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To date, seasonal dynamics of the denitrifying bacterial community in floodplain lakes is unknown. Here, we investigated the alpha diversity, abundance and composition of the sediment nirS-type denitrifying bacteria in Poyang Lake during the wet, mid-dry and dry seasons using Illumina MiSeq sequencing and quantitative polymerase chain reaction assay. The results showed that only a small part of the total operational taxonomic units (OTUs) were shared by the three seasons. OTU richness, Chao richness estimator and Shannon index exhibited higher values in the wet season than in the dry season. Some regular patterns of variation in the composition of the nirS-type denitrifying community at three classification levels (phylum, class and genus) were found among seasons. Community structures of nirS-type denitrifying bacteria were significantly different across seasons. In addition, the abundance of nirS gene showed no seasonal pattern. Total nitrogen, total phosphorous and pH were the most significant factors elucidating the compositional variation of the nirS-type denitrifying community. This study provided a new evidence for the ecological effects of seasonal water level fluctuations and improved our understanding of the nitrogen removal processes in floodplain lakes. [ABSTRACT FROM AUTHOR]

We conducted a study to characterize the nutritional composition of the main aquatic herbaceous plants in two protected areas within the Central Amazon. Our investigation aimed to evaluate possible nutritional variations in these plant species between two floodplains contrasting in fertility throughout the annual hydrological cycle and to examine if such differences might influence Amazonian manatee migration patterns. Plant samples were collected during high water levels (2007), receding water levels (2013), and low water levels (2008). Bromatological analysis was employed to characterize various nutritional parameters including dry matter, moisture, crude protein, fat, mineral matter, non-nitrogenous extract, and digestible energy. Our findings revealed no significant variations in nutritional contents between herbaceous plants from várzea and igapó environments. However, nutrient compositions varied within each floodplain type across different hydrological periods. High levels of fat and crude fiber observed in both environments during high and receding water periods suggest an energetic contribution to the manatee's reproductive, migratory, and feeding restrictions. Nonetheless, irrespective of hydrological periods and environmental types, Amazonian manatees appear to have assess to aquatic plants with adequate nutritional requirements. Thus, migrations may be more closely associated with physical constraints of the environments rather than solely driven by the animal's feeding demands. [ABSTRACT FROM AUTHOR]

The preconcentration of uranium VI (U(VI)) at trace levels in some real water and wastewater samples and its determination by spectrophotometry using a homogeneous solvent-based microextraction method, specifically in-situ solvent formation microextraction, were investigated. This microextraction method uses a unique task-specific ionic liquid (IL) as the specific complexing agent and/or extracting phase. A pyrrolidinium-based IL modified with (E)-5-(bromomethyl)-2-(pyridin-2-yldiazenyl) phenol as a task-specific IL (E)-1-(3-hydroxy-4-(pyridin-2-yldiazenyl) benzyl)-1-methylpyrrolidinium bromide (TSIL/Br) was successfully synthesized and characterized by 1HNMR and FTIR analyses. TSIL/Br chelated with U(VI) ions in the aqueous phase to form a hydrophilic [U(VI)-TSIL/Br2] complex with high efficiency. It was then converted to a hydrophobic [U(VI)-TSIL/(NTf2)2] complex through a counter-ion agent, such as bis(trifluoromethanesulfonyl)imide ( NTF 2 - ) for separation from the aqueous solution phase. This process eliminates the need for a separate complexing agent, because TSIL/Br acts simultaneously as both a complexing agent and an extracting solvent. In brief, the conditions of the microextraction process must be optimized for the analysis of real water samples. Under the optimum conditions, a preconcentration factor, detection limit, quantification limit, linear dynamic range, and relative standard deviation of 218, 1.62 ng·mL−1, 5.42 ng·mL−1, 20.0–450.0 ng·mL−1, and 2.47% (n = 10, 20 ng·mL−1) were obtained, respectively. Finally, to assess the method's ability, it was successfully employed to determine the U(VI) ion content in various real water, wastewater and reference material samples. [ABSTRACT FROM AUTHOR]

Environmental impacts related to arsenic (As) contamination are a persistent issue of particular interest in Latin American countries with increasing mining activities. In Ecuador, the redefinition of public policies to promote the increase in mining since 2008 has led to a significant rise in the presence of this heavy metal in rivers and effluents, sometimes exceeding the 0.1 mg L−1, limit recommended by Ecuadorian Environmental Regulations. This study aimed to evaluate the sublethal effects through the detection of biochemical biomarker changes (Catalase, Antioxidant capacity by FRAP, and Glutathione S-transferase) generated in larvae of Nectopsyche sp following prolonged exposure to different concentrations of As (C1 = 0.05 mg L−1, C2 = 0.1 mg L−1, C3 = 0.8 mg L−1) in a controlled environment, emulating the maximum limits allowed by current Ecuadorian legislation. While As concentration levels in water increased, so did levels in the tissue of Nectopsyche sp specimens. On the other hand, behavioral parameters (mortality and mobility) did not show differences in either time or As concentrations. However, both Catalase and Antioxidant capacity by FRAP levels tended to decrease with increasing As concentration, and in both cases, the differences were significant. Additionally, Glutathione S-transferase activity did not increase significantly. These results preliminarily demonstrate that biochemical responses change with varying As concentrations in Nectopsyche sp and are affected at behavioral and biochemical levels produced by the As at chronic levels. [ABSTRACT FROM AUTHOR]

Twenty years of surface elevation table and marker horizon monitoring at three sites along the Fire Island (New York, USA) barrier island indicates that rates of marsh surface elevation change (Watch Hill, 4.4 mm year−1; Hospital Point, 3.5 mm year−1; Great Gun, − 0.3 mm year−1) were lower than the rate of monthly mean sea-level rise during the 2002–2022 monitoring period (5.1 mm year−1, NOAA Sandy Hook, NJ, water level station). The Great Gun monitoring site, with an elevation deficit relative to sea-level rise, shallow subsidence (surface accretion > marsh elevation rate), low elevation capital, prolonged marsh surface flooding, and declining vegetation cover, displays characteristics common to deteriorating marshes. The submergence trend was not as evident at the other monitoring sites, but with low tidal range (0.4 m) and projections of accelerated sea-level rise, sustainability is questioned if marsh elevation change continues to lag behind the local rate of relative sea-level rise. Hurricane Sandy occurred during the monitoring period (October 2012), creating a new inlet located about 300 m from one of the monitoring sites. Surprisingly, no immediate signals of deposition or erosion were noted from the marker horizon sampling. Overwash sand deposits on the marsh surface were extensive along Fire Island, although not reaching the monitoring sites, and will likely provide opportunities for future salt marsh growth, as will the flood-tide delta created by the inlet. Projecting the future of barrier island salt marshes under a regime of accelerated sea-level rise and episodic storms requires knowledge of marsh elevation and accretion processes and geomorphic dynamics. [ABSTRACT FROM AUTHOR]

Horizontal wells have gained popularity as a technology for exploring water resources and remediating aquifers over the last decades, due to costs and numerous technical benefits compared to traditional vertical wells. This study presents a set of analytical solutions for drawdown distribution and various components of water budget contributing to flow toward a horizontal well in an aquifer-aquitard system interacting with a fully penetrating stream. It is assumed that the water level in the upper unconfined aquifer remains fixed at a specific elevation during the course of the pumping in the lower leaky aquifer. The water budget components account for inflows from aquifer storage, stream depletion, and leakage across the aquifer-aquitard interface. Analytical solutions to this three-dimensional, transient, non-axisymmetric Darcian flow model are given for both transient and steady-state flow conditions, relying on a four-fold integral transform technique that includes a Robin-type boundary condition at the aquifer-aquitard interface. It is shown how various components of water budget collectively counterbalance the effect of pumping discharge, confirming that the mass is conserved under both continuous and non-continuous pumping scenarios. Response maps are prepared to assess how different components of water budget react to changes in the well position. Furthermore, it is found that the components of water budget are most sensitive to the well-to-stream distance and anisotropy ratio of the leaky aquifer. [ABSTRACT FROM AUTHOR]

