Water Level Observations Research Articles

Characterizing Tidal Marsh Inundation with Synthetic Aperture Radar, Radiometric Modeling, and In Situ Water Level Observations

Tidal marshes play a globally critical role in carbon and hydrologic cycles by sequestering carbon dioxide from the atmosphere and exporting dissolved organic carbon to connected estuaries. These ecosystems provide critical habitat to a variety of fauna and also reduce coastal flood impacts. Accurate characterization of tidal marsh inundation dynamics is crucial for understanding these processes and ecosystem services. In this study, we developed remote sensing-based inundation classifications over a range of tidal stages for marshes of the Mid-Atlantic and Gulf of Mexico regions of the United States. Inundation products were derived from C-band and L-band synthetic aperture radar (SAR) imagery using backscatter thresholding and temporal change detection approaches. Inundation products were validated with in situ water level observations and radiometric modeling. The Michigan Microwave Canopy Scattering (MIMICS) radiometric model was used to simulate radar backscatter response for tidal marshes across a range of vegetation parameterizations and simulated hydrologic states. Our findings demonstrate that inundation classifications based on L-band SAR—developed using backscatter thresholding applied to single-date imagery—were comparable in accuracy to the best performing C-band SAR inundation classifications that required change detection approaches applied to time-series imagery (90.0% vs. 88.8% accuracy, respectively). L-band SAR backscatter threshold inundation products were also compared to polarimetric decompositions from quad-polarimetric Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2) and L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) imagery. Polarimetric decomposition analysis showed a relative shift from volume and single-bounce scattering to double-bounce scattering in response to increasing tidal stage and associated increases in classified inundated area. MIMICS modeling similarly showed a relative shift to double-bounce scattering and a decrease in total backscatter in response to inundation. These findings have relevance to the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission, as threshold-based classifications of wetland inundation dynamics will be employed to verify that NISAR datasets satisfy associated mission science requirements to map wetland inundation with classification accuracies better than 80% at 1 hectare spatial scales.

A Water Mass Balance–Based Procedure Using ERA5 Land Reanalysis and Level Observation to Reconstruct the Past Level Changes of Closed Lakes toward Future Management

Abstract This paper aims to refine an effective procedure to reconstruct the past level changes of closed lakes, as a tool for future management. In most cases, such water bodies are overlooked (particularly when they are small), even if they play a significant role in local communities from the economic and social points of view. In this perspective, this study explores the potential of using reanalysis data, as a single source of data to compute the lake water mass balance, and water level observations. It focuses on some closed lakes with minimal anthropogenic influence in Europe, Africa, and the United States. The number of cases studied is limited by the fact that a significant time series of water levels is difficult to obtain for small lakes. The research leverages ERA5 Land (ERA5L), the land component of ERA5 reanalysis, incorporating the Freshwater Lake (FLake) model. FLake allows simulation of the interaction of inland water bodies with the atmosphere. The use of ERA5L is preceded by data validation by considering satellite observation. To simulate the water mass balance of the selected lakes, the proposed procedure combines precipitation, runoff, and evaporation from the lake, provided by ERA5L, and the lake water level observations. The results indicate that even with a short time series of water level observations, a good agreement (Pearson coefficient ranging from 50% to 90%) between the observed monthly variation of the lake level and the corresponding values of the water storage, computed by using ERA5L, is achieved. The procedure exhibits adaptability and robustness, with an accurate representation of the lake water level trends. However, occasional discrepancies are noted during specific periods, primarily attributed to ERA5L precipitation biases. The proposed procedure can be used only when lake water level observations are available. This limits the number of lakes that it can be applied to. However, the procedure can be applied even with a short time series of data, without the need for additional ground-based or remotely sensed data to compute the water mass balance. Significance Statement This study employs ERA5L reanalysis data and lake level observations to effectively reconstruct the natural variability of closed lake water levels in some monitored lakes in Europe, Africa, and the United States. Results demonstrate the adaptability and robustness of the proposed procedure in capturing the past level changes. Despite occasional discrepancies attributed to precipitation biases, the procedure proves reliable for assessing lake water level trends. Future studies could refine the procedure and extend its applicability, enhancing the ability to monitor environmental changes.

