Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji

Masters Thesis


Moishin, Mohammed. 2021. Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji. Masters Thesis Master of Science (Research). University of Southern Queensland. https://doi.org/10.26192/zwww-vw94
Title

Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji

TypeMasters Thesis
Authors
AuthorMoishin, Mohammed
SupervisorDeo, Ravinesh C.
Prasad, Ramendra
Raj, Nawin
Abdulla, Shahab
Institution of OriginUniversity of Southern Queensland
Qualification NameMaster of Science (Research)
Number of Pages98
Year2021
Digital Object Identifier (DOI)https://doi.org/10.26192/zwww-vw94
Abstract

Floods are frequently occurring natural disasters that can cause significant damage to human lives, natural resources, and the civil infrastructures. The devastating impacts of flood events warrant the need to develop innovative means of both monitoring and forecasting of flood events to assist in reducing the damage caused by such events. In this research project, new mathematical methods designed to provide an objective explanation of the progression and forecasting of future flood events in Fiji are explored. Firstly, a flood monitoring tool known as the Flood Index (

Keywordshydrology, flood forecasting, deep learning, flood index, artificial intelligence
ANZSRC Field of Research 2020460299. Artificial intelligence not elsewhere classified
370799. Hydrology not elsewhere classified
Byline AffiliationsSchool of Sciences
Permalink -

https://research.usq.edu.au/item/q6qx6/development-of-flood-risk-monitoring-and-forecasting-system-with-artificial-intelligence-predictive-models-for-community-risk-management-in-fiji

Download files


Published Version
  • 350
    total views
  • 112
    total downloads
  • 2
    views this month
  • 3
    downloads this month

Export as

Related outputs

Designing Deep-based Learning Flood Forecast Model with ConvLSTM Hybrid Algorithm
Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Designing Deep-based Learning Flood Forecast Model with ConvLSTM Hybrid Algorithm." IEEE Access. 9, pp. 50982-50993. https://doi.org/10.1109/ACCESS.2021.3065939
Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji
Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji." Stochastic Environmental Research and Risk Assessment. 35 (7), pp. 1387-1402. https://doi.org/10.1007/s00477-020-01899-6