A method for the determination of phthalates in water is validated. It includes the sorption of hydrophobic components of a sample on a liquid chromatography column and the separation of analyte concentrated by online reversed-phase HPLC: for the quantitative determination of priority phthalates (PPhs) in surface waters at a trace level; qualitative assessment of the ratio of stable carbon isotopes 13C/12C in the PPh composition. It is shown that there is no contribution of PPhs from the laboratory background to the measurement results. The limits of determination (0.15−0.22 μg/L) and the accuracy of the determination (±δ = 10−20%) are found using online reversed-phase HPLC and the UV detection of the analytes. The boundary values for the 13C/12C isotope ratio are substantiated for a qualitative assessment of the results of measuring the Δ13C value in the structure of di(2-ethylhexyl) phthalate and its ingress into waters of Lake Baikal from biogenic and abiogenic sources is revealed. A procedure for determining PPhs by reversed-phase HPLC with online UV detection is tested in the field using a portable liquid chromatograph; the concentration ranges for di-n-butyl phthalate (from <0.15 to 1.6 μg/L) and di(2-ethylhexyl) phthalate (from <0.22 to 1.6 µg/L) in the coastal zone of Lake Baikal are evaluated. [ABSTRACT FROM AUTHOR]

The release rate of CO2 gas can be influenced by peatlands' physical properties, such as water level and soil moisture, and rainfall. To anticipate the unstable condition which is when the peatland emit more carbon, we developed the Generalized Space Time Autoregressive (GSTAR) model in predicting these physical properties for the following weeks. As the innovation in modelling, the spatial weight matrix was based on three-dimensional coordinates with a modification on the height factor. The data we used are real-time data of water level on the peatlands in Pulang Pisau Regency, Central Kalimantan Province from 20 February 2021 to 18 March 2023. We then used Ordinary Kriging interpolation on the prediction results to create contour maps on different dates. There were empty data on several dates, especially from 24 March until 3 August 2022. To fill the empty data, we used linear interpolation and then we added white noise to the interpolation results. From the data, the water level has a downward trend pattern from around November to September and an upward trend pattern from October to November. Furthermore, we found that the best model for water level was GSTAR (2;0.1) with a modified matrix a = 0.1 and b = 1.1 . Based on the predicted water level, there is a risk of changes in the properties of the peatlands in several areas in Pulang Pisau Regency. [ABSTRACT FROM AUTHOR]

Currently, the alarm functions of existing levee seepage monitoring systems are limited to single-parameter monitoring and lack rate-of-change alarms and correlation alarms. This can lead to false alarms, missed alarms, equipment failures, or unnecessary downtime. To enhance the intelligence of levee safety monitoring and seepage alarms, a levee seepage intelligent alarm system based on a Bidirectional Long Short-Term Memory (BILSTM) network model was designed and implemented. Firstly, data cleaning and preprocessing are carried out on the engineering safety monitoring operation data to reduce the influence of dirty data such as outliers and repetitive values on the accuracy of alarms. Secondly, for the correlation between the piezometric tube water levels of the levee and the Yangtze River water levels, a correlation analysis based on Mutual Information (MI) theory was conducted to minimize the effect of piezometric tube water level change delays on correlation. Finally, the BILSTM model was used to predict trends in these potentially abnormal data intervals. Based on engineering application requirements, alarm thresholds were established, and a multi-level alarm module was developed. Field operation test results show that the proposed method can accurately predict the piezometric tube water levels of levees, achieving intelligent alarms within the engineering safety monitoring system. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to the spatiotemporal design of groundwater quality monitoring networks for coastal aquifers. A fusion model combines the outputs of several developed simulation models to make estimates more accurate. A modified GALDIT method is used to incorporate the aquifer vulnerability to saltwater intrusion. The value of information (VOI) theory is applied to determine sufficient monitoring wells. The groundwater quality monitoring network is designed by employing a robust decision-making (RDM) approach under different management strategies and economic considerations. This approach incorporates the deep uncertainties of some critical variables, including water level and total dissolved solids (TDS) concentration at the coastline and pumping flow rates of agricultural wells. The new methodology is implemented in the coastal Qom-Kahak aquifer, Iran. The results illustrate that the combination model has significantly improved evaluation criteria compared to individual prediction models. The fusion model results indicate that thirty monitoring wells would be ideal. The RDM-based analyses in the Qom-Kahak aquifer showed that an optimal network with 30 monitoring wells outperforms the current network regarding various criteria, such as VOI and variance of estimation error. The new well configuration also demonstrates a suitable spatial distribution. Given that the current sampling frequencies are unsuitable for areas with varying vulnerabilities, we recommend sampling every 3 months in areas with moderate vulnerabilities and once every three seasons in areas with low vulnerabilities, based on the information transfer index. Finally, a management strategy in which the pumping rate should be less than 60% of the current rate is suggested to prevent saltwater intrusion into the aquifer. [ABSTRACT FROM AUTHOR]

This paper presents deep learning using LSTM, machine learning employing RF and GB algorithms, and the rating curve (RC) that can be used for estimating daily streamflow at the outlet of river basins. The Kone River basin in Vietnam is selected as an example for demonstrating the ability of these approaches. Hydro-meteorological data, including rainfall at Vinh Kim as well as water level and streamflow at Binh Tuong, were collected in the long period from 1/1/1979 to 31/12/2018. Multiple approaches mentioned above are implemented and applied for estimating daily streamflow at Binh Tuong in the Kone River basin. Firstly, coefficients and hyper-parameters in each approach are carefully determined using available hydro-meteorological data from 1/1/1979 to 31/12/2009 and dimensional and dimensionless error indexes. The results revealed that deep learning using LSTM presents the most suitable performance of the observed streamflow, with correlation coefficient r and NSE being close unity, while RMSE and MAE are less than 1.5% of the observed magnitude of streamflow. The RC and machine learning employing RF and GB algorithms procedures acceptably the observed streamflow, with r and NSE varying between 0.77 and 0.98, and RMSE and MAE ranging from 0.4 to 6.0% of the observed magnitude of streamflow. Secondly, multiple approaches are also applied for estimating daily streamflow from 1/1/2010 to 31/12/2018, revealing consistent statistical characteristics of streamflow in the river basin. Finally, the impacts of input data on output streamflow are discussed. [ABSTRACT FROM AUTHOR]

A heated junction thermocouple (HJTC) is a device designed to monitor the water level of nuclear reactors to prevent explosions due to overheating. This device consists of heated and non-heated thermocouples. When heat is applied, the temperature rise in HJTC varies depending on whether the device is submerged in water or exposed to air. In this study, we analyzed the thermal characteristics of HJTC through 3D COMSOL simulation. The temperature profile of the cross-section was extracted based on three design parameters: applied heat, heating length of the wound coil, and diameter of the HJTC. The temperature difference between the two thermocouples was more pronounced upon exposure to air. Meanwhile, high applied heat, short coil heating length, and small diameter of the HJTC contributed to a more pronounced temperature difference based on the surrounding environment. These results can aid in the appropriate HJTC design to achieve the desired detection sensitivity. [ABSTRACT FROM AUTHOR]

High-accuracy deformation monitoring is crucial for investigating landslide–pipeline interaction problems, in which the fiber optic nerve system (FONS) holds enormous potential. This paper presents a theoretical framework for interpreting landslide–pipeline interactions using the FONS and proposes a novel method for calculating characteristic parameters of pipe–soil interfaces based on distributed strain measurements. The feasibility of this method is validated through a full-scale model test, and its application for studying pipeline behaviors is demonstrated in the Xinpu landslide, situated in the Three Gorges Reservoir region, China. The field monitoring results reveal that short-duration, high-intensity rainfall events triggered immediate acceleration of landslide movements, leading to pipeline elongation and flexure. Strain measurements of the underground pipeline allow for the identification of the local slipping interface of the landslide. Furthermore, the relationships between reservoir water level (RWL) fluctuations, rainfall events, landslide deformation, and the structural response of the pipe are analyzed. The findings suggest that the deformation of the landslide in the leading and middle parts exhibits high correlations with the combined effect of rainfall and RWL drawdown. [ABSTRACT FROM AUTHOR]

