Abstract Diagnosing monthly evapotranspiration (ET) under water‐balance constraints is essential for understanding land‐atmosphere interactions and managing water resources under changing climate conditions. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow‐On (GRACE/‐FO) missions have provided precise observations of terrestrial water storage, enabling improved constraints on large‐scale water balance. Building on these advances, we develop a GRACE/‐FO‐constrained diagnostic to framework to reproduce monthly ET derived from water‐balance (ET Budget ). The framework that applies the one‐parameter Budyko formulation during dry (water‐limited) months and the two‐parameter power‐law formulation during wet (energy‐limited) months, with the aridity index distinguishing between them. The framework is evaluated across 297 major river basins using ET Budget as a reference and compared with conventional Budyko‐only approaches. Results show that, relative to the Budyko‐only approaches, the proposed framework substantially reduces deviations from ET Budget , especially in 189 humid basins, while maintaining robust performance in 15 arid and 93 semi‐arid regions. The proposed framework yields mean annual ET and P‐ET of 612.5 and 191.4 mm yr −1 over major river basins, respectively, showing no significant long‐term trends but distinct spatial patterns and contrasting responses to the El Niño‐Southern Oscillation phases. These findings highlight the value of the proposed framework as a diagnostic tool for improving the representation of monthly water‐balance ET across diverse hydroclimatic conditions.

Under global climate change and human intervention, an increased frequency of alternating drought and flood events exists, making such extreme conditions seemingly the new normal. These frequent events result in greater variability in terrestrial water storage anomalies (TWSA) (i.e., nonstationary behavior). In this study, we introduce a novel and straightforward metric, i.e., the standard deviation of TWSA (STDTWSA), to detect regions with nonstationary in TWSA and gain insight into the impact of global change on regional TWSA. TWSA estimates from the Center for Space Research (CSR) Mascon are used to calculate STDTWSA and estimated in a rolling window approach, and the results are compared with STD in precipitation anomalies (PAs) and temperature anomalies (TAs). Our results reveal that 63.8% of global land areas show significant prevalence of increasing TWSA variability with nonstationary, while only 3.5% exhibit a decrease. Among the 40 large basins analyzed, 11 show significant upward trends in STDTWSA, with only one basin showing a significant decline from 2002 to 2022. In 34 of these basins, precipitation accounts for over 50% of TWSA variability, suggesting that variabilities in PAs can be used to model and explain the nonstationary behavior of TWSA in these regions. In addition, in three of the remaining six basins, we observed significant correlations between TWSA and PA variability at a five-year window. Furthermore, WaterGAP v2.2e hydrological model (WGHM)-modeled STDTWSA estimates align with the STDTWSA from CSR and show consistent trends in most basins. By linking precipitation-driven dynamics to TWSA variability, this study demonstrates the utility of STDTWSA as a practical tool for identifying regions vulnerable to hydrological extremes. This study provides valuable insights into global TWSA nonstationarity and enhances our understanding of the impacts of global climate change and human intervention on water storage changes.

The delayed response of groundwater to surface soil moisture anomalies (Topt), which reflects how quickly surface signals propagate to aquifers, varies across wetness regimes. Understanding its spatiotemporal variability may help diagnose flash droughts, yet it remains underexplored. Here we examine global relationships between modeled Topt and flash droughts using a dynamic exponential filter. We find that background atmospheric aridity generally controls this relationship, since longer Topt occurs with frequent flash droughts in drylands. However, seasonal variability is largely governed by background terrestrial wetness conditions, with stronger bidirectional Topt–flash drought sensitivities during wetter seasons, even in non-hotspots. This is because flash droughts driven by rapid atmospheric dryness propagation to the land are reflected in Topt memory, predominantly shaped by land-atmosphere interplays. Combined evapotranspiration-runoff deficit in dry conditions, especially the dominance of evapotranspiration, rapidly prolongs Topt and reduces its sensitivity to flash droughts. These insights highlight Topt as a promising flash drought diagnostic indicator, offering a practical pathway for improving prediction. Background atmospheric aridity and seasonal terrestrial wetness jointly regulate modeled groundwater–land surface response time, highlighting modeled dynamic groundwater response time as a promising indicator for diagnosing flash droughts over drylands, according to a global analysis using a dynamic exponential filter.

