the total water availability. However, biorefinery water requirements can aggravate the water stress situation in many regions, including the Great Plains, California Central Valley, and the upper Columbia-Snake River basin in Washington. Bioenergy productions in these regions can be largely constrained by water. It is projected that biofuel production will concentrate in Northern Plains, Lake States, and Corn Belt regions, which contribute 94.4% of the conventional, 86.1% of biodiesel, and 54.8% of cellulosic biofuel production mandated by the renewable fuel standard. If biorefineries are constrained to use less than 10% of the locally available water, up to 7% of planned cellulosic biofuel production will be affected. Findings from this study can aid the sustainable planning of national bioenergy production.

Deep learning shows declining groundwater levels in Germany until 2100 due to climate change

In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21^st century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites well distributed over Germany to assess the groundwater level development under different RCP scenarios (2.6, 4.5, 8.5). We consider only direct meteorological inputs, while highly uncertain anthropogenic factors such as groundwater extractions are excluded. While less pronounced and fewer significant trends can be found under RCP2.6 and RCP4.5, we detect significantly declining trends of groundwater levels for most of the sites under RCP8.5, revealing a spatial pattern of stronger decreases, especially in the northern and eastern part of Germany, emphasizing already existing decreasing trends in these regions. We can further show an increased variability and longer periods of low groundwater levels during the annual cycle towards the end of the century.

Competency of groundwater recharge of irrigated cotton field subjacent to sowing methods, plastic mulch, water productivity, and yield under climate change

Irrigated agriculture is a foremost consumer of water resources to fulfill the demand for food and fiber with an increasing population under climate changes; cotton is no exception. Depleting groundwater recharge and water productivity is critical for the sustainable cotton crop yield peculiarly in the semiarid region. This study investigated the water productivity and cotton yield under six different treatments: three sowing methods, i.e., flat, ridge, and bed planting with and without plastic mulch. Cotton bed planting without mulch showed maximum water productivity (0.24 kg.m-3) and the highest cotton yield (1946 kg.ha-1). Plastic mulching may reduce water productivity and cotton yield. HYDRUS-1D unsaturated flow model was used to access the groundwater recharge for 150 days under six treatments after model performance evaluation. Maximum cumulative recharge was observed 71 cm for the flat sowing method without plastic mulch. CanESM2 was used to predict climate scenarios for RCP 2.6, 4.5, and 8.5 for the 2050s and 2080s by statistical downscale modeling (SDSM) using historical data from 1975 to 2005 to access future groundwater recharge flux. Average cumulative recharge flux declined 36.53% in 2050 and 22.91% in 2080 compared to 2017 without plastic mulch. Multivariate regression analysis revealed that a maximum 23.78% reduction in groundwater recharge could influence future climate change. Further study may require to understand the remaining influencing factor of depleting groundwater recharge. Findings highlight the significance of climate change and the cotton sowing method while accessing future groundwater resources in irrigated agriculture.

Integrated Hydrological Modeling to Analyze the Effects of Precipitation on Surface Water and Groundwater Hydrologic Processes in a Small Watershed

The main objective of this study is to evaluate the performance of the integrated hydrological model, MIKE SHE in a small watershed to analyze the effect of two different precipitation sources on model outputs (groundwater elevation and surface water flows). The model was calibrated and validated with observed groundwater elevations and surface water flows measured at the United States Geological Survey (USGS) gage stations in the basin. The model calibration performance for surface water flows (R = 0.80, MAE= 0.20 m3/s, BIAS = −0.14 m3/s, NSE = 0.59) and groundwater elevations (R = 0.74, MAE = 0.45 m, BIAS = 0.08 m, NSE = 0.35) showed that the model was able to predict hydrological processes based on forcing variables in a small watershed. The analysis did not show the model with precipitation at the nearer (NOAA-Edwardsville) gauge station has better performance than the farther gauge station (NOAA-St. Louis). The quantitative analyses for the most sensitive model output variable suggested that precipitation uncertainties had noticeable impacts on surface water flows (0.81% to 11.19%), than groundwater elevations (0.06% to 0.07%), with an average of 6.71% and 0.66%, respectively. Our results showed noticeable differences in simulated surface water flows in spring (12.9%) and winter (36%) seasons compared to summer (11.4%) and fall (4.6%) as a result of difference (6% to 18%) in precipitation, which indicated that uncertainties in precipitation impact simulated surface water flows in a small watershed vary with different seasons. Our analyses have shown that precipitation affects the simulated hydrological processes and care should be taken while selecting input datasets (i.e., precipitation) for better hydrological model performance, specifically for surface water flows.

