A geospatial approach to assessing soil erosion in a watershed by integrating socio-economic determinants and the RUSLE model

Bhandari, Krishna Prasad; Aryal, Jagannath; Darnsawasdi, Rotchanatch

doi:10.1007/s11069-014-1321-2

Cited by 55 publications

(22 citation statements)

References 21 publications

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“…To study the changes in soil erosion and the conditions under which it occurs, researchers have examined the formation and changes in global soil erosion from ancient times to the present, and summarized efforts to restore and conserve soil, through terracing, reforesting, agriculture size, etc. [1,35]. Water erosion on watershed slopes is a complex process that brings together the impact of raindrops, removal of slope deposits and transport of loose material by overland flow [36].…”

Section: Discussionmentioning

confidence: 99%

Study of soil water-erosion intensity and vegetation cover of an oak-spruce forest in the Pokutsko-Bukovina Carpathians, Ukraine

Blinkova¹,

Lavrov²

2017

ARCH BIOL SCI BELGRA

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The effect of soil erosion on dynamic changes in vegetation cover is an important subject of regional ecological research of the Ukrainian Carpathians. Studies on soil erosion on the Pokutsko-Bukovina Carpathians have focused on the impact of soil water erosion on tree, shrub and herbaceous layers in intensive, moderate, slight and light erosion zones. Results have shown that the intensity of water erosion and runoff, which depend on slope steepness, have a great impact on changes in the vegetation cover. This paper compares the main morphometric parameters of formed ravines, the health and composition of trees, and the composition of the herbaceous layer. The floristic list of the all experimental plots comprised 61 grass species. The stands formed Quercus robur L. and Abies alba L. Assessment of the functional types of plant species showed that the balance between competition, stress and disturbance is disrupted along a gradient of water-erosion soil transformation. Soil erosion is likely to have caused a change in the edaphic matrix. The distribution of life forms is also disturbed. Analysis of species richness of the vegetation cover under water erosion and the prevailing soil conditions showed that the values of indices depend on erosion intensity.

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Section: Discussionmentioning

confidence: 99%

Study of soil water-erosion intensity and vegetation cover of an oak-spruce forest in the Pokutsko-Bukovina Carpathians, Ukraine

Blinkova¹,

Lavrov²

2017

ARCH BIOL SCI BELGRA

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“…Humans can never destroy natural erosion or tolerable soil erosion [51]. However, humans' significant contribution to accelerating and decelerating soil erosion is well documented at various spatiotemporal scales and in various geographical locations [52][53][54][55]. Consequently, one of the key tasks of soil conservation is to avoid human-accelerated erosion [53].…”

Section: Enlightenment After the Comparison Of The Two Sc Methodsmentioning

confidence: 99%

Uncertainties of Two Methods in Selecting Priority Areas for Protecting Soil Conservation Service at Regional Scale

Zhang

Lü

et al. 2017

Sustainability

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Soil conservation (SC) is an important ecosystem regulating service. At present, methods for SC mapping to identify priority areas are primarily based on empirical soil erosion models, such as the RUSLE (Revised Universal Soil Loss Equation) based model. However, the parameters of the empirical soil conservation model are based on long-term observations of field experiments at small spatial scales, which are very difficult to obtain and must be simplified when implementing these models at large spatial scales. Such simplification of model parameters may lead to uncertainty in quantifying SC at regional scale. In this study, we have analyzed a new method to map SC in Jiangxi Province of China based on the multiplication of multiple biophysical data. After comparing the spatial-temporal changes of SC from the RUSLE based model and those from the surrogate indicator based method in the study area, the similarities and differences of these methods for identifying SC priority areas were revealed. The result showed that the two methods similarly represented the effects of vegetation coverage and land use types on SC, however, they were significantly different in representing the spatial pattern of SC priority areas and its temporal change. Based on the comparisons, the advantages and drawbacks for both methods were made clear and suggestions were made for the suitable use of the two methods, which may benefit for the research and application of concerning the planning and assessment with SC as key criteria.

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“…The integration of the commonly used soil loss and sediment yield models, Revised / Universal Soil Loss Equation (R/USLE) (e.g. Arekhi et al, 2012;Bhandari et al, 2015;Meusburger et al, 2010), Soil and water assessment tool (SWAT) model (e.g. Wang et al, 2015) or G2 model (Panagos et al, 2012) to remote sensing data in GIS platform have boosted watershed management (e.g.…”

Section: Remote Sensing In Soil Erodibility and Landslide Mappingmentioning

confidence: 99%

Landslide scar/soil erodibility mapping using Landsat TM/ETM+ bands 7 and 3 Normalised Difference Index: A case study of central region of Kenya

et al. 2015

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Landsat series multispectral remote sensing imagery has gained increasing attention in providing solutions to environmental problems such as land degradation which exacerbate soil erosion and landslide disasters in the case of rainfall events. Multispectral data has facilitated the mapping of soils, land-cover and structural geology, all of which are factors affecting landslide occurrence. The main aim of this research was to develop a methodology to visualize and map past landslides as well as identify land degradation effects through soil erosion and land-use using remote sensing techniques in the central region of Kenya. The study area has rugged terrain and rainfall has been the main source of landslide trigger. The methodology comprised visualizing landslide scars using a False Colour Composite (FCC) and mapping soil erodibility using FCC components applying expert based classification. The components of the FCC were: the first independent component (IC1), Principal Component (PC) with most geological information, and a Normalised Difference Index (NDI) involving Landsat TM/ETM+ band 7 and 3. The FCC components formed the inputs for knowledge-based classification with the following 13 classes: runoff, extreme erosions, other erosions, landslide areas, highly erodible, stable, exposed volcanic rocks, agriculture, green forest, new forest regrowth areas, clear, turbid and salty water. Validation of the mapped landslide areas with field GPS locations of landslide affected areas showed that 66% of the points coincided well with landslide areas mapped in the year 2000. The classification maps showed landslide areas on the steep ridge faces, other erosions in agricultural areas, highly erodible zones being already

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A geospatial approach to assessing soil erosion in a watershed by integrating socio-economic determinants and the RUSLE model

Cited by 55 publications

References 21 publications

Study of soil water-erosion intensity and vegetation cover of an oak-spruce forest in the Pokutsko-Bukovina Carpathians, Ukraine

Study of soil water-erosion intensity and vegetation cover of an oak-spruce forest in the Pokutsko-Bukovina Carpathians, Ukraine

Uncertainties of Two Methods in Selecting Priority Areas for Protecting Soil Conservation Service at Regional Scale

Landslide scar/soil erodibility mapping using Landsat TM/ETM+ bands 7 and 3 Normalised Difference Index: A case study of central region of Kenya

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