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Water is a naturally circulating resource that is constantly recharged. Therefore, even though the stocks of water in natural and artificial reservoirs are helpful to increase the available water resources for human society, the flow of water should be the main focus in water resources assessments. The climate system puts an upper limit on the circulation rate of available renewable freshwater resources (RFWR). Although current global withdrawals are well below the upper limit, more than two billion people live in highly water-stressed areas because of the uneven distribution of RFWR in time and space. Climate change is expected to accelerate water cycles and thereby increase the available RFWR. This would slow down the increase of people living under water stress; however, changes in seasonal patterns and increasing probability of extreme events may offset this effect. Reducing current vulnerability will be the first step to prepare for such anticipated changes.

Long revisit intervals and cloud susceptibility have restricted the applicability of earth observation satellites in surface water studies. Integrating multiple satellites offers potential for more frequent observations, yet combining different satellite sources, particularly optical and SAR satellites, presents complexities. This research explores the data-fusion potential and limitations of Landsat-8/9 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture (SAR) satellites to enhance surface water monitoring. By focusing on segmented surface water images, we demonstrate that combining optical and SAR data is generally effective and straightforward using a simple statistical thresholding algorithm. Kappa coefficients(κ) ranging from 0.80 to 0.95 indicate very strong harmony for integration across reservoirs, lakes, and river environments. In vegetative environments, integration with S1SAR shows weak harmony, with κ values ranging from 0.27 to 0.45, indicating the need for further studies. Global revisit interval maps reveal significant improvement in median revisit intervals from 15.87 to 22.81 days using L8/9 alone, to 4.51 to 7.77 days after incorporating S2, and further to 3.48 to 4.62 days after adding S1SAR. Even during wet season months, multi-satellite fusion maintained the median revisit intervals to less than a week. Maximizing all available open-source earth observation satellites is integral for advancing studies requiring more frequent surface water observations, such as flood, inundation, and hydrological modeling.

Detecting surface water beneath vegetation canopies remains a major challenge for widely used water indices, which often underestimate water obscured by vegetation. This limitation is further compounded by the scarcity of reliable in situ data needed for robust index development and validation. To address this, we introduce a Vegetation-Adjusted Water Index using a logarithmic transformation of the ratio between the Land Surface Water Index (LSWI) and the Enhanced Vegetation Index (EVI), referred to as VAWIlog. This transformation compresses high vegetation values while expanding the range typical of water surfaces, enhancing contrast in mixed land cover areas and improving class separability. The index was developed and validated using in situ water level measurements, providing a strong empirical basis for detecting surface water under variable vegetation conditions. VAWIlog consistently outperformed established indices in detecting surface water beneath vegetation, demonstrating superior detection accuracy and overall performance, with a balanced accuracy (BA) of 0.69 and a producer’s accuracy (PA) of 0.80. This reflects an average improvement of 25% over conventional methods. Benchmarking against the Dynamic World V1 dataset further confirmed the improved capability of the proposed index to detect surface water in vegetated areas, which are often missed by the dataset. This enhanced performance can be attributed to the fact that the proposed index was developed using on-the-ground observations, rather than relying solely on expert-labeled imagery as in the case of Dynamic World. Overall, VAWIlog provides a simple yet effective solution for improved surface water mapping in vegetated landscapes. Its compatibility with open-source optical satellite data enables broader applications, including irrigation monitoring and greenhouse gas assessments.

Current global river routing models do not represent floodplain inundation dynamics realistically because the storage and movement of surface waters are regulated by small‐scale topography rather than the commonly used spatial resolution of global models. In this study, we propose a new global river routing model, CaMa‐Flood, which explicitly parameterizes the subgrid‐scale topography of a floodplain, thus describing floodplain inundation dynamics. The relationship between water storage, water level, and flooded area in the model is decided on the basis of the subgrid‐scale topographic parameters based on 1 km resolution digital elevation model. Horizontal water transport is calculated with a diffusive wave equation, which realizes the backwater effect in flat river basins. A set of global‐scale river flow simulations demonstrated an improved predictability of daily‐scale river discharge in many major world rivers by incorporating the floodplain inundation dynamics. Detailed analysis of the simulated results for the Amazon River suggested that introduction of the diffusive wave equation is essential for simulating water surface elevation realistically. The simulated spatiotemporal variation of the flooded area in the Amazon basin showed a good correlation with satellite observations, especially when the backwater effect was considered. The improved predictability for daily river discharge, water surface elevation, and inundated areas by the proposed model will promote climate system studies and water resource assessments. Key Points Physically based representation of floodplain inundation dynamics Improved predictability for daily‐scale river discharge in world major rivers Prediction of water surface elevation and flooded areas

