1,721,109 research outputs found
Explorative Spatial Analysis of Neandertal Sites using Terrain Analysis and Stochastic Environmental Modelling
No full textThe role of soil-protecting forests in reducing soil erosion in young glacial landscapes of Northern-Central Poland
No full textReconstructing the Roman topography and environmental features of the Sarno River Plain (Italy) before the AD 79 eruption of Somma-Vesuvius
No full textA methodology was developed to reconstruct the Roman topography and environmental features of the Sarno River plain, Italy, before the AD 79 eruption of the Somma-Vesuvius volcanic complex. We collected, localized and digitized more than 1800 core drilling data to gain a representative network of stratigraphical information covering the entire plain. Besides other stratigraphical data including the characteristics of the pre-AD 79 stratum, the depth to the pre-AD 79 surface was identified from the available drilling documentations. Instead of a simple interpolation method, we used a machine based learning approach based on classification and regression trees to reconstruct the pre-AD 79 topography. We hypothesize that the present-day topography reflects the ancient topography and related surface processes, because volcanic deposits from the AD 79 eruption coated the ancient landscape. Thus, ancient physiographic elements of the Sarno River plain are still recognizable in the present-day topography. Therefore, a high-resolution, present-day digital elevation model (DEM) was generated. A detailed terrain analysis yielded 15 different primary and secondary topographic indices. Subsequently, a classification and regression model was applied to predict the depth of the pre-AD 79 surface combining present-day topographic indices with other physiographic data. This model was calibrated with the measured depth of the pre-AD 79 surface. The resulting pre-AD 79 DEM was compared with the classified characteristic of the pre-AD 79 stratum, identified from the drilling documentations. This allowed the reconstruction of pre-AD 79 environmental features of the Sarno River plain such as the ancient coastline, the paleo-course of the Sarno River and its floodplain. To the knowledge of the authors, it is the first time that the pre-AD 79 topography of the Sarno River plain was systematically reconstructed using a detailed database and sophisticated data mining technologies. © 2009 Elsevier B.V. All rights reserved
An integrated assessment of soil erosion dynamics with special emphasis on gully erosion in the Mazayjan basin, southwestern Iran
No full textModeling the spatial distribution of AD 79 pumice fallout and pyroclastic density current and derived deposits of Somma-Vesuvius (Campania, Italy) integrating primary deposition and secondary redistribution
No full textThe spatial distributions of primary deposits and related reworked ones from Plinian fallout and from pyroclastic density currents (PDCs) of the AD 79 eruption of Somma-Vesuvius were independently modeled for the Sarno River plain (Campania, Italy). The simulation takes into consideration both primary deposition of the volcanic products and their secondary redistribution by geomorphic processes of erosion, transport, and redeposition. We hypothesize that the pre-eruption topography controlled both the intial volcanic deposition of PDCs and the subsequent processes redistributing material of the pumice fallout and PDC deposits, and thus significantly controlled the thickness of the final volcaniclastic deposits. The methodology applied is based on a reconstructed pre-AD 79 digital elevation model of the Sarno River plain, an extensive tephrostratigraphic dataset from about 1,200 core drillings and a predictive modeling technique. The two models produce contrasting spatial distribution patterns for both the AD 79 deposits from fallout plus their derivates, versus from PDCs and their derivatives. The contrast allows determination of the most important factors controlling the thickness of the AD 79 volcaniclastic deposits. This provides new insights into the process dynamics during and immediately after the AD 79 Plinian eruption including primary deposition, erosion, and redistribution. © 2013 Springer-Verlag Berlin Heidelberg
Assessment of gully erosion process dynamics for water resources management in a semiarid catchment of Swaziland (Southern Africa)
No full textIn southern African countries, soil erosion and related problems like water quality issues or decreasing soil productivity are increasingly affecting the inhabitants of rural and urban areas. Problems related to soil erosion therefore have received increased attention in the recent past. Gully erosion processes especially play an important role for sediment production in many southern African catchments. Nevertheless, gully erosion phenomena have been widely neglected in erosion modelling. This study concerns the identification of spatially distributed erosion forms and processes in the Mbuluzi River catchment (Kingdom of Swaziland), with particular attention to gully erosion phenomena. The modelling of gully erosion was done successfully with models accounting for the two stages of development of a gully. The input data were obtained using remote sensing techniques and GIS-analyses. The example from Southern Africa shows that the methods applied are suitable for identifying and simulating the relevant erosional processes
A functional entity approach to predict soil erosion processes in a small Plio-Pleistocene Mediterranean catchment in Northern Chianti, Italy
