River Sediment Load Research Articles

Monthly Suspended Sediment Load Estimation Using Artificial Neural Network and Traditional Models in Krishna River Basin, India

The measurement of sediment yield is essential for getting the information of the mass balance between sea and land. It is difficult to directly measure the suspended sediment because it takes more time and money. One of the most common pollutants in the aquatic environment is suspended sediments. The sediment loads in rivers are controlled by variables like canal slope, basin volume, precipitation seasonality and tectonic activity. Water discharge and water level are the major controlling factor for estimate the sediment load in the Krishna River. Artificial neural network (ANN) is used for sediment yield modeling in the Krishna River basin, India. The comparative results show that the ANN is the easiest model for the suspended sediment yield estimates and provides a satisfactory prediction for very high, medium and low values. It is also noted that the Multiple Linear Regressions (MLR) model predicted an many number of negative sediment outputs at lower values. This is entirely unreality because the suspended sediment result can not be negative in nature. The ANN is provided better results than traditional models. The proposed ANN model will be helpful where the sediment measures are not available.

River suspended sediment load prediction based on river discharge information: application of newly developed data mining models

ABSTRACTSuspended sediment load (SSL) is one of the essential hydrological processes that affects river engineering sustainability. Sediment has a major influence on the operation of dams and reservoir capacity. This investigation is aimed at exploring a new version of machine learning models (i.e. data mining), including M5P, attribute selected classifier (AS M5P), M5Rule (M5R), and K Star (KS) models for SSL prediction at the Trenton meteorological station on the Delaware River, USA. Different input scenarios were examined based on the river flow discharge and sediment load database. The performance of the applied data mining models was evaluated using various statistical metrics and graphical presentation. Among the applied data mining models, the M5P model gave a superior prediction result. The current and one-day lead time river flow and sediment load were the influential predictors for one-day-ahead SSL prediction. Overall, the applied data mining models achieved excellent predictions of the SSL process.

Применение ГИС-технологий для выявления потенциальных очагов возникновения опасных гидрологических явлений (на примере гор Южной Сибири)

Captured evidences of debris flows declare the obvious changes of mudflow regime in the West Sayan midland and lowland areas and require the need to review the levels of regional hazard risk. The analysis of natural and man-made preconditions of debris flows increasing revealed the priority impact of the last ones. The absence of meaningful deviations from the normal of precipitation intensity targets was identified. It has been found that small debris flows on the middle grade of steepness slopes are a result of the combined activity of the different economic activities. Surface mining, associated road construction work, forming considerable amount of free of loose material, and active logging as well all contribute to emergence of debris flows hazard in basins of small rivers. The disruption of plant cover stabilizing role lead to the intensification of slope erosion processes. Taiga belt degradation was caused mainly by the large logging lasted in the region more than half a century. It is shown, that a slight decrease in the general forest cover has led to a serious changes of forest structure, which affects the intensity of slope erosion processes and increase in the sediment loads in rivers for several decades. A comprehensive approach to identify potential hotbeds of debris flows was proposed. It comprises the use of remote techniques in detection of human impact areas, morphometric analysis of watersheds affected by a large anthropogenic disturbance, assessment of areas under transformation, analysis of the temporal variability of hydro-meteorological characteristics and landscape structure dynamics. Due to the lack of availability of cadastral information of vegetation, soil and slope characteristics at an appropriate scale there is a need for more field research in key areas aimed at updating of the existing database.

