scholarly journals Societal landslide and flood risk in Italy

2010 ◽  
Vol 10 (3) ◽  
pp. 465-483 ◽  
Author(s):  
P. Salvati ◽  
C. Bianchi ◽  
M. Rossi ◽  
F. Guzzetti
Keyword(s):  
Flood Risk ◽  
Mass Function ◽  
Landslide Risk ◽  
Probability Mass Function ◽  
Scaling Exponent ◽  
Flood Events ◽  
Negative Power ◽  
Missing Persons ◽  
Italian Regions ◽  
Societal Risk

Abstract. We assessed societal landslide and flood risk to the population of Italy. The assessment was conducted at the national (synoptic) and at the regional scales. For the assessment, we used an improved version of the catalogue of historical landslide and flood events that have resulted in loss of life, missing persons, injuries and homelessness in Italy, from 1850 to 2008. This is the recent portion of a larger catalogue spanning the 1941-year period from 68 to 2008. We started by discussing uncertainty and completeness in the historical catalogue, and we performed an analysis of the temporal and geographical pattern of harmful landslide and flood events, in Italy. We found that sites affected by harmful landslides or floods are not distributed evenly in Italy, and we attributed the differences to different physiographical settings. To determine societal risk, we investigated the distribution of the number of landslide and flood casualties (deaths, missing persons, and injured people) in Italy, and in the 20 Italian Regions. Using order statistics, we found that the intensity of a landslide or flood event – measured by the total number of casualties in the event – follows a general negative power law trend. Next, we modelled the empirical distributions of the frequency of landslide and flood events with casualties in Italy and in each Region using a Zipf distribution. We used the scaling exponent s of the probability mass function (PMF) of the intensity of the events, which controls the proportion of small, medium, and large events, to compare societal risk levels in different geographical areas and for different periods. Lastly, to consider the frequency of the events with casualties, we scaled the PMF obtained for the individual Regions to the total number of events in each Region, in the period 1950–2008, and we used the results to rank societal landslide and flood risk in Italy. We found that in the considered period societal landslide risk is largest in Trentino-Alto Adige and Campania, and societal flood risk is highest in Piedmont and Sicily.

scholarly journals Perception of flood and landslide risk in Italy: a preliminary analysis

2014 ◽  
Vol 2 (5) ◽  
pp. 3465-3497 ◽  
Author(s):  
P. Salvati ◽  
C. Bianchi ◽  
F. Fiorucci ◽  
P. Giostrella ◽  
I. Marchesini ◽  
...  
Keyword(s):  
Risk Perception ◽  
Flood Risk ◽  
Volcanic Eruptions ◽  
Landslide Risk ◽  
Computer Assisted ◽  
Successful Implementation ◽  
General Knowledge ◽  
Flood Hazards ◽  
Italian Regions ◽  
Accurate Perception

Abstract. Inundations and landslides are widespread phenomena in Italy, where they cause severe damage and pose a threat to the population. Little is known on the perception of the population of landslides and floods. This is surprising, as an accurate perception is important for the successful implementation of many risk reduction or adaptation strategies. In an attempt to fill this gap, we have conducted two national surveys to measure the perception of landslide and flood risk of the population of Italy. The surveys were executed in 2012 and 2013, performing for each survey approximately 3100 computer assisted telephone interviews. The samples of the interviewees were statistically representative for a national scale quantitative assessment. The interviewees were asked questions designed to obtain information on their: (i) perception of natural, environmental, and technological risks, (ii) direct experience or general knowledge on the occurrence of landslides and floods in their municipality, (iii) perception of the possible threat posed by landslides and floods to their safety, (iv) general knowledge on the number of victims caused by landslides or floods, and on (v) the factors that they considered important to control landslide and flood risks in Italy. The surveys revealed that the population of Italy fears technological risks more than natural risks. Of the natural risks, earthquakes were considered more dangerous than floods, landslides, and volcanic eruptions. Examination of the temporal and geographical distribution of the responses revealed that the occurrence of recent damaging events influenced risk perception locally, and that the perception persisted longer for earthquakes and decreased more rapidly for landslides and floods. We justify the differentiation with the diverse consequences of the risks. The interviewees considered inappropriate land management the main cause of landslide and flood risk, followed by illegal construction, abandonment of the territory, and climate change. Comparison of the risk perception with actual measures of landslide and flood risk, including the number of fatal events, the number of fatalities, and the mortality rates, revealed that in most of the Italian regions the perception of the threat did not match the long-term risk posed by landslides and floods to the population. This outcome points to the need to fostering the understanding of the population of landslide and flood hazards and risks in Italy.