Construction of a Block-Based Water-Level Monitoring System for RDII Management in a Separate Sewer System

In a separate sewer system designed to independently discharge sewage and stormwater, operational issues such as sewage manhole overflow and overloading of the sewage treatment plant capacity can arise during rainfall events owing to Rainfall-Derived Inflow and Infiltration (RDII) into the sewage pipelines. Although various management strategies for RDII have been studied both domestically and internationally, research on monitoring systems that can precisely identify specific locations where RDII occurs remains insufficient. Therefore, this study analyzed the shortcomings of the existing water-level monitoring system using a case study of City A, which was designed as a separate sewer system. To efficiently manage RDII, we propose a methodology for establishing a block-based water-level monitoring system divided into large, middle, and small blocks, inspired by the block system concept used in water supply networks. By conducting water-level observations at the exits of the middle and small blocks, the specific locations of RDII occurrence can be identified. This approach is expected to facilitate effective and prompt countermeasures by accurately identifying the locations where RDII occurs.

Full-grid bathymetry estimation in the numerical simulation of 8 tidal constituents using an ensemble adjustment Kalman filter-smoothing scheme

The spatially varying geographic-parameters introduce significant uncertainty into the ocean model. Due to the impracticality of manually tuning spatial varying parameters, data assimilation methods are widely used for geographic-parameter optimization (GPO). Practically, the limited observations do not contain enough information to perform GPO directly on the entire grid. Therefore, techniques are required to reduce the complexity of the parameters. A full-grid GPO scheme based on the ensemble adjustment Kalman filter (EAKF) is developed. Via smoothing the spatial distribution of posterior parameter members, the EAKF-smoothing (EAKF-S) introduces additional spatial correlations among parameters. Meanwhile, the small-scale correlation between the state and the parameters, which exhibit strong pseudo-correlations, is filtered out. A tide model of the Bohai Sea and Yellow Sea, considering 8 principal tidal constituents. is constructed using the Princeton Ocean Model with the generalized coordinate system (POMgcs). The EAKF-S is employed for optimizing the full-grid bathymetry. In twin experiment, based on idealized water level observations, EAKF-S effectively reduced model errors and approximately inverted the “true” bathymetry. After GPO, the lowest mean absolute error of the parameter ensemble is 0.83 m. A series of practical GPO experiments based on synthetic water level observations calculated from NAO.99Jb data are performed. First, the improvement of EAKF-S in accuracy and efficiency over standard EAKF is proven using an M2 tide model. After that, a practical experiment on an 8 constituents tide model is performed. The results show that the forecasting performance of all 8 constituents is improved after GPO, indicating the efficacy of EAKF-S.

Dissipation Scaled Internal Wave Drag in a Global Heterogeneously Coupled Internal/External Mode Total Water Level Model

AbstractThis study showcases a global, heterogeneously coupled total water level system wherein salinity and temperature outputs from a coarser‐resolution (12 km) ocean general circulation model are used to calculate density‐driven terms within a global, higher‐resolution (2.5 km) depth‐averaged total water level model. We demonstrate that the inclusion of baroclinic forcing in the barotropic model requires modification of the internal wave drag term to prevent excess degradation of tidal results compared to the barotropic model. By scaling the internal tide dissipation by an easy to calculate dissipation ratio, the resulting heterogeneously coupled model has complex root mean square errors (RMSE) of 2.27 cm in the deep ocean and 12.16 cm in shallow waters for the tidal constituent. While this represents a 10%–20% deterioration as compared to the barotropic model, the improvements in total water level prediction more than offset this degradation. Global median RMSE compared to observations of total water levels, 30‐day sea levels, and non‐tidal residuals improve by 1.86 (18.5%), 2.55 (42.5%), and 0.36 (5.3%) cm respectively. The drastic improvement in model performance highlights the importance of including density‐driven effects within global hydrodynamic models and will help to improve the results of both hindcasts and forecasts in modeling extreme and nuisance flooding. With only an 11% increase in model run time compared to the fully barotropic total water level model, this approach paves the way for high resolution coastal water level and flood models to be used alongside climate models, improving operational forecasting of total water levels.

