River Monitoring Research Articles

Carbon dioxide exchange across water–air interface and its influencing factors in middle reaches of Yellow River during winter

ABSTRACT River systems strongly contribute to CO2 emissions. However, despite numerous reports on gas emissions from ice, the current understanding of CO2 exchange of rivers in winter and the factors affecting it is still relatively limited. To shed light on CO2 exchange and the factors influencing it for rivers during winter. Based on intensive field measurements using floating chambers, riverine CO2 exchange in middle reaches of Yellow River in China was examined. Our results showed net emissions of CO2 across the ice-free interface (51.874∼162.478 mg/m²·h). Compared with other rivers worldwide, the CO2 exchange is higher than most major rivers, such as the Lena and Kolyma Rivers. However, at the ice-covered river monitoring site, CO2 exchange across the water–air interface exhibited a net uptake, ranging from −36.336 to 0 mg/m²·h. Furthermore, the relationships between CO2 exchange and relevant physicochemical variables showed that CO2 emissions negatively correlated with pH and ice thickness and positively correlated with water velocity, wind speed, water temperature, atmospheric temperature, ammonia nitrogen levels, and total phosphorous content. This study is scientifically valuable as the findings provide insight into the CO2 exchange pattern that occurs at the water–air interface of rivers during winter both ice-covered and ice-free sites.

Impact of low-dose free chlorine on the conjugative transfer of antibiotic resistance genes in wastewater effluents: Identifying key environmental factors for predictive modeling.

Reclaimed water disinfection results in the coexistence of antibiotic resistance genes (ARGs) and low-dose free chlorine in receiving environments. However, the impact of low-dose free chlorine on ARGs conjugative transfer and the key factors influencing the transfer under complex environmental conditions remain unclear, hindering the establishment of an effective monitoring system for resistance pollution in reclaimed water. This study investigated ARGs conjugative transfer under the influence of free chlorine at environmentally relevant concentrations and key interactive factors using machine learning models. The results showed that low-dose free chlorine (0.05-0.3 mg/L) promoted ARGs conjugative transfer, with 0.15 mg/L having a greater promoting effect than free chlorine concentrations of 0.05 and 0.3 mg/L. Additionally, different exposure patterns of low-dose chlorine affected ARGs conjugative transfer, with intermittent exposure posing a higher risk of ARGs dissemination. SVM linear model performed best in predicting ARGs conjugative transfer (RMSE=0.012, R2=0.975), and the SHapley Additive Explanations (SHAP) method revealed that key factors such as HCO3-, SAA, NO3-, and HA had positive SHAP values, indicating a positive influence on ARGs transfer under low-dose chlorine, making them the key features for predicting the ARGs conjugative transfer under the low-dose chlorine exposure. This study also revealed potential mechanisms of ARGs transfer under continuous low-dose free chlorine exposure, including intracellular reactive oxygen species (ROS), enzyme activity, cell membrane permeability, and gene expression. The integration of the machine learning model and post-hoc interpretation methods clarified the key drivers of ARGs conjugative transfer in reclaimed water-replenished environments, providing new insights for the safe reuse of reclaimed water and the development of river monitoring indicators.

A simplified method for estimating the alpha coefficient in surface velocity based river discharge measurements

Remote sensing techniques for river monitoring facilitate faster measurement campaigns compared to traditional methods, reduce risks to personnel and instruments, and allow measurements under critical flow conditions. An alpha coefficient (α) is commonly employed to convert surface velocities, obtained by contactless techniques, into depth-averaged velocities, which are used for the application of the velocity-area method for assessing discharge. Some optical-based software programs use a constant α value, based on a theoretical “standard”. However, analyses of empirical vertical velocity profiles in real cases reveal that α can significantly deviate from this standard due to various factors (roughness, turbulence, etc.).This study analyzes several ADCP (Acoustic Doppler Current Profiler)-based measurements in Sicily, Italy, to explore factors influencing flow velocity distribution and potential errors from using the standard α for discharge estimation via surface velocity-based methods. The results confirmed substantial variability in α, which is functionally related to some geometric factors characterizing the cross-section shape and the specific vertical where the velocity profile is computed. The generated dataset of empirical α values is also used to implement an Artificial Neural Network (ANN), offering a straightforward tool suitable for non-contact techniques. The ANN predicts α at any vertical of a measurement transect as a function of variables however necessary for discharge assessment by non-intrusive methods, leading to depth-averaged velocity estimates from surface velocities that are more accurate than those derived from conventional approaches, as demonstrated by four test cases.