No full textIn this paper we evaluate different methods to predict soil erosion processes. We derived different layers of predictor variables for the study area in the Northern Chianti, Italy, describing the soil-lithologic complex, land use, and topographic characteristics. For a subcatchment of the Orme River, we mapped erosion processes by interpreting aerial photographs and field observations. These were classified as erosional response units (ERU), i.e. spatial areas of homogeneous erosion processes. The ERU were used as the response variable in the soil erosion modelling process. We applied two models i) bootstrap aggregation (Random Forest: RF), and ii) stochastic gradient boosting (TreeNet: TN) to predict the potential spatial distribution of erosion processes for the entire Orme River catchment. The models are statistically evaluated using training data and a set of performance parameters such as the area under the receiver operating characteristic curve (AUC), Cohen's Kappa, and pseudo R2. Variable importance and response curves provide further insight into controlling factors of erosion. Both models provided good performance in terms of classification and calibration; however, TN outperformed RF. Similar classes such as active and inactive landslides can be discriminated and well interpreted by considering response curves and relative variable importance. The spatial distribution of the predicted erosion susceptibilities generally follows topographic constraints and is similar for both models. Hence, the model-based delineation of ERU on the basis of soil and terrain information is a valuable tool in geomorphology; it provides insights into factors controlling erosion processes and may allow the extrapolation and prediction of erosion processes in unsurveyed areas. © 2010 Elsevier B.V
The response units concept and its application for the assessment of hydrologically related erosion processes in semiarid catchments of Southern Africa
No full textProper management of valuable land resources is of paramount importance especially in regions affected by natural hazards. The sustainable development of land resources depends on the understanding of the processes and dynamics active within the landscape. In Southern African countries water shortage and water quality issues related to soil erosion are a major problem affecting the population in rural and urban areas. Consequently, during the last decade increasing attention has been focussed especially on such issues, and an increasing number of integrated hydrological and erosion studies, including the development and application of respective integrated regionalization concepts, is reflecting this development. The present study deals with the regionalization of spatially distributed hydrological related erosion processes in the catchments of the Mkomazi river (KwaZulu-Natal, South Africa) and the Mbuluzi-river (Kingdom of Swaziland). It was carried out within the framework of an interdisciplinary EU-funded project developing an Integrated Water Resources Management System (IWRMS) in semiarid catchments of Southern Africa. Within this project the concept of "Response Units (RUs)" was applied and adapted as Erosion Response Units (ERUs) to regionalize the distribution of hydrologically induced soil erosion in space and time. ERUs are landscape model entities identifying relative homogeneous hydrological related erosion processes, thus providing a spatially distributed model structure for regionalization. The examples from Southern Africa presented in this paper discuss the methods used to delineate such Response Units integrating remote sensing and GIS techniques
Future long-term changes in global water resources driven by socio-economic and climatic changes
No full textA global water model is used to analyse the impacts of climate change and socio-economic driving forces (derived from the A2 and B2 scenarios of IPCC) on future global water stress. This work extends previous global water research by analysing not only the impact of climate change and population, but also the effects of income, electricity production, water-use efficiency and other driving forces, on water stress. Depending on the scenario and climate model, water stress increases (between current conditions and the 2050s) over 62.0-75.8% of total river basin area and decreases over 19.7-29.0% of this area. The remaining areas have small changes. The principal cause of decreasing water stress (where it occurs) is the greater availability of water due to increased annual precipitation related to climate change. The principal cause of increasing water stress is growing water withdrawals, and the most important factor for this increase is the growth of domestic water use stimulated by income growth. (Population growth was a much less important factor and irrigated area was assumed to remain constant.) To address the uncertainty of water stress estimates, three different indicators of water stress were computed and compared. The overlap area of their computation of "severe stress" in the 2050s was large (approximately 23 × 106 km2 or 56-73% of the total "severe stress" area). This indicates a moderate level of agreement and robustness in estimates of future water stress. At the same time the indicators disagreed in many other areas, suggesting that work is still needed to elaborate general indicators and concepts of water stress. Copyright © 2007 IAHS Press
Explorative analysis of varying spatial resolutions on a soil type classification model and it's transferability in an agricultural lowland area of Lombardy, Italy
No full textIn Digital Soil Mapping (DSM), assessing the transferability of soil type classification models across different spatial resolutions is a pivotal step in ensuring their robustness and applicability to diverse terrains. This study investigates the impact of spatial resolutions on soil type mapping within an intensively used agricultural lowland region in Lombardy, Italy, based on a Random Forest algorithm. Employing Digital Elevation Models (DEMs) at resolutions of 5 m, 10 m, and 25 m, this study aims to identify the optimal spatial resolution for accurate soil type maps and explores the transferability of models across different resolutions. The nested LeaveOne-Out Cross-Validation (nested-LOOCV) results indicate a substantial impact of resolution on model performance, with higher resolutions demonstrating superior accuracy. The model developed at 10 m resolution emerges as the most robust performer, achieving an overall accuracy of 40.3%. Model transferability analysis reveals challenges when transitioning from finer to coarser resolutions, while models at coarser resolutions adapt favourably to higher resolution data. The implications extend to DSM, emphasizing the need for careful consideration of spatial resolution in model development and transfer. The findings provide valuable insights for researchers and practitioners, urging tailored approaches based on the scale and objectives of the study area. The study encourages future research to focus on advanced techniques enhancing model transferability within DSM. Overall, this research contributes to the optimization of soil classification models, advancing our understanding of soil taxonomy in agriculturally vital lowland areas
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