scholarly journals Perception of flood and landslide risk in Italy: a preliminary analysis

2014 ◽  
Vol 14 (9) ◽  
pp. 2589-2603 ◽  
Author(s):  
P. Salvati ◽  
C. Bianchi ◽  
F. Fiorucci ◽  
P. Giostrella ◽  
I. Marchesini ◽  
...  
Keyword(s):  
Risk Perception ◽  
Flood Risk ◽  
Public Perception ◽  
Volcanic Eruptions ◽  
Landslide Risk ◽  
Computer Assisted ◽  
Successful Implementation ◽  
General Knowledge ◽  
The Public ◽  
Italian Regions

Abstract. Inundations and landslides are widespread phenomena in Italy, where they cause severe damage and pose a threat to the population. Little is known about the public perception of landslide and flood risk. This is surprising, as an accurate perception is important for the successful implementation of many risk reduction or adaptation strategies. In an attempt to address this gap, we have conducted two national surveys to measure the perception of landslide and flood risk amongst the population of Italy. The surveys were conducted in 2012 and 2013, and consisted of approximately 3100 computer-assisted telephone interviews for each survey. The samples of the interviewees were statistically representative for a national-scale quantitative assessment. The interviewees were asked questions designed to obtain information on (i) their perception of natural, environmental, and technological risks, (ii) direct experience or general knowledge of the occurrence of landslides and floods in their municipality, (iii) perception of the possible threat posed by landslides and floods to their safety, (iv) general knowledge on the number of victims affected by landslides or floods, and on (v) the factors that the interviewees considered important for controlling landslide and flood risks in Italy. The surveys revealed that the population of Italy fears technological risks more than natural risks. Of the natural risks, earthquakes were considered more dangerous than floods, landslides, and volcanic eruptions. Examination of the temporal and geographical distributions of the responses revealed that the occurrence of recent damaging events influenced risk perception locally, and that the perception persisted longer for earthquakes and decreased more rapidly for landslides and floods. We explain the difference by the diverse consequences of the risks. The interviewees considered inappropriate land management the main cause of landslide and food risk, followed by illegal construction, abandonment of the territory, and climate change. Comparison of the risk perception with actual measures of landslide and flood risk, including the number of fatal events, the number of fatalities, and the mortality rates, revealed that in most of the Italian regions, the perception of the threat did not match the long-term risk posed to the population by landslides and floods. This outcome points to a need to foster an understanding of the public towards landslide and flood hazards and risks in Italy.

scholarly journals Flood Risk and Adaptation Strategies for Soybean Production Systems on the Flood-Prone Pampas under Climate Change

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1187
Author(s):  
Wouter Julius Smolenaars ◽  
Spyridon Paparrizos ◽  
Saskia Werners ◽  
Fulco Ludwig
Keyword(s):  
Climate Change ◽  
Flood Risk ◽  
Risk Perceptions ◽  
Production Systems ◽  
Adaptation Strategies ◽  
Flood Events ◽  
Climate Data ◽  
Soybean Production ◽  
Drying Trend ◽  
Sowing Season

In recent decades, multiple flood events have had a devastating impact on soybean production in Argentina. Recent advances suggest that the frequency and intensity of destructive flood events on the Argentinian Pampas will increase under pressure from climate change. This paper provides bottom-up insight into the flood risk for soybean production systems under climate change and the suitability of adaptation strategies in two of the most flood-prone areas of the Pampas region. The flood risk perceptions of soybean producers were explored through interviews, translated into climatic indicators and then studied using a multi-model climate data analysis. Soybean producers perceived the present flood risk for rural accessibility to be of the highest concern, especially during the harvest and sowing seasons when heavy machinery needs to reach soybean lots. An analysis of climatic change projections found a rising trend in annual and harvest precipitation and a slight drying trend during the sowing season. This indicates that the flood risk for harvest accessibility may increase under climate change. Several adaptation strategies were identified that can systemically address flood risks, but these require collaborative action and cannot be undertaken by individual producers. The results suggest that if cooperative adaptation efforts are not made in the short term, the continued increase in flood risk may force soybean producers in the case study locations to shift away from soybean towards more robust land uses.

