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 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

Integration of root systems into a GIS-based slip surface model: computational experiments in a generic hillslope environment

Root systems of trees reinforce the underlying soil in hillslope environments and therefore potentially increase slope stability. So far, the influence of root systems is disregarded in Geographic Information System (GIS) models that calculate slope stability along distinct failure plane. In this study, we analyse the impact of different root system compositions and densities on slope stability conditions computed by a GIS-based slip surface model. We apply the 2.5D slip surface model r.slope.stability to 23 root system scenarios imposed on pyramidoid-shaped elements of a generic landscape. Shallow, taproot and mixed root systems are approximated by paraboloids and different stand and patch densities are considered. The slope failure probability (Pf) is derived for each raster cell of the generic landscape, considering the reinforcement through root cohesion. Average and standard deviation of Pf are analysed for each scenario. As expected, the r.slope.stability yields the highest values of Pf for the scenario without roots. In contrast, homogeneous stands with taproot or mixed root systems yield the lowest values of Pf. Pf generally decreases with increasing stand density, whereby stand density appears to exert a more pronounced influence on Pf than patch density. For patchy stands, Pf increases with a decreasing size of the tested slip surfaces. The patterns yielded by the computational experiments are largely in line with the results of previous studies. This approach provides an innovative and simple strategy to approximate the additional cohesion supplied by root systems and thereby considers various compositions of forest stands in 2.5D slip surface models. Our findings will be useful for developing strategies towards appropriately parameterising root reinforcement in real-world slope stability modelling campaigns.© The Author(s) 201

Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity

Despite the importance of land cover on landscape hydrology and slope stability, the representation of land cover dynamics in physically based models and their associated ecohydrological effects on slope stability is rather scarce. In this study, we assess the impact of different levels of complexity in land cover parameterisation on the explanatory power of a dynamic and process‐based spatial slope stability model. Firstly, we present available and collected data sets and account for the stepwise parameterisation of the model. Secondly, we present approaches to simulate land cover: 1) a grassland landscape without forest coverage; 2) spatially static forest conditions, in which we assume limited knowledge about forest composition; 3) more detailed information of forested areas based on the computation of leaf area development and the implementation of vegetation‐related processes; 4) similar to the third approach but with the additional consideration of the spatial expansion and vertical growth of vegetation. Lastly, the model is calibrated based on meteorological data sets and groundwater measurements. The model results are quantitatively validated for two landslide‐triggering events that occurred in Western Austria. Predictive performances are estimated using the Area Under the receiver operating characteristic Curve (AUC). Our findings indicate that the performance of the slope stability model was strongly determined by model complexity and land cover parameterisation. The implementation of leaf area development and land cover dynamics further yield an acceptable predictive performance (AUC ~0.71‐0.75) and a better conservativeness of the predicted unstable areas (FoC ~0.71). The consideration of dynamic land cover expansion provided better performances than the solely consideration of leaf area development. The results of this study highlight that an increase of effort in the land cover parameterisation of a dynamic slope stability model can increase the explanatory power of the model.© 2018 The Author