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Drought indices are crucial for assessing and managing water scarcity and agricultural risks; however, the lack of a unified data foundation in existing datasets leads to inconsistencies that challenge the comparability of drought indices. This study is dedicated to creating CHM_Drought, an innovative and comprehensive long-term meteorological drought dataset with a spatial resolution of 0.1° and data collected from 1961 to 2022 in mainland China. It features six pivotal meteorological drought indices: the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), evaporative demand drought index (EDDI), Palmer drought severity index (PDSI), self-calibrating Palmer drought severity index (SC-PDSI), and vapor pressure deficit (VPD), of which SPI, SPEI, and EDDI contain multi-scale features for periods of 2 weeks and 1–12 months. The dataset features a comprehensive application of high-density meteorological station data and a complete framework starting from basic meteorological elements (the China Hydro-Meteorology dataset, CHM). Demonstrating its robustness, the dataset excels in accurately capturing drought events across mainland China, as evidenced by its detailed depiction of the 2022 summer drought in the Yangtze River basin. In addition, to evaluate CHM_Drought, we performed consistency tests with the drought indices calculated based on Climatic Research Unit (CRU) and CN05.1 data and found that all indices had high consistency overall and that the 2-week scale SPI, SPEI, and EDDI had potential early warning roles in drought monitoring. Overall, our dataset bridges the gap in high-precision multi-index drought data in China, and the complete CHM-based framework ensures the consistency and reliability of the dataset, which contributes to enhancing the understanding of drought patterns and trends in China. Free access to the dataset can be found at https://doi.org/10.6084/m9.figshare.25656951.v2 (Zhang and Miao, 2024). [ABSTRACT FROM AUTHOR]

Low flows in the Swiss Plateau are expected to occur more often, to last longer and, hence, to be more severe under climate change. To predict and manage such periods of water scarcity effectively, more precise information on the drainage behavior of catchments is required. The drainage behavior of a catchment can be characterized by recession analysis methods (RAMs; e.g., recession curves) of which several have been developed in the last decades. Their recession parameters have been related to different aquifer characteristics or more general catchment characteristics like lithology, topography, or climatology. Such parameters vary widely, and the effects of uncertainties on the model's outcomes are diverse and complex. Despite the obvious potential of recession curves for prediction, they have so far not been used for operational low flow prediction and guidance for hazard mitigation. In addition, recession curves of slowly draining catchment states are hardly represented by current RAMs. To fill the gap of RAMs representing slow draining catchment states we developed two novel RAMs, one fully automated and based on the matching strip method (MRC_slow), the other one (SDSC) relying on a careful expert-based selection of few recession segments with the slowest recession behavior. Alongside we used three established RAMs from the literature (one further matching strip model, linear regression and lower envelope in the discharge decay – discharge recession diagram). We applied the five RAMs on previously extracted low flow segments of 33 catchments in the Swiss Plateau and compared them on their recession curvatures, durations, and volumes. We designed a procedure that evaluates which of any selected RAMs best matches the recession behavior of individual low flow segments of a hydrograph. Applying this in a simulated prediction situation, we evaluated in retrospect, which of the five specifically selected RAMs predicted the low flow hydrographs between 2021 and 2022 most accurately. We found the variability of recession durations and volumes between catchments to be higher than between the five RAMs. Within 30 of the 33 catchments, the order of recession durations and recession volumes was the same. Hence the different recession behaviors of the RAMs could be related to different catchment states. Upon evaluating the low flow predictions, we found that the MRC_slow approach overall performed best followed by linear regression and SDSC. However, for operational low flow prediction we recommend using four of the five RAMs. This allows for changing the recession model(s) at every timestep if the recession behavior changes. It is also possible to present predictions with a model ensemble, indicating a range of uncertainties if several models perform similarly well. The described data-driven approach and the newly developed models are, therefore, very promising for improving low flow predictions in gauged catchments. [ABSTRACT FROM AUTHOR]

Water scarcity is often triggered by shifting climate patterns as well as rising water usage, yet state-of-the-art Earth system models typically do not represent human water demand. Here we present an enhancement to the Community Earth System Model (CESM) and its land (CLM) and river (MOSART) components by introducing sectoral water abstractions. The new module enables a better understanding of water demand and supply dynamics across various sectors, including domestic, livestock, thermoelectric, manufacturing, mining, and irrigation. The module conserves water by integrating abstractions from the land component with river component flows, and dynamically calculates daily water scarcity based on local demand and supply. Through land-only simulations spanning 1971–2010, we verify our model against known water scarcity hotspots, historical global water withdrawal trends, and regional variations in water use. Our findings reaffirm the role of irrigation in modulating local surface energy fluxes, while emphasizing the importance of including all sectors for water scarcity assessment capabilities. While the model captures global patterns, it also discerns regional nuances, expanding on the conventional focus on irrigation withdrawals in Earth system models (ESMs). Despite its advancements, the model's limitations, such as its exclusive focus on river water abstractions, highlight areas for potential future refinement. This research paves the way for a more holistic representation of human-water interactions in ESMs, aiming to inform sustainable water management decisions in an evolving global landscape. [ABSTRACT FROM AUTHOR]

A cascade of drought impacts refers to a series of interconnected events that trigger a chain reaction of impacts, extending beyond water scarcity, to affect agricultural production, socio-economic factors, and the environment. This paper aims to understand the role of society in mitigating drought impacts, particularly through policy responses. Conducting a case study in Ceará state, northeast Brazil, we used a global rare dataset of continuously drought monitoring, complemented by interviews with smallholder farmers and agricultural extension technicians. Additionally, we analyzed policy documents related to public policies implemented at the local level. Employing a classification of drought impacts as our analytical framework, our findings indicate that socio-environmental-economic impacts of drought are less frequently reported, suggesting that development policies are mitigating cascading effects on livelihoods. Most impacts are associated with hydrological impacts of drought, suggesting unintended consequences of investments in increasing water supply. We emphasize the significant contribution of public policies to mitigating the cascading effects of drought, which do not necessarily involve increasing water availability, but strengthen the local economy. [ABSTRACT FROM AUTHOR]

The water supply of water resources allocation under extreme drought is insufficient, and the limited available water resources make it urgent to tap the potential of water supply. In this paper, the Yellow River water supply area in Henan Province is taken as an example to study the multi-water source allocation under extreme drought. According to the Palmer Drought Severity Index (PDSI), the extreme drought years are selected, and the water supply and demand balance in the extreme drought years is analyzed, and the water shortage degree of each water supply area is obtained. In this paper, unconventional water, flood resource utilization and elastic exploitation of groundwater are used as potential water sources. Different water supply scenarios are set up according to different potential tapping measures, and multi-scenario supply increase under extreme drought is explored. A multi-water source allocation model with the goal of minimizing water shortage is constructed, and a multi-scenario supply increase allocation scheme is proposed, which provides a basis for the study of water supply increase allocation to alleviate the drought degree of the the Yellow River Water Supply Area in Henan. Through the Multi-scenario potential tapping of multiple water sources, the existing potential water volume can be maximized, which is conducive to reducing the water supply pressure and water use restrictions of conventional water sources, improving the support capacity and guarantee capacity of water resources, and reducing the economic and social development bottlenecks caused by extreme drought. [ABSTRACT FROM AUTHOR]

Water scarcity is a pressing global issue driven by increasing water demands and changing climate conditions. Based on novel estimates of water availability and water use in Chile, we examine the challenges and risks associated with groundwater (GW) withdrawals in the country's central-north region (27–35° S), where extreme water stress conditions prevail. As total water use within a basin approaches the renewable freshwater resources, the dependence on GW reserves intensifies in unsustainable ways. This overuse has consequences that extend beyond mere resource depletion, manifesting into environmental degradation, societal conflict, and economic costs. We argue that the "Day Zero" scenario, often concealed by the uncertain attributes of GW resources, calls for a reconsideration of water allocation rules and a broader recognition of the long-term implications of unsustainable GW use. Our results offer insights for regions worldwide facing similar water scarcity challenges and emphasize the importance of proactive and sustainable water management strategies. [ABSTRACT FROM AUTHOR]

The increasing water demand due to human activities has aggravated water scarcity, and conflicts among stakeholders have increased the risk of unsustainable development. Ignoring the effects of trade-offs leads to misguided policy recommendations. This study highlights the concept of synergy among different aspects of the water allocation process. A process-based three-layer synergistic optimal-allocation (PTSOA) model is established to integrate the interests of stakeholders across sub-regions, decision levels, and time steps while simultaneously coupling reclaimed water to establish environmentally friendly solutions. A synergy degree index is constructed by applying network analysis for optimization. PTSOA is applied in Yiwu, southeast China, and is shown to be able to improve the contradictions among different dimensionalities in a complex system. Overall, 2.43×107 – 3.95×107 m 3 of conventional water is saved, and notable improvements in management are achieved. The application demonstrates the efficiency and excellent performance of the PTSOA model. [ABSTRACT FROM AUTHOR]

