http://www.cnr.it/ontology/cnr/individuo/prodotto/ID193700
A simple approach for stochastic generation of spatial rainfall patterns (Articolo in rivista)
- Type
- Label
- A simple approach for stochastic generation of spatial rainfall patterns (Articolo in rivista) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.jhydrol.2012.09.010 (literal)
- Alternative label
A. Tarpanelli, M. Franchini, L. Brocca, S. Camici, F. Melone, T. Moramarco (2012)
A simple approach for stochastic generation of spatial rainfall patterns
in Journal of hydrology (Amst.)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- A. Tarpanelli, M. Franchini, L. Brocca, S. Camici, F. Melone, T. Moramarco (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.sciencedirect.com/science/article/pii/S0022169412007603 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-IRPI
Università degli studi di Ferrara, Dipartimento di Ingegneria (literal)
- Titolo
- A simple approach for stochastic generation of spatial rainfall patterns (literal)
- Abstract
- Rainfall scenarios are of considerable interest for design flood and flood risk analysis. To this end, the stochastic
generation of continuous rainfall sequences is often coupled with the continuous hydrological
modelling. In this context, the spatial and the temporal rainfall variability represents a significant issue,
especially for basins in which the rainfall field cannot be approximated through the use of a single
station. Therefore, methodologies for the spatially and temporally correlated rainfall generation are welcome.
An example of such a methodology is the well-established Spatial-Temporal Neyman-Scott Rectangular
Pulse (STNSRP), a modification of the single-site Neyman-Scott Rectangular Pulse (NSRP)
approach, designed to incorporate specific features to reproduce the rainfall spatial cross-correlation.
In order to provide a simple alternative to the STNSRP, a new method of generating synthetic rainfall
time series with pre-set spatial-temporal correlation is proposed herein. This approach relies on the single-
site NSRP model, which is used to generate synthetic hourly independent rainfall time series at each
rain gauge station with the required temporal autocorrelation (and several other appropriately selected
statistics). The rank correlation method of Iman and Conover (IC) is then applied to these synthetic rainfall
time series in order to introduce the same spatial cross-correlation that exists between the observed
time series. This combination of the NSRP model with the IC method consents the reproduction of the
observed spatial-temporal variability of a rainfall field.
In order to verify the proposed procedure, four sub-basins of the Upper Tiber River basin are investigated
whose basin areas range from 165 km² to 2040 km². Results show that the procedure is able to preserve
both the rainfall temporal autocorrelation at single site and the rainfall spatial cross-correlation at
basin scale, and its performance is comparable with that of the STNSRP model for rainfall field generation.
Given its simple formal structure (based on well established methods: i.e. NSRP and IC), we believe that
the proposed approach can be conveniently utilized to generate spatially and temporally correlated rainfall
scenarios. (literal)
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