An attempt to estimate tolerable soil erosion rates by matching soil formation with denudation in Alpine grasslands

Alewell, Christine; Egli, Markus; Meusburger, Katrin

doi:10.1007/s11368-014-0920-6

Cited by 78 publications

(76 citation statements)

References 73 publications

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“…The soil loss tolerance value serves as a basis for judging whether soil has a potential risk for productivity loss or generally for soil degradation [61]. About 39% of Uganda's erosion-prone lands had an unsustainable mean estimated soil erosion rate >1 t·ha −1 ·y −1 (Figure 5b and Table 3) [56][57][58].…”

Section: Overview Of Estimated Soil Erosion Risk In Ugandamentioning

confidence: 99%

Soil Erosion Risk Assessment in Uganda

Karamage

Zhang

Liu

et al. 2017

Forests

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Land use without adequate soil erosion control measures is continuously increasing the risk of soil erosion by water mainly in developing tropical countries. These countries are prone to environmental disturbance due to high population growth and high rainfall intensity. The aim of this study is to assess the state of soil erosion by water in Uganda at national and district levels, for various land cover and land use (LCLU) types, in protected areas as well to predict the impact of support practices on soil loss reduction. Predictions obtained using the Revised Universal Soil Loss Equation (RUSLE) model indicated that the mean rate of soil loss risk in Uganda's erosion-prone lands was 3.2 t·ha −1 ·y −1 , resulting in a total annual soil loss of about 62 million tons in 2014. About 39% of the country's erosion-prone lands were comprised of unsustainable mean soil loss rates >1 t·ha −1 ·y −1 . Out of 112 districts in Uganda, 66 districts were found to have unsustainable estimated soil loss rates >1 t·ha −1 ·y −1 . Six districts in Uganda were found to have mean annual soil loss rates of >10 t·ha −1 ·y −1 : Bududa (46.3 t·ha −1 ·y −1 ), Kasese (37.5 t·ha −1 ·y −1 ), Bundibugyo (28.9 t·ha −1 ·y −1 ), Bulambuli (20.9 t·ha −1 ·y −1 ), Sironko (14.6 t·ha −1 ·y −1 ) and Kotido (12.5 t·ha −1 ·y −1 ). Among the LCLU types, the highest soil loss rates of 11 t·ha −1 ·y −1 and 10.6 t·ha −1 ·y −1 were found in moderate natural forest and dense natural forest, respectively, mainly due to their locations in highland areas characterized by steep slopes ranging between 16% to 21% and their high rainfall intensity, ranging from 1255 mm·y −1 to 1292 mm·y −1 . Only five protected areas in Uganda were found to have high mean estimated mean soil loss rates >10 t·ha −1 ·y −1 : Rwenzori Mountains (142.94 t·ha −1 ·y −1 ), Mount Elgon (33.81 t·ha −1 ·y −1 ), Bokora corridor (12.13 t·ha −1 ·y −1 ), Matheniko (10.39 t·ha −1 ·y −1 ), and Nangolibwel (10.33 t·ha −1 ·y −1 ). To manage soil erosion in Uganda's protected areas, there is an urgent need to control wildfires and human-induced disturbances such as timber harvesting and soil compaction from domestic animals. Our study analysis revealed that well-established terraces and strip-cropping could significantly reduce soil loss rates in Uganda's croplands by 80% (from 1.5 t·ha −1 ·y −1 to 0.3 t·ha −1 ·y −1 ) and by 47% (from 1.5 t·ha −1 ·y −1 to 0.8 t·ha −1 ·y −1 ), respectively, well below the sustainable soil erosion tolerance rate (1 t·ha −1 ·y −1 ) for land and water conservation.

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Section: Overview Of Estimated Soil Erosion Risk In Ugandamentioning

confidence: 99%

Soil Erosion Risk Assessment in Uganda

Karamage

Zhang

Liu

et al. 2017

Forests

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“…According to Fujisaka (1994), due to excessive reductions in soil depth, sustainable agriculture cannot be maintained in the distant future. Alewell et al (2014) evaluated the soil erosion rates of the Urseren Valley in Switzerland using the USLE model plus soil loss due to landslides. These calculations yielded soil losses of 1.80 ton ha -1 year -1 , which considerably exceeds the production rates of the soils.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of Soil Erosion and Sustainable Land Use Management in the Sarısu Basin

Karaş

Oğuz

2017

Turkish JAF Sci.Tech.

