River Water Bodies Research Articles

Using machine learning for the assessment of ecological status of unmonitored waters in Poland

Advancements in Artificial Intelligence (AI) technology allow for development of new tools for analytics and management which present new opportunities in field of environmental protection. The following study showcases usage of Machine Learning (ML) techniques as a complementary method for water status assessment of water bodies. Since the main goal of Water Framework Directive (WFD) is to improve the quality of water and reach good status in all the water bodies across Europe intensive monitoring program was launched together with water status assessment procedure. Based on requirements of the European Union’s WFD concerning ecological status assessment it is presented how ML can be used for assessment of Polish unmonitored river water bodies. Due to the absence of monitoring data, the foremost challenge lay in securing relevant alternative data which was set to be anthropogenic pressures. The pivotal solution was implementation of ML techniques which enable processing of seemingly unrelated information concerning pressures in the catchment. Decision Tree, Random Forest, KNN, Support Vector Machine, Multinomial Naive Bayes, XGBoost models have been tested and the results indicated most suitable techniques. Study shows highest efficiency of XGBoost and Random Forest algorithms for classification of unmonitored water bodies. The models were compared by their overall accuracy (OA) reaching approximately 93% for binary classification and 72% for comprehensive classification as well as partial class accuracies and the Probability of Misclassification (PoM) parameter. The analyses demonstrates a practical application of AI in assessment of unmonitored water bodies in case of binary classification used for reporting water status objectives of WFD as well as possible usage of full classification for planning and operational uses. OA and PoM are postulated as the best measures of goodness of classification.

Chaos analysis and traveling wave solutions for fractional (3+1)-dimensional Wazwaz Kaur Boussinesq equation with beta derivative

Wazwaz Kaur Boussinesq (WKB) equation can effectively simulate the behavior of water waves in shallow water, including the nonlinear effect and dispersion phenomenon of waves, which is of great significance for understanding the dynamic process of ocean, river and other water bodies. To enrich the wave equation theory, the (3+1)-dimensional integer order derivative of WKB equation is changed to the fractional one with beta derivative. The current work deals with the fractional (3+1)-dimensional WKB equation for discussing its chaotic behavior and establishing some new analytic solutions. The chaotic properties of the equation are verified by the trend of evolution along with time, Lyapunov exponents and initial sensitivity analysis. And then complete discrimination system for polynomial method is applied to derive some trigonometric, hyperbolic, Jacobi elliptic and other solutions. The graphical demonstrations are provided for part of these solutions. From these visualized graphs, the solitary, periodic and quasi-periodic wave are shown and the effect of fractional derivatives on the equation can be seen intuitively.

Exploring Water Quality Assessment through AHP and Picture Fuzzy PROMETHEE - II: An In-Depth Investigation

Effective analysis of water quality is crucial for the well-being of ecosystems and human populations, notably in rivers like Thirumanimutharu. This study advances current methodologies by integrating the picture fuzzy PROMETHEE II approach with the analytic hierarchy process (AHP), offering a robust solution to the challenges posed by data ambiguity and imprecision. Born from the fusion of PROMETHEE II with picture fuzzy sets, this innovative method adeptly represents qualitative criteria and linguistic notions inherent in water quality assessment. A practical case study, utilising real water quality data, demonstrates the superior accuracy and durability of the combined picture fuzzy PROMETHEE II and AHP approach compared to traditional methods. These results significantly contribute to our understanding of water quality assessment, providing essential insights for environmental experts and decision-makers. The approach�s efficacy is particularly highlighted in the management and conservation of water resources in the Thirumanimutharu river, emphasising the need for advanced methodologies in environmental conservation and resource management. This research underscores the importance of adopting sophisticated techniques for more informed decision-making, ultimately contributing to the water resources and the preservation of ecological balance in the Thirumanimutharu river and similar water bodies.