Aqua Quadcopter an Engineering Solution for Water Sample Collection

An “Aqua Quadcopter” designed for water sample collection is a specialized quadcopter capable of flying over water bodies and collecting water samples for analysis. This type of drone combines aerial mobility with aquatic capabilities, making it suitable for environmental monitoring, scientific research, and pollution detection in rivers, lakes, oceans, and other water bodies. Traditional methods of water sample collection are often labour- intensive, time consuming, and may require boats or human intervention in potentially hazardous environments. This project addresses the need for a more efficient, safer, and autonomous solution that can access remote or hard-to-reach areas and provide real-time data for environmental analysis. We are going to design drone and water sampler, adding some specifications like GPS system to target the area where it is polluted and observe the stability of quadcopter.

Automatic in situ sensor based on K2S2O8 oxidation method for total phosphorus detection in marine water

Phosphorus is a key indicator for water quality management due to its role in eutrophication. The variety of phosphorus-containing substances necessitates highly sensitive detection of total phosphorus, particularly through automated methods, to ensure water safety. This study involved the independent development of a sensor featuring an automated in situ detection technique. Utilizing potassium persulfate high-temperature oxidation and phosphorus molybdenum blue spectrophotometry, total phosphorus was monitored in situ via sequential injection technology. Additionally, the detection process and reaction conditions of the sensor were optimized, and a temperature compensation algorithm and turbidity correction were applied to mitigate environmental factors. Under optimal conditions, the sensor demonstrated a detection limit of 1.9 µg/L with a range of 6.5–1000 µg/L in seawater, and 1.2 µg/L with a range of 4.1–2000 µg/L in freshwater. The digestion efficiency for five representative phosphorus-containing substances was found to range from 87.3% ± 1.7% to 103.1% ± 0.6%. Notably, the sensor was deployed for in situ operation at a marine experimental station and online at a river monitoring station. With its integration, low power consumption, and high precision, the sensor enabled long-term unattended monitoring, delivering accurate, stable, and reliable results.

A hybrid model of ARIMA and MLP with a Grasshopper optimization algorithm for time series forecasting of water quality

Water quality monitoring of rivers is necessary in order to properly manage their basins so that steps can be taken to control the amount of pollutants and bring them to the allowable level. The ARIMA (autoregressive integrated moving average) model does not consider nonlinear patterns in modeling water quality components. Also, in modeling using the MLP (Multilayer Perceptrons) model, both linear and nonlinear pattern are not controlled equally. Therefore, in the present study, linear time series models (ARIMA), MLP model, and a hybrid model of MLP and ARIMA optimized by a Grasshopper optimization algorithm are used to predict water quality components in the statistical period of 2011–2019. In the proposed hybrid method, the ability of the ARIMA and the MLP model are exploited. Observational water quality data for forecasting time series in the hybrid method include dissolved oxygen, water temperature, and boron over 108 months. Since, the hybrid model is capable of realizing the nonlinear essence of complicated time series, it makes more reliable forecasts. In the hybrid model, the correlation coefficients between the observational data and the predicted values are 0.9 for dissolved oxygen, 0.91 for water temperature, and 0.91 for boron. To compare the three ARIMA, MLP, and hybrid models, the accuracy indices of each model are calculated. The results show that the hybrid model’s higher accuracy compared with the other two models.

Response of Water Quality to Land Use and Landscape Pattern in the Ganjiang River Watershed.

