River Level Research Articles

Utilization of Tamarind Seed Biocoagulant as Learning Material for Water Purification Practicum in Colloidal System

Discharging wastewater directly into the environment can harm nearby organisms. Efforts to increase environmental awareness, especially about sewage, can be started with educational activities. The study investigates the correlation between chemistry material and water purification using tamarind seed bio coagulant, assessing its feasibility for chemistry experiment design in schools. This research uses descriptive qualitative research. This study described data from observations of water purification using tamarind seedcoagulant, literature studies on chemistry practicum, and interviews with two chemistry teachers and two high school students.The results showed that the relationship between colloidal material and the experiment was to determine the types of products that contain colloidal systems in daily life and the properties of colloids. The results of the chemical parameter test revealed significant changes in the pH levels of river, laundry, and batik wastewater samples, with batik coloring waste showing the most significant changes. The organoleptic test results revealed significant changes in the color, odor, and sediment of batik dyeing wastewater. The protein in tamarind seeds can destabilize substances that cause turbidity. Based on literature studies and interviews, tamarind seed bio coagulant is feasible as a teaching material for chemistry practicum on colloidal system.

Flash floods in Mediterranean catchments: a meta-model decision support system based on Bayesian networks

Natural disasters, especially those related to water—like storms and floods—have increased over the last decades both in number and intensity. Under the current Climate Change framework, several reports predict an increase in the intensity and duration of these extreme climatic events, where the Mediterranean area would be one of the most affected. This paper develops a decision support system based on Bayesian inference able to predict a flood alert in Andalusian Mediterranean catchments. The key point is that, using simple weather forecasts and live measurements of river level, we can get a flood-alert several hours before it happens. A set of models based on Bayesian networks was learnt for each of the catchments included in the study area, and joined together into a more complex model based on a rule system. This final meta-model was validated using data from both non-extreme and extreme storm events. Results show that the methodology proposed provides an accurate forecast of the flood situation of the greatest catchment areas of Andalusia.

Синоптические условия повышения уровня рек на юге Иркутской области и Забайкалья в июле 2023 года

The article discusses natural and anthropogenic factors of rising river levels and associated environmental consequences, existing probabilistic estimates of the amount of floods using various hydrological and climate models. Orographic, climatic and circulation features of the occurrence of floods in the Irkutsk region are identified. A study was carried out of the circulation and weather factors of increasing the intensity and duration of precipitation in early July 2023, which was accompanied by an increase in river levels in the south of the Irkutsk region and the Baikal region. The dynamics of atmospheric processes near the Earth's surface and at the levels of isobaric surfaces AT850 hPa, AT-700 hPa, AT-500 hPa and AT-300 hPa, reflecting the conditions of surface and highaltitude cyclo- and frontogenesis, are analyzed. The contribution of advective flows of heat and moisture, mesojets in the middle troposphere and upper tropospheric jet currents in increasing the amount and duration of atmospheric precipitation is highlighted. A significant contribution to the increase in precipitation and the rise in river levels was made by moist air masses moving in the lower troposphere from the water area of the lake. Baikal, in the middle troposphere from the Yellow Sea. The time of passage of the flood and the height of the rise in the level of individual watercourses as a result of the rains were estimated.

Mixed lanthanide–organic frameworks with borono groups for colorimetric detection of excess fluoride levels in rivers

The colorimetric visual detection of fluoride ions in river was realized through weak double dynamic interactions between mixed lanthanide-organic framework and fluoride ions.

Analysis of the level regime of the Iga river of the Nizhnevartovsk district of the Khanty-Mansi autonomous district Siberia

Obtaining hydrological information in general, as well as determining the estimated water levels on water bodies, are mostly associated with the construction of hydraulic structures that allow the use of water for the needs of the national economy. The oil production industry is widely developed on the territory of the Khanty-Mansi Autonomous Okrug. Often oil and gas fields are located in sparsely populated areas where there is no information about the hydrological regime of watercourses. In order to ensure the safe operation of construction projects, there is a need to obtain hydrological information for crossed or nearby watercourses. Thus, this type of work is performed almost everywhere to solve similar problems. In this article, studies of the Iga River, located in the right bank of the Ob River, were carried out. To identify the degree of influence of the river level in different periods of the year, hydrological calculations of spring floods and rain floods were performed. Based on the calculations, a graph of the relationship between costs and levels was constructed. To determine the possible backup of the level of the Ob River to the level regime of the Iga River during periods of high waters, the levels of the Ob River were determined. Based on the analysis of joint levels, a conclusion was made about the influence of the Ob on the hydrological regime of the Iga River

Analysis of the Yellow River water and sediment monitoring data

Abstract Graphics are drawn about the sediment content, water flow, and water level of the Yellow River with time. A cluster scatter plot of sand content is made with changes over time. Using variance analysis of a factor, it is concluded that sediment content is affected by two variables month and year. By studying the changing pattern of water-sand flux, the timing diagram of the water and sediment flux of the Yellow River with time is drawn. The flux of water and sand is predicted for the next two years. According to the prediction results, the optimal sampling and monitoring scheme is developed.

