Collaborative spatial information as an alternative data source for hydrodynamic model calibration: a Pernambuco State case study, Brazil

Gabriel Araujo Oliveira (), Ayane Aparecida Silva Ribeiro () and José Almir Cirilo ()
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Gabriel Araujo Oliveira: Federal University of Pernambuco
Ayane Aparecida Silva Ribeiro: Federal University of Pernambuco
José Almir Cirilo: Federal University of Pernambuco

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 118, issue 2, No 30, 1535-1559

Abstract: Abstract This paper explores collaborative spatial data as an alternative data source for hydrodynamic model calibration, specifically concerning flood risk mapping. This study is motivated by the multiple uncertainties in the modeling process, especially in the relevant calibration and validation stages. Furthermore, information shared collaboratively can play a fundamental role when data are scarce, which is a usual modeling limitation. This paper tackled aspects like developing a collaborative platform (a mobile app) to collect flood marks; identifying strategies to motivate and engage potential collaborators; developing tools to analyze data consistency; and assessing the capability and restrictions in collaborative information use. Results validate the hypothesis that collaborative spatial data can be an alternative in hydrodynamic model calibration. Developing mechanisms to assess data consistency was crucial for achieving a good performance in the results, as simulations using collaborative data presented errors (RMSE) below 10 cm. Finally, regarding public motivation and engagement, elementary school students performed the best in data collection, highlighting the importance of direct actions, such as face-to-face workshops. Thus, the study hopes to reduce uncertainty in hydrological risk mapping, focusing specifically on observed data scarcity and its influence on model calibration and validation.

Keywords: Flood; Uncertainty; HEC-RAS; Hidromapp; Volunteered geographic information (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06073-z

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