Alternate erosion and deposition in the Yangtze Estuary and the future change

The morphological changing trend of the Yangtze Estuary, the largest estuary of Asia, has become a focus of research in recent years. Based on a long series of topographic data from 1950 to 2015, this paper studied the erosion-deposition pattern of the entire Yangtze Estuary. An alternation between erosion and deposition was found during the past 65 years, which was in correspondence to the alternation between flood and dry periods identified by multi-year average duration days of high-level water flow (defined as discharge ≥ 60,000 m3/s, namely, D≥60,000) from the Yangtze River Basin. A quantitative relationship was further developed between the erosional/depositional rate of the Yangtze Estuary and the interpreting variables of yearly water discharge, D≥60,000 and yearly river sediment load, with contributing rates of 1%, 59% and 40%, respectively. Mechanism behind the alternate erosion and deposition pattern was analyzed by examining residual water surface slope and the corresponding capacity of sediment transport in flood and dry periods. In flood periods, a larger discharge results in steeper slope of residual water level which permits a greater capacity of sediment transport. Therefore, more bed materials can be washed to the sea, leading to erosion of the estuary. In contrast, flatter slope of residual water level occurs in dry periods, and deposition dominates the estuarine area due to the decreased capacity of sediment transport and the increased backwater effect of flood-tide. Coastal dynamics and estuarine engineering projects alter the local morphological changes, but slightly affect the total erosional/depositional rate of the whole estuarine region. Heavy sedimentation within the Yangtze Estuary after the impoundment of the Three Gorges Dam can be attributed to the reduced occurrence frequency of flood years due to water regulation by the dam, and largely (at least 36%–52%) sourced from the sea. Deposition is still possible to occur in the Yangtze Estuary in the future, because the multi-year average D≥60,000 is unlikely to exceed the critical value of 14 days/yr which corresponds to the future equilibrium state of the Yangtze Estuary, under the water regulation of the large cascade dams in the upper Yangtze. Nevertheless, the mean depositional rate will not surpass the peak value of the past years, since the total sediment load entering the Yangtze Estuary has presented a decreasing trend.

Sediment Transport and Its Impacts on Lake Kivu, Gihira Water Treatment Plant and Various Hydropower Plants along Sebeya River in Rwanda

Complex processes of sediment transport in a river impact on overall aquatic system and result in the productivity decrease of socio-economic development projects taking the river as a source of water. The present study was designed to estimate Sebeya river sediment load and assess its impacts on Lake Kivu, Gihira water treatment plant and various hydropower plants constructed in Sebeya catchment located in Western Province of Rwanda. Water samples were hand-collected from five different sampling points along Sebeya river during rainy and dry seasons. Laboratory analysis for turbidity, total suspended solids, sieve analysis for bed load materials and NPK content of water samples were conducted. The results revealed that the average turbidity was found to be high during rainy season compared to dry season. The same trend was found in total suspended solids concentrations. At all 5 sampling sites and during rainy season compared to dry season, the average mass flowrates of bed load materials were 7.84 and 2.96 kg/hr respectively. Sieve analysis results showed that all bed load sediments were mainly composed of high proportions of fine sand of more than 70% which adversely causes damages on hydropower turbines and the effect of high soil erosion rates on Gihira water treatment plant was traduced by high turbidity of raw water and excessive costs of reagents. At Sebeya outlet, nutrients load and high turbidity reduce significantly the aesthetic quality of Lake Kivu, having a harmful impact on recreation and tourism, aquatic life and affect the livelihoods of people living in the vicinity. Researchers recommend two options of reducing the amount of sediment load in Sebeya river: either to prevent soil erosion or to trap eroded sediment at the upstream of the hydropower and the water treatment plants. Assessing the sediment load fluctuations in Sebeya river is useful for water managers and planners to adjust operations accordingly at water treatment and hydropower plants.

Improving total sediment load prediction using genetic programming technique (Case Study: Malaysia)

Predicted total sediment load is usually used to identify the intensity of a sedimentation process. Currently, the existing available models to predict total load are mostly developed based on data collected from flumes, channels and rivers located in western countries. These models known as sediment transport model may not be valid to predict total sediment load of rivers in the tropics due to significant differences in the hydrological and sediment characteristics conditions. A new technique called Genetic programming (GP) technique is used to develop a new model to improve the prediction of total sediment load for rivers in tropical Malaysia. The new model named Evolutionary Polynomial Regression (EPR) model is compared with other three available sediment transport models using the different techniques including, Regression Equation, Modified Graf and Multiple Regression. Statistical analyses based on 82 data sets show the sediment transport model using this new technique perform well compare to other models.

