Comparing different multiple flow algorithms to calculate RUSLE factors of slope length (L) and slope steepness (S) in Switzerland

Bircher, Pascal; Liniger, Hanspeter; Prasuhn, Volker

doi:10.1016/j.geomorph.2019.106850

Cited by 45 publications

(33 citation statements)

References 70 publications

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“…Length and slope (LS-factor) are fundamental for estimating soil erosion rates and the sediment transport capacity (Renard et al, 1997). In RULSE, LS calculation takes into account the upward area contribution and a rillinterrill erosion ratio (Bircher;Liniger;Prasuhn, 2019). The methodology applied in this study was initially based on Pelton, Frazier and Pickilingis (2012) proposal, with the support of Algebra map, which allows the application of the equation developed by Mitasova et al (1996) (Equation 4).…”

Section: A = R • K • Ls • Cp (1)mentioning

confidence: 99%

“…Despite its empirical structure, in its revised version (RUSLE), several applications have been generated at watersheds with restrict database for calibration and validation of the process-based models, using an interface with GIS (Tang et al, 2015). Recent studies have been carried out in different countries and basins using RUSLE, such as Italy (Terranova et al, 2009), Brazil (Beskow et al, 2009), Vietnam (Ranzi;Le;Rulli, 2012), Spain (Fernández;Vega, 2018), Ethiopia (Zerihun et al, 2018), Switzerland (Bircher;Liniger;Prasuhn, 2019), China (Teng et al, 2018), India (Pal;Chakrabortty, 2019), among others.…”

Section: Introductionmentioning

confidence: 99%

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Environmental degradation risk by water erosion in a water producer Colombian Andes basin

2021

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Globally, soil degradation by water erosion has become one of the major environmental problems in tropical regions, especially under the severe environmental conditions of the Andes. This study aims to detail the soil risk to degradation by water erosion in a water producer basin located in the Tropical Colombian Andes (Combeima River basin), applying the RUSLE model, discussing how to minimize the erosion processes under its environmental conditions (steep slope, climatic variability, soil classes and properties diversity, and alternative land uses). RUSLE was applied with the support of GIS to estimate current and potential risk to soil erosion in the basin, allowing the identification of areas more prone to degradation. It was found that currently, 50.5% of the basin’s area presents, on average, annual soil losses greater than 25 Mg ha-1 yr-1, meaning a very high risk to water erosion, with 30.4% showing a severe risk (> 100 Mg ha-1 yr-1). It was possible to conclude that the current land uses and soil management systems have not been effective in mitigating soil erosion, mainly when situated in steep topography. Therefore, it is necessary sustainable planning for the conservation of soil, water, organic carbon, plant nutrients, and other elements (not-nutrients) in this tropical Andes region.

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Section: A = R • K • Ls • Cp (1)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Environmental degradation risk by water erosion in a water producer Colombian Andes basin

2021

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“…Moreover, the resolution of DEM data has influenced the accuracy of LS value, especially in the complex terrain regions [62,63]. The flow direction algorithm is also an effective tool in determining the LS value [64,65]. Given the necessity of these determining factors, we can conclude that the LS is a sensitive aspect of soil loss prediction by the USLE model [66].…”

Section: Erodibility Factor (K)mentioning

confidence: 99%

Understanding Indigenous Farming Systems in Response to Climate Change: An Investigation into Soil Erosion in the Mountainous Regions of Central Vietnam