Remote sensing is now a valued solution for more accurately budgeting water supply by identifying spectral and spatial information. A study was put in place in a Vitis vinifera L. cv. Cabernet-Sauvignon vineyard in the San Joaquin Valley, CA, USA, where a variable rate automated irrigation system was installed to irrigate vines with twelve different water regimes in four randomized replicates, totaling 48 experimental zones. The purpose of this experimental design was to create variability in grapevine water status, in order to produce a robust dataset for modeling purposes. Throughout the growing season, spectral data within these zones was gathered using a Near InfraRed (NIR) - Short Wavelength Infrared (SWIR) hyperspectral camera (900 to 1700 nm) mounted on an Unmanned Aircraft Vehicle (UAV). Given the high water-absorption in this spectral domain, this sensor was deployed to assess grapevine stem water potential, Ψstem, a standard reference for water status assessment in plants, from pure grapevine pixels in hyperspectral images. The Ψstem was acquired simultaneously in the field from bunch closure to harvest and modeled via machine-learning methods using the remotely sensed NIR-SWIR data as predictors in regression and classification modes (classes consisted of physiologically different water stress levels). Hyperspectral images were converted to bottom of atmosphere reflectance using standard panels on the ground and through the Quick Atmospheric Correction Method (QUAC) and the results were compared. The best models used data obtained with standard panels on the ground and allowed predicting Ψstem values with an R2 of 0.54 and an RMSE of 0.11 MPa as estimated in cross-validation, and the best classification reached an accuracy of 74%. This project aims to develop new methods for precisely monitoring and managing irrigation in vineyards while providing useful information about plant physiology response to deficit irrigation. [ABSTRACT FROM AUTHOR]

The Coastal Ice Ocean Prediction System for the East Coast of Canada (CIOPS-E) was developed and implemented operationally at Environment and Climate Change Canada (ECCC) to support a variety of critical marine applications. These include support for ice services, search and rescue, environmental emergency response and maritime safety. CIOPS-E uses a 1/36° horizontal grid (~ 2 km) to simulate sea ice and ocean conditions over the northwest Atlantic Ocean and the Gulf of St. Lawrence (GSL). Forcing at lateral open boundaries is taken from ECCC's data assimilative Regional Ice-Ocean Prediction System (RIOPS). A spectral nudging method is applied offshore to keep mesoscale features consistent with RIOPS. Over the continental shelf and GSL, the CIOPS-E solution is free to evolve according to the model dynamics. Overall, CIOPS-E significantly improves the representation of tidal and sub-tidal water levels compared to ECCC's lower resolution systems: RIOPS (~ 6 km) and the Regional Marine Prediction System – GSL (RMPS-GSL, 5 km). Improvements in the GSL are due to the higher resolution and a better representation of bathymetry, boundary forcing and dynamics in the upper St. Lawrence Estuary. Sea surface temperatures show persistent summertime cold bias, larger in CIOPS-E than in RIOPS, as the latter is constrained by observations. The seasonal cycle of sea ice extent and volume, unconstrained in CIOPS-E, compares well with observational estimates, RIOPS and RMPS-GSL. A greater number of fine-scale features are found in CIOPS-E with narrow leads and more intense ice convergence zones, compared to both RIOPS and RMPS-GSL. [ABSTRACT FROM AUTHOR]

Altitude changes induce climate-driven alterations in plants and soils over geographic distances, which provides a framework for predicting the pattern and mechanism of soil microbial evolution in global change scenarios. This study aimed to identify the respective contributions of plant diversity and edaphic variables to soil fungal assemblages across three altitude transects in southwestern China. Illumina sequencing technology was applied to determine the altitude-induced changes in fungal composition and diversity. We found that the responses of soil fungal compositions to altitude changes varied with taxa. A significant decrease in abundance was observed for the dominant Ascomycota from low to high altitude, following the decreased plant diversity. In contrast, that of subdominant Basidiomycota was rich at medium altitude, Mortierellomycota had rich abundances at high altitude in accordance with the increased water and nutrient levels in soil. At the class level, Sordariomycetes abundance from low to high altitude showed a significant decrease, but Agaricomycetes abundance was rich at medium altitude, while Eurotiomycetes and Tremellomycetes had rich abundances at high altitude. At the genus level, Isaria was rich at medium altitude, and Mortierella and Penicillium had rich abundances at high altitude. In particular, the abundance of Mortierella (Mortierellomycota) was richer than the Trechispora (Basidiomycota) at the high altitude. Furthermore, soil fungal diversity decreased on average by 24.62% with increasing altitude, for which was plant diversity primarily contributed by plant diversity (9.56–15.42%). However, the fungi compositions at the phylum (8.63–14.97%), class (7.71–8.97%), and genus (9.29–11.86%) levels were mainly affected by soil properties. At the phylum level, total nitrogen, available nitrogen, soil organic matter, pH, soil temperature, and soil water content contributed to the variations in fungal composition. Our results suggested that altitude-induced changes of plant and edaphic properties had differential contribution to shifts in the soil fungal assemblage, probably associated with their roles in meeting the metabolic and habitat demand of fungi. [ABSTRACT FROM AUTHOR]

Understanding the complex relationships between benthic algal communities and environmental factors is crucial for ecosystem management and conservation. In this study, we investigated benthic algal communities in the upper Red River Basin in China. We collected data on land use, topography and other factors at the watershed scales to gain a comprehensive understanding in the upper Red River Basin in China. Partial canonical correspondence analysis, partial redundancy analysis and variance partitioning analysis methods were used to assess the effects of watershed and local environmental factors on benthic algal communities and their variation. The percentage of landscape that was forest (F-PL), the percentage of landscape that was cropland (C-PL), the percentage of landscape that was water (W-PL), elevation, slope, pH and water level fluctuation (WF) were identified as significant factors affecting the distribution of benthic algal communities. The diversity of benthic algal communities were greatly affected by environmental factors as F-PL, W-PL, precipitation (Prcp), slope, permanganate index (CODMn) and index of substrate (IOS). Slope, F-PL and Prcp showed a positive correlation with species evenness and a negative correlation with community density. The characteristics of functional groups of benthic algae were also shown to be strongly influenced by C-PL and IOS. According to the variance decomposition (VPA) results, it can be seen that, although the explanatory power of individual local and watershed environmental factors was roughly similar, their joint explanatory power was relatively low. Therefore, the influence of watershed environmental factors on benthic algal communities should not be overlooked. [ABSTRACT FROM AUTHOR]

Alpine landscapes are notable regarding their sensitivity to environmental change. Surface waters are especially sensitive as many are influenced by glacial meltwaters that are diminishing with the retreat of glaciers worldwide. The Macun Lakes region, Swiss National Park, is an alpine cirque landscape housing a number of lakes interconnected by streams. The area has been non-glaciated for decades, although rock glaciers are still present in the south basin. Surface waters, 10 stream sites in the present study, have been monitored in mid-summer since the year 2001 for physico-chemistry, periphyton and macroinvertebrates (including 74 species of chironomids). Water physico-chemistry revealed that the two main basins in the catchment differed, reflecting the inputs of rock glacier waters in the south basin. However, trends suggest that waters are becoming more similar as rock glacier inputs diminish over time along with a general decrease in nitrogen levels in all waters. Periphyton biomass showed some spatial differences among sites and a general decrease after 2010. Macroinvertebrate assemblages, including chironomids, clearly differed among basins and spatially along the stream network in each basin. Notably, no significant temporal trend was observed in the long-term data for macroinvertebrates, including chironomids, at the monitored sites. The results suggest that lotic macroinvertebrates may be buffered by the interconnectedness of streams and lakes in the landscape, which mitigates major response patterns of running waters to environmental change. [ABSTRACT FROM AUTHOR]

Introducing a novel meta-heuristic optimization algorithm, the Flood Algorithm (FLA) draws inspiration from the intricate movement and flow patterns of water masses during flooding events in river basins. FLA mathematically models key phenomena such as the movement of water toward slopes, flow rates over time, soil permeability effects, and periodic increases and decreases in water levels from precipitation and losses. Leveraging these models, the algorithm guides the movement and evolution of a population of potential solutions toward enhanced optimality. The algorithm endeavors to establish an appropriate correlation between the fundamental aspects of natural flood events and the optimization process. Its formulation and working mechanism are described in detail. It operates in two main phases—a regular movement phase, where the population moves naturally toward current best solutions, and a flooding phase, which introduces random disturbances to increase diversity. New solutions are periodically introduced while weaker ones are removed, mirroring the natural cycles of water levels. FLA's effectiveness is demonstrated through its application on well-known benchmark optimization problems and engineering design problems. Extensive comparisons have been carried out on CEC2005 functions using 16 algorithms in both basic and enhanced modes, as well as on CEC2014 functions with dimensions 30, 50, and 100 using a total of 20 other algorithms. These rigorous studies unequivocally confirm the robustness and strength of the proposed algorithm. Furthermore, the algorithm's performance on 12 constrained engineering problems demonstrates its ability to tackle real-world challenges. The FLA's source code is publicly available at https://www.optim-app.com/projects/fla. [ABSTRACT FROM AUTHOR]