Responses of river discharge and sediment load to climate change in the transboundary Mekong River Basin

AbstractClimate change is expected to alter streamflow and sediment load in the transboundary Mekong River Basin (MRB), thereby affecting aquatic ecosystem and people’s livelihoods. Thus, future decisions on sustainable management of water resources in the basin should take climate change impact into consideration. In this study, the responses of river discharge and sediment (total suspended sediment [TSS]) load to future climate change in the transboundary MRB have been investigated. The Soil and Water Assessment Tool (SWAT) model is used as a simulation tool, which has been carefully calibrated and validated against the observation data in the period of 1982–2005 before applying to evaluate the impact of climate change scenarios for the near‐future period of 2016–2040. The climate change scenarios, which are acquired from four different Regional Climate Models (RCMs) downscaled from the Hadley Centre Global Environmental Model version 2‐Atmosphere (HadGEM2‐AO), are applied in the present study. In regard to the effect of changing climate, the annual river discharge and TSS load are forecasted to rise from 3.35 to 9.13% and from 7.45 to 13.15%, respectively. Generally, the TSS loading projection varies larger than the streamflow projection concerning changing climate. The findings here are also agreed with the conclusions of previous investigations on the future impacts of changing climate in the MRB.

The potential impact of climate variability on siltation of Andean reservoirs

Recent changes in global climate, and especially changes in precipitation patterns, may negatively impact on siltation of Andean storage reservoirs, thereby putting at risk the provision of resources to the local population. The extent to which this may happen is poorly understood. We therefore studied the catchment of the Cañete River in the western Peruvian Coastal Range as it plays an important role in the socioeconomic development of the region. It houses the 220 MW El Platanal hydroelectric plant and the Capillucas reservoir that provide the surrounding areas with water and energy. We used a hydrological model (HEC-HMS) coupled with a sediment transport model (HEC-RAS) to simulate future changes in river discharge and sediment load. This information was then used to calculate the siltation of the Capillucas storage reservoir. Ten scenarios were developed, a combination of two different precipitation patterns and five different precipitation rates. The precipitation patterns differed in the distribution of the precipitation change during the rainfall season, and the precipitation rates differed in the extent of change in precipitation amounts. The average sediment load of the Cañete River was estimated at 981 kTon/yr upstream of the Capillucas reservoir and showed that the calculated life span of the Capillucas reservoir is about 17 years. The most pessimistic scenario suggested a reduction in the life span of the reservoir to 7 years and the most optimistic scenario to 31 years. Even under the most optimistic scenario, the life span of the reservoir is shorter than its officially expected functionality of 50 years. As such, our results demonstrated the vulnerability of Andean hydroelectric reservoirs against future climate change.

GLAM Bio-Lith RT: A Tool for Remote Sensing Reflectance Simulation and Water Components Concentration Retrieval in Glacial Lakes

A new open--source software tool, called GLAM BioLith--RT (Glacier Lakes Assisted Melting Biological Lithological Radiative Transfer), has been developed for modeling of Radiative Transfer (RT) in water bodies containing suspended lithic particles , phytoplankton, dissolved salts, and colored dissolved organic matter. Although our objective is an application to glacial lakes of High Mountain Asia, the model has potential application for the study of seawater, organic-rich lakes, rivers, etc. The tool is built on a solid foundation of an existing published open-source code called WASI, which has been reviewed and augmented with new capabilities, notably the addition of a suspended lithic particle grain size parameterization. GLAM BioLith-RT operates in both a forward modeling and inverse modeling mode. The forward mode is specifically designed to compute the reflectance spectra of glacier lakes from inherent optical water properties. Conversely, in the inverse mode, measured spectral reflectance is employed with other inputs to derive best fitting water component properties (e.g., suspended particles concentration). The inverse modeling includes Bayesian Optimization of the output which is a significant advance over the existing software. We have tested the code for sensitivity to noise, and uncertainties in input parameters. The model succeeds in nearly reproducing the hyperspectral reflectance of some glacial lakes in Nepal as observed by the EO-1 Hyperion hyperspectral imager. The inverse modeling approach, when supported up by validated forward modeling, offers a means for remote sensing characterization of suspended sediment load in glacial lakes and rivers and hence, use of suspended sediment as a proxy for glacial activity; and many other potential applications in other thematic areas.