Drought is a complex climatic phenomenon characterized by water scarcity recognized as the most widespread and insidious natural hazard, posing significant challenges to ecosystems and human society. In this study, we propose a new daily based index for characterizing droughts, which involves standardizing precipitation and/or precipitation minus potential evapotranspiration data. The performance of this new index is assessed with data from the evaluation runs of the Coordinated Regional Climate Downscaling Experiment for the European domain and the observational data from the Iberian Gridded Dataset, covering the period from 1989 to 2009. Comparative assessments are conducted against the daily Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and a simple Z-Score standardization of climatic variables. Seven different accumulation periods are considered (7, 15, 30, 90, 180, 360, and 720 days) with three drought levels: moderate, severe, and extreme. The evaluation focuses mainly on the direct comparison amongst indices, added value assessment using the Distribution Added Value and a simple bias difference for drought characteristics. Results reveal that not only does the new index allow the characterization of flash droughts, but also demonstrates added value when compared to SPI and SPEI, especially for longer accumulation periods. In comparison to the Z-Score, the new index shows slightly greater gains, particularly for extreme drought events at lower accumulation periods. Furthermore, an assessment of the spatial extent of drought for the 2004–2005 event is performed using the observational dataset. All three indices generally provide similar representations, except for the Z-Score, which exhibits limitations in capturing extreme drought events at lower accumulation periods. Overall, the findings suggest that the new index offers improved performance and adds value comparatively to similar indices with a daily time step. [ABSTRACT FROM AUTHOR]

Large-scale hydrological models (LHMs) are commonly used for regional and global assessment of future water shortage outcomes under climate and socioeconomic scenarios. The irrigation of croplands, which accounts for the lion's share of human water consumption, is critical in understanding these water shortage trajectories. Despite irrigation's defining role, LHM frameworks typically impose trajectories of land use that underlie irrigation demand, neglecting potential dynamic feedbacks in the form of human instigation of and subsequent adaptation to water shortages via irrigated crop area changes. We extend an LHM, MOSART-WM, with adaptive farmer agents, applying the model to the continental United States to explore water shortage outcomes that emerge from the interplay between hydrologic-driven surface water availability, reservoir management, and farmer irrigated crop area adaptation. The extended modeling framework is used to conduct a hypothetical computational experiment comparing differences between a model run with and without the incorporation of adaptive farmer agents. These comparative simulations reveal that accounting for farmer adaptation via irrigated crop area changes substantially alters modeled water shortage outcomes, with US-wide annual water shortages being reduced by as much as 42 % when comparing adaptive and non-adaptive versions of the model forced with US climatology from the period 1950–2009. [ABSTRACT FROM AUTHOR]

Inter-basin water transfer projects are the main measure to address the water deficit crisis caused by uneven distribution of water resources. The current water transfer operation mainly tends to be present in areas with small water transfer costs and is prone to encounter the problem of spatial and temporal imbalances in water allocation. To address these issues, this paper defines a water deficit evenness index (WDEI), aimed at minimizing regional differences in water scarcity and sharing the pressure of water scarcity as a social demand objective. This index is incorporated into a joint optimization model for the Jiangsu section of the South-to-North Water Diversion Project (J-SNWDP), which comprises both the ecological objective of the total water deficit (TWD) and the economic objective of the pumping water (PW). Further, the Nondominated Sorting Genetic Algorithm III (NSGA-III) and multi-attribute decision-making were applied to solve the model and obtain an optimal operation strategy. The results showed the following: (1) the WDEI defined in this paper can mitigate the synchronized water scarcity in certain water users. In typical normal years (wet year and dry year), the WDEI shows a reduction of 94.2 % (81.8 %, 76.7 %) compared to the historical operation strategy. (2) The optimized operation strategy can significantly reduce TWD and PW by 82.06% (37.69 %, 52.36 %) and 45.13 % (3.25 %, 21.51 %) compared with the historical values, respectively, which can improve the water supply satisfaction and reduce the project cost. At the same time, the lake storage capacity of the optimal operation strategy performs well, and the water transfer efficiency of the river is significantly improved. (3) In this paper, targeted optimal operation strategies and potential ways to secure the project tasks are proposed for different natural flow. Overall, it is of great significance to study the water supply equity in the J-SNWDP to alleviate the concentrated water deficit in Jiangsu Province and other similar regions. [ABSTRACT FROM AUTHOR]

Water productivity (or efficiency) data inform water policy, zoning, and planning, along with water allocation decisions under water scarcity pressure. This paper demonstrates that different water productivity metrics lead to different conclusions about who is using water more effectively. In addition to supporting the population's drinking and sanitation needs, water generates many other public and private social, environmental, and economic values. For the group of municipalities comprising the Phoenix metropolitan area, we compare several water productivity metrics by calculating the water value intensity (WVI) of potable water delivered by the municipality to its residential and non-residential customers. Core cities with more industrial water uses are less productive by the conventional efficiency measure of water used per capita, but core cities generate more tax revenues, business revenues, and payroll per unit of water delivered, achieving a higher water productivity by these measures. We argue that policymakers should consider a more diverse set of socio-economic water productivity measures to ensure that a broader set of values are represented in water allocation policies. [ABSTRACT FROM AUTHOR]

The availability of fresh water over land may become increasingly scarce under climate change, and natural and human-induced tree cover changes can further enhance or negate the water scarcity. Previous studies showed that global tree cover change can have large impacts on water availability under current climate conditions, but did not touch upon the implications of global tree cover change under climate change. Here, we study the hydrological impacts of large-scale tree cover change (climate-induced changes in combination with large-scale afforestation) in a future climate (SSP3-7.0) following an interdisciplinary approach. By combining data from five CMIP6 climate models with a future potential tree cover dataset, six Budyko models, and the UTrack moisture recycling dataset, we can disentangle the impacts of climate change and future tree cover change on evaporation, precipitation, and runoff. We quantify per grid cell and for five selected river basins (Yukon, Mississippi, Amazon, Danube, and Murray-Darling) if tree cover changes enhance or counteract the climate-driven changes in runoff due to their impact on evapotranspiration and moisture recycling. Globally averaged, the impacts of climate change and large-scale tree cover change on runoff are of similar magnitude with opposite signs. While climate change increases the global runoff, the changing tree cover reverses this effect which overall results in a limited net impact on runoff relative to the present climate and current tree cover. Nevertheless, locally the change in runoff due to tree cover change and climate change can be substantial with increases and decreases of more than 100 mmyear-1. We show that for approximately 16 % of the land surface, tree cover change can increase the water availability significantly. However, we also find that, for 14 % of the land surface, both tree cover change and climate change might decrease water availability with more than 5 mm year-1. For each of the selected catchments, the direction and magnitude of the impacts of climate change and tree cover change vary, with dominating climate change impacts in all basins except the Mississippi River basin. Our results show that ecosystem restoration projects targeting an altered tree cover should consider the corresponding hydrological impacts to limit unwanted (non-)local reductions in water availability. [ABSTRACT FROM AUTHOR]

Potential for regional climate engineering is gaining interest as a means of solving regional environmental problems like water scarcity and high temperatures. In the hyper-arid United Arab Emirates (UAE), water scarcity is reaching a crisis point due to high consumption and over-extraction and is being exacerbated by climate change. To counteract this problem, the UAE has conducted cloud-seeding operations and intensive desalination for many years but is now considering other means of increasing water resources. Very large "artificial black surfaces" (ABSs), made of black mesh, black-painted, or solar photovoltaic (PV) panels have been proposed as a means of enhancing convective precipitation via surface heating and amplification of vertical motion. Under the influence of the daily UAE sea breeze, this can lead to convection initiation under the right conditions. Currently it is not known how strong this rainfall enhancement would be or what scale of black surface would need to be employed. This study simulates the impacts at different ABS scales using the WRF-Noah-MP model chain and investigates impacts on precipitation quantities and underlying convective processes. Simulations of five square ABSs of 10, 20, 30, 40, and 50 km sizes were made on four 1 d cases, each for a period of 24 h. These were compared with a Control model run, with no land use change, to quantify impacts. The ABSs themselves were simulated by altering land cover static data and prescribing a unique set of land surface parameters like albedo and roughness length. On all 4 d, rainfall is enhanced by low-albedo surfaces of 20 km or larger, primarily through a reduction of convection inhibition and production of convergence lines and buoyant updrafts. The 10 km square ABS had very little impact. From 20 km upwards there is a strong scale dependency, with ABS size influencing the strength of convective processes and volume of rainfall. In terms of rainfall increases, 20 km produces a mean rainfall increase over the Control simulation of 571 616 m 3 d -1 , with the other sizes as follows: 30 km (∼ 1 million m 3 d -1), 40 km (∼ 1.5 million m 3 d -1), and 50 km (∼ 2.3 million m 3 d -1). If we assume that such rainfall events happen only on 10 d in a year, this would equate to respective annual water supplies for > 31 000, > 50 000, > 79 000, and > 125 000 extra people yr -1 at UAE per capita consumption rates. Thus, artificial heat islands made from black panels or solar PV offer a means of enhancing rainfall in arid regions like the UAE and should be made a high priority for further research. [ABSTRACT FROM AUTHOR]