Abstract Groundwater is a vital component of the hydrological cycle, and understanding its dynamics is crucial for water resource management under climate change. This study employs GRACE-FO satellite data to assess groundwater storage (GWS) dynamics in Hunan Province during the 2024 flood season (April-September). Given the abundant surface water resources in this region, we explicitly incorporate the water storage of Dongting Lake and 28 large reservoirs when calculating surface water storage anomaly (SWSA), which is crucial for estimating the GWS anomaly (GWSA). Accordingly, GWSA is obtained by subtracting the soil moisture storage anomaly (SMSA) and SWSA from the GRACE-FO-derived terrestrial water storage anomaly (TWSA). Furthermore, correlation coefficients and contribution of each water storage component to TWSA are calculated to reveal inter-component interactions and response mechanisms to precipitation. Results show that original TWSA, SWSA, and GWSA increase markedly from March to July 2024. After detrending and deseasonalizing, SWSA and GWSA exhibit a complementary relationship (correlation coefficient: −0.20), with changes of −3.08 km 3 and −1.12 km 3 over the flood season, largely attributed to anthropogenic flood control operations. In contrast, SMSA and GWSA are weakly positively correlated (0.29), reflecting limited direct recharge efficiency. TWSA is strongly correlated with both SMSA (0.78) and GWSA (0.71), reflecting synergistic variation among water storage components. Consistently, GWSA contributes the most (44.52%) to TWSA fluctuations, followed by SMSA (31.80%) and SWSA (23.68%), highlighting the critical role of groundwater in the regional water cycle. These findings provide a valuable scientific basis for sustainable water resource management and regulation in Hunan Province.

In recent years, frequent flood disasters have posed significant threats to human life and property. From 28 July to 1 August 2023, a basin-wide extreme flood occurred in the Haihe River Basin (“23·7” flood). The Gravity Recovery and Climate Experiment satellite can effectively detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA) and has been widely used in flood disaster monitoring. However, flood events usually occur on a submonthly scale. This study first utilizes near-real-time precipitation data to illustrate the evolution of the “23·7” extreme flood. We then reconstruct daily TWSA to improve the issues of coarse temporal resolution and data latency and further calculate wetness index (WI) to explore its flood warning. In addition, we analyze soil moisture storage anomalies to provide a comprehensive understanding of flood mechanisms. The study also compares the 2023 floods to a severe flood event in 2021. Results indicate that reconstructed daily TWSA increases by 143.43 mm in 6 days during the “23·7” flood, highlighting the high sensitivity of our approach to extreme events. Moreover, compared to daily runoff data, the WI consistently exceeds warning thresholds 2–3 days in advance, demonstrating the flood warning capability. The flood event 2021 is characterized by long duration and large precipitation extremes, whereas the 2023 flood affects a wider area. This study provides a reference for using daily TWSA to monitor short-term flood events and evaluate the flood warning potential of WI, aiming to enhance near-real-time flood monitoring and support flood prevention and damage mitigation efforts.

Study region Nine major basins in China. Study focus To enhance understanding of water resource dynamics in China, the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA), from April 2002 to December 2016, are assessed using the advanced GRACE time-variable gravity field model Tongji-Grace2022. The underlying driving factors are further identified together with meteorological data and water consumption statistics. New hydrological insights for the region The results indicate that Tongji-Grace2022 model exhibits superior performance compared to three state-of-the-art spherical harmonic solutions (CSR RL06, JPL RL06, GFZ RL06), characterized by reduced north-south striping noise and higher signal-to-noise ratio, thereby enabling more accurate TWSA estimations. Long-term trend analysis of TWSA in China reveals the spatiotemporal heterogeneity across the nine basins: basins in the humid climatic zone present increasing TWSA, primarily attributable to abundant precipitation; basins in other climatic zones present decreasing TWSA with varying trend magnitudes, which are driven by intensified evapotranspiration and human activities, such as agricultural irrigation and industrial development, and more extensive human activities lead to faster decreases in TWSA. Moreover, TWSA changes exhibit temporal lags behind precipitation and evapotranspiration, and the longer lag months occur in basins with complex hydrogeological environments, such as those featuring multiple aquifers or karstic landscapes. The outcomes can provide theoretical supports for formulating targeted regulation policies in different basins, and eventually achieve the sustainable water resource utilization.