Analysing the impact of landscape composition and structure on water quality at different scales is of great significance to water quality protection. The aim of this study was to determine scale-dependent impacts of land use/landscape patterns on water quality. The Ganjiang River, the largest water system in the Poyang Lake watershed, the largest freshwater lake in China. The response of water quality to land use and landscape patterns in the Ganjiang River watershed was explored based on land use and water quality data using redundancy and Spearman correlation analyses. Considering upstream monitoring of the entire Ganjiang River watershed; watersheds at the county level administrative region; and 1, 2, 5, 10, 15, 20, and 30 km-radius circular buffer zones, a total of nine scales of land use/landscape patterns that influence water quality in the Ganjiang River watershed were analysed. Results indicated that the county-level scale and the land use type of the 20 km-radius buffer zone upstream of the monitoring site were closely linked to water quality (96.28% and 93.23%, respectively). Among the land use types, construction land and cultivated land were the main output sources of pollutants. Regarding landscape pattern index, the greater the fragmentation of the landscape, the heavier was the water pollution load; the more the patches per unit area, the more stable was the ecosystem and the lower was the pollutant concentration. In addition, the eco-hydrological system of the Ganjiang River watershed was revealed to some extent through multi-angle analysis. These conclusions can serve as a reference for government departments to formulate land management and water quality protection measures.

Improving multiple stressor-response models through the inclusion of nonlinearity and interactions among stressor gradients.

Stressor-response models are used to detect and predict changes within ecosystems in response to anthropogenic and naturally occurring stressors. While nonlinear stressor-response relationships and interactions between stressors are common in nature, predictive models often do not account for them due to perceived difficulties in the interpretation of results. We used Irish river monitoring data from 177 river sites to investigate if multiple stressor-response models can be improved by accounting for nonlinearity, interactions in stressor-response relationships and environmental context dependencies. Out of the six models of distinct biological responses, five models benefited from the inclusion of nonlinearity while all six benefited from the inclusion of interactions. The addition of nonlinearity means that we can better see the exponential increase in Trophic Diatom Index (TDI3) as phosphorus increases, inferring ecological conditions deteriorating at a faster rate with increasing phosphorus. Furthermore, our results show that the relationship between stressor and response has the potential to be dependent on other variables, as seen in the interaction of elevation with both siltation and nutrients in relation to Ephemeroptera, Plecoptera and Trichoptera (EPT) richness. Both relationships weakened at higher elevations, perhaps demonstrating that there is a decreased capacity for resilience to stressors at lower elevations due to greater cumulative effects. Understanding interactions such as this is vital to managing ecosystems. Our findings provide empirical support for the need to further develop and employ more complex modelling techniques in environmental assessment and management.

Spatial assessment of water quality in Mananga River in Talisay City, Cebu, Philippines

This paper focuses on the degradation of water quality in the Mananga River and aims to analyze spatial changes for the recommendation for rehabilitation. The use of ArcGIS and JMP software allows for the assessment of water quality and the identification of the causes of the contaminants coming from probable sources that are near the river. These activities are mainly rural areas and businesses that could have affected the degradation of the quality of the water in the river. By generating spatial distribution maps and conducting rapid profiling, this paper provides recommendations for rehabilitation. The significance of this paper lies in contributing to decision-making processes and the formulation of protective laws that can help in stop the degradation of the water quality of the river. Limitation includes the quarterly frequency of the water monitoring of the river. The results of this paper suggest that the Mananga River does not meet the requirements for DENR Administrative Order 2016-08 for type A rivers. The spatial distribution maps generated were able to visualize and identify the anthropogenic activities that may be affecting the water quality of the river. The DO showed a value from 0.0011 mg/L – 18.800 mg/L, BOD has a value ranging from 1.000 mg/L to 81.500 mg/L, 4.000 mg/L – 325.980 mg/L for TSS, and pH showed values from 7.400 to 8.800. These findings emphasize the need for government intervention and the development of automated river monitoring systems to facilitate testing and rehabilitation efforts.

Histological Based Environmental Monitoring of the Lower Nun River: Using the Histo-morphometry of Kidney, Gills, Liver, and Testes of Coptodon zillii

