Deep learning insights into spatial patterns of stable isotopes in Iran's precipitation: a novel approach to climatological mapping.

Stable isotope techniques are precise methods for studying various aspects of hydrology, such as precipitation characteristics. However, understanding the variations in the stable isotope content in precipitation is challenging in Iran due to numerous climatic and geographic factors. To address this, forty-two precipitation sampling stations were selected across Iran to assess the fractional importance of these climatic and geographic parameters influencing stable isotopes. Additionally, deep learning models were employed to simulate the stable isotope content, with missing data initially addressed using the predictive mean matching (PMM) method. Subsequently, the recursive feature elimination (RFE) technique was applied to identify influential parameters impacting Iran's precipitation stable isotope content. Following this, long short-term memory (LSTM) and deep neural network (DNN) models were utilized to predict stable isotope values in precipitation. Interpolated maps of these values across Iran were developed using inverse distance weighting (IDW), while an interpolated reconstruction error (RE) map was generated to quantify deviations between observed and predicted values at study stations, offering insights into model precision. Validation using evaluation metrics demonstrated that the model based on DNN exhibited higher accuracy. Furthermore, RE maps confirmed acceptable accuracy in simulating the stable isotope content, albeit with minor weaknesses observed in simulation maps. The methodology outlined in this study holds promise for application in regions worldwide characterized by diverse climatic conditions.

How much rainwater contributes to a spring discharge in the Guarani Aquifer System: insights from stable isotopes and a mass balance model.

Outcrops play an important role in groundwater recharge. Understanding groundwater origins, dynamics and its correlation with different water sources is essential for effective water resources management and planning in terms of quantity and quality. In the case of the Guarani Aquifer System (GAS) outcrop areas are particularly vulnerable to groundwater pollution due to direct recharge processes. This study focuses on the Alto Jacaré-Pepira sub-basin, a watershed near Brotas, a city in the central region of the state of São Paulo, Brazil, where groundwater is vital for supporting tourism, agriculture, urban water supply, creeks, river and wetlands. The area has a humid tropical climate with periods of both intense rainfall and drought, and the rivers remain perennial throughout the year. Therefore, the aim of this study is to investigate the interconnections between a spring and its potential sources of contribution, namely rain and groundwater, in order to elucidate the relationships between the different water sources. To achieve this, on-site monitoring of groundwater depth, rainfall amount, and stable isotope ratios (deuterium (2H) and oxygen-18 (18O)) from rain, spring discharge, and a monitoring well was carried out from 2013 to 2021. The results indicate that the mean and standard deviations for δ18O in rainwater exhibit higher variability, resulting in -4.49 ± 3.18 ‰ VSMOW, while δ18O values from the well show minor variations, similar to those of the spring, recording -7.25 ± 0.32 ‰ and -6.94 ± 0.28 ‰ VSMOW, respectively. The mixing model's outcomes reveal seasonal variations in water sources contribution and indicate that groundwater accounts for approximately 80 % of spring discharge throughout the year. Incorporating stable isotopes into hydrological monitoring provides valuable data for complementing watershed analysis. The values obtained support the significance of the aquifer as a primary source, thereby offering critical insights into stream dynamics of the region.

The role of hyetograph shape and designer subjectivity in the design of an urban drainage system.

Even though it has been established that a hyetograph's shape affects the results of hydrological simulations, common engineering practice does not always account for this fact. Instead, a single design storm is often considered sufficient for designing a urban drainage system. This study examines the impact that this design paradigm, combined with the uncertainty introduced by subjective choices made during the design process, has on the robustness of a designed system. To do so, we evaluated a set of individual designs created by engineering students using the same Chicago hyetograph as a design storm. We then created ensembles of hyetographs with the same precipitation volume and duration as the Chicago hyetograph and evaluated the designs' hydrological responses. The results showed that designs, which performed equally well for the initial design storm, triggered varying responses for the storms in the ensembles and, consequently, showed different levels of robustness, hinting at a need to adapt the current design approach.

Hydrologic variability governs GHG emissions in rice-based cropping systems of Eastern India.

