Interpreting gaps: a geoarchaeological point of view on the Gravettian record of Ach and Lone valleys (Swabian Jura, SW Germany)

Unlike other Upper Paleolithic industries, Gravettian assemblages from the Swabian Jura are documented solely in the Ach Valley (35-30 Kcal BP). On the other hand, traces of contemporaneous occupations in the nearby Lone Valley are sparse. It is debated whether this gap is due to a phase of human depopulation, or taphonomic issues related with landscape changes. In this paper we present ERT, EC-logging and GPR data showing that in both Ach and Lone valleys sediments and archaeological materials eroded from caves and deposited above river incisions after 37-32 Kcal BP. We argued that the rate of cave erosion was higher after phases of downcutting, when hillside erosion was more intensive. To investigate on the causes responsible for the dearth of Gravettian materials in the Lone Valley we test two alternative hypotheses: i) Gravettian humans occupied less intensively this part of the Swabian Jura. ii) Erosion of cave deposits did not occur at the same time in the two valleys. We conclude that the second hypothesis is most likely. Ages from the Lone Valley show increasing multimillennial gaps between 36 and 18 Kcal BP, while a similar gap is present in the Ach Valley between 28 and 16 Kcal BP. Based on geoarchaeological data from previous studies and presented in this paper, we interpreted these gaps in radiocarbon data as indicating of cave erosion. Furthermore, we argued that the time difference across the two valleys show that the erosion of cave deposits began and terminated earlier in the Lone Valley, resulting in a more intensive removal of Gravettian-aged deposits. The hypothesis that cave erosion was triggered by regional landscape changes seems to be supported by geochronological data from the Danube Valley, which show that terrace formation at the end of the Pleistocene moved westwards throughout southern Germany with a time lag of few millennia.PTDC/HAR-ARQ/27833/2017info:eu-repo/semantics/publishedVersio

Connectivity elements and mitigation measures in policy-relevant soil erosion models: A survey across Europe

The current use of soil erosion models in Europe was investigated through an exploratory survey of 46 model applications covering 18 European countries. This revealed novel information on erosion model applications, their parameterisation, incorporation of landscape elements and mitigation measures with implications for connectivity and their use in decision-making in Europe. The model application predictions were applied at national, regional, catchment or field scale. The majority of model applications used the USLE or versions thereof, but a range of semi-empirical, decision-tree and process-based models were also used. The majority of model applications were used for policy relevant purposes such as erosion risk assessment or mitigation measure implementation at a range of spatial scales. The analysis identified an evident prevalence towards the use of national or regional data sets and a highly varying parameterisation of model applications. Landscape elements and mitigation measures with effects on connectivity were implemented in most model applications, but not with a focus on modelling connectivity within the landscape. Altogether, the results demonstrate a need for improving connectivity modelling in diverse agricultural landscapes across multiple scales. Models should be chosen dependent on their ability to reflect erosion risk at different spatial scales. Albeit, harmonisation of data sets, parameterisation procedures and validation approaches is needed for certain modelling scenarios to ensure comparability of soil erosion risk assessment and suitable mitigation practices. Furthermore, we recommend that policy-relevant erosion risk maps should be verified by empirical data and thresholds derived from erosion risk maps should be adapted to regional conditions when used for policy guidelines. Hence, comparability, comprehensibility and regional adaptation are essential qualities of policy-relevant erosion maps

Assessment of Shallow Landslide Initiation Areas Using stochastic Modelling: The Vernazza Torrent Case Study, Liguria, Italy. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

The objective of this study is the assessment of potential failure zones of landslides in unstable areas. For this purpose, two different stochastic classification models were used: A boosted decision tree approach with TreeNet (TN), and a bagging decision tree approach with Random Forests (RF). Both topographic and soil parameters were considered as predictor variables for training and testing the models. We assume that several predictor variables will lead to misclassification and incorrectness, especially soil parameters. Hence, the misclassification of these particular predictors should be avoided, using the strategy of tree boosting. The investigated area is the hydrological basin of Vernazza in Cinque Terre, Northwest Italy. A disastrous flash flood on the 25th of October 2011 with numerous landslides caused fatalities and economic losses amounting to millions of Euros. We mapped landslide areas in the field and checked the resulting maps with high resolution remote sensing images. Furthermore, the relevant soil parameters were collected based on a geostatistical approach. We measured topographic parameters, and physical and hydrological soil characteristics such as maximum shear strength under saturated and unsaturated conditions, and hydraulic conductivity (Ksat), and attributed random points in three distinguished classes: i) initiation areas, representing the most likely failure areas for possible landslides, ii) transport areas which were considered as a mix of classes 1 and 3, and iii) stable areas, such as valley bottom, ridges, and unconditionally stable areas. We ran both models with a training dataset (0.8 of the total points Ntot) and a test dataset (0.2 of Ntot) and each with 2000 grown decision trees. We validated the models with a Receiver Operating Characteristic (ROC) curve integral. The regionalized results of the TreeNet dataset yielded potential susceptible landslide areas of a total area of 1.74 km², which is 29.74% of the total area. In contrast, the Random Forests model classified a much greater susceptible area (84.27% of the total area). The results show that Treenet is outperforming RF. The latter misclassifies especially the soil related variables, whereas TreeNet yields robust model results

