Future Water Resources Research Articles

Over 60% precipitation transformed into terrestrial water storage in global river basins from 2002 to 2021

The crucial role of precipitation as a primary driver for terrestrial water cycle is well-established. However, quantifying the transformation of daily precipitation into terrestrial water storage remains a challenge. Here we address this by introducing a quantitative metric, average daily fraction of precipitation transformed into terrestrial water storage, providing an important advancement into the dynamics of water storage by utilizing the enhanced terrestrial water storage statistical reconstruction method and water storage data from the Gravity Recovery and Climate Experiment satellites and their follow-on mission. This study reveals that approximately 64% of land precipitation contributes to terrestrial water storage in global 121 river basins from 2002 to 2021, with evident variations observed across different climatic and geographical regions. Our findings deepen perception into the complex interactions between precipitation, land surface processes, and climate change, offering valuable implications for future water resource management and hydrological modeling.

Impact of urbanization on groundwater recharge: altered recharge rates and water cycle dynamics for Arusha, Tanzania

Abstract The profound effects of urbanization on groundwater recharge rates are investigated by conducting a comprehensive land use and land cover analysis in Arusha, Tanzania, using the WetSpass model. Between 1995 and 2016, the urban area has expanded from 14 to 45% within the study area. This rapid urbanization has resulted in the conversion of forested areas, agricultural land, shrublands, and bare soil into urban zones. Results indicated that under preurban conditions, groundwater recharge from precipitation was ~116 mm/year, which increased to an average of 148 mm/year by 2016. When accounting for anthropogenic factors such as drinking water leakage and on-site sanitation, recharge further increased to 195 mm/year. These supplementary recharge sources, along with reduced evapotranspiration due to land-use changes, contributed to the increase, despite higher surface runoff. These findings underscore the significance of land use and leakage management in urban areas, as well as the spatial variability in groundwater recharge rates across different urban zones, emphasizing the importance of local factors. This study advances the understanding of the intricate relationship between urbanization and groundwater dynamics, and provides insights for future water resource management in rapidly growing urban regions.

Comparative study on lake ice phenology changes and driving factors in large lakes of mid-latitude Xinjiang, China.

The changes in lake ice phenology (LIP) can intuitively reflect the climate evolution in the regions where lakes are located, serving as an important indicator of climate change. The Tianshan Mountains, situated at the southern edge of freezing lakes in the Northern Hemisphere, are a crucial water resource base in Xinjiang and support significant ecosystems closely related to human activities. In the context of intensified climate change, this study focuses on the geographical location, altitude, and water quality differences among large lake groups in the mid-latitude region of Xinjiang, aiming to explore the characteristics of LIP changes in these lakes and their responses to driving factors, thereby providing a basis for effective environmental management and protection. This research conducts a comparative analysis of the LIP changes and driving factors of three large lakes-Sayram Lake (SL), Bosten Lake (BL), and Ebnur Lake (EL)-using multi-source remote sensing data to reveal the response and adaptation mechanisms of lakes under global warming. It effectively captures the time series variations of ice formation and melting, as well as the common responses to environmental and climatic factors. The results indicate that SL has experienced significant climate change effects, with earlier freezing times and accelerated melting speeds; In contrast, EL and BL have shown relatively minor changes, suggesting that geographical and hydrological factors may buffer the impacts of climate. The study finds that all three lakes are jointly influenced by environmental factors such as temperature, wind speed, and precipitation; however, due to differences in altitude, lake surface area, and water transparency, their responses to these climatic factors vary significantly. For instance, SL's high altitude gives water transparency a dominant role in LIP, while BL's larger surface area enhances the impact of precipitation and thermal capacity on the melting process. This indicates that, despite facing similar climate pressures, local environmental conditions can lead to different trends in ice phenology changes. This study offers a novel and efficient monitoring method for LIP, providing valuable insights for future LIP research and water resource management.

