This paper presents a comparative analysis between rain-gauge storm tracking techniques in order to achieve a better knowledge of the rainfall dynamics over an urbanized area. The temporal and spatial distribution and kinematics of short term rainfall are recognized as one of the most important reasons in error production in rainfall-runoff on urban catchments. The uncertainty due to rainfall variability can greatly affect urban drainage modeling performance and reliability thus reducing the confidence of operators in their results. Modeling representations of urban catchments and drainage systems are commonly adopted for surface flooding forecasting and management and an adequate knowledge of rainfall spatial and temporal variability should be considered as a fundamental step for a robust interpretation of the physical processes that take part in urban areas during intense rainfall events. The starting basis of such studies is usually given by a network of high resolution raingauges disseminated inside and around the examined urban area. One of the raingauge techniques used is based on simulating the storm motion by visualizing the sequence of the rainfall patterns obtained using rain-gauge data and on spatial correlation. The storm speed and direction are obtained using the rain-gauge method by tracking the advance of the maximum rainfall intensity in time and space. A second method is based on the identification, for each gauge, of the time of occurrence of some significant features such the time of onset of a storm or the time of peak. A third method is based on the classical idea of spacetime autocorrelation function; This function describes the way in which the correspondence between the rainfall patterns at two points in space-time reduces as the distance between two points is increased. The analysis has been carried out on the basis given by high resolution rainfall data collected over Palermo urban area (Italy). The urban area has a surface of around 30 km2 and it is mainly distributed on North West – South East direction. The monitoring network is made of 10 tipping bucket raingauges. Bucket volume is equivalent to 0.1 mm rainfall. Raingauges have been uniformly distributed over the urban areas allocating them mainly over public buildings and school in order to allow for easy access. The network has been put in place in January 2006 and it is still working. Data is monthly collected by the operator that also provide for clock synchronization and ordinary maintenance and cleaning. An accurate analysis of the results of this comparison between the techniques has been carried out and, since the city of Palermo is not covered by any meteorological radar, the analysis of storm dynamics will allow to create a system monitoring hydrometeorological conditions which operates on time basis using the information coming from the raingauge network as forecast triggers.
Lo Conti, F., Noto, L., Quatrosi, A., La Loggia, G. (2009). USING HIGH RESOLUTION RAINGAUGE DATA FOR STORM TRACKING ANALYSIS IN THE URBAN AREA OF PALERMO, ITALY. In 8th INTERNATIONAL WORKSHOP on PRECIPITATION IN URBAN AREAS "Rainfall in the urban context: forecasting, risk and climate change" (pp.166-171). P. Molnar, P. Burlando, T. Einfalt.
USING HIGH RESOLUTION RAINGAUGE DATA FOR STORM TRACKING ANALYSIS IN THE URBAN AREA OF PALERMO, ITALY
LO CONTI, Francesco;NOTO, Leonardo;LA LOGGIA, Goffredo
2009-01-01
Abstract
This paper presents a comparative analysis between rain-gauge storm tracking techniques in order to achieve a better knowledge of the rainfall dynamics over an urbanized area. The temporal and spatial distribution and kinematics of short term rainfall are recognized as one of the most important reasons in error production in rainfall-runoff on urban catchments. The uncertainty due to rainfall variability can greatly affect urban drainage modeling performance and reliability thus reducing the confidence of operators in their results. Modeling representations of urban catchments and drainage systems are commonly adopted for surface flooding forecasting and management and an adequate knowledge of rainfall spatial and temporal variability should be considered as a fundamental step for a robust interpretation of the physical processes that take part in urban areas during intense rainfall events. The starting basis of such studies is usually given by a network of high resolution raingauges disseminated inside and around the examined urban area. One of the raingauge techniques used is based on simulating the storm motion by visualizing the sequence of the rainfall patterns obtained using rain-gauge data and on spatial correlation. The storm speed and direction are obtained using the rain-gauge method by tracking the advance of the maximum rainfall intensity in time and space. A second method is based on the identification, for each gauge, of the time of occurrence of some significant features such the time of onset of a storm or the time of peak. A third method is based on the classical idea of spacetime autocorrelation function; This function describes the way in which the correspondence between the rainfall patterns at two points in space-time reduces as the distance between two points is increased. The analysis has been carried out on the basis given by high resolution rainfall data collected over Palermo urban area (Italy). The urban area has a surface of around 30 km2 and it is mainly distributed on North West – South East direction. The monitoring network is made of 10 tipping bucket raingauges. Bucket volume is equivalent to 0.1 mm rainfall. Raingauges have been uniformly distributed over the urban areas allocating them mainly over public buildings and school in order to allow for easy access. The network has been put in place in January 2006 and it is still working. Data is monthly collected by the operator that also provide for clock synchronization and ordinary maintenance and cleaning. An accurate analysis of the results of this comparison between the techniques has been carried out and, since the city of Palermo is not covered by any meteorological radar, the analysis of storm dynamics will allow to create a system monitoring hydrometeorological conditions which operates on time basis using the information coming from the raingauge network as forecast triggers.File | Dimensione | Formato | |
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