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Geomorphologic map of the 1<Superscript>st</Superscript> Mutnaya River,Southeastern Kamchatka,Russia
Gheorghe Romanescu Sergey Chalov Cristian Constantin Stoleriu Alin Mihu-Pintilie Silvia Eleonora Angileri Yulia Kuznetsova Mariaelena Cama Michael Maerker 《山地科学学报》2017,14(12):2373-2390
The Kamchatka Peninsula–situated in the Pacific “Ring of Fire”–has 29 active and over 400 extinct volcanoes. Since it is situated in the northeastern extremity of Russia, in subarctic climate, the volcanic landforms are overprinted by the 446 glaciers. This research focuses on the 1stMutnaya catchment which drains the southern slopes of two active volcanoes: Avachinsky and Koryaksky. Those volcanoes are a permanent threat for the cities of Petropavlovsk and Elizovo, which are the 2 of 3 cities of the peninsula. Hence, most of the studies carried out in the area dealt with the natural hazards and only few focus on landscape evolution. Thus, the purpose of this study was to elaborate a cartographic approach which integrates classic geomorphology with state of the art GIS and remote sensing techniques. As result, different landforms and related processes have been analysed and included in the first general geomorphologic map of the 1stMutnaya catchment. 相似文献
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Alberto Bosino Paolo Giordani Geraldine Quénéhervé Michael Maerker 《地球表面变化过程与地形》2020,45(12):3025-3041
Soil erosion is one of the most important environmental problems distributed worldwide. In the last decades, numerous studies have been published on the assessment of soil erosion and the related processes and forms using empirical, conceptual and physically based models. For the prediction of the spatial distribution, more and more sophisticated stochastic modelling approaches have been proposed – especially on smaller spatial scales such as river basins. In this work, we apply a maximum entropy model (MaxEnt) to evaluate badlands (calanchi) and rill–interrill (sheet erosion) areas in the Oltrepo Pavese (Northern Apennines, Italy). The aim of the work is to assess the important environmental predictors that influence calanchi and rill–interrill erosion at the regional scale. We used 13 topographic parameters derived from a 12 m digital elevation model (TanDEM-X) and data on the lithology and land use. Additional information about the vegetation is introduced through the normalized difference vegetation index based on remotely sensed data (ASTER images). The results are presented in the form of susceptibility maps showing the spatial distribution of the occurrence probability for calanchi and rill–interrill erosion. For the validation of the MaxEnt model results, a support vector machine approach was applied. The models show reliable results and highlight several locations of the study area that are potentially prone to future soil erosion. Thus, coping and mitigation strategies may be developed to prevent or fight the soil erosion phenomenon under consideration. © 2020 John Wiley & Sons, Ltd. 相似文献
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Maerker Michael Qu&#;n&#;herv&#; Geraldine Bachofer Felix Mori Simone 《Natural Hazards》2015,76(1):235-257
Gully erosion is a major threat concerning landscape degradation in large areas along the northern Tanzanian Rift valley. It is the dominant erosion process producing large parts of the sediments that are effectively conducted into the river network. The study area is located in the Lake Manyara—Makuyuni River catchment, Arusha, northern Tanzania. During fieldwork, we measured topographic data of eight gully systems close to Makuyuni Town. The main focus of this study is to assess gully erosion dynamics using improved DEMs with original resolutions of 30 and 20 m, respectively. We assessed terrain characteristics to extract information on environmental drivers. To improve the DEM, we integrated information deduced from satellite images as well as from acquired GPS field data. Topographic indices such as Stream Power Index or Transport Capacity Index were derived from the re-interpolated DEM. To evaluate gully evolution, we assessed also the longitudinal slope profiles. Finally, the gully evolution phases of each gully were classified according to the concept proposed by Kosov et al. (Eksperimental’naya geomorfologiya, vol 3. Moscow University, Moskva, pp 113–140, 1978). The re-interpolated DEMs revealed a positive response especially for the more developed gullies. We show that the extraction of information on this spatial process scale based on “low-resolution” data is feasible with little additional fieldwork and image interpretation. In fact, areas identified as having a greater risk of gully erosion have been confirmed by observations and surveys carried out in the field. 相似文献
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A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster 总被引：2，自引：1，他引：1
A model building strategy is tested to assess the susceptibility for extreme climatic events driven shallow landslides. In fact, extreme climatic inputs such as storms typically are very local phenomena in the Mediterranean areas, so that with the exception of recently stricken areas, the landslide inventories which are required to train any stochastic model are actually unavailable. A solution is here proposed, consisting in training a susceptibility model in a source catchment, which was implemented by applying the binary logistic regression technique, and exporting its predicting function (selected predictors regressed coefficients) in a target catchment to predict its landslide distribution. To test the method, we exploit the disaster that occurred in the Messina area (southern Italy) on 1 October 2009 where, following a 250-mm/8-h storm, approximately two thousand debris flow/debris avalanches landslides in an area of 21 km2 triggered, killing 37 people and injuring more than 100, and causing 0.5 M € worth of structural damage. The debris flows and debris avalanches phenomena involved the thin weathered mantle of the Varisican low to high-grade metamorphic rocks that outcrop in the eastern slopes of the Peloritani Mounts. Two 10-km2-wide stream catchments, which are located inside the storm core area, were exploited: susceptibility models trained in the Briga catchment were tested when exported to predict the landslides distribution in the Giampilieri catchment. The prediction performance (based on goodness of fit, prediction skill, accuracy and precision assessment) of the exported model was then compared with that of a model prepared in the Giampilieri catchment exploiting its landslide inventory. The results demonstrate that the landslide scenario observed in the Giampilieri catchment can be predicted with the same high performance without knowing its landslide distribution: we obtained, in fact, a very poor decrease in predictive performance when comparing the exported model to the native random partition-based model. 相似文献
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Soil erosion by water is a significant problem in arid and semi-arid areas of large parts of Iran. Water erosion is one of the most effective phenomena that leads to decreasing soil productivity and pollution of water resources; especially, in the Mazayjan watershed in the southwest of Fars Province gully erosion contributes to the sediment dynamics in a significant way. Consequently, the intention of this research is to identify the different types of soil erosion processes acting in the area and to assess the process dynamics in an integrative way. Therefore, we applied GIS and satellite image analysis techniques to derive input information for the numeric models. For sheet and rill erosion the Unit Stream Power-based Erosion Deposition Model (USPED) was utilized. The spatial distribution of gully erosion was assessed using a statistical approach, which used three variables (stream power index, slope, and flow accumulation) to predict the spatial distribution of gullies in the study area. The eroded gully volumes were estimated for a 7-year period by fieldwork and Google Earth high-resolution images. Finally the gully retreat rates were integrated into the USPED model. The results show that the integration of the SPI approach to quantify gully erosion with the USPED model is a suitable method to qualitatively and quantitatively assess water erosion processes. The application of GIS and stochastic model approaches to spatialize the USPED model input yields valuable results for the prediction of soil erosion in the Mazayjan catchment. The results of this research help to develop an appropriate management of soil and water resources in the southwestern parts of Iran. 相似文献
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