Glacier area variation in Uttarakhand Himalaya: Investigating trends and influencing factors

AbstractUnderstanding the intricate interplay between topography and glacier changes is vital for predicting future water resources and addressing the impacts of climate change. This study examines changes in glacier area in the Uttarakhand Himalayan region, where the River Ganga originates, between 2000 and 2023 using high‐resolution satellite imagery. A manual digitization process was employed to delineate the glacier boundaries of 116 glaciers for the years 2000 and 2023. Multivariate regression analysis was then conducted to identify and quantify the controlling topographical and morphological parameters. The analysis revealed significant reductions in total glacier area, decreasing from 979.05 ± 46.89 km2 in 2000 to 957.60 ± 13.67 km2 in 2023, with an overall deglaciation rate of 0.095% per year, highlighting variability in glacier responses. This variability is driven by a complex interplay of mainly slope, shape index, glacier elevation and surface ice velocity. Among these factors, the shape index emerged as the most influential. Glaciers with a higher shape index (more elongated) were found to be more stable than those with a lower shape index (more circular). A 10% difference in shape index results in a glacier with a higher shape index losing 0.112% per year less area compared to a glacier with a lower shape index. The second controlling parameter is glacier slope; glaciers with a 10% steeper slope lost 0.11% per year less area compared to those with a gentler slope. The other two parameters showed some minor impact on glacier area variation in the sample glaciers but not across the entire Uttarakhand region.

Identification of Suitable Sites for Rainwater Harvesting Using AHP and GIS in the Middle and High Moulouya Basin, Morocco

Several researchers have utilized various methodological frameworks to determine appropriate locations and methodologies for Runoff Water Harvesting (RWH) in semi-arid and arid area. This plays a crucial role in addressing water scarcity during dry periods. Establishing RWH sites within basins to collect rainwater from small basin and facilitate artificial groundwater replenishment is a viable solution to mitigate water deficiencies in the middle and upper Moulouya basin. In this study, a methodology integrating remote sensing data and geographic information systems was developed based on a model created in SIG software. Seven factors including lithology, climate, land cover/land use, digital elevation, recharge, and surface runoff. Were employed to assess the suitability of sites for RWH. The resulting spatial distribution of the suitability map categorized the basin into five classes of RWH potential, ranging from very high to very low suitability. These findings offer significant promise in terms of identifying suitable sites for RWH. The RWH suitability map revealed that within the Moulouya basin, areas were classified into unsuitable (20.15%), less suitable (40.82%), moderately suitable (24.38%), well-suited (9.60%), and highly suitable (5.02%) categories for RWH. This final map serves as a valuable resource for decision-makers, hydrologists, and urban planners, offering crucial guidance for future water resource and land management initiatives by swiftly pinpointing areas with the highest potential for rainwater harvesting.

Comparisons of Montane Snow Water Equivalent Projections: Calculating Total Snow Mass in Regions with Projection Agreement and Divergence in the Western US

Abstract Montane snowpack is a vital source of water in the Western United States. Here, we use a large-ensemble approach to evaluate the agreement across 124 snow water equivalent (SWE) projections with statistically downscaled forcing between end-of-century (2076 – 2095) and early 21st century (2106 – 2035) periods. Comparisons were performed on dates corresponding with the end of winter (15 April) and mid-spring snowmelt (15 May) in five western US domains. Using 1) the percent change to end-of-century SWE across different ensembles of snow projections, and 2) the shift between early 21st century and end-of-century SWE distributions for each snow projection, we identified relationships between projections that were consistent across each domain. In low to mid-elevations, end-of-century SWE decreases were 48% and larger on 15 April. These regions had projected changes to SWE that were both high-confidence and in relative agreement across projections. Despite this, the majority of 15 April SWE volume existed in higher elevations where the magnitude and direction (positive or negative) of SWE changes were most uncertain. The results of this study show that large-ensemble approaches can be used to measure coherence between snow projections and identify 1) the highest-confidence changes to future snow water resources, and 2) the locations and periods where and when improvements to snow projections would most benefit estimates of future snow water resources.