Reducing methane (CH4) emissions is increasingly recognized as an urgent greenhouse gas mitigation priority for avoiding ecosystem 'tipping points' that will accelerate global warming. Agricultural systems, namely ruminant livestock and rice cultivation are dominant sources of CH4 emissions. Efforts to reduce methane from rice typically focus on water management strategies that implicitly assume that irrigated rice systems are consistently flooded and that farmers exert a high level of control over the field water balance. In India most rice is cultivated during the monsoon season and hydrologic variability is common, particularly in the Eastern Gangetic Plains (EGP) where high but variable rainfall, shallow groundwater, and subtle differences in topography interact to create complex mosaics of field water conditions. Here, we characterize the hydrologic variability of monsoon season rice fields (n = 207) in the Indian EGP ('Eastern India') across two contrasting climate years (2021, 2022) and use the Denitrification Decomposition (DNDC) model to estimate GHG emissions for the observed hydrologic conditions. Five distinct clusters of field hydrology patterns were evident in each year, but cluster characteristics were not stable across years. In 2021, average GHG emissions (8.14 mt CO2-eq ha-1) were twice as high as in 2022 (3.81 mt CO2-eq ha-1). Importantly, intra-annual variability between fields was also high, underlining the need to characterize representative emission distributions across the landscape and across seasons to appropriately target GHG mitigation strategies and generate accurate baseline values. Simulation results were also analyzed to identify main drivers of emissions, with readily identified factors such as flooding period and hydrologic interactions with crop residues and nitrogen management practices emerging as important. These insights provide a foundation for understanding landscape variability in GHG emissions from rice in Eastern India and suggest priorities for mitigation that honor the hydrologic complexity of the region.

New directions for malaria vector control using geography and geospatial analysis.

As we strive towards the ambitious goal of malaria elimination, we must embrace integrated strategies and interventions. Like many diseases, malaria is heterogeneously distributed. This inherent spatial component means that geography and geospatial data is likely to have an important role in malaria control strategies. For instance, focussing interventions in areas where malaria risk is highest is likely to provide more cost-effective malaria control programmes. Equally, many malaria vector control strategies, particularly interventions like larval source management, would benefit from accurate maps of malaria vector habitats - sources of water that are used for malarial mosquito oviposition and larval development. In many landscapes, particularly in rural areas, the formation and persistence of these habitats is controlled by geographical factors, notably those related to hydrology. This is especially true for malaria vector species like Anopheles funestsus that show a preference for more permanent, often naturally occurring water sources like small rivers and spring-fed ponds. Previous work has embraced geographical concepts, techniques, and geospatial data for studying malaria risk and vector habitats. But there is much to be learnt if we are to fully exploit what the broader geographical discipline can offer in terms of operational malaria control, particularly in the face of a changing climate. This chapter outlines potential new directions related to several geographical concepts, data sources and analytical approaches, including terrain analysis, satellite imagery, drone technology and field-based observations. These directions are discussed within the context of designing new protocols and procedures that could be readily deployed within malaria control programmes, particularly those within sub-Saharan Africa, with a particular focus on experiences in the Kilombero Valley and the Zanzibar Archipelago, United Republic of Tanzania.

Water level regime variation is a crucial driver for taxonomic, functional, and phylogenetic diversity in seasonally flooded tropical forests.

Floodplains contribute significantly to terrestrial ecosystem service provision but are also among the most vulnerable and degraded ecosystems worldwide. Heterogeneity in floodplain properties arises from variations in river-specific flood regimes, watershed characteristics, and valley morphology, influencing seasonally flooded forests' taxonomic, functional, and phylogenetic diversity. This study addresses persisting knowledge gaps in floodplain ecology, focusing on the seasonally dry tropics. We explore the relationships between flood regime, environmental conditions, vegetation composition, functional and phylogenetic diversity, and the impact of environmental variables on above-ground biomass (AGB) and ecological strategies. The study spans six rivers in southeastern Brazil's main river basins: Rio Grande and São Francisco. We identified five eco-units in each floodplain based on flooding regimes and surveyed six plots per eco-unit. We measured trees with DBH > 5 cm and collected functional traits, along with detailed soil, climate, and water level data. We calculated plot-level floristic composition, taxonomic, functional, and phylogenetic diversity, wood density, and AGB. Functional and phylogenetic dissimilarity were analyzed, and the effects of climate, soil, and hydrological variables were quantified using generalized linear mixed models. We show how flood frequency and duration affect floristic composition across the floodplains. Taxonomic and phylogenetic diversity responded to climate, soil, and hydrological variables, while functional diversity responded primarily to hydrological variables, emphasizing the role of environmental filtering. Hydrological seasonality, soil fertility, and flood regime emerged as key factors shaping community structure and ecological strategies in the studied seasonally flooded tropical forests. Plot-level AGB responded to phosphorus but not to climate or hydrological variables. The study also highlights functional and phylogenetic dissimilarities among eco-units and basins, indicating potential climate change impacts.