et al. 2020

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Soil erosion is a considerable concern in the upland areas of Central Vietnam. This situation is most serious in regions, where the terrain is sloped and subjected to heavy rainfall. Our research was conducted in a mountainous area, belonging to Central Vietnam, the area of Song Kon commune in the Dong Giang district. The objective of this study is first to estimate the impact of soil erosion risk in these areas, and second to assess the capacity of farming systems which are based on indigenous knowledge (IK) to respond to soil erosion. Our data were collected by Participatory Rural Appraisal (PRA) and processed using Geographical Information System (GIS) methods. We then interpreted this research using the Universal Soil Loss Equation (USLE) in order to calculate the soil erosion rate. The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) were also used as measurements to compare the difference of land surface covers between different farming systems. The results showed that the lowest soil erosion rate was found in the narrow valley regions, which are populated by both agricultural and residential areas. On the other hand, soil erosion was extremely high in the more northerly quadrant of our research area. Our findings also indicate that local farmers are highly aware of soil erosion, which has positively influenced the adoption of adaptation measures (AMs) in their agricultural activities. The most common AMs are as follows: changes in cropping patterns, the adjustments of their planting calendars, the use of native varieties, and intercropping methods. These AMs are mediated by the cultural observances of the local ethnic minority peoples in relation to their IK. We have concluded that when farmers apply IK in their farming systems, the soil erosion rate tends to decrease as compared with non-indigenous knowledge (NIK) practices. We hope to bring a better understanding of the processes that shape farmers’ AMs and thereby to develop well-targeted adaptation policies that can then be applied at the local level. Our findings may be instrumental in future adaptation planning and policies in regard to climate change, and that they will help to increase awareness not only in matters of the soil erosion but also in other interconnected aspects of climate change in these areas.

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“…This limitation has been removed in the Revised Universal Soil Loss Equation (RUSLE) by taking into consideration the rainfall energy [15]. Recent research, integrating RUSLE in the Geographic Information System (GIS) and remote sensing techniques, aided by the ever-increasing power and efficiency of computers [26], enables estimating soil loss for large areas quickly and at a reasonable cost [27][28][29][30][31][32][33][34][35][36][37][38] in different climatic zones [39].…”

Section: Introductionmentioning

confidence: 99%

New Insight on Soil Loss Estimation in the Northwestern Region of the Zagros Fold and Thrust Belt

Othman¹,

Obaid

Ali

et al. 2021

IJGI

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Soil loss is one of the most important causes of land degradation. It is an inevitable environmental and socio-economic problem that exists in many physiographic regions of the world, which, besides other impacts, has a direct bearing on agricultural productivity. A reliable estimate of soil loss is critical for designing and implementing any mitigation measures. We applied the widely used Revised Universal Soil Loss Equation (RUSLE) in the Khabur River Basin (KhRB) within the NW part of the Zagros Fold and Thrust Belt (ZFTB). The areas such as the NW Zagros range, characterized by rugged topography, steep slope, high rainfall, and sparse vegetation, are most susceptible to soil erosion. We used the Digital Elevation Model (DEM) of the Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), Harmonized World Soil Database (HWSD), and Landsat imagery to estimate annual soil loss using the RUSLE model. In addition, we estimated sediment yield (SY) at sub-basin scale, in the KhRB where a number of dams are planned, and where basic studies on soil erosion are lacking. Estimation of SY will be useful in mitigation of excessive sedimentation affecting dam performance and watershed management in this region. We determined the average annual soil loss and the SY in the KhRB to be 11.16 t.ha−1.y−1 and 57.79 t.ha−1.y−1, respectively. The rainfall and runoff erosivity (R factor), slope length (L factor), and slope steepness (S factor), are the three main factors controlling soil loss in the region. This is the first study to determine soil loss at the sub-basin scale along with identifying suitable locations for check dams to trap the sediment before it enters downstream reservoirs. The study provides valuable input data for design of the dams to prevent excessive siltation. This study also aims at offering a new approach in relating potential soil erosion to the actual erosion and hypsometric integrals.

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Comparing different multiple flow algorithms to calculate RUSLE factors of slope length (L) and slope steepness (S) in Switzerland

Cited by 45 publications

References 70 publications

Environmental degradation risk by water erosion in a water producer Colombian Andes basin

Environmental degradation risk by water erosion in a water producer Colombian Andes basin

Understanding Indigenous Farming Systems in Response to Climate Change: An Investigation into Soil Erosion in the Mountainous Regions of Central Vietnam

New Insight on Soil Loss Estimation in the Northwestern Region of the Zagros Fold and Thrust Belt

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