scholarly journals Occurrence analysis of daily rainfalls through non-homogeneous Poissonian processes

2011 ◽  
Vol 11 (6) ◽  
pp. 1657-1668 ◽  
Author(s):  
B. Sirangelo ◽  
E. Ferrari ◽  
D. L. De Luca
Keyword(s):  
Southern Italy ◽  
Daily Rainfall ◽  
Seasonal Effects ◽  
Validation Period ◽  
Threshold Values ◽  
Fourier Law ◽  
Homogeneous Poisson Process ◽  
Rain Gauges ◽  
Rainfall Occurrence ◽  
Non Homogeneous Poisson Process

Abstract. A stochastic model based on a non-homogeneous Poisson process, characterised by a time-dependent intensity of rainfall occurrence, is employed to explain seasonal effects of daily rainfalls exceeding prefixed threshold values. The data modelling has been performed with a partition of observed daily rainfall data into a calibration period for parameter estimation and a validation period for checking on occurrence process changes. The model has been applied to a set of rain gauges located in different geographical areas of Southern Italy. The results show a good fit for time-varying intensity of rainfall occurrence process by 2-harmonic Fourier law and no statistically significant evidence of changes in the validation period for different threshold values.

scholarly journals Changes in the occurrence of rainfall-induced landslides in Calabria, Southern Italy, in the 20th century

2015 ◽  
Vol 3 (6) ◽  
pp. 3579-3619
Author(s):  
S. L. Gariano ◽  
O. Petrucci ◽  
F. Guzzetti
Keyword(s):  
Southern Italy ◽  
Geographical Area ◽  
Daily Rainfall ◽  
Recent Period ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Entire Observation Period ◽  
Geographical Variations ◽  
The Impact ◽  
Observation Period

Abstract. We exploit a catalogue of 1466 rainfall events with landslides in the 90 year period 1921–2010 to study temporal and geographical variations in the occurrence of landslides in Calabria, Southern Italy. We use daily rainfall records obtained by a network of 318 rain gauges to reconstruct 448 493 rainfall events. Combining the rainfall and the landslide information, we obtain a catalogue of 1466 rainfall events with landslides (REL) in Calabria from 1921 to 2010, where a REL is the occurrence of one or more landslide during or immediately after a rainfall event. We find that the geographical and the temporal distributions of the rainfall-induced landslides have changed in the observation period. The average and the maximum values of the cumulated event rainfall that have resulted in landslides in the recent-most 30 year period 1981–2010 are lower than the values necessary to trigger landslides in previous periods, whereas the duration of the rainfall events that triggered landslides has remained the same. This can be considered evidence of variations in rainfall conditions, but also an increase in the vulnerability of the territory. We further find that the yearly distribution of rainfall-induced landslides has changed in the observation period, analysing the variations in the number of rainfall events with landslides occurred in each month in three 30 year periods. To investigate variations in the impact of REL on the population, we compared the number of REL in each of the 409 municipalities in Calabria, with the size of the population in the municipalities, measured by national Censuses conducted in 1951, 1981, and 2011. For the purpose, we adopted two strategies. The first strategy considered impact as IREL = #REL/P and the second strategy measured impact as RREL = #REL × P, where #REL is the total number of REL in a period, and P is the size of the population in the same period and geographical area. Considering the entire observation period, IREL and RREL have both increased in Calabria. However, considering the changes between the recent period 1981–2010 and the previous period 1951–1980, results are more variegated with a number of municipalities where IREL and RREL have increased, or decreased. Municipalities where IREL has increased are mainly in the mountains, and municipalities where RREL has increased are mainly along the coasts.

Kernel Based Estimation for a Non-Homogeneous Poisson Processes

2013 ◽  
Vol 805-806 ◽  
pp. 1948-1951
Author(s):  
Tian Jin
Keyword(s):  
Air Pollution ◽  
Nonparametric Estimation ◽  
Simulation Study ◽  
Poisson Model ◽  
Poisson Processes ◽  
Finite Sample ◽  
Process Data ◽  
Homogeneous Poisson Process ◽  
Finite Sample Properties ◽  
Non Homogeneous Poisson Process

The non-homogeneous Poisson model has been applied to various situations, including air pollution data. In this paper, we propose a kernel based nonparametric estimation for fitting the non-homogeneous Poisson process data. We show that our proposed estimator is-consistent and asymptotically normally distributed. We also study the finite-sample properties with a simulation study.

scholarly journals Bayesian Time Series Modelling of the Italian Daily Rainfall Data using Mixed Distribution

2019 ◽  
Vol 8 (4) ◽  
pp. 2279-2288
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Daily Rainfall Data ◽  
Mixed Distribution ◽  
Time Series Modelling ◽  
Bayesian Time Series ◽  
The Ideal

A combination of continuous and discrete elements is referred to as a mixed distribution. For example, daily rainfall data consist of zero and positive values. We aim to develop a Bayesian time series model that captures the evolution of the daily rainfall data in Italy, focussing on directly linking the amount and occurrence of rainfall. Two gamma (G1 and G2) distributions with different parameterisations and lognormal distribution were investigated to identify the ideal distribution representing the amount process. Truncated Fourier series was used to incorporate the seasonal effects which captures the variability in daily rainfall amounts throughout the year. A first-order Markov chain was used to model rainfall occurrence conditional on the presence or absence of rainfall on the previous day. We also built a hierarchical prior structure to represent our subjective beliefs and capture the initial uncertainties of the unknown model parameters for both amount and occurrence processes. The daily rainfall data from Urbino rain gauge station in Italy were then used to demonstrate the applicability of our proposed methods. Residual analysis and posterior predictive checking method were utilised to assess the adequacy of model fit. In conclusion, we clearly found that our proposed method satisfactorily and accurately fits the Italian daily rainfall data. The gamma distribution was found to be the ideal probability density function to represent the amount of daily rainfall.

