Pressure-specific and multiple pressure response of fish assemblages in European running waters

We classified homogenous river types across Europe and searched for fish metrics qualified to show responses to specific pressures (hydromorphological pressures or water quality pressures) vs. multiple pressures in these river types. We analysed fish taxa lists from 3105 sites in 16 ecoregions and 14 countries. Sites were pre-classified for 15 selected pressures to separate unimpacted from impacted sites. Hierarchical cluster analysis was used to split unimpacted sites into four homogenous river types based on species composition and geographical location. Classification trees were employed to predict associated river types for impacted sites with four environmental variables. We defined a set of 129 candidate fish metrics to select the best reacting metrics for each river type. The candidate metrics represented tolerances/intolerances of species associated with six metric types: habitat, migration, water quality sensitivity, reproduction, trophic level and biodiversity. The results showed that 17 uncorrelated metrics reacted to pressures in the four river types. Metrics responded specifically to water quality pressures and hydromorphological pressures in three river types and to multiple pressures in all river types. Four metrics associated with water quality sensitivity showed a significant reaction in up to three river types, whereas 13 metrics were specific to individual river types. Our results contribute to the better understanding of fish assemblage response to human pressures at a pan-European scale. The results are especially important for European river management and restoration, as it is necessary to uncover underlying processes and effects of human pressures on aquatic communities.     

Fusion of multi‐resolution surface (terrestrial laser scanning) and subsurface geodata (ERT,SRT) for karst landform investigation and geomorphometric quantification

A multi‐method research design based on terrestrial laser scanning, GIS, geophysical prospecting (electrical resistivity tomography, refraction seismics) and sedimentology is applied for the first time to investigate enclosed karst depressions in an integrated way. Fusing multi‐resolution surface and subsurface geodata provides profound insights into the formation, geometry and geomorphologic processes of dolines. The studied landforms, which are located in the Dikti Mountains of East Crete, are shown to be filled by loose sediments of thicknesses of up to 30 m that mainly consist of fine‐grained material overlying solid bedrock at depths below 35 to 45 m. By combining subsurface observations with geomorphometric calculations, local doline genesis can be traced back to initial collapse of fractured bedrock followed by subsequent infilling with colluvials. In order to define crucial methodological requirements and guidelines for data fusion, both the impact of different elevation models and the influence of data resolution are assessed. Surface volumes of depressions derived by the digital surface model are 7–21% higher than the results obtained from the terrain model due to vegetation. Similarly, estimates of infill volume calculated on the basis of geophysical outcomes and elevation data differ by up to 13%. Calculations of the landforms' current volumes (i.e. total surface and subsurface volume), however, are fairly insensitive to raster resolution. Hence, the distinct geomorphologic properties of landforms (e.g. shape, terrain roughness, slope inclination) substantially determine the geomorphometric analysis of both surface and subsurface data. As shown by the findings, data fusion to integrate digital terrain, geophysical and sedimentological datasets of varied resolutions benefits geomorphologic studies and helps provide a comprehensive image of landforms. Copyright © 2013 John Wiley & Sons, Ltd.     

Modelling climate and land-use change impacts with SWIM: lessons learnt from multiple applications

Abstract

The Soil and Water Integrated Model (SWIM) is a continuous-time semi-distributed ecohydrological model, integrating hydrological processes, vegetation, nutrients and erosion. It was developed for impact assessment at the river basin scale. SWIM is coupled to GIS and has modest data requirements. During the last decade SWIM was extensively tested in mesoscale and large catchments for hydrological processes (discharge, groundwater), nutrients, extreme events (floods and low flows), crop yield and erosion. Several modules were developed further (wetlands and snow dynamics) or introduced (glaciers, reservoirs). After validation, SWIM can be applied for impact assessment. Four exemplary studies are presented here, and several questions important to the impact modelling community are discussed. For which processes and areas can the model be used? Where are the limits in model application? How to apply the model in data-poor situations or in ungauged basins? How to use the model in basins subject to strong anthropogenic pressure?

