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Water 2016, 8(2), 39; doi:10.3390/w8020039

An Analysis of the Occurrence Probabilities of Wet and Dry Periods through a Stochastic Monthly Rainfall Model

1
National Research Council—Institute for Agricultural and Forest Systems in Mediterranean (CNR-ISAFOM), Via Cavour 4/6, 87036 Rende (Cs), Italy
2
Department of Environmental and Chemical Engineering (DIATIC), University of Calabria, Via P. Bucci 41C, 87036 Rende (CS), Italy
3
National Research Council—Research Institute for Geo-Hydrological Protection (CNR-IRPI), Via Cavour 4/6, 87036 Rende (Cs), Italy
4
Department of Computer Engineering, Modeling, Electronics, and Systems Science (DIMES), University of Calabria, Via P. Bucci 41C, 87036 Rende (CS), Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Ataur Rahman
Received: 27 September 2015 / Revised: 11 January 2016 / Accepted: 22 January 2016 / Published: 28 January 2016
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Abstract

Stochastic simulators can effectively generate the intrinsic variability of the rainfall process, which is an important issue in the analysis of the projections uncertainties. In this paper, a procedure for stochastic modeling of precipitation at monthly scale is proposed. The model adopts variable transformations, which are finalized to the deseasonalization and the Gaussianization of the monthly rainfall process, and includes a procedure for testing the autocorrelation. The model was applied to a homogeneous database of monthly rainfall values registered in 12 rain gauges in the region of Calabria (Southern Italy). After the estimation of the model parameters, a set of 104 years of monthly rainfall for each rain gauge was generated by means of a Monte Carlo technique. Then, dry and wet periods were analyzed through the application of the standardized precipitation index (SPI). Some results, confirmed through the application of the drought severity index (DSI), showed that the proposed model provided a good representation of the monthly rainfall for the considered rain gauges. Moreover, the results of the SPI application indicate a greater probability of dry conditions than wet conditions, especially when long-term precipitation patterns are considered. View Full-Text
Keywords: monthly rainfall; stochastic model; dry and wet periods; Calabria monthly rainfall; stochastic model; dry and wet periods; Calabria
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Caloiero, T.; Sirangelo, B.; Coscarelli, R.; Ferrari, E. An Analysis of the Occurrence Probabilities of Wet and Dry Periods through a Stochastic Monthly Rainfall Model. Water 2016, 8, 39.

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