Assessment of soil erosion, sediment yield and basin specific controlling factors using RUSLE-SDR and PLSR approach in Konar river basin, India

2020 ◽  
Vol 587 ◽  
pp. 124935 ◽  
Author(s):  
J. Rajbanshi ◽  
S. Bhattacharya
Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 39 ◽  
Author(s):  
Lifeng Yuan ◽  
Kenneth J. Forshay

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.


2017 ◽  
Author(s):  
Somil Swarnkar ◽  
Anshu Malini ◽  
Shivam Tripathi ◽  
Rajiv Sinha

Abstract. High soil erosion and excessive sediment load are serious problems in several Himalayan River basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties of SE over two distinct morpho-climatic regimes of the Garra River basin, namely, upper mountainous region & lower alluvial plains. The results suggest that average SE in the basin falls in very high category (20.4 ± 4.1 t/ha/y) with higher values in the upper mountainous region (84.4 ± 13.9 t/ha/y) than in the lower alluvial plains (17.7 ± 3.6 t/ha/y). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin – Nanak Sagar dam (NSD) for the period 1962–2008 and Husepur gauging station (HGS) for 1987–2002. The SY at NSD and HGS are estimated to be 8.0 ± 1.4 × 105 t/y and 7.9 ± 1.7 ×106 t/y, respectively, and the estimated 90 % confidence interval contains the observed values 6.4 × 105 t/y and 7.2 × 106 t/y. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.


Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 990
Author(s):  
Yongfen Zhang ◽  
Nong Wang ◽  
Chongjun Tang ◽  
Shiqiang Zhang ◽  
Yuejun Song ◽  
...  

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.


Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 952 ◽  
Author(s):  
Devraj Chalise ◽  
Lalit Kumar ◽  
Velibor Spalevic ◽  
Goran Skataric

Soil erosion is a severe environmental problem worldwide as it washes away the fertile topsoil and reduces agricultural production. Nepal, being a hilly country, has significant erosion disputes as well. It is important to cognise the soil erosion processes occurring in a river basin to manage the erosion severity and plan for better soil conservation programs. This paper seeks to calculate the sediment yield and maximum outflow from the Sarada river basin located in the western hills of Nepal using the computer-graphic Intensity of Erosion and Outflow (IntErO) model. Asymmetry coefficient of 0.63 was calculated, which suggests a possibility of large floods to come in the river basin in the future whereas the maximum outflow from the river basin was 1918 m³ s−1. An erosion coefficient value of 0.40 was obtained, which indicates surface erosion of medium strength prevails in the river basin. Similarly, the gross soil loss rate of 10.74 Mg ha−1 year−1 was obtained with the IntErO modeling which compares well with the soil loss from the erosion plot measurements. The IntErO model was used for the very first time to calculate soil erosion rates in the Nepalese hills and has a very good opportunity to be applied in similar river basins.


2018 ◽  
Vol 22 (4) ◽  
pp. 2471-2485 ◽  
Author(s):  
Somil Swarnkar ◽  
Anshu Malini ◽  
Shivam Tripathi ◽  
Rajiv Sinha

Abstract. High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha−1 yr−1) with higher values in the upper mountainous region (92 ± 15.2 t ha−1 yr−1) compared to the lower alluvial plains (19.3 ± 4 t ha−1 yr−1). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin – Nanak Sagar Dam (NSD) for the period 1962–2008 and Husepur gauging station (HGS) for 1987–2002. The SY at NSD and HGS are estimated to be 6.9 ± 1.2 × 105 t yr−1 and 6.7 ± 1.4 × 106 t yr−1, respectively, and the estimated 90 % interval contains the observed values of 6.4 × 105 t yr−1 and 7.2 × 106 t yr−1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.


Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3503
Author(s):  
Ty Sok ◽  
Chantha Oeurng ◽  
Ilan Ich ◽  
Sabine Sauvage ◽  
José Miguel Sánchez-Pérez

The Mekong River Basin (MRB) in Southeast Asia is among the world’s ten largest rivers, both in terms of its discharge and sediment load. The spatial and temporal resolution to accurately determine the sediment load/yield from tributaries and sub-basin that enters the Mekong mainstream still lacks from the large-scale model. In this study, the SWAT model was applied to the MRB to assess long-term basin hydrology and to quantify the sediment load and spatial sediment yield in the MRB. The model was calibrated and validated (1985–2016) at a monthly time step. The overall proportions of streamflow in the Mekong River were 34% from surface runoff, 21% from lateral flow, 45% from groundwater contribution. The average annual sediments yield presented 1295 t/km2/year in the upper part of the basin, 218 t/km2/year in the middle, 78 t/km2/year in the intensive agricultural area and 138 t/km2/year in the highland area in the lower part. The annual average sediment yield for the Mekong River was 310 t/km2/year from upper 80% of the total MRB before entering the delta. The derived sediment yield and a spatial soil erosion map can explicitly illustrate the identification and prioritization of the critical soil erosion-prone areas of the MR sub-basins.


2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Ebenezer Boakye ◽  
F. O. K. Anyemedu ◽  
Emmanuel A. Donkor ◽  
Jonathan A. Quaye-Ballard

Author(s):  
Belayneh Yigez ◽  
Donghong Xiong ◽  
Baojun Zhang ◽  
Yong Yuan ◽  
Muhammad Aslam Baig ◽  
...  

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