An assessment of the global impact of 21st century land use change on soil erosion

Borrelli, Pasquale; Robinson, David A.; Fleischer, Larissa R.; Lugato, Emanuele; Ballabio, Cristiano; Alewell, Christine; Meusburger, Katrin; Modugno, Sirio; Schütt, Brigitta; Ferro, Vito; Bagarello, Vincenzo; Oost, Kristof Van; Montanarella, Luca; Panagos, Panos

doi:10.1038/s41467-017-02142-7

Cited by 1,809 publications

(1,156 citation statements)

References 63 publications

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“…Recent large‐scale modelling approaches showed substantial progress in the spatial description of these soil degradation process influence factors. This has especially become possible through a wider integration of geospatial technologies such as GISs, satellite data, and robust spatial interpolations (Borrelli et al, ; Cerdan et al, ; Fleskens, Kirkby, & Irvine, ; Panagos, Borrelli, Meusburger, et al, ; Teng et al, ; Yue et al, , among others). Human influence on the landscape through land use as the main driver of soil erosion, however, is still roughly approximated in most modelling studies dealing with study areas that reach beyond a few square kilometres in study area size.…”

Section: Introductionmentioning

confidence: 99%

Object‐oriented soil erosion modelling: A possible paradigm shift from potential to actual risk assessments in agricultural environments

et al. 2018

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Over the last 2 decades, geospatial technologies such as Geographic Information System and spatial interpolation methods have facilitated the development of increasingly accurate spatially explicit assessments of soil erosion. Despite these advances, current modelling approaches rest on (a) an insufficient definition of the proportion of arable land that is exploited for crop production and (b) a neglect of the intra‐annual variability of soil cover conditions in arable land. To overcome these inaccuracies, this study introduces a novel spatio‐temporal approach to compute an enhanced cover‐management factor (C) for revised universal soil loss equation‐based models. It combines highly accurate agricultural parcel information contained in the Land Parcel Identification System with an object‐oriented Landsat imagery classification technique to assess spatial conditions and interannual variability of soil cover conditions at field scale. With its strong link to Land Parcel Identification System and Earth observation satellite data, the approach documents an unprecedented representation of farming operations. This opens the door for the transition from the currently used potential soil erosion risk assessments towards the assessment of the actual soil erosion risk. Testing this method in a medium‐size catchment located in the Swiss Plateau (Upper Enziwigger River Catchment), this study lays an important foundation for the application of the very same methods for large‐scale or even pan‐European applications. Soil loss rates modelled in this study were compared with the insights gained from emerging techniques to differentiate sediment source contribution through compound‐specific isotope analysis on river sediments. The presented technique is adaptable beyond revised universal soil loss equation‐type soil erosion models.

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Section: Introductionmentioning

confidence: 99%

Object‐oriented soil erosion modelling: A possible paradigm shift from potential to actual risk assessments in agricultural environments

et al. 2018

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“…However, future work is required to reduce error for field SfM surveys in peatlands, and for other environments (Borrelli et al, 2017) where erosion or deposition is only a few cm or mm per year. However, future work is required to reduce error for field SfM surveys in peatlands, and for other environments (Borrelli et al, 2017) where erosion or deposition is only a few cm or mm per year.…”

Section: Implications Of Sfm Applications For Peat Erosion Studymentioning

confidence: 99%

Patterns and drivers of peat topographic changes determined from Structure‐from‐Motion photogrammetry at field plot and laboratory scales