The issue of water scarcity, exacerbated by climate change and demographic increase, has become a growing concern in many regions throughout the world. Understanding hydrological behaviour to promote resilient and sustainable water management is paramount. Hydrological models that integrate natural processes and anthropogenic alterations of the basin's hydrology are a powerful tool to support decision-making. We developed a SWAT+ hydrological model including stakeholder expert knowledge on water management and introducing a novel calibration and validation approach suitable for heterogeneous basins in space and / or time. We also assessed spatio-temporal patterns and trends of streamflow during the first two decades of the 21st century in the Catalan River Basin District, in the western Mediterranean, using a wide variety of indicators to fully characterize the hydrological regime. We calibrated and validated the model using data from 50 gauging stations, verifying the usefulness of the new calibration and validation strategy. Co-development with stakeholders and the integration of expert knowledge, most notably on reservoir operations, helped improve model performance. Results revealed a generalized streamflow reduction, as well as increased dominance of streamflow flashiness and zero-flows recurrence. We also observed differences in seasonal trends, with autumn being the most affected season. These results provide insights into how climate change and anthropogenic pressures are going to keep affecting water resources availability in the future, thus raising the need for sustainable management practices in the Catalan River Basin District, as well as other regions vulnerable to water scarcity. [ABSTRACT FROM AUTHOR]

Understanding the thermal behavior of lakes is crucial for water quality management. Under climate change, lakes are warming and undergoing alterations in their thermal structure, including surface water and deepwater temperatures. These changes require continuous monitoring due to the possible major ecological implications for water quality and lake processes. We combined numerical modeling and satellite thermal data to create a regional dataset (LakeTSim: Lake Temperature Simulations) of long-term water temperatures for 401 French lakes in order to tackle the scarcity of in situ water temperature (Sharaf et al., 2023; 10.57745/OF9WXR). The dataset consists of daily epilimnion and hypolimnion water temperatures for the period 1959–2020 simulated with the semi-empirical OKPLM (Ottosson–Kettle–Prats Lake Model) and the associated uncertainties. Here, we describe the model and its performance. Additionally, we present an uncertainty analysis of simulations with default parameter values (parameterized as a function of lake characteristics) and calibrated parameter values along with the analysis of the sensitivity of the model to parameter values and biases in the input data. Overall, the 90 % confidence uncertainty range is largest for hypolimnion temperature simulations, with medians of 8.5 and 2.32 ∘ C, respectively, with default and calibrated parameter values. There is less uncertainty associated with epilimnion temperature simulations, with medians of 5.42 and 1.85 ∘ C, respectively, before and after parameter calibration. This dataset provides over 6 decades of epilimnion and hypolimnion temperature data crucial for climate change studies at a regional scale. It will help provide insight into the thermal functioning of French lakes and can be used to help decision-making and stakeholders. [ABSTRACT FROM AUTHOR]

Human actions induce and modify droughts. However, scientific gaps remain with respect to how hydrological processes, anthropogenic dynamics, and individuals' perceptions of impacts are intrinsically entangled in drought occurrence and evolution. This adds complexity to drought assessment studies that cannot be addressed by the natural and environmental sciences alone. Furthermore, it poses a challenge with respect to developing ways to evaluate human behaviour and its pattern of co-evolution with the hydrological cycle – mainly related to water use and landscape modifications. During fieldwork in Brazil, we observed how drought impacts were experienced by people who were exposed to a multi-year drought. Evaluating our data, it appeared that prospect theory, a behavioural economic theory that is usually applied to explain decision-making processes under uncertainty, has explanatory power regarding what we observed in the field. Therefore, we propose an interdisciplinary approach to improve the understanding of drought impact emergence using this theory. When employing prospect theory in this context, drought impacts are considered failed welfare expectations ("prospects") due to water shortage. A shifting baseline after prolonged exposure to drought can therefore mitigate experienced drought impacts. We demonstrate that this theory can also contribute to explaining socio-hydrological phenomena, such as reservoir effects. This new approach can help bridge natural science and social science perspectives, resulting in integrated drought management that considers the local context. [ABSTRACT FROM AUTHOR]

The relation between drought severity and drought impacts is complex and relatively unexplored in the African continent. This study assesses the relation between reported drought impacts, drought indices, water scarcity and aridity across several counties in Kenya. The monthly bulletins of the National Drought Management Authority in Kenya provided drought impact data. A random forest (RF) model was used to explore which set of drought indices (standardized precipitation index, standardized precipitation evapotranspiration index, standardized soil moisture index and standardized streamflow index) best explains drought impacts on pasture, livestock deaths, milk production, crop losses, food insecurity, trekking distance for water and malnutrition. The findings of this study suggest a relation between drought severity and the frequency of drought impacts, whereby the latter also showed a positive relation with aridity. A relation between water scarcity and aridity was not found. The RF model revealed that every region, aggregated by aridity, had their own set of predictors for every impact category. Longer timescales (≥ 12 months) and the standardized streamflow index were strongly represented in the list of predictors, indicating the importance of hydrological drought to predict drought impact occurrences. This study highlights the potential of linking drought indices with text-based impact reports while acknowledging that the findings strongly depend on the availability of drought impact data. Moreover, it emphasizes the importance of considering spatial differences in aridity, water scarcity and socio-economic conditions within a region when exploring the relationships between drought impacts and indices. [ABSTRACT FROM AUTHOR]

The European continent is regularly affected by a wide range of extreme events and natural hazards including heatwaves, extreme precipitation, droughts, cold spells, windstorms, and storm surges. Many of these events do not occur as single extreme events, but rather show a multivariate character, the so-called compound events. Within the scope of the interdisciplinary project climXtreme (https://climxtreme.net/), we investigate the interplay of extreme weather events, their characteristics and changes, intensity, frequency and uncertainties in the past, present and future and associated impacts on various socio-economic sectors in Germany and Central Europe. This contribution presents several case studies with special emphasis on the calendar year of 2018, which is of particular interest given the exceptional sequence of different compound events across large parts of Europe, with devastating impacts on human lives, ecosystems and infrastructure. We provide new evidence on drivers of spatially and temporally compound events (heat and drought; heavy precipitation in combination with extreme winds) with adverse impacts on ecosystems and society using large-scale atmospheric patterns. We shed light on the interannual influence of droughts on surface water and the impact of water scarcity and heatwaves on agriculture and forests. We assessed projected changes in compound events at different current and future global surface temperature levels, demonstrating the importance of better quantifying the likelihood of future extreme events for adaptation planning. Finally, we addressed research needs and future pathways, emphasising the need to define composite events primarily in terms of their impacts prior to their statistical characterisation. [ABSTRACT FROM AUTHOR]

Large-scale hydrological models (LHMs) are commonly used for regional and global assessment of future water shortage outcomes under climate and socioeconomic scenarios. The irrigation of croplands, which accounts for the lion's share of human water consumption, is critical in understanding these water shortage trajectories. Despite irrigation's defining role, LHM frameworks typically impose trajectories of land use that underlie irrigation demand, neglecting potential dynamic feedbacks in the form of human instigation of and subsequent adaptation to water shortage via irrigated crop area changes. We extend an LHM, MOSART-WM, with adaptive farmer agents, applying the model to the Continental United States to explore water shortage outcomes that emerge from the interplay between hydrologic-driven surface water availability, reservoir management, and farmer irrigated crop area adaptation. The extended modeling framework is used to conduct hypothetical computational experiment comparing differences between a model run with and without the incorporation of adaptive farmer agents. These comparative simulations reveal that accounting for farmer adaptation via irrigated crop area changes substantially alters modeled water shortage outcomes, with U.S.-wide annual water shortage reduced by as much as 42 percent when comparing adaptive and non-adaptive versions of the model forced with U.S. climatology from 1950–2009. [ABSTRACT FROM AUTHOR]