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

The Gravity Recovery and Climate Experiment (GRACE) satellites and its successor mission, the GRACE Follow-On (GRACE-FO) satellites provide a unique capability to monitor terrestrial water storage anomalies (TWSA) and key hydrological variables associated with flood events. However, GRACE data is only available from 2002 onwards, which poses challenges for long-term studies of terrestrial water storage and flooding. Additionally, the monthly temporal resolution of GRACE (-FO) data limits its utility for detailed flood studies on finer time scales. Against these issues, this study employed a statistical model to reconstruct daily TWSA on a grid scale in China from 1963 to 2022. Considering that flood events have three-dimensional spatiotemporal characteristics, this study identified 359 flood events that occurred in China between 1963 and 2022 using a three-dimensional Image-CONnectivity based FLOOD identification (ICON-FLOOD) approach, combined with Normalized Daily Flood Potential Index (NDFPI) calculated from reconstructed daily TWSA and surface runoff. The spatiotemporal variations characteristics of flood events in China over the past 60 years were also analyzed. The results show that 60 flood events that were not recorded in these three disaster databases but actually occurred were detected. The average duration, intensity, and affected area have experienced an "increase-decrease-increase-decrease-increase" process. Notably, in the past 20 years, the duration, intensity, and affected area of flood events are increasing. The methods and findings of this study may provide valuable references for flood risk management and mechanism analysis.

As global warming intensifies, the frequency of drought events increases, drawing attention to enhanced drought monitoring. While drought indices play a crucial role, most are available only on a monthly scale, and daily indicators remain limited. This study addresses this gap by reconstructing daily Terrestrial Water Storage Anomalies (TWSA) from 1963 to 2022 and proposing a Daily Standardized GRACE Reconstructed TWSA Index (D-SGRTI). The index is applied to nine exorheic basins in China. Results indicate that D-SGRTI shows strong agreement with other drought indices, including the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSI), and Standardized Runoff Index (SRI). The correlation coefficient (CC) analysis shows that between D-SGRTI and SSI in the Songhuajiang River Basin (SRB) is 0.84, while CCs between D-SGRTI and SRI are highest in the other eight basins, reaching 0.91 in the Middle Yangtze River Basin (MYRB). The semi-arid and semi-humid basins show higher drought frequency, longer duration, and slower recovery over the study period. In contrast, in the humid basins, D-SGRTI reveals lower drought frequency, shorter duration, and quicker recovery. Generally, the drought frequency in autumn and winter is higher than that in spring and summer. This study presents an alternative method for monitoring drought at a daily scale, offering valuable insights for drought assessment across various regions in China. The approach holds potential for broader application in global drought monitoring efforts.

The crucial role of precipitation as a primary driver for terrestrial water cycle is well-established. However, quantifying the transformation of daily precipitation into terrestrial water storage remains a challenge. Here we address this by introducing a quantitative metric, average daily fraction of precipitation transformed into terrestrial water storage, providing an important advancement into the dynamics of water storage by utilizing the enhanced terrestrial water storage statistical reconstruction method and water storage data from the Gravity Recovery and Climate Experiment satellites and their follow-on mission. This study reveals that approximately 64

