Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

Meusburger, Katrin; Konz, Nadine; Schaub, Monika; Alewell, Christine

doi:10.1016/j.jag.2010.02.004

Cited by 88 publications

(48 citation statements)

References 32 publications

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“…9), even if a lower value was observed in the TA (8.8 Mg ha −1 yr −1 vs. 13.4 Mg ha −1 yr −1 in RA and 12.6 Mg ha −1 yr −1 in SB). These values were in the range of yearly values (7-37 Mg ha −1 yr −1 ) determined, also with the 137 Cs method, by Konz et al (2009Konz et al ( , 2010 for steep alpine slopes in the Central Swiss Alps, which were also partly heavily affected by avalanche activity. Taking into account the mean bulk density of the different soil layers, the erosion rates ranged between 0.97 mm yr −1 and 1.90 mm yr −1 in TA and SB, equivalent to a total soil erosion, during the 24-yr period (1986-2010) of 23.29 mm and 45.71 mm, respectively.…”

Section: Assessment Of Total Soil Erosion Rates Using 137 Cs Approachsupporting

confidence: 55%

“…Moreover the estimates of erosion due to the avalanche activity were significantly greater than the erosion rates related only to runoff processes during the growing season. For example Konz et al (2010) found values in the range of 0-68 kg ha −1 month −1 , and also other studies confirmed low erosion rates during the vegetation period (e.g. Felix and Johannes, 1995;Simonato et al, 2002), even if the effective magnitude of this process depends strongly Fig.…”

Section: Comparison Between the Conventional And The 137 Cs Approachessupporting

confidence: 53%

“…However, only few studies exist on soil erosion measurement and quantification in lowmountain ranges (e.g. Nearing et al, 1999;Leser et al, 2002;Gabriels et al, 2003;Prasuhn et al, 2007) or in alpine environments characterized by specific climatic and topographic conditions (Felix and Johannes, 1995;Descroix and Mathys, 2003;Isselin-Nondedeu and Bedecarrats, 2007;Konz et al, 2009Konz et al, , 2010Konz et al, , 2011Meusburger et al, 2010). Moreover, most of the studies focus on soil erosion measurement during the vegetation period, while only few works deal with soil erosion caused by snow movements related processes (Ackroyd, 1987;Bell et al, 1990;Kohl et al, 2001;Heckmann et al, 2005;Konz et al, 2009Konz et al, , 2011Freppaz et al,, 2010).…”

Section: E Ceaglio Et Al: Soil Redistribution Rates and Snow Movementsmentioning

confidence: 99%

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Estimation of soil redistribution rates due to snow cover related processes in a mountainous area (Valle d'Aosta, NW Italy)

Ceaglio

Meusburger

Freppaz

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. Mountain areas are widely affected by soil erosion, which is generally linked to runoff processes occurring in the growing season and snowmelt period. Also processes like snow gliding and full-depth snow avalanches may be important factors that can enhance soil erosion, however the role and importance of snow movements as agents of soil redistribution are not well understood yet. The aim of this study was to provide information on the relative importance of snow related processes in comparison to runoff processes. In the study area, which is an avalanche path characterized by intense snow movements, soil redistribution rates were quantified with two methods: (i) by field measurements of sediment yield in an avalanche deposition area during 2009 and 2010 winter seasons; (ii) by caesium-137 method, which supplies the cumulative net soil loss/gain since 1986, including all the soil erosion processes. The snow related soil accumulation estimated with data from the deposit area (27.5 Mg ha −1 event −1 and 161.0 Mg ha −1 event −1 ) was not only higher than the yearly sediment amounts, reported in literature, due to runoff processes, but it was even more intense than the yearly total deposition rate assessed with 137 Cs (12.6 Mg ha −1 yr −1 ). The snow related soil erosion rates estimated from the sediment yield at the avalanche deposit area (3.7 Mg ha −1 and 20.8 Mg ha −1 ) were greater than the erosion rates reported in literature and related to runoff processes; they were comparable to the yearly total erosion rates assessed with the 137 Cs method (13.4 Mg ha −1 yr −1 and 8.8 Mg ha −1 yr −1 ). The 137 Cs method also showed that, where the ground avalanche does not release, the erosion and deposition of soil particles from the upper part of the basin was considerable and likely related to snow gliding. Even though the comparison of both the approaches is linked to high methodological uncertainties, mainly due to the different spatial and temporal scales considered, we still can deduce, from the similarity of the erosion rates, that soil redistribution in this catchment is driven by snow movement, with a greater impact in comparison to the runoff processes occurring in the snow-free season. Nonetheless, the study highlights that soil erosion processes due to the snow movements should be considered in the assessment of soil vulnerability in mountain areas, as they significantly determine the pattern of soil redistribution.