Multiyear changes of the Danube delta marine edge

With the help of field and remote (space) methods, detailed studies of long-term changes of the Danube delta coastline (DCL) were carried out. It was established that the DCL displacements (progradation or retreat) can be an effective indicator of delta formation process as a whole: the dynamics of the delta channel network and the redistribution of water flow and sediment load between the branches, the impact of external factors on the delta (river water flow and sediment load, wind and wave action, rise or drop of the sea level). To determine the causes and characteristics of the Danube DCL changes on seven genetically homogeneous areas the contribution of various factors to the balance of sand sediments forming the DCL was evaluated. Locations of the DCL progradation or retreat were determined. Comparison of the results of a study of the Danube DCL dynamics with the data on changes of morphology and regime of other large deltas may allow one to assess the causes and trends of modern processes in river deltas.

Spatiotemporal Variation of Annual Runoff and Sediment Load in the Pearl River during 1953–2017

Anthropogenic activities have had a great impact on the characteristics of runoff and sediment load along the Pearl River in China in recent decades. We investigated the spatiotemporal variations, including the trends, abrupt changes, and periodicities of annual runoff and sediment load in the Pearl River by using the datasets from nine hydrological stations for the period of 1953–2017. We found that annual runoff was stable during the study period, with only two stations in the upper reach showing decreasing trends. Annual sediment load has generally experienced a significant decreasing trend, while one of the stations in the middle reach showed an opposite trend due to severe rocky desertification and soil erosion in the local karst terrain. Abrupt changes in sediment load were mainly between the 1990s and 2000s, when many hydraulic projects were conducted, implying the significant impact of anthropogenic activities on river sediment load. Results also indicate 2–4 year and 4–8 year periodicities in both annual runoff and sediment load, with long periodicities less significant than the short ones. Our study is conducive to water and soil resource management in the Pearl River basin, whilst provides a guide for other basins, particularly those characterized by karst terrains where local desertification and soil erosion might likewise cause increase in river sediment load.

Effects of Climate Variability and Human Activities on Suspended Sediment Load in the Ganjiang River Basin, China

AbstractClimate variability and human activities have substantially affected the delivery process of suspended sediment load (SSL) in rivers, which is a major driving force of river configuration a...

Disentangling the relative impacts of climate change and human activities on fluvial sediment supply to the coast by the world\u2019s large rivers: Pearl River Basin, China

The world’s large rivers are under stress and experiencing unprecedented changes in hydrology, ecosystems, and fluvial sediment loads. Many of these rivers terminate at the great deltas of the world (home to 500 million people), which depend on fluvial sediments for their very existence. While fluvial sediment loads of large rivers have already been greatly modified by human activities, climate change is expected to further exacerbate the situation. But how does the effect of climate change on fluvial sediment loads compare with that of human impacts? Here, we address this question by combining historical observations and 21st century projections for one of the world’s largest 25 rivers containing two mega dams; Pearl River, China. Our analysis shows that variations in fluvial sediment supply to the coast from the Pearl river over a ~150 year study period are dominated by human activities. Projected climate change driven 21st century increases in riverflow will only compensate for about 1% of the human induced deficit in sediment load, leading to the coastal zone being starved of about 6000 Mt of sediment over the remainder of this century. A similar dominance of human impacts on fluvial sediment supply is likely at other heavily engineered rivers.

Local and landscape influences on turbidity in urban streams: a global approach using citizen scientists

The ecological degradation of urban rivers and streams has been termed the ‘urban stream syndrome’ and attributed to increased catchment urbanization. Limiting future degradation requires an understanding of the drivers of reduced water quality at both catchment and site scales. The goal of this study was to identify the probable drivers of turbidity in river ecosystems in highly urbanized areas, under the premise that turbidity does not respond consistently to urbanization. Catchment-scale data were compiled from remotely sensed datasets, whereas local-scale data were collected by citizen scientists as part of the global FreshWater Watch (FWW) program. The local-scale data included nearly 2600 coincident measurements of turbidity and observations of other local characteristics taken with a common method between March 2013 and June 2016 across 127 unique locations in 6 major population centers: Vancouver (Canada), São Paulo (Brazil), Curitiba (Brazil), Buenos Aires (Argentina), Hong Kong SAR (China), and Guangzhou-Foshan (China). Catchment- and site-scale information were modeled with Boosted Regression Trees (BRT) to identify likely drivers of increased turbidity both across the entire dataset and within individual cities. Urbanization was not consistently associated with turbidity. The global BRT model explained 60% of the variation in turbidity, and key predictors were catchment area, % of the catchment as grassland, rainfall, Gross Domestic Product, and % of the catchment as artificial surfaces. City-specific BRT models explained 35–67% of the variation in turbidity. Key predictors varied between cities and were often different than those observed at the global scale. Local-scale data collected by citizen scientists were less predictive of turbidity than catchment-scale factors and explained ~12% of the observed global variability in turbidity. Factors such as riverbank vegetation and the presence of point pollution sources explained some of the variation in turbidity, indicating their management could help mitigate elevated turbidity and sediment load in some urban rivers. Through this high-resolution, site-scale information, we highlight how community-sourced data may add value to freshwater monitoring programs.

