Preprints
https://doi.org/10.5194/hess-2021-353
https://doi.org/10.5194/hess-2021-353

  08 Jul 2021

08 Jul 2021

Review status: this preprint is currently under review for the journal HESS.

Synthesizing the impacts of baseflow contribution on C-Q relationships across Australia using a Bayesian Hierarchical Model

Danlu Guo1, Camille Minaudo2, Anna Lintern3, Ulrike Bende-Michl4, Shuci Liu1, Kefeng Zhang5, and Clément Duvert6,7 Danlu Guo et al.
  • 1Department of Infrastructure Engineering, University of Melbourne, Victoria, 3010, Australia
  • 2EPFL, Physics of Aquatic Systems Laboratory, Margaretha Kamprad Chair, Lausanne, Switzerland
  • 3Department of Civil Engineering, Monash University, Victoria, 3800, Australia
  • 4Bureau of Meteorology, 2601 Canberra, Australia
  • 5Water Research Centre, School of Civil and Environmental Engineering, UNSW Sydney, High St, Kensington, NSW 2052, Australia
  • 6Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, Australia
  • 7National Centre for Groundwater Research and Training (NCGRT), Australia

Abstract. The spatial and temporal variation of concentration-discharge (C-Q) relationships inform solute and particulate export processes. Previous studies have shown that the extent to which baseflow contributes to streamflow can affect C-Q relationships in some catchments. However, these patterns have not yet been investigated across large spatial scales. To address this, the study aims to assess how baseflow contributions, as defined by the median catchment baseflow index (BFI_m), influence C-Q slopes across 157 catchments in Australia spanning five climate zones. This study focuses on six water quality variables: electrical conductivity (EC), total phosphorus (TP), soluble reactive phosphorus (SRP), total suspended solids (TSS), nitrate–nitrite (NOx) and total nitrogen (TN). The impact of baseflow contribution is explored with a novel Bayesian hierarchical model.

We found that BFI_m has a strong impact on C-Q slopes. C-Q slopes are largely positive for nutrient species (NOx, TN, SRP and TP) and are steeper in catchments with higher BFI_m across all climate zones (for TN, SRP and TP). On the other hand, we also found a generally higher variation in instantaneous BFI for catchments with high BFI_m. Thus, the steeper C-Q slopes found in catchments with high BFI_m may be a result of a larger variation in water sources and flow pathways between low (baseflow-dominated) and high (quickflow-dominated) flow conditions. In contrast, catchments with low BFI_m may have more homogeneous flow pathways at both low and high flows, resulting in less variable concentrations and thus a flatter C-Q slope. Our model can explain over half of the observed variability in concentration of TSS, EC and P species across all catchments (93 % for EC, 63 % for TP, 63 % for SRP, and 60 % for TSS), while being able to predict C-Q slopes across space by BFI_m. This indicates that our parsimonious model has potential for predicting the C-Q slopes for catchments in different climate zones, and thus improving the predictive capacity for water quality across Australia.

Danlu Guo et al.

Status: open (until 02 Sep 2021)

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Short summary
This study aims to understand the impact of baseflow contribution on the concentration-flow (C-Q) relationships across large spatial scales. We developed a novel Bayesian hierarchical model for six water quality variables, across 157 catchments in Australia spanning five climate zones. For all water quality variables, C-Q slope is generally steeper for catchments with higher median baseflow contribution, which likely explained by the variability of flow pathways in individual catchments.