High-resolution simulation of coastal flooding under extreme storm tides and sea level rise: A case study of Macau

In the face of climate change, coastal cities are challenged with growing risks from rising sea levels and intensified storm surges which could turn urban areas into temporary waterways. To address this, our study developed a high-resolution coastal urban flood model, OUC-CUFM (Ocean University of China – Coastal Urban Flood Model), designed to help municipal governments make precise coastal flood forecasts and reduce potential threats to people and property. This model is based on two-dimensional nonlinear Navier–Stokes shallow water equations, incorporating factors like local acceleration, convection, bottom friction, wind stress, and shallow water effects. Using the finite difference method with upwind spatial discretization and a leapfrog time scheme, it can simulate detailed street-level water flow interactions with buildings. In a case study on Macau, we used a 5-m resolution digital elevation model to simulate storm tide flooding from Typhoons Hato (2017) and Mangkhut (2018), with the former for model calibration and the later for validation. Comparisons between simulated and observed water levels showed that the model accurately captured storm water arrival, overtopping, and flood extent and depth. The model also projected flood changes under sea level rise (SLR) scenarios of 0.5 m (by 2070) and 1.0 m (by 2100) for Typhoon Hato, indicating that such SLRs would significantly increase storm-induced flood depth and extent. This model serves as a valuable tool for street-scale flood risk analysis, hazard mapping, and assessing the impact of coastal defenses, like dyke upgrades or new dyke construction, in densely built coastal cities.

Estimation of Terrestrial Water Storage Changes in Brazil From the Joint Inversion of GRACE‐Based Geopotential Difference and GNSS Vertical Displacement Data

AbstractGravity Recovery and Climate Experiment (GRACE) satellite gravimetry and Global Navigation Satellite System (GNSS) surface displacement measurements offer complementary advantages for monitoring terrestrial water storage (TWS) changes. We propose a new joint inversion model based on the combination of GRACE‐based geopotential difference (GPD) observations using the mascon method and GNSS vertical displacements through the Green's function method to obtain reliable TWS changes in Brazil. The performance of the jointly inverted TWS changes is assessed through closed‐loop simulations and comparisons with hydrometeorological data (precipitation‐P, evapotranspiration‐ET, and runoff‐R) using water budget closure (P‐ET‐R) and river water level observations from satellite altimetry. The simulation results indicate that the joint inversion results exhibit higher accuracy and reliability than GRACE GPD‐based mascon (GPD‐mascon) and GNSS solutions, and the standard deviations (STDs) of joint results decrease by ∼6.98 and ∼37.5 mm compared to those from GPD‐mascon and GNSS solutions. The joint inversion of real GRACE and GNSS data demonstrates notably lower uncertainty than that of GPD‐mascon solutions and exhibits significant improvement than GNSS‐only solutions. The STDs and correlation coefficients between monthly R time series derived from three inversion methods (joint inversion, GPD‐mascon and GNSS solutions, combined with P and ET through water budget closure) and in situ observations are 19.607 mm and 0.912, 20.879 mm and 0.904, and 31.370 mm and 0.778, respectively. The joint estimates also yield better correlation with river water level observations compared to GPD‐mascon and GNSS solutions. Furthermore, at the weekly time scale, the joint inversion results show better consistency with P‐ET‐R data than those from GPD‐mascon and GNSS solutions.

