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Assessment of an Extreme Rainfall Detection System for Flood Prediction over Queensland (Australia)

ITHACA—Information Technology for Humanitarian Assistance, Cooperation and Action, 10138 Torino, Italy
Politecnico di Torino, Dipartimento di Ingegneria dell’Ambiente, del Territorio e delle Infrastrutture, 10129 Torino, Italy
Politecnico di Torino, Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio, 10125 Torino, Italy
Author to whom correspondence should be addressed.
Presented at the 3rd International Electronic Conference on Remote Sensing, 22 May–5 June 2019; Available online:
Proceedings 2019, 18(1), 1;
Published: 23 May 2019
(This article belongs to the Proceedings of 3rd International Electronic Conference on Remote Sensing)
Flood events represent some of the most catastrophic natural disasters, especially in localities where appropriate measurement instruments and early warning systems 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— was developed and implemented by ITHACA with the aim of monitoring and forecasting exceptional rainfall events and providing information in an understandable way for researchers as well as non-specialized users. The near real-time rainfall monitoring is performed by taking advantage of NASA GPM (Global Precipitation Measurement) IMERG (Integrated Multi-satellite Retrievals for GPM) 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 rivers) overflowed, expanding to a width of tens of kilometers. 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 outputs were 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 gain a clear look at 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 early warning system; extreme events; flood monitoring; GPM; hydrology; rainfall
MDPI and ACS Style

Mazzoglio, P.; Laio, F.; Sandu, C.; Boccardo, P. Assessment of an Extreme Rainfall Detection System for Flood Prediction over Queensland (Australia). Proceedings 2019, 18, 1.

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