A high-resolution soil erosion risk map of Switzerland as strategic policy support system

Prasuhn, Volker; Liniger, Hanspeter; Gisler, Simon; Herweg, Karl Günter; Candinas, Anton; Clément, Jean‐Pierre

doi:10.1016/j.landusepol.2012.11.006

Cited by 86 publications

(60 citation statements)

References 48 publications

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“…Considering the geometrical resolution of DEMs, many studies found that better model performances are reported in the range of four to 10 m, while coarser pixels generate poor performances [38][39][40]; however, at the same time, it seems that no linear relationship is guaranteed between finer DEM resolution and better reliability, in terms of model output.…”

Section: The Planning Outcomesmentioning

confidence: 99%

The Integration of Ecosystem Services in Planning: An Evaluation of the Nutrient Retention Model Using InVEST Software

Salata

Garnero

Barbieri

et al. 2017

Land

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Abstract:Mapping ecosystem services (ES) increases the awareness of natural capital value, leading to building sustainability into decision-making processes. Recently, many techniques to assess the value of ES delivered by different scenarios of land use/land cover (LULC) are available, thus becoming important practices in mapping to support the land use planning process. The spatial analysis of the biophysical ES distribution allows a better comprehension of the environmental and social implications of planning, especially when ES concerns the management of risk (e.g., erosion, pollution). This paper investigates the nutrient retention model of InVEST software through its spatial distribution and its quantitative value. The model was analyzed by testing its response to changes in input parameters: (1) the digital terrain elevation model (DEM); and (2) different LULC attribute configurations. The paper increases the level of attention to specific ES models that use water runoff as a proxy of nutrient delivery. It shows that the spatial distribution of biophysical values is highly influenced by many factors, among which the characteristics of the DEM and its interaction with LULC are included. The results seem to confirm that the biophysical value of ES is still affected by a high degree of uncertainty and encourage an expert field campaign as the only solution to use ES mapping for a regulative land use framework.

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Section: The Planning Outcomesmentioning

confidence: 99%

The Integration of Ecosystem Services in Planning: An Evaluation of the Nutrient Retention Model Using InVEST Software

Salata

Garnero

Barbieri

et al. 2017

Land

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“…This initiative corresponds to the growing demand for soil erosion risk maps in Europe (PRASUHN et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Usually soil erosion risk maps are obtained based on erosion models (PRASUHN et al 2013). When dealing with soil erosion modeling one can choose from several different approaches ranging from indicator-based ones to advanced process-based models.…”

Section: Introductionmentioning

confidence: 99%

“…It has been used for erosion risk assessment in many European countries as well as for European-wide studies . USLE/RUSLE based high-resolution erosion risk maps for entire regions, and even countries, are also available (e.g., PRASUHN et al 2013;TETZLAFF et al 2013;MARTÍN-FERNÁ NDEZ and MARTÍNEZ-NÚ Ň EZ 2011;PARK et al 2011;DEUMLICH et al 2006). In Poland, this approach has never been applied as a tool of regional high-resolution assessment for soil erosion risks.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

Drzewiecki

Wężyk

Pierzchalski

et al. 2013

Pure Appl. Geophys.

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Abstract-In 2011 the Marshal Office of Małopolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Małopolska region was done based on the USLE approach. The special workflow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km 2 ). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Małopolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of areas (municipalities) according to erosion control needs is visible. The study shows that, high-resolution satellite imagery and OBIA may be efficiently used for P-factor mapping and thus contribute to a refined soil erosion risk assessment.

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“…An exhaustive review is provided by De Vente and Poesen (2005), who underlined the fact that the existing approaches consider a variety of parameters, but none of them fulfills all modeling objectives. One of the most commonly applied methods for soil erosion estimation is the Revised Universal Soil Loss Equation (RUSLE) derived from USLE (Wischmeier and Smith, 1978), which has received considerable improvements after the introduction of geographic information systems and has been then applied to a large variety of environments (Desmet and Govers, 1996;Prasannakumar et al, 2012;Prasuhn et al, 2013;Zhang et al, 2013). The RUSLE model provides an estimate of long-term average water soil erosion rate in t ha yr −1 , which is obtained by multiplying five factors (R, rainfall erosivity; K, soil erodibility, LS, topography; C, vegetation cover; P , soil protection practices).…”

mentioning

confidence: 99%

Soil erosion in an avalanche release site (Valle d'Aosta: Italy): towards a winter factor for RUSLE in the Alps

Stanchi

Freppaz

Ceaglio³

et al. 2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Soil erosion in Alpine areas is mainly related to extreme topographic and weather conditions. Although different methods of assessing soil erosion exist, the knowledge of erosive forces of the snow cover needs more investigation in order to allow soil erosion modeling in areas where the snow lays on the ground for several months. This study aims to assess whether the RUSLE (Revised Universal Soil Loss Equation) empirical prediction model, which gives an estimation of water erosion in t ha yr −1 obtained from a combination of five factors (rainfall erosivity, soil erodibility, topography, soil cover, protection practices) can be applied to mountain areas by introducing a winter factor (W ), which should account for the soil erosion occurring in winter time by the snow cover. The W factor is calculated from the ratio of Ceasium-137 ( 137 Cs) to RUSLE erosion rates. Ceasium-137 is another possible way of assessing soil erosion rates in the field. In contrast to RUSLE, it not only provides waterinduced erosion but integrates all erosion agents involved. Thus, we hypothesize that in mountain areas the difference between the two approaches is related to the soil erosion by snow. In this study we compared 137 Cs-based measurement of soil redistribution and soil loss estimated with RUSLE in a mountain slope affected by avalanches, in order to assess the relative importance of winter erosion processes such as snow gliding and full-depth avalanches. Three subareas were considered: DS, avalanche defense structures, RA, release area, and TA, track area, characterized by different prevalent winter processes. The RUSLE estimates and the 137 Cs redistribution gave significantly different results. The resulting ranges of W evidenced relevant differences in the role of winter erosion in the considered subareas, and the application of an avalanche simulation model corroborated these findings. Thus, the higher rates obtained with the 137 Cs method confirmed the relevant role of winter soil erosion. Despite the limited sample size (11 points), the inclusion of a W factor in RUSLE seems promising for the improvement of soil erosion estimates in Alpine environments affected by snow movements.

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A high-resolution soil erosion risk map of Switzerland as strategic policy support system

Cited by 86 publications

References 48 publications

The Integration of Ecosystem Services in Planning: An Evaluation of the Nutrient Retention Model Using InVEST Software

The Integration of Ecosystem Services in Planning: An Evaluation of the Nutrient Retention Model Using InVEST Software

Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

Soil erosion in an avalanche release site (Valle d'Aosta: Italy): towards a winter factor for RUSLE in the Alps

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