Research and application of hydraulic fracturing axial roof cutting technology for gently inclined hard roof based on abrasive jet

In order to explore a new method and mode of gently inclined hard roof treatment, the hydraulic fracturing axial roof cutting technology based on abrasive jet is introduced, and the key technical parameters of abrasive jet axial cutting and fracturing are determined based on indoor experiments and field industrial experiments. Taking the mining of working face under the condition of hard roof in Kuangou Coal Mine as the background, the implementation process and the effect of mining process are tested by means of water pressure gauge, drilling peep and observation well water level observation, mi-croseismic monitoring, support fracture monitoring and coal stress monitoring. The research results show that the key technical parameters of slotting and fracturing are mastered in the axial cutting test of abrasive jet. Wherein the kerf depth is 200 m, the kerf length is 300 m, the kerf pressure is 40–50 mpa, the fracturing pressure is 50–55 mpa, and the fracturing time is 20–30 min. After grooving fracturing, the cracks in the roof strata are effectively generated and expanded, which destroys the integrity of the roof, and the fracturing radius is 10–20 m. During the mining period, compared with the tradi-tional blasting technology, the concentrated area of microseismic events was shifted from 80 m in front of the working face to 130 m after the combined treatment of abrasive jet axial roof cutting and blasting, and the microseismic energy release was mainly small energy events. After the application of abrasive jet axial roof cutting and scour prevention technology in hard roof, the periodic weighting step is obviously reduced, the influence range of mining stress and stress concentration coefficient are obviously reduced, the activity intensity and dynamic load effect of surrounding rock are obviously weakened. The research results provide a basis for effective prevention and control of rockburst disasters under the condition of hard roof.

Interannual variations of terrestrial water storage in the East African Rift region

Abstract. The US–German GRACE (Gravity Recovery and Climate Experiment, 2002–2017) and GRACE-FO (GRACE Follow-On, since 2018) satellite missions observe terrestrial water storage (TWS) variations. Over 20 years of data allow for investigating interannual variations beyond linear trends and seasonal signals. However, the origin of observed TWS changes cannot be determined solely with GRACE and GRACE-FO observations. This study focuses on the northern part of the East African Rift around the lakes of Turkana, Victoria, and Tanganyika. It aims to characterise and analyse the interannual TWS variations compared to meteorological and geodetic observations of the water storage compartments (surface water, soil moisture, and groundwater). We apply the STL (Seasonal-Trend decomposition using LOESS) method to decompose the signal into a seasonal signal, an interannual signal, and residuals. By clustering the interannual TWS dynamics for the African continent, we define the exact outline of the study region. We observe a TWS decrease until 2006, followed by a steady rise until 2016, and then the most significant TWS gain in Africa in 2019 and 2020. Besides meteorological variability, surface water storage variations in the lakes explain large parts of the TWS decrease before 2006. The storage dynamics of Lake Victoria alone contribute up to 50 % of these TWS changes. On the other hand, the significant TWS increase around 2020 can be attributed to nearly equal rises in groundwater and surface water storage, which coincide with a substantial precipitation surplus. Soil moisture explains most of the seasonal variability but does not influence the interannual variations. As Lake Victoria dominates the surface water storage variations in the region, we further investigate the lake and the downstream Nile River. The Nalubaale Dam regulates Lake Victoria's outflow. Water level observations from satellite altimetry reveal the impact of dam operations on downstream discharge and on TWS decreases in the drought years before 2006. On the other hand, we do not find evidence for an impact of the Nalubaale Dam regulations on the strong TWS increase after 2019.

A coupled regional-scale numerical model for hydrological processes and interactions between groundwater and surface water in a controlled drainage district

