High-resolution rain analysis in FVG, Northeastern Italy

The Julian Alps, located in the region of Friuli Venezia Giulia (FVG, Northeastern Italy), record the heaviest precipitation annual totals in the country. Due to the complex orography and several other prone factors, effects of both prolonged and extreme precipitation can be particularly damaging in this area, causing debris flow, flash floods, avalanches. A proper planning of protection against natural hazards then requires the understanding of possible modification in rainfall characteristics. Since the mountain watersheds of the Alpine area are characterized by a very short time of concentration and hydrological response, extreme events are of particular interest, and rainfall analyses at sub-daily scale could not be appropriate. The region counts on a dense ground-station network which is managed by the regional Civil Protection Agency, constituted by 2 main rain-gauges networks, based on CAE and Micros-SIAP technology, respectively; this last is co-managed by the OSMER-ARPA (OSservatorio MEteorologico Regionale-Agenzia Regionale per la Protezione dell’Ambiente) FVG. The networks count a total of about 200 rain-gauges; for some stations, data at 5-minute resolution are available since the 1996 (CAE network), whereas Micros-SIAP works continuously and at high resolution since the early 2000s. Over the last two decades, the temporal resolution of stations has been progressively increased up to 1-minute step. In this work, we propose a comprehensive analysis of the available dataset at high temporal resolution (i.e. 30 min, 5 min and 1 min) in order to verify whether trends in very short rainfall duration are underway. At this aim, we first analyzed the continuous time series of data recorded by a sample of rain-gauges by the two networks. A preliminary analysis aims at verifying the consistency of the dataset at the higher resolutions. Statistical trends are then assessed by comparing two methods, i.e., the classical Mann-Kendall and the quantile regression at different thresholds and durations. The quantile regression method, which is increasingly used in hydrology, allows to detect changes in the tails of the rainfall distributions and to screen the whole rainfall time series, differently than the traditional methods that require a subset of data (e.g., the rainfall annual maxima)

Preliminary analysis of high-resolution precipitation in Friuli Venezia Giulia region, Italy

The northeastern area of Italy, and specifically of Friuli Venezia Giulia region (FVG), is characterized by the heaviest precipitation annual totals in the country. Effects of both prolonged and extreme precipitation can be particularly damaging in this area, causing debris flow, flash floods, avalanches. Due to the very short times of concentration and hydrological response of the mountain watersheds of the analyzed area, extreme and short events are of particular interest. The region has a dense ground-station network which is managed by the regional Civil Protection Agency, constituted by 2 main rain-gauges networks, based on CAE and Micros-SIAP technology, respectively; this last is co-managed by the OSMER-ARPA (OSservatorio MEteorologico Regionale-Agenzia Regionale per la Protezione dell’Ambiente) FVG. The networks count a total of about 200 rain-gauges; for some stations, data at 5-minute resolution are available since the 1996 (CAE network), whereas Micros-SIAP works continuously and at high resolution since the early 2000s. Over the last two decades, the temporal resolution of stations has been progressively increased up to 1-minute step. This work presents a comprehensive analysis of the available dataset at high temporal resolution (i.e. 30 min, 5 min and 1 min) to verify whether trends in very short rainfall duration are underway. The continuous time series of data recorded by a sample of rain-gauges by the two networks are first analyzed. A preliminary analysis aims at verifying the consistency of the dataset at the higher resolutions. Statistical trends are then assessed by comparing two methods, i.e., the classical Mann-Kendall and the quantile regression at different thresholds and durations. Differently than the traditional methods that require a subset of data (e.g., the rainfall annual maxima), the quantile regression method allows to detect changes in the tails of the rainfall distributions and to screen the whole rainfall time series