A SWAT model depicts the impact of land use change on hydrology, nutrient, and sediment loads in a Lake Michigan watershed

High levels of nutrient loads in a catchment indicate the presence of pollution sources that must be identified and quantified. These loads in surface and groundwater have been a major concern that impacts water quality in the Midwestern US, including the Great Lakes Basin. In this study, we use the Soil and Water Assessment Tool (SWAT) to assess the impact of land use changes on hydrology, nutrients, and sediment loads for the St. Joseph River Basin (SJRB), which drains an area of 12,200 km2 in Southwest Michigan/Northwest Indiana and is a primary source of pollutant to Lake Michigan. The SWAT models were developed to simulate streamflow, baseflow, total suspended solids (TSS), total phosphorous (TP), dissolved reactive phosphate (DRP), total nitrogen (TN), and nitrate (NO3-N), using data from two stream gauges. The calibrated models accurately simulated the studied variables across the SJRB. The simulated average annual baseflow for Niles and Paw Paw subwatersheds were 153 and 190 mm, respectively. The impacts of land use change on variables from the SJRB were also explored. The impact of land use change on water quality over time was statistically significant but trends were not linear. Hydrology, sediments and nutrients were also quantified at the subbasin level. Subbasins with heavy urbanization or agricultural drainage infrastructure, showed more substantial increases in sediment and nutrient loads as well as decreased groundwater recharge. This study will aid in the evaluation of historical and future water resources for Midwestern rivers, enabling stakeholders to prepare for future impacts, and to execute conservation and management to sustain the SJRB.

Evaluation and prediction of carrying capacity of soil and water resources in Lanzhou City based on the CA–Markov model

ABSTRACT To promote sustainable development, evaluating the carrying capacity of soil and water resources has become indispensable. This study establishes an evaluation system using the driving force–pressure–state–impact–response framework and employs the entropy weight cloud model to comprehensively assess the water and soil resource capacity of Lanzhou. Additionally, the CA–Markov model and the gray prediction model were deployed to forecast Lanzhou's future water and soil resource capacity. The evaluation from 2010 to 2022 indicates consistent classification at overloaded or severely overloaded levels, highlighting systemic inefficiency in water and soil resource utilization, which poses a significant obstacle to sustainability. Notably, urbanization rate, water productivity coefficient, and per capita water resources were identified as key factors influencing these results. Based on the forecast for the next 5 years (2023–2027), the water and soil resource capacity of Lanzhou is expected to further decline, posing challenges to sustainable development. This study provides technical support and decision-making guidance for the formulation of Lanzhou's water and soil resource management strategies and sustainable development planning, playing a key role in promoting efficient resource utilization and protecting regional water and soil resources.

Applying Budyko framework to explore the projected hydrologic changes in southern Taiwan

This study combines future rainfall and temperature projections with the Budyko framework to analyze future water resource changes in four key watersheds in southern Taiwan under climate change scenarios. Since only temperature and rainfall data are available in the future climate change projections, the future evapotranspiration projections are estimated by this study. This study establishes Budyko equations of each watershed, using historical evapotranspiration and temperature data along with potential evapotranspiration estimates, to project future evapotranspiration based on future temperature and rainfall data. The future rainfall is expected to gradually increase, with the most significant increase under the SSP5-8.5 scenario. However, the rainfall increase varies with the geographical location (latitude) of the watershed, with higher rainfall increases in northern watersheds, such as Zengwen, Jiaxian, and Nanhua. Moreover, the projected evapotranspiration differs in watersheds in southern Taiwan indicating the uncertainty and challenge of evapotranspiration projection under climate change. The future runoff projections indicate an increasing trend with a significant increase (13.4–20.3%) by the end of the century (2081–2100), due to projected increases in rainfall and minor changes in evapotranspiration. The projected increase in runoff implies an optimistic outlook in water resources planning and management, but may pose a threat in flood disasters due to increased rainfall in the wet season.