Humans abstract water from various sources to sustain their livelihood and society. Some global hydrological models (GHMs) include explicit schemes of human water abstraction, but the representation and performance of these schemes remain limited. We substantially enhanced the water abstraction schemes of the H08 GHM. This enabled us to estimate water abstraction from six major water sources, namely, river flow regulated by global reservoirs (i.e., reservoirs regulating the flow of the world's major rivers), aqueduct water transfer, local reservoirs, seawater desalination, renewable groundwater, and nonrenewable groundwater. In its standard setup, the model covers the whole globe at a spatial resolution of 0.5° × 0.5°, and the calculation interval is 1 day. All the interactions were simulated in a single computer program, and all water fluxes and storage were strictly traceable at any place and time during the simulation period. A global hydrological simulation was conducted to validate the performance of the model for the period of 1979–2013 (land use was fixed for the year 2000). The simulated water fluxes for water abstraction were validated against those reported in earlier publications and showed a reasonable agreement at the global and country level. The simulated monthly river discharge and terrestrial water storage (TWS) for six of the world's most significantly human-affected river basins were compared with gauge observations and the data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. It is found that the simulation including the newly added schemes outperformed the simulation without human activities. The simulated results indicated that, in 2000, of the 3628±75 km3 yr−1 global freshwater requirement, 2839±50 km3 yr−1 was taken from surface water and 789±30 km3 yr−1 from groundwater. Streamflow, aqueduct water transfer, local reservoirs, and seawater desalination accounted for 1786±23, 199±10, 106±5, and 1.8±0 km3 yr−1 of the surface water, respectively. The remaining 747±45 km3 yr−1 freshwater requirement was unmet, or surface water was not available when and where it was needed in our simulation. Renewable and nonrenewable groundwater accounted for 607±11 and 182±26 km3 yr−1 of the groundwater total, respectively. Each source differed in its renewability, economic costs for development, and environmental consequences of usage. The model is useful for performing global water resource assessments by considering the aspects of sustainability, economy, and environment.

Flood risk is expected to increase as the climate warms. This study, for the first time, uses several climate models to estimate the global risk of flooding at the end of the century. Projections show a large increase in flood frequency in some areas, whereas other regions can expect a decrease. Vulnerability is dependent on the degree of warming and the interannual variability in precipitation. A warmer climate would increase the risk of floods 1 . So far, only a few studies 2 , 3 have projected changes in floods on a global scale. None of these studies relied on multiple climate models. A few global studies 4 , 5 have started to estimate the exposure to flooding (population in potential inundation areas) as a proxy of risk, but none of them has estimated it in a warmer future climate. Here we present global flood risk for the end of this century based on the outputs of 11 climate models. A state-of-the-art global river routing model with an inundation scheme 6 was employed to compute river discharge and inundation area. An ensemble of projections under a new high-concentration scenario 7 demonstrates a large increase in flood frequency in Southeast Asia, Peninsular India, eastern Africa and the northern half of the Andes, with small uncertainty in the direction of change. In certain areas of the world, however, flood frequency is projected to decrease. Another larger ensemble of projections under four new concentration scenarios 7 reveals that the global exposure to floods would increase depending on the degree of warming, but interannual variability of the exposure may imply the necessity of adaptation before significant warming.