Controlled drainage (CD) has emerged as an effective strategy to prevent field waterlogging and mitigate drought during crop growth by altering the hydrological process, while few studies have quantified its effect on groundwater-surface water interactions and groundwater recharge at a regional scale. In this study, a new model is developed for the coupled numerical simulation of water flow in ditches, soil, and underground aquifers under CD conditions. The domain is partitioned into horizontal sub-areas and two vertical layers, with ditches discretized into segments based on groundwater flow grids. The Saint-Venant equations, Richards equation, and MODFLOW are applied to describe water movement processes in ditches, soil, and underground aquifers, respectively. The proposed model is calibrated and validated using five years of observations of ditch water levels (DWL) and groundwater levels, demonstrating excellent agreement with observed data. Subsequently, water balance components of the shallow aquifer below 1 m depth (GW), 1 m of root layer soil profile (SW), and ditch water (DW) under seven scenarios with different control schemes during flood and dry seasons are analyzed to quantify variations in hydrological processes caused by CD. The results show that CD significantly impacts water within SW, GW, and DW, soil evaporation, infiltration, and net recharge from GW to SW (GtoS) by altering regional groundwater table depth (GWT) through the exchange between DW and GW (DtoG and GtoD). GWT and DW show moderate correlation with GtoD, while their correlation with DtoG varies significantly under different rainfall conditions. Smaller precipitation results that precipitation and GWT have a higher linear correlation with water balance components during the dry season compared to the flood season. The correlation values (r) between transpiration (T) and GWT range from −0.99 to 0.96 and −1 to −0.85 during the flood and dry seasons, respectively, indicating a pronounced influence of CD on crop growth. On average, a 1 m increase in DWL control scheme leads to a 0.51 m increase in DWL, and regional GWT decreases by 0.35 m and 0.24 m during flood and dry seasons, respectively. Furthermore, for every 1 m decrease in GWT, net GtoS increases by 36.1 mm and 28.1 mm, respectively, resulting in an increase in SW by 13.9 mm and 11.8 mm, respectively. Considering the varying main crop water stress and the impact of CD under different rainfall conditions, an appropriate CD scheme needs to be adjusted accordingly. These findings provide a quantitative reference for the effect of CD on regional hydrological process and serve as a typical case for similar areas aiming to implement CD strategies for waterlogging and drought control.

Combining earth observations with ground data to assess river topography and morphologic change: Case study of the lower Jamuna River

The Jamuna is a major braided river of Bangladesh and poses enormous challenges related to flooding, erosion, and sedimentation. Effective river management requires an understanding of the Jamuna’s sediment transport dynamics and channel morphology. Yet, developing that understanding is hindered by a lack of topographic data for the river corridor. In this study, the waterline method was applied to a 65 km reach of the Jamuna to derive river channel and floodplain topography above the low water level. The analysis relies on surface water detection from Sentinel-1 and Sentinel-2 data, along with in-situ water level observations, to generate river-floodplain DEMs for the years 2016–2019. Morphologic change was assessed through DEMs of difference for sequential years and for the overall study period. A quantitative uncertainty analysis was conducted to characterize errors in the waterline DEMs, vertical change detection, and gross and net volumetric changes. The results indicate that gross annual erosion and accretion volumes have a similar order of magnitude to contemporary estimates of the river’s sediment influx. The study highlights that localized and reach-scale lateral exchange is a key component of the overall sediment budget. Finally, the uncertainty analysis framework provides insight and recommendations for how errors can be assessed and reduced in future waterline applications.

Wave runup and total water level observations from time series imagery at several sites with varying nearshore morphologies

Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. We utilize over 7000 hand-digitized timestacks from six diverse locations to train and validate machine learning models to automate the process of TWL extraction. Using these data, we evaluate two deep learning model architectures for the task of runup detection. One is based on a fully convolutional architecture trained from scratch, and the other is a transformer-based architecture trained using transfer learning. The deep learning models provide a probability of each pixel being either wet or dry. When contoured at the 50% level (equal chance of being wet or dry), the deep learning models more accurately identified TWL maxima than minima at all sites. This resulted in accurate predictions of 2% exceedance runup, but under predictions of significant swash and over predictions of wave setup. Improved agreement with the complete TWL time series was obtained through post-processing by utilizing the wet/dry probability of each pixel to weight the contouring toward lower dryness probabilities for runup minima (maxima agreed well with observations without tuning). Overall, a transformer-based model using transfer learning provided the best agreement with wave runup statistics, including a) the 2% exceedance runup, b) significant swash, and c) wave setup at the shoreline. For a random subset of images, the model was found to be within the uncertainty range of hand-digitization. The relative success of the transfer learning model suggests that fine-tuning a large model has advantages compared to training a smaller model from scratch. Models provide per-pixel probabilistic estimates in less than 10 s per timestack on a single computational unit, versus the more than 5 min required for hand-digitization. The model is therefore well-suited for near real-time applications, allowing for the development of early warning systems for difficult to forecast events. Real-time wave runup and total water level observations can also be incorporated into coastal hazards forecasts for data assimilation and continual model validation and improvement.