Editor D. Koutsoyiannis; Associate editor C. Perrin     

Evaluation of MIVIS Hyperspectral Data for Mapping Soil Degradation in an Upland Ecosystem of Southern Italy

Abstract

This paper describes the first stage of an experiment aiming to evaluate the potential and limitations of MIVIS data for mapping the degradational state of soils in a sub‐scene of a southern Apennines study area (Italy). After radiometric rectification of the image data and the collection of a field/laboratory spectral library, linear spectral mixture modelling (SMA) was used to decompose image spectra into fractions of spectrally distinct mixing components. Spectral endmember selection was based upon a principal component analysis (PCA) applied to a set of soil spectra, collected from the spectral library. The resulting abundance estimates (fractions) trough SMA were then analysed to identify soil conditions and to obtain an improved measure of dry and green vegetation cover. A map of soil conditions and dry‐green vegetation abundance, based upon MIVIS data was then derived from normalised fractions of soil‐vegetation endmembers obtained from SMA.     

Twentieth century precipitation trends in the upper Mzingwane sub-catchment of the northern Limpopo basin,Zimbabwe

Theoretical and Applied Climatology - This study evaluates precipitation trends in the upper Mzingwane sub-catchment (UMS) of Zimbabwe using ten World Meteorological Organization (WMO)’s...     

Spatial modelling of social and economic vulnerability to floods at the district level in Búzi, Mozambique

In Mozambique, the district level is empowered through recent policies to carry out disaster risk reduction activities. To address risk and associated activities appropriately, both information on the occurrence and distribution of hazards and information on the spatial distribution of vulnerability have to be available. Within this paper, a method is presented to model the social and economic dimension of vulnerability in a spatial and integrative manner applying the geon approach. Homogenous vulnerability regions are identified through the application of integrated modelling approaches, which build on expert and upscaled local knowledge and weightings. A set of indicators is proposed, which allow the modelling of vulnerability in a data-scarce environment. Finally, the different perceptions between national experts and local community members are visualised through maps, and opportunities are discussed. Overall, the method and results presented aim to facilitate the identification of critical vulnerability areas through different views, serving the needs at decision makers?? and experts?? level.     

Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980�C2010 period

Several different inventories of global and regional anthropogenic and biomass burning emissions are assessed for the 1980?C2010 period. The species considered in this study are carbon monoxide, nitrogen oxides, sulfur dioxide and black carbon. The inventories considered include the ACCMIP historical emissions developed in support of the simulations for the IPCC AR5 assessment. Emissions for 2005 and 2010 from the Representative Concentration Pathways (RCPs) are also included. Large discrepancies between the global and regional emissions are identified, which shows that there is still no consensus on the best estimates for surface emissions of atmospheric compounds. At the global scale, anthropogenic emissions of CO, NO_x and SO₂ show the best agreement for most years, although agreement does not necessarily mean that uncertainty is low. The agreement is low for BC emissions, particularly in the period prior to 2000. The best consensus is for NO_x emissions for all periods and all regions, except for China, where emissions in 1980 and 1990 need to be better defined. Emissions of CO need better quantification in the USA and India for all periods; in Central Europe, the evolution of emissions during the past two decades needs to be better determined. The agreement between the different SO₂ emissions datasets is rather good for the USA, but better quantification is needed elsewhere, particularly for Central Europe, India and China. The comparisons performed in this study show that the use of RCP8.5 for the extension of the ACCMIP inventory beyond 2000 is reasonable, until more global or regional estimates become available. Concerning biomass burning emissions, most inventories agree within 50?C80%, depending on the year and season. The large differences between biomass burning inventories are due to differences in the estimates of burned areas from the different available products, as well as in the amount of biomass burned.     

Greenhouse gas taxes on animal food products: rationale, tax scheme and climate mitigation effects

Agriculture is responsible for 25?C30% of global anthropogenic greenhouse gas (GHG) emissions but has thus far been largely exempted from climate policies. Because of high monitoring costs and comparatively low technical potential for emission reductions in the agricultural sector, output taxes on emission-intensive agricultural goods may be an efficient policy instrument to deal with agricultural GHG emissions. In this study we assess the emission mitigation potential of GHG weighted consumption taxes on animal food products in the EU. We also estimate the decrease in agricultural land area through the related changes in food production and the additional mitigation potential in devoting this land to bioenergy production. Estimates are based on a model of food consumption and the related land use and GHG emissions in the EU. Results indicate that agricultural emissions in the EU27 can be reduced by approximately 32 million tons of CO₂-eq with a GHG weighted tax on animal food products corresponding to ?60 per ton CO₂-eq. The effect of the tax is estimated to be six times higher if lignocellulosic crops are grown on the land made available and used to substitute for coal in power generation. Most of the effect of a GHG weighted tax on animal food can be captured by taxing the consumption of ruminant meat alone.     