Recently, against the backdrop of current climate, several regional studies have investigated the applicability of the Clausius–Clapeyron relation to the scaling relationship between extreme precipitation intensity and surface air temperature. Nevertheless, the temperature relationship of the extreme precipitation intensity on a global scale is still unclear. We assess, for the first time, the global relationship between the extreme daily precipitation intensity and the daily surface air temperature using in‐situ data. The extreme daily precipitation intensity increased monotonically with the daily surface air temperature at high latitudes and decreased monotonically in the tropics. Similarly, the extreme daily precipitation intensity at middle latitudes increased at low temperatures and decreased at high temperatures; this decrease could be largely attributed to the decrease in the wet‐event duration. The Clausius–Clapeyron scaling is applicable to the increase in the extreme daily precipitation intensity in a limited number of regions. However, the potential applicability of the Clausius–Clapeyron scaling on sub‐hourly timescale was observed, even in regions where the Clausius–Clapeyron scaling on daily timescale was not applicable. This implies the potential of warming to intensify extreme precipitation on sub‐hourly timescales. Key Points The global relationship between extreme rain and temperature was assessed The decrease in heavy rain amount was attributed to that in the rain duration Sub‐hourly extreme rain amount may increase with rising temperature

Water scarcity is a global concern that necessitates a global perspective, but it is also the product of multiple regional issues that require regional solutions. Water markets constitute a regionally applicable non-structural measure to counter water scarcity that has received the attention of academics and policy-makers, but there is no global view on their applicability. We present the global distribution of potential nations and states where water markets could be instituted in a legal sense, by investigating 296 water laws internationally, with special reference to a minimum set of key rules: legalization of water reallocation, the separation of water rights and landownership, and the modification of the cancellation rule for non-use. We also suggest two additional globally distributed prerequisites and policy implications: the predictability of the available water before irrigation periods and public control of groundwater pumping throughout its jurisdiction.

Sustainable management of cultural heritage in mountainous regions requires effective strategies to mitigate natural hazards such as landslides. Landslide susceptibility mapping (LSM) provides a critical tool to support these conservation efforts. This study presents a hybrid framework that integrates probabilistic slope stability modeling with ensemble learning for LSM in the UNESCO World Heritage sites of Shirakawa-gō and Gokayama, Japan. The framework uses probabilities of failure from Bishop’s simplified method combined with Monte Carlo simulations to guide non-landslide sample selection. An enhanced tri-parametric optimization was applied to refine the slope unit segmentation process. SHAP analysis revealed that the hybrid framework emphasizes physically meaningful features such as rainfall. The proposed method results in AUC gains of 0.072 for XGBoost, 0.066 CatBoost for, and 0.063 for LightGBM compared to their buffer-based counterparts. Future landslide susceptibility was mapped based on the 2035 precipitation projections from ARIMA time-series modeling. By enhancing accuracy, interpretability, and geotechnical consistency, the proposed approach delivers a robust tool for sustainable risk management. The study further evaluates the exposure of Gasshō-style houses and other historic buildings to varying levels of landslide susceptibility, offering actionable insights for local planning and heritage conservation.

This work explores the changes in vegetation coverage and submergence time of floodplains along the middle and lower reaches of the Yangtze River (i.e., the Jingjiang River) and the relations between them. As the Three Gorges Dam has been operating for more than 10 years, the original vegetative environment has been greatly altered in this region. The two main aspects of these changes were discovered by analyzing year-end image data from remote sensing satellites using a dimidiate pixel model, based on the normalized difference vegetation index, and by calculating water level and topographic data over a distance of 360 km from 2003–2015. Given that the channels had adjusted laterally, thus exhibiting deeper and broader geometries due to the Three Gorges Dam, 11 floodplains were classified into three groups with distinctive features. The evidence shows that, the floodplains with high elevation have formed steady vegetation areas and could hardly be affected by runoff and usually occupied by humans. The low elevation group has not met the minimal threshold of submerging time for vegetation growth, and no plants were observed so far. Based on the facts summed up from the floodplains with variable elevation, days needed to spot vegetation ranges from 70 to 120 days which happened typically near 2006 and between 2008 and 2010, respectively, and a negative correlation was detected between submergence time and vegetation coverage within a certain range. Thus, floods optimized by the Three Gorges Dam have directly influenced plant growth in the floodplains and may also affect our ability to manage certain types of large floods. Our conclusions may provide a basis for establishing flood criteria to manage the floodplain vegetation and evaluating possible increases in resistance caused by high-flow flooding when these floodplains are submerged.