Characterization of the recent (2019–2022) La Plata Basin hydrological drought from a centennial-scale perspective

Several major rivers within the La Plata Basin (LPB), the third largest basin in the world, have experienced record-low water levels between 2019 and 2022, with significant impacts for the economy of the region. This hydrological drought originated from a precipitation deficit over the headwaters of the Paraná, Paraguay, and Uruguay rivers, in response to an unusual multi-year La Niña episode. The objective of this study is to characterize the hydrological drought and quantify its unusualness by analyzing a set of indices based on daily, monthly, and annual streamflow and water levels of the main rivers of LPB, using centennial records. The results indicate that the recent hydrological drought was unprecedented in the context of the past 50 years in terms of severity and duration, featuring extreme drought conditions and duration over 25 months. The atmospheric drivers of the drought are analyzed, and future perspectives for water management are discussed.

Beyond Exact Repeat Missions: Embracing Geodetic Altimetry for Inland Water Monitoring and Modeling

Satellite radar altimetry has become an essential tool for hydrological research over the past 2 decades. Unlike imagery that quantifies the water dynamics from the horizontal dimension, altimetry observations deliver vertical information, which is crucial for hydrological research. Geodetic mission (GM) altimetry data, characterized by long repeat periods compared to exact repeat missions, have been underutilized in hydrology. This paper aims to advocate for integrating geodetic altimetry data into inland water research and bring awareness to its potential applications. We demonstrated the values of GM data from CryoSat-2, Saral/AltiKa, Jason-1, and Jason-2 through 3 applications: (a) large-scale lake monitoring for improved understanding of regional and global hydrological cycles, (b) retrieval of local geoid undulations over large lakes to enhance the precision of individual water level observations, and (c) mapping river longitudinal profiles and construction of time series of river levels. We believe that the findings of this study will pave the way for more comprehensive utilization of geodetic altimetry data in diverse hydrological applications, ultimately advancing inland water altimetry.

Characterization of larval habitats of Anopheles (Nyssorhynchus) darlingi and associated species in malaria areas in western Brazilian Amazon.

Anopheles darlingi is the most efficient vector of malaria parasites in the Neotropics. Nevertheless, the specificities of its larval habitats are still poorly known. Characterize permanent larval habitats, and population dynamics of An. darlingi and other potential vectors in relation to climate, physicochemical variables, insect fauna and malaria cases. A 14-month longitudinal study was conducted in Porto Velho, Rondônia, western Brazilian Amazon. Monthly, 21 permanent water bodies were sampled. Immature anophelines and associated fauna were collected, physicochemical characteristics, and climate variables were recorded and analyzed. Five types of habitats were identified: lagoon, stream, stream combined with lagoon, stream combined with dam, and fishpond. A total of 60,927 anophelines were collected. The most abundant species in all habitats were Anopheles braziliensis and An. darlingi. The highest density was found in the lagoon, while streams had the highest species richness. Abundance was higher during the transition period wet-dry season. There was a lag of respectively four and five months between the peak of rainfall and the Madeira River level and the highest abundance of An. darlingi larvae, which were positively correlated with habitats partially shaded, pH close to neutrality, increase dissolved oxygen and sulphates. The present study provides data on key factors defining permanent larval habitats for the surveillance of An. darlingi and other potential vectors as well as a log-linear Negative Binomial model based on immature mosquito abundance and climate variables to predict the increase in the number of malaria cases.

