Modelling floodplain vegetation responses to catchment hydrology under different climate change scenarios

PhD Thesis


Muhury, Newton. 2023. Modelling floodplain vegetation responses to catchment hydrology under different climate change scenarios. PhD Thesis Doctor of Philosophy . University of Southern Queensland. https://doi.org/10.26192/z7895
Title

Modelling floodplain vegetation responses to catchment hydrology under different climate change scenarios

TypePhD Thesis
AuthorsMuhury, Newton
Supervisor
1. FirstProf Armando Apan
2. SecondProf Tek Maraseni
Institution of OriginUniversity of Southern Queensland
Qualification NameDoctor of Philosophy
Number of Pages193
Year2023
PublisherUniversity of Southern Queensland
Place of PublicationAustralia
Digital Object Identifier (DOI)https://doi.org/10.26192/z7895
Abstract

The floodplain ecosystems are the most ecologically and economically significant areas increasingly becoming vulnerable and facing severe challenges due to climate change. Understanding how floodplain vegetation responds to changes in climate is essential for effective conservation and management strategies. This study was conducted in an Australian floodplain, with the following objectives: 1) to assess the relationship between surface water interannual variability and responses of different vegetation types in floodplain areas; 2) to evaluate the spatiotemporal impacts of groundwater dynamics on floodplain vegetation; and 3) to model floodplain vegetation responses under different climate change scenarios. To address the first objective, a hydrological model was set up in the Burrinjuck sub-catchment area and calibrated against daily rainfall and streamflow data to simulate catchment runoff. Model performance was evaluated against the Nash Sutcliffe Coefficient of efficiency (NSE) value of 0.95, indicating very good performance. The modelling results show high positive relationships (r=0.85, 0.82, and 0.81) between the observed and predicted NDVI values of grass-type vegetation (distant from the stream) against the rainfall, runoff, and streamflow, respectively, during the dry season. However, these relationships were reduced by 26.8% (r=0.60) and 33.33% (r=0.54) against runoff and streamflow during the wet season. For the second objective, different floodplain vegetation types in the study area were analysed against groundwater dynamics at the catchment level using ArcSWAT. The SWAT model was calibrated and validated in SWAT-CUP software using ten years (2001–2010) of monthly streamflow data. The modelling results show high positive relationships (r = 0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the sub-basin against the groundwater flow (GW), soil water content (SWC), and combination of these two variables, respectively, during the dry season. For the third objective, the SWAT model was simulated against future time series of climate data projections under RCP4.5 and RCP8.5 climate scenarios. The modelling results reveal that vegetation greenness (LAI) decreased by 147.8% during winter and increased by 5.3% in the summer. The MODIS satellite imagery has been proven effective in studying floodplain vegetation at the catchment level, as evidenced by this study. Additionally, the study emphasises how climate change will affect future floodplain vegetation sustainability. The strategic information gathered from this study regarding current and future floodplain vegetation in Australia will be valuable for long-term planning and management of floodplain vegetation in the country.

KeywordsClimate; Catchment-hydrology; ArcSWAT; LAI; NDVI; SIMHYD
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020310301. Behavioural ecology
Public Notes

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Byline AffiliationsSchool of Surveying and Built Environment
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