It is an ecotoxicological study aimed at using chemical and bio-monitoring methods to pollution status of the Lower Nun River (LNR) basin using the histo-morphometry of the Liver, Kidney, Gills, and the Testes of Coptodon zillii. Based on literature review on the environmental burdens of the LNR, the following Target Chemicals (TC) were chosen for the study: Cadmium (Cd), Chromium (Cr), Copper (Cu), Nickel (Ni) and Lead (Pb). The study involved the sampling of water, sediment and feral fish from two stations along the LNR, Peremabiri (PER) and Igbomotoru(IGB) – Experimental sites.Water and sediment samples were analyzed to ascertain the physico-chemical concentrations of potential contaminants, while the harvest fish organs of liver, kidney, gills and testes were subjected to histological study to ascertain the exposure effect. Control fishes were harvested from African Aqua-culture Centre (ARAC) – Reference Site. Analyzed sediment and water values were used to evaluate Environmental Water Quality Index (EWQI) and sediment quality, while the fish organs were analyzes and used for pollution certification and stratification. Study results showed that EWQI of PER was poor (41.9); sediment quality showed that Cr, CU and Pb were above the Maximum Allowable Toxicant Concentration (MATC) for fresh water body. Fish from IGB showed worse lesion prevalence and organ histopathologic Index (Iorg) when compared to PER, with ARAC having the best outcome. The environmental pollution status (EPS) LNR was normal at PER and was slightly polluted at IGB. The study gave credence to the use of histology as a biomarker to assess sublethal effects of environmental stressors, and in determination of the pollution status.

A synergic approach using the model and remote sensing data for flood monitoring in under-observed transboundary rivers

ABSTRACT The southern plain of Nepal recognized as the ‘granary of Nepal’, confronts recurrent monsoon-induced flooding, posing a substantial threat to its pivotal role as a major agricultural contributor to the national economy. As an analysis, this study employs advanced satellite imagery to delineate historical floods in nine flood-prone transboundary basins and compares the rainfall-induced model-based inundation in the West Rapti Basin (WRB) to validate the result. The extent of flooding was mapped between 2015 and 2022 using Sentinel-1 Synthetic Aperture Radar data processed on Google Earth Engine. Hydrodynamic modelling centred on the WRB, incorporated daily measured precipitation data with varying return periods over a 10 m resolution digital elevation model generated through an in situ survey. The model was calibrated for the August 2017 flood event with Nash–Sutcliffe efficiency greater than 70% and validation reasonably with satellite-derived flood maps with Cohen's Kappa value of 0.58 and an overall accuracy metric of 0.84. This synergic approach integrates climatology, remote sensing data, and hydraulics to monitor transboundary river floods in Nepal where precise hydro-meteorological data are limited, thus, offering continuous all-weather monitoring.

State of the World's Rivers

In this review, we thoroughly analyze the state of global rivers, focusing on their physical and ecological characteristics as well as management strategies. The review results have helped us generate four recommendations. Firstly, rivers should be managed under a legally binding global accord at the basin level. Secondly, challenges related to river pollution and inappropriate project implementation can be mitigated by adopting newly defined strategic environmental assessments and the United Nations System of Environmental Economic Accounting. Thirdly, we need data from the latest scientific sources, such as geospatial sources, to better understand rivers at different scales as composite systems. The last recommendation calls for taking into account climate change concerns in river management approaches. We also outline a proposition for developing a river monitoring and assessment program in order to perform comprehensive and planet-wide river assessment. The article elaborates on the strategies for achieving these recommendations.

A Hybrid Method for Designing Sustainable River Monitoring Networks Using Fuzzy Logic Site Selection and Genetic Algorithm Optimization

A Hybrid Method for Designing Sustainable River Monitoring Networks Using Fuzzy Logic Site Selection and Genetic Algorithm Optimization

Framework for UAV-based river flow velocity determination employing optical recognition

The determination of river velocity is important for hydromorphological analyses and river monitoring systems. Indirect measurements of river velocity using videos recorded by unmanned aerial vehicles (UAV) allow fast and cost-effective processing of information about the river stretch. This paper presents a method for computing flow velocity of the river surface using deep supervised model RAFT to determine the optical flow in combination with image pre-processing by convolutional operations. Moreover, the windiness coefficients and variance score were proposed to evaluate reliability of the collected data and the obtained results of optical flow detection. Various image pre-processing techniques were applied, namely the selection of the analysed area and the number of convolutional operations to select the one with the lowest variance score. This score represents the consistency of the river flow velocity during the video and can be used to filter out unreliable results. The numerical experiments were performed using the videos and directly measured velocity values of 4 shallow rivers in Lithuania collected during the field surveys. The optical velocity estimation method showed good correspondence to the directly measured values for the velocity range from 0 m/s to 0.8 m/s in the points with low variance score up to 0.192 that represents the first quartile of the variance. The optical flow method tends to underestimate the velocity up to 0.5 m/s for the quartiles with the higher variance scores. It was shown that in most cases the lowest variance score value was obtained using pre-processing techniques without convolutional operations. However, the need to analyse various pre-processing techniques arises from the different origin of the objects moving on the river surface.