Changing of the riverine sediment load supply into Lake Baikal: The natural and anthropogenic causes (Russia)

The influences of natural and anthropogenic factors on temporal changes in sediment load of the main Baikal rivers (Upper Angara River and Barguzin River) were analyzed through the relationship between hydro-climatic parameters (air temperature, precipitation, water discharge and sediment load) and their variation tendencies for the periods of 1945–2014, 1945–1975 and 1976–2014. Mann–Kendall test, abrupt change test were employed to analyze the hydro-climatic data. The results indicated that the air temperature increased on 1.0–1.1 °C in the watersheds over the warming period (1976–2014), and the precipitation had an insignificant decreasing trend in this period, and the reduction was −2.6% and −4.9%. The statistically insignificant increasing in water discharge was 4.2% and 1.3% in the Upper Angara and Barguzin over the period 1976–2014, respectively. Meanwhile, there was a strong decrease in sediment load of −66% and −70%. The abrupt decrease the sediment load in the Upper Angara since the mid-1970s was caused by the combination of human activities in river basin and changes of natural processes. In the Barguzin basin, the significant anthropogenic impact against the background the changes of natural processes in the mid-1980s was began. In the Upper Angara, the period of rapid decline of sediment load from 1976 to 1984 continued, in the Barguzin – from 1976 to 1991, after that, the other regime of sediment load had established. In recent decades, the actual sediment load supply from the Upper Angara and Barguzin into Lake Baikal are 92 × 103 t y−1 and 27 × 103 t y−1 or 22% and 18% of the 1945–1975, respectively.

Creation of river terrain data using region growing method based on point cloud data from UAV photography

The geo-spatial information in the river area is essential for river management such as river planning, flood analysis, and sediment load analysis. Recently, unmanned aerial vehicle (UAV) technology has been actively studied to acquire three-dimensional terrain data. However, the UAV acquired river terrain data is a digital surface model (DSM) that includes the height of a tree or grass in a river. It is different from the digital elevation model (DEM) required by river surveys. In this study, the ground point was extracted by using point cloud point obtained from UAV with Terra Scan software, and the DEM were constructed using the region growth algorithm. In order to evaluate the accuracy of the DEM data, the TRUE value of 100 test points was obtained by using virtual reference station (VRS) and total station survey equipment. As a result, the standard deviation of DSM and DEM were ±3.84 m and ±0.12 m, respectively. Furthermore, the cross section of DEM showed similar elevation values with cross section in the report of basic plan for Gap River. Therefore, DEM can be secured by applying the UAV point cloud based on region growth algorithm, and it can be effectively used for the river management tasks.

A Wavelet Based Data Mining Technique for Suspended Sediment Load Modeling

The suspended sediment load (SSL) modeling generated within a catchment is a significant issue in the environmental and water resources planning and management of watersheds. The estimation methods of SSL are limited by the important parameters and boundary conditions (which are based on the flow and sediment properties). In this situation, soft computing approaches have proven to be an efficient tool in modelling the sediment load of rivers. In this study, the hybrid Wavelet-M5 model was introduced to model SSL of two different rivers (Lighvanchai and Upper Rio Grande) at both daily and monthly scales. In this way, first, the runoff and suspended sediment load time series were decomposed using the wavelet transform to several sub-time series to handle the non-stationary of the runoff and sediment time series. Then, the obtained sub-series were applied to M5 model tree as inputs. The obtained results for the Upper Rio Grande River at daily time scale, showed the better performance of Wavelet-M5 model in comparison with individual Artificial Neural Network (ANN) and M5 models so that the obtained Nash-Sutcliffe efficiency (NSE) was 0.94 by the hybrid Wavelet-M5 model while it was calculated as 0.89 and 0.77 by Wavelet-ANN (WANN) and M5 tree models, respectively. Also, the obtained NSE for the Lighvanchai River at monthly time scale was 0.90 by the hybrid Wavelet-M5 model while it was calculated as 0.78 and 0.69 by Wavelet-ANN (WANN) and M5 tree models in the verification step, respectively.