The performance of gravity recovery and climate experiment (GRACE) and GRACE-Follow On (GRACE-FO) satellites in estimating groundwater level (GWL) changes on a local scale is a challenging issue. Then, this study aims to investigate the performance of GRACE and GRACE-FO in monitoring GWL changes on a local scale compared to observations at groundwater wells and the results of groundwater modeling. The study utilized hundreds of groundwater observational data points and 180 satellite data from 2002 to 2020 in five Iranian provinces. The data from satellites GRACE and GRACE-FO were modified by subtracting hydrological parameters outputs of the global land data assimilation system (GLDAS) from the satellites' estimations. The significant trends in GWL changes were studied by Sen's slope and Mann–Kendall, which represented a significant declining trend in GWL in all studied provinces. Applying 1–2 month time lags to the observational data improved the correlation coefficients between satellite estimations and the observations at groundwater wells. The best correlation coefficients between observational GWL changes and GRACE estimations in Fars, Khorasan Razavi, Sistan and Baluchistan, East Azerbaijan, and Golestan provinces were calculated as 0.53, 0.42, 0.4, 0.51, and 0.36. Those values for GRACE-FO were calculated as 0.95, 0.67, 0.72, 0.78, and 0.3, respectively, which proved the better performance of GRACE-FO compared to GRACE. Meanwhile, the GWL changes estimated from GRACE-FO were compared to the results of groundwater modeling, which was performed by using MODFLOW via the GMS10.4 interface in Azarshahr aquifer located at East Azarbaijan revealed a satisfactory agreement. [ABSTRACT FROM AUTHOR]

The analysis of the influence of human activities and climate change on groundwater is an important basis for formulating groundwater management policies. However, the relationship between climate change, human activities and groundwater system is complex, and the research on the response of groundwater to changing environment is in the initial stage. In this paper, the interactions between groundwater water cycle and climate change and human activities are analyzed, based on climate change data and hydrogeological information from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). The MODFLOW model was used to develop a numerical model of shallow groundwater movement in Zhongmu County, Henan province, and to predict the response of groundwater levels to climate change and human activities in three cases from 2016 to 2050. The results show that under the current scenario, the groundwater level will decrease at an average annual rate of 4.24 cm/A from 2016 to 2050. Under the climate change scenario, the precipitation increased by an average of 5.01%, the annual evaporation increased by an average of 17.84% and the annual temperature increased by an average of 1.29 °C from 2016 to 2050 under the three emission cases of RCP2.6, RCP4.5 and RCP8.5, under the climate change–autonomous human activities scenario, when water conservation and South–North Water Transfer Project water supply are implemented simultaneously, the water table will decrease by an average of 5.58 CMA per year under the direct impact scenario and by an average of 4.44 CMA per year under the indirect impact scenario, the water table dropped by 3.21 cm/A. The changing environment will have an important effect on groundwater circulation, and appropriate measures must be taken to deal with the continuous decline of groundwater level. [ABSTRACT FROM AUTHOR]

Since its impoundment in 2003, more than 5,000 landslides have been identified in the Three Gorges Reservoir, and more than 600 slides have apparent activity, which causes significant damage and threats to residents and water infrastructure. Understanding the kinematic behavior and velocity characteristics, mechanisms, trigger factors, and dynamic models of landslides contribute to their instability evaluation and prevention. However, landslide stability analysis is challenging because of complex influencing factors and unclear structural features. The primary objectives of this study were to investigate the kinematic, mechanical, and dynamic characteristics of the Chuwangjing landslide and to identify the trigger factors. We applied multi-resource remote sensing techniques, including satellite Tri-Stereo, unmanned aerial vehicle (UAV) surveys, light detection and ranging (LiDAR) point clouds, and interferometric synthetic aperture radar (InSAR) techniques, to analyze morphological, kinematic, and dynamic features, combined with meteorological and hydrological data. The increased velocity during periods of intense rainfall and prolonged water function, particularly during periodic rapid drawdown periods at high water levels, indicates that deformation is primarily governed by these two factors. The composition of cracks and scrapes detected by LiDAR and satellite Tri-Stereo technology and the deformation distribution on the slope indicated a retrogressive model. We analyzed the landslide's kinematic model and dynamic conditions by considering characteristics such as step-like deformation, influencing factors, and geological composition. Furthermore, by comparing the application effects of multi-remote sensing technology combinations in landslide analysis, this study proved the usefulness of an integrated method for landslide analysis and trending evaluation. [ABSTRACT FROM AUTHOR]

Long-term variations of ecological and hydrological parameters governing the natural reproduction of sturgeon are analyzed. It was found that long-term variations of hydrological characteristics are taking place against the background of cyclic development of phases with different water abundance and transformation of the annual redistribution of runoff. The contribution of long-term runoff regulation by the Iriklinskoe Reservoir to water regime variations in the Ural River is considered for its middle reaches. A conclusion is made regarding the need to restore the sturgeon herd in the Northern Caspian Sea. Recommendations are made regarding the priority measures for preserving the potential of sturgeon spawning grounds in the middle reaches of the Ural River. [ABSTRACT FROM AUTHOR]

The data of long-term Roshydromet hydrochemical monitoring were used to establish space and time regularities in water quality variations in the Ural River. Trends in variations in the concentrations of various pollutants in river water over the period 1986–2021 were identified. The effect of the interannual and intra-annual dynamics of water flow on water quality was evaluated. It has been shown that there is no strict dependence of river water pollution on water abundance or the season of the year in the Ural River basin. It has been found that the level of river water pollution in both high-water and low-water periods shows a significant influence of point and diffuse pollution sources in different parts of the river network. [ABSTRACT FROM AUTHOR]

A numerical hydrodynamic model was constructed for the segment of the Ural River from the Iriklinskoe Reservoir (inclusive) to a site 30 km downstream of the Sakmara River inflow; therefore, the total length of the model reach was >700 km. To reduce the time of model development and to accelerate the calibration and variant calculations, the segment was divided into three successive parts of the channel, interacting through consistent boundary conditions. The simulation is carried out with the use of a domestic high-accuracy software package STREAM 2D CUDA, taking into account abrupt changes in bottom elevation and multifractional soil composition. The model was calibrated for constant water discharges. Calculations were carried out for a spring flood with an exceedance probability of 1% and a breakthrough wave of the Iriklinskii Hydropower System under two scenarios. Maximal water levels, depths, and inundation zones were obtained. An effect of a many-time increase in the steepness of the leading front of the flood wave within the domain was revealed. [ABSTRACT FROM AUTHOR]

Based on stationary and expeditionary hydrological data and information about the water management complex and volumes of water use, we have calculated for the first time the minimum permissible, average, and optimal hydrographs (in monthly increments) of the influx of Ural waters from Russia to the West Kazakhstan and Atyrau regions, which would not limit the functioning of the main participants of the Kazakhstan water management complex, would not deteriorate the quality of life of the population and existence conditions for aquatic and near-water biocenoses, and would preserve the river as a hydrographic object. The resulting hydrographs summarize (1) the values of current and future water consumption in the cities of Uralsk and Atyrau and numerous rural settlements, as well as water intake by irrigation and water supply canals, including the Kushum Canal; (2) the needs of river navigation for controlling depths and continuous navigation from May to October; (3) the environmental flow necessary for the reproduction of sturgeon fish species and the preservation of the bioproductivity and biodiversity of floodplain ecosystems. The latter element required nonstandard solutions, including those based on the existing domestic approaches to determining critical and optimal values (with respect to floodplain–channel ecosystems) values. Another and completely new result of this research is analysis of the long-term dynamics of maximum and minimum levels in the lower reaches of the Ural River and the frequency, duration, and depth of floodplain flooding. [ABSTRACT FROM AUTHOR]