An agent-based socio-hydrological modeling to identify the feedbacks between agricultural irrigation and ecological water conveyance tradeoffs in Hotan River basin

Study regionHotan River basin in Northwest China Study focusThe conflict between agricultural irrigation and ecological water conveyance is particularly critical in arid inland river basins. Water resource systems involve multiple stakeholders and sectors, complicating the identification of dynamic feedback between agriculture and ecology. This study presents an agent-based socio-hydrological modeling (ABSHM) framework to address these interactions. New hydrological insights for the regionFeedback is quantified using dynamic state variable of oasis decision-making sensitivity in the Hotan River basin. When this sensitivity ranges from 0.03 to 0.06, water managers prioritize agricultural irrigation, increasing its usage from 8 to 47 million m3 at the expense of ecological water. Conversely, when sensitivity is from 0.015 to 0.03, ecological health requires increasing ecological water use from 27 to 66 million m³ by reducing irrigation. The ABSHM framework effectively captures these dynamic feedback processes, supporting basin water resources management and decision-making. The uniqueness of the ABSHM framework lies in its ability to capture the impact of individual decision-making behaviors on the overall water resource system. This offers new perspectives and approaches for addressing current and future water resource management challenges.

Assessment of Aquifer Resistivity, Depth, and Thickness using Vertical Electrical Sounding (VES) in Parts of Bori Metropolis for Groundwater Exploration

Groundwater exploration is vital to guaranteeing a reliable water supply in both urban and rural locations. In Bori Metropolis, the growing demand for potable water necessitates a thorough examination of the aquifer system. Therefore, the purpose of this study is to determine the groundwater potential in Bori Metropolis by assessing aquifer resistivity, depth, and thickness using Vertical Electrical Sounding (VES). A total of 13 VES surveys were completed in the study region using the Schlumberger array. The apparent resistivity measurements were analyzed using 1D inversion techniques to determine aquifer depth and thickness. The results showed that aquifer resistivity values ranged from to at depths ranging from to . Aquifer thicknesses ranged from to , indicating a high groundwater potential in the area. The results indicate that the Bori Metropolis area comprises a well-defined aquifer system with a high potential for groundwater extraction. These findings give important information for future water resource management in the region.

Multispectral Assessment of Net Radiations Using Comprehensive Multi-Satellite Data

Precise estimation of net radiation (Rn) is fundamental to understanding surface energy balance and is critical for accurately determining crop water requirements, especially using remote sensing and geospatial techniques. The core objective of this study is to evaluate multi-satellite-based net radiations on major cropped areas of the Punjab and Sindh provinces of Pakistan. In this study, overlapping scenes from the Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 8, and Sentinel 2 were used from 2016 to 2020 along with three temperature products MOD11A1, Landsat 8 (brightness temperature), and ERA5. The multi-satellite-based net radiation estimations on overlapping days were compared with the Global Land Data Assimilation System (GLDAS) dataset. The models based on Landsat 8 and Sentinel 2 data exhibited good performance, with a Nash–Sutcliffe Efficiency (NSE) of 68.9%, a mean error (ME) of 13.918 W/m2, and a bias of 50.669 W/m2. The results indicated that Landsat 8 and Sentinel 2 data produced reliable estimations of net radiation, while MODIS data tended to overestimate due to its higher spatial resolution and broader coverage area. Landsat 8-based estimations are good compared to others, as it has good correlation coefficient and lower RMSE values. The study concludes that Landsat 8 provides the most reliable estimates of net radiation for determining crop water requirements, outperforming other datasets in accuracy. The findings underscore the importance of using high-resolution multi-satellite data for precise agricultural water management, recommending its use in future studies and water resource planning in Pakistan.

Uncharted water conflicts ahead: mapping the scenario space for Germany in the year 2050