Enhancing real-time flood forecasting and warning system by integrating ensemble techniques and hydrologic model simulations

ABSTRACT Flooding poses a severe threat to communities and infrastructure worldwide, which requires advanced flood forecasting warning systems. In this research paper, a real-time flood forecasting and warning system for the Dharoi Dam in the state of Gujarat, India is developed. This novel system combines ensemble techniques and hydrological modeling simulations to enhance flood prediction accuracy and provides a timely warning. The study focuses on critical gaps in the current flood forecasting capabilities, recognizes the need for improved flood management in the region, and builds upon the existing research conducted globally and in India. The real-time flood forecasting and warning system uses information from various sources such as rainfall, river flows, and water level observations. The system enhances the accuracy of flood forecasts with a 1–5-day lead time by utilizing ensemble techniques, which incorporate multiple models and their corresponding forecasts. The 2-day and 3-day lead times combined with postprocessing techniques yield excellent results, as evidenced by the reservoir inflow correlation value of 0.86 and the receiver operating characteristic-area under the curve (ROC-AUC) value of 0.93. This work aims to reduce the impact of floods in this region and can be used by decision-makers as a disaster management tool.

Global sensitivity analysis of water level response to harmonic aquifer disturbances through a Monte-Carlo based surrogate model with random forest algorithm

Oscillatory water levels are often observed in monitoring wells, when aquifers are disturbed by periodical pressure diffusion (PD) sources, such as oscillatory pumping and ocean tide, and by volumetric strain (VS) sources including the far-field seismic wave and earth tide. The measured water level responses are extensively utilized to interpret aquifer properties and seismic hydrological phenomena. However, owing to wellbore effects, water levels are not always truly representative of pore pressure in aquifers, and can be significantly attenuated or even unobservable in wells. To clarify how water level responds to these disturbances, this study analyzes a global parameter sensitivity of the coupled well-aquifer model based on the assumption of a confined homogeneous aquifer. Parameter uncertainties concerning aquifer properties, source characteristics, and wellbore construction are first analyzed separately for the PD and VS sources. Subsequently, Monte-Carlo based surrogate models linking parameters and response indices are developed using the random forest algorithm. For the PD source, sensitivity results indicate that hydraulic conductivity is the most influential parameter for the yes/no responses. When hydraulic conductivity exceeds 10-4 m/s, water level observations basically represent pore pressure in aquifers. Significant amplitude changes and phase delay occur when the period of disturbances is less than 50 s, majorly due to water column inertia. For VS sources, water level responses are typically observed in aquifers with hydraulic conductivity larger than 10-7 m/s and when disturbed by a source with amplitude greater than 10-3 MPa. However, pronounced amplitude changes and phase shifts occur when the source period varies within 100 s. Consideration of the impact of wellbore effects is recommended, when interpreting water level responses induced by all periodic aquifer disturbances, especially in low-conductivity aquifers with conductivities less than 10-4 m/s.

Evaluation of repeat bathymetric surveys on water surface elevations on the Saint Clair River

The Great Lakes contain 20 percent of the world’s fresh surface water, a drinking source for 30- million people. The system is vital to manufacturing, largely due to efficient transportation of commodities and an abundance of natural resources. Understanding the water balance and predicting future water levels is important for many industries including commercial navigation, the tourist industry, hydropower and shoreline property owners, just to name a few. These predictions require an understanding of both the hydroclimate drivers across the Great Lakes as well as physical changes in the connecting channels that pass water between each lake. Since the International Upper Great Lakes Study began, the St. Clair River has been the topic of conveyance change investigations. This study tests the sensitivity of water surface elevations to small differences in bathymetric changes. Greater than 80 percent of the surveyed points had less than 0.24 m of change between any combination of survey years. Repeat bathymetric surveys collected in 2007, 2012 and 2021, along with hydrodynamic modeling, find changes in water surface elevations associated with bathymetric change are on the sub-centimeter scale. These changes are put into perspective and compared to known anthropogenic and naturally occurring conveyance changes. While these surveys represent a short duration in the observed water level record of the Great Lakes, they represent an important documentation of the geomorphic state of the St. Clair River. These changes can and should be compared to similar future surveys of the river over longer engineering and geomorphic timescales.

