Prophecy of Sediment Load Using Hybrid AI Approaches at Various Gauge Station in Mahanadi River Basin, India

2021 ◽  
pp. 211-236
Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo ◽  
Dillip K. Ghose
Keyword(s):  
River Basin ◽  
Sediment Load ◽  
Mahanadi River ◽  
Gauge Station

scholarly journals Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 39 ◽  
Author(s):  
Lifeng Yuan ◽  
Kenneth J. Forshay
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Lake Sediment ◽  
Sediment Yield ◽  
Sediment Load ◽  
Poyang Lake ◽  
Sediment Source ◽  
Sediment Loading ◽  
Source Areas ◽  
Annual Sediment

Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge (1985–2009) and monthly suspended sediment load data (1985–2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation’s standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha−1year−1 on riparian lowlands of the Xinjiang main channel to 33 ton ha−1year−1 on mountain highlands, with a basin-wide mean of 19 ton ha−1year−1. The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha−1year−1). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25° were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.

Impact of climate change on streamflow and water quality in the upper Dong Nai river basin, Vietnam

2018 ◽  
pp. 70-79 ◽  
Author(s):  
Le Viet Thang ◽  
Dao Nguyen Khoi ◽  
Ho Long Phi
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
River Basin ◽  
Sediment Load ◽  
Swat Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Nutrient Load ◽  
Impact Of Climate Change ◽  
The Impact

In this study, we investigated the impact of climate change on streamflow and water quality (TSS, T-N, and T-P loads) in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a reasonable tool for simulating streamflow and water quality for this basin. Based on the well-calibrated SWAT model, the responses of streamflow, sediment load, and nutrient load to climate change were simulated. Climate change scenarios (RCP 4.5 and RCP 8.5) were developed from five GCM simulations (CanESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) using the delta change method. The results indicated that climate in the study area would become warmer and wetter in the future. Climate change leads to increases in streamflow, sediment load, T-N load, and T-P load. Besides that, the impacts of climate change would exacerbate serious problems related to water shortage in the dry season and soil erosion and degradation in the wet season. In addition, it is indicated that changes in sediment yield and nutrient load due to climate change are larger than the corresponding changes in streamflow.

scholarly journals Effects of Climate Change and Human Activities on Soil Erosion in the Xihe River Basin, China

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1085 ◽  
Author(s):  
Shanshan Guo ◽  
Zhengru Zhu ◽  
Leting Lyu
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
River Basin ◽  
Air Temperature ◽  
Human Activities ◽  
Sediment Load ◽  
Sudden Increase ◽  
Validation Period ◽  
Total Change ◽  
Calibration Period

Climate change and human activities are the major factors affecting runoff and sediment load. We analyzed the inter-annual variation trend of the average rainfall, air temperature, runoff and sediment load in the Xihe River Basin from 1969–2015. Pettitt’s test and the Soil and Water Assessment Tool (SWAT) model were used to detect sudden change in hydro-meteorological variables and simulate the basin hydrological cycle, respectively. According to the simulation results, we explored spatial distribution of soil erosion in the watershed by utilizing ArcGIS10.0, analyzed the average erosion modulus by different type of land use, and quantified the contributions of climate change and human activities to runoff and sediment load in changes. The results showed that: (1) From 1969–2015, both rainfall and air temperature increased, and air temperature increased significantly (p < 0.01) at 0.326 °C/10 a (annual). Runoff and sediment load decreased, and sediment load decreased significantly (p < 0.01) at 1.63 × 105 t/10 a. In 1988, air temperature experienced a sudden increase and sediment load decreased. (2) For runoff, R2 and Nash and Sutcliffe efficiency coefficient (Ens) were 0.92 and 0.91 during the calibration period and 0.90 and 0.87 during the validation period, for sediment load, R2 and Ens were 0.60 and 0.55 during the calibration period and 0.70 and 0.69 during the validation period, meeting the model’s applicability requirements. (3) Soil erosion was worse in the upper basin than other regions, and highest in cultivated land. Climate change exacerbates runoff and sediment load with overall contribution to the total change of −26.54% and −8.8%, respectively. Human activities decreased runoff and sediment load with overall contribution to the total change of 126.54% and 108.8% respectively. Runoff and sediment load change in the Xihe River Basin are largely caused by human activities.

scholarly journals Dynamics of suspended sediment load in the upper part of the Rasina River Basin in 2010

2013 ◽  
Vol 93 (4) ◽  
pp. 23-40
Author(s):  
Sanja Mustafic ◽  
Predrag Manojlovic ◽  
Predrag Kostic
Keyword(s):  
Suspended Sediment ◽  
River Basin ◽  
Sediment Load ◽  
Suspended Sediment Load ◽  
Spring Season ◽  
Autumn Season ◽  
Specific Transport ◽  
Suspended Sediment Concentrations ◽  
Load Transport

The paper treats the issue of the suspended sediment load transport in the upper part of the Rasina River Basin, upstream from the "Celije" reservoir during the year of 2010. Measurements of the suspended sediment concentrations were being done at two hydrological profiles Brus and Ravni. Total quantity of the suspended sediment load that was transported at the profile of Brus in 2010 amounted to 3,437.3 t, which gave the specific transport of 16.4 t/km2/year. At the downstream profile of Ravni, 43,165 t of the suspended sediment load was transported, that is, 95.7 t/km2/year. The basin on the whole is characterized by the existence of two seasons, which by their characteristics in the load transport represent the extreme variants. During the winter-spring season, 74-85.8 % of the total annual load was transported, ?nd during the summer-autumn season between 14.2 and 26 %.

scholarly journals Artificial Neural Network Model for Estimation of Suspended Sediment Load in Krishna River Basin, India

2020 ◽  
Vol 9 (3) ◽  
pp. 3701-3705
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Water Level ◽  
Suspended Sediment ◽  
River Basin ◽  
Flood Control ◽  
Sediment Load ◽  
Water Discharge ◽  
Suspended Sediment Load ◽  
Artificial Neural

The correct assessment of amount of sediment during design, management and operation of water resources projects is very important. Efficiency of dam has been reduced due to sedimentation which is built for flood control, irrigation, power generation etc. There are traditional methods for the estimation of sediment are available but these cannot provide the accurate results because of involvement of very complex variables and processes. One of the best suitable artificial intelligence technique for modeling this phenomenon is artificial neural network (ANN). In the current study ANN techniques used for simulation monthly suspended sediment load at Vijayawada gauging station in Krishna river basin, Andhra Pradesh, India. Trial & error method were used during the optimization of parameters that are involved in this model. Estimation of suspended sediment load (SSL) is done using water discharge and water level data as inputs. The water discharge, water level and sediment load is collected from January 1966 to December 2005. This approach is used for modelled the SSL. By considering the results, ANN has the satisfactory performance and more accurate results in the simulation of monthly SSL for the study location.

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