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Section: Assessment Of Total Soil Erosion Rates Using 137 Cs Approachsupporting

confidence: 55%

Section: Comparison Between the Conventional And The 137 Cs Approachessupporting

confidence: 53%

Section: E Ceaglio Et Al: Soil Redistribution Rates and Snow Movementsmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of soil redistribution rates due to snow cover related processes in a mountainous area (Valle d'Aosta, NW Italy)

Ceaglio

Meusburger

Freppaz

et al. 2012

Hydrol. Earth Syst. Sci.

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“…Land use classification derived from these satellite data allows for a better spatial and substantial distinction between different land use classes. This is shown in different studies, where land use classification derived from e.g., QuickBird or IKONOS-2 data is used for different applications, e.g., agricultural, environmental or soil erosion topics [11][12][13]. Nevertheless, multi-spectral scanners are restricted by lower data availability due to haze or clouds, especially when based on a satellite system.…”

Section: Introductionmentioning

confidence: 99%

Multi-Temporal Land-Cover Classification of Agricultural Areas in Two European Regions with High Resolution Spotlight TerraSAR-X Data

Bargiel

Herrmann

2011

Remote Sensing

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Functioning ecosystems offer multiple services for human well-being (e.g., food, freshwater, fiber). Agriculture provides several of these services but also can cause negative impacts. Thus, it is essential to derive up-to-date information about agricultural land use and its change. This paper describes the multi-temporal classification of agricultural land use based on high resolution spotlight TerraSAR-X images. A stack of l4 dual-polarized radar images taken during the vegetation season have been used for two different study areas (North of Germany and Southeast Poland). They represent extremely diverse regions with regard to their population density, agricultural management, as well as geological and geomorphological conditions. Thereby, the transferability of the classification method for different regions is tested. The Maximum Likelihood classification is based on a high amount of ground truth samples. Classification accuracies differ in both regions. Overall accuracy for all classes for the German area is 61.78% and 39.25% for the Polish region. Accuracies improved notably for both regions (about 90%) when single vegetation classes were merged into groups of classes. Such regular land use classifications, applicable for different European agricultural sites, can serve as basis for monitoring systems for agricultural land use and its related ecosystems.

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“…High LS values are largely documented in the literature for non-agricultural environments. For example, Meusburger et al (2010) reported LS values in the range 0-57.5 for a study site in the Swiss Alps with an average slope of 24.6 • . The slope angle interval (Table 1) confirms that the area is potentially prone to both snow gliding (Leitinger et al, 2008) and glide-snow avalanches (Confortola et al, 2012).…”

Section: Rusle-based Average Long-term Erosion Ratesmentioning

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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Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

Cited by 88 publications

References 32 publications

Estimation of soil redistribution rates due to snow cover related processes in a mountainous area (Valle d'Aosta, NW Italy)

Estimation of soil redistribution rates due to snow cover related processes in a mountainous area (Valle d'Aosta, NW Italy)

Multi-Temporal Land-Cover Classification of Agricultural Areas in Two European Regions with High Resolution Spotlight TerraSAR-X Data

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

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