Contributions of rising mean river level of the Río de la Plata estuary on recorded changes in positive storm surges

Contributions of rising mean river level of the Río de la Plata estuary on recorded changes in positive storm surges

Estimating the Total Annual Economic Loss Attributed to Climate Variations in Agusan Marsh Wildlife Sanctuary: The Case of Fishing and Farming Activities in Talacogon, Agusan del Sur, Philippines

The cost of alterations in the quantity or quality of ecosystem services (ES) that are traded on commercial markets can be approximated with the aid of a revealed preference approach, such as the market price method. This study used the market price method to estimate the total annual economic loss from the changes in the demand and supply of fish and crops due to climate variations in Agusan Marsh Wildlife Sanctuary (AMWS). Household interviews were done in the municipality of Talacogon using four sets of structured survey instruments to gather information such as the quantity supplied monthly by fisherfolks and farmers as well as the quantity demanded by residents at different market prices. The consumer surplus and producer surplus during peak and off-seasons were calculated to estimate the annual loss in economic benefits to consumers and producers. The most commonly consumed and produced products in terms of fishing and farming were Channa striata and Oryza sativa L., respectively. Climate variations have an impact on both fishing and farming commercial activities. During the dry season (March to August), fewer fish are caught due to low water levels in rivers and lakes, while crops cannot be planted during the wet season (September to February) because a lot of land areas are flooded. The total annual economic loss was calculated at PHP 99,974.50. This estimated monetary value can be a basis for decision-makers and concerned stakeholders to efficiently allocate funds for sustainable programs to capacitate the fisherfolks and farmers to increase adaptation mechanisms for climate variations.

An integrated climate and water resource climate service prototype for long term water allocation in the Upper Yellow River region of China

Water Resourcing in China has historically been a complex issue requiring the ability to deal with regular floods, droughts and diverse water needs. Climate change represents another challenge to this sector, albeit one that is not traditionally considered by water managers. In this sector in China water management is predominantly based on historic, seasonal and annual forecast data while multi-annual and (multi-)decadal data are seldom used. In this paper, we present the co-development of a climate service prototype designed to provide water managers with insights into the impacts of climate change on the Upper Yellow River region for the next century. The paper is an outcome from our project that encouraged water resource planners and water resource managers to utilise long-term climate information to understand the uncertainties and the challenges our changing climate is likely to have in the region. Using an interdisciplinary team and adopting a user-centred, co-production approach, a prototype web-based data visualisation tool was developed. The development of the prototype was based on a design specification constructed from the findings of detailed interviews that allowed it to be developed and tested under SARS-CoV-2 pandemic restrictions that prevented the typical development process to be undertaken. The developed prototype presents climate information and communicates uncertainties regarding climate change in the remainder of the century through data sets that are typically used by the water sector in China in a simple, easy to understand style. Models that estimate river levels under different extraction scenarios and results about estimated river level and flow, and flood risk are also presented. The prototype was shown to be successful, as key messages relating to the impact of climate change and the challenges for water resource management could be effectively communicated through the tool interface. Practical implicationsUnderstanding the impacts of climate change on water resourcing is complicated and multifaceted. There is a need for better data about what water there is and how it is moving around between and within catchments. Estimates of past, present and future climate variables along with historical measurements of river flow can be used to help visualise some of the uncertainties and changes that may happen in the next 50 years. In addition, there is a need to understand changing water demands and water resource management practices. Current water resource management practices are based on historical conditions and assumptions that are less likely to hold true in a more variable and warmer climate. Communicating how future changes will impact future water resourcing is critical to water resources in a changing climate (Belcher et al. 2018).This research outlines the construction of a tool to visualise the impacts of climate change on water availability in part of China that is typically water scarce, using models developed using the Soil Water Assessment Toolkit (SWAT). A model of the Upper Yellow River (UYR) was developed to demonstrate the impact of climate change on river levels in the catchment based on climate variables. The rainfall-runoff model was based on climate predictions from the CMIP5 assessment HadGEM3-GC3.05 climate model and incorporated information about water resource allocations for different administrative regions of the catchment The general climate trend for the region is that it is expected to become significantly warmer. The total amount of precipitation is likely to be about the same, and yet it is expected that overall, the catchment will become significantly drier over time as winter shortens and summer lengthens. The outputs from the model reflect the changes in climate variables. The uncertainties were communicated via a Web based tool. Water resource managers in China helped to coproduce the tool by participating in workshops and providing feedback on prototypes. The workshops helped scientists and water resource managers to communicate about climate change impacts on water resources and water resource management.