Grayson

Smith

et al. 2019

Earth Surf Processes Landf

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Little is known about the spatial and temporal variability of peat erosion nor some of its topographic and weather‐related drivers. We present field and laboratory observations of peat erosion using Structure‐from‐Motion (SfM) photogrammetry. Over a 12 month period, 11 repeated SfM surveys were conducted on four geomorphological sites of 18–28 m2 (peat hagg, gully wall, riparian area and gully head) in a blanket peatland in northern England. A net topographic change of –14 to +30 mm yr–1 for the four sites was observed during the whole monitoring period. Cold conditions in the winter of 2016 resulted in highly variable volume change (net surface topographic rise first and lowering afterwards) via freeze–thaw processes. Long periods of dry conditions in the summer of 2017 led to desiccation and drying and cracking of the peat surface and a corresponding surface lowering. Topographic changes were mainly observed over short‐term intervals when intense rainfall, flow wash, needle‐ice production or surface desiccation was observed. In the laboratory, we applied rainfall simulations on peat blocks and compared the peat losses quantified by traditional sediment flux measurements with SfM derived topographic data. The magnitude of topographic change determined by SfM (mean value: 0.7 mm, SD: 4.3 mm) was very different to the areal average determined by the sediment yield from the blocks (mean value: –0.1 mm, SD: 0.1 mm). Topographic controls on spatial patterns of topographic change were illustrated from both field and laboratory surveys. Roughness was positively correlated to positive topographic change and was negatively correlated to negative topographic change at field plot scale and laboratory macroscale. Overall, the importance of event‐scale change and the direct relationship between surface roughness and the rate of topographic change are important characteristics which we suggest are generalizable to other environments. © 2018 John Wiley & Sons, Ltd.

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“…Rill erosion is one of the most important soil degradation processes because it is responsible of a large amount of soil loss (Borrelli et al, ; Di Stefano, Ferro, Pampalone, & Sanzone, ; Rejman & Brodowski, ; Wirtz, Seeger, & Ries, ). Measurement of rill channels can be carried out by direct and indirect methods.…”

Section: Introductionmentioning

confidence: 99%

An automatic approach for rill network extraction to measure rill erosion by terrestrial and low‐cost unmanned aerial vehicle photogrammetry

Stefano

Palmeri

Pampalone

2019

Hydrological Processes

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For an erosion event (October 2016) occurred at the Sparacia experimental area (Southern Italy), both terrestrial and low‐altitude aerial surveys were carried out by consumer grade camera and quadcopter (low‐cost unmanned aerial vehicle [UAV]) to measure rill erosion on two plots with steepness of 22% and 26%. Applying the structure from motion (SfM) technique, the three‐dimensional digital terrain models (3D‐DTMs) and the quasi three‐dimensional models (2.5D‐digital elevation model [DEM]) were obtained by the two surveys. Furthermore, 3D‐DTM and DEM were built using the available aerial photographs (166) and adding 40 terrestrial photographs. For the first time, the convergence index was applied to high‐resolution rill data for extracting the rill network, and a subsequent separation into contributing and non‐contributing rills was carried out. The comparison among the three surveys (terrestrial, UAV, and UAV + terrestrial) was developed using two morphometric parameters of the rill network (drainage density and drainage frequency). Moreover, using as reference the weight of sediment stored on the tanks located downstream of the plots, the reliability of soil loss measurement by 3D models was tested. For both contributing and non‐contributing rills, the morphometric parameters were higher for the terrestrial than for UAV and UAV + terrestrial surveys. For both plots, SfM always provided reliable soil loss measurements, which were affected by errors ranging from −8% to 13%. Although the applied technique used a low‐cost UAV and a consumer grade camera, the obtained results demonstrated that a reliable estimate of rill erosion can be obtained in an area of interest.

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An assessment of the global impact of 21st century land use change on soil erosion

Cited by 1,809 publications

References 63 publications

Object‐oriented soil erosion modelling: A possible paradigm shift from potential to actual risk assessments in agricultural environments

Object‐oriented soil erosion modelling: A possible paradigm shift from potential to actual risk assessments in agricultural environments

Patterns and drivers of peat topographic changes determined from Structure‐from‐Motion photogrammetry at field plot and laboratory scales

An automatic approach for rill network extraction to measure rill erosion by terrestrial and low‐cost unmanned aerial vehicle photogrammetry

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