Daily suspended sediment concentration simulation using hydrological data of Pranhita River Basin, India

2017 ◽  
Vol 138 ◽  
pp. 20-28 ◽  
Author(s):  
Anurag Malik ◽  
Anil Kumar ◽  
Jamshid Piri
Keyword(s):  
Suspended Sediment ◽  
River Basin ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Hydrological Data

scholarly journals Insights on the Impacts of Hydroclimatic Extremes and Anthropogenic Activities on Sediment Yield of a River Basin

Earth ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 32-50
Author(s):  
Rocky Talchabhadel ◽  
Jeeban Panthi ◽  
Sanjib Sharma ◽  
Ganesh R. Ghimire ◽  
Rupesh Baniya ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
River Basin ◽  
Extreme Precipitation ◽  
Suspended Sediment Concentration ◽  
Anthropogenic Activities ◽  
Sediment Concentration ◽  
Sediment Flux ◽  
Mountain River ◽  
Ecological Processes ◽  
Precipitation Indices

Streamflow and sediment flux variations in a mountain river basin directly affect the downstream biodiversity and ecological processes. Precipitation is expected to be one of the main drivers of these variations in the Himalayas. However, such relations have not been explored for the mountain river basin, Nepal. This paper explores the variation in streamflow and sediment flux from 2006 to 2019 in central Nepal’s Kali Gandaki River basin and correlates them to precipitation indices computed from 77 stations across the basin. Nine precipitation indices and four other ratio-based indices are used for comparison. Percentage contributions of maximum 1-day, consecutive 3-day, 5-day and 7-day precipitation to the annual precipitation provide information on the severity of precipitation extremeness. We found that maximum suspended sediment concentration had a significant positive correlation with the maximum consecutive 3-day precipitation. In contrast, average suspended sediment concentration had significant positive correlations with all ratio-based precipitation indices. The existing sediment erosion trend, driven by the amount, intensity, and frequency of extreme precipitation, demands urgency in sediment source management on the Nepal Himalaya’s mountain slopes. The increment in extreme sediment transports partially resulted from anthropogenic interventions, especially landslides triggered by poorly-constructed roads, and the changing nature of extreme precipitation driven by climate variability.

scholarly journals The Evaluation of Dissolved Oxygen (DO), Total Suspended Solids (TSS) and Suspended Sediment Concentration (SSC) in Terengganu River, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 44
Author(s):  
Noorjima Abd Wahab ◽  
Mohd Khairul Amri Kamarudin ◽  
Mohd Ekhwan Toriman ◽  
Frankie Marcus Ata ◽  
Hafizan Juahir ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Dissolved Oxygen ◽  
Suspended Sediment ◽  
River Basin ◽  
Suspended Solids ◽  
Suspended Sediment Concentration ◽  
Total Suspended Solids ◽  
Sediment Concentration ◽  
Quality Parameters

Terengganu River Basin is situated in the north eastern coastal region of Peninsular Malaysia. 29 sampling stations were selected. The water quality parameters were measured such as Dissolved Oxygen (DO), Total Suspended Solids (TSS) and Suspended Sediment Concentration (SSC). Results showed that the range of DO (2.11 mg/L – 8.07 mg/L), TSS (0.4 mg/L – 128.2 mg/L) and SSC (0.07 mg/L – 25.6 mg/L). The distribution of land use and land cover activities effected to the level of water quality in watersheds. The analyses of variance (ANOVA) was applied and provide a better understanding for the complex relationships among water quality parameters. Graphical data helps a better view of the overall analysis to appoint sources of pollutants to their effect. Terengganu River Basin is a shallow and has a sensitive ecosystem that responds to the land use changes and development activities of its surroundings. Water quality analysis showed that TSS and SSC were higher in the dry season but DO were higher in the wet season. Overall, the water in the Terengganu River Basin classified slightly contaminated especially the main sources of pollutants were possibly waste products and waste from development activities such as sand mining, farming, residential and agricultural.  

scholarly journals Estimation of Suspended Sediment Concentration in Downstream of the Ba River Basin using Remote Sensing Images