The feeding habits of the Amur whitefish Coregonus ussuriensis in the Amur River, China

To study their feeding habits, Coregonus ussuriensis samples were collected seasonally in the Amur River, China. A total of 574 samples were collected, including 200 individuals with empty stomachs. The stomach contents of the remaining 374 samples were identified, counted, weighed, and analyzed. The results showed that the vacuity rate of Coregonus ussuriensis was 34.84% in total; the rates in summer and autumn were higher than in spring and winter. Prey items could be divided into three categories: fish, benthos, and mammals, with 62 taxonomic units. Of these, fish had the highest relative importance index (IRI), followed by benthos and mammals. Specifically, Exopalaemon modestus was the dominant species among the food species of Coregonus ussuriensis, and unidentified fish, Hydropsyche sp., Hemiculter leucisculus, Abbottina rivularis, and Saurogobio dabryi were important species. The average repletion index (RI, %) of Coregonus ussuriensis was highest in autumn (1.86), followed by winter (1.40), summer (1.26), and spring (1.02). The main food of Coregonus ussuriensis was benthos in spring and autumn, and fish in summer and winter. Cluster analysis showed that, according to the similarity level of the bait biological composition, the fork length group samples of Coregonus ussuriensis could be divided into three groups: 210–330 mm, 330–450 mm, and >450 mm. The highest IRI% of feed organisms in these three groups of samples were fish (73.67%), benthos (75.12%), and benthos (94.46%), respectively. It can be observed that with the growth of the fork length of Coregonus ussuriensis, the importance of benthos in its diet increases. The results of an RDA analysis on the relationship between main bait organisms and various factors indicated that season, river level, river width, and fish size have a significant impact on bait organisms and a positive or negative impact on the quality scores of some bait species. This study filled the gap in biological research on the feeding ecology of Coregonus ussuriensis and laid a research foundation for ecological research on this species and its resource protection and aquaculture.

Droughts and controlled rivers: how Belo Monte Dam has affected the food security of Amazonian riverine communities

SummaryThe Neotropics have vast river catchments with untapped hydroelectric potential, but there are multiple expected negative impacts of dams, including those on local food security and livelihoods. Yet, monitoring of dam effects on subsistence is rare, particularly during initial implementation. Our study assessed changes in human fish consumption near the Belo Monte Dam in the Brazilian Amazon during the period 2012–2021, which covers construction, operation and a severe El Niño-induced drought. Over time, fish became less common and were consumed in smaller amounts, even though fewer people shared meals. The largest changes occurred between 2013 and 2016 (post-construction but prior to full operation), resulting in a downward trend in fish consumption, particularly during the drought season. Adding more fish species to the diet did not increase consumption per person. These changes in fish consumption suggest that they stem from environmental impacts of the project (e.g., reduced river level), despite secondary effects from climatic events. These findings underscore the urgent need for comprehensive assessments of the social and ecological impacts of large infrastructure projects in the Amazon, along with sustainable and equitable management strategies to ensure food security and meet the needs of local communities.

Smart Disaster Mitigation: The Role of IoT and Machine Learning

This prototype output research has the aim of creating a dashboard that is used to monitor river water levels. The dashboard created will display data in real-time and prediction results. The use of the dashboard is to minimize the risk in the event of flooding caused by river overflow. The way this prototype works is to take data from sensors that have been installed at several points. The recorded data will be stored in a database using the working principles of the Internet of Things. For predictions, machine learning is used to produce future river water level figures. The machine learning used is using time series regression with rainfall input and river water level output. Long-term output data is needed, therefore to forecast future rainfall the Hybrid method is used. Data generated from sensors as well as from prediction results are stored in one database. From the database, data visualization is displayed along with important figures used for river overflow intelligence. Therefore, the dashboard is very useful for people living around the river flow.

Cross-domain flood risk assessment for smart cities using dynamic knowledge graphs

This paper investigates the usage of knowledge graphs to bridge the gap between current data silos in deriving a holistic perspective on the impact of flooding. It builds on the idea of connected digital twins based on the World Avatar dynamic knowledge graph to deploy an ecosystem of autonomous software agents to continuously ingest new real-world information and operate on it. Multiple publicly available yet isolated data sources, including geospatial building information and property sales data as well as real-time river levels, weather observations, and flood warnings, are connected to instantiate a semantically rich ecosystem of knowledge, data, and computational capabilities to provide cross-domain insights in projected flooding events and their potential impact on population and built infrastructure. The extensibility of the proposed approach is highlighted by further integrating power, water, and telecoms infrastructure as part of the very same system, in order to analyse flood-induced asset failures and their propagation across networks. The World Avatar promotes evidence-based decision making during several disaster management phases, supporting both tactical and strategic risk assessments, which supports the United Nations Sustainable Development Goal 11 to improve the assessment of vulnerability, exposure, and risk of communities imposed by flooding events.