Seasonal effects of rainfall on the shallow pyroclastic deposits of the Campania region (southern Italy)

Landslides ◽  
2013 ◽  
Vol 11 (5) ◽  
pp. 779-792 ◽  
Author(s):  
Leonardo Cascini ◽  
Giuseppe Sorbino ◽  
Sabatino Cuomo ◽  
Settimio Ferlisi
Keyword(s):  
Southern Italy ◽  
Seasonal Effects ◽  
Pyroclastic Deposits ◽  
Campania Region

Santa Cesarea Terme, a sulphuric acid speleogenetic system intensely influenced by marine waters

2021 ◽  
Author(s):  
Ilenia M. D'Angeli ◽  
Jo De Waele ◽  
Adriano Fiorucci ◽  
Bartolomeo Vigna ◽  
Stefano M. Bernasconi ◽  
...  
Keyword(s):  
Sulphuric Acid ◽  
Southern Italy ◽  
Sea Water ◽  
Sampling Site ◽  
Seasonal Effects ◽  
Water Sampling ◽  
Marine Waters ◽  
Water Head ◽  
Marine Influence ◽  
By Products

<p>Santa Cesarea Terme (SCT) karst system opens along the Adriatic coastline of Apulia (southern Italy) and is composed of four sub-horizontally caves Fetida, Sulfurea, Gattulla and Solfatara. Being influenced by rising sulphidic waters, it is used as thermal spa for human health treatments. The caves show interesting signs of hypogene sulphuric acid speleogenetic (SAS) activity such as peculiar morphologies and mineralogical by-products. From the geomorphological standpoint it is possible to observe ceiling cupolas, megacusps (former megascallops), rising channels, submerged feeders, weathered walls, replacement pockets, whereas for mineralogy sulphur, gypsum and jarosite deposits have been recorded. Despite the presence of extensive SAS features, SCT is also intensely influenced by marine water.</p><p>All these observations induced us to conduct a long-lasting (2015-2018) geochemical monitoring to understand intensity and tendency of the two main domains (rising acidic vs. marine).</p><p>Water sampling was done every 3-4 months at 4 sites in Fetida (2 in areas influenced by sea water movements, and 2 in the innermost zone, less but still influenced by sea), and 1 site in Gattulla. Moreover, 1 sampling site located along the coastline (sea water) was constantly monitoring for comparative reasons.</p><p>Collected groundwaters exhibit mean temperatures of 23 °C (7 °C higher than average annual air temperature) and circumneutral pH. All samples belong to the Na-Cl-SO<sub>4</sub> type of waters. Sea waters display the highest pH (ranging between 8.15 and 8.20), [Na<sup>+</sup>], [K<sup>+</sup>], [Mg<sup>2+</sup>], [Cl<sup>-</sup>], [SO<sub>4</sub><sup>2-</sup>], and total dissolved solids (TDS), and on the other hands one of the innermost sampling site in Fetida Cave showed the highest values of temperature (29 °C), [HS<sup>-</sup>], [Ca<sup>2+</sup>] and the lowest pH (6.76). In addition, the Ba<sup>2+</sup>/Sr<sup>2+ </sup>ratio compared with Ca<sup>2+</sup>/HCO<sub>3</sub><sup>-</sup> or Ca<sup>2+</sup>/SO<sub>4</sub><sup>2-</sup> clearly exhibit the presence of two main domains: rising acid and marine. In particular, the samples collected in the Adriatic Sea are always in the domain of marine influence, whilst all the others from Gattulla and Fetida, depending on sampling conditions (tides, waves, etc..), can fall in both domains.</p><p>Our investigations demonstrated rising sulphidic fluids to reach the surface through deep tectonic fractures and karst flowpaths, but seasonal effects due to modest water head variations (tides) and meteomarine conditions affect the geochemical variability, even in the innermost portion of the caves, inducing these slightly thermal acidic fluids to partially mix with marine waters.</p>

scholarly journals Generalized Entropies, Variance and Applications

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 709 ◽  
Author(s):  
Abdolsaeed Toomaj ◽  
Antonio Di Crescenzo
Keyword(s):  
Residual Entropy ◽  
Dispersion Measure ◽  
Homogeneous Poisson Process ◽  
Cumulative Residual Entropy ◽  
Excess Wealth Order ◽  
Dynamic Version ◽  
Cumulative Residual ◽  
Non Homogeneous Poisson Process ◽  
Generalized Entropies ◽  
Cumulative Entropy

The generalized cumulative residual entropy is a recently defined dispersion measure. In this paper, we obtain some further results for such a measure, in relation to the generalized cumulative residual entropy and the variance of random lifetimes. We show that it has an intimate connection with the non-homogeneous Poisson process. We also get new expressions, bounds and stochastic comparisons involving such measures. Moreover, the dynamic version of the mentioned notions is studied through the residual lifetimes and suitable aging notions. In this framework we achieve some findings of interest in reliability theory, such as a characterization for the exponential distribution, various results on k-out-of-n systems, and a connection to the excess wealth order. We also obtain similar results for the generalized cumulative entropy, which is a dual measure to the generalized cumulative residual entropy.

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