IntroductionIn recent years, conflicts surrounding the use, distribution, and governance of surface water and groundwater in Germany have gained prominence in the media, on the political agenda, and in research. Increasing effects of climate change, such as heatwaves and drought but also extreme rain events and flooding, are considered to become more prominent and pressing in the future by different societal actors. However, it remains highly uncertain if and what type of conflicts related to water quantity Germany might actually face in the future (and how they will be framed). This paper addresses one dimension of this uncertainty—namely the future context uncertainty of possible resource and water governance conflicts. Our research contributes to an improved understanding of the uncertainty concerning future climatic, natural, land use related, political, economic, and other societal contexts that could impact water conflicts.MethodWe ask: What are possible coherent context scenarios for Germany in the year 2050, and how are they expected to influence future water conflicts? In an expert-based process, we apply a qualitative and systematic method of systems analysis, cross-impact balances (CIB). With CIB, we build internally consistent scenarios of possible futures and map the future scenario space.Results and discussionDiversity mapping with a new CIB web application of the ScenarioWizard reveals that the scenario space is rather large and diverse. The identified scenario space of n = 355 internally consistent scenarios spans four most diverse scenarios “Polycrisis,” “Economy and agriculture in crisis,” “Growth through adaptation to climate change,” and “Sustainable transformation.” Depending on the development of future contexts, the risk for future water resource and governance conflicts may unfold in various ways. We conclude that our scenario analysis provides a useful base for research and practice to address the context uncertainty of water conflicts in Germany. Our results can be used for risk assessment, to define societal framework assumptions for societal-hydrological modeling, and to develop robust and adaptive strategies and policies.

Vegetation Restoration Enhanced Canopy Interception and Soil Evaporation but Constrained Transpiration in Hekou–Longmen Section During 2000–2018

The quantitative assessment of the impact of vegetation restoration on evapotranspiration and its components is of great significance in developing sustainable ecological restoration strategies for water resources in a given region. In this study, we used the Priestley-Taylor Jet Pro-pulsion Laboratory (PT-JPL) to simulate the ET components in the Helong section (HLS) of the Yellow River basin. The effects of vegetation restoration on ET and its components, vegetation transpiration (Et), soil evaporation (Es), and canopy interception evaporation (Ei) were separated by manipulating model variables. Our findings are as follows: (1) The simulation results are compared with the ET calculated by water balance and the annual average ET of MODIS products. The R2 of the validation results are 0.61 and 0.78, respectively. The results show that the PT-JPL model tracks the change in ET in the HLS well. During 2000–2018, the ET, Ei, and Es increased at a rate of 1.33, 0.87, and 2.99 mm/a, respectively, while the Et decreased at a rate of 2.52 mm/a. (2) Vegetation restoration increased the annual ET in the region from 331.26 mm (vegetation-unchanged scenario) to 338.85 mm (vegetation change scenario) during the study period, an increase of 2.3%. (3) TMP (temperature) and VPD (vapor pressure deficit) were the dominant factors affecting ET changes in most areas of the HLS. In more than 37.2% of the HLS, TMP dominated the change affecting ET, and vapor pressure difference (VPD) dominated the area affecting ET in 30.5% of the HLS. Overall, the precipitation (PRE) and VPD were the main factors affecting ET changes. Compared with previous studies that directly explore the relationship between many influencing factors and ET results through correlation research methods, our study uses control variables to obtain results under two different scenarios and then performs difference analysis. This method can reduce the excessive interference of influencing factors other than vegetation changes on the research results. Our findings can provide strategic support for future water resource management and sustainable vegetation restoration in the HLS region.

Projected impacts of climate change on global irrigation water withdrawals

Investigating processes causing water resource depletion risks is key to understanding past, present, and future excessive irrigation water withdrawal. Quantitative spatiotemporal analysis of the factors driving excessive irrigation water withdrawal is currently inadequate. Although multiple drivers typically contribute to this risk, we studied, for the first time, whether and how Actual Irrigation Water Withdrawals (AIWW) could affect global future water resources projection. Here, we used AIWW datasets from five CMIP6 climate models based on two Shared Socioeconomic Scenarios (SSP370 and 585) and a global hydrological model (H08) to compare the historical (1981–2014) with the future periods: 2041–2070 and 2071–2100. Results show that the temporal AIWW average variations have shown a statistically significant increase during 1981–2014 (p<0.05 and R2 = 0.98) ranging from 101.82 to 136.24 mm yr−1 (mean = 120.5 mm yr−1). Under SSP370 and SSP585, the global spatial AIWW average during 2041–2070 and 2071–2100 are 142.55 and 145.55, and 144.91 and 149.74 mm yr−1, respectively. Under SSP370 and SSP585, the average AIWW changes for 2041–2070 and 2071–2100 are projected to be 96.71, 97.55, 103.52, and 106.98 %, respectively. Under SSP370 and 585, the average global AIWW anomaly changes for 2041–2070 and 2071–2100 are also projected to be −96.86, −106.29, −97.72, and −111.48 %, respectively. Higher AIWW increases are mainly concentrated in India, South China, parts of the United States, parts of Europe, and parts of South African and Latin American countries. Substantiated with population increase, and higher food demand, an increased AIWW will further aggravate globally. Thus, exploring future AIWW changes is a key step forward that requires greater attention in irrigation research interventions helpful to inform societies to reduce future risks of water resource depletion. Adaptation policies targeting the future use of water for irrigation are crucial to lessen water resource depletion risk, suggesting the need for large-scale policy interventions.