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Ba Dung NGUYEN ◽  
Tuyet Minh DANG
Keyword(s):  
Remote Sensing ◽  
Suspended Sediment ◽  
River Basin ◽  
Large Scale ◽  
Suspended Sediment Concentration ◽  
Image Interpretation ◽  
Sediment Concentration ◽  
Initial Result ◽  
Remote Sensing And Gis ◽  
Landsat Satellite

Assessing the tendency of suspended sediment concentration (SSC) in the river watershedsenables a better understanding of the hydromorphological properties of its basins and the associatedprocesses. In addition, analyzing this trend is essential to address several important issues such as erosion,water pollution, human health risks, etc. Therefore, it is critical to determine a proper method to quantifyspatio-temporal variability in SSC. In recent years, remote sensing and GIS technologies are being widelyapplied to support scientists, researchers, and environmental resource investigators to quickly andsynchronously capture information on a large scale. The combination of remote sensing and GIS data willbecome the reliable and timely updated data source for the managers, researchers on many fields. Thereare several tools, software, algorithms being used in extracting information from satellites and support forthe analysis, image interpretation, data collection. The information from satellite images related to waterresources includes vegetational cover, flooding events on a large scale, rain forecast, populationdistribution, forest fire, landslide movements, sedimentation, etc., and especially information on waterquality, sediment concentration. This paper presents the initial result from LANDSAT satellite imageinterpretation to investigate the amount of sediment carried downstream of the Ba river basin.

scholarly journals A Modeling Approach to Diagnose the Impacts of Global Changes on Discharge and Suspended Sediment Concentration within the Red River Basin

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 958 ◽  
Author(s):  
Xi Wei ◽  
Sabine Sauvage ◽  
Thi Phuong Quynh Le ◽  
Sylvain Ouillon ◽  
Didier Orange ◽  
...  
Keyword(s):  
Climate Variability ◽  
Suspended Sediment ◽  
River Basin ◽  
Suspended Sediment Concentration ◽  
Influence Factor ◽  
Sediment Concentration ◽  
Red River ◽  
Global Changes ◽  
Natural Conditions ◽  
Red River Basin

The Red River basin is a typical Asian river system affected by climate and anthropogenic changes. The purpose of this study is to build a tool to separate the effect of climate variability and anthropogenic influences on hydrology and suspended sediments. A modeling method combining in situ and climatic satellite data was used to analyze the discharge (Q) and suspended sediment concentration (SSC) at a daily time scale from 2000 to 2014. Scenarios of natural and actual conditions were implemented to quantify the impacts of climate variability and dams. The modeling gained satisfactory simulation results of water regime and SSC compared to the observations. Under natural conditions, the Q and SSC show decreasing tendencies, and climate variability is the main influence factor reducing the Q. Under actual conditions, SSC is mainly reduced by dams. At the outlet, annual mean Q got reduced by 13% (9% by climate and 4% by dams), and annual mean SSC got reduced to 89% (13% due to climate and 76% due to dams) of that under natural conditions. The climate tendencies are mainly explained by a decrease of 9% on precipitation and 5% on evapotranspiration, which results in a 13% decrease of available water for the whole basin.

Neural networks approached for modelling river suspended sediment concentration due to tropical storms

2013 ◽  
Vol 11 (4) ◽  
pp. 457-466
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Time Series Data ◽  
Water Discharge ◽  
Sediment Concentration ◽  
Series Data ◽  
Generalized Regression Neural Network ◽  
Event Based

Artificial neural networks are one of the advanced technologies employed in hydrology modelling. This paper investigates the potential of two algorithm networks, the feed forward backpropagation (BP) and generalized regression neural network (GRNN) in comparison with the classical regression for modelling the event-based suspended sediment concentration at Jiasian diversion weir in Southern Taiwan. For this study, the hourly time series data comprised of water discharge, turbidity and suspended sediment concentration during the storm events in the year of 2002 are taken into account in the models. The statistical performances comparison showed that both BP and GRNN are superior to the classical regression in the weir sediment modelling. Additionally, the turbidity was found to be a dominant input variable over the water discharge for suspended sediment concentration estimation. Statistically, both neural network models can be successfully applied for the event-based suspended sediment concentration modelling in the weir studied herein when few data are available.

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