Water Resources Research Articles

Electrical resistivity tomography inversion combining deep variational autoencoder and stochastic adaptive sampling

Geophysical methods, such as electrical resistivity tomography (ERT), can be used to imaging the near-surface electrical resistivity as field measurements depend on the subsurface porosity, water saturation and fluid salinity. ERT has been widely applied to investigate mineral and groundwater resources, and in archaeological, environmental, and engineering studies. The prediction of subsurface electrical conductivity from ERT data requires solving a geophysical inverse problem. For near-surface characterization studies, this is often accomplished with deterministic inverse methods. These methods linearize the problem around an initial solution, and their smoothness depends on an imposed a priori spatial regularization term. Depending on this parameterization, these methodologies might struggle to capture the natural variability of the subsurface. Moreover, deterministic solutions have limited capabilities for uncertainty assessment. On the contrary, stochastic inverse methods can assess uncertainties by predicting multiple model realizations that fit similarly the recorded ERT data. However, they are often more computationally expensive than deterministic solutions. Deep learning algorithms based on deep generative models have been used to re-parametrize model and data spaces into low-dimensional domains and efficiently solve geophysical inverse problems. However, within this context, uncertainty assessment is challenging. We propose a deep convolutional variational autoencoder (VAE) coupled with stochastic adaptive optimization to perform stochastic ERT inversion. Geostatistical simulations of electrical resistivity are used as training data set of the VAE. After training, the VAE generates electrical resistivity models that reproduce the statistics and spatial continuity patterns of the training data set. Then, the VAE latent space is iteratively perturbed and updated with adaptive stochastic sampling based on the misfit between observed and predicted ERT data. The proposed methodology is illustrated in two-dimensional synthetic and real data sets to illustrate the ability of the proposed method to predict reliable electrical resistivity models while generating multiple possible scenarios for uncertainty assessment.

Groundwater resources: challenges and future opportunities

Groundwater resources: challenges and future opportunities

Water for Whom? Unravelling the Allocation of Water Storage Capacity between Irrigation and Electricity Uses in Spain during the 20th Century

This work explores the intricate dynamics of water management, energy generation, and irrigation in Spain by examining the evolving regulatory framework governing water resource allocation. It introduces a novel approach to quantify water usage and unpacks the ‘mixed uses’ category for the first time, focusing on entities holding water allocation concessions rather than mere dam ownership. Our f indings reveal the profound influence of private electricity companies on water resource management, despite the significant portion of state-owned dams. The results point to hydroelectric dominance in water allocation and underscore the complex interaction between public ownership and private management of electric companies. This research emphasises the need for nuanced policy considerations in the broader context of energy and agriculture while contributing to a richer understanding of Spain’s unique water governance landscape.

An integrated model approach for disaster impact reduction: lessons from a slow onset disaster in Chile

Purpose The prolonged drought in Chile’s Coquimbo region has created a permanent state of emergency, forcing the state to spend millions each year distributing drinking water to rural communities. The purpose of this article is to detail a study focused on optimizing the supply of drinking water through trucks in the 15 communes of the region and how the problem was faced in a context of a slowonset disaster. Design/methodology/approach A geo-referenced census and optimization analysis of the 5.541 households that receive drinking water was conducted to determine the feasibility of removing trucks from the system. To generate a greater reduction in distribution costs, it was suggested to incorporate water distribution infrastructure projects, changing the concept of ‘expenses’ to ‘investment’. Findings The study was born out of the concern for the increased demand for drinking water from rural areas. The proposed and implemented framework allowed an additional 20% reduction in the initial transportation costs; this confirmed the assumption that the proposed optimization model alone would not offer a robust solution and was complemented and integrated with this type of alternative, forming an “integrated model”. Research limitations/implications The paper has implications for the resilience of territories affected by climate change. Practical implications The methodology can be replicated in other areas where similar interactions occur. Social implications Families impacted by drought can improve their quality of life and reduce distress in the face of the constant emergency. Originality/value This research aims to contribute knowledge from the perspective of a slow-onset disaster where water resources are scarce. It presents a framework where two disciplines converge, resulting in an “integrated model” that, through its implementation, reduces the costs of resource delivery while simultaneously improving the sanitary conditions of the beneficiary families.