Assessing methane emissions and soil carbon stocks in the Camargue coastal wetlands: Management implications for climate change regulation.

Coastal wetlands are crucial in climate change regulation due to their capacity to act as either sinks or sources of carbon, resulting from the balance between greenhouse gas (GHG) emissions, mainly methane (CH4), and soil carbon sequestration. Despite the paramount role of wetlands in climate regulation few studies investigate both aspects. The Camargue is one of the largest wetlands in Europe, yet the ways in which environmental and anthropic factors drive carbon dynamics remain poorly studied. We examined GHG emissions and soil organic carbon (SOC) stocks and accumulation rates in twelve representative wetlands, including two rice fields, to gain insights into the carbon dynamics and how it is influenced by hydrology and salinity. Mean CH4 rates ranged between - 87.0 and 131.0 mg m-2 h-1and the main drivers were water conductivity and redox, water table depth and soil temperature. High emission rates were restricted to freshwater conditions during summer flooding periods whereas they were low in wetlands subjected to summer drought and water conductivity higher than 10 mS cm-1. Nitrous oxide emissions were low, ranging from - 0.5 to 0.9 mg N2O m-2 h-1. The SOC stocks in the upper meter ranged from 17 to 90 Mg OC ha-1. Our research highlights the critical role of low-saline wetlands in carbon budgeting which potentially are large sources of CH4 but also contain the largest SOC stocks in the Camargue. Natural hydroperiods, involving summer drought, can maintain them as carbon sinks, but altered hydrology can transform them into sources. Artificial freshwater supply during summer leads to substantial CH4 emissions, offsetting their SOC accumulation rates. In conclusion, we advocate for readjusting the altered hydrology in marshes and for the search of management compromises to ensure the compatibility of economic and leisure activities with the preservation of the inherent climate-regulating capacity of coastal wetlands.

Sharp decline in surface water resources for agriculture and fisheries in the Lower Mekong Basin over 2000-2020.

Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000-2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000-2020. In the floodplains of the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries over the period 2000-2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.

Seeking a pathway towards a more sustainable human-water relationship by coupled model - From a perspective of socio-hydrology.

It is essential to systematically consider social, economic, and natural endowments in managing and allocating water resources. However, few studies have comprehensively quantitatively evaluated the allocation of regional water resources from a socio-hydrology perspective and provided recommendations. To explore this research gap, we have constructed a tightly coupled framework that integrates system dynamics models and optimization algorithms to carry out an innovative redistribution of water resources in Shaanxi Province. The system dynamics model simulation results showed that the error was almost always within 10% over the research period, indicating robust simulation capability and laying a solid foundation for subsequent model coupling. The coupled model achieves convergence in approximately 30 generations by formulating the optimization problem with four individual objectives. Optimizing four objectives concurrently results in convergence around the 150th generation. The optimized Pareto solution sets visually demonstrate the trade-offs between different objectives. In the optimized water allocation schedule, the water consumption in Yulin exhibits a change of 1.22 ×108m3, reflecting the most significant optimization effects on agricultural and domestic water allocation. The results indicated that the comprehensive Gini coefficient typically ranged between 0.2 and 0.3. Over the period from the year 2010-2021, the Gini coefficient exhibited a declining trend, signifying a positive trajectory in water resource allocation throughout the research period and a high level of fairness. The annual total green WF of grain in Weinan was the highest at 14.26 ×108m3, followed by Xianyang at 9.52 ×108m3, and the lowest in Tongchuan at 0.54 ×108m3. The annual average amount of blue WF of grain is the highest in Hanzhong, at 11.33 ×108m3, followed by Weinan at 9.60 ×108m3, and the lowest in Tongchuan at 0.14 ×108m3. The coupled framework proposed in this study exhibits significant innovation, scalability, and practical efficiency. It can inspire future research and decision-making and holds the potential for application in other regions.

Factors controlling the water quality of rock glacier springs in European and American mountain ranges.