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Land use management requires controlling natural resources for sustainability. Soil erosion related to improper land use is a major issue around the world. Land degradation may harm the health of ecosystems. Defining the soil loss in a basin is the starting point in the restoration of soil quality for crop production. Reducing soil losses to a tolerable rate is one of the primary objectives for sustainability and soil conservation. Central Anatolia is under considerable risk due to an increase in the cultivation of marginal lands for food production. Cultivated lands have already been reached the final limits throughout the last 50 years. Moreover, forests and considerable areas of pasture have recently been converted to ploughed fields due to agricultural expansion. This study was conducted in the Sarısu basin to evaluate soil losses and land use management for sustainability. The Universal Soil Loss Equation model and Geographic Information System techniques were used to estimate the soil losses. The mean potential soil loss of the basin was calculated to be 1.88 t ha-1 per year with the Universal Soil Loss Equation model. These results are comparatively small when compared to the average value for Turkey of 13 t ha-1 yearly. Our calculated results are closer to the value for the Sakarya river basin, which is approximately 2.77 t ha-1 y-1. In this study, land usages in the Sarısu basin were evaluated in terms of soil losses, tolerable soil loss rates and soil conservation precautions.

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“…Landslides and erosion represent major challenges for natural hazard management and sustainable agriculture in mountain areas (Turner et al, 1996;Alewell et al, 2015). Being a specific type of gravitational mass movements, landslides shape the landscape and they can cause damage on humans and infrastructure (Kjekstad and Highland, 2009;Petley, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Being a specific type of gravitational mass movements, landslides shape the landscape and they can cause damage on humans and infrastructure (Kjekstad and Highland, 2009;Petley, 2012). Furthermore, these processes lead to a loss of soil and degrade agricultural land (Wiegand and Geitner, 2010;Alewell et al, 2015). These problems concern both the occurrence of new landslides and the reactivation and secondary erosion of existing ones.…”

Section: Introductionmentioning

confidence: 99%

Multitemporal Analysis of Objects in 3d Point Clouds for Landslide Monitoring

Mayr¹,

Rutzinger²,

Geitner³

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:To date multi-temporal 3D point clouds from close-range sensing are used for landslide and erosion monitoring in an operational manner. Morphological changes are typically derived by calculating distances between points from different acquisition epochs. The identification of the underlying processes resulting in surface changes, however, is often challenging, for example due to the complex surface structures and influences from seasonal vegetation dynamics. We present an approach for object-based 3D landslide monitoring based on topographic LiDAR point cloud time series separating specific surface change types automatically. The workflow removes vegetation and relates surface changes derived from a point cloud time series directly to (i) geomorphological object classes (landslide scarp, eroded area, deposit) and (ii) to individual, spatially contiguous objects (such as parts of the landslide scarp and clods of material moving in the landslide). We apply this approach to a time series of nine point cloud epochs from a slope affected by two shallow landslides. A parameter test addresses the influence of the registration error and the associated level of detection on the magnitude of derived object changes. The results of our case study are in accordance with field observations at the test site as well as conceptual landslide models, where retrogressive erosion of the scarp and downslope movement of the sliding mass are major principles of secondary landslide development. We conclude that the presented methods are well suited to extract information on geomorphological process dynamics from the complex point clouds and aggregate it at different levels of abstraction to assist landslide and erosion assessment.

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An attempt to estimate tolerable soil erosion rates by matching soil formation with denudation in Alpine grasslands

Cited by 78 publications

References 73 publications

Soil Erosion Risk Assessment in Uganda

Soil Erosion Risk Assessment in Uganda

Evaluation of Soil Erosion and Sustainable Land Use Management in the Sarısu Basin

Multitemporal Analysis of Objects in 3d Point Clouds for Landslide Monitoring

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