The country's first tubular microfiltration membranes for water purification from various contaminants, made from an alternative natural material—wood,—was developed at the Dumansky Institute of Colloid and Water Chemistry of the National Academy of Sciences of Ukraine. The proposed procedure cuts significantly the costs of manufacturing membranes. They studied the main patterns of the defluoridation process of water using these lignocellulosic (wooden) membranes, which were modified with a dynamic layer of hydrophilic A-300 aerosil. The modification of the lignocellulosic membranes involved the preliminary formation of an additional retentive layer on their surface, due to the steric mechanism, in the form of a dynamic membrane. The research demonstrated the high efficiency of the water defluoridation process using a dynamic membrane made of SiO2 particles, which retained fluoride ions (F–) ions due to the electrostatic mechanism of their interaction. Specific conditions for forming the dynamic membrane included concentrations of modifying and membrane-supporting aerosil additives at 500 and 100 mg/dm3, respectively, with an operating pressure of 1.0 MPa and a formation duration of 120 min. The concentration of suspended SiO2 particles in the permeate (turbidity) did not exceed the maximum permissible concentration (0.3 mg/dm3) in water. The modified lignocellulosic membrane could decrease the fluoride concentration in water to the permissible level for drinking water (0.7–1.5 mg/dm3) from an initial concentration of up to 7.5 mg/dm3 and a neutral pH at an operating pressure of 1.0 MPa. The membrane's specific productivity was 0.024 m3/(m2 h), due to significant pore blockage by SiO2 particles. [ABSTRACT FROM AUTHOR]

The directed energy deposition arc (DED-Arc) has been extensively used to develop metallic parts with varying complexities. A major challenge for austenitic stainless steels is managing heat accumulation due to their low thermal conductivity. This study aimed to characterize the microstructure and mechanical properties of AISI 316L preforms manufactured by additive manufacturing (AM) under different deposition paths and cooling conditions. Samples underwent macro- and microstructural analyses, and tensile and hardness tests to evaluate their mechanical behavior. Additionally, the effect of active cooling using near immersion active cooling (NIAC) in water on the microstructure was assessed by examining the secondary interdendritic spacing and ferritic phase fraction. The NIAC technique has shown potential for enhancing productivity by producing preforms with more uniform thickness and consistent solidification/cooling conditions throughout the multiple layers. This approach eliminated deposition idle time, leading to a productivity increase of up to 108%. Microstructures obtained with active cooling were more refined than those resulting from natural cooling, evidenced by a reduction in secondary interdendritic spacing and an increased fraction of delta ferrite. These microstructural changes resulted in higher hardness and mechanical strength in the material processed with the NIAC technique. However, difficulties in precisely controlling the water level resulted in increased apparent porosity when using the NIAC technique. [ABSTRACT FROM AUTHOR]

Landslide is a disastrous geological hazard in the Three Gorges Reservoir (TGR) area of China. In this study, random limit equilibrium analysis is conducted to assess a layered slope stability influenced by multi-factors in spatially variable soils, where the effects of earthquake, reservoir water level drawdown and rainfall are investigated, and possible failure modes and failure paths are identified. Furthermore, some sensitive analysis is performed to investigate the effects of the spatial variability of soil properties, water level drawdown velocity, rainfall intensity and pattern. Results show that the layered slope under complex working conditions exhibits the shallow failure modes, and the sliding surfaces are mainly located at the interface between soil layers. Meanwhile, the shear strength parameters in the shallow depth plays a crucial role in the layered slope failure probability. The earthquake has a prominent effect on slope stability, followed by reservoir water level drawdown and rainfall infiltration. The probability of failure under the combined effects of earthquake and other factors (e.g., 23.5%, 31.4% and 44.6%) is significantly higher than under the combined effects of rainfall and water level drawdown (e.g., 15.9%). Moreover, it can be found that the spatial variability of soil properties, water level drawdown velocity, rainfall intensity and pattern have essential impacts on the slope failure probability. [ABSTRACT FROM AUTHOR]

In the Casablanca-Mohammedia corridor (Morocco), flooding episodes have happened frequently over the past 20 years, damaging coastal settlements through overtopping and overflowing processes. In this context, a realistic assessment of the flood risk on this coastline is required. For this, the marine water level variations were computed by combining the involved variables (astronomical tide, storm surge, wave run-up, and sea level rise) during energetic events. They were compared with the seafront altitude to delineate the maximum spatial extent of flooded areas for the current and future (2100) time horizons. These variables were obtained through numerical and empirical modeling using topobathymetry, tide gauge, wind, and reanalysis data for wave and atmospheric pressure. Statistical methods were used to determine trends and distributions, including linear regression and the GEV model. Our approach was validated by comparing the estimated results of the total water level with the observations made in situ during previous events. Results show that flooding occurs mainly at high tides. The run-up is the largest contributor to total water level during energetic events (45–60% in structure defense areas against ~ 35% in natural areas). Currently, the floodable area for all of Casablanca-Mohammedia's coastline (109 km2) is estimated to be ~ 23.5 km2, of which ~ 13.9 km2 is urban. This area would grow by 10.87% and 20.9% by 2100, respectively. The most vulnerable zones are Mohammedia, Ain Sbâa, and Merzeg quarters, as well as Tamaris beaches. The touristic quarters of Ain Diab and the promenades on either side of the Hassan II Mosque are also vulnerable and can be dangerous for pedestrians. This study is crowned by the proposal of numerous necessary protection and adaptation measures, considering the specificities of the sections characterizing this coastline. [ABSTRACT FROM AUTHOR]

Flood hazard assessment is essential for climate-change management planning. River flow frequency and size affect basin flood regime. This study evaluates the flood hazard of delta region of a large Indian river basin, the Mahanadi River basin, for possible future flood scenarios. Based on flood severity and frequency, basin flood regime change is examined. Four different flood scenarios are considered such as reference scenario (1955–2001), present scenario (1981–2011) and two possible future scenarios, by modifying the peak flood series with percentage change approach. Flood hazard was assessed based on the results of hydrodynamic modelling. Based on flood estimations at head of delta region, flood intensity is increasing in delta region of Mahanadi basin. Floods of higher return period (61 years) in the reference scenario happens to be a lower return period flood (11 years) in possible future scenario. In recent years, high floods have maximum water level profiles equal to or higher than 5- and 10-year return period floods of hypothetical future flood scenarios. Flood inundation evaluation under multiple land-uses shows that economically significant land-uses including farmland, built-up land, and aquaculture are more vulnerable to future floods. In the Mahanadi delta, 'high' and 'very high' flood depth coverage increases and 'low' depth diminishes. Inundation area for 'very high' flood depth is increasing, indicating agricultural vulnerability in the delta region. [ABSTRACT FROM AUTHOR]

This paper examines the problem of unobserved heterogeneity in urban water demand. It uses a panel quantile regression (QR) approach to focus on segments of consumers with different levels of water consumption. This estimation strategy is applied to a rich set of panel microdata capturing the consumption of water for 4,023 households in Valencia (Spain) between the years 2009 and 2011. To capture heterogeneity in a city's residential household water consumption, a QR approach is applied to the specified water demand model, enabling analysis for different quantiles (levels) of consumption. The QR shows the behaviour of the parameters for different consumption levels. It enables differentiation of consumer reactions to different independent variables at each quantile of the distribution of the dependent variable. The results provide strong evidence of unobserved heterogeneity at different levels. This approach is useful in that it can lead to better-informed tariff design by providing an understanding of heterogeneity in price elasticities. [ABSTRACT FROM AUTHOR]