Rock glaciers (RGs) provide significant water resources in mountain areas under climate change. Recent research has highlighted high concentrations of solutes including trace elements in RG-fed waters, with negative implications on water quality. Yet, sparse studies from a few locations hinder conclusions about the main drivers of solute export from RGs. Here, in an unprecedented effort, we collected published and unpublished data on rock glacier hydrochemistry around the globe. We considered 201 RG springs from mountain ranges across Europe, North and South America, using a combination of machine learning, multivariate and univariate analyses, and geochemical modeling. We found that 35 % of springs issuing from intact RGs (containing internal ice) have water quality below drinking water standards, compared to 5 % of springs connected to relict RGs (without internal ice). The interaction of ice and bedrock lithology is responsible for solute concentrations in RG springs. Indeed, we found higher concentrations of sulfate and trace elements in springs sourcing from intact RGs compared to water originating from relict RGs, mostly in specific lithological settings. Enhanced sulfide oxidation in intact RGs is responsible for the elevated trace element concentrations. Challenges for water management may arise in mountain catchments rich in intact RGs, and where the predisposing geology would make these areas geochemical RG hotspots. Our work represents a first comprehensive attempt to identify the main drivers of solute concentrations in RG waters.

Creating sustainable capacity for river science in the Congo basin through the CRuHM project.

In this article, we examine the scientific and sustainable research capacity outcomes of the 'Congo River: user Hydraulics and Morphology' or CRuHM project, a six-year effort supported by the Royal Society's Africa Capacity Building Initiative. This project brought together a consortium of African and UK universities to undertake the first large-scale scientific expeditions to the Congo basin of the modern era in order to better understand the hydraulics and geomorphology of this understudied but globally important river. The river is essential for navigation, irrigation, drinking water and hydroelectric power generation for the 10 basin countries and is critically important for biodiversity and global nutrient, carbon and climatological cycles. This article summarizes the new scientific understanding contributed by the project and the steps taken to ensure a meaningful legacy that would continue long beyond the finite lifetime of available funding. Actions taken to achieve this include establishing a new hydrology research centre at the University of Kinshasa as well as steps to build a wider international community of Congo basin researchers. In this way, we hope to build momentum for future funding initiatives and collaboration.

Moisture availability and groundwater recharge paced by orbital forcing over the past 750,000 years in the southwestern USA.

Quaternary climate changes are driven in part by variations in the distribution and strength of insolation due to orbital parameters. Continental climate variability is well documented for the most recent glacial-interglacial cycles, yet few records extend further back in time. Such records are critically needed to comprehensively assess the entire spectrum of natural climate variability against the backdrop of anthropogenic warming. Here, we apply uranium isotope geochronology to calcite deposits to date groundwater-table changes in Devils Hole cave, Nevada. The deposits record multi-meter groundwater-table fluctuations over the last 750,000 years, reflecting the long-term evolution of hydroclimate in this presently arid region. During periods between glacial or interglacial extremes, the water table responded sensitively to variations in 65°N summer insolation, likely caused by the increasing extent of North American ice sheets during cold period, which steered moisture-laden trajectories towards the southwestern USA. These orbitally-driven hydroclimatic changes are superimposed on a tectonically-driven long-term decline in the regional groundwater table observed prior to 438,000 ± 14,000 years ago.

Human-made small reservoirs alter dryland hydrological connectivity.

Our research shed light on the distribution, number, and impact of small reservoirs (SRs) on rural dryland water availability and hydrology. We measured the storage capacity, relationship to environmental variables, and effects on the hydrology of all SRs (1225) found within a Sonoran Desert basin. SRs were predominantly associated with Tertiary conglomerates and Quaternary alluvium and were less common in extrusive rocks. A higher concentration of reservoirs was observed in woodlands and thornscrub, with fewer SRs in desertscrub than anticipated by chance. The average size of these small reservoirs was 5205 m2. All SRs reached full storage capacity during the rainy season, but only 20 % retained water throughout the year. Furthermore, our analysis revealed a significant impact on basin connectivity, with only 41 % of superficial drainage being connected. Notably, two large dams were found to disconnect 26 % of the basin. Despite their relatively small watershed footprint, SRs were found to be responsible for disconnecting 33 % of the total basin area. The magnitude of rainfall events played a crucial role in connectivity dynamics. Low-magnitude rainfall events led to sediment retention in SRs, reducing connectivity, while moderate events increased connectivity by repeatedly filling SRs. High-magnitude events reshaped channels, transported sediments, and enhanced overall connectivity. The concentration of SRs in the upper reaches of the basin coincides with higher stocking rates. SRs, are relatively recent additions to desert landscapes, impacting ecological dynamics. Their construction and use fragment an already disjointed basin, thereby restricting water retention by larger dams. These findings emphasize the intricate relationship between SRs, rainfall occurrences, and the overall connectivity of the basin. We underline that documenting the cumulative effects of SRs yields valuable insights for managing water resources in arid ecosystems.

