The variation and controls of mean transit times in Australian headwater catchments

Abstract

Determining mean transit times in headwater catchments is critical for understanding catchment functioning and understanding their responses to changes in landuse or climate. Determining whether mean transit times (MTTs) correlate with drainage density, slope angle, area, or land cover permits a better understanding of the controls on water flow through catchments and allows first‐order predictions of MTTs in other catchments to be made. This study assesses whether there are identifiable controls on MTTs determined using 3H in headwater catchments of southeast Australia. Despite MTTs at baseflow varying from a few years to >100 years