Fault Roughness at Seismogenic Depths from LIDAR and Photogrammetric Analysis

Fault surface roughness is a principal factor influencing earthquake mechanics, and particularly rupture initiation, propagation, and arrest. However, little data currently exist on fault surfaces at seismogenic depths. Here, we investigate the roughness of slip surfaces from the seismogenic strike-slip Gole Larghe Fault Zone, exhumed from ca. 10 km depth. The fault zone exploited pre-existing joints and is hosted in granitoid rocks of the Adamello batholith (Italian Alps). Individual seismogenic slip surfaces generally show a first phase of cataclasite production, and a second phase with beautifully preserved pseudotachylytes of variable thickness. We determined the geometry of fault traces over almost five orders of magnitude using terrestrial laser-scanning (LIDAR, ca. 500 to <1 m scale), and 3D mosaics of high-resolution rectified digital photographs (10 m to ca. 1 mm scale). LIDAR scans and photomosaics were georeferenced in 3D using a Differential Global Positioning System, allowing detailed multiscale reconstruction of fault traces in Gocad^®. The combination of LIDAR and high-resolution photos has the advantage, compared with classical LIDAR-only surveys, that the spatial resolution of rectified photographs can be very high (up to 0.2 mm/pixel in this study), allowing for detailed outcrop characterization. Fourier power spectrum analysis of the fault traces revealed a self-affine behaviour over 3–5 orders of magnitude, with Hurst exponents ranging between 0.6 and 0.8. Parameters from Fourier analysis have been used to reconstruct synthetic 3D fault surfaces with an equivalent roughness by means of 2D Fourier synthesis. Roughness of pre-existing joints is in a typical range for this kind of structure. Roughness of faults at small scale (1 m to 1 mm) shows a clear genetic relationship with the roughness of precursor joints, and some anisotropy in the self-affine Hurst exponent. Roughness of faults at scales larger than net slip (>1–10 m) is not anisotropic and less evolved than at smaller scales. These observations are consistent with an evolution of roughness, due to fault surface processes, that takes place only at scales smaller or comparable to the observed net slip. Differences in roughness evolution between shallow and deeper faults, the latter showing evidences of seismic activity, are interpreted as the result of different weakening versus induration processes, which also result in localization versus delocalization of deformation in the fault zone. From a methodological point of view, the technique used here is advantageous over direct measurements of exposed fault surfaces in that it preserves, in cross-section, all of the structures which contribute to fault roughness, and removes any subjectivity introduced by the need to distinguish roughness of original slip surfaces from roughness induced by secondary weathering processes. Moreover, offsets can be measured by means of suitable markers and fault rocks are preserved, hence their thickness, composition and structural features can be characterised, providing an integrated dataset which sheds new light on mechanisms of roughness evolution with slip and concomitant fault rock production.     

Optimal design of superelastic‐friction base isolators for seismic protection of highway bridges against near‐field earthquakes

The seismic response of a multi‐span continuous bridge isolated with novel superelastic‐friction base isolator (S‐FBI) is investigated under near‐field earthquakes. The isolation system consists of a flat steel‐Teflon sliding bearing and a superelastic NiTi shape memory alloy (SMA) device. The key design parameters of an S‐FBI system are the natural period of the isolated bridge, the yielding displacement of the SMA device, and the friction coefficient of the sliding bearings. The goal of this study is to obtain optimal values for each design parameter by performing sensitivity analysis of a bridge isolated by an S‐FBI system. First, a three‐span continuous bridge is modeled as two‐degrees‐of‐freedom with the S‐FBI system. A neuro‐fuzzy model is used to capture rate‐ and temperature‐dependent nonlinear behavior of the SMA device. Then, a set of nonlinear time history analyses of the isolated bridge is performed. The variation of the peak response quantities of interest is shown as a function of design parameters of the S‐FBI system and the optimal values for each parameter are evaluated. Next, in order to assess the effectiveness of the S‐FBI system, the response of the bridge isolated by the S‐FBI system is compared with the response of the non‐isolated bridge and the same bridge isolated by pure‐friction (P‐F) sliding isolation system. Finally, the influence of temperature variations on the performance of the S‐FBI system is evaluated. The results show that the optimum design of a bridge with the S‐FBI system can be achieved by a judicious specification of design parameters. Copyright © 2010 John Wiley & Sons, Ltd.