Enhancing the SWAT model for creating efficient rainwater harvesting and reuse strategies to improve water resources management.

Rain barrels/cisterns are a type of green infrastructure (GI) practice that can help restore urban hydrology. Roof runoff captured and stored by rain barrels/cisterns can serve as a valuable resource for landscape irrigation, which would reduce municipal water usage and decrease runoff that other stormwater infrastructures need to treat. The expected benefits of rainwater harvesting and reuse with rain barrels/cisterns are comprehensive but neither systematically investigated nor well documented. A comprehensive tool is needed to help stakeholders develop efficient strategies to harvest rainwater for landscape irrigation with rain barrels/cisterns. This study further improved the Soil and Water Assessment Tool (SWAT) in simulating urban drainage networks by coupling the Storm Water Management Model (SWMM)'s closed pipe drainage network (CPDN) simulation methods with the SWAT model that was previously improved for simulating the impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns. The newly improved SWAT or SWAT-CPDN was applied to simulate the urban hydrology of the Brentwood watershed (Austin, TX) and evaluate the long-term effects of rainwater harvesting for landscape irrigation with rain barrels/cisterns at the field and watershed scales. The results indicated that the SWAT-CPDN could improve the prediction accuracy of urban hydrology with good performance in simulating discharges (15 min, daily, and monthly), evapotranspiration (monthly), and leaf area index (monthly). The impacts of different scenarios of rainwater harvesting and reuse strategies (rain barrel/cistern sizes, percentages of suitable areas with rain barrels/cisterns implemented, auto landscape irrigation rates, and landscape irrigation starting times) on each indicator (runoff depth, discharge volume, peak runoff, peak discharge, combined sewer overflow-CSO, freshwater demand, and plant growth) at the field or watershed scale varied, providing insights for the long-term multi-functional impacts (stormwater management and rainwater harvesting/reuse) of rainwater harvesting for landscape irrigation with rain barrels/cisterns. The varied rankings of scenarios found for achieving each goal at the field or watershed scale indicated that tradeoffs in rainwater harvesting and reuse strategies exist for various goals, and the strategies should be evaluated individually for different goals to optimize the strategies. Efficient rainwater harvesting and reuse strategies at the field or watershed scale can be created by stakeholders with the assist of the SWAT-CPDN to reduce runoff depth, discharge volume, peak runoff, peak discharge, CSO, and freshwater demand, as well as improve plant growth.

Advances in modern Balneology: new evidence-based indications from recent studies.

Balneotherapy (BT) is a therapeutic approach that utilizes various forms of water-based treatments to promote health and well-being. BT possesses a rich historical heritage and has garnered recognition from esteemed institutions such as the World Health Organization (WHO). Recent scientific research enables the identification of relevant diseases (obesity, metabolic diseases, sleep disorders, mental health conditions, Long-COVID-19, and cancer rehabilitation) that could potentially benefit from balneo-therapeutic treatments, thereby presenting new avenues of opportunity for SPA ("Salus per Aquam") medicine. These conditions exemplify the potential benefits of BT for ailments beyond the traditional scope of treatment associated with BT (most commonly osteoarthritis, fibromyalgia, rheumatic back pain, and chronic inflammatory respiratory or skin disorders). Overall, the current scientific evidence suggests that BT holds significant potential for enhancing both individual wellbeing and public health. However, further high-quality clinical trials are essential to corroborate these preliminary findings and to provide critical insights into the therapeutic benefits of BT, paving the way for its broader integration into healthcare practices and public health initiatives.

Balancing aquaculture and estuarine ecosystems: machine learning-based water quality indices for effective management.

This study delves into the environmental impact of inland aquaculture on estuarine ecosystems by examining the water quality of four estuarine streams within the key inland aquaculture zone of South India. In this region, extensive and intensive aquaculture practices are common, posing potential challenges to estuarine health. The research explores the predictive capabilities of the Gaussian elimination method (GEM) and machine learning techniques, specifically multi-linear regression (MLR) and support vector regressor (SVR), in forecasting the water quality index of these streams. Through comprehensive evaluation using performance metrics such as coefficient of determination (R2) and average mean absolute percentage error (MAPE), MLR and SVR demonstrate higher prediction efficiency. Notably, employing key water parameters as inputs in machine learning models is also more effective. Biochemical oxygen demand (BOD) emerges as a critical water parameter, identified by both MLR and SVR, exhibiting high specificity in predicting water quality. This suggests that MLR and SVR, incorporating key water parameters, should be prioritized for future water quality monitoring in intensive aquaculture zones, facilitating timely warnings and interventions to safeguard water quality.

