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Multi-instrumental Analysis of the Extreme Meteorological Event Occurred in Matera (Italy) on November 2019

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

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Abstract

Most of the municipalities of the Italian territory are located in areas of high hydrogeological risk, i.e. exposed to flooding and landslides. Consequently, part of the existing cultural heritage on the national territory is located in areas subject to flood risk, which compromises the accessibility, preservation and integrity of cultural heritage. As an example, we consider a single flood event that occurred in southern Italy on November 11th and 12th, 2019, which mainly affected the city of Matera and its surroundings. This episode appears to be significant for the violence of the phenomenon that led to considerable quantities of water flowing inside the city, a UNESCO World Heritage Site, causing damage to buildings, including historical ones. The event has been analysed using both meteorology and geomatic technologies, to have an overview on spatial and temporal evolution of the phenomenon. Global Navigation Satellite System Zenith Total Delay (GNSS-ZTD) data obtained by receivers located around the city of Matera, were compared with measurements from ground-based devices (i.e. weather stations), Numerical Weather Prediction (NWP) models, and ERA5 reanalysis. To assess the extent of the flood and show the flooded areas, the images provided by the Sentinel-1 Synthetic Aperture Radar (SAR) were used, isolating and analyzing the images captured before and after the event. Finally, through a digital terrain model, developed using Agisoft Metashape software from satellite images, the morphology of Matera was recreated to evidence the areas of accumulation of water. Once all the information was obtained, the data correlated showed an overall view of the event.

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Acknowledgements

In this work the raw GNSS data were kindly provided by Geomatics Research & Development Srl (GReD), developer of the goGPS software. We would like to thank Valeria Belloni, Lorenzo Lastilla and Roberta Ravanelli for having made available to the research the DSM they developed. We would like to thank Civil Protection Department for providing us the rainfall data.

Author information

Authors and Affiliations

  1. Geodesy and Geomatic Division, University of Rome “La Sapienza”, Rome, Italy

    Virginia Coletta

  2. Department of Geosciences, University of Padova, Padova, Italy

    Alessandra Mascitelli

  3. CNR-ISAC, The Institute of Atmospheric Sciences and Climate, Rome, Italy

    Virginia Coletta, Alessandro Ciarravano, Stefano Federico, Fernanda Prestileo, Rosa Claudia Torcasio & Stefano Dietrich

  4. CNR-ISAC, The Institute of Atmospheric Sciences and Climate, Bologna, Italy

    Alessandra Bonazza

Authors
  1. Virginia Coletta
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  2. Alessandra Mascitelli
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  3. Alessandra Bonazza
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  4. Alessandro Ciarravano
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  5. Stefano Federico
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  7. Rosa Claudia Torcasio
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  8. Stefano Dietrich
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Correspondence to Virginia Coletta .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Coletta, V. et al. (2021). Multi-instrumental Analysis of the Extreme Meteorological Event Occurred in Matera (Italy) on November 2019. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12956. Springer, Cham. https://doi.org/10.1007/978-3-030-87010-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-87010-2_10

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-87010-2

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