The Mediterranean Basin has experienced one of the highest warming rates on earth during the last few decades, and climate projections predict water scarcity in the future. Mid-latitude Mediterranean mountain areas, such as the Pyrenees, play a key role in the hydrological resources for the highly populated lowland areas. However, there are still large uncertainties about the impact of climate change on snowpack in the high mountain ranges of this region. Here, we perform a snow sensitivity to temperature and precipitation change analysis of the Pyrenean snowpack (1980–2019 period) using five key snow–climatological indicators. We analyzed snow sensitivity to temperature and precipitation during four different compound weather conditions (cold–dry (CD), cold–wet (CW), warm–dry (WD), and warm–wet (WW)) at low elevations (1500 m), mid elevations (1800 m), and high elevations (2400 m) in the Pyrenees. In particular, we forced a physically based energy and mass balance snow model (FSM2), with validation by ground-truth data, and applied this model to the entire range, with forcing of perturbed reanalysis climate data for the period 1980 to 2019 as the baseline. The FSM2 model results successfully reproduced the observed snow depth (HS) values (R2>0.8), with relative root mean square error and mean absolute error values less than 10 % of the observed HS values. Overall, the snow sensitivity to temperature and precipitation change decreased with elevation and increased towards the eastern Pyrenees. When the temperature increased progressively at 1 ∘ C intervals, the largest seasonal HS decreases from the baseline were at +1 ∘ C. A 10 % increase in precipitation counterbalanced the temperature increases (≤1 ∘ C) at high elevations during the coldest months because temperature was far from the isothermal 0 ∘ C conditions. The maximal seasonal HS and peak HS max reductions were during WW seasons, and the minimal reductions were during CD seasons. During WW (CD) seasons, the seasonal HS decline per degree Celsius was 37 % (28 %) at low elevations, 34 % (30 %) at mid elevations, and 27 % (22 %) at high elevations. Further, the peak HS date was on average anticipated for 2, 3, and 8 d at low, mid, and high elevation, respectively. Results suggest snow sensitivity to temperature and precipitation change will be similar at other mid-latitude mountain areas, where snowpack reductions will have major consequences for the nearby ecological and socioeconomic systems. [ABSTRACT FROM AUTHOR]

The impact of droughts on vegetation is essentially manifested as the transition of water shortage from the meteorological to ecological stages. Therefore, understanding the mechanism of drought propagation from meteorological to ecological drought is crucial for ecological conservation. This study proposes a method for calculating the probability of meteorological drought to trigger ecological drought at different magnitudes in northwestern China. In this approach, meteorological and ecological drought events during 1982–2020 are identified using the three-dimensional identification method; the propagated drought events are extracted according to a certain spatiotemporal overlap rule, and propagation probability is calculated by coupling the machine learning model and C-vine copula. The results indicate that (1) 46 drought events are successfully paired with 130 meteorological and 184 ecological drought events during 1982–2020, and ecological drought exhibits a longer duration but smaller affected area and severity than meteorological drought; (2) a quadratic discriminant analysis (QDA) classifier performs the best among the 11 commonly used machine learning models which are combined with four-dimensional C-vine copula to construct the drought propagation probability model; and (3) the hybrid method considers more drought characteristics and a more detailed propagation process which addresses the limited applicability of the traditional method to regions with large spatial extent. [ABSTRACT FROM AUTHOR]

Although evidence of the hydrological response of watersheds to climate change is abundant, reliable assessments of water yield (WY) over mountainous regions, such as the Upper Brahmaputra River (UBR) basin, remain unclear. Here, we examine long-term WY changes during 1982–2013 in the UBR basin, based on multi-station runoff observations. We find that there are significant shifts in hydrological regimes in the late 1990s; WY increases in the range of ∼10 % to ∼80 %, while the directions reverse from increasing to decreasing. Additionally, the double mass curve (DMC) technique is used to assess the effects of climate, vegetation, and cryosphere on WY changes. Results show that cryosphere and climate together contribute to over 80 % of the increase in WY across the entire UBR basin, while the role of vegetation is negligible. The combined effects, however, are either offsetting or additive, thus leading to slight or substantial magnitude increases, respectively. The downward WY trend has primarily been regulated by decreased precipitation in recent years. However, we find that meltwater may alleviate the resulting water shortage in some basins. Therefore, the combined effects of climate and cryosphere on WY should be considered in future water resources management over mountainous basins, particularly involving co-benefits between upstream and downstream regions. [ABSTRACT FROM AUTHOR]

Ambient fine particulate matter (PM 2.5) pollution is a major health risk. Networks of low-cost sensors (LCS) are increasingly being used to understand local-scale air pollution variation. However, measurements from LCS have uncertainties that can act as a potential barrier to effective decision making. LCS data thus need adequate calibration to obtain good quality PM 2.5 estimates. In order to develop calibration factors, one or more LCS are typically co-located with reference monitors for short or long periods of time. A calibration model is then developed that characterizes the relationships between the raw output of the LCS and measurements from the reference monitors. This calibration model is then typically transferred from the co-located sensors to other sensors in the network. Calibration models tend to be evaluated based on their performance only at co-location sites. It is often implicitly assumed that the conditions at the relatively sparse co-location sites are representative of the LCS network overall and that the calibration model developed is not overfitted to the co-location sites. Little work has explicitly evaluated how transferable calibration models developed at co-location sites are to the rest of an LCS network, even after appropriate cross-validation. Further, few studies have evaluated the sensitivity of key LCS use cases, such as hotspot detection, to the calibration model applied. Finally, there has been a dearth of research on how the duration of co-location (short-term or long-term) can impact these results. This paper attempts to fill these gaps using data from a dense network of LCS monitors in Denver deployed through the city's "Love My Air" program. It offers a series of transferability metrics for calibration models that can be used in other LCS networks and some suggestions as to which calibration model would be most useful for achieving different end goals. [ABSTRACT FROM AUTHOR]

Hydrological modeling tools can support collaborative decision processes by visually displaying hydrological systems connections, uncertainties, as well as conflicting preferences over water management strategies. Nevertheless, many challenges remain in the real application of these technical tools to successfully implement, capture, and communicate with non-experts the complexities of coupled human hydrological systems. A 5-step process shows how a WEAP-based hydrological study aiming to explore the disappearance of a 12 km 2 lake in the Aculeo basin in Chile was transformed into a multiple question-driven sociohydrological modeling process to help answer the diversity of questions instigating conflict. Collaboration allowed construction of a surface–groundwater hydrological model that responded to local stakeholders' uncertainties. While testing a subset of socially accepted management strategies under two climate change scenarios, combining the strategies allows recovering up to half the lake water volume. However, the 5-step participatory modeling process also shows how the increasing social–environmental conflicts over the causes and effects of the water scarcity are challenging barriers to overcome with modeling tools. As presented in this article, although flexible approaches and research agendas could better support the exploration of synergies towards collaboration and production of useful and socially acceptable hydrological models, there are still value-driven aspects of water management that need to be explored to better support science policy dialogues. [ABSTRACT FROM AUTHOR]

Sustainable management of the water–energy–food (WEF) nexus remains an urgent challenge, as interactions between WEF and human sensitivity and reservoir operation in the water system are typically neglected. This study proposes a new approach for modeling the WEF nexus by incorporating human sensitivity and reservoir operation into the system. The co-evolution behaviors of the nexus across water, energy, food, and society (WEFS) were simulated using the system dynamic model. Reservoir operation was simulated to determine the water supply for energy and food systems by the Interactive River–Aquifer Simulation water resources allocation model. Shortage rates for water, energy, and food resulting from the simulations were used to qualify their impacts on the WEFS nexus through environmental awareness in society. Human sensitivity indicated by environmental awareness can then adjust the co-evolution behaviors of the WEFS nexus through feedback loops. The proposed approach was applied to the mid–lower reaches of the Hanjiang River basin in China as a case study. Results indicate that environmental awareness shows the potential to capture human sensitivity to shortages from water, energy, and food systems. Parameters related to boundary conditions and critical values can dominate environmental awareness feedback to regulate socioeconomic expansion to maintain the integrated system from constant resource shortages. The annual average energy shortage rate thereby decreased from 17.16 % to 5.80 % by taking environmental awareness feedback, which contributes to the sustainability of the WEFS nexus. Rational water resources allocation can ensure water supply through reservoir operation. The annual average water shortage rate decreased from 15.89 % to 7.20 % as water resources allocation was considered. Threats from water shortage on the concordant development of the WEFS nexus are significantly alleviated, particularly for the area with a limited regulating capacity for the water project. Therefore, this study contributes to the understanding of interactions across the WEFS systems and helps in improving the efficiency of resource management. [ABSTRACT FROM AUTHOR]