The response of non-point source pollution to climate change in an orchard-dominant coastal watershed.

China is the largest global orchard distribution area, where high fertilization rates, complex terrain, and uncertainties associated with future climate change present challenges in managing non-point source pollution (NPSP) in orchard-dominant growing areas (ODGA). Given the complex processes of climate, hydrology, and soil nutrient loss, this study utilized an enhanced Soil and Water Assessment Tool model (SWAT-CO2) to investigate the impact of future climate on NPSP in ODGA in a coastal basin of North China. Our investigation focused on climate-induced variations in hydrology, nitrogen (N), and phosphorus (P) losses in soil, considering three Coupled Model Intercomparison Project phase 6 (CMIP6) climate scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Research results indicated that continuous changes in CO2 levels significantly influenced evapotranspiration (ET) and water yield in ODGA. Influenced by sandy soils, nitrate leaching through percolation was the principal pathway for N loss in the ODGA. Surface runoff was identified as the primary pathway for P loss. Compared to the reference period (1971-2000), under three future climate scenarios, the increase in precipitation of ODGA ranged from 15% to 28%, while the growth rates of P loss and surface runoff were the most significant, both exceeding 120%. Orchards in the northwest basin proved susceptible to nitrate leaching, while others were more sensitive to N and P losses via surface runoff. Implementing targeted strategies, such as augmenting organic fertilizer usage and constructing terraced fields, based on ODGA's response characteristics to future climate, could effectively improve the basin's environment.

Field dataset of the depth to water from diverse wetland types in relation to habitat and soil.

Wetlands perform important functions and provide essential ecological services, including flood attenuation, groundwater recharge and discharge, and water purification. Human activities such as urban and rural development, drainage, and land alteration can cause major disturbances, often resulting in the drying up of wetlands. Therefore, many restoration projects aim to restore wetland hydrology. Hydrology significantly affects wetland functions by modifying and determining the wetlands physicochemical environment that allows for the development of a specific biota. Despite the importance of hydrology, monitoring efforts are mainly focused on surveying and characterizing wetland habitats or plant composition. There are few datasets available from the monitoring of the depth to water table (DTW) in wetlands and when available they are rarely shared. Collecting hydrological data can contribute to a better understanding of the relationship between hydrology, soil and habitat and can help understand the effect of climate change. From 2021 to 2023, depth to water table, soil and habitat data were collected across a variety of wetland types in France with a focus on hydrological data. Using data loggers placed in 37 monitoring wells across 17 wetlands, 469001 hourly depth to water table and water temperature data were collected. The dataset includes two files containing a total of 22 variables that describe the location of sites, habitat (EUNIS: European Nature Information System), soil hydromorphy, depth to water table, and water temperature. The dataset can be used to better understand wetland hydrology and its relationship to soil and habitat. The data collection process may be used to help restoration project achieve their goal.

Isotope hydrology of the intermontane Elk Valley, British Columbia: an assessment of water resources around coal mining operations.

This study aimed to synthesise and interpret stable isotopic data (δ2H and δ18O) from various sources to understand the isotope hydrology around coal mine operations in Elk Valley, B.C., Canada. The data, including precipitation, groundwaters, seeps, and mine rock drains, were used to construct a local meteoric water line (LMWL) for the Elk Valley, evaluate the spatiotemporal isotopic composition of its groundwater, and assess mine seepage and mine rock drain discharge. The study revealed a robust LMWL relation (δ2H = 7.4 ± 0.2 · δ18O - 4.3 ± 4.1). The groundwater and seep data indicated a winter season bias and a north-south latitudinal gradient, suggesting rapid near-surface groundwater flow without significant post-precipitation evaporation. Porewater isotope samples from unsaturated mine rock piles (MRPs) showed site-specific evaporation patterns, potentially due to convective air flows or exothermic sulphide oxidation. This research revealed the influence of groundwater and meltwater on rock drain discharge. Based on evaporative mass balance calculations, MRPs seasonally contributed ca. 5 %(December base flow) and 22 % (snowmelt) to drain discharge. The findings underscore the value of stable isotope data collections in the Elk Valley to help better define and quantify the hydrology-hydrogeology, including a better understanding of evaporative conditions in MRPs.