Water Level Observations Research Articles

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.

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.

Refining ICESAT-2 ATL13 Altimetry Data for Improving Water Surface Elevation Accuracy on Rivers

The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect solely with water. It is acknowledged that the ATL13 product has noise elevations of the adjacent land, resulting in biased high mean WSEs at VSs. Earlier studies have relied on human intervention or water masks to resolve this. Both approaches are unsatisfactory solutions for large river basins where the issue becomes pronounced due to many tributaries and meanders. There is no automated procedure to partition the truly representative water height from the totality of the along-track ICESAT-2 photon segments (portions of photon points along a beam) for increasing precision of the mean WSE at VSs. We have developed an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparing the ATL13-derived WSEs with direct water level observations at 10 different gauging stations on 37 different dates along the Lower Murray River, Australia. The concordance between the two datasets is significantly high and without detectable bias. In addition, we evaluated the effects of four methods for calculating the mean WSEs at VSs after auto-segmentation processing. Our results reveal that all methods perform almost equally well, with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189 m) and MAE (0.130–0.142 m). We also found that the R2, RMSE and MAE are better under the high flow condition (0.999, 0.124 and 0.111 m) than those under the normal-low flow condition (0.997, 0.208 and 0.160 m). Overall, our auto-segmentation method is an effective and efficient approach for deriving accurate mean WSEs at river VSs. It will contribute to the improvement of ICESAT-2 ATL13 altimetry data utility on rivers.

Development and Field Testing of the Technical Implementation Unit for Lowland Automatic Water Level Recorder (AWLR BTR) for Water Level Measurement in Jejangkit Lowland Irrigation Area, South Kalimantan

Observation of water levels using tide gauge is typically conducted by designated personnel or observers. However, its on-field implementation is deemed to be less effective due to the relatively low accuracy of readings. Additionally, hourly water level readings are necessary to generate detailed tidal patterns. Hence, Automatic Water Level Recorder (AWLR) plays a crucial role as an alternative to tide gauge. The utilization of AWLR is considered more practical, yielding more accurate reading data. Furthermore, readings can be conducted continuously, ensuring data acquisition in all conditions. The development of the AWLR BTR system involved literature reviews, software development, hardware assembly, device testing, field trials, and data comparison with the Valeport Tide Gauge. Field trials were conducted at DIR Jejangkit, South Kalimantan. The conducted trials involved operating the AWLR BTR and comparing it with the Valeport AWLR data for validation. Through calculations, the comparison of data between AWLR BTR and AWLR Valeport demonstrates similar water level values, where the average value from AWLR BTR data is 39,69 and Valeport is 39,55. Meanwhile, the Pearson correlation coefficient between the water levels of AWLR BTR and AWLR Valeport is found to be 0,9976, indicating a strong positive correlation between these two data variables.

Water resources management considering groundwater instability affected by climate change scenarios

In the present study, using GMS and MODFLOW code, a model of Khorramabad aquifer (Iran) was developed under unsteady conditions with considering the climate change (as a study innovation) in scenarios of RCP26 (optimistic) and RCP85 (pessimistic) based on results of CNRM-CM5 global climate model (Centre National de Recherches Me'te'orologiques—phase 5 of the Coupled Model). Using surface runoff data and computational level output from GMS, an integrated model was created in WEAP. According to scenarios of RCP26 and RCP85 for periods (2040–2069) and (2070–2099), the climate change effects on surface water and groundwater were evaluated. Results showed that water level calculated by GMS was obtained with high accuracy in calibration period (RMSR = 1.42 m, MSR = 0.85 m) and in verification period (MAE = 0.88, r = 0.98 and NSE = 0.97), which was in agreement with observed water levels of wells in region. The water level in RCP26 (2040–2069 and 2070–2099) compared to observed water level, on average, decreased by 0.154 m and 1.175 m, respectively, and in RCP85 for the same period, a decrease of 0.621 m and 0.753 m of calculated water level was observed compared to baseline. Then, allocation of surface water and groundwater resources to consumption sectors (agricultural, urban and industrial sectors) was analyzed using WEAP. Results showed that the lowest deficit of water resources in all sectors occurred in RCP26 (2040–2069) with a value of 7% and the highest deficit occurred in RCP85 (2070–2099) with a value of 180% compared to baseline.

Quantifying compound flood event uncertainties in a wave and tidally dominated coastal region: The impacts of copula selection, sampling, record length, and precipitation gauge selection

AbstractCoastal flooding is a growing hazard. Compound event characterization and uncertainty quantification are critical to accurate flood risk assessment. This study presents univariate, conditional, and joint probabilities for observed water levels, precipitation, and waves. Design events for 10‐ and 100‐year marine water level and precipitation events are developed. A total water level formulation explicitly accounting for wave impacts is presented. Uncertainties associated with sampling method, copula selection, data record length, and utilized rainfall gauge are determined. Eight copulas are used to quantify multivariate uncertainty. Generally, copulas present similar results, except the BB5. Sampling method uncertainty was quantified using four sampling types; annual maximum, annual coinciding, wet season monthly maximum, and wet season monthly coinciding sampling. Annual coinciding sampling typically produced the lowest event magnitude estimates. Uncertainty associated with record length was explored by partitioning a 100‐year record into various subsets. Withholding 30 years of observations (i.e., records of less than 70 years) resulted in substantial variability of both the 10‐ and 100‐year return period estimates. Approximately equidistant rainfall gauges led to large event estimate differences, suggesting microclimatology and gauge selection play a key role in characterizing compound events. Generally, event estimate uncertainty was dominated by sampling method and rainfall gauge selection.