UAV Quantitative Remote Sensing of Riparian Zone Vegetation for River and Lake Health Assessment: A Review

River and lake health assessment (RLHA) is an important approach to alleviating the conflict between protecting river and lake ecosystems and fostering socioeconomic development, aiming for comprehensive protection, governance, and management. Vegetation, a key component of the riparian zone, supports and maintains river and lake health (RLH) by providing a range of ecological functions. While research on riparian zone vegetation is ongoing, these studies have not yet been synthesized from the perspective of integrating RLHA with the ecological functions of riparian zone vegetation. In this paper, based on the bibliometric method, the relevant literature studies on the topics of RLHA and unmanned aerial vehicle (UAV) remote sensing of vegetation were screened and counted, and the keywords were highlighted, respectively. Based on the connotation of RLH, this paper categorizes the indicators of RLHA into five aspects: water space: the critical area from the river and lake water body to the land in the riparian zone; water resources: the amount of water in the river and lake; water environment: the quality of water in the river and lake; water ecology:aquatic organisms in the river and lake; and water services:the function of ecosystem services in the river and lake. Based on these five aspects, this paper analyzes the key role of riparian zone vegetation in RLHA. In this paper, the key roles of riparian zone vegetation in RLHA are summarized as follows: stabilizing riverbanks, purifying water quality, regulating water temperature, providing food, replenishing groundwater, providing biological habitats, and beautifying human habitats. This paper analyzes the application of riparian zone vegetation ecological functions in RLH, summarizing the correlation between RLHA indicators and these ecological functions. Moreover, this paper analyzes the advantages of UAV remote sensing technology in the quantitative monitoring of riparian zone vegetation. This analysis is based on the high spatial and temporal resolution characteristics of UAV remote sensing technology and focuses on monitoring the ecological functions of riparian zone vegetation. On this basis, this paper summarizes the content and indicators of UAV quantitative remote sensing monitoring of riparian zone vegetation for RLHA. It covers several aspects: delineation of riparian zone extent, identification of vegetation types and distribution, the influence of vegetation on changes in the river floodplain, vegetation cover, plant diversity, and the impact of vegetation distribution on biological habitat. This paper summarizes the monitoring objects involved in monitoring riparian zones, riparian zone vegetation, river floodplains, and biological habitats, and summarizes the monitoring indicators for each category. Finally, this paper analyzes the challenges of UAV quantitative remote sensing for riparian zone vegetation at the current stage, including the limitations of UAV platforms and sensors, and the complexity of UAV remote sensing data information. This paper envisages the future application prospects of UAV quantitative remote sensing for riparian zone vegetation, including the development of hardware and software such as UAV platforms, sensors, and data technologies, as well as the development of integrated air-to-ground monitoring systems and the construction of UAV quantitative remote sensing platforms tailored to actual management applications.

Extraction of River Water Bodies Based on ICESat-2 Photon Classification

The accurate extraction of river water bodies is crucial for the utilization of water resources and understanding climate patterns. Compared with traditional methods of extracting rivers using remote sensing imagery, the launch of satellite-based photon-counting LiDAR (ICESat-2) provides a novel approach for river water body extraction. The use of ICESat-2 ATL03 photon data for inland river water body extraction is relatively underexplored and thus warrants investigation. To extract inland river water bodies accurately, this study proposes a method based on the spatial distribution of ATL03 photon data and the elevation variation characteristics of inland river water bodies. The proposed method first applies low-pass filtering to denoised photon data to mitigate the impact of high-frequency signals on data processing. Then, the elevation’s standard deviation of the low-pass-filtered data is calculated via a sliding window, and the photon data are classified on the basis of the standard deviation threshold obtained through Gaussian kernel density estimation. The results revealed that the average overall accuracy (OA) and Kappa coefficient (KC) for the extraction of inland river water bodies across the four study areas were 99.12% and 97.81%, respectively. Compared with the improved RANSAC algorithm and the combined RANSAC and DBSCAN algorithms, the average OA of the proposed method improved by 17.98% and 7.12%, respectively, and the average KC improved by 58.38% and 17.69%, respectively. This study provides a new method for extracting inland river water bodies.