Flash droughts cause serious damage to ecosystems and human societies due to their rapid onset and intensification. Their fast changes pose significant challenge to existing drought warning and monitoring systems. Although previous studies have focused on meteorological, ecological and soil moisture indicators for assessing flash droughts, an effective quantitative indicator capturing the direct manifestation of flash droughts-specifically, the rapid decline in terrestrial water storage (TWS)-remains unavailable. To address this gap, we propose a pentad-scale hydrological flash drought identification framework based on a daily-scale reconstructed TWS anomaly dataset derived from Gravity Recovery and Climate Experiment (GRACE) observations. We further analyze global flash drought hotspot regions, their spatiotemporal evolution, and key drivers from 1979 to 2018. Our findings reveal that, on a spatial scale, flash drought hotspots are primarily concentrated in humid and semi-humid climate zones. On a temporal scale, the impact of flash droughts has intensified in regions such as Northern Europe, Northern Asia, Southeast Asia, and South Asia, whereas the Amazon, East Africa, and West Africa exhibit a decreasing trend. In other study regions, no significant changes in flash drought conditions are observed. At the global scale, energy-related factors (including temperature and solar radiation) contribute significantly more to flash drought development than water-related factors (such as precipitation). Additionally, approximately 48 % of flash droughts worldwide evolve into long-term droughts, with this transition occurring primarily during the vegetation growing season in humid regions. The hydrological flash drought identification framework proposed in this study effectively addresses gaps in existing monitoring systems, providing a crucial scientific basis for drought early warning and disaster mitigation.

Understanding the impact of human activities on regional water resources is essential for sustainable basin management. This study examines long-term terrestrial water storage anomalies (TWSA) in the Three Gorges Reservoir Area (TGRA) over two decades, from 2003 to 2023. The analysis utilizes data from the Gravity Recovery and Climate Experiment (GRACE) and its successor mission (GRACE-FO), complemented by Global Land Data Assimilation System (GLDAS) models and ECMWF Reanalysis v5 (ERA5) datasets. The research methodically explores the comparative contributions of natural factors and human activities to the region’s hydrological dynamics. By integrating the GRACE Drought Severity Index (GRACE-DSI), this study uncovers the dynamics of droughts during extreme climate events. It also reveals the pivotal role of the Three Gorges Dam (TGD) in mitigating these events and managing regional water resources. Our findings indicate a notable upward trend in TWSA within the TGRA, with an annual increase of 0.93 cm/year. This trend is largely due to the effective regulatory operations of TGD. The dam effectively balances the seasonal distribution of water storage between summer and winter and substantially reduces the adverse effects of extreme droughts on regional water resources. Further, the GRACE-DSI analysis underscores the swift recovery of TWSA following the 2022 drought, highlighting TGD’s critical role in responding to extreme climatic conditions. Through correlation analysis, it was found that compared with natural factors (correlation 0.62), human activities (correlation 0.91) exhibit a higher relative contribution to TWSA variability. The human-induced contributions were derived from the difference between GRACE and GLDAS datasets, capturing the combined effects of all human activities, including the operations of the TGD, agricultural irrigation, and urbanization. However, the TGD serves as a key regulatory facility that significantly influences regional water resource dynamics, particularly in mitigating extreme climatic events. This study provides a scientific basis for water resource management in the TGRA and similar large reservoir regions, emphasizing the necessity of integrating the interactions between human activities and natural factors in basin management strategies.

The Global Navigation Satellite System (GNSS) is vital for monitoring terrestrial water storage (TWS). However, effectively extracting hydrological load deformation from GNSS observations poses a significant challenge. This study proposes a novel strategy; the seasonal hydrological load signals are removed from the raw data, and the remaining signals use principal component analysis (PCA). Simulation results from Yunnan Province demonstrate that the spatial distribution of the root mean square error (RMSE) is improved by approximately 15 % compared with traditional PCA extraction from raw data. From January 2013 to December 2022, TWS was inverted from 24 GNSS stations in Yunnan Province. The spatial distribution and time series of TWS inverted from GNSS align well with those TWS inferred from the Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GFO), and the Global Land Data Assimilation System (GLDAS) land surface model. However, the amplitude of the GNSS-inverted TWS is slightly higher. Since GNSS ground stations are more sensitive to hydrological load signals, they show correlations with precipitation data that are 8.6 % and 6.0 % higher than those of GRACE and GLDAS, respectively. In the power spectral density analysis of GRACE/GFO, GLDAS, and GNSS, the signal strength of GNSS is much higher than that of GRACE/GFO and GLDAS in the June and February cycles. These findings suggest that the new data extraction strategy can capture higher frequency hydrological signals in TWS, and GNSS observations can help address limitations in GRACE/GFO observations. This study demonstrates the potential of GNSS TWS in capturing higher-frequency hydrological signals and climate extremes application.

