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<!DOCTYPE article SYSTEM "http://www.hydrol-earth-syst-sci.net/inc/hess/copernicus.dtd">
<article language="en">
	<journal>
		<journal_title>Hydrology and Earth System Sciences</journal_title>
		<journal_url>www.hydrol-earth-syst-sci.net</journal_url>
		<issn>1027-5606</issn>
		<eissn>1607-7938</eissn>
		<volume_number>10</volume_number>
		<issue_number>3</issue_number>
		<publication_year>2006</publication_year>
	</journal>
	<doi>10.5194/hess-10-413-2006</doi>
	<article_url>http://www.hydrol-earth-syst-sci.net/10/413/2006/</article_url>
	<abstract_html>http://www.hydrol-earth-syst-sci.net/10/413/2006/hess-10-413-2006.html</abstract_html>
	<fulltext_pdf>http://www.hydrol-earth-syst-sci.net/10/413/2006/hess-10-413-2006.pdf</fulltext_pdf>
	<start_page>413</start_page>
	<end_page>426</end_page>
	<publication_date>2006-06-07</publication_date>
	<article_title content_type="html">A Bayesian decision approach to rainfall thresholds based flood warning</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>M. L. V. Martina</name>
		</author>
		<author numeration="2" affiliations="1">
			<name>E. Todini</name>
		</author>
		<author numeration="3" affiliations="1">
			<name>A. Libralon</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Dept. of Earth and Geo-Environmental Sciences, Univ. of Bologna, Piazza di Porta San Donato, 1, Bologna, 40126, Italy</affiliation>
	</affiliations>
	<abstract content_type="html">Operational real time flood forecasting systems generally require a
hydrological model to run in real time as well as a series of
hydro-informatics tools to transform the flood forecast into relatively
simple and clear messages to the decision makers involved in flood defense.
The scope of this paper is to set forth the possibility of providing flood
warnings at given river sections based on the direct comparison of the
quantitative precipitation forecast with critical &lt;I&gt;rainfall threshold&lt;/I&gt; values, without the need
of an on-line real time forecasting system. This approach leads to an
extremely simplified alert system to be used by non technical stakeholders
and could also be used to supplement the traditional flood forecasting
systems in case of system failures. The critical rainfall threshold values,
incorporating the soil moisture initial conditions, result from statistical
analyses using long hydrological time series combined with a Bayesian
utility function minimization. In the paper, results of an application of
the proposed methodology to the Sieve river, a tributary of the Arno river
in Italy, are given to exemplify its practical applicability.</abstract>
	<references>
	</references>
</article>