Evaluating the Sustainable Development Science Satellite 1 (SDGSAT-1) Multi-Spectral Data for River Water Mapping: A Comparative Study with Sentinel-2

SDGSAT-1, the first scientific satellite dedicated to advancing the United Nations 2030 Agenda for Sustainable Development, brings renewed vigor and opportunities to water resource monitoring and research. This study evaluates the effectiveness of SDGSAT-1 in extracting water bodies in comparison to Sentinel-2 multi-spectral imager (MSI) data. We applied a confidence thresholding method to delineate river water from land, utilizing the Normalized Differential Water Body Index (NDWI), Normalized Difference Water Index (MNDWI), and Shaded Water Body Index (SWI). It was found that the SWI works best for SDGSAT-1 while the NDWI works best for Sentinel-2. Specifically, the NDWI demonstrates proficiency in delineating a broader spectrum of water bodies and the MNDWI effectively mitigates the impact of shadows, while SDGSAT-1’s SWI extraction of rivers offers high precision, clear outlines, and shadow exclusion. SDGSAT-1’s SWI overall outperforms Sentinel-2’s NDWI in water extraction accuracy (overall accuracy: 90% vs. 91%, Kappa coefficient: 0.771 vs. 0.416, and F1 value: 0.844 vs. 0.651), likely due to its deep blue bands. This study highlights the comprehensive advantages of SDGSAT-1 data in extracting river water bodies, providing a theoretical basis for future research.

Spatiotemporal variations of plankton communities in different water bodies of the Yellow River: Structural characteristics, biogeographic patterns, environmental responses, and community assembly

Phytoplankton and zooplankton serve as critical indicators of aquatic ecological health, playing vital roles in nutrient cycling in aquatic ecosystems. Nevertheless, their biogeographic patterns and community assembly remain poorly understood, especially in large-scale watersheds. In this study, we collected plankton samples from typical reservoirs and river sections along the Yellow River during spring and summer to investigate their spatiotemporal dynamics, geographic patterns, and community assembly. Our results revealed that the diversity and composition of plankton communities varied with season significantly, showcasing higher diversity and density during summer. Distance-decay relationships highlighted significant correlations between environmental gradients and plankton community heterogeneity in both seasons, whereas spatial factors exerted a more prominent effect on phytoplankton during summer. Water temperature, dissolved oxygen, chemical oxygen demand, and total suspended sediments emerged as the main environmental attributes affecting plankton composition, as illustrated by Mantel’s test. Both ecological niche differentiation and dispersal limitation contributed to plankton community construction, with ecological niche differentiation being more dominant in spring and dispersal limitation more influential on phytoplankton in summer. These findings enhance our understanding of the structural characteristics of plankton communities in the large-scale Yellow River, shedding light on their biogeographic patterns and community construction mechanisms within large river ecosystems.

Spatial and temporal differentiation and coupling analysis of land use change and ecosystem service value in Jiangsu Province

A detailed exploration of the nexus between land use change (LUC) and ecosystem service value (ESV) at the urban level is crucial for fostering high-quality urban economic growth alongside the sustainable management of land resources. This study focuses on Jiangsu Province, employing an enhanced and refined ESV assessment model to perform a dynamic examination of the spatial and temporal variations in land use and ESV across the region from 2000 to 2020. Additionally, it delves into the intricate coupled coordination dynamics between land use intensity and ESV by developing a coupled coordination model. Key findings include: (1) Jiangsu Province experienced notable land use transformations over the two decades, with a marked reduction in cropland and a significant expansion of construction sites being the most prominent shifts. (2) The ESV in Jiangsu Province has exhibited fluctuating trends over the past 20 years, with water bodies and agricultural lands serving as the cornerstone for the province's ESV. Areas with high ESV are predominantly located around the Yangtze River's water bodies, along the coastline, and around lakes and radiate outward from these aquatic centers. (3) The coupling between LUC and ESV in Jiangsu Province has been upward, albeit with pronounced city disparities. This coupling displays distinct spatial patterns, characterized by higher levels in the east and lower levels in the west, as well as higher levels in the north and lower levels in the south. The outcomes of this analysis offer valuable insights and policy recommendations for enhancing land use planning, refining land use configurations, and promoting the synergistic development of land use and ecosystem service functions in Jiangsu Province.

Application Research on Optimal Allocation of Drainage Rights Based on Computer Big Data in Anhui Province of Huai-River Basin

In this paper, a three-dimensional visualization model of river water body based on Vega is proposed. This system can not only display the water quality information of each monitoring point on the geographic information platform, but also carry out virtual reality roaming of the river. Then the mechanism of interactive allocation of initial water discharge rights is analyzed. According to the principle of interaction and negotiation between different regions and industries, a two-level diagnosis and optimization model is established. Secondly, the optimal equation and diagnostic criteria of comprehensive benefits based on regional economy and society are constructed based on the strict control of the maximum emission permit. The initial emission rights are interactively configured between the primary and secondary levels. Emission reduction targets for each region and industry were proposed. Considering the fairness and effectiveness of the allocation of water discharge rights between regions and industries, the comprehensive benefits of each region and the whole basin are maximized. The feasibility of the scheme is illustrated by an example analysis. It is urgent to carry out the research on the rational allocation of drainage rights in Huaihe River, and the relevant research results will contribute to the sustainable supply of grain in Anhui province, help avoid water disputes around the Huaihe River, and promote the sustainable economic and social development of Anhui province.

