Soil Erosion and Sediment Yield Modelling

Fish, U. C. Kothyari

doi:10.1080/09715010.2008.10514895

Cited by 8 publications

(4 citation statements)

References 42 publications

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“…The sediment transportation revealed the intensity of soil erosion [38]. The gully erosion induced by snowmelt could be identified by the sediment transportation at the three observation sites.…”

Section: Snow Melting Sediment Transportation Of Gullymentioning

confidence: 93%

Gully Erosion Induced by Snowmelt in Northeast China: A Case Study

Liu

et al. 2019

Sustainability

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Gully erosion stands out as one of the worst aspects of farmland degradation, which induces the loss of arable soil and tractor operation. Most of the gully erosion studies focused on the influence of precipitation erosion, slope erosion, and the freeze–thaw cycle on soil characteristics. Few studies discussed the effect of snowmelt on gully development. In this paper, the gully development induced by snowmelt was observed in a typical gully in Hailun City, the center of the Mollisols area of northeast China. The results showed that, during the snow melting period of 2017, the soil loss induced by snow melting was 0.22 t at the gully head + 0 m, 14.27 t at the gully head + 77 m, and 7.63 t at the gully head + 239 m, while 98.1% of the sediment was from the gully erosion. The horizontal projected area of the observed gully increased by 56.96 m2, and the gully head advanced 2.3 m during the snow melting period. About 92.2% of the total runoff occurred in the initial snow melting period. The discharge runoff and sediment concentration had a significant correlation with the air temperature above 0 °C, and the same relationship existed between the discharge runoff and sediment concentration in the initial and middle snowmelt stages. The results indicate that the gully development induced by snowmelt should not be ignored in the area.

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Section: Snow Melting Sediment Transportation Of Gullymentioning

confidence: 93%

Gully Erosion Induced by Snowmelt in Northeast China: A Case Study

Liu

et al. 2019

Sustainability

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“…Many actions have been taken by the government for rectification of the problem and preventing further destruction of the soil layer. In India, almost 130 million hectares of land (Kothyari, 1996), i.e., 45% of the total geographical surface area, is affected by serious soil erosion through the gorge and gully, shifting cultivation, cultivated wastelands, sandy areas, deserts and water logging. Excessive soil erosion with a resultant high rate of sedimentation in the reservoirs and decreased fertility has become solemn environmental problems for the country with disastrous economic consequences.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Soil Erosion by RUSLE Model using remote sensing and QGIS: A Case Study on Sina River Basin

S.S,

P.R,

S.R

et al. 2023

IJSREM

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Soil erosion is a significant environmental problem that affects river basins globally, leading to the loss of fertile topsoil, degradation of agricultural lands, and water pollution. The Revised Universal Soil Loss Equation (RUSLE) model is commonly used to assess soil erosion by considering various factors such as rainfall erosivity, soil erodibility, slope length and steepness, vegetation cover, and conservation practices. To obtain the necessary data for accurate predictions, remote sensing techniques and Quantum Geographic Information Systems (QGIS), specifically QGIS software, are utilized. The objectives of this research are to determine to estimate soil loss using the Revised Universal Soil Loss Equation (RUSLE) model for the Sina River watershed using QGIS. This research paper focuses on assessing soil erosion in the Sina River Basin located in Ahmednagar, Maharashtra, India, using the RUSLE model and QGIS, having a drainage area of 12,372 km2 . The parameters of the RUSLE model were estimated using remote sensing data and the erosion was determined using QGIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 83 to 84 MJ/mm·ha−1hr−1/year, 0 to 0.25t ha−1·MJ−1·mm−and 0 to 957.083, 0 to 0.19 respectively. The results indicate that the estimated total annual potential soil loss of about 14.37 t/yr. The predicted soil erosion rate due to the increase in a barren area is about 9.76 t/yr. The results can certainly aid in the implementation of soil management and conservation practices to reduce soil erosion in the Sina River Basin.

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“…Basin sediment yield can be predicted coupling a model estimating gross erosion with a mathematical operator which expresses the sediment transport efficiency of both the hillslopes and the channel network (Richards, 1993;Atkinson, 1995;Lane et al, 2000;Kothyari, 2008). Sediment delivery ratio, the ratio of basin sediment yield to the gross erosion, is a commonly applied index of the basin sediment transport efficiency (Dickinson & Collins, 1998).…”

Section: Introductionmentioning

confidence: 99%

Testing Sediment Connectivity at the Experimental SPA2 Basin, Sicily (Italy)

Stefano

Ferro

2017

Land Degrad Dev

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The concept of sediment delivery can be used as a measure of sediment connectivity, and it can be linked to the structural connectivity (morphological unit, slope length, slope steepness, travel time) of a basin and to the hydrological connectivity (rainfall–runoff processes at morphological unit scale). In this paper, the sediment connectivity concept was tested at basin scale applying SEdiment Delivery Distributed model, which takes into account the hillslope sediment transport, and using sediment yield measurements carried out at SPA2 experimental basin (Sicily, Italy). For the SPA2 basin discretized into morphological units, the SEdiment Delivery Distributed model was first calibrated at event scale using the sediment yield measurements carried out at the outlet of the experimental basin in the period April 2000–March 2015. The model calibration was used to determine the relationships useful for estimating the unique coefficient βe of the model appearing in the expression used to calculate the sediment delivery ratio of each morphological unit. The developed analysis allowed establishing that the functional connectivity is dependent on the magnitude of erosion events, and for low events the sediment connectivity is only governed by its structural component. Then, at annual scale, the model was calibrated for the period 2000–2015, and relationships for the estimate of the coefficient βa taking into account the intensity of erosion events occurring in each year were determined. Finally, a physical interpretation of β coefficient at the two temporal scales (βe, βa) and its link to sediment connectivity was proposed. Copyright © 2017 John Wiley & Sons, Ltd.

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Soil Erosion and Sediment Yield Modelling

Cited by 8 publications

References 42 publications

Gully Erosion Induced by Snowmelt in Northeast China: A Case Study

Gully Erosion Induced by Snowmelt in Northeast China: A Case Study

Assessment of Soil Erosion by RUSLE Model using remote sensing and QGIS: A Case Study on Sina River Basin

Testing Sediment Connectivity at the Experimental SPA2 Basin, Sicily (Italy)

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