Traditional reservoir operations often take power production as the main purpose. However, blindly maximizing power production will prompt the reservoirs to work continuously at high water levels, leading to lower water release and possible damage to the river ecosystem. In this paper, a multi-objective optimal operation model was established for a cascade reservoir system, with the goals of maximizing power production and ecological benefit. The ecological benefit was defined based on a suitable interval of ecological flow, which was calculated by the Tennant and flow duration curve methods. To efficiently solve the model, a multi-objective butterfly optimization algorithm was proposed by coupling the improved initial population strategy, dynamic switching probability strategy, archive elite solution-guided evolution, and polynomial mutation strategy. This algorithm was compared with three popular multi-objective optimization algorithms on benchmark functions and a cascade reservoir operation problem in the lower reaches of the Yalong River. Results showed that the proposed algorithm achieved the maximum hydropower production, with 82.5, 76.4 and 64.2 billion kW‧h in the wet, normal and dry years. It also obtained the highest ecological benefit values, which were 0.76, 0.80 and 0.86 in the wet, normal and dry years, respectively. The proposed algorithm has the potential to solve multi-objective optimization problems. Under different inflow scenarios, a certain competitive relationship between targets was witnessed. As the decrease of inflow, the competition tended to intensify. [ABSTRACT FROM AUTHOR]

Water-rich open-pit mines can have problems with large water inflows, slope reinforcement difficulties, and hazardous mining risks. The construction of a water cut-off curtain to control groundwater in the loose layer of an open-pit mine can effectively reduce the amount of water that must be pumped and eliminate the problem of flooding in the pit. However, the rise of the water level outside the curtain and changes in the geotechnical properties of the slope's material will affect the stability and safety of the pit's slope. A computational model was constructed and limit equilibrium and numerical simulation methods were used to determine the influence of a water cut-off curtain on the stability of the slope. Results show that with the the water cut-off curtain, the water level outside of the cut-off curtain in the loose layer of the open-pit mine continues to rise and the hydrostatic pressure and horizontal thrust of the slope body increases. As a result, the sliding force of the slope increases and the resisting force decreases, ultimately lessening the slope- stability coefficient (factor of safety) of the open pit. If the construction position of the curtain is moved outward, the stability coefficient of the slope will increase, assuming that the water level outside the curtain remains unchanged. Conversely, if the position of the curtain is moved toward the pit, the stability coefficient of the slope will decrease. The maximum shear stress on the slope increases as the water level outside the water curtain rises. The maximum shear stress is mainly concentrated at the toe of the slope of the first bench below the surface and at the interface between the curtain and the bottom of the loose material. If designed properly, the water curtain can control the water table in the slope's material, maintaining the stability of the slope. [ABSTRACT FROM AUTHOR]

This study exploits a convenient, stable, accurate estimation of the spatio-temporal distribution of ocean wave heights by stereo observation using a single unmanned aerial vehicle (UAV) with two independent optical cameras fixed to it. To accurately estimate the spatio-temporal distribution of water levels, the photographing rate of each camera is set to 240 frames per second (fps), and luminescence captured during flight is used to realize the time synchronization within ~ 4 ms between the cameras. Based on the setting of the UAV and the cameras, we carry out aerial stereo observation of the spatio-temporal distribution of nearshore water levels. The estimated water levels showed good agreement with ground truth observation. We examine the dependence of the estimation accuracy on the photographing time difference between the cameras. Simulations were conducted to increase the time difference by decreasing the photographing rate. The estimation based on low photographing rates (e.g., 60 and 30 fps) likely failed when breaking wave crests prevailed in the optical images. This indicates that strict time synchronization (e.g., ~ 4 ms) between the cameras is an important, necessary condition to accomplish accurate stereo observation of ocean waves including wave breaking. [ABSTRACT FROM AUTHOR]

Biological data collection often overlooks short-term environmental variations, potentially leading to under- or over-estimation of species abundance and ineffective conservation actions. This study investigated the complex relationship between oceanic and meteorological processes and the short-term abundance patterns of two economically important fish species in Bahía Santa Elena, a tropical bay on the north Pacific coast of Costa Rica. Using two months of continuous acoustic telemetry data from 14 Colorado (Lutjanus colorado) and 16 Pacific dog (Lutjanus novemfasciatus) snappers, we investigated temporal and spatial changes in their relative abundance patterns. A wavelet analysis revealed dominant diurnal and semidiurnal frequencies in both species. The observed semi-diurnal and diurnal periodicity in fish abundance was correlated with water level and sunlight, particularly near the mangrove in the inner bay, suggesting that both species may be using these habitats for food and shelter during periods of high tide and at night. Understanding how oceanic and meteorological conditions influence the dynamics of marine organisms in coastal environments, particularly those that are often exploited by fisheries is crucial for developing effective management and conservation approaches. [ABSTRACT FROM AUTHOR]

Reservoir impoundment and water level fluctuations often trigger landslides and their secondary disasters, such as potential impulse waves, posing a serious threat to the safety of people along the reservoir and dam areas, causing economic losses and even catastrophic consequences. This study delves into a comprehensive field investigation and monitoring of the engineering geological conditions and deformation mechanisms of the Mogu rock landslide. The impoundment is identified as the primary factor inducing slope deformation, with the cumulative displacement of the sliding body showing no signs of convergence, indicating potential instability. By coupling the elasto-visco-plasticity model and the RNG turbulence model in FLOW-3D, an actual impulse wave disaster near the Lianghekou reservoir dam area is replicated to validate the reliability of the numerical method. Building upon this, a three-dimensional model is established to calculate potential impulse waves generated by the Mogu rock landslide, and the risk to the dam is evaluated. Under different water level conditions, the simulated run-ups of impulse waves do not surpass the dam elevation, demonstrating a satisfactory safety margin. Given the inherent danger of landslide-induced wave disasters, continuous attention is warranted, and preventive measures and suggestions are proposed to address these concerns. Additionally, the study explores the contributions of water level fluctuations to the primary tsunami amplitude, the maximum run-up on the opposite bank and the dam, and the attenuation rate of the tsunami amplitude along the river channel. The results provide significant reference values for the early warning and prevention of comparable reservoir landslides and potential landslide-induced waves worldwide. [ABSTRACT FROM AUTHOR]

This study presents a long-term reactivation monitoring approach using multi-source satellite SAR and optical data. It also explores the relationship between landslide deformations and hydrological factors for reactivation assessment and management. More specifically, this approach is applied to investigate the long-term reactivation evolution of the Huangtupo landslide under the local engineering work conducted in four different phases. The spatial–temporal evolutions of the Huangtupo landslide were mapped by the multi-temporal optical images from the PlanetScope satellite, revealing that the building areas were gradually replaced by the vegetation covers. The long-term reactivated deformations were explored by the multi-source satellite SAR data from ALOS-2 and Sentinel-1A/B based on time-series InSAR analysis. Cross-validation between the multi-source InSAR results showed that the ALOS-2 and Sentinel-1A/B measurements are highly correlated. Long-term spatial–temporal deformations were investigated using the Sentinel-1A/B Track 11 data between 2016 and 2022. A long stack of SAR datasets was divided into four consecutive branches based on the local engineering work plan. A general slowing down deformation trend can be observed from the time series analysis, indicating the effectiveness of local measures for maintaining the slope stability. Most importantly, seasonal fluctuations caused by changes in rainfall and Three Gorges Reservoir (TGR) water level can be clearly observed from the time series evolutions of deformation during each phase. Through the gray correlation analysis and cross wavelet analysis, it is found that the lower part of the Huangtupo landslide shows a higher correlation with the TGR water level changes, while the upper slope mainly responds to rainfall. Importantly, it is found that the lowest common power was observed at P4 since August, 2020, suggesting that the upper part of the slope has been changed to be more rainfall erosion resistant due to the effort of the drainage system and vegetation restoration from the ecological restoration project. [ABSTRACT FROM AUTHOR]