Maintaining good surface water quality is crucial to protect ecosystem health and for safeguarding human water use activities. Yet, our quantitative understanding of surface water quality is mostly predicated upon observations at monitoring stations that are highly limited in space and fragmented across time. Physically-based models, based upon pollutant emissions and subsequent routing through the hydrological network, provide opportunities to overcome these shortcomings. To this end, we have developed the dynamical surface water quality model (DynQual) for simulating water temperature (Tw) and concentrations of total dissolved solids (TDS), biological oxygen demand (BOD) and fecal coliform (FC) with a daily timestep and at 5 arc-minute (~10km) spatial resolution. Here, we describe the main components of this new global surface water quality model and evaluate model performance against in-situ water quality observations. Furthermore, we describe both the spatial patterns and temporal trends in TDS, BOD and FC concentrations for the period 1980-2019, also attributing the dominant contributing sectors. The model code is available open-source (https://github.com/UU-Hydro/DYNQUAL) and we provide global datasets of simulated hydrology, Tw, TDS, BOD and FC at 5 arc-minute resolution with a monthly timestep (https://doi.org/10.5281/zenodo.7139222). This data has potential to inform assessments in a broad range of fields, including ecological, human health and water scarcity studies. [ABSTRACT FROM AUTHOR]

Observational data scarcity often limits the potential of rainfall-runoff modelling around the globe. In ungauged catchments, earth-observations or reanalysis products could be used to replace missing ground-based station data. However, performance of different datasets needs to be thoroughly tested, especially at finer temporal resolutions such as hourly time steps. This study evaluates the performance of ERA5-Land and COSMO-REA6 precipitation reanalysis products (PRPs) using 16 meso-scale catchments located in Slovenia, Europe. These two PRPs are firstly compared with a gridded precipitation dataset that was constructed based on ground observational data. Secondly, a comparison of the temperature data of these reanalysis products with station-based air temperature data is conducted. Thirdly, several data combinations are defined and used as input for the rainfall-runoff modelling using the GR4H model. A special focus is on the application of an additional snow module. Both tested PRPs underestimate, for at least 20 %, extreme rainfall events that are the driving force of natural hazards such as floods. In terms of air temperature both tested reanalysis products show similar deviations from the observational dataset that was catchment-specific. Additionally, air temperature deviations are smaller in winter compared to summer. In terms of rainfall-runoff modelling, the ERA5-Land yields slightly better performance than COSMO-REA6. If a re-calibration with PRP has been carried out, the performance is similar compared to the simulations where station-based data was used as input. Model recalibration proves to be essential in providing relatively sufficient rainfall-runoff modelling results. Hence, tested PRPs could be used as an alternative to the station-based based data in case that precipitation or air temperature data are lacking, but model calibration using discharge data would be needed to improve the performance. [ABSTRACT FROM AUTHOR]

The China–Pakistan Economic Corridor (CPEC) is one of the flagship projects of the One Belt One Road Initiative, which faces threats from water shortage and mountain disasters in the high-elevation region, such as glacial lake outburst floods (GLOFs). An up-to-date high-quality glacial lake dataset with parameters such as lake area, volume, and type, which is fundamental to water resource and flood risk assessments and prediction of glacier–lake evolutions, is still largely absent for the entire CPEC. This study describes a glacial lake dataset for the CPEC using a threshold-based mapping method associated with rigorous visual inspection workflows. This dataset includes (1) multi-temporal inventories for 1990, 2000, and 2020 produced from 30 m resolution Landsat images and (2) a glacial lake inventory for the year 2020 at 10 m resolution produced from Sentinel-2 images. The results show that, in 2020, 2234 lakes were derived from the Landsat images, covering a total area of 86.31±14.98 km 2 with a minimum mapping unit (MMU) of 5 pixels (4500 m 2), whereas 7560 glacial lakes were derived from the Sentinel-2 images with a total area of 103.70±8.45 km 2 with an MMU of 5 pixels (500 m 2). The discrepancy shows that Sentinel-2 can detect a large quantity of smaller lakes compared to Landsat due to its finer spatial resolution. Glacial lake data in 2020 were validated by Google Earth-derived lake boundaries with a median (± standard deviation) difference of 7.66±4.96 % for the Landsat-derived product and 4.46±4.62 % for the Sentinel-derived product. The total number and area of glacial lakes from consistent 30 m resolution Landsat images remain relatively stable despite a slight increase from 1990 to 2020. A range of critical attributes has been generated in the dataset, including lake types and mapping uncertainty estimated by an improved equation of Hanshaw and Bookhagen (2014). This comprehensive glacial lake dataset has the potential to be widely applied in studies on water resource assessment, glacial lake-related hazards, and glacier–lake interactions and is freely available at 10.12380/Glaci.msdc.000001 (Lesi et al., 2022). [ABSTRACT FROM AUTHOR]

The Mediterranean basin has experienced one of the highest warming rates on Earth over the last decades and climate projections anticipate water-scarcity future scenarios. Mid-latitude Mediterranean mountain areas such as the Pyrenees play a key role in the hydrological resources for intensely populated lowland areas. However, there are still large uncertainties about the impact of climate change on the snowpack in high mountain ranges of the Mediterranean region. Here, we provide a climate sensitivity analysis of the Pyrenean snowpack through five key snow climate indicators. Snow sensitivity is analyzed during compound temperature and precipitation extreme seasons, namely Cold-Dry (CD), Cold-Wet (CW), Warm-Dry (WD) and Warm-Wet (WW) seasons, for low (1500 m), mid (1800 m) and high (2400 m) elevation sectors of the Pyrenees. To this end, a physically-based energy and mass balance snow model (FSM2) is validated by ground-truth data, and subsequently applied to the entire range, forcing perturbed reanalysis climate data for the 1980–2019 baseline scenario. The results have shown that FSM2 successfully reproduces the observed snow depth (HS) values, reaching R2 > 0.8, and relative RMSE and MAE lower than 10 % of the observed HS. Overall, climate sensitivity decreases with elevation and increases towards the eastern Pyrenees. When temperature is progressively warmed at 1 ºC intervals, the largest seasonal HS decreases from baseline climate are found at +1 ºC, reaching values of -47 %, -48 % and -25 % for low, mid and high elevations, respectively. Only an upward trend of precipitation (+10 %) could counterbalance temperature increases (<= 1 ºC) at high elevations during the coldest months of the season, since temperature is far from the isothermal 0 ºC conditions. The maximum (minimum) seasonal HS and peak HS max reductions are observed on WW (CD) seasons. During the latter seasons, the seasonal HS is expected to be reduced by -37 % (- 28 %), -34 % (- 30 %), -27 % (-22 %) per ºC, at low, mid and high elevation areas, respectively. For snow ablation climate indicators, the largest decreases are observed during WD seasons, when the peak HS date is anticipated 10 days and snow duration (ablation) decreases (increases) 12 % per ºC. The results suggest similar climate sensitivities in mid-latitude mountain areas; where significant snowpack reductions are anticipated, with relevant consequences in the ecological and socioeconomic systems. [ABSTRACT FROM AUTHOR]

Water scarcity is an emerging threat to food security and socio-economic prosperity, and it is crucial to assess crop production response to water scarcity in large river basins. The water footprint, which considers water use in supply chains, provides a powerful tool for assessing the contributions of water resources within a certain region by tracking the volume and structure of virtual water flows. In this study of the structure of the water footprint network from a complexity perspective, we reassessed the significance of water resources for crop services in a large river basin with a severe water shortage – the Yellow River basin (YRB) of China. The temporal increase of the complexity index indicated that the virtual water outflows (VWFs) from the YRB were becoming increasingly critical to China; i.e. the ability of YRB to produce crops boosted the difficulty of its water being replaced by water exporting from other basins. Decomposition of complexity suggested that during the 1980s to 2000s, the temporally increased complexity was due mainly to the lack of competitors and the increasing uniqueness of crops supporting VWFs. This complexity deeply embedded the YRB into the footprints of a water network that facilitated further development with constrained water resources. Still, it also reinforced reliance from other regions on YRB's scarce water. Based on this analysis, we suggest that resource regulation should be carried out appropriately to ensure ecological sustainability and high-quality development of river basins. [ABSTRACT FROM AUTHOR]

The relation between drought severity, as expressed through widely used drought indices, and drought impacts is complex. In particular in water-limited regions where water scarcity is prevalent, the attribution of drought impacts is difficult. This study assesses the relation between reported drought impacts, drought indices, water scarcity, and aridity across several counties in Kenya. The monthly bulletins of the National Drought Management Authority in Kenya have been used to gather drought impact data. A Random Forest (RF) model was used to explore which set of drought indices best explains drought impacts on: pasture, livestock deaths, milk production, crop losses, food insecurity, trekking distance for water, and malnutrition. The findings of this study suggest a relation between drought severity and the frequency of drought impacts, whereby the latter also showed a relation with aridity, whilst water scarcity did not. The results of the RF model reveal that drought impacts can be explained by a range of drought indices across regions with different aridity. While the findings strongly depend on the availability of drought impact data and the socio-economic circumstances within a region, this study highlights the potential of linking drought indices with text-based impact reports. In doing so, however, spatial differences in aridity and water scarcity conditions have to be taken into account. [ABSTRACT FROM AUTHOR]