Adaptive Structural Design of River Monitoring Systems: Enhancing Environmental Monitoring Capabilities and Sustainability

The accelerating degradation of river ecosystems due to pollution necessitates the innovation of River Monitoring Systems (RMS) to protect these critical waterways. This research presents a novel design for adaptive RMS camera structures, aimed at enhancing monitoring capabilities and addressing the limitations of current systems. Highlighting the essential role rivers play in sustaining biodiversity, our study underscores the severe consequences of pollution, as exemplified by the deteriorating condition of Malaysia’s Klang River. We identify the need for a flexible RMS structure to overcome challenges such as excessive weight, corrosion susceptibility, and maintenance difficulties. Our methodology integrates advanced 3D Drawing Software for structural design, Fusion 360 for weight analysis, and a combination of manual calculations and simulations for vibration analysis. The findings reveal that Carbon Fiber Reinforced Polymers (CFRP) are the optimal material choice, offering an excellent balance of performance and cost-efficiency. This research successfully develops a structurally sound, user-friendly, and dynamically stable RMS camera structure, significantly advancing environmental monitoring practices. The study's contributions provide a foundation for future innovations in adaptive structural design, with broad implications for safeguarding river ecosystems worldwide.

Evaluation of LoRa Network Performance for Water Quality Monitoring Systems

Conserving water resources from scarcity and pollution is the basis of water resource management and water quality monitoring programs. However, due to industrialization and population growth in Malaysia, which have resulted in poor water quality in many areas, this program needs to be improved. A smart water quality monitoring system based on the internet of things (IoT) paradigm was designed to analyze water conditions in real time and enable effective water management. Long-range (LoRa) application of the low-power, wide-area networking concept has become a phenomenon in IoT smart monitoring applications. This study proposes the implementation of a LoRa network in a water quality monitoring system-based IoT approach. The LoRa nodes were embedded with measuring sensors pH, turbidity, temperature, total dissolved solids, and dissolved oxygen, in the designated water stations. They operate at a transmission power of 14 dB and a bandwidth of 125 kHz. The network properties were tested with two different antenna gains of 2.1 dBi and 3 dBi, with three different spread factors of 7, 9, and 12. The water stations were located on the Sungai Pantai and Sungai Anak Air Batu rivers on the Universiti Malaya campus, Malaysia. Following a dashboard display and K-means analysis of the water quality data received by the LoRa gateway, it was determined that both rivers are Class II B rivers. The results from the evaluation of LoRa performance on the received strength signal indicator, signal noise ratio, loss packet, and path loss at best were −83 dBm, 7 dB, <0%, and 64.41 dB, respectively, with a minimum received sensitivity of −129.1 dBm. LoRa has demonstrated its efficiency in an urban environment for smart river monitoring purposes.

Research on UAV Remote Sensing in River Monitoring

Research on UAV Remote Sensing in River Monitoring

A critical review of biomonitoring in East African rivers: fostering community-based collaboration for environmental change observation

The contribution of citizen scientists to environmental monitoring is notably increasing significantly. Governments worldwide establish Water Users Associations (WUAs) as a good practice model to implement Integrated Water Resource Management (IWRM) at local levels. These associations target different stakeholders depending on the expected outcome. However, their effectiveness, especially in East Africa, can only be determined case by case. In Kenya, Water Resources Users Associations are registered, voluntary community groups whose members are water users and land owners. Similarly, in Uganda, community-based initiatives exist, especially along degraded rivers, involving cooperation between local communities and regional water authorities. On the contrary, it has been reported that in Tanzania, many community initiatives created become non-functional within 2–3 years of induction. In general, the main responsibility of Water Users Associations or its equivalent is to manage and conserve water resources for sustainable uses. In most cases, water quality monitoring by communities through citizen science is limited to the visual appearance of water in the river channel. While this can indicate the water’s esthetic value, it is insufficient for assessing the ecological status of rivers, which is influenced by a variety of physical, chemical, biological, and socioeconomic factors. The use of bioindicators has been advocated as a feasible method for community-based water quality river monitoring. Therefore, this review explores the commonly used bio-indicators and bio-assessment tools for river health assessment and their complexities when using a biomonitoring community-based approach through citizen science. Tolerance and intolerance macroinvertebrate and fish metric protocols that utilize identification keys have been recommended. These protocols are designed to be user-friendly and require minimal taxonomic expertise, making them easy for community volunteers to use with minimal basic training. The sustainability of these citizen science initiatives relies on the motivation of volunteers, the frequency of monitoring activities, and collaboration with researchers and government agencies. These initiatives not only facilitate environmental monitoring but also foster community engagement and awareness regarding the ecological status of rivers, thereby addressing knowledge and data gaps necessary for effective policy-making. This approach provides a practical model for environmental stewardship and participatory resource management in East Africa.

