Risk modeling of soil erosion under different land use and rainfall conditions in Soan river basin, sub-Himalayan region and mitigation options

<p>Land degradation is a global concern posing significant threat to sustainable development. One of its major aspects is soil erosion, which is recognised as one of the critical geomorphic processes controlling sediment budget and landscape evolution. Natural rate of soil erosion is exacerbated due to anthropogenic activities that may lead to soil infertility. Therefore, assessment of soil erosion at basin scale is needed to understand its spatial pattern so as to effectively plan for soil conservation. This study focuses on Parbati river basin, a major north flowing cratonic river and a tributary of river Chambal to identify erosion prone areas using RUSLE model. Soil erodibility (K), Rainfall erosivity (R), and Topographic (LS) factors were derived from National Bureau of Soil Survey and Land Use Planning, Nagpur (NBSS-LUP) soil maps, India Meteorological Department (IMD) datasets, and SRTM30m DEM, respectively in GIS environment. The crop management (C) and support practice (P) factors were calculated by assigning appropriate values to Land use /land cover (LULC) classes derived by random forest based supervised classification of Sentinel-2 level-1C satellite remote sensing data in Google Earth Engine platform. High and very high soil erosion were observed in NE and NW parts of the basin, respectively, which may be attributed to the presence of barren land, fallow areas and rugged topography. The result reveals that annual rate of soil loss for the Parbati river basin is ~319 tons/ha/yr (with the mean of 1.2 tons/ha/yr). Lowest rate of soil loss (i.e. ~36 tons/ha/yr with mean of 0.22 tons/ha/yr) has been observed in the open forest class whereas highest rate of soil loss (i.e. ~316 tons/ha/yr with mean of 32.08 tons/ha/yr) have been observed in gullied area class. The study indicates that gullied areas are contributing most to the high soil erosion rate in the basin. Further, the rate of soil loss in the gullied areas is much higher than the permissible value of 4.5&#8211;11 tons/ha/yr recognized for India. The study helps in understanding spatial pattern of soil loss in the study area and is therefore useful in identifying and prioritising erosion prone areas so as to plan for their conservation.</p>

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Application of Revised Universal Soil Loss Equation (Rusle) Model to Assess Soil Erosion in “Kalu Ganga” River Basin in Sri Lanka

Applied and Environmental Soil Science ◽

10.1155/2019/4037379 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 5

Author(s):

D. L. D. Panditharathne ◽

N. S. Abeysingha ◽

K. G. S. Nirmanee ◽

Ananda Mallawatantri

Keyword(s):

Land Use ◽

Sri Lanka ◽

Soil Erosion ◽

River Basin ◽

Soil Loss ◽

Management Practices ◽

Agricultural Land ◽

Universal Soil Loss Equation ◽

Rusle Model ◽

Soil Loss Equation

Soil erosion is one of the main forms of land degradation. Erosion contributes to loss of agricultural land productivity and ecological and esthetic values of natural environment, and it impairs the production of safe drinking water and hydroenergy production. Thus, assessment of soil erosion and identifying the lands more prone to erosion are vital for erosion management process. Revised Universal Soil Loss Equation (Rusle) model supported by a GIS system was used to assess the spatial variability of erosion occurring at Kalu Ganga river basin in Sri Lanka. Digital Elevation Model (30 × 30 m), twenty years’ rainfall data measured at 11 rain gauge stations across the basin, land use and soil maps, and published literature were used as inputs to the model. The average annual soil loss in Kalu Ganga river basin varied from 0 to 134 t ha−1 year−1 and mean annual soil loss was estimated at 0.63 t ha−1 year−1. Based on erosion estimates, the basin landscape was divided into four different erosion severity classes: very low, low, moderate, and high. About 1.68% of the areas (4714 ha) in the river basin were identified with moderate to high erosion severity (>5 t ha−1 year−1) class which urgently need measures to control soil erosion. Lands with moderate to high soil erosion classes were mostly found in Bulathsinghala, Kuruwita, and Rathnapura divisional secretarial divisions. Use of the erosion severity information coupled with basin wide individual RUSLE parameters can help to design the appropriate land use management practices and improved management based on the observations to minimize soil erosion in the basin.