Operational USLE-based modelling of soil erosion in Czech Republic, Austria, and Bavaria - differences in model adaptation, parametrization, and data availability

In the European Union, soil erosion is identified as one of the main environmental threats, addressed with a variety of rules and regulations for soil and water conservation. The by far most often officially used tool to determine soil erosion is the Universal Soil Loss Equation (USLE) and its regional adaptions. The aim of this study is to use three different regional USLE-based approaches in three different test catchments in the Czech Republic, Germany, and Austria to determine differences in model results and compare these with the revised USLE-base European soil erosion map. The different regional model adaptations and implementation techniques result in substantial differences in test catchment specific mean erosion (up to 75% difference). Much more pronounced differences were modelled for individual fields. The comparison of the region-specific USLE approaches with the revised USLE-base European erosion map underlines the problems and limitations of harmonization procedures. The EU map limits the range of modelled erosion and overall shows a substantially lower mean erosion compared to all region-specific approaches. In general, the results indicate that even if many EU countries use USLE technology as basis for soil conservation planning, a truly consistent method does not exist, and more efforts are needed to homogenize the different methods without losing the USLE-specific knowledge developed in the different regions over the last decades

Assessment of Shallow Landslide Initiation Areas Using stochastic Modelling: The Vernazza Torrent Case Study, Liguria, Italy. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

The objective of this study is the assessment of potential failure zones of landslides in unstable areas. For this purpose, two different stochastic classification models were used: A boosted decision tree approach with TreeNet (TN), and a bagging decision tree approach with Random Forests (RF). Both topographic and soil parameters were considered as predictor variables for training and testing the models. We assume that several predictor variables will lead to misclassification and incorrectness, especially soil parameters. Hence, the misclassification of these particular predictors should be avoided, using the strategy of tree boosting. The investigated area is the hydrological basin of Vernazza in Cinque Terre, Northwest Italy. A disastrous flash flood on the 25th of October 2011 with numerous landslides caused fatalities and economic losses amounting to millions of Euros. We mapped landslide areas in the field and checked the resulting maps with high resolution remote sensing images. Furthermore, the relevant soil parameters were collected based on a geostatistical approach. We measured topographic parameters, and physical and hydrological soil characteristics such as maximum shear strength under saturated and unsaturated conditions, and hydraulic conductivity (Ksat), and attributed random points in three distinguished classes: i) initiation areas, representing the most likely failure areas for possible landslides, ii) transport areas which were considered as a mix of classes 1 and 3, and iii) stable areas, such as valley bottom, ridges, and unconditionally stable areas. We ran both models with a training dataset (0.8 of the total points Ntot) and a test dataset (0.2 of Ntot) and each with 2000 grown decision trees. We validated the models with a Receiver Operating Characteristic (ROC) curve integral. The regionalized results of the TreeNet dataset yielded potential susceptible landslide areas of a total area of 1.74 km², which is 29.74% of the total area. In contrast, the Random Forests model classified a much greater susceptible area (84.27% of the total area). The results show that Treenet is outperforming RF. The latter misclassifies especially the soil related variables, whereas TreeNet yields robust model results

Assessment of groundwater response and soil moisture fluctuations in the mugello basin (Central Italy)

Extreme meteorological events such as heavy rainstorms are considered to increase due to global warming. The consequences of such events can be manifold, and might cause massive interferences of the hydrological system of a landscape. Particularly the intramontane basins of the Apennine in Italy are frequently threatened by extreme rainfall events that cause severe damage on buildings and infrastructure. Moreover, the lithological and geomorphological settings of these basins, which depict the products of a complex landscape history, amplify these threats. In order to develop possible mitigation strategies, it is crucial to assess landscape functioning by analysing hydrological processes of the landscape system. In this study, we conducted spatially distributed and dynamic hydrological modelling on a catchment in the intramontane basin of the Mugello valley in Tuscany, Italy. Foremost, measurements of saturated hydraulic conductivity and texture analyses were performed to estimate both infiltration and hydraulic conductivity of the surface and topsoil, respectively. We regionalised the collected data with a stochastic gradient treeboost method for the whole catchment. Soil depth was estimated with a simple sine-cosine-slope relation, whereas, hydropedologic parameters for the hydrological model were estimated with pedotransferfunctions applied on the collected infiltration data. We modelled a period of 100 days, representing each day per time step. A synthetic rainfall period was compiled based on measured data from meteorological stations within the Mugello basin. To produce a reliable synthetic rainfall data set, the estimated precipitation values were set in comparison to calculated return periods for extreme events of all available meteorological station. To assess the diversity of the hydrological response of several locations in the catchment, six semirandom test locations were located on hillslopes and spots were sedimentation is apparent. The results show that groundwater and soil moisture fluctuations appear to be significantly different for both hillslopes and areas were sediments are deposited. The differences cannot be explained by the topographical settings but rather by the approximated thickness of the weathered zone and the spatial diversity of the hydropedological properties of the soil