- Title
- Modelling non-stationarity in rainfall-runoff relationships in Australian catchments
- Creator
- Deb, Proloy
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2019
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Water resources management relies on hydrological (or rainfall runoff (R-R)) models. These models are typically used with an implicit assumption that hydrological processes and catchment characteristics are stationary. However, state-of-the-art R-R and eco-hydrological models (including the Australian Water Resources Assessment (AWRA) and the Source modelling platform) have been found to overestimate runoff during multi-year droughts in Southeast Australia (SEA), especially when calibrated during non-dry epochs. Therefore, it is necessary to identify the reasons why R-R models fail to realistically simulate runoff in catchments associated with non-stationarity in climate and/or catchment conditions. In this thesis, mechanisms governing both the annual and seasonal scale non-stationarity in R-R relationships were evaluated for two heterogeneous catchments in the SEA. The mechanisms evaluated were selected from the literature and were categorised into endogenous and exogenous (climate associated) catchment mechanisms. The results show that groundwater (GW) table (and associated surface water (SW)-GW interactions), baseflow (sub-surface water flow) and Leaf Area Index (LAI) (a proxy for vegetation cover) are the main endogenous catchment mechanisms which govern R-R non stationarity at both annual and seasonal scales. For exogenous catchment mechanisms, maximum temperature (Tmax), rainfall and potential evapotranspiration (ET₀) are found to be the most influential on R-R non-stationarity at annual and seasonal scales. These insights into important endogenous and exogenous catchment mechanisms were then supplemented by an investigation into which R-R model performs best under hydroclimatic variability and non-stationarity for the two study catchments in SEA. Multiple criteria analysis was used to decide on three R-R models (a conceptually lumped model (IHACRES), a process-based semi-distributed model (HEC-HMS) and a fully-distributed model (SWATgrid)) to compare under contrasting hydroclimatic conditions (Average1, Average2, Dry1, Dry2, Wet1 and Wet2 conditions). The models were calibrated for the Average1, Dry1 and Wet1 epochs and validated for Average2, Dry2 and Wet2 epochs for each calibration epochs. It was found that while SWATgrid model realistically simulates runoff at the smaller catchment for calibration/validation during the Average1 and Wet1 epochs. None of the models realistically simulate runoff under any climatic epoch in the larger catchment. This highlights the knowledge gap already mentioned, that existing R-R models do not realistically simulate runoff in catchments associated with non-stationarity in hydroclimatic conditions. In theory, a semi- or fully-distributed R-R model should account for mechanisms governing non-stationarity in R-R relationships. However, this is obviously not happening and it is hypothesised that a reason for this is the lack of realistic representation of SW-GW interactions in current R-R models. Therefore, in order to address this, a linked SW-GW modelling approach was developed and tested in the two study catchments. The linked SW-GW modelling approach couples a SW (or R-R) model (which is SWATgrid as it was identified to be the best performing model under hydroclimatic variability) and a GW model (MODFLOW, chosen based on multiple criteria analysis). First, SWATgrid was calibrated using its integrated GW approach of lumped baseflow components (stand-alone SWATgrid) and MODFLOW was calibrated under steady state condition with its integrated recharge calculation scheme. This was followed by the linked SW-GW approach simulation, where, the lumped baseflow estimation was replaced by the detailed GW flow estimation by MODFLOW and the recharge calculation of MODFLOW was replaced by the comprehensive recharge estimation by the SWATgrid model. The findings show that for both study catchments the linked SW-GW modelling approach results in more realistic runoff simulation under hydroclimatic variability compared to the stand-alone SWATgrid model. The findings of this thesis emphasise the importance of the identification of mechanisms governing R-R non-stationarity at both annual and seasonal scales. Also, it is recommended that, for arid/semi-arid catchments that have experienced, or are projected to experience, non-stationarity in R-R relationships (e.g. during multi-year droughts), a linked SW-GW modelling approach, such as that presented here, be employed. Otherwise, runoff estimates will continue to be unrealistic, especially during droughts and especially given projections of a hotter and drier future for much of SEA. These findings have direct implications for current and future water resources management in Australia, and anywhere else which experiences, or is projected to experience, non-stationarity in R-R relationships. Furthermore, the insights gained also contribute to the aims of the International Association of Hydrological Sciences decade (2013-2022) Panta Rhei, which focusses on improving our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment.
- Subject
- hydrological modelling; SWAT; MODFLOW; IHACRES; surface water-groundwater interaction; coupled modelling; drought; thesis by publication
- Identifier
- http://hdl.handle.net/1959.13/1410281
- Identifier
- uon:36156
- Rights
- Copyright 2019 Proloy Deb
- Language
- eng
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