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Using 137Cs measurements to quantify soil erosion and redistribution rates for areas under different land use in the Upper Kaleya River basin, southern Zambia

Geoderma ◽

10.1016/s0016-7061(01)00087-8 ◽

2001 ◽

Vol 104 (3-4) ◽

pp. 299-323 ◽

Cited By ~ 68

Author(s):

A.L Collins ◽

D.E Walling ◽

H.M Sichingabula ◽

G.J.L Leeks

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin

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Spatial–temporal evolution patterns of soil erosion in the Yellow River Basin from 1990 to 2015: impacts of natural factors and land use change

Geomatics Natural Hazards and Risk ◽

10.1080/19475705.2020.1861112 ◽

2020 ◽

Vol 12 (1) ◽

pp. 103-122

Author(s):

Xiao ◽

Yang ◽

Bing Guo ◽

Yuefeng Lu ◽

Rui Zhang ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Use Change ◽

River Basin ◽

Temporal Evolution ◽

Yellow River ◽

Yellow River Basin ◽

The Yellow River ◽

Natural Factors ◽

The Yellow River Basin

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How land use change contributes to reducing soil erosion in the Jialing River Basin, China

Agricultural Water Management ◽

10.1016/j.agwat.2013.10.016 ◽

2014 ◽

Vol 133 ◽

pp. 65-73 ◽

Cited By ~ 21

Author(s):

Shanghong Zhang ◽

Yan Liu ◽

Taiwei Wang

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Use Change ◽

River Basin ◽

Jialing River

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Mapping soil erosion in the Da Dang river basin, Lam Dong province

Science & Technology Development Journal - Science of The Earth & Environment ◽

10.32508/stdjsee.v1im2.444 ◽

2017 ◽

Vol 1 (M2) ◽

pp. 47-56

Author(s):

Hung Pham ◽

Phu Le Vo ◽

Trung Van Le

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin ◽

Management Practices ◽

Mountainous Area ◽

Essential Information ◽

High Erosion Rate ◽

Using Data ◽

Soil Surveys ◽

Basin Area

The Da Dang river basin, located in the Upper Part of Dong Nai River, plays a crucial role to protect water resources in the downstream parts. The purpose of this study is to assess and develop a soil erosion map in the Da Dang river basin by using the Revised Universal Soil Loss Equation (RUSLE) combined with remote sensing (RS) and Geographic Information System (GIS). The factors used in the RUSLE equation (R, K, LS, C, and P) were computed by using data obtained from local meteorological stations, topographic maps, soil surveys, and satellite images. The data on water quality (TSS) of 75 surface water samples was deployed at 15 monitoring sites in the river basin in the period of 2012 – 2016, provided by DONRE of Lam Dong. The results showed that 14.41% of the basin area is subjected to a high erosion rate with an extent of 10 tons/ha/year or more. Furthermore, the study also indicated that TSS concentration has a closely correlation with land use practices and the the spatial distribution of soil erosion. These findings are essential information and practical implications for local authorities in formulating provincial planning policy for land use and the management practices of soil and water protection in the Da Dang river basin, a sensitively mountainous area, in the context of climate change.

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A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽

10.3390/land10090990 ◽

2021 ◽

Vol 10 (9) ◽

pp. 990

Author(s):

Yongfen Zhang ◽

Nong Wang ◽

Chongjun Tang ◽

Shiqiang Zhang ◽

Yuejun Song ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin ◽

Landscape Metrics ◽

Landscape Pattern ◽

Sediment Yield ◽

River Basins ◽

Landscape Patterns ◽

Soil Erodibility ◽

Land Use Pattern

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.

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