Antibiotic consumption and antibiotics occurrence into the environment: a case study of hospital in Metro, Lampung

Increased antibiotic consumption has exposed bacterial communities and environmental ecosystems to large amounts of antibiotic residues derived from the excretion of irrationally consumed antibiotics. This study provides an overview of antibiotic consumption patterns in hospital inpatients and the distribution of residues released into the environment. Medical record data was used to calculate the amount of consumption from hospital inpatients, and based on the type of antibiotics that have a DU90% value, ecotoxicological risk calculations were carried out to estimate the level of danger that occurs in the environment. A total of 27 types of antibiotics were prescribed, with a total consumption of 20504.42 Kg/year. Antibiotics such as ceftriaxone, cefixime, cefadroxil, and levofloxacin are the most widely used antibiotics based on medical record data. The results of estimating the release of antibiotic residues in wastewater obtained ecotoxicological risk values for algae, invertebrates, and fish greater than one (RQs>1). This condition indicates an ecotoxicological risk at the health facility site due to the release of antibiotic residues into the river water body from the WWTP outlet. The release of antibiotic residues into the water can result in ecosystem damage and pollution of the aquatic environment.

Monitoring Spatial–Temporal Variations in River Width in the Aral Sea Basin with Sentinel-2 Imagery

Rivers in arid regions serve as crucial freshwater resources for local communities and play an essential role in global hydrological and biogeochemical cycles. The Aral Sea Basin (ASB) in Central Asia is characterized by an arid climate and river dynamics that are sensitive to climate change and human activities. Monitoring the spatiotemporal variations in river water extent in the ASB is essential to maintain an ecological balance and ensure water security. In this study, we extracted data regarding monthly river water bodies in the ASB from 2017 to 2022 by synthesizing monthly Sentinel-2 images. The water extents on the Sentinel images were automatically mapped using the Otsu method, and the river widths for all river channels were calculated using the RivWidth algorithm. We investigated the relationships between the river dynamics and the geomorphology, climatic change, human activities, and the annual and interannual variations in the river width in different reaches of the basin. The results show a seasonal variability in the river width, with most rivers reaching the largest width in the warm season and a few rivers in the middle and lower areas reaching the valley value in the warm season. Compared to their tributaries, the mainstem in the middle/lower regions showed less seasonal variability. According to interannual analysis, most of the rivers in the ASB significantly narrowed between 2017 and 2022, a phenomenon which is generally impacted by temperature and evapotranspiration variations. Comparisons show that our results provide improved information about the narrow river reaches and denser river networks compared to the previous global dataset, demonstrating the advantageous properties of high spatial resolution in Sentinel-2 imagery.

Response of microbial communities to exogenous nitrate nitrogen input in black and odorous sediment

Since nitrate nitrogen (NO3−-N) input has proved an effective approach for the treatment of black and odorous river waterbody, it was controversial whether the total nitrogen concentration standard should be raised when the effluent from the sewage treatment plant is discharged into the polluted river. To reveal the effect of exogenous nitrate (NO3−-N) on black odorous waterbody, sediments with different features from contaminated rivers were collected, and the changes of physical and chemical characteristics and microbial community structure in sediments before and after the addition of exogenous NO3−-N were investigated. The results showed that after the input of NO3−-N, reducing substances such as acid volatile sulfide (AVS) in the sediment decreased by 80 % on average, ferrous (Fe2+) decreased by 50 %, yet the changing trend of ammonia nitrogen (NH4+-N) in some sediment samples increased while others decreased. High-throughput sequencing results showed that the abundance of Thiobacillus at most sites increased significantly, becoming the dominant genus in the sediment, and the abundance of functional genes in the metabolome increased, such as soxA, soxX, soxY, soxZ. Network analysis showed that sediment microorganisms evolved from a single sulfur oxidation ecological function to diverse ecological functions, such as nitrogen cycle nirB, nirD, nirK, nosZ, and aerobic decomposition. In summary, inputting an appropriate amount of exogenous NO3−-N is beneficial for restoring and maintaining the oxidation states of river sediment ecosystems.

