Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Doctorat → Australie → 2019 → Modelling non-stationarity in rainfall-runoff relationships in Australian catchments

University of Newcastle (2019)

Modelling non-stationarity in rainfall-runoff relationships in Australian catchments

Deb Proloy

Titre : Modelling non-stationarity in rainfall-runoff relationships in Australian catchments

Auteur : Deb Proloy

Université de soutenance : University of Newcastle

Grade : Doctor of Philosophy (PhD) in Earth Sciences 2019

Résumé partiel
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.

Mots clés : hydrological modelling ; SWAT ; MODFLOW ; IHACRES ; surface water-groundwater interaction ; coupled modelling ; drought ; thesis by publication

Présentation

Version intégrale

Page publiée le 6 avril 2022