The middle and lower reaches of the Yangtze River, a primary region for freshwater lakes in China, have undergone significant transformations throughout the Holocene. These changes, driven by factors such as sea-level rise, climate change, and human activities, have led to the progressive elevation of water levels in this area. As a result, a floodplain has emerged, characterized by the formation of numerous shallow lakes along the river course. However, the pattern of water-level changes in the main channel of the Yangtze River during the Holocene remains unclear. This gap in knowledge poses challenges for understanding sediment transport dynamics, the interactions between the river and its adjacent lakes, and the prevention and control of flood disasters in the Yangtze River basin. To shed light on these issues, our study compiled data on the surface elevation and water depth of 81 lakes in the mid-lower reaches of the Yangtze River basin. Additionally, we analyzed historical water-level records from the 1900s to the 1970s at eight gauging stations from Shashi to Jiangyin along the river's main stream. Our findings reveal that, particularly along the Jingjiang section, the basal elevation of most lakes is lower than the Yangtze River's water level during the dry season. Conversely, the water level of the main stream exceeds that of both the floodplain and the lakes enclosed by the Jingjiang embankment. In the tidal reach, especially within the Taihu Lake basin, the basal elevation of lakes typically falls below sea level. Meanwhile, lakes located along the section from Chenglingji to Wuhu exhibit basal elevations that correspond with the Yangtze River's annual average and dry season water levels. Given the widespread presence of lakes along the middle and lower reaches of the Yangtze River, our study introduces a new proxy for reconstructing the mean water level of the mid-lower Yangtze River in the Holocene. By analyzing sediments from Nanyi Lake and Chenyao Lake in the lower Yangtze River, we attempted to reconstruct the water level of the Yangtze River's main channel since 8 ka BP. [ABSTRACT FROM AUTHOR]

Near coasts and shelves are strongly affected by the hydrodynamic forces and involves important information about the long term and permanent changes. Understanding the past dynamic transformations of shelves and near coasts can shed the future projections about effects of climate changes. High-resolution seismic and multibeam bathymetry data shed light on sedimentation since the last sea level lowstand in the Bandırma Bay, southern shelf area of the Marmara Sea. Five different seismic units were identified from the bottom upward based on seismic stratigraphic analysis, which are bounded by the reflection surfaces. Differential hydrological and depositional processes in the bay are shown by the definition and mapping of these unique seismic units and surfaces in the shallow sedimentary record: The water level in the basin crossed the threshold between the two basins, and advancing flows began from the north to the western basin. The basin continued to fill with water, and progressive depositions were interrupted with the onlaps of U3–4. The water level rose above the threshold in both basins, resulting in the two lakes becoming a single lake and the creation of marine conditions. The initial deposition in the eastern basin was fluvial, deposited in the form of regressive systems tracts. The overall morphology and stratigraphic settings observed in Bandırma Bay have nearly the same characteristics as those observed in the Sea of Marmara (like northern and western Marmara shelf, Gemlik Bay, Büyükçekmece Bay etc.) oceanography, implying that similar hydrodynamic conditions and erosional and depositional processes are controlled mainly by sea level changes controlled by climate changes related to morphological properties. [ABSTRACT FROM AUTHOR]

Salt marshes act as natural barriers that reduce wave energy during storm events and help protect coastal communities located in low-lying areas. This ecosystem can be an important asset for climate adaptation due to its particular capability of vertically accrete to adjust to long-term changes in water levels. Therefore, understanding marsh protection benefits thresholds in the face of sea-level rise (SLR) is important for planning future climate adaptation. In this context, the main goal of this manuscript is to examine how the storm protection benefits provided by salt marshes might evolve under SLR projections with different probability levels and emission pathways. In this study, a modeling framework that employs marsh migration predictions from the Sea Level Affecting Marshes Model (SLAMM) as parameterization into a hydrodynamic and wave model (ADCIRC + SWAN) was utilized to explicitly represent wave attenuation by vegetation under storm surge conditions. SLAMM predictions indicate that the SLR scenario, a combination of probability level and emission pathways, plays a substantial role in determining future marsh migration or marsh area loss. For example, results based on the 50% probability, stabilized emissions scenario show an increase of 45% in the marsh area on Maryland's Lower Eastern Shore by 2100, whereas Dorchester County alone could experience a 75% reduction in total salt marsh areas by 2100 under the 1% probability, growing emissions scenario. ADCIRC + SWAN results using SLAMM land cover and elevation outputs indicate that distinct temporal thresholds emerge where marsh extent sharply decreases and wave heights increase, especially after 2050, and exacerbates further after 2080. These findings can be utilized for guiding environmental policies and to aid informed decisions and actions in response to SLR-driven environmental changes. [ABSTRACT FROM AUTHOR]

Groundwater accounting is becoming increasingly important for sustainable societal development. To gain insights into the long-term spatiotemporal changes from 1992 to 2015 regarding groundwater resources in Kumamoto, southern Japan, we analyzed climatological time series, discharge from the groundwater-fed lake (Ezu Lake), and groundwater levels from 94 wells. To explicitly detect temporal changes in these variables and assess potential drivers of change, we used three different trend analyses: the Mann-Kendall Test (MKT), Seasonal Mann-Kendall Test (SMKT), and Innovative Trend Analysis (ITA). Our results revealed a consistently increasing trend in monthly mean temperature, monthly total precipitation, and maximum hourly rainfall. However, a decreasing trend was detected for the discharge rate from the Ezu Lake from 1992 to 2015. Among the 94 investigated groundwater wells, 64 wells showed an upward trend (p ≤ 0.05), while 23 wells showed a downward trend (p ≤ 0.05) for groundwater level. The observed decline in groundwater level is related to the decline in Ezu Lake discharge. However, the increase for the majority of groundwater wells is related to the increased precipitation and applied artificial groundwater recharge as well as a decrease in the groundwater abstraction rate. The ITA outperformed both SMKT and MKT, particularly in detecting minor variations in hydrological time-series data. The results and approach presented in this study can provide a scientific basis for improve groundwater accounting and water resources management in Kumamoto area and other regions with similar climate and socioeconomic conditions. [ABSTRACT FROM AUTHOR]

The generation of streamflow is linked with different factors such as water level, rainfall intensity, meteorological variables, and many more. In this study, we have developed a new hybrid approach (named LASSO-HF-SAA) by integrating the least absolute shrinkage and selection operator (LASSO) and Hampel filter (HF) with three data-driven models i.e. support vector machine (SVM), artificial neural network (ANN) and autoregressive distributed lag (ARDL). Firstly, LASSO selects meteorological variables important in daily streamflow prediction. Next, the HF detects and correct outliers in the variables to handle the randomness and noise of data. Thirdly, the HF-corrected data is fed to SVM, ANN, and ARDL models to obtain the predictions of the proposed LASSO-HF-SVM, LASSO-HF-ANN, and LASSO-HF-ARDL models. The performance of these models is checked using performance indices and the Diebold-Mariano (DM) test. The proposed hybrid approach is illustrated on the streamflow data of the Kabul River (Nowshera station) of Pakistan. Based on Nash-Sutcliffe efficiency (NSE), it is revealed that the prediction accuracy of the LASSO-HF-SVM hybrid model (NSE = 0.52) is better than SVM (NSE = 0.43), HF-SVM (NSE = 0.49) and LASSO-SVM (NSE = 0.47) models in testing phase. Similar findings are for the proposed LASSO-HF-ARDL and LASSO-HF-ANN hybrid models. Overall, the suggested LASSO-HF-ARDL hybrid model has shown winning performance compared to all models in the study. The root mean squared error (RMSE) and NSE of the proposed LASSO-HF-ARDL model is 443.5m3/s and 0.68 on the test data. The DM test confirms that the prediction accuracy of the proposed hybrid models is better than their respective single, HF-based, and LASSO-based models versions of SVM, ANN, and ARDL models respectively. [ABSTRACT FROM AUTHOR]

The optimization of the initial design or the development of repair and replacement strategies for pipes within the water distribution network (WDN) during its operational phase relies on the utilization of crisp values. Some input variables such as nodes demand, pipe's roughness coefficient and reservoir water level have the uncertain nature. Alterations in input parameter values during the operational period, attributed to uncertainty, induce shifts in the behavior and performance of the WDN compared to scenarios with crisp input parameters. Recognizing and analyzing these variations are imperative for making informed decisions to address their ramifications and mitigate problems within the water distribution network. This research analyzes the uncertainty surrounding WDN node pressures, post-implementation of optimal instructions for pipe repair and replacement. The input parameters considered for this analysis include the uncertainty associated with the pipe's roughness coefficient and the nodes demand within the network. To achieve this objective, a combined approach utilizing both a simulation model (EPANET) and the fuzzy α-cut methodology is employed. Triangular fuzzy membership functions (MF) are chosen for both the input and output variables in the analysis. The extreme value combinations of the two uncertain input variables, at each level of uncertainty, are formulated into four distinct scenarios, serving as the input fuzzy set for the simulation model. Among the research scenarios, the second scenario, characterized by the combination of the minimum pipe's roughness coefficient and the maximum demand, is designated as the critical scenario. The findings indicate that in the critical scenario, under the highest level of uncertainty, the WDN reliability index diminishes significantly, ranging from approximately 30–40%. This decrease is primarily attributed to the inadequate supply of required pressure to most nodes within the network. At lower levels of uncertainty, the reliability index of the network surpasses 75%, indicating a relatively acceptable performance. Specifically, in the first and fourth scenarios, the network reliability index consistently exceeds 72%. Notably, in the third scenario, the network reliability index remains consistently above 90% across all uncertainty levels. [ABSTRACT FROM AUTHOR]