RAU-Net++: River Channel Extraction Methods for Remote Sensing Images of Cold and Arid Regions

Extracting river channels from remote sensing images is crucial for locating river water bodies and efficiently managing water resources, especially in cold and arid regions. The dynamic nature of river channels in these regions during the flood season necessitates a method that can finely delineate the edges of perennially changing river channels and accurately capture information about variable fine river branches. To address this need, we propose a river channel extraction method designed specifically for detecting fine river branches in remote sensing images within cold and arid regions. The method introduces a novel river attention U-shaped network structure (RAU-Net++), leveraging the rich convolutional features of VGG16 for effective feature extraction. For optimal feature extraction along channel edges and fine river branches, we incorporate a CBAM attention module into the upper sampling area at the end of the encoder. Additionally, a residual attention feature fusion module (RAFF) is embedded at each short jump connection in the dense jump connection. Dense skip connections play a crucial role in extracting detailed texture features from river channel features with varying receptive fields obtained during the downsampling process. The integration of the RAFF module mitigates the loss of river information, optimizing the extraction of lost river detail feature information in the original dense jump connection. This tightens the combination between the detailed texture features of the river and the high-level semantic features. To enhance network performance and reduce pixel-level segmentation errors in medium-resolution remote sensing imagery, we employ a weighted loss function comprising cross-entropy (CE) loss, dice loss, focal loss, and Jaccard loss. The RAU-Net++ demonstrates impressive performance metrics, with precision, IOU, recall, and F1 scores reaching 99.78%, 99.39%, 99.71%, and 99.75%, respectively. Meanwhile, both ED and ED′ of the RAU-Net++ are optimal, with values of 1.411 and 0.003, respectively. Moreover, its effectiveness has been validated on NWPU-RESISC45 datasets. Experimental results conclusively demonstrate the superiority of the proposed network over existing mainstream methods.

Risks of Surface Water Pollution in Southern Vietnam

The study was carried out to assess surface water quality and ecological risks in water bodies in the southern region of Vietnam. The study used monitoring data at 58 locations, which were collected in March, May, June, July, August, October, November, and December of 2022, with 11 water quality parameters (temperature, pH, DO, TSS, BOD, COD, NH4+-N, NO3--N, Fe, Pb, and Cd). Comprehensive pollution index (CPI), ecological risk level, and multivariate statistical analysis methods were utilized. The values of CPI showed that the surface water quality was mildly polluted, moderately polluted, and severely polluted, accounting for 37.93, 46.93, and 15.52%, respectively. In particular, heavy pollution was concentrated in the water bodies of the Sai Gon and Vam Co Rivers. TSS, BOD, COD, NH4+-N, and Fe had a moderate to high level of risk, while water samples contaminated with NO3--N, Pb, and Cd had a level of risk from low to safe. High levels of risk were concentrated in the water bodies of the Sai Gon River and Vam Co River, typically BOD and COD. Based on the impact level, the positions were classified into five groups, with the locations on the Sai Gon River and Vam Co River (Groups 4 and 5) being affected by various waste sources in the inner city of Ho Chi Minh City. The PCA results presented three sources, such as discharge from residential areas, soil erosion, and agriculture, that have caused water quality fluctuations and increased the impact on the water quality of water bodies. Measures to protect water resources according to environmental protection laws must be implemented soon to minimize ecological risks from water-polluting sources. Doi: 10.28991/CEJ-2023-09-11-06 Full Text: PDF

A multivariate approach to assessing the water quality of the Bamako reach of the Niger River in Mali as irrigation water.