A coupled stability and eco-hydrological model to predict shallow landslides

Knowledge of spatio-temporal dynamics of soil water content, groundwater and infiltration processes is of considerable importance for the understanding and prediction of landslides. Rainfall and consequent water infiltration affect slope stability in various ways, mainly acting on the pore pressure distribution whose increase causes a decrease of the shearing resistance of the soil. For such reasons rainfall and transient changes in the hydrological systems are considered the most common triggers of landslides. So far, the difficulty to monitor groundwater levels or soil moisture contents in unstable terrain have made modeling of landslide a complex issue. At the present, the availability of sophisticated hydrological and physically based models, able to simulate the main hydrological processes, has allowed the development of coupled hydrologicalstability models able to predict when and where a failure could occur. In this study, a slope-failure module, with capability to predict shallow landslides, implemented into an ecohydrological model, tRIBS-VEGGIE (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator with VEGetation Generator for Interactive Evolution), is presented. The model evaluates the stability dynamics in term of factor of safety consequent to the soil moisture dynamics, strictly depending on the textural soil characteristics and hillslope geometry. Failure criterion used to derive factor of safety equation accounts for the stabilizing effect of matric suction arising in unsaturated soils. The eco-hydrological framework allows also to take into account the effect of vegetation with its cohesive effect as well as its weight load. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, has been selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. A static analysis based on susceptibility mapping approach was also carried out on the same area at a larger spatial scale, providing the hot spot of landsliding area. Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides. Moreover, stability dynamics have been assessed for different meteorological forcing and soil types, to better evaluate the influence of hydrological dynamics on slope stability

Parameter Uncertainty in Shallow Rainfall-triggered Landslide Modeling at Basin Scale: A Probabilistic Approach

This study proposes a methodology to account for the uncertainty of hydrological and mechanical parameters in coupled distributed hydrological-stability models for shallow landslide assessment. A probabilistic approach was implemented in an existing eco-hydrological and landslide model by randomizing soil cohesion, friction angle and soil retention parameters. The model estimates the probability of failure through an assumed theoretical Factor of Safety (FS) distribution, conditioned on soil moisture content. The time-dependent and spatially distributed FS statistics are approximated by the First Order Second Moment (FOSM) method. The model was applied to the Rio Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico

A coupled stability and eco-hydrological model to predict shallow landslides

4openopenARNONE, Elisa; NOTO, Leonardo; Lepore, C; Bras RLArnone, Elisa; Noto, Leonardo; Lepore, C; Bras, R

Field programmable gate arrays implementations of low complexity soft-input soft-output low-density parity-check decoders

Low-density parity-check (LDPC) codes are very efficient error control codes that are being considered for use in many next-generation communication systems. In this study low complexity soft-input, soft-output (SISO) field programmable gate arrays (FPGA) implementations of a novel logarithmic sum-product (LogSP) iterative LDPC decoder and a recently proposed simplified soft Euclidean distance (SSD) iterative LDPC decoder are presented, and their complexities and performance are compared. These implementations operate over any choice of parity check matrix (including those randomly generated, structurally generated and either systematic or non-systematic) and can be parametrically adapted for any code rate. The proposed implementations are both of very low complexity, because they operate using only sums, subtractions, comparisons and look-up tables, which makes them particularly suitable for FPGA realisation. The SSD decoder has a lower implementation complexity than the LogSP LDPC decoder and it also offers the advantage of not requiring knowledge of the channel signal-to-noise ratio, unlike most other LDPC decoders.Fil: Arnone, Leonardo Jose. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica; ArgentinaFil: Castiñeira Moreira, Jorge. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; ArgentinaFil: Farrell, P. G.. Lancaster University; Reino Unid

Assessing the hydrological changes due to land use alterations

The increase of urbanized areas and, consequently, of the impervious surfaces in land-use distributions may have important implications on the basin hydrological response. As a direct impact, the increase of cemented areas reduces the available storage volume for water in the watershed, which in turn exacerbates the runoff generation. Additionally, drainage pathways can be altered and the travel time to the watershed outlet considerably speeded up, with impacts on the hydrograph characteristics. The complex interactions among different hydrological processes make the estimations of the hydrological changes highly non linear. The aim of this work is using an advanced physically-based and distributed model, i.e. tRIBS (TIN-based real-time integrated basin simulator), to evaluate how the changes in the hydrological properties affect the watershed response not only in terms of outlet discharge but also in terms of spatial distribution of the main hydrological variables (e.g., soil moisture patterns, groundwater level, etc...). Moreover, we evaluate whether and how the spatial pattern of the impervious areas increase affects the change in the hydrological response. The work has been carried out on the Baron Fork watershed, located in OK (USA), characterized by an area of about 800 km2 and for which the tRIBS model was successfully calibrated in the past. Specifically, we eval- uate the hydrological response for different extreme events typical of the area and different land-use configurations