In Khartoum/Sudan the consumption of water per capita in urban areas far below the real need and WHO standard and huge volume of untreated municipal wastes water and industrial waste is discharged directly to an upstream from the town's sewage water and treatment plants. Only 5% of resident received waste water treatment services, and 95% of waste discharge in unregulated dumps and injected into ground, these leading to pollution of the atmosphere, surface and ground waters, and poses a serious environmental hazard downstream. The main objective of this paper to Simulate pollutant produce from water sector demands being prime indicators of water and environment challenge, using WEAP model, and GIS software.The methodology used in this study to identified appropriate indicators and creates a model that represents water resource status, and pollution generator sectors for a specific system boundary.Khartoum satellite Landsat Mosaic Image (copy write), and Digital elevation model, (DEM) for Sudan, from Global ESRI map, and Land cover map, acquired from Sudanese remote sensing and seismology authority are used in this study to create maps.The Basin Catchment model WEAP21 system scenarios with Remote Sensing, and GIS predicted response and evaluated water deterioration risk quantity and quality related to river Nile catchment area in Khartoum. The model software selected provides decision makers with watershed environmental response factors, with allocation for sustainable water concern lower River Nile catchments.The model approach across user was taken into consideration to ensure withdrawals, assumed improvement in consumption, researcher assumed building a reservoir to improve quality, and reduces people suffering from water shortage, building expansion to reform waste, with reference time from 2015 and projected year by 2030.To fulfill objectives the models was used for pollutant transport from upstream to watershed, to evaluate the effect of applying alternative management practices by development of different Scenarios.Water quality data are collected from Ground water central laboratories, also from Khartoum state data base center. While Waste water data collected from waste water treatment plants in the towns, and from constructional and environmental laboratories, centre. Also, field samples were collected from discharge point in lagoons near river shore and from the cross point of discharge into the river. The study result show how satellite technology combined with local monitoring, GIS, and advanced modeling system can be used to investigate the improved accuracy of the model results, and to improve operations and performance of service providers downstream. The result indicated that scenarios can be developed to explore options for the future and sustainability, and implication of various policies can evaluated. For environmental carrying capacities, the model results indicated that, 90% of water consuming by sector demands end at the receptors as waste water need to be treated. The pollutant load produced by those waste water treatment plants were measured and simulated including pollutant (BOD, COD, TSS, Phosphate, Nitrate, Total organic carbon, heavy metals (Pb, Cr, Zn, Cu), which in turn affects the quality of water resources available for direct use. The improvements in water collection systems affect water supply and wastewater treatment, while the improvement in waste water treatment plants after built new environmental expansion and technology may reduce the flow of waste water to receptors 50% by 2030. In order to ensure a long term development of water resources, and to avoid water becoming a limiting factor in the development of dependent activities, we recommend that country should develop environmental pollution reform and management policy based on an integrated management which associates management of surface and underground waters, qualitative and quantitative measures and management of use by various water sector. [ABSTRACT FROM AUTHOR]

Increasing water scarcity in the Central Andes due to ongoing climate change recently caused a controversy and debate on the significance of permafrost occurrences for the hydrologic cycle. The lack of comprehensive field measurements and quantitative data on the local variability in internal structure and ground ice content further exacerbates the situation. We present field-based data from six extensive geophysical campaigns undertaken since 2016 in three different high-altitude regions of the Central Andes of Chile and Argentina (28 to 32 ∘ S). Our data cover various permafrost landforms ranging from ice-poor bedrock to ice-rich rock glaciers and are complemented by ground truthing information from boreholes and numerous test pits near the geophysical profiles. In addition to determining the thickness of the potential ice-rich layers from the individual profiles, we also use a quantitative four-phase model to estimate the volumetric ground ice content in representative zones of the geophysical profiles. Our analysis of 52 geoelectrical and 24 refraction seismic profiles within this study confirmed that ice-rich permafrost is not restricted to rock glaciers but is also observed in non-rock-glacier permafrost slopes in the form of interstitial ice, as well as layers with excess ice, resulting in substantial ice contents. Consequently, non-rock-glacier permafrost landforms, whose role for local hydrology has so far not been considered in remote-sensing-based approaches, may be similarly relevant in terms of ground ice content on a catchment scale and should not be ignored when quantifying the potential hydrological significance of permafrost. We show that field-geophysics-based estimates of ground ice content, while more labour intensive, are considerably more accurate than remote sensing approaches. The geophysical data can then be further used in upscaling studies to the catchment scale in order to reliably estimate the hydrological significance of permafrost within a catchment. [ABSTRACT FROM AUTHOR]

This study investigates present and future European heat wave magnitudes, represented by the HeatWave Magnitude Index-daily (HWMId), for regional climate models (RCMs) and their driving global climate models (GCMs) over Europe. A subset of the large EURO-CORDEX ensemble is employed to study sources of uncertainties related to choice of GCMs, RCMs and their combinations. We initially compare the evaluation runs of the RCMs driven by ERA-interim reanalysis to the observations, finding that the RCMs are able to capture most of the observed spatial and temporal features of HWMId. With their higher resolution, RCMs can reveal spatial features of HWMId associated with small-scale processes; moreover, RCMs represent large scale features of HWMId in a satisfactory way. Our results indicate a clear added value of the RCMs in relation to their driving GCMs. Forced with the emission scenario RCP8.5, all the GCM and RCM simulations consistently project a rise in HWMId at an exponential-like rate. However, the climate change signals projected by the GCMs are generally attenuated when downscaled by the RCMs, with the spatial pattern also altered. The uncertainty in a simulated future change of heat wave magnitudes following global warming can be attributed almost equally to the difference in model physics (as represented by different RCMs) and to the driving data associated with different GCMs. Regarding the uncertainty associated with RCM choice, representation of the orographic effects differently is a major factor. No consistent spatial pattern in the ensemble spread associated with different GCMs is observed between the RCMs, suggesting GCMs' uncertainties are transformed by RCMs in a complex manner due to the nonlinear nature of model dynamics and physics. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the risk of municipal urban water shortage in the state of Rio Grande do Norte (RN) through the results of the Index of Water Shortage Risk (IRDH). The theoretical-methodological assumptions are based on Walle and Birkmann (2015); Almeida, Welle and Birkman (2016); Medeiros (2018); Oliveira (2018); Macedo et al. (2020 e 2021). In this context, the IRDH was structured in a systemic perspective, where the territories of water shortage risk were identified through environmental, social and economic, and state planning indicators, using 19 variables as instruments of analysis. The research was conducted qualitatively and quantitatively, evaluating and analyzing the risk of water shortage in RN and the 153 cities that compose the system of supply managed by the Company of Waters and Sewers of Rio Grande do Norte (CAERN), a state concessionaire (representing 92% of the 167 cities of the State), in its seven regions of water supply. The result of the IRDH of Rio Grande do Norte proved the relationship between the indicators in the water shortage problem in the State, classifying 49% of the analyzed cities in the classes of “high” and “very high” risk, which places them in a situation of higher attention regarding the potential damages derived from the water shortage, 40.5% of them being “medium” and 10% “low” risks, with no occurrences of “very low” risk examples. In absolute values, 1 city was classified as “very high”; 74 were classified as “high”; 62 as “medium”; and 16 were considered of “low” risk of water shortage. With the goal of reducing/mitigating the results of the IRDH in the State, a transposition of watersheds, integration of supply systems, hydrogeologic research, among others, were proposed. [ABSTRACT FROM AUTHOR]

The densely populated plains of the lower Indus Basin largely depend on water resources originating in the mountains of the transboundary upper Indus Basin. Recent studies have improved our understanding of this upstream–downstream linkage and the impact of climate change. However, water use in the mountainous part of the Indus and its hydropolitical implications have been largely ignored. This study quantifies the comparative impact of upper Indus water usage, through space and time, on downstream water availability under future climate change and socio-economic development. Future water consumption and relative pressure on water resources will vary greatly across seasons and between the various sub-basins of the upper Indus. During the dry season, the share of surface water required within the upper Indus is high and increasing, and in some transboundary sub-basins future water requirements exceed availability during the critical winter months. In turn this drives spatiotemporal hotspots to emerge in the lower Indus where seasonal water availability is reduced by over 25 % compared to natural conditions. This will play an important, but previously unaccounted for, compounding role in the steep decline of per capita seasonal water availability in the lower Indus in the future, alongside downstream population growth. Increasing consumption in the upper Indus may thus locally lead to water scarcity issues, and increasingly be a driver of downstream water stress during the dry season. Our quantified perspective on the evolving upstream–downstream linkages in the transboundary Indus Basin highlights that long-term shared water management here must account for rapid socio-economic change in the upper Indus and anticipate increasing competition between upstream and downstream riparian states. [ABSTRACT FROM AUTHOR]

