A USLE-based model with modified LS-factor combined with sediment delivery module for Alpine basins

Kaffas, Konstantinos; Pisinaras, Vassilios; Sayah, Mario J. Al; Santopietro, Simone; Righetti, Maurizio

doi:10.1016/j.catena.2021.105655

Cited by 28 publications

(9 citation statements)

References 70 publications

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“…Patro et al Journal of Environmental Management 320 (2022) 115826 et al, 2015 and added the advantage of seasonal erosion evaluation. Kaffas et al (2021) used a USLE-based model for an Alpine basin with a modified LS-factor to account for rock in the soil surface which is non-erodible. They found model validation to be improved by 10%.…”

Section: Discussionmentioning

confidence: 99%

Assessment of current reservoir sedimentation rate and storage capacity loss: An Italian overview

Patro

Michele

Granata

et al. 2022

Journal of Environmental Management

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Section: Discussionmentioning

confidence: 99%

Assessment of current reservoir sedimentation rate and storage capacity loss: An Italian overview

Patro

Michele

Granata

et al. 2022

Journal of Environmental Management

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“…The distribution of soil erosion displayed significant heterogeneity, with erosion hotspots (over 50 t ha −1 a −1 ) covering only 21.1% of the basin area, yet accounting for 69.5% of the gross erosion. These hotspots presented a characteristic erosion pattern of mountainous basins, where severe erosions occur in mountain peaks and boundary areas, and are spatially limited (Ali & De Boer, 2010; Kaffas et al, 2021). Precipitation in such basins tends to diverge into a bivariate pattern between dry and wet like in the LJRB, which was expected to exert a first‐order control on the erosion pattern (Yusof et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Other than that, physics‐based erosion models sometimes lack prediction quality (Jetten et al, 2003), whereas simpler lumped models seem to be more practical. The revised universal soil loss equation (RUSLE) (Renard et al, 1991) has been validated in mountainous basins for its wide applicability, computational accuracy, and reliable model performance (Aneseyee et al, 2020; Kaffas et al, 2021). Along with emerging geographic information system (GIS) technologies, the availability of global environmental datasets and modelling techniques have enabled the estimation of large‐scale erosion rates in a cost‐effective and accurate manner without time‐consuming field surveys (Nearing et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Predicting soil erosion and sediment delivery in large, data‐sparse, mountainous basins

Tan,

Liu,

2024

Earth Surf Processes Landf

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Intense hydroelectric exploitation requires information on sediment flux to prevent the potential siltation of cascade reservoirs. As the main sediment source for the Yangtze River, the lower Jinsha River Basin (LJRB) lacks data on its sediment budget, which urges a thorough investigation to provide reliable estimates. This paper proposed a modelling framework to study soil erosion, sediment delivery, and sediment yield in this critical area with an emphasis on analyzing the underlying controls. Over the past 50 years, basin average erosion rates decreased from 26.5 to 23.7 t ha−1 a−1, with erosion hotspots (>50 t ha−1 a−1) comprising only 21.1% of the basin area but contributing 69.5% of the gross erosion. Local steepness and sparse landcover conditions were found to be directly responsible for high erosions, rather than precipitation or soils. With a dimensionality reduction strategy to remove redundant factors, the optimal variables for modelling sediment delivery ratio (SDR) were identified as Specific Catchment Area, Maximum Elevation, and Drainage Area. These three variables all had a positive correlation with SDR, and the established model can explain 86% of the SDR variation. Further modelling revealed regionalised SDRs ranging from 0.07 to 0.38 for 39 subbasins, about 30% of which were no less than 0.35. Regionalised specific sediment yield (SSY) ranged from 1.3 to 16.9 t ha−1 a−1 with 38% of the high SSYs (above 8 t ha−1 a−1) concentrating in the reservoir area from Wudongde to Xiluodu that poses siltation risks. This study addressed the scarcity of sediment budget knowledge in the LJRB, and the coupled model of erosion and sediment delivery has been validated with satisfactory predictions. Therefore, the modelling framework proposed may be adopted to diverse river basins for its low parameter requirements and solid modelling performance.

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“…The percentage of rock in a basin's surface is neglected by the USLE‐based models when this is not large enough to be considered a land‐cover category (Kaffas et al, 2021). To compensate for this limitation, we include an additional factor to the original MUSLE as suggested by Box and Meyer (1984).…”

Section: Methodology and Methodsmentioning

confidence: 99%

Forecasting soil erosion and sediment yields during flash floods: The disastrous case of Mandra, Greece, 2017

Kaffas

Papaioannou

Varlas

et al. 2022

Earth Surf Processes Landf

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Flash floods, among the most destructive natural hazards, are commonly studied as to their catastrophic power in terms of fatalities, infrastructure damages and economic losses. A devastating aftermath of flash floods, which has not received much‐deserved attention in the literature, is the sizeable and permanent soil loss due to soil erosion and sediment yields. This study aims at forecasting soil erosion and sediment yields due to the disastrous storm event that occurred in Mandra town (western Attica, Greece) on 15 November 2017. Gridded hydrometeorological forecasts were conducted at 5‐min and 1‐h time steps by means of the chemical hydrological atmospheric ocean wave system (CHAOS). The forecasts of soil erosion and sediment yields were achieved by a high‐resolution geographic information system (GIS) application of the modified universal soil loss equation (MUSLE) on the basis of the forecasted surface runoff hydrographs. The entire event lasted from the afternoon of 14 November until noon of 15 November, but the bulk of the disastrous storm occurred in the morning of 15 November 2017, flooding two torrent basins. As a result of the extreme flash flood, 2195 tons and 1435 tons of sediment were forecasted to be detached from the body of the soil's surface and transported to the stream networks of the Soures and Agia Aikaterini Torrent basins which cross Mandra. Soil erosion maps were constructed for every hour and the spatial and temporal evolution of soil erosion was shown throughout the event. This study provides concrete insights on the erosion‐prone areas of the study basins, which can inform actions against erosion.

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A USLE-based model with modified LS-factor combined with sediment delivery module for Alpine basins

Cited by 28 publications

References 70 publications

Assessment of current reservoir sedimentation rate and storage capacity loss: An Italian overview

Assessment of current reservoir sedimentation rate and storage capacity loss: An Italian overview

Predicting soil erosion and sediment delivery in large, data‐sparse, mountainous basins

Forecasting soil erosion and sediment yields during flash floods: The disastrous case of Mandra, Greece, 2017

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