Innovative Strategy for Rainwater Harvesting in Saline-affected Urban Areas: A Case Study of a Sports Complex in Delhi

Water scarcity remains a critical global challenge, requiring immediate, sustainable management strategies, particularly in areas with an increasing disparity between water supply and demand. In India, and especially in Delhi, this issue is acute. In response to growing environmental concerns and the urgent need for sustainable water resource management, rainwater harvesting has emerged as a practical and effective solution for water conservation. This study investigates the application of rainwater harvesting to sustainably support water needs for a sports complex located in a salinity affected region. The land, originally intended for agriculture, has been converted into a complex featuring hydro-landscape facilities, including swimming pools, water polo areas, diving pools, toddler pools, and leisure pools. These facilities require an initial water input of 6,754.5 m³ and an annual replenishment of 7,957.28 m³ due to evaporation and seepage. By calculating the total rainwater harvesting potential based on the runoff coefficient, annual rainfall intensity, and the complex's catchment area, the study reveals that 29,693.8 m³ of rainwater can be harvested annually, providing a surplus of 14,981.7 m³ of potable water. This analysis demonstrates the viability of designing sports complexes in saline areas using efficient land use and rainwater harvesting, and presenting a scalable model for sustainable water management in similar regions worldwide.

Unveiling Groundwater Potential in Hangu District, Pakistan: A GIS-Driven Bivariate Modeling and Remote Sensing Approach for Achieving SDGs

Sustainable groundwater development stands out as a contemporary concern for growing global populations, particularly in stressed riverine arid and semi-arid regions. This study integrated satellite-based (Sentinel-2, ALOS-DEM, and CHIRPS rainfall) data with ancillary lithology and infrastructure datasets using Weight of Evidence (WoE) and Frequency Ratio (FR) models to delineate Groundwater Potential Zones (GWPZs) in the Hangu District, a hydrologically stressed riverine region in northern Pakistan, to support the Sustainable Development Goals (SDGs). Ten key variables, including elevation, slope, aspect, distance to drainage (DD), rainfall, land use/land cover, Normalized Difference Vegetation Index, lithology, and road proximity, were incorporated into the Geographic information system (GIS) environment. The FR model outperformed the WoE model, achieving success and prediction rates of 89% and 93%, compared to 82% and 86%. The GWPZs-FR model identified 23% (317 km2) as high potential, located in highly fractured pediment fans below 550 m, with gentle slopes (<5 degrees), DD (within 200 m), and high rainfall in areas of natural trees and vegetation on valley terrace deposits. The research findings significantly support multiple SDGs, with estimated achievement potentials of 37.5% for SDG 6 (Clean Water and Sanitation), 20% for SDG 13 (Climate Action), 15% for SDG 8 (Decent Work and Economic Growth), 12.5% for SDG 9 (Industry, Innovation, and Infrastructure), and notable contributions of 10% for SDG 2 and 5% for SDG 3. This approach provides valuable insights for policymakers, offering a framework for managing groundwater resources and advancing sustainable practices in similar hydrologically stressed regions.