Study region: Guangdong Province, located in southern China. Study focus: This study finely quantified the spatiotemporal evolution of the flood event in April 2024. We analyzed the extreme precipitation process in the Guangdong Province based on the near real-time precipitation data from the China Meteorological Administration Land Data Assimilation System, and reconstructed the daily terrestrial water storage anomalies (TWSA) based on the Gravity Recovery and Climate Experiment Follow-On data as well as various temperature and precipitation data to monitor the spatiotemporal dynamics of the flood. Furthermore, a computationally normalized daily flood potential index (NDFPI) based on the reconstructed daily TWSA was used for flood warning. New hydrological insights for the region: The results showed that the reconstructed daily TWSA increased by 124.1 mm from April 16 to May 4, and the corresponding water storage increased by 29.3 km3 in Guangdong Province. The NDFPI issued flood warnings 2 days earlier than water level alerts at most river gauging stations, demonstrating its potential for early flood warning. Further studies showed that the El Nino Southern Oscillation is strongly correlated with TWSA and precipitation anomalies, revealing the crucial driving role of the climate patterns influenced by ENSO in extreme precipitation events. This study provides new insights into flood event monitoring and early warning in southern China.

Constrained by limited evapotranspiration (ET) observations, it is difficult to determine which ET product provides a more accurate ET estimate. However, due to the abundant potential evapotranspiration (PET) observations, evaluating the performance of forcing data for estimating PET to determine the performance of forcing data for ET estimation is a viable option. In this study, we proposed a new method to assess the performance of different reanalysis meteorological forcing data in ET estimation indirectly by evaluating their performance in PET estimation. Based on meteorological data from 1,978 meteorological observation stations during 2003-2018 in China, five widely used products (ERA5L, CFSV2, GLDASV21, JRA55, and MERRA2) were evaluated. Results show that: (1) From the perspective of overall performance in annual PET estimation, ERA5L captures both the magnitude and interannual fluctuations of PET the best, with median R2 and RMSE of 0.52 and 40.91 mm, respectively. (2) From the perspective of meteorological variables accuracy, the reanalysis forcing has the best precision for surface temperature (Ta) and the lowest precision for 2 m wind speed (U2), with average R2 of 0.96 and 0.26, respectively. The net surface radiation (Rn), U2, Ta, actual vapor pressure (ea), and surface pressure (Pa) from five products yield median errors in PET estimation of 28.34, 19.94, 21.31, 30.95, and 0.06 mm, respectively. (3) For each meteorological variable, we selected the forcing data that performed the best (ea, U2, and Pa provided by ERA5L, Rnand Ta by MERRA2), forming an optimal combination for calculating ET. The basin water balance and eddy covariance flux station evaluation showed that the optimal combination can improve the performance of ET estimated using the PML-V2 model in terms of magnitude, interannual fluctuations, and trends compared to the original reanalysis forcing. Our study provides a new framework for selecting more appropriate forcing data in estimating ET, which further facilitates an improved understanding of largescale ET dynamics.

In 2024, China experiences frequent and severe hydrological extremes, including record-breaking rainfall and widespread droughts, reflecting the intensifying impacts of climate change. The significant changes in terrestrial water storage (TWS) caused by these extreme precipitation events require more detailed analysis to assess short-term hydrological dynamics. Here, we first analyze precipitation anomalies (PA) and percentage of PA (PPA) across mainland China from April to August 2024. The results reveal that PA and PPA in most regions exhibit extreme values in different months, resulting in severe droughts, floods, and abrupt drought-to-flood transitions. To assess the associated water storage changes, we define and apply the terrestrial water flux (TWF), the differenceof GRACE/GRACE-FO-derived TWS anomalies in two adjacent months, as a diagnostic indicator of short-term hydrological variability. Relative to 2002–2024, the grids with TWF percentiles within the 0-10th and 90-100th ranges respectively account for 36.52%, 46.22%, 44.79%, and 46.48% of the total grids from April to August in China. Additionally, 19.89% of grids have the maximum TWF value in 2024. These extremes closely align with variations in precipitation, suggesting that intensified TWF is primarily driven by meteorological factors rather than GRACE-FO data uncertainties. Overall, this study demonstrates the effectiveness of TWF in capturing rapid hydrological changes under climate extremes. The findings provide critical insights into the impacts of climate change on regional hydrological processes and offer a valuable reference for future climate risk management and adaptation strategies at both national and global scales.