Agricultural production in the Bamako region has been raised, and its output quality has been questionable due to the discharge of wastewater into the Niger River. This study assessed the Niger River water body variations for irrigation application temporally and spatially. Thirteen parameters, potential of hydrogen, electrical conductivity, nitrate, total dissolved solids, phosphate, sulfate, chloride, ammonium, calcium, magnesium, potassium, sodium, and bicarbonate, were analyzed at the 15 sampling locations. Parameters examination indicated that most pollutants had higher concentrations over the high-flow phase than in the low-flow period. All parameters were within the Food and Agriculture Organization's recommended values levels. Irrigation variables, sodium adsorption ratio, sodium percentage, soluble sodium percentage, residual sodium bicarbonate, Kelly's ration, permeability index, total hardness, and potential salinity showed the water samples' convenience for irrigation. However, the magnesium hazard concentration exceeded the recommended values levels. Besides, the chloroalkaline indices indicated a trend of degradation that should be addressed. Therefore, a river management plan and regular irrigation water quality monitoring are needed to reduce water hardness in Bamako. The Niger River's sustainable management process must be thrived on all actors' participation. A scientific assessment will be conducted using appropriate methods to identify pollution sources in Bamako. The results of this study will serve as a cornerstone for future investigations concerning the quality of surface water, which is essential for irrigation purposes. PRACTITIONER POINTS: Human activities affected the Niger River water bodies in Bamako city. Quantitative and qualitative assessments reveal the pollution status and trend of the Niger River. The water quality trend is better in the low-flow season, which is an ideal period for vegetable production in Bamako. Most multivariate approaches indicated that the Niger River water is healthy for irrigation purposes. Magnesium hazard exceeded the standard levels, and the chloroalkaline indices indicated a trend of the Niger River water quality deterioration.

Impact and analysis of urban water system connectivity project on regional water environment based on Storm Water Management Model (SWMM)

SWMM stands as a dynamic rainfall-runoff urban hydrological model, crafted by the U.S. Environmental Protection Agency. It adeptly replicates urban rainfall production and ground runoff, and the Pressure-State-Response (PSR) theory artfully reflects human-environment interactions. Urban Water System Connectivity (UWSC) fortifies connections among regional rivers, transforming them into an intricate, dense network. To study the improvement of the regional water environment by the UWSC project, this study takes the UWSC project in Runan County, Zhumadian, China as the research object, constructs a hydrodynamic and water quality model based on SWMM, and simulates it under different rainfall situations. At the same time, the ecological service value theory and PSR theory are used to establish an ecological effect index system to analyze the ecological effect before and after the UWSC project. This paper evaluates the urban water system connectivity project from three aspects: hydrodynamic, water quality, and ecological effects. Results underscore that the post-UWSC era witnesses decreased river flood flows in varied design rainfalls, accompanied by delayed flood peaks. Under P = 10a and P = 20a rainfalls, peak flow reductions of 6.6% and 4.96% respectively, manifest with peak time lags of 0.17h. Flow rate adjustments align with flow behavior, exhibiting decreased peak flow rates accompanied by temporal lags. Initial river flow increases by about 30%, amplifying river water body exchange capacity. Following the UWSC implementation, the study area's five primary rivers display TSS reductions ranging from 46% to 86.94%, COD from 36.98% to 92.43%, TN from 45.9% to 92.96%, TP from 35.71% to 84.78%, and NH3–N from 38.52% to 92.19%. Simulated point source pollution, under comparable initial conditions, indicates pollutant decay rates escalating from 3.2%–20%–35.71%–92.43%. Ecological impact ascends from 6.33 × 108 RMB to 9.65 × 108 RMB, reflecting a 52.5% escalation. The UWSC initiative enriches urban river flood resilience and water quality, emblematic of urban water ecological civilization progress.

Water turbidity dynamics using random forest in the Yangtze River Delta Region, China

Turbidity is a water quality indicator that is essential for the sustainable development of aquatic ecosystems and the protection of biodiversity. The turbidity of different water surfaces and its response mechanisms to regional climatic factors and human activities in the Yangtze River Delta Region (YRDR), an important rapid economic development region in China, remain poorly understood. To enhance the knowledge of turbidity variations and dominant drivers of YRDR water surfaces, a complete long-term turbidity series was obtained using Landsat images from 1990 to 2020. The results show that the turbidity trend differed from −1.3 NTU/yr to 0.7 NTU/yr in different water surfaces. Turbidity decreased significantly in the mainstream of the Yangtze River (MYR), aquaculture ponds (AP) and other water bodies, whilst increasing significantly in the medium lakes (ML) and mainstream of the Qiantang River (MQR). Meanwhile, no significant changes in turbidity were observed in the great lakes (GL) and small lakes (SL). Rather than climatic factors, urbanisation and decreasing wastewater discharge were the dominant drivers of turbidity trends during the study period. In addition, ecological engineering in AP increased water transparency. The Three Gorges Dam also decreased turbidity in MYR. Increasing turbidity in the downstream of MQR was driven by increasing seasonal water surfaces and reclamation projects near Hangzhou Bay. GL faced no significant increase in turbidity due to the offset of afforestation to urbanisation-induced turbidity increase. These findings provide important information for government decision-making for subsequent aquatic environmental protection and restoration in the YRDR.