Forecasting Gate-Front Water Levels Using a Coupled GRU–TCN–Transformer Model and Permutation Entropy Algorithm

Water level forecasting has significant impacts on transportation, agriculture, and flood control measures. Accurate water level values can enhance the safety and efficiency of water conservancy hub operation scheduling, reduce flood risks, and are essential for ensuring sustainable regional development. Addressing the nonlinearity and non-stationarity characteristics of gate-front water level sequences, this paper introduces a gate-front water level forecasting method based on a GRU–TCN–Transformer coupled model and permutation entropy (PE) algorithm. Firstly, an analysis method combining Singular Spectrum Analysis (SSA) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is used to separate the original water level data into different frequency modal components. The PE algorithm subsequently divides each modal component into sequences of high and low frequencies. The GRU model is applied to predict the high-frequency sequence part, while the TCN–Transformer combination model is used for the low-frequency sequence part. The forecasting from both models are combined to obtain the final water level forecasting value. Multiple evaluation metrics are used to assess the forecasting performance. The findings indicate that the combined GRU–TCN–Transformer model achieves a Mean Absolute Error (MAE) of 0.0154, a Root Mean Square Error (RMSE) of 0.0205, and a Coefficient of Determination (R2) of 0.8076. These metrics indicate that the model outperforms machine learning Support Vector Machine (SVM) models, GRU models, Transformer models, and TCN–Transformer combination models in forecasting performance. The forecasting results have high credibility. This model provides a new reference for improving the accuracy of gate-front water level forecasting and offers significant insights for water resource management and flood prevention, demonstrating promising application prospects.

A Novel Rainfall Classification for Mapping Rainwater Harvesting: A Case Study in Kalar, Iraq

Increasing water demand driven by population growth and climate change strains water resources, especially in arid regions. The effectiveness of rainwater harvesting (RWH) as a viable solution is contingent upon the meticulous selection of appropriate sites. Contemporary efforts have increasingly utilized Geographic Information Systems (GIS) and remote sensing technologies to optimize the identification of ideal locations for implementing RWH infrastructure. However, inconsistencies in rainfall classification methodologies can compromise the accuracy of the resulted suitability maps. Consequently, a standardized approach to grading rainfall depth for mapping RWH sites becomes imperative. This study presents an innovative rainfall classification method tailored for both micro and macro catchment areas, offering a reliable and adaptable approach to rainfall analysis. By refining classification criteria, this method aims to improve the consistency and precision of RWH mapping, addressing a gap in existing methodologies and providing a more standardized approach. Through the application of FAHP and Fuzzy overlay techniques in ArcGIS 10.4, the study compares traditional rainfall classification with the proposed new classification method to assess RWH suitability in Kalar. The comparison highlights that the new rainfall classification-based map yielded higher accuracy and realism compared to traditional methods.

Water resource vulnerability assessment in Hubei Province: a case study

Water resource vulnerability assessment in Hubei Province: a case study

Study on the Spatial–Temporal Variation of Groundwater Depth and Its Impact on Vegetation Coverage in Ejina Oasis

Ejina, a representative inland river basin situated in the arid region of northwest China, exhibits a delicate ecological environment and its vegetation coverage is intrinsically linked to regional ecological security. Based on MOD13Q1-NDVI data from 2018 to 2023 and groundwater depth monitoring data during the same period, this study analyzed the spatial–temporal variation characteristics of vegetation coverage and its relationship with groundwater depth in Ejina. It is found that the vegetation coverage in Ejina is generally low and mainly distributed along the riverbanks in the form of strips. During the study period, the overall trend of vegetation coverage showed a fluctuating pattern of first increasing and then decreasing, revealing the fragility of the regional ecology. The groundwater depth shows the characteristic of being higher in the east river than the west, and the trend of groundwater depth along the river flow is first increasing and then decreasing. The spatial groundwater depth indicates that the east river is higher than that of the west river, and the groundwater depth along the river flow first increases and then decreases. In terms of inter-annual changes, the groundwater depth experiences a process of first decreasing and then stabilizing. Further analysis indicates that vegetation growth and coverage in Ejina are significantly affected by water conditions, and areas with high Normalized Difference Vegetation Index (NDVI) values are mainly distributed along the riverbanks. In addition, there is a certain degree of correlation between groundwater depth and NDVI. When the depth of groundwater is too deep or too shallow, the positive correlation between NDVI and groundwater depth increases slightly and the negative correlation decreases slightly. The findings of this study are of great significance for understanding and predicting the response of vegetation coverage to groundwater changes in arid areas, and provide a scientific basis for water resources management and ecological protection in Ejina.

Analysis of Existing Area, Clean Water Treatment, and Distribution Network Evaluation in Nagari Magek, Agam Regency, West Sumatra

Nagari Magek Village in Agam Regency, West Sumatra, faces significant challenges in managing clean water resources. To address these challenges comprehensively, a holistic approach is essential, involving through area analysis, water treatment, and evaluation of distribution networks to ensure efficient and equitable water distribution. It is crucial to adhere to the principles of water resource conservation, utilization, and management as stipulated in Law Number 17 of 2019 on water resource management, which must be observed to ensure legal clarity in water management practices. The community service team handles clean water problems in Nagari Magek by designing a clean water treatment system that includes aeration, sedimentation, and filtration units. This process improves water quality by reducing yellowish color and eliminating unpleasant odors. However, the capacity of the treatment plant is not able to meet the increasing water demand, while the galvanized pipe distribution network has not been functioning optimally. Based on simulations using EPANET 2.2 software, it was found that the water flow speed in the pipes was still below the optimal range due to the diameter of the pipes being too large. The solution applied was to increase the processing discharge to 10 L/s (0,01 m3/s), which succeeded in increasing the flow rate according to the regulatory criteria. This recommendation improves the efficiency of the distribution system and ensures better water quality for the people in Nagari Magek.

Geospatially Informed Water Pricing for Sustainability: A Mixed Methods Approach to the Increasing Block Tariff Model for Groundwater Management in Arid Regions of Northwest Bangladesh

Groundwater depletion in arid regions poses a significant threat to agricultural sustainability and rural livelihoods. This study employs geospatial analysis and economic modeling to address groundwater depletion in the arid Barind region of Northwest Bangladesh, where 84% of the rural population depends on agriculture. Using remote sensing and GIS, we developed an elevation map revealing areas up to 60 m above sea level, exacerbating evaporation and aquifer dryness. Field data collected through Participatory Rural Appraisal tools showed farmers exhibiting “ignorant myopic” behavior, prioritizing short-term profits over resource conservation. To address this, an Increasing Block Tariff (IBT) water pricing model was developed, dividing water usage into three blocks based on irrigation hours: 1–275 h, 276–550 h, and 551+ h. The proposed IBT model significantly increases water prices across the three blocks: 117 BDT/hour for the first block (from current 100–110 BDT/hour), 120 BDT/hour for the second block, and 138 BDT/hour for the third block. A demand function (y = −0.1178x + 241.8) was formulated to evaluate the model’s impact. The results show potential reductions in groundwater consumption: 59 h in the first block, 26 h in the second block, and 158 h in the third block. These reductions align with the principles of integrated water resource management (IWRM): social equity, economic efficiency, and environmental integration. The model incorporates economic externalities (e.g., well lifting costs) and environmental externalities (e.g., crop pattern shifts), with total costs reaching 92,709,049 BDT for environmental factors. This research provides a framework for sustainable groundwater management in arid regions, potentially reducing overextraction while maintaining agricultural productivity. The proposed IBT model offers a locally driven solution to balance resource conservation with the livelihood needs of farming communities in the Barind tract. By combining remote sensing, GIS, and economic modeling, this research provides a framework for sustainable groundwater management in arid regions, demonstrating the power of geospatial technologies in addressing complex water resource challenges.

Assessing pollution and water resources suitability for multiple uses under extended drought and climate change conditions: the case of the Grombalia aquifer in Tunisia

Assessing pollution and water resources suitability for multiple uses under extended drought and climate change conditions: the case of the Grombalia aquifer in Tunisia

Energy‐Aware Power Control Scheme For Water Quality Monitoring Systems

ABSTRACTThis research introduces an innovative power management approach for wireless sensor networks in aquatic environmental monitoring. The study presents a dynamic algorithm that optimizes energy consumption in long range (LoRa) communication nodes by adaptively adjusting transmission power based on sensor–gateway distances. Leveraging GPS data and a log‐normal shadowing model, the method enables efficient power allocation. Field testing in an aquaculture setting demonstrates the energy‐aware power control (EAPC) algorithm's efficacy. Nodes at 500 m from gateways achieve up to 39% reduction in power consumption compared to fixed‐power systems. At 1250 m, savings decrease to 22%, and at 1500 m, to 11%, while maintaining reliable communication. This research advances sustainable aquatic resource management, offering applications in aquaculture, environmental conservation, and water resource management. By optimizing power usage, the approach contributes to more effective long‐term monitoring of aquatic environments.

Appraising meteoric-surface-groundwater interaction through analyses of hydrochemical evolution of water resources in the Lower Niger River Basin, Nigeria

Appraising meteoric-surface-groundwater interaction through analyses of hydrochemical evolution of water resources in the Lower Niger River Basin, Nigeria

Adaptive Agronomic Strategies for Enhancing Cereal Yield Resilience Under Changing Climate in Poland

Climate-driven changes have raised concerns about their long-term impacts on the yield resilience of cereal crops. This issue is critical in Poland as it affects major cereal crops like winter triticale, spring wheat, winter wheat, spring barley, and winter barley. This study investigates how soil nutrient profiles, fertilization practices, and crop management conditions influence the yield resilience of key cereal crops over a thirteen-year period (2009–2022) in the context of changing climate expressed as varying Climatic Water Balance. Data from 47 locations provided by the Research Centre for Cultivar Testing were analyzed to assess the combined effects of agronomic practices and climate-related water availability on crop performance. Yield outcomes under moderate and enhanced management practices were contrasted using Classification and Regression Trees to evaluate the relationships between yield variations and agronomic factors, including soil pH, nitrogen, phosphorus, potassium fertilization, and levels of phosphorus, potassium, and magnesium in the soil. The study found a downward trend in Climatic Water Balance, highlighting the increasing influence of climate change on regional water resources. Crop yields responded positively to increased agricultural inputs, especially nitrogen. Optimal soil pH and medium phosphorus levels were identified as crucial for maximizing yield. The findings underscore the importance of tailored nutrient management and adaptive strategies to mitigate the adverse effects of climate variability on cereal production. The results provide insights for field crop research and practical approaches to sustain cereal production in changing climatic conditions.

Hydroacoustic Observations Reveal Drivers of Mixing and Salinization of a Karst Subterranean Estuary During Intense Precipitation

AbstractKarst subterranean estuaries within globally ubiquitous carbonate aquifers are coastal groundwater ecosystems that provide an essential water resource for human populations. To understand the drivers of salinization within a coastal aquifer in the Yucatan Peninsula (Mexico), we employed hydroacoustics in flooded caves to observe how oceanic and atmospheric events facilitate mixing between the meteoric lens (fresh‐brackish groundwater) and the saline groundwater on tidal and episodic timescales. Precipitation during Tropical Storm Carlotta increased the flow and salinity of the meteoric lens without evidence for vertical mixing across the halocline. We postulate that vertical migration of haloclines in the conduit relative to those within the rock matrix during precipitation creates lateral density gradients that drive mixing, and ultimately creates a brackish layer within the meteoric lens. These results provide a mechanistic explanation for vertical and lateral exchange in a coastal carbonate aquifer, which has implications for groundwater response to future climatic change.

Indicadores de Sustentabilidade para Gestão da Água

Water safety involves the sustainable use and protection of water sources, so that water is available in adequate quantity and quality to health, livelihoods, ecosystems and production, in addition to protecting it from the negative effects of extreme weather events. Internationally, the concept of water security began being discussed in the 1990s, and more so since 2009, when the issue became the subject of a greater number of publications. In Brazil Federal Law 9433/97, which establishes the National Water Resources Policy, and corresponding state laws implicitly provide the concept of water security. However, the National Water Safety Plan was only launched in 2019, and has became the fundamental instrument for decision-making on this issue. The objective of the research was to pre-select indicators to analyze the water safety of the municipalities contemplated in the Capibaribe river watershed, within the framework of sustainable water management. To achieve the objective, the following methodology was adopted: pre-selection of indicators; application of a questionnaire to a panel of experts; structure a database. Thus, this work aims to bring subsidies that contribute to water security actions and public policies through the development of an indicator database. Additionally, this research is a proposal for future work, helping to define an equation of the water security index for the municipalities in the watershed.

Groundwater potential mapping in semi-arid region of Northern Nigeria by integrating analytic hierarchy process and GIS

Groundwater resource management in drylands, characterized by climate variability and population growth, is difficult. Exploration and exploitation of groundwater, due to inadequate surface water is very costly. This study employed the analytic hierarchy process (AHP) and GIS to identify groundwater potential (GWP) areas in a semi-arid region of Nigeria. Land-use-land-cover, drainage density, slope, rainfall, static water level, soil, lithology, and aquifer were selected for GWP analysis. Parameter weights were determined using AHP and ranked based on their contribution to GWP by experts. The parameters were then integrated using the weighted overlay tool in ArcGIS 10.5 to produce a GWP map of the study area. Borehole yield data from 245 wells were collected to determine the model accuracy and model validation. Results classified the study area into very high GWP (1.9%), high GWP (8.8%), moderate GWP (62%), low GWP (20.70%) and very low GWP (6.6%). Areas with better GWP include Gurun, Dugol, Zago, Kumbo, Dukku, Doguwa, Riruwai, Dambazau, etc. Moderate GWP areas are widely spread across the state while areas with poor GWP include Sharawa, Kadewa, Koya, Dagar, Jigilawa, Galwanga, Yanganau, Kunchi, Tofa, Tsanyawa, etc. Validation of the AHP model with borehole yield data shows a correlation coefficient of 71.3% giving a good prediction. AHP and GIS can be used to successfully map GWP areas which could serve as an exploration guide for sustainable management of groundwater resources in semi-arid areas.

Summer High-Altitude Diurnal Rainfall Change in the Three Rivers Source Region and Associated Mechanism

Abstract The Tibetan Plateau (TP), a crucial area influencing global climatic patterns and water resources, is experiencing a unique climatic paradox, particularly evident in the Three Rivers Source Region (TRSR). A striking summer asymmetry in the increases of near-surface temperature and precipitation is observed from 1989 to 2018: the rate of daily minimum temperature (0.64°C decade−1) surpasses the daily maximum temperature (0.52°C decade−1), while the daytime precipitation intensity (0.40 mm day−1 decade−1) increases at a faster rate compared to nighttime (0.30 mm day−1 decade−1). Despite these trends, the summer mean nighttime precipitation intensity consistently remains higher than the daytime average. Notably, this pattern is accompanied by an increasing trend of moisture transport during both daytime and nighttime in TRSR. This paper deciphers the thermodynamic and dynamic processes behind this trend. The daytime warmth not only alters the stability of atmosphere but also modulates convective inhibition (CIN), thereby reshaping precipitation mechanics and potentially dampening or delaying daytime convection. Thermodynamically, a shift from unstable to stable anomalies in the summer troposphere suppresses precipitation development. The combination of increased CIN during those period leads to fewer but more intense rainy days. Dynamically, the shift from a consistent downward motion anomaly throughout troposphere to an upward motion anomaly becomes dominant during nighttime, exhibiting a similar transition but only below 500 hPa during daytime. These findings reveal the complex interplay between thermodynamics, dynamics, and precipitation, highlighting the need for refined climatic models that can accurately simulate these summer diurnal processes.