Managers of urban water systems constantly make decisions to guarantee water services by overcoming problems related to supply–demand imbalances. A preferred strategy has been supply augmentation through hydraulic infrastructure development. However, despite considerable investments, many systems seem to be trapped in lacklustre development pathways making some problems seem like an enduring, almost stubborn, characteristic of the systems: overexploitation and pollution of water sources, distribution networks overwhelmed by leakages and non-revenue water, and unequal water insecurity. Because of these strategies and persistent problems, water conflicts have emerged, whereby social actors oppose these strategies and propose alternative technologies and strategies. This can create development pathway crossroads of the urban water system, defined as a critical point whereby actors in conflict will either reinforce the current business-as-usual pathway based on large supply augmentation or implement alternative solutions for the urban water system. To study this development pathway crossroads, we selected the Zapotillo conflict in Mexico where a large supply augmentation project for two cities experiencing water shortages is at stake. The paper concludes that urban water systems that are engaged in a trajectory characterized by supply-side strategies may experience a temporal relief but neglect equally pressing issues that stymie the human right to water in the medium and long run. However, there is not a straightforward, self-evident development pathway to choose from, only a range of multiple alternatives with multiple trade-offs that need to be thoroughly discussed and negotiated between the stakeholders. We argue that this development pathway crossroads can cross-fertilize contrasting disciplines such as socio-hydrology and critical studies on water because both can complement technical and socio-political analyses to make their knowledge actionable and relevant. [ABSTRACT FROM AUTHOR]

Trees employ mechanisms to maintain safe xylem water transport including variations in trunk water storage and the depth of root water uptake. We tested the hypotheses that 1) trunk water storage is correlated with root water uptake in Eastern hemlock, 2) and that water use strategy varies with tree size. High spatiotemporal sampling of soil and hemlock xylem (30 trees) water isotopic ratios (2H, 18O) and tree tissue Relative Water Content (RWC) was conducted across seven months. Hemlock accessing more evaporatively enriched water from shallow soils stored less water within their trunks during dry periods, and more during wet periods. Soil and xylem water isotopic compositions revealed older and lower elevation hemlock primarily sourced water uptake from the upper 10 cm of soils, whereas younger and higher elevation trees sourced some water uptake from deeper soil layers. Larger diameter hemlock showed significant temporal changes in trunk RWC. In contrast, smaller diameter trees exhibited more temporally stable RWC. Observed species-level heterogeneity in xylem water isotope composition suggests the need for reporting of tree ages and a standardization of field sampling protocols to support our understanding of tree water use strategies. Our results inform the development of plant hydraulic strategies in ecohydrological- and terrestrial biosphere-models to understand forest responses to external stressors. [ABSTRACT FROM AUTHOR]

Agricultural production is under threat of water scarcity due to increasingly frequent and severe drought events under climate change. Whether a change in cropping systems can be used as an effective adaptation strategy against drought is still unclear. We investigated how plant water uptake patterns of a field-grown pea–barley (Pisum sativum L. and Hordeum vulgare L.) mixture, an important fodder intercrop, responded to experimental drought under four cropping systems, i.e. organic intensive tillage, conventional intensive tillage, conventional no tillage, and organic reduced tillage. Drought was simulated after crop establishment using rain shelters. Proportional contributions to plant water uptake from different soil layers were estimated based on stable water isotopes using Bayesian mixing models. Pea plants always took up proportionally more water from shallower depths than barley plants. Water uptake patterns of neither species were affected by cropping systems. Both species showed similar responses to the drought simulation and increased their proportional water uptake from the shallow soil layer (0–20 cm) in all cropping systems. Our results highlight the impact of drought on plant water uptake patterns for two important crop species and suggest that cropping systems might not be as successful as adaptation strategies against drought as previously thought. [ABSTRACT FROM AUTHOR]

Water management in sub-Saharan African river basins is challenged by an uncertain future climatic, social and economical patterns potentially causing diverging water demands and availability, and by multi-stakeholder dynamics, resulting in evolving conflicts and tradeoffs. In such contexts, a better understanding of the sensitivity of water management to the different sources of uncertainty can support policymakers in identifying robust water supply policies balancing optimality and low vulnerability against likely adverse future conditions. This paper contributes an integrated decision-analytic framework combining an optimization, robustness, sensitivity, and uncertainty analysis to retrieve the main sources of vulnerability to optimal and robust reservoir operating policies across multi-dimensional objective spaces. We demonstrate our approach on the lower Umbeluzi river basin, Mozambique, which an archetypal example of sub-Saharan river basin, where surface water scarcity compounded by substantial climatic variability, uncontrolled urbanization rate, and agricultural expansion are hampering the Pequenos Libombos dam's ability to supply the agricultural, energy, and urban sectors. We adopt an Evolutionary Multi-Objective Direct Policy Search (EMODPS) optimization approach for designing optimal operating policies, whose robustness against social, agricultural, infrastructural, and climatic uncertainties is assessed via robustness analysis. We then implement the generalized likelihood uncertainty estimation (GLUE) and PAWN uncertainty and sensitivity analysis methods for disentangling the main challenges to the sustainability of the operating policies and quantifying their impacts on the urban, agricultural, and energy sectors. Numerical results highlight the importance of a robustness analysis when dealing with uncertain scenarios, with optimal non-robust reservoir operating policies largely being dominated by robust control strategies across all stakeholders. Furthermore, while robust policies are usually vulnerable only to hydrological perturbations and are able to sustain the majority of population growth and agricultural expansion scenarios, non-robust policies are sensitive also to social and agricultural changes and require structural interventions to ensure stable supply. [ABSTRACT FROM AUTHOR]

Water management in mountain regions is facing multiple pressures due to climate change and anthropogenic activities. This is particularly relevant for mountain areas where water abundance in the past allowed for many anthropogenic activities, exposing them to future water scarcity. Here stochastic system dynamics modelling (SDM) was implemented to explore water scarcity conditions affecting the stored water and turbined outflows in the Santa Giustina (S. Giustina) reservoir (Autonomous Province of Trento, Italy). The analysis relies on a model chain integrating outputs from climate change simulations into a hydrological model, the output of which was used to test and select statistical models in an SDM for replicating turbined water and stored volume within the S. Giustina dam reservoir. The study aims at simulating future conditions of the S. Giustina reservoir in terms of outflow and volume as well as implementing a set of metrics to analyse volume extreme conditions. Average results on 30-year slices of simulations show that even under the short-term RCP4.5 scenario (2021–2050) future reductions for stored volume and turbined outflow are expected to be severe compared to the 14-year baseline (1999–2004 and 2009–2016; - 24.9 % of turbined outflow and - 19.9 % of stored volume). Similar reductions are expected also for the long-term RCP8.5 scenario (2041–2070; - 26.2 % of turbined outflow and - 20.8 % of stored volume), mainly driven by the projected precipitations having a similar but lower trend especially in the last part of the 2041–2070 period. At a monthly level, stored volume and turbined outflow are expected to increase for December to March (outflow only), January to April (volume only) depending on scenarios and up to + 32.5 % of stored volume in March for RCP8.5 for 2021–2050. Reductions are persistently occurring for the rest of the year from April to November for turbined outflows (down to - 56.3 % in August) and from May to December for stored volume (down to - 44.1 % in June). Metrics of frequency, duration and severity of future stored volume values suggest a general increase in terms of low volume below the 10th and 20th percentiles and a decrease of high-volume conditions above the 80th and 90th percentiles. These results point at higher percentage increases in frequency and severity for values below the 10th percentile, while volume values below the 20th percentile are expected to last longer. Above the 90th percentile, values are expected to be less frequent than baseline conditions, while showing smaller severity reductions compared to values above the 80th percentile. These results call for the adoption of adaptation strategies focusing on water demand reductions. Months of expected increases in water availability should be considered periods for water accumulation while preparing for potential persistent reductions of stored water and turbined outflows. This study provides results and methodological insights that can be used for future SDM upscaling to integrate different strategic mountain socio-economic sectors (e.g. hydropower, agriculture and tourism) and prepare for potential multi-risk conditions. [ABSTRACT FROM AUTHOR]