scholarly journals Detecting Different Road Infrastructural Elements Based on the Stochastic Characterization of Speed Patterns

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Mario Muñoz-Organero ◽  
Ramona Ruiz-Blázquez
Keyword(s):  
Total Variation ◽  
Traffic Congestion ◽  
Automatic Detection ◽  
Mass Function ◽  
Total Variation Distance ◽  
Statistical Moments ◽  
Probability Mass Function ◽  
Traffic Lights ◽  
Traffic Conditions ◽  
Variation Distance

The automatic detection of road related information using data from sensors while driving has many potential applications such as traffic congestion detection or automatic routable map generation. This paper focuses on the automatic detection of road elements based on GPS data from on-vehicle systems. A new algorithm is developed that uses the total variation distance instead of the statistical moments to improve the classification accuracy. The algorithm is validated for detecting traffic lights, roundabouts, and street-crossings in a real scenario and the obtained accuracy (0.75) improves the best results using previous approaches based on statistical moments based features (0.71). Each road element to be detected is characterized as a vector of speeds measured when a driver goes through it. We first eliminate the speed samples in congested traffic conditions which are not comparable with clear traffic conditions and would contaminate the dataset. Then, we calculate the probability mass function for the speed (in 1 m/s intervals) at each point. The total variation distance is then used to find the similarity among different points of interest (which can contain a similar road element or a different one). Finally, a k-NN approach is used for assigning a class to each unlabelled element.

scholarly journals Modified Recursions for a Class of Compound Distributions

1996 ◽  
Vol 26 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Karl-Heinz Waldmann
Keyword(s):  
Distribution Function ◽  
Cumulative Distribution Function ◽  
Mass Function ◽  
Cumulative Distribution ◽  
Probability Mass Function ◽  
Initial Value ◽  
Compound Distributions ◽  
Claim Frequency ◽  
Probability Mass ◽  
Stop Loss

AbstractRecursions are derived for a class of compound distributions having a claim frequency distribution of the well known (a,b)-type. The probability mass function on which the recursions are usually based is replaced by the distribution function in order to obtain increasing iterates. A monotone transformation is suggested to avoid an underflow in the initial stages of the iteration. The faster increase of the transformed iterates is diminished by use of a scaling function. Further, an adaptive weighting depending on the initial value and the increase of the iterates is derived. It enables us to manage an arbitrary large portfolio. Some numerical results are displayed demonstrating the efficiency of the different methods. The computation of the stop-loss premiums using these methods are indicated. Finally, related iteration schemes based on the cumulative distribution function are outlined.

HEAVY TRAFFIC APPROXIMATIONS FOR A SYSTEM OF INFINITE SERVERS WITH LOAD BALANCING

1999 ◽  
Vol 13 (3) ◽  
pp. 251-273 ◽  
Author(s):  
Philip J. Fleming ◽  
Burton Simon
Keyword(s):  
State Space ◽  
Heavy Traffic ◽  
Joint Probability ◽  
Mass Function ◽  
Accurate Estimate ◽  
The State ◽  
Probability Mass Function ◽  
Traffic Loads ◽  
Wide Range ◽  
Heavy Traffic Approximations

We consider an exponential queueing system with multiple stations, each of which has an infinite number of servers and a dedicated arrival stream of jobs. In addition, there is an arrival stream of jobs that choose a station based on the state of the system. In this paper we describe two heavy traffic approximations for the stationary joint probability mass function of the number of busy servers at each station. One of the approximations involves state-space collapse and is accurate for large traffic loads. The state-space in the second approximation does not collapse. It provides an accurate estimate of the stationary behavior of the system over a wide range of traffic loads.