Estimating the Capability of Shatt Al - Hilla within Hilla City to Carry the Total Bed – Material Load

The case study is Shatt Al – Hilla within Hilla City, where no sediment measurement has been done whatsoever. Data on bed soil and expected hydraulic parameters at Km. 39.000 of Shatt Al – Hilla just at the upstream of Hilla City for the developed design discharge of (303 m3/s) were previously investigated. The main objective of this research is to apply different commonly – used approaches worldwide to estimate the capability of an alluvial channel to carry total bed – material load, taking Shatt Al – Hilla within Hilla City as the case study. Five, somehow different formulas to estimate the bed – material load were used. These are: Laursen 1958, Karim & Kennedy 1990, Engelund & Hansen 1967-1962, Ackers & White 1973-1990, and Yang 1973. Considering the results by Yang 1973 of judgment, the research indicated: 1) the expected bed – material load at the considered location is about (200000 m3/Year). 2) Differences of results of predicting sediment load in rivers by different formulas by some folds is not a surprise. 3) Measurement of sediment load at important locations such as those contributing to life and property in an important city (like in the case study) is essential.

A performance evaluation of neuro-fuzzy and regression methods in estimation of sediment load of selective rivers

Sediment rating curves (SRCs) have been recognized as the most popular method for estimating sediment in the hydrology of river sediments and in watersheds. In this regard, in order to compare and correct estimation methods of river sediment load, estimated rates of several univariate types of SRCs and a multivariate type of SRCs (MSRCs) were studied using the neuro-fuzzy and tree regression models in five selective hydrometric stations of different climatic zones of Iran and with various indexes of the accuracy (AI) and the precision (PI). The results of the data analysis showed that the mean of the AI of neuro-fuzzy and tree regression models in selective stations is 151 and 536%, respectively, which shows the low efficiency compared with SRCs. Also according to the results, the best rate of the AI of the MSRCs belongs to the Glink station with the rate of 1.12. Also, the average value of the AI of MSRCs is 1.15 which is an acceptable amount of the other considered various methods.

The Use of River Flow Discharge and Sediment Load for Multi-Objective Calibration of SWAT Based on the Bayesian Inference

The soil and water assessment tool (SWAT) is widely used to quantify the spatial and temporal patterns of sediment loads for watershed-scale management of sediment and nonpoint-source pollutants. However few studies considered the trade-off between flow and sediment objectives during model calibration processes. This study proposes a new multi-objective calibration method that incorporates both flow and sediment observed information into a likelihood function based on the Bayesian inference. For comparison, two likelihood functions, i.e., the Nash–Sutcliffe efficiency coefficient (NSE) approach that assumes model residuals follow the Gaussian distribution, and the BC-GED approach that assumes model residuals after Box–Cox transformation (BC) follow the generalized error distribution (GED), are applied for calibrating the flow and sediment parameters of SWAT with the water balance model and the variable source area concept (SWAT-WB-VSA) in the Baocun watershed, Eastern China. Compared with the single-objective method, the multi-objective approach improves the performance of sediment simulations without significantly impairing the performance of flow simulations, and reduces the uncertainty of flow parameters, especially flow concentration parameters. With the NSE approach, SWAT-WB-VSA captures extreme flood events well, but fails to mimic low values of river discharge and sediment load, possibly because the NSE approach is an informal likelihood function, and puts greater emphasis on high values. By contrast, the BC-GED approach approximates a formal likelihood function, and balances consideration of the high- and low- values. As a result, inferred results of the BC-GED method are more reasonable and consistent with the field survey results and previous related-studies. This method even discriminates the nonerodible characteristic of main channels.