Effect of Integrated Landscape Characteristics Around Chaohu Lake on River Water Quality Based on Watershed Units

Considering the impact of differences in watershed characteristics on river water quality, with the Chaohu Lake Basin as the research object, based on the data of water quality, meteorology, topography, soil, and remote sensing images of the river monitoring points from October 2019 to September 2020, the watershed unit at each monitoring point was divided through digital terrain analysis, and the comprehensive landscape characteristics based on the watershed unit were explored through the comprehensive use of correlation analysis, redundancy analysis, and multiple regression analysis to investigate the influence of comprehensive landscape characteristics based on watershed units (including land use, climate, topography, soil, etc.) on the water quality of rivers around Chaohu Lake. The results showed that:① the water quality of rivers around Chaohu Lake had large spatial differences, with the main pollutants being total nitrogen and ammonia nitrogen. Most of the rivers had total nitrogen concentrations exceeding the Class V water quality standards, and the areas with serious nitrogen and phosphorus pollution were concentrated in the urban area of Hefei and the surrounding rivers, as well as in the middle and lower reaches of the Fengle and Hangbu Rivers. ② The comprehensive landscape characteristics of the watershed unit had a significant impact on the river water quality. Among them, the proportion of built-up land, the density of patches, the dispersion and juxtaposition index, and the Shannon diversity index were positively correlated with the water quality indicators, whereas the proportion of forest and grassland and the spreading index were negatively correlated with the water quality indicators. ③ In different seasons, the effect of the integrated landscape characteristics of the watershed unit on river water quality was stronger in the wet season than in the dry season, which was mainly caused by the difference in precipitation in the dry and wet seasons.

The Use of Unmanned Aerial Systems for River Monitoring: A Bibliometric Analysis Covering the Last 25 Years

Cutting-edge technology for fluvial monitoring has revolutionised the field, enabling more comprehensive data collection, analysis, and interpretation. Traditional monitoring methods were limited in their spatial and temporal resolutions, but advancements in remote sensing, unmanned aerial systems (UASs), and other innovative technologies have significantly enhanced the fluvial monitoring capabilities. UASs equipped with advanced sensors enable detailed and precise fluvial monitoring by capturing high-resolution topographic data, generate accurate digital elevation models, and provide imagery of river channels, banks, and riparian zones. These data enable the identification of erosion and deposition patterns, the quantification of sediment transport, the evaluation of habitat quality, and the monitoring of river flows. The latter allows us to understand the dynamics of rivers during various hydrological events, including floods, droughts, and seasonal variations. This manuscript aims to provide an update on the main research themes and topics in the literature on the use of UASs for river monitoring. The latter is achieved through a bibliometric analysis of the publication trends and identifies the field’s key themes and collaborative networks. The bibliometric analysis shows trends in the number of publications, number of citations, top contributing countries, top publishing journals, top contributing institutions, and top authors. A total of 1085 publications on UAS monitoring in rivers are identified, published between 1999 and 2023, showing a steady annual growth rate of 24.44%. Bibliographic records are exported from the Web of Science (WoS) database using a comprehensive set of keywords. The bibliometric analysis of the raw data obtained from the WoS database is performed using the R software. The results highlight important trends and valuable insights related to the use of UASs in river monitoring, particularly in the last decade. The most frequently used author keywords outline the core themes of UASs monitoring research and highlight the interdisciplinary nature and collaborative efforts within the field. “River”, “topography”, “photogrammetry”, and “Structure-from-Motion” are the core themes of UASs monitoring research. These findings can guide future research and promote new interdisciplinary collaborations.