Extreme climate variability and impacts of future climate change on the streamflow in the southeast Queensland, Australia

PhD by Publication


Pakdel, Hadis. 2024. Extreme climate variability and impacts of future climate change on the streamflow in the southeast Queensland, Australia. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z9y78
Title

Extreme climate variability and impacts of future climate change on the streamflow in the southeast Queensland, Australia

TypePhD by Publication
AuthorsPakdel, Hadis
Supervisor
1. FirstDr Sreeni Chadalavada
2. SecondDr Md Jahangir Alam
3. ThirdDr Dev Raj Paudyal
Institution of OriginUniversity of Southern Queensland
Qualification NameDoctor of Philosophy
Number of Pages163
Year2024
PublisherUniversity of Southern Queensland
Place of PublicationAustralia
Digital Object Identifier (DOI)https://doi.org/10.26192/z9y78
Abstract

South East Queensland has experienced a series of recent catastrophic climatic events. From December 2010 to January 2011 and in February 2022, heavy rains caused flooding impacting over 2.5 million people and causing approximately 33 deaths. These events challenged the assumption of stationary conditions as no longer viable. The persistent use of this baseline assumption could potentially lead to misestimations in forecasting future floods. The severity and frequency of extremes are escalating; thus, it is necessary to evaluate the impacts of land cover changes and urbanisation, along with climate change. A framework of the trend analysis methods to analyse temporal patterns, spatial analysis techniques utilising the Google Earth Engine (GEE), Generalised Extreme Value (GEV) method, and land cover patterns classification including Random Forest (RF) and Support Vector Machine (SVM) can be useful for hydrometeorological variables extreme events analysis. This research highlights the importance of using spatiotemporal techniques and trend analysis by underscoring the changing frequency and severity of extreme events analysis. The aim of this research is to evaluate extreme events under non-stationary conditions, where the location parameter has a linear function with time. For this study, a unique framework consisting of the hydrological model in line with the Process-informed Non-Stationary Extreme Value Analysis (ProNEVA) GEV model and the ensemble of General Circulation Models (GCMs), mapping land cover patterns using classification methods within the GEE platform, were employed to comprehensively analyse the impacts of climate variability and land cover changes on extreme hydrological events. Runoff was projected under two scenarios for eight GCMs and by incorporating the percentage of each land cover into the hydrological model for two horizons, (2020-2065 and 2066-2085). The outcomes of this study suggest that neglecting non-stationary assumptions of flood frequency can lead to underestimating the magnitude of flooding. This, in turn, can lead to greater and increased risks to infrastructure planning and design. The framework of this research paper is adaptable to various geographical regions for the purposes of estimating extreme conditions; thereby offering valuable insights for infrastructure design, planning, risk assessment, and the sustainable management of future water resources in the context of long-term water management plans.

KeywordsNon-stationary extremes; climate change; Hydraulic structures; GEV distribution; Hydrological modelling
Related Output
Has partGoogle Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam
Has partA Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia
Has partVariability of Extreme Climate Events and Prediction of Land Cover Change and Future Climate Change Effects on the Streamflow in Southeast Queensland, Australia
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020400599. Civil engineering not elsewhere classified
400513. Water resources engineering
400599. Civil engineering not elsewhere classified
Public Notes

File reproduced in accordance with the copyright policy of the publisher/author/creator.

Byline AffiliationsAcademic Registrar's Office
School of Engineering
School of Surveying and Built Environment
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Related outputs

Variability of Extreme Climate Events and Prediction of Land Cover Change and Future Climate Change Effects on the Streamflow in Southeast Queensland, Australia
Pakdel, Hadis, Chadalavada, Sreeni, Alam, Md Jahangir, Paudyal, Dev Raj and Vazifedoust, Majid. 2024. "Variability of Extreme Climate Events and Prediction of Land Cover Change and Future Climate Change Effects on the Streamflow in Southeast Queensland, Australia." ISPRS International Journal of Geo-Information. 13 (4). https://doi.org/10.3390/ijgi13040123
A Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia
Pakdel, Hadis, Paudyal, Dev Raj, Chadalavada, Sreeni, Alam, Md Jahangir and Vazifedoust, Majid. 2023. "A Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia." ISPRS International Journal of Geo-Information. 12 (9). https://doi.org/10.3390/ijgi12090370
Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam
Pakdel-Khasmakhi, Hadis, Vazifedoust, Majid, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir. 2022. "Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam." ISPRS International Journal of Geo-Information. 11 (11), pp. 1-28. https://doi.org/10.3390/ijgi11110535