Historical flood reconstruction in a torrential alpine catchment and its implication for flood hazard assessments

Flood marks and descriptions of past floods in archival records are valuable sources of information to complement the often short – and sometimes lacunary – systematic records provided by gauge stations, especially in mountain and smaller catchments for which the network of recording stations is still fragmentary. Yet, historical accounts of floods are only rarely used to calculate discharge during past floods and to complement estimates of flood frequency and magnitude. This is because the definition of flood types and the reconstruction of past topography of the now urbanized riverscapes is often challenging. Here, we employ an approach by which we combine (i) archival (1331–1965) and continuous gauge (1966–2020) records of past floods, (ii) information on past topography and mitigation measures found on topographic maps and contemporary documents specifying the dimensions of contemporary engineering plans and (iii) a hydraulic model to derive a c. 700-year history of flood activity and related discharges for the Saltina River, Brig-Glis (Valais, Swiss Alps). Periods of increased flood activity match with flood-rich episodes in the Rhone River and high lake levels at Lago Maggiore (Ticino), and the time series passes stationarity tests since at least 1828 CE. For a total of 32 floods occurring prior to the installation of the gauge station in 1966, we provide discharges following a descriptive classification, and demonstrate that major floods occurred in 1755 (∼140 m3s−1), 1828 (∼160 m3s−1), and 1921 (∼120 m3s−1). We also evidence that the construction of mitigation measures has contributed to a reduction in flood frequency, but that the occurrence of extraordinary floods has again been on the rise since the early 21st century.

A methodology for evaluating the relative pollution level of metal pollution in surface sediments of rivers based on the statistical results of relevant literatures covering world-wide rivers

Due to the intervention of human activities, the background values of riverbed sediment exhibit spatiotemporal variability, which can affect the accuracy of risk assessment results. Using risk assessment that do not rely on background values is an executable alternative to avoid such problems. In this study, a relative pollution level assessment (RPLA) method which was based on the statistical results of relevant literatures was proposed. This method includes a four-step data processing procedure to extract the evaluation indexes of relative pollution degree of pollutants in environment and a series of relative pollution status assessment methods to evaluate the overall relative pollution level and regional difference of world-wide rivers. To demonstrate how to use RPLA method, 310 relevant literatures covering world-wide rivers were selected. And the ambient background value (x̅), the world-wide threshold values (WWTV) and the relative pollution grades (LEVEL I ∼ IV) of 9 target metals (Cr, Ni, Cu, Zn, As, Cd, Pb, Sb and Tl) in riverbed surface sediments of world-wide rivers were extracted and used for evaluation. Moreover, the stability and applicability of RPLA method were evaluated. Results show that the evaluation results of RPLA method are robust and comparable with traditional evaluation method.

A Dual-Threshold Algorithm for Ice-Covered Lake Water Level Retrieval Using Sentinel-3 SAR Altimetry Waveforms.

Satellite altimetry has been proven to measure water levels in lakes and rivers effectively. The Sentinel-3A satellite is equipped with a dual-frequency synthetic aperture radar altimeter (SRAL), which allows for inland water levels to be measured with higher precision and improved spatial resolution. However, in regions at middle and high latitudes, where many lakes are covered by ice during the winter, the non-uniformity of the altimeter footprint can substantially impact the accuracy of water level estimates, resulting in abnormal readings when applying standard SRAL synthetic aperture radar (SAR) waveform retracking algorithms (retrackers). In this study, a modified method is proposed to determine the current surface type of lakes, analyzing changes in backscattering coefficients and brightness temperature. This method aligns with ground station observations and ensures consistent surface type classification. Additionally, a dual-threshold algorithm that addresses the limitations of the original bimodal algorithm by identifying multiple peaks without needing elevation correction is introduced. This innovative approach significantly enhances the precision of equivalent water level measurements for ice-covered lakes. The study retrieves and compares the water level data of nine North American lakes covered by ice from 2016-2019 using the dual-threshold and the SAMOSA-3 algorithm with in situ data. For Lake Athabasca, Cedar Lake, Great Slave Lake, Lake Winnipeg, and Lake Erie, the root mean square error (RMSE) of SAMOSA-3 is 39.58 cm, 46.18 cm, 45.75 cm, 42.64 cm, and 6.89 cm, respectively. However, the dual-threshold algorithm achieves an RMSE of 6.75 cm, 9.47 cm, 5.90 cm, 7.67 cm, and 5.01 cm, respectively, representing a decrease of 75%, 79%, 87%, 82%, and 27%, respectively, compared to SAMOSA-3. The dual-threshold algorithm can accurately estimate water levels in ice-covered lakes during winter. It offers a promising prospect for achieving long-term, continuous, and high-precision water level measurements for middle- and high-latitude lakes.

A new integrated prediction method of river level based on spatiotemporal correlation

A new integrated prediction method of river level based on spatiotemporal correlation