In Iran, Behesht Abad Water Transfer from the headwaters of Karoon to the central plateau is one of the most critical inter-basin water transfer projects. This study aims to evaluate the impacts of the Water Transfer (WT) on the water level and flow of Farsan Aquifer in the origin basin. To achieve this goal, WEAP-GMS was used. Some defined scenarios include maximum water transfer from the origin to the destination basin in three modes of normal hydrologic, drought, and increasing environmental demand of the river. The maximum transferable water in a normal year is 450 and deceases to 160 MCM in a drought year. Also, the groundwater level before and after WT, the flow direction, the dry aquifer surface, and the dry wells were calculated. The results demonstrate that water transfer in the long term will cause a drop in the aquifer volume and level of the origin basin. Almost 34% of the aquifer surface and 138 wells will be thoroughly dried. Based on the results, inter-basin water transfer plans may solve the water shortage of the destination basin (recipients) over the short-term, but in long periods have adverse impacts on the environmental sustainability of the origin basin (donor). [ABSTRACT FROM AUTHOR]

The study aims to simulate the stage-wise, year-wise mine seepage predictions and the corresponding impact on the groundwater regime (drawdown and heads) in accordance with the approved mine plan for certain coal mines in Central India. To that end, the optimized and efficient watershed area of 997.61 km2 has been delineated by using ArcGIS software and was synthesized in a finite difference numerical model with the concept of 21 layers (multi-layered aquifer system) encompassing six working mines. Initially, the groundwater-flow model was constructed for the simulation of groundwater conditions during May 2022 which shows a good model fit of the observed and simulated water levels, with the majority of the data lying close to the 1:1 line as indicated by an RMS value of less than 5 m. Then, the zone budget of different forecast scenarios reveals that the inflows into the various mine excavation area are: 13,733 (Gevra OC), 12,732 (Kusmunda OC), 8569 (Dipka OC), 8308 (Surakchar UG), 8018 (Manikpur OC), and 7511 (Balgi UG) m3/day. The zone of influence defined by zero drawdown extends up to 1.22 km to the NW of Kusmunda OCP, 2 km to the east of Dipka OCP, and 1.25 km to the SW from the quarry surface boundary of Gevra OCP and is negligible, i.e. up to < 0.5 km, in the western side with the predicted drawdown of 10 m within the project lease area. However, the progressive recovery of water levels will start in accordance with the closure of mines and the cone of depressions due to mine dewatering tend to vanish by 2050. The simulations suggest that mining activities have impacted neither the flow system of the Hasdeo River (effluent stream) nor the aquifers that are interacting with the river, as the river has not contributed any groundwater flows in to these mining areas. [ABSTRACT FROM AUTHOR]

The geospatial techniques are being used in this research to determine the depths, trends, water levels, and likely groundwater zones in the Deori Tehsil. In the research area, topography maps of India and water quality analysis are used to define physical parameters for the inverse distance weighting (IDW) interpolation method. The soil slopes from 150 to 300 m at this point. With the branches of Navegaon Mountain and Chichgarh Hills to the south of it, it is situated 302 m above sea level. The study shows that the pre-monsoon water levels in the deeper aquifer range from 5.7 to 14.85 mbgl in May 2021, and the post-monsoon water levels in the deeper aquifer range from 0.2 to 2.5 mbgl in November 2021. This study region has the highest drinkable water quality (41.27%), followed by excellent water (17.46%) and good water (23.81%). This is because there is not much urbanization in the area, the water quality is excellent, and there is developed agricultural land nearby. There, the quality of the water appears to have declined. It has a capacity of 30.16% for bad water, 7.94% for unsuitable water, and 20.63% for extremely poor water, all of which are good for drinking and farming. [ABSTRACT FROM AUTHOR]

On February 17 2023, a landslide occurred on a highway slope along the Xiaolangdi Reservoir of the Yellow River, involving approximately 1,200 m3. This event directly resulted in road interruption and had profound social repercussions. This paper researches the landslide using a combination of field investigation, remote sensing imagery, laboratory tests, and numerical simulation. It traces the evolution of landslide occurrences influenced by human engineering activities and investigates the mechanisms by considering climatic factors, water levels fluctuations, and stress changes. The results indicate that: (1) fluctuations in water levels can reduce the stability coefficient of ancient landslides, albeit without directly triggering them. Moreover, alterations in soil stress induced by artificial excavation changes the distribution of the slope plastic zone, consequently altering potential sliding zones. (2) rainfall and temperature emerge as primary factors influencing the occurrence of accumulation landslides, it is particularly susceptible with the transition between winter and spring. (3) freeze-thaw action exerts significant pressure on sandstone bedding, which causes notable expansion deformation. Consequently, it is advisable to consider soil temperature and bedrock deformation when monitoring similar slopes. [ABSTRACT FROM AUTHOR]

The Río de la Plata Estuary (RdP) is frequently affected by large storm surges that have historically caused social and economic losses. According to recent research, the number and strength of surge events have been increasing over time as a result of climate change. Although process-based models have been widely used for the storm surge prediction, their high computational demand may be a significant disadvantage in some applications, such as rapid or neartime forecasting. Artificial neural network (ANN) becomes an alternative tool to forecast the water level, taking into account meteorological and astronomical forcing as numerical models also do. In this work, an ANN model performance was evaluated to hindcast and forecast water levels in the RdP. Several combinations of lead times and inputs were assessed in order to find the best configuration. The resulting model provides 4-day forecasts for Buenos Aires and Torre Oyarvide stations (located at the upper and intermediate estuary, respectively), using observed water levels, meteorological inputs and predicted astronomical tides. Results also support the ANN model's ability to simulate even extreme events. For instance, for a 12 h-forecast, the RMSE is about 20 cm. Finally, we conclude that the model developed here can effectively complement the empirical and numerical forecasts executed by Naval Hydrographic Service, reducing computational costs and leveraging available datasets. [ABSTRACT FROM AUTHOR]

Baishuihe Landslide is a large active landslide that threatens shipping transportation in the Three Gorges Reservoir (China). A manual monitoring system has been implemented since 2003. However, after some intervention works in 2018–2019, new automatic instruments providing continuous data on displacements, rainfall, reservoir water level, and groundwater table were installed. The data recorded by the new system show that interventions led to an effective stabilization improvement since the present displacement rate is smaller than that before interventions. However, the relevance of the Three Gorges basin and the potential hazard of a possible collapse requires a reliable forecast of the landslide evolution in a time scale from a few hours to a few days. To this aim, a two-step procedure is proposed here. In the first step, after a preliminary preprocessing-denoising of data, carried out by means of Discrete Wavelet Transform (DWT), a Continuous Wavelet Transform (CWT) procedure is used to provide scalograms of the time series of three quantities, e.g., landslide displacement rate, rainfall and the difference of water level between one piezometer and reservoir water level (RWL). In the second step, to evaluate the relationships among the velocity trend and the other significant quantities and obtain a reliable velocity forecast, the images given by binding together two or three scalograms of the mentioned quantities were analyzed using Convolutional Neural Network (CNN) tool. Several trials with different combinations of input time series of 2 or 3 quantities were carried out in order to recognize the factors which mainly affect the current displacement evolution. The results show that, after the interventions, rainfall is an important factor inducing deformation acceleration. The hydrodynamic pressure induced by the difference between the groundwater pressure and reservoir water level also plays a dominant role in accelerating the Baishuihe landslide. Furthermore, the coupling of rainfall and hydrodynamic pressure produces displacement velocities higher than what the quantities singularly do. These results provide valuable indications for optimizing the monitoring configuration on the landslide and obtaining velocity forecasts in a few hours/days. [ABSTRACT FROM AUTHOR]