Hydrogeochemical characterizations and quality evaluation of groundwater in the major river basins of a geologically and anthropogenically driven semi-arid tract of India

Access to clean drinking water has been acknowledged as a human right and assessing the hydrogeochemistry and groundwater quality status plays an important role in proving cleaner and safer water for human consumption. This study evaluated the sources and driving factors of the groundwater facies in the five major river basins (viz. Ajay, Mayurakshi, Kopai, Brahmani and Dwarka) of an agroeconomic semi-arid Indian tract through hydrogeochemical and principal component analyses based on 2200 groundwater samples (N_s = 2200) obtained during the pre- and post-monsoon cycles from 1100 wells (N_w = 1100). The results revealed that minerals weathering, ion/reverse ion exchange, mixing and evaporation processes along with anthropogenic inputs are responsible for the deteriorated groundwater quality of the river basins. The study has considered the cokriging approach that uses geostatistical and multivariate statistical techniques to interpolate a dataset. To determine the spatio-seasonal variabilities of the groundwater facies more accurately, the estimation accuracies of different interpolation techniques viz. inverse distance weighting, kriging/cokriging and splines techniques were compared and kriging/cokriging was found to represent the variability more accurately. Shannon's entropy theory was employed to assess the groundwater quality of the river basins as it eliminates the subjective bias and inherent uncertainties of the groundwater systems. Groundwater in ~37.45-38.42% of the total area was moderate to extremely poor for human consumption where 10.40-12.14%, 9.09-12.40%, 21.18-22.35%, 15.20-19.93% and 6.48-8.80% samples from the Ajay (N_w = 175), Brahmani (N_w = 175), Dwarka (N_w = 180), Kopai (N_w = 350) and Mayurakshi (N_w = 220) river basins exhibited unfit to drink water quality. The sensitivity of the water quality model was analyzed to identify the influences of the individual parameters which revealed that the outcome does not depend solely on one parameter. The study recommends adaptation of the treatment techniques to ensure clean drinking water for the residents. Managed aquifer recharge techniques might also improve the groundwater quality in certain areas.

Dynamic Changes in Groundwater Level under Climate Changes in the Gnangara Region, Western Australia

The groundwater-dependent ecosystem in the Gnangara region is confronted with great threats due to the decline in groundwater level since the 1970s. The aim of this study is to apply multiple trend analysis methods at 351 monitoring bores to detect the trends in groundwater level using spatial, temporal and Hydrograph Analysis: Rainfall and Time Trend models, which were applied to evaluate the impacts of rainfall on the groundwater level in the Gnangara region, Western Australia. In the period of 1977–2017, the groundwater level decreased from the Gnangara’s edge to the central-north area, with a maximum trend magnitude of −0.28 m/year. The groundwater level in 1998–2017 exhibited an increasing trend in December–March and a decreasing trend in April–November with the exception of September when compared to 1978–1997. The rainfall + time model based on the cumulative annual residual rainfall technique with a one-month lag during 1990–2017 was determined as the best model. Rainfall had great impacts on the groundwater level in central Gnangara, with the highest impact coefficient being 0.00473, and the impacts reduced gradually from the central area to the boundary region. Other factors such as pine plantation, the topography and landforms, the Tamala Limestone formation, and aquifer groundwater abstraction also had important influences on the groundwater level.

Evaluating firefly extinction risk: Initial red list assessments for North America

Fireflies are a family of charismatic beetles known for their bioluminescent signals. Recent anecdotal reports suggest that firefly populations in North America may be in decline. However, prior to this work, no studies have undertaken a systematic compilation of geographic distribution, habitat specificity, and threats facing North American fireflies. To better understand their extinction risks, we conducted baseline assessments according to the categories and criteria of the International Union for Conservation of Nature (IUCN) Red List for 132 species from the United States and Canada (approximately 79% of described species in the region). We found at least 18 species (14%) are threatened with extinction (e.g. categorized as Critically Endangered, Endangered, or Vulnerable) due to various pressures, including habitat loss, light pollution, and climate change (sea level rise and drought). In addition, more than half of the species (53%) could not be evaluated against the assessment criteria due to insufficient data, highlighting the need for further study. Future research and conservation efforts should prioritize monitoring and protecting populations of at-risk species, preserving and restoring habitat, gathering data on population trends, and filling critical information gaps for data deficient species suspected to be at risk.