Streamflow forecasts are traditionally effective in mitigating water scarcity and flood defense. This study developed an artificial intelligence (AI)-based management methodology that integrated multi-step streamflow forecasts and multi-objective reservoir operation optimization for water resource allocation. Following the methodology, we aimed to assess forecast quality and forecast-informed reservoir operation performance together due to the influence of inflow forecast uncertainty. Varying combinations of climate and hydrological variables were input into three AI-based models, namely a long short-term memory (LSTM), a gated recurrent unit (GRU), and a least-squares support vector machine (LSSVM), to forecast short-term streamflow. Based on three deterministic forecasts, the stochastic inflow scenarios were further developed using Bayesian model averaging (BMA) for quantifying uncertainty. The forecasting scheme was further coupled with a multi-reservoir optimization model, and the multi-objective programming was solved using the parameterized multi-objective robust decision-making (MORDM) approach. The AI-based management framework was applied and demonstrated over a multi-reservoir system (25 reservoirs) in the Zhoushan Islands, China. Three main conclusions were drawn from this study: (1) GRU and LSTM performed equally well on streamflow forecasts, and GRU might be the preferred method over LSTM, given that it had simpler structures and less modeling time; (2) higher forecast performance could lead to improved reservoir operation, while uncertain forecasts were more valuable than deterministic forecasts, regarding two performance metrics, i.e., water supply reliability and operating costs; (3) the relationship between the forecast horizon and reservoir operation was complex and depended on the operating configurations (forecast quality and uncertainty) and performance measures. This study reinforces the potential of an AI-based stochastic streamflow forecasting scheme to seek robust strategies under uncertainty. [ABSTRACT FROM AUTHOR]

In the last 2 decades, Morocco has known rapid growth of urban transformation followed by significant Population growth, which causes serious environmental problems related to water pollution and scarcity, and social with the deficiencies of infrastructures. And this has been witnessed in the city of Biougra which requires taking serious steps and adopting new projects to solve these issues as soon as possible. And as a reflection of that, this paper takes advantage of Geographic information system (GIS) coupled tools in the first place to locate future sites for building new schools using weighted overlay analysis approach, to improve the education system. And in the second place to choose potential sites for implementing new wastewater treatment plant (WWTP) by adopting multicriteria analysis (MCA). Finally, as a part of saving cultural heritage, and improving the social and economic situation for local citizens, we aim to value cooperative of this region as a replacement of poor touristic quality in the city, by making a track of the existing cooperative and profit from 3d modeling as a part of providing the traveler the best possible guide to reach these points of interest and also develop a desktop application for editing and manipulating different types of file related to cooperatives. This study showed successful results by localizing a new site to build a school in the northeastern of the city, and a match between the found site for WWTP and the existing station but with giving a possibility for expansion. [ABSTRACT FROM AUTHOR]

Managing water–human systems during water shortages or droughts is key to avoid the overexploitation of water resources and, in particular, groundwater. Groundwater is a crucial water resource during droughts as it sustains both environmental and anthropogenic water demand. Drought management is often guided by drought policies, to avoid crisis management, and actively introduced management strategies. However, the impact of drought management strategies on hydrological droughts is rarely assessed. In this study, we present a newly developed socio-hydrological model, simulating the relation between water availability and managed water use over 3 decades. Thereby, we aim to assess the impact of drought policies on both baseflow and groundwater droughts. We tested this model in an idealised virtual catchment based on climate data, water resource management practices and drought policies in England. The model includes surface water storage (reservoir), groundwater storage for a range of hydrogeological conditions and optional imported surface water or groundwater. These modelled water sources can all be used to satisfy anthropogenic and environmental water demand. We tested the following four aspects of drought management strategies: (1) increased water supply, (2) restricted water demand, (3) conjunctive water use and (4) maintained environmental flow requirements by restricting groundwater abstractions. These four strategies were evaluated in separate and combined scenarios. Results show mitigated droughts for both baseflow and groundwater droughts in scenarios applying conjunctive use, particularly in systems with small groundwater storage. In systems with large groundwater storage, maintaining environmental flows reduces hydrological droughts most. Scenarios increasing water supply or restricting water demand have an opposing effect on hydrological droughts, although these scenarios are in balance when combined at the same time. Most combined scenarios reduce the severity and occurrence of hydrological droughts, given an incremental dependency on imported water that satisfies up to a third of the total anthropogenic water demand. The necessity for importing water shows the considerable pressure on water resources, and the delicate balance of water–human systems during droughts calls for short-term and long-term sustainability targets within drought policies. [ABSTRACT FROM AUTHOR]

Frequently occurring mega-droughts under current global climate change have attracted broad social attention. A paleoclimatic perspective is needed to increase our understanding of the causes and effects of droughts. South-western (SW) China has been threatened by severe seasonal droughts. Our current knowledge of millennial-scale dry and wet phases in this region is primarily based on the variability of the Indian summer monsoon. However, water availability over land does not always follow patterns of monsoonal precipitation but also depends on water loss from evaporation and transpiration. Here, we reconstructed precipitation intensity, lake hydrological balance and the soil water stress index (SWSI) for the last 27 000 years. Grain size, geochemical and pollen records from Yilong Lake reveal the long-term relationships and inconsistencies of dry–wet patterns in meteorological, hydrological and soil systems in the central Yunnan region, SW China. Our results show that the long-term trends among precipitation, hydrological balance and soil moisture varied through time. The hydrological balance and soil moisture were primarily controlled by temperature-induced evaporation change during periods of low precipitation such as the Last Glacial Maximum and Younger Dryas. During periods of high precipitation (the early to late Holocene), intensified evaporation from the lake surface offset the effects of increased precipitation on the hydrological balance. However, abundant rainfall and the dense vegetation canopy circumvented a soil moisture deficit that might have resulted from rising temperature. In conclusion, the hydrological balance in the central Yunnan region was more sensitive to temperature change while soil moisture could be further regulated by vegetation changes over millennial timescales. Therefore, under future climate warming, the surface water shortage in the central Yunnan region may become even more serious. Our study suggests that reforestation efforts may provide some relief to soil moisture deficits in this region. [ABSTRACT FROM AUTHOR]

Agricultural production is under threat of water scarcity due to increasingly frequent and severe drought events under climate change. Whether a change in cropping systems can be used as an effective adaptation strategy against drought is still unclear. We investigated how plant water uptake patterns of a field-grown pea-barley (Pisum sativum L. and Hordeum vulgare L.) mixture, an important fodder crop, responded to experimental drought under four cropping systems, i.e., organic intensive tillage, conventional intensive tillage, conventional no-tillage, and organic reduced tillage. Drought was simulated after crop establishment using rain shelters. Proportional contributions to plant water uptake from different soil layers were estimated based on stable water isotopes using Bayesian mixing models. Pea plants always took up proportionally more water from shallower depths than barley plants. Water uptake patterns of neither species were affected by cropping systems. Both species showed similar responses to the drought simulation and increased their proportional contributions from shallow soil layer (0-20 cm) in all cropping systems. Our results highlight the impact of drought on plant water uptake patterns for two important crop species and suggest that cropping systems might not be as successful as adaptation strategies against drought as previously thought. [ABSTRACT FROM AUTHOR]

Drought affects the European Alpine mountain region, despite a humid climate. Droughts' damaging character in the past and increasing probability in future projections call for an understanding of drought impacts in the mountain regions. The European Drought Impact report Inventory (EDII) collects text reports on negative drought impacts. This study presents a considerably updated EDII focusing on the Alpine region. This first version release of an Alpine Drought Impact report Inventory (EDII ALPS) classifies impact reports into categories covering various affected sectors and enables comparisons of the drought impact characteristics. We analysed the distribution of reported impacts on the spatial, temporal and seasonal scale and by drought type for soil moisture drought and hydrological drought. For the spatial analysis, we compared the impact data located in the Alpine region to the whole of Europe. Furthermore, we compared impact data between different climatic and altitudinal domains (the northern region vs. the southern region and the pre-Alpine region vs. the high-altitude region) and between the Alpine countries. Compared to the whole of Europe, in the Alpine region agriculture and livestock farming impacts are even more frequently reported, especially in the southern region. Public water supply is the second most relevant sector but overall less prominent compared to Europe, especially in spring when snowmelt mitigates water shortages. Impacts occur mostly in summer and early autumn, with a delay between those impacts initiated by soil moisture and those initiated by hydrological drought. The high-altitude region shows this delay the strongest. From 1975 to 2020, the number of archived reports increases, with substantially more impacts noted during the drought events of 1976, 2003, 2015 and 2018. Moreover, reported impacts diversify from agricultural dominance to multi-faceted impact types covering forestry, water quality, industry and so forth. Though EDII ALPS is biased by reporting behaviour, the region-specific results of negative drought impacts across the water-rich European mountain region demonstrate the need to move from emergency response to prevention and preparedness actions. These may be guided by EDII ALPS ' insights to regional patterns, seasons and drought types. [ABSTRACT FROM AUTHOR]