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Assessment of an Extreme Rainfall Detection System for flood prediction over Queensland (Australia)
Paola Mazzoglio * 1 , Francesco Laio 2 , Constantin Sandu 1 , Piero Boccardo 3
1  ITHACA - Information Technology for Humanitarian Assistance, Cooperation and Action, Torino, 10138, Italy
2  Politecnico di Torino, Dipartimento di Ingegneria dell’Ambiente, del Territorio e delle Infrastrutture, Torino, 10129, Italy
3  Politecnico di Torino, Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio, Torino, 10125, Italy

10.3390/ECRS-3-06187
Abstract:

Flood events represent some of the most catastrophic natural disasters, especially in localities where appropriate measurement instruments and early warning system are not available. Remotely sensed data can often help to obtain near real-time rainfall information with a global spatial coverage without the limitations that characterize other instruments. In order to achieve this goal, a freely accessible Extreme Rainfall Detection System (ERDS – erds.ithacaweb.org) was developed and implemented by ITHACA with the aim of monitoring and forecasting exceptional rainfall events and providing information in an understandable way also for non-specialized users. The near real-time rainfall monitoring is performed taking advantages of NASA GPM IMERG half-hourly data (one of the most advanced rainfall measurements provided by satellite).
This study aims to evaluate ERDS performance in the detection of the extreme rainfall that led to a massive flood event in Queensland (Australia) between January and February 2019. Due to the impressive amount of rainfall that affected the area, Flinders River (one of the longest Australian river) overflowed, expanding to a width of tens of kilometres. Several cities were also partially affected and Copernicus Emergency Management Service was activated with the aim of providing an assessment of the impact of the event.
In this research, ERDS output was validated using both in-situ and open source remotely sensed data. Specifically, taking advantage of both NASA MODIS (Moderate-resolution Imaging Spectroradiometer) and Copernicus Sentinel datasets it was possible to have a clear look of the full extent of the flood event. GPM data proved to be a reliable source of rainfall information for the evaluation of areas affected by heavy rainfall. By merging these data, it was possible to recreate the dynamics of the event.

Keywords: early warning system; extreme events; flood monitoring; GPM; hydrology; rainfall
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