Investigation of Groundwater Depletion in the State of Qatar and Its Implication to Energy Water and Food Nexus

Groundwater is a precious freshwater resource heavily relied upon by agricultural activities in many parts of the world, and especially by countries with limited water resources located in arid regions. Groundwater resources are under severe pressures due to population increase, urbanisation and socio-economic development, with potential for causing long-term threats to human life and natural ecosystems. This study attempts to investigate the impacts of local and regional climatic trends, and establish key forcing functions that have changed local groundwater resources. The main questions answered through this study include: Are these changes beneficial or detrimental? If they are detrimental, what is the future outlook for impacts on the ecosystem? What are the corrective actions needed to avert the long-term risks in arid environments? In view of this, the methodology developed in this study focuses on a joint time-series statistical analysis using ground data as well as Gravity Recovery and Climate Experiment (GRACE) satellite data. Results show a substantial depletion in the groundwater thickness (0.24 ± 0.20 cm/year) during the period of observation (2002–2020). Long-term temperature data indicates that the annual mean temperature increased significantly by 1.02 °C between 1987 and 2016, while total rainfall exhibited a slight decreasing trend. In addition to groundwater extraction, fluctuations in monthly rainfall, soil moisture, evapotranspiration and relative humidity support the groundwater thickness reduction of GRACE datasets. The use of desalinated water and wastewater reuse in the agriculture sector may reduce the pressure on groundwater resources. Optimization, adaptation and mitigation in the EWF nexus will further improve the sustainability of the EWF resources.

Optimization of Groundwater Exploitation in an Irrigation Area in the Arid Upper Peacock River, NW China: Implications for Sustainable Agriculture and Ecology

Groundwater is the main irrigation water source in the Upper Peacock River. As fast enlargement of irrigation areas continues in recent years, the groundwater level declines continuously and has posed a threat to the sustainability of local agriculture and ecology. A numerical model was established with the code MODFLOW–2000 in order to predict the declining trend of groundwater level and formulate measures to counter the overexploitation, in which the river–aquifer interaction was elaborated and characterized by field survey. The results show that under current intensity of groundwater withdrawal, the levels of both unconfined and confined waters would decline continuously in 7 years from 2015. To stop the groundwater level from declining on the regional scale, the withdrawal rate should be compressed by 45% with respect to that in 2015. Moreover, taking consideration of the constraint of maintaining the ecological water level in the vicinity of the Euphrates Poplar forest in the study area, the withdrawal rate should be compressed 70% for seven towns around the forest.

An In-Depth Analysis of Physical Blue and Green Water Scarcity in Agriculture in Terms of Causes and Events and Perceived Amenability to Economic Interpretation

An analytical review of physical blue and green water scarcity in terms of agricultural use, and its amenability to economic interpretation, is presented, employing more than 600 references. The main definitions and classifications involved and information about reserves and resources are critically analyzed, blue and green water scarcity are examined along with their interchange, while their causal connection with climate in general is analyzed along with the particular instances of Europe, Africa, Asia and the WANA region. The role of teleconnections and evaporation/moisture import-export is examined as forms of action at a distance. The human intervention scarcity driver is examined extensively in terms of land use land cover change (LULCC), as well as population increase. The discussion deals with following critical problems: green and blue water availability, inadequate accessibility, blue water loss, unevenly distributed precipitation, climate uncertainty and country level over global level precedence. The conclusion singles out, among others, problems emerging from the inter-relationship of physical variables and the difficulty to translate them into economic instrumental variables, as well as the lack of imbedding uncertainty in the underlying physical theory due to the fact that country level measurements are not methodically assumed to be the basic building block of regional and global water scarcity.