Quantification of Low-Cycle Fatigue Life for a Gas Turbine Compressor Vane Carrier Under Varying Operating Conditions

2020 ◽  
Author(s):  
Zixi Han ◽  
Zixian Jiang ◽  
Sophie Ehrt ◽  
Mian Li
Keyword(s):  
Low Cycle Fatigue ◽  
Computational Cost ◽  
Mass Function ◽  
Operating Conditions ◽  
Probability Mass Function ◽  
Assessment Approach ◽  
Probability Mass ◽  
Gas Turbine Compressor ◽  
Operating Cycles ◽  
Operational Data

Abstract The design of a gas turbine compressor vane carrier (CVC) should meet mechanical integrity requirements on, among others, low-cycle fatigue (LCF). The number of cycles to the LCF failure is the result of cyclic mechanical and thermal strain effects caused by operating conditions on the components. The conventional LCF assessment is usually based on the assumption on standard operating cycles — supplemented by the consideration of predefined extreme operations and safety factors to compensate a potential underestimate on the LCF damage caused by multiple reasons such as non-standard operating cycles. However, real operating cycles can vary significantly from those standard ones considered in the conventional methods. The conventional prediction of LCF life can be very different from real cases, due to the included safety margins. This work presents a probabilistic method to estimate the distributions of the LCF life under varying operating conditions using operational fleet data. Finite element analysis (FEA) results indicate that the first ramp-up loading in each cycle and the turning time before hot-restart cycles are two predominant contributors to the LCF damage. A surrogate model of LCF damage has been built with regard to these two features to reduce the computational cost of FEA. Miner’s rule is applied to calculate the accumulated LCF damage on the component and then obtain the LCF life. The proposed LCF assessment approach has two special points. First, a new data processing technique inspired by the cumulative sum (CUSUM) control chart is proposed to identify the first ramp-up period of each cycle from noised operational data. Second, the probability mass function of the LCF life for a CVC is estimated using the sequential convolution of the single-cycle damage distribution obtained from operational data. The result from the proposed method shows that the mean value of the LCF life at a critical location of the CVC is significantly larger than the calculated result from the deterministic assessment, and the LCF lives for different gas turbines of the same class are also very different. Finally, to avoid high computational cost of sequential convolution, a quick approximation approach for the probability mass function of the LCF life is given. With the capability of dealing with varying operating conditions and noises in the operational data, the enhanced LCF assessment approach proposed in this work provides a probabilistic reference both for reliability analysis in CVC design, and for predictive maintenance in after-sales service.

A critical analysis of French flood risk governance

2021 ◽  
Author(s):  
Ioannis Kougkoulos ◽  
Myriam Merad ◽  
Simon Cook ◽  
Ioannis Andredakis
Keyword(s):  
Flood Risk ◽  
Swot Analysis ◽  
Drainage Basin ◽  
Local Population ◽  
Risk Prevention ◽  
Risk Governance ◽  
Flood Events ◽  
Risk Models ◽  
Local Inhabitant ◽  
Do So

<p>France experiences catastrophic floods on a yearly basis, with significant societal impacts. In this paper, we critically evaluate the French Flood Risk Governance (FRG) system with the aim of identifying any shortcoming and, thereby, to suggest improvements. To do so, we employ a historical assessment of catastrophic past flood events in the Provence-Alpes-Côte d'Azur (PACA) region and perform Strengths-Weaknesses-Opportunities-Threats (SWOT)-analysis. Our evaluation shows that despite persistent government efforts, the impacts of flood events in the region do not appear to have lessened over time. Identical losses in the same locations (e.g. Riou de l’Argentière watershed) can be observed after repetitive catastrophic events (e.g. 2015, 2019) triggering local inhabitant protests. We argue that the French FRG system can benefit from the following improvements: a) regular updates of the risk prevention plans and tools; b) the adoption of a Build Back Better logic instead of promoting the reconstruction of damaged elements in the same locations; c) taking into account undeclared damages into flood risk models (and not only those declared to flood insurance); d) increased communication between the actors of the different steps of each cycle (prepare, control, organise etc.); e) increased communication between three main elements of the cycle (risk prevention, emergency management and disaster recovery); f) an approach that extends the risk analysis outside the borders of the drainage basin (to be used in combination with the current basin risk models); and g) increased participation in FRG from local population. We also briefly discuss the use operational research methods for the optimisation of the French FRG.</p>

Sign in / Sign up

Export Citation Format

Share Document