Unveiling the hidden dynamics of intermittent surface water: A remote sensing framework

Intermittent surface water frequently transitioning between water and land over months and years, plays a crucial and increasingly significant role in both social and ecological systems. However, their vital and dramatic dynamics have mainly remained invisible due to monitoring limitations. We present a new remote sensing framework to capture the long-term monthly dynamics of surface water bodies, applying it to Poyang Lake, the largest freshwater lake in China. This framework employed a random forest classifier on all available Landsat data to identify monthly surface water bodies. Additionally, we developed a Spatial and Temporal Neighborhood Similarity-based Gap Filling method to restore water bodies obscured by clouds and ensure spatial integrity. Furthermore, we introduced an index to quantify the intermittency of surface water bodies on a scale from 0 to 1, allowing for the classification of water bodies into three categories: perennial, wet intermittent, and dry intermittent. Employing this framework, we reconstructed the most complete monthly 30-m surface water dataset for cloudy regions to date, covering April 1986 to September 2023, demonstrating a strong correlation (Spearman's rank correlation coefficient of 0.909) with observed water levels. The results reveal a landscape dominantly composed of intermittent water bodies (91.2%), with a rapidly shrinking trend of perennial water bodies at 1303.58 ha per year. Notably, 162,685 ha (21.9%) of water bodies transitioned toward drier and more intermittent statuses. Dry intermittent water bodies exhibited the most pronounced land-water transitions, with the highest water-to-land (82.5%) and land-to-water (89.9%) proportions among the three categories. By uncovering the hidden dynamics of intermittent surface water, and highlighting its prevalence, expansion, and vulnerability, this framework paves the way for a better understanding of these critical water dynamics across the globe.

Spatio-Temporal Variation in Suspended Sediment during Typhoon Ampil under Wave–Current Interactions in the Yangtze River Estuary

Suspended sediment plays a major role in estuary morphological change and shoal erosion and deposition. The impact of storm waves on sediment transport and resuspension in the Yangtze River Estuary (YRE) was investigated using a 3D coupling hydrodynamic-wave model with a sediment transport model during Typhoon Ampil. This model has been validated in field observations of water level, current, wave, and sediment concentration. The model was run for tide only, tide + wind, tide + wind and wave forcing conditions. It was found that: (1) typhoons can increase the suspended sediment concentration (SSC) by enhancing bed shear stress (BSS), especially in the offshore area of the YRE, and there is hysteresis between SSC and BSS variation; (2) exponential and vertical-line types are the main vertical profile of the SSC in the YRE and typhoons can strengthen vertical mixing and reconstruct the vertical distribution; and (3) waves are the dominating forcing factor for the SSC in the majority of the YRE through wave-induced BSS which releases sediment from the seabed. This study comprehensively investigates the spatio-temporal variation in SSC induced by Typhoon Ampil in the main branch of the YRE, which provides insights into sediment transport and resuspension during severe storms for estuaries around the world.

