UAV RGB,thermal infrared and multispectral imagery used to investigate the control of terrain on the spatial distribution of dryland biocrust

Biocrusts (topsoil communities formed by mosses, lichens, bacteria, fungi, algae, and cyanobacteria) are a key biotic component of dryland ecosystems. Whilst climate patterns control the distribution of biocrusts in drylands worldwide, terrain and soil attributes can influence biocrust distribution at landscape scale. Multi-source unmanned aerial vehicle (UAV) imagery was used to map and study biocrust ecology in a typical dryland ecosystem in central Spain. Red, green and blue (RGB) imagery was processed using structure-from-motion techniques to map terrain attributes related to microclimate and terrain stability. Multispectral imagery was used to produce accurate maps (accuracy > 80%) of dryland ecosystem components (vegetation, bare soil and biocrust composition). Finally, thermal infrared (TIR) and multispectral imagery was used to calculate the apparent thermal inertia (ATI) of soil and to evaluate how ATI was related to soil moisture (r² = 0.83). The relationship between soil properties and UAV-derived variables was first evaluated at the field plot level. Then, the maps obtained were used to explore the relationship between biocrusts and terrain attributes at ecosystem level through a redundancy analysis. The most significant variables that explain biocrust distribution are: ATI (34.4% of variance, F = 130.75; p < 0.001), Elevation (25.8%, F = 97.6; p < 0.001), and potential solar incoming radiation (PSIR) (52.9%, F = 200.1; p < 0.001). Differences were found between areas dominated by lichens and mosses. Lichen-dominated biocrusts were associated with areas with high slopes and low values of ATI, with soil characterized by a higher amount of soluble salts, and lower amount of organic carbon, total phosphorus (P_tot) and total nitrogen (N_tot). Biocrust-forming mosses dominated lower and moister areas, characterized by gentler slopes and higher values of ATI with soils with higher contents of organic carbon, P_tot and N_tot. This study shows the potential to use UAVs to improve our understanding of drylands and to evaluate the control that the terrain has on biocrust distribution.     

The role of floating mucilage in the invasive spread of the benthic microalga Chrysophaeum taylorii

Chrysophaeum taylorii Lewis & Bryan (Pelagophyceae) is a mucilage‐producing benthic microalga that has recently begun to spread in the Mediterranean Sea, where a range expansion is occurring. This paper presents the results of three field experiments that aimed to increase the knowledge on mucilage provision mechanisms for this benthic microalga and to evaluate the importance of mucilage in its range expansion. By means of two correlative field experiments (several years of data were considered to encompass the variability of mucilage cover) we found that, on the sea bottom, mucilage cover does not depend on epilithic cell density and that both its cover and settling are affected by water flow. We also tested the hypothesis that cells embedded in floating mucilage fall on the underlying substratum, where their abundance depends on water flow. To this aim, in the field we manipulated the presence of floating mucilaginous aggregates in cages with different levels of exposure to winds. The abundance of C. taylorii cells on the substratum under cages with mucilage was compared with that of two control treatments: cages without mucilage and mucilage in still water, in the field and lab, respectively. The results suggested that mucilage can represent an excellent strategy for the species to disperse, as C. taylorii cells fall from the floating mucilage and, if the water flow is unimportant, settle on hard substrata just underneath the cage. This study enriches the portfolio of knowledge of the dispersal strategies of microalgae and contributes to the understanding of the spread of invasive species.     

A probabilistic model for rainfall—induced shallow landslide prediction at the regional scale

This paper presents a new probabilistic physically-based computational model (called PG_TRIGRS) for the probabilistic analysis of rainfall-induced landslide hazard at a regional scale. The model is based on the deterministic approach implemented in the original TRIGRS code, developed by Baum et al. (USGS Open File Report 02–424, 2002) and Baum et al. (USGS Open File Report 08–1159, 2008). Its key innovative features are: (a) the application of Ordinary Kriging for the estimation of the spatial distributions of the first two statistical moments of the probability density functions of the relevant soil properties over the entire area, based on limited available information gathered from available information from limited site investigation campaigns, and (b) the use of Rosenblueth’s Point Estimate method as a more efficient alternative to the classical Monte Carlo method for the reliability analysis performed at the single-cell level to obtain the probability of failure associated to a given rainfall event. The application of the PG_TRIGRS code to a selected study area located in the Umbria Region for different idealized but realistic rainfall scenarios has demonstrated the computational efficiency and the accuracy of the proposed methodology, assessed by comparing predicted landslide densities with available field observations reported by the IFFI project. In particular, while the model might fail to identify all individual landslide events, its predictions are remarkably good in identifying the areas of higher landslide density.     

Cost-sensitive rainfall thresholds for shallow landslides

The risk management of rainfall-induced landslides requires reliable rainfall thresholds to issue early warning alerts. The practical application of these thresholds often leads to misclassifications, either false negative or false positive, which induce costs for the society. Since missed-alarm (false negative) and false-alarm (false positive) cost may be significantly different, it is necessary to find an optimal threshold that accounts for and minimises such costs, tuning the false-alarm and missed-alarm rates. In this paper, we propose a new methodology to develop cost-sensitive rainfall thresholds, and we also analyse several factors that produce uncertainty, such as the accuracy of rainfall intensity values at landslide location, the time of occurrence, the minimum rainfall amount to define the non-triggering event, and the variability of cost scenarios. Starting from a detailed mapping of landslides that occurred during five large-scale rainfall events in the Italian Central Alps, we first developed rainfall threshold curves with a ROC-based approach by using both rain gauge and bias-adjusted weather radar data. Then, based on a reference cost scenario in which we quantified several cost items for both missed alarms and false alarms, we developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). Finally, we studied the sensitivity of cost items. The study confirms how important is the information regarding rainfall intensity at the landslide site for the development of rainfall thresholds. Although the use of bias-corrected radar strongly improves these values, a large uncertainty related to the exact time of landslide occurrence still remains, negatively affecting the analysis. Accounting for the different missed-alarm and false-alarm misclassification costs is important because different combinations of these costs make an increase or decrease of the rainfall thresholds convenient. In our reference cost scenario, the most convenient threshold is lower than ROC-based thresholds because it seeks to minimise the number of missed alarms, whereas the missed-alarm costs are almost seven times greater than false-alarm costs. However, for different cost scenarios, threshold may vary significantly, as much as half an order of magnitude.