Integrating Machine Learning, Land Cover, and Hydrological Modeling to Contribute Parameters for Climate Impacts on Water Resource Management

The purpose of this study is to establish basic policies for managing the impacts of climate change on water resources using the integration of machine learning and land cover modeling. We predicted future changes in land cover within the water management and assessed its vulnerability to climate change. After confirming this vulnerability, we considered measures to improve climate resilience and presented future water resource parameters. We reviewed the finances available to promote climate projects, noting the major river management funds. The future project will serve as a stepping stone to promote climate resilience projects addressing water resource challenges exacerbated by future climate change. The study examined the results of analyzing changes in land cover maps due to climate change and assessed vulnerability in water management areas until 2050. According to the analysis results, the regulations for our study areas were set lower than those for other water management zones, resulting in a high rate of urbanization. Therefore, the climate resilience project in the water management area should be implemented first, despite the need for a long-term view in adapting to climate change.

Geological influence on groundwater quality in volcanic aquifers of Eastern Mount Cameroon, West of the Penda Mboko River

This study explores the utility of silica concentration in deciphering geological controls and hydrogeochemical processes affecting groundwater quality in Mount Cameroon’s volcanic terrain. Fifty water samples from wells, boreholes, springs, and rivers were analysed for hydrochemical properties (EC, pH, temperature, TDS) and major ion concentrations (Ca2+ > Mg2+ > K +> Na+ and HCO3− > Cl −> NO3− > SO42−). The groundwater exhibits low mineralization, with a dominance of Ca2+, Mg2+, HCO3−, and SiO2, reflecting minimal water–rock interaction and short residence times. Spatial variations in hydrochemistry suggest diverse water–rock interactions and potential mixing processes (76% of samples in rock dominance zone). Silica concentrations (5.8–58.7 mg/L) and estimated chalcedony temperatures (> 60 ℃ at five sites) indicated depths exceeding 1000 m. This research highlights silica’s effectiveness in tracking water–rock interactions across diverse geological settings, regardless of flow depth or interaction time variations. Mineral saturation indices pointed towards supersaturation with silicate minerals (quartz) but undersaturation with carbonates, sulphates, and halides. These findings contribute to a better understanding of groundwater evolution in Mount Cameroon, valuable insights into the hydrogeochemical processes shaping groundwater quality, aiding sustainable water resource management practices that can benefit local communities by ensuring a reliable source of freshwater. However, opportunities exist to improve future studies and water resource management. For a more comprehensive understanding, future analyses should include a broader range of geochemical tracers, such as nitrate (NO3−) and phosphate (PO43−), to assess potential agricultural or anthropogenic contamination. The study also found elevated levels of chloride and sodium, suggesting potential anthropogenic influences on groundwater quality, such as agricultural practices and waste disposal.

Future Projection of Water Resources of Ruzizi River Basin: What Are the Challenges for Management Strategy?