The occurrence of the devastating 2023 Herat earthquake sequence shattered 1200 yr period of seismic quiescence in western Afghanistan. In this study, we utilize Interferometric Synthetic Aperture Radar (InSAR) data to derive the surface displacements associated with this swarm, demonstrating a maximum coseismic displacement of 82 cm in the InSAR line of sight direction. The rupture models estimated from InSARmapped coseismic deformation suggest that the major slips in the seismic swarm are dominated by thrust faulting concentrated at a shallow depth of 4-6 km, characterized by low dip angles and corresponding to a sliding structure in a shallow layer. These unmapped blind ruptures manifest as isolated asperities, generally corresponding to the five major events. Given the spatial distribution of these slips, these five major events should be sequential occurrences due to a strong interaction, and a high-potential seismic risk should be still in the Herat fault system. Using the time-series satellite gravity change in the recent two decades, we find that prolonged drought in this arid region has resulted in a cumulative water storage loss of similar to 200 mm, which can produce Coulomb stress change of similar to 1.4 kPa on the Herat fault and impact a positive stress effect to promote the occurrence of this seismic swarm.

Evapotranspiration (ET) serves as a crucial indicator for understanding both global and regional water cycles and the impacts of climate change. Traditionally, water balance-based ET derived using satellite gravimetry, runoff and precipitation is considered as a benchmark for ET assessment. However, this method faces limitations in providing long-term, high temporal resolution ET estimates because of the relatively short observation period of the Gravity Recovery and Climate Experiment (GRACE) satellites. To address this challenge, we reconstruct long-term terrestrial water storage change (TWSC) using statistical reconstruction and hydrological models. Then we estimate the long-term ET and its driving factors in the Yangtze River Basin (YRB) using the water balance equation and ridge regression. Dividing the study period into three subperiods between the end of the 20th century and around 2015, ET in the upper and middle YRB exhibits a decreasing-rising-decreasing trend. ET and precipitation in the upper and middle YRB show an increasing trend throughout the entire study period, indicating an intensification of the water cycle in the YRB. ET changes over the past four decades are mainly driven by changes in surface vegetation cover and precipitation. This study provides valuable scientific references for the reproduction and prediction of the basin water cycle and the refinement of ET models under historical and different future climate scenarios.

In recent years, frequent flood disasters have posed significant threats to human life and property. From 28 July to 1 August 2023, a basin-wide extreme flood occurred in the Haihe River Basin ("23.7" flood). The Gravity Recovery and Climate Experiment satellite can effectively detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA) and has been widely used in flood disaster monitoring. However, flood events usually occur on a submonthly scale. This study first utilizes near-real-time precipitation data to illustrate the evolution of the "23.7" extreme flood. We then reconstruct daily TWSA to improve the issues of coarse temporal resolution and data latency and further calculate wetness index (WI) to explore its flood warning. In addition, we analyze soil moisture storage anomalies to provide a comprehensive understanding of flood mechanisms. The study also compares the 2023 floods to a severe flood event in 2021. Results indicate that reconstructed daily TWSA increases by 143.43 mm in 6 days during the "23.7" flood, highlighting the high sensitivity of our approach to extreme events. Moreover, compared to daily runoff data, the WI consistently exceeds warning thresholds 2-3 days in advance, demonstrating the flood warning capability. The flood event 2021 is characterized by long duration and large precipitation extremes, whereas the 2023 flood affects a wider area. This study provides a reference for using daily TWSA to monitor short-term flood events and evaluate the flood warning potential of WI, aiming to enhance near-real-time flood monitoring and support flood prevention and damage mitigation efforts.