Unraveling the drivers of intensified landslide regimes in Western Ghats, India

The Western Ghats (WG) mountain range in the Indian sub-continent is a biodiversity hotspot, now faces a severe threat to the valley population and ecosystem because of changing rainfall patterns and land-use changes. Here, we use the 2018-2019 landslide inventory data together with various geo-environmental factors and show that the landslide activity in the WG region is amplified by anthropogenic disturbances. We applied a generalized feature selection algorithm and a random forest susceptibility model to demonstrate the major topographic controls of landslides and the risk associated with them in the WG region. Our results show that road cutting and slopes modified to plantations are the strongest environmental variable (50% - 73% within 300 m buffer distance) related to the landslide patterns, whereas short-duration intense precipitation in the high elevated terrain, profile concavity, and stream power contributed to the initiation of landslides. The susceptibility models made for the present, and Global Climate Models (GCM) under the representative concentration pathway (RCP) 8.5 scenario predicts the vulnerable nature of WG for future climate extremes. Our results highlight the impacts of Anthropocene hazards and sensitivity of the WG ecosystem, and a greater focus therefore should be placed to reduce the vulnerability and increase preparedness for future events.

Evaluation of Climate Change Impact on Groundwater Recharge in Groundwater Regions in Taiwan

Climate change can directly or indirectly influence groundwater resources. The mechanisms of this influence are complex and not easily quantified. Understanding the effect of climate change on groundwater systems can help governments adopt suitable strategies for water resources. The baseflow concept can be used to relate climate conditions to groundwater systems for assessing the climate change impact on groundwater resources. This study applies the stable baseflow concept to the estimation of the groundwater recharge in ten groundwater regions in Taiwan, under historical and climate scenario conditions. The recharge rates at the main river gauge stations in the groundwater regions were assessed using historical data. Regression equations between rainfall and groundwater recharge quantities were developed for the ten groundwater regions. The assessment results can be used for recharge evaluation in Taiwan. The climate change estimation results show that climate change would increase groundwater recharge by 32.6% or decrease it by 28.9% on average under the climate scenarios, with respect to the baseline quantity in Taiwan. The impact of climate change on groundwater systems may be positive. This study proposes a method for assessing the impact of climate change on groundwater systems. The assessment results provide important information for strategy development in groundwater resources management.

Simplified Method for the In Situ Collection and Laboratory Analysis of Cosmogenic Tracers (Sulfur-35 and Sodium-22) to Determine Residence Time Distributions and Water Ages

The use of cosmogenically produced sulfur-35 (T_1/2 = 87 days) and sodium-22 (T_1/2 = 2.6 years) as intrinsic tracers can provide valuable information on catchment hydrology, flow paths, and subsurface storage. A new and straightforward method was created to determine the activities of both ³⁵S and ²²Na in various water sources by pumping large volumes (up to 1000 L) of water through cation- and anion-exchange resin columns in the field to collect sodium and sulfate ions and simple chemistry in the lab. Samples are counted for ³⁵S using liquid scintillation counting (LSC) and for ²²Na via γ spectroscopy. Our novel in situ method provides faster sample throughput as well as better counting statistics and lower detection limits. Both methods were successfully applied at the Southern Sierra Critical Zone Observatory.

Reliable Evapotranspiration Predictions with a Probabilistic Machine Learning Framework

Evapotranspiration is often expressed in terms of reference crop evapotranspiration (ETo), actual evapotranspiration (ETa), or surface water evaporation (Esw), and their reliable predictions are critical for groundwater, irrigation, and aquatic ecosystem management in semi-arid regions. We demonstrated that a newly developed probabilistic machine learning (ML) model, using a hybridized “boosting” framework, can simultaneously predict the daily ETo, Esw, & ETa from local hydroclimate data with high accuracy. The probabilistic approach exhibited great potential to overcome data uncertainties, in which 100% of the ETo, 89.9% of the Esw, and 93% of the ETa test data at three watersheds were within the models’ 95% prediction intervals. The modeling results revealed that the hybrid boosting framework can be used as a reliable computational tool to predict ETo while bypassing net solar radiation calculations, estimate Esw while overcoming uncertainties associated with pan evaporation & pan coefficients, and predict ETa while offsetting high capital & operational costs of EC towers. In addition, using the Shapley analysis built on a coalition game theory, we identified the order of importance and interactions between the hydroclimatic variables to enhance the models’ transparency and trustworthiness.

Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.