This study investigates the impact of climate change on hydrological dynamics in the Ruzizi River Basin (RRB) by leveraging a combination of observational historical data and downscaled climate model outputs. The primary objective is to evaluate changes in precipitation, temperature, and water balance components under different climate scenarios. We employed a multi-modal ensemble (MME) approach to enhance the accuracy of climate projections, integrating historical climate data spanning from 1950 to 2014 with downscaled projections for the SSP2-4.5 and SSP5-8.5 scenarios, covering future periods from 2040 to 2100. Our methodology involved calibrating and validating the SWAT model against observed hydrological data to ensure reliable simulations of future climate scenarios. The model’s performance was assessed using metrics such as R2, NSE, KGE, and PBIAS, which closely aligned with recommended standards. Results reveal a significant decline in mean annual precipitation, with reductions of up to 37.86% by mid-century under the SSP5-8.5 scenario. This decline is projected to lead to substantial reductions in surface runoff, evapotranspiration, and water yield, alongside a marked decrease in mean monthly stream flow, critically impacting agricultural, domestic, and ecological water needs. The study underscores the necessity of adaptive water resource management strategies to address these anticipated changes. Key recommendations include implementing a dynamic reservoir operation system, enhancing forecasting tools, and incorporating green infrastructure to maintain water quality, support ecosystem resilience, and ensure sustainable water use in the RRB. This research emphasizes the need for localized strategies to address climate-driven hydrological changes and protect future water resources.

Global spatial and temporal dynamics of the green water coefficient and analysis of factor from 1992 to 2020

In recent years, the impacts of climate change have variably affected the global ecological environment, exacerbating water scarcity and related issues. Meantime, as part of soil evapotranspiration and plant transpiration in water resources, green water is of great significance in stabilizing the global water cycle and promoting the sustainable development of agriculture. Therefore, the green water coefficient in this study calculates the conversion rate of precipitation to green water, which is important for the balance between blue and green water and the stability of the ecological environment. Based on trend analysis methods and Geodetector, this study analyses the spatial and temporal characteristics and driving mechanisms of the green water coefficient on the globe and on each land-use type from 1992 to 2020. The findings revealed that: (1) The global green water coefficient is clearly spatially differentiated, showing certain latitudinal distribution differences, with the lowest near the equator. The areas with higher green water coefficients are mainly in northern and southern Africa, central Asia, Oceania and northern and western North America, while the areas with lower green water coefficients are concentrated in northern South America and Southeast Asia. (2) The global average value of green water coefficient decreases before increasing. Except for water, the green water coefficient of other land use types (crop land, forest land, grassland, urban land, unused land) changes significantly and there are fewer abrupt change points. Areas where the green water coefficient is too low and changes drastically are not suitable for rainfed agriculture. (3) Different influential factors act on the green water coefficients of different land use types, and there is a two-factor enhancement and non-linear enhancement relationship between them, with a combination of factors affecting the green water coefficient. By studying the characteristics of the green water coefficient globally and across different land use types, we quantified the influence of climate factors such as precipitation, temperature, wind speed, evapotranspiration, radiation, etc., on the green water coefficient, thereby providing some information for future global rain-fed agriculture and water resources management.

Study on Large-Scale Urban Water Distribution Network Computation Method Based on a GPU Framework

Large-scale urban water distribution network simulation plays a critical role in the construction, monitoring, and maintenance of urban water distribution systems. However, during the simulation process, matrix inversion calculations generate a large amount of computational data and consume significant amounts of time, posing challenges for practical applications. To address this issue, this paper proposes a parallel gradient calculation algorithm based on GPU hardware and the CUDA Toolkit library and compares it with the EPANET model and a model based on CPU hardware and the Armadillo library. The results show that the GPU-based model not only achieves a precision level very close to the EPANET model, reaching 99% accuracy, but also significantly outperforms the CPU-based model. Furthermore, during the simulation, the GPU architecture is able to efficiently handle large-scale data and achieve faster convergence, significantly reducing the overall simulation time. Particularly in handling larger-scale water distribution networks, the GPU architecture can improve computational efficiency by up to 13 times. Further analysis reveals that different GPU models exhibit significant differences in computational efficiency, with memory capacity being a key factor affecting performance. GPU devices with larger memory capacity demonstrate higher computational efficiency when processing large-scale water distribution networks. This study demonstrates the advantages of GPU acceleration technology in the simulation of large-scale urban water distribution networks and provides important theoretical and technical support for practical applications in this field. By carefully selecting and configuring GPU devices, the computational efficiency of large-scale water distribution networks can be significantly improved, providing more efficient solutions for future urban water resource management and planning.