Separation of Floodplain Flow and Bankfull Discharge: Application of 1D Momentum Equation Solver and MIKE 21C

A floodplain is an area of low-lying land adjacent to a river, stream, or other water body that is regularly inundated by water during periods of high flow. Floodplains typically have relatively flat terrain and are composed of sediments deposited by the river over time. Floodplain flow refers to the movement of water across the surface of the floodplain during periods of high flow. This flow can occur as a result of water spilling over the river banks or seeping into the ground and then re-emerging on the surface of the floodplain. Bankfull discharge is the flow of water that just fills the channel of a river or stream to the top of its banks. It is the point at which the river or stream is at its maximum capacity without overflowing onto the floodplain. Bankfull discharge is often used as a reference point for assessing flood risk and planning floodplain management strategies. To examine the bank-to-bank hydro-morphodynamics of a river, it is necessary to comprehend the flow distribution throughout the main stream and floodplain. Along with river hydraulics, bankfull discharge is a crucial parameter for estimating river bank erosion. For evaluating the distribution and generation of river flow over the floodplain and main stream, a variety of modeling tools and approaches are available. This study investigates methods for separating floodplain flow and bankfull discharge from observed discharge data using the one-dimensional momentum equation. A two-dimensional modeling tool (MIKE 21C) was also employed to investigate the usefulness of the proposed method in a region with an enormous floodplain.

The Dynamic Nature of Wrack: An Investigation into Wrack Movement and Impacts on Coastal Marshes Using sUAS

This study investigates the use of small unoccupied aerial systems (sUAS) as a new remote sensing tool to identify and track the spatial distribution of wrack on coastal tidal marsh systems. We used sUAS to map the wrack movement in a Spartina alterniflora-dominated salt marsh monthly for one year including before and after Hurricane Isaias that brought strong winds, rain, and storm surge to the area of interest in August 2020. Flight parameters for each data collection mission were held constant including collection only during low tide. Wrack was visually identified and digitized in a GIS using every mission orthomosaic created from the mission images. The digitized polygons were visualized using a raster data model and a combination of all of the digitized wrack polygons. Results indicate that wrack mats deposited before and as a result of a hurricane event remained for approximately three months. Furthermore, 55% of all wrack detritus was closer than 10 m to river or stream water bodies, 64% were within 15 m, and 71% were within 20 m, indicating the spatial dependence of wrack location in a marsh system on water and water movement. However, following the passing of Isaias, the percentage of wrack closer than 10 m to a river or creek decreased to a low of 44%, which was not seen again during the year-long study. This study highlights the on-demand image collection of a sUAS for providing new insights into how quickly wrack distribution and vegetation can change over a short time.

Novel Threshold Self-Regulating Water Extraction Method

Water resources are crucial for human activities and sustainable socioeconomic development. Understanding surface water information can play a key role in water resource management, which affects the global water cycle and ecological environments. Considering the Hailar River water body as an example, this study proposes a new threshold self-learning water body extraction method (TSLWEM) based on modified normalized difference water index (MNDWI) data. The optimal water extraction thresholds determined by the TSLWEM algorithm for four test images were −0.0030, 0, 0.1990, and −0.0800. The TSLWEM algorithm effectively identified the target water body with recognition accuracies of 98.08%, 99.93%, 93.39%, and 93.20% for the four test images. Moreover, it can accurately identify small tributaries, such as lakes and rivers. The TSLWEM algorithm is suitable for Landsat 8 Operational Land Imager (OLI) data, which can effectively monitor and map complex surface water in temperate and semiarid regions while improving the accuracy of water body identification. The study’s findings provide technical support for the protection of water resources as well as their rational utilization and monitoring.