Assessment of water levels from 43 years of NOAA’s Coastal Ocean Reanalysis (CORA) for the Gulf of Mexico and East Coasts

Coastal water level information is crucial for understanding flood occurrences and changing risks. Here, we validate the preliminary version (0.9) of NOAA’s Coastal Ocean Reanalysis (CORA), which is a 43-year reanalysis (1979–2021) of hourly coastal water levels for the Gulf of Mexico and Atlantic Ocean (i.e., the Gulf and East Coast region, or GEC). CORA-GEC v0.9 was conducted by the Renaissance Computing Institute using the coupled ADCIRC+SWAN coastal circulation and wave model. The model uses an unstructured mesh of nodes with varying spatial resolution that averages 400 m near the coast and is much coarser in the open ocean. Water level variations associated with tides and meteorological forcing are explicitly modeled, while lower-frequency water level variations are included by dynamically assimilating observations from NOAA’s National Water Level Observation Network. We compare CORA to water level observations that were either assimilated or not, and find that the reanalysis generally performs better than a state-of-the-art global ocean reanalysis (GLORYS12) in capturing the variability on monthly, seasonal, and interannual timescales as well as the long-term trend. The variability of hourly non-tidal residuals is also shown to be well resolved in CORA when compared to water level observations. Lastly, we present a case study of extreme water levels and coastal inundations around Miami, Florida to demonstrate an application of CORA for studying flood risks. Our assessment suggests that NOAA’s CORA-GEC v0.9 provides valuable information on water levels and flooding occurrence from 1979–2021 in areas that are experiencing changes across multiple time scales. CORA potentially can enhance flood risk assessment along parts of the U.S. Coast that do not have historical water level observations.

Modelling Approach for Assessment of Groundwater Potential of the Moghra Aquifer, Egypt, for Extensive Rural Development

Groundwater-dependent cultivation is imperative to meet the ever-increasing food demands in Egypt. To explore the Moghra aquifer’s potential, where a large-scale rural community is being established, a finite element groundwater flow (i.e., FEFLOW®) model was invoked. The developed model was calibrated against the observed water levels. GRACE-based groundwater storage was incorporated into the tuning procedure of the developed model. Eight abstraction rates from 1000 wells, changing from 800 to 1500 m3/day/well, were simulated for a 100-year test period. The maximum resulting drawdown values, respectively, ranged from 59 to 112 m equating to about 20–40% of the aquifer’s saturated thickness. The implications of the climate change from gradual sea level rise and an increase in crop consumptive water use were investigated. Extending seawater invasion into the aquifer caused a slight increase in the piezometric levels within a narrow strip along the seaside. Applying a chronologically increasing withdrawal rate to meet the projected increment in crop water requirements raised the maximum resulting drawdown by about 7.5%. The sustainable exploitation regime was defined as a time-increasing withdrawal rate adequate to reclaim 85,715 acres (34,688 ha). The recommended development scheme is compatible with the withdrawal rationing rule, aiming to maintain that the resulting drawdown does not exceed one meter a year.

Temporal and spatial variation of typhoon-induced surges and the impact of rainfall in a tidal river

The Huangpu River, which flows into the Yangtze Estuary, runs through Shanghai Municipality in China. During the flood season, typhoon-induced surges result in extremely high water levels in the Huangpu River, which is the main factor threatening flood control safety in Shanghai. Based on observations of water levels at three stations along the Huangpu River from 2008 to 2021, together with wind and rainfall, this paper investigates: the trends of the annual highest storm surges; the differences in periodic variation and magnitude of surges during the spring-neap cycle; the longitudinal variation of surges; and the impact of rainfall. The results show that the annual highest surges at three stations all show a significant increasing trend, which is caused by the increasing wind speed, and the intensity and duration of rainfall during typhoon events, induced by the increasing frequency of landfall and close-to-YE (Yangtze Estuary) typhoon events, and strong and very strong typhoon events. The periodic variation and magnitude of surges show clear differences during the spring-neap cycle, resulting from the largest nonlinear surge-tide interaction during spring tide and the smallest during neap tide. Heavy rainfall can reduce the probability of 6–7 h and 2.7–3.3 h periods, and change the phase of the periodic variation, inducing partial main peaks and maximum surges during ebb or low tide. The longitudinal variation of storm surge along the Huangpu River can be divided into three types: decreasing upstream, first increasing then decreasing, and increasing upstream. Heavy and long-duration rainfall increases the water discharge from the basin to the river, amplifying the surge, with the largest impact in the upper reach and the smallest in the lower reach, which is the main factor inducing the latter two types, particularly the third type.