     

Cost–benefit analysis of flood mitigation measures: a case study employing high-performance hydraulic and damage modelling

Natural Hazards - This paper shows a detailed, advanced procedure to implement cost–benefit analyses (CBAs) in order to assess the effectiveness of flood mitigation measures. The town of Lodi...     

Dam-break Modeling in Alpine Valleys

Dam-break analysis is of great importance in mountain environment,especially where reservoirs are located upstream of densely populated areas and hydraulic hazard should be assessed for land planning purposes.Accordingly,there is a need to identify suitable operative tools which may differ from the ones used in flat flood-prone areas.This paper shows the results provided by a 1D and a 2D model based on the Shallow Water Equations（SWE） for dam-break wave propagation in alpine regions.The 1D model takes advantage of a topographic toolkit that includes an algorithm for pre-processing the Digital Elevation Model（DEM） and of a novel criterion for the automatic cross-section space refinement.The 2D model is FLO-2D,a commercial software widely used for flood routing in mountain areas.In order to verify the predictive effectiveness of these numerical models,the test case of the Cancano dam-break has been recovered from the historical study of De Marchi（1945）,which provides a unique laboratory data set concerning the consequences of the potential collapse of the former Cancano dam（Northern Italy）.The measured discharge hydrograph at the dam also provides the data to test a simplified method recently proposed for the characterization of the hydrograph following a sudden dam-break.     

New photometric models of galactic evolution applied to the HDF

We summarize our modelling of galaxy photometric evolution (the GRASIL code). By including the effects of dust grains and PAH molecules in a two-phase clumpy medium, where clumps are associated with star-forming regions, we reproduce the observed UV to radio SEDs of galaxies with star formation rates from zero to several hundred M _⊙ yr^-1.GRASIL is a powerful tool for investigating star formation, the initial mass function and the supernova rate in nearby starbursts and normal galaxies, as well as for predicting the evolution of luminosity functions of different types of galaxies at wavelengths covering six decades. It may be interfaced with any device to provide the star formation and metallicity histories of a galaxy. As an application, we have investigated the properties of early-type galaxies in the HDF, tracking the contribution of this population to the cosmic star formation history, which has a broad peak between z = 1.5 and 4.To explain the absence of objects at z ≳ 1.3, we suggest a sequence of dust-enshrouded merger-driven starbursts in the first few Gyr of galaxy lifetimes. We are at present working on a complementary sample of late-type objects selected in a similar way. This revised version was published online in July 2006 with corrections to the Cover Date.     

Optical Frequency Comb as a general-purpose and wide-band calibration source for astronomical high resolution infrared spectrographs

A spectrally filtered Optical Frequency Comb (OFC) laser is proposed as a versatile calibration source for astronomical spectrometers in the 1?C2 ??m spectral range. Such a source overcomes the limitations of current calibration lamps providing a uniform spectrum of equally spaced lines with similar intensity and extremely high long-term frequency stability. We present preliminary studies and results of a system which filters the OFC from a 100 MHz comb spacing to 16 GHz one, an adequate spacing for spectrometers with resolving power ????/???>30000. The first approach employs two Fabry-Perot cavities in series, made of dielectric coated mirrors, followed by a non-linear optical broadening system. The limitations of such a filtering process are discussed. These can be overcome by the second approach, based on filtering cavities with metallic coated mirrors.     

Understanding hydrological processes in glacierized catchments: Evidence and implications of highly variable isotopic and electrical conductivity data

The spatial and temporal characterization of geochemical tracers over Alpine glacierized catchments is particularly difficult, but fundamental to quantify groundwater, glacier melt, and rain water contribution to stream runoff. In this study, we analysed the spatial and temporal variability of δ²H and electrical conductivity (EC) in various water sources during three ablation seasons in an 8.4‐km² glacierized catchment in the Italian Alps, in relation to snow cover and hydro‐meteorological conditions. Variations in the daily streamflow range due to melt‐induced runoff events were controlled by maximum daily air temperature and snow covered area in the catchment. Maximum daily streamflow decreased with increasing snow cover, and a threshold relation was found between maximum daily temperature and daily streamflow range. During melt‐induced runoff events, stream water EC decreased due to the contribution of glacier melt water to stream runoff. In this catchment, EC could be used to distinguish the contribution of subglacial flow (identified as an end member, enriched in EC) from glacier melt water to stream runoff, whereas spring water in the study area could not be considered as an end member. The isotopic composition of snow, glacier ice, and melt water was not significantly correlated with the sampling point elevation, and the spatial variability was more likely affected by postdepositional processes. The high spatial and temporal variability in the tracer signature of the end members (subglacial flow, rain water, glacier melt water, and residual winter snow), together with small daily variability in stream water δ²H dynamics, are problematic for the quantification of the contribution of the identified end members to stream runoff, and call for further research, possibly integrated with other natural or artificial tracers.