Michael Märker

Future long-term changes in global water resources driven by socio-economic and climatic changes

Abstract A 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.

Gully erosion susceptibility assessment by means of GIS-based logistic regression: A case of Sicily (Italy)

article i nfo Article history: This research aims at characterizing susceptibility conditions to gully erosion by means of GIS and multivariate statistical analysis. The study area is a 9.5 km 2 river catchment in central-northern Sicily, where agriculture ac- tivities are limited by intense erosion. By means of field surveys and interpretation of aerial images, we prepared a digitalmap of thespatial distribution of 260 gulliesinthestudy area.Inaddition,fromavailable thematicmaps, a 5 m cell size digital elevation model and field checks, we derived 27 environmental attributes that describe the variability of lithology, land use, topography and road position. These attributes were selected for their potential influence on erosion processes, while the dependent variable was given by presence or absence of gullies within two different types of mapping units: 5 m grid cells and slope units (average size = 2.66 ha). The functional re- lationships between gully occurrence and the controlling factors were obtained from forward stepwise logistic regression to calculate the probability to host a gully for each mapping unit. In order to train and test the predictive models, three calibration and three validation subsets, of both grid cells and slope units, were randomly selected. Results of validation, based on ROC (receiving operating characteristic) curves, attest for acceptable to excellent accuracies of the models, showing better predictive skill and more stable performance of the susceptibility model based on grid cells.

Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy)

Abstract This study aims to compare binary logistic regression (BLR) and stochastic gradient treeboost (SGT) methods in assessing landslide susceptibility within the Mediterranean region for multiple-occurrence regional landslide events. A test area was selected in the north-eastern sector of Sicily (southern Italy) where thousands of debris flows and debris avalanches triggered on the first October 2009 due to an extreme storm. Exploiting the same set of predictors and the 2009 event landslide archive, BLR- and SGT-based susceptibility models have been obtained for the two catchments separately, adopting a random partition (RP) technique for validation. In addition, the models trained in one catchment have been tested in predicting the landslide distribution in the second, adopting a spatial partition (SP)-based validation. The models produced high predictive performances with a general consistency between BLR and SGT in the susceptibility maps, predictor importance and role. In particular, SGT models reached a higher prediction performance with respect to BLR models for RP-modelling, while for the SP-based models, the difference in predictive skills dropped, converging to equally excellent performances. However, analysing the precision of the probability estimates, BLR produced more robust models around the mean value for each pixel, indicating possible overfitting effects, which affect decision trees to a greater extent. The assessment of the predictor roles allowed identifying the activation mechanisms which are primarily controlled by steep south-facing open slopes located near the coastal area. These slopes are characterised by low/middle altitude downhill from mountain tops, having a medium-grade metamorphic bedrock, under grassland and cultivated (terraced) uses.

Gully erosion modelling and landscape response in the Mbuluzi River catchment of Swaziland

Abstract In southern African countries soil erosion and the related problems, such as water quality issues or decreasing soil productivity, are the main topics affecting the inhabitants of both rural and urban areas. Therefore, the attention has been recently placed on those problems related to soil erosion. This can also be documented by an increasing number of studies carried out on erosion and by the development and application of erosion models. Nevertheless, gully erosion phenomena have been widely neglected in erosion modelling. This is because the development of erosion models was focused on those regions with an intense agriculture typical of developed countries on the one hand, and because of the spatial and temporal heterogeneity of gully erosion processes on the other hand. This study regards the identification of gully erosion forms and processes in the Mbuluzi River catchment (Kingdom of Swaziland) by using the Erosion Response Units (ERU) concept. The following modelling of gully erosion was done through the stable gully model [Catena 37 (1999) 401]. The input data were obtained through the application of remote sensing techniques (API method) and GIS-analyses. The example from Swaziland shows that the applied methods are able to identify areas affected by gully erosion. Furthermore, it is possible to estimate the amount of soil loss due to gully erosion, which, for example, is not taken into consideration by the USLE-type models.

The Delineation of Paleo-Shorelines in the Lake Manyara Basin Using TerraSAR-X Data

The purpose of this paper is to describe the delineation of paleo-shorelines using high resolution microwave images and digital image processing tools, and with that to contribute to the understanding of the complex landscape evolution of the Lake Manyara Basin. The surroundings of Lake Manyara are the focus of several paleo-archeological investigations, since the location is close to Olduvai Gorge, where paleo-anthropological findings can be traced back to homo habilis. In the catchment of Lake Manyara two hominin-bearing sites (0.78 to 0.63 Ma), lots of vertebrate fossils and hand axes from different periods were found. Understanding the development and extent of the lake is crucial for understanding the regional paleo-environment of the Quaternary. Morphological structures of shorelines and terraces east of Lake Manyara were identified from TerraSAR-X StripMap images. By applying a Canny edge detector, linear features were extracted and revised for different image acquisitions using a contextual approach. Those features match literature and field references. A digital elevation model of the region was used to map the most distinct paleo-shorelines according to their elevation.

Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region : the role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling

SOC is the most important indicator of soil fertility and monitoring its space-time changes is a prerequisite to establish strategies to reduce soil loss and preserve its quality. Here we modelled the topsoil (0-0.3m) SOC concentration of the cultivated area of Sicily in 1993 and 2008. Sicily is an extremely variable region with a high number of ecosystems, soils, and microclimates. We studied the role of time and land use in the modelling of SOC, and assessed the role of remote sensing (RS) covariates in the boosted regression trees modelling. The models obtained showed a high pseudo-R2 (0.63-0.69) and low uncertainty (s.d.<0.76gCkg-1 with RS, and <1.25gCkg-1 without RS). These outputs allowed depicting a time variation of SOC at 1arcsec. SOC estimation strongly depended on the soil texture, land use, rainfall and topographic indices related to erosion and deposition. RS indices captured one fifth of the total variance explained, slightly changed the ranking of variance explained by the non-RS predictors, and reduced the variability of the model replicates. During the study period, SOC decreased in the areas with relatively high initial SOC, and increased in the area with high temperature and low rainfall, dominated by arables. This was likely due to the compulsory application of some Good Agricultural and Environmental practices. These results confirm that the importance of texture and land use in short-term SOC variation is comparable to climate. The present results call for agronomic and policy intervention at the district level to maintain fertility and yield potential. In addition, the present results suggest that the application of RS covariates enhanced the modelling performance.

Revised modelling of the post-AD 79 volcanic deposits of Somma-Vesuvius to reconstruct the pre-AD 79 topography of the Sarno River plain (Italy)

Revised modelling of the post-AD 79 volcanic deposits of Somma-Vesuvius to reconstruct the pre-AD 79 topography of the Sarno River plain (Italy) In this study the methodology proposed by Vogel & Märker (2010) to reconstruct the pre-AD 79 topography and paleo-environmental features of the Sarno River plain (Italy) was considerably revised and improved. The methodology is based on an extensive dataset of stratigraphical information from the entire Sarno River plain, a high-resolution present-day digital elevation model (DEM) and a classification and regression tree approach. The dataset was re-evaluated and 32 additional stratigraphical drillings were collected in areas that were not or insufficiently covered by previous stratigraphic data. Altogether, an assemblage of 1,840 drillings, containing information about the depth from the present-day surface to the pre-AD 79 paleo-surface (thickness of post-AD 79 deposits) and the character of the pre-AD 79 paleo-layer of the Sarno River plain was utilized. Moreover, an improved preprocessing of the input parameters attained a distinct progress in model performance in comparison to the previous model of Vogel & Märker (2010). Subsequently, a spatial model of the post-AD 79 deposits was generated. The modelled deposits were then used to reconstruct the pre-AD 79 topography of the Sarno River plain. Moreover, paleo-environmental and paleo-geomorphological features such as the paleo-coastline, the paleo-Sarno River and its floodplain, alluvial fans near the Tyrrhenian coast as well as abrasion terraces of historical and protohistorical coastlines were identified. This reconstruction represents a qualitative improvement of the previous work by Vogel & Märker (2010).

Multisensoral Topsoil Mapping in the Semiarid Lake Manyara Region, Northern Tanzania

This study pursues the mapping of the distribution of topsoils and surface substrates of the Lake Manyara area of northern Tanzania. The nine soil and lithological target classes were selected through fieldwork and laboratory analysis of soil samples. High-resolution WorldView-2 data, TerraSAR-X intensity data, medium-resolution ASTER spectral bands and indices, as well as ENVISAT ASAR intensity and SRTM-X-derived topographic parameters served as input features. Objects were derived from image segmentation. The classification of the image objects was conducted applying a nonlinear support vector machine approach. With the recursive feature elimination approach, the most input-relevant features for separating the target classes were selected. Despite multiple target classes, an overall accuracy of 71.9% was achieved. Inaccuracies occurred between classes with high CaCO3 content and between classes of silica-rich substrates. The incorporation of different input feature datasets improved the classification accuracy. An in-depth interpretation of the classification result was conducted with three soil profile transects.

Carta geomorfológica de la sección central y occidental de la Región Metropolitana de Santiago

The geomorphologic chart of the western part of the Santiago Metropolitan Region was made considering a lito-morphologic units definition purpose, especially for the interpretation and classification of homogenous slope systems. The chart goal was the identification of homogenous slopes systems, in which the base of the morpho dynamic interpretation is sustained in the geologic nature of the materials. Structurally, the monoclinals reliefs are emphasized. Also, the lithological nature of the layers and not it position in the monoclinal is considered into the analysis of the medium and low mountain environment because, from a geodynamic point of view, they generally operate in a similar way. In the intrusive reliefs, remnants of erosional surfaces are distinguished. The notion of tenaces is also considered in the alluvial forms according to age, distinguishing between pleistocenic, holocenic, and indeterminated tenaces. As results, polygons of units of equal morphogenesis, lithologic and present geodynamics are generated.

Modeling 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

The 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.