Water Resources Management Research Articles

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.

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.

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.

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.

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.

Rainfall Projections for the Brazilian Legal Amazon: An Artificial Neural Networks First Approach

Rainfall in the Brazilian Legal Amazon (BLA) is vital for climate and water resource management. This research uses spatial downscaling and validated rainfall data from the National Water and Sanitation Agency (ANA) to ensure accurate rain projections with artificial intelligence. To make an initial approach, Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) were employed to forecast rainfall from 2012 to 2020. The RNN model showed strong alignment with the observed patterns, accurately predicting rainfall seasonality. However, median comparisons revealed fair approximations with discrepancies. The Root Mean Square Error (RMSE) ranged from 6.7 mm to 11.2 mm, and the coefficient of determination (R2) was low in some series. Extensive analyses showed a low Wilmott agreement and high Mean Absolute Percentage Error (MAPE), highlighting limitations in projecting anomalies and days without rain. Despite challenges, this study lays a foundation for future advancements in climate modeling and water resource management in the BLA.

A comparative analysis of deep-learning models for dam discharge forecasting for disaster management

ABSTRACT This paper represents a comprehensive study of dam water discharge prediction using various deep-learning models. The main aim of this paper is to provide a data-driven solution for effective water resource management and thereby controlling the effects of floods and droughts. The Malampuzha dam, which has a spillway, a right bank canal (RBC), and a left bank canal (LBC), is considered for the study. While the spillway helps to control the water level in the reservoir by allowing extra water to flow downstream during times of severe rainfall or high inflow, hence reducing the risk of floods, the LBC and RBC are intended to divert water for agriculture. Altogether, 10 years of consecutive meteorological and dam-related data are utilized for training and testing the models in forecasting water discharge through LBC, RBC, and the spillway. Different deep-learning models, namely, long short-term memory, Bi-directional long-short term memory, recurrent neural network, gated recurrent unit, one-dimensional convolutional neural network (1D-CNN), deep neural network, autoencoder, and residual networks are explored in predicting the accuracy of dam water discharge. After testing eight deep-learning models, it was discovered that 1D-CNN performed well in predicting the discharge of water.

Field survey for assessing seawater reverse osmosis (SWRO) applications on very small islands in Indonesia

Very small islands in Indonesia face challenges in accessing clean water due to limited space for building water resource facilities, such as reservoirs. Most of the time, the inhabitants of these islands rely on rainwater and wells, which are not sustainable sources due to drought seasons and seawater intrusion. To address this issue, Seawater Reverse Osmosis (SWRO) can be implemented in these areas where seawater is abundant. However, there may be obstacles when applying SWRO systems in such environments. This study aimed to assess the capabilities of SWRO facilities, and the obstacles involved in evaluating clean water access on very small islands. We used a combination of structured questionnaires, interviews, and direct observations on two small islands in Indonesia, Belakang Padang Island and Labu Island. On Belakang Padang Island, we interviewed the water resource manager in October 2022 and March 2023 and surveyed 61 households in the Tanjung Sari subdistrict in October 2022. On Labu Island, we interviewed the staff of the SWRO system and surveyed 35 coastal households in September 2023. On both islands, the government improved residents’ access to clean water by constructing SWRO facilities in 2016 on Belakang Padang Island and in 2021 on Labu Island. However, on Belakang Padang Island, the system was not operational when we visited on March 15, 2023. The main obstacles were slow bureaucratic processes for repairs and maintaining the operation of SWRO facilities. These problems need to be addressed before expanding the implementation of this system to other very small islands in Indonesia.

Cascade reservoirs affected chemical compositions of dissolved organic matter and greenhouse gas dynamics in the Lancang River.

Dissolved organic matter (DOM) is an important component in aquatic systems. There has been much debate about the potential effects of cascade reservoirs on the transport and transformation of DOM. Here, through a survey of source to leave-boundary section of Lancang River (LCR) in June and November of 2017-2018, our results revealed that weak spatiotemporal variations were observed for DOC content, whereas DOM parameters were significantly different between natural and reservoir reaches. And DOM showed higher humification degree from allochthonous sources with increasing autochthonous matter in reservoir reach, may due to high particulate organic matter and releasing autochthonous DOM from phytoplankton blooms in the LCR, which can be evidenced by depleted DIC, enriched δ13CDIC and higher BIX. A unique fluorescent fraction (C5) appeared in the reservoir reach and increased along water flow, which was strongly associated with dissolved CO2 and N2O. Meanwhile, BIX value decreased with increasing dam height, hydraulic residence time (HRT), and reservoir capacity, which may promote CH4 production, highlighting variation of DOM compositions in understanding the effect of greenhouse gas (GHG) dynamics in the LCR. The findings were essential for comprehending the influences of cascade reservoirs on carbon cycle, and informed policy development for the sustainable management of transboundary water resources like the LCR.

Rainwater harvesting technologies in arid plains of Argentina: small local strategies vs. large centralized projects

Access to water has been and remains one of humanity’s greatest challenges. Especially in arid plains exposed to significant climatic fluctuations and future global change trends. In the past and present, local communities of the arid plains of central-western Argentina (i.e., Guanacache Lagoons, Cuyo region) have developed multiple strategies to manage water supply problems. The aims of this study are: i) to characterize the different water harvesting technologies (pre-Hispanic and modern) used, and ii) to compare the small local strategies of water harvesting (bottom-up solutions) with the large centralized projects (top-down solutions). On the one hand, we show the transformations of these technologies over time, and the challenges faced by inhabitants in the context of climate change trends. On the other hand, we analyze the role of the state through hydraulic policies and projects implemented by the provincial states over the last two centuries and how this impacted the study area. This review is based on a historical and archaeological bibliography, and recent publications about the region, including articles based on our ethnographic fieldwork. Our results demonstrate the valuable experience accumulated by local populations in water harvesting methods, particularly in areas where groundwater is deep and saline, and shows the adaptability of these technologies in contexts of increasing scarcity. We considered that local indigenous knowledge can largely contribute to the sustainable management of water resources. This study might be useful for decision-makers and water managers in drylands around the world to find and equitable approach that combines technical advances with local knowledge.

Assessing Drought Patterns in Al-Baha: Implications for Water Resources and Climate Adaptation

Due to growing water demands and changing hydro-meteorological variables brought on by climate change, drought is becoming an increasingly serious climate concern. The Al-Baha region of Saudi Arabia is the subject of this study because it is susceptible to both agricultural and meteorological droughts. This study investigates how climate change affects patterns of drought in Al-Baha by analyzing four drought indices (Agricultural Standardized Precipitation Index (aSPI), the Standardized Precipitation Index (SPI), the Rainfall Deficiency Index (RDI), and the Effective Reconnaissance Drought Index (eRDI)) for the years 1991–2022. Analysis of rainfall data was carried out to classify drought events according to their duration, frequency, and severity. Results showed that severe droughts occurred in 2009, 2010, 2012, 2016, and 2022, with 2010 being the worst year. Results also indicated a notable decrease in precipitation, which has resulted in extended dry spells. Several indices indicate that this tendency has significant ramifications for agriculture, particularly in areas where farming is a major economic activity. In addition, the possible occurrence of hydrological drought was also observed based on the negative values for the Reservoir Storage Index (RSI) in Al-Baha. Projections for the future under two Representative Concentration Pathways (RCPs) showed notable variations in temperature and precipitation. Both the RCP4.5 (low emission) and the RCP8.5 (high emission) projection scenarios indicate that drought conditions will likely worsen further. Depending on the emission scenario, it is projected to show a temperature increase of 1–2 °C, whereas the variability in precipitation projections indicates significant uncertainty, with a reduction change in the range of 1.2–27% between 2050 and 2100. The findings highlight the urgent need for proactive adaptation strategies, effective water resource management, and the development of sophisticated drought prediction tools. Addressing these challenges is crucial for sustaining agriculture and managing water scarcity in Saudi Arabia in the face of increasing drought risk.

Enhancing the SDG 6 Index: Implementing New Directions and Trends in Priorities of Integrated Water Resources Management Principles in the Republic of Korea

Enhancement of water and sanitation management acts as a significant component of global development as it is part of the United Nation’s sixth Sustainable Development Goal. Due to peculiar geographical and climatic attributes of the country and sincere efforts toward implementing IWRM, South Korea has improved its position in the SDG 6 index. The purpose of this research work is to evaluate the advancements that have been made in the IWRM of South Korea from 2018 to 2023 concerning policy changes, technical advancements, and societal engagement. Thus, this paper, through surveys and literature review, examines the measures that have been taken in the recent past to address the hydrological vulnerabilities resulting from climate change, as depicted by the UN Environment Program. Centrally, since South Korea has become more sensitive to climate change effects, and thus hydrological issues, the findings will assist in the improvement of current IWRM processes and help them achieve the SDG 6 goals. This study implies that there should be sustainable water management practices that balance natural and human interferences amidst prevailing climate change effects.

Analysis of Water Dynamics at the Effluent Treatment Station of Cooperoque: Evaluation of Precipitation, Evaporation, and Infiltration of Effluent from a Milk Refrigeration Station

Purpose: The study aims to analyze water dynamics at the Cooperoque Effluent Treatment Station, focusing on the interactions between precipitation, evaporation, and effluent infiltration to enhance water resource management. Theoretical reference: The research references various studies and methodologies related to the quantification of evaporation from lakes and reservoirs, particularly in semi-arid regions, utilizing the Jensen-Haise Method for evaporation estimation. The research aligns with previous studies, such as Mallmann (2014), on water infiltration in soil management, emphasizing the importance of understanding water dynamics for sustainable resource management. Method: The study employs the Jensen-Haise Method to calculate evaporation rates, covering the period from January 2023 to October 2024. It examines the effects of precipitation, evaporation, and effluent infiltration on tank levels. Results and conclusion: The results reveal that tank levels are influenced by precipitation, evaporation, and effluent infiltration, with more significant declines during dry months and smaller reductions during periods of high precipitation. Evaporation rates, calculated using the Jensen-Haise Method, are higher in warmer months, contributing to lower tank levels, while these rates decrease in colder months. A notable anomaly occurred in May 2024 when effluent infiltration exceeded the volume of generated effluents and rainfall due to the activation of an irrigation system. Key findings indicate that lake levels drop more during dry months, with a significant negative water balance observed in May 2024 due to excessive infiltration during heavy rainfall. The study concludes that adaptive water management strategies are necessary to address climatic variations and improve the efficiency of the effluent treatment system. Implications of research: The research provides valuable insights for developing adaptive water management strategies to address climatic variations and improve the efficiency of effluent treatment systems. Continuous monitoring is emphasized as crucial for sustainable water resource management. Originality/value: The study highlights the complex interactions between precipitation, evaporation, and effluent dynamics, offering a foundation for improved water management practices and contributing to the preservation of regional water resources. The study contributes to the understanding of water dynamics at effluent treatment stations, offering practical insights for managing water resources effectively. It highlights the importance of adaptive strategies and continuous monitoring to maintain pond levels and optimize the treatment process.

Research on Hydraulic Characteristics of Water Leakage Phenomenon of Waterproof Hammer Air Valve in Water Supply Pressure Pipeline Based on Sustainable Utilization of Water Resources in Irrigation Areas

To investigate the causes of water leakage in the waterproof hammer air valve and its impact on sustainable water resource management, the DN100 waterproof hammer air valve was taken as the research object. By using the overset grid solution method of ANSYS Fluent 2021 R1 software, the flow field simulation of the waterproof hammer air valve was carried out. The transient action during the ascent phase of the key structural component floating ball, and the velocity and pressure distribution of the flow field inside the air valve are analyzed. The results showed that by giving different inlet flow velocities, the normal flow velocity range for the floating ball to float up was below 35 m/s and above 50 m/s. When the inlet flow velocity was between 35 m/s and 50 m/s, the growth rate of the pressure difference above and below the floating ball increased from 1.48% to 5.79% and then decreased to 0.4%. The floating ball would not be able to float up due to excessive outlet pressure above, which would cause the DN100 waterproof hammer air valve to leak water and fail to provide water hammer protection. When the inlet flow rate is 5 m/s, the velocity and pressure inside the valve body increase with time during the upward movement of the floating ball inside the waterproof hammer air valve and tend to stabilize at 400 ms. Through the generated pressure and velocity cloud maps, it can be observed that the location of maximum pressure is at the bottom of the buoy, directly below the floating ball, and at the narrow channels on both sides of the outflow domain. The location of the maximum velocity is at the small inlet of the bottom of the buoy. When the inlet speed of the valve is constant, a large amount of water flow is blocked by the floating ball, reducing the flow velocity and forming partial backflow below the floating ball, with an obvious vortex phenomenon. A small portion of the water flow passes through the air valve at a high velocity from both ends of the channel, and the water flow below the floating ball is in an extremely unstable state under the impact of high-speed water flow, resulting in a large gradient of water flow velocity passing through the valve. The research results not only help to improve the operational efficiency of water resource management systems but also reduce unnecessary water resource waste, thereby supporting the goal of sustainable water resource management.

Investigating Effective Reconnaissance Drought Index Ability to Reproduce Drought Signature over the Massili Basin (Burkina Faso)

Drought is a significant natural hazard particularly in arid and semi-arid regions where water resources management is already challenging. Burkina Faso, a landlocked country located in the Sahel region, is highly vulnerable to drought due to its arid climate. The country has experienced recurrent droughts since the 1970s, with significant impacts on its population and economy. To develop effective drought mitigation strategies, a comprehensive understanding of drought characteristics is required. This study investigates historical long-term drought trends in the Massili basin located in central Burkina Faso. For this purpose, drought features has been analyzed based on the Effective Reconnaissance Drought Index (eRDI) at various months of accumulation. To calculate the Effective Reconnaissance Drought Index for the Massili Basin, monthly precipitation (Prct), minimum temperature (Tmin), and maximum temperature (Tmax) data spanning from 1960 to 2021 were obtained from the National Meteorological Agency of Burkina Faso. The Potential evapotranspiration (ETP) was estimated using the Hargreaves method. Our findings indicate that under eRDI-3, 1964 (1.86), 2020 (1.53), and 2021 (0.63) are the wettest years, while 1963 (-0.65) and 1998 (-0.76) are the driest. Under eRDI-12, a significant portion of the values falls within the range of -0.14 to 0.03. In the case of eRDI-24, a substantial number of the values cluster between -0.08 and 0.08. This distribution highlights near-normal drought conditions (-0.99 to 0.99) as the most frequent occurrence within the watershed. The desertification of the Sahel area has been a topic of discussion for decades. However, these findings of this study reinforce the prevailing belief in a partial re-greening of the Sahel region.

CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration

Abstract. Accurate maps of irrigation extent and dynamics are crucial for studying food security and its far-reaching impacts on Earth systems and the environment. While several efforts have been made to map irrigated area in China, few have provided multiyear maps, incorporated national land surveys, addressed data discrepancies, and considered the fractional coverage of cropland within coarse-resolution pixels. Here, we addressed these important gaps and developed new annual maps of China's irrigated cropland from 2000 to 2020, named CIrrMap250 (China's irrigation map with a 250 m resolution). We harmonized irrigation statistics and surveys and reconciled them with remote sensing data. The refined estimates of irrigated area were then integrated with multiple remote sensing data (i.e. vegetation indices, hybrid cropland products, and paddy field maps) and an irrigation suitability map by means of a semi-automatic training approach. We evaluated our CIrrMap250 maps using ∼ 20 000 reference samples, high-resolution irrigation water withdrawal data, and existing local to nationwide maps. Our CIrrMap250 maps demonstrated an overall accuracy of 0.79–0.88 for the years 2000, 2010, and 2020 and outperformed currently available maps. The CIrrMap250-estimated irrigation area explained 50 %–60 % of the variance in irrigation water withdrawal across China. CIrrMap250 revealed that China's irrigation area increased by about 180 000 km2 (or 25 %) from 2000 to 2020, with the majority (61 %) occurring in the water-unsustainable regions facing severe to extreme water stress. Moreover, our product unveiled a noticeable northward shift of China's irrigation area, attributed to substantial expansions in irrigated cropland across northeastern and northwestern China. The accurate representation of irrigation extent in CIrrMap250 will greatly support hydrologic, agricultural, and climate studies in China, aiding in improved water and land resources management. CIrrMap250 can be accessed at https://doi.org/10.6084/m9.figshare.24814293.v2 (Zhang et al., 2023a).

Agricultural Water Conservation Methods: Application, Difficulties, and Innovation

The largest growth in water usage among water-using industries has been in agriculture due to the growing need for agricultural goods to feed the world's expanding population. Presently, agricultural water conservation encompasses a range of technologies that are mostly grounded in human understanding, but also include a number of complex strategies that significantly rely on cutting-edge mechanical and electrical techniques. Modern agronomic practices like precision agriculture may conserve water. Precision agriculture is a modern agronomic strategy that may preserve water.Modern agricultural investments, land transfers, and urbanisation have left these irregular and traditionally built villages with an ambiguous and ever-changing land use pattern. This may hinder water-saving adoption. In addition to taking into account the growth of the agricultural sector, the agricultural water management policy prioritises the long-term ecological economy and the sustainability of the water resource supply network. Water needs are predicted to rise significantly by the end of the twenty-first century, particularly for irrigation. Reducing the amount of water used in agriculture is crucial. With temperatures rising and droughts occurring more frequently in many nations, water is a vital component of agricultural output. Certain technology-based practices coupled with efficient farmers and humans management of water resources will be the key features for improving water conservation.

Assessing the grey water footprint of pesticide use in the Mendoza wine region (Argentina): implications for sustainable water resources management

This paper assesses the impact of viticulture on water resource quality in the Mendoza wine region using the grey water footprint (GWF) approach to estimate the amount of water required to dilute pesticides commonly used in local vineyards. Our analysis indicates that to progress towards sustainable water management in viticulture, limiting or replacing pesticides with high GWF values is essential. We provide detailed results for 24 fungicides, 7 insecticides, and 7 herbicides, assessed at both microregion and district levels, offering insights into pesticide impacts across both detailed and broader spatial scales. At the microregion level, the herbicide Fluroxypyr-meptyl was found to have the highest GWF (1.10 m³ kg-1), followed by the fungicide Fosetyl-aluminium (0.59 m³ kg-1) and the insecticide Imidacloprid (0.41 m³ kg-1). Our findings also show that pesticide impacts vary at the district level, highlighting the need for localised management strategies. Additionally, the significant variability in GWFs at the local level underscores the necessity for region-specific water quality standards to more accurately assess and manage the environmental impact of pesticide use. This study provides a framework for similar assessments in other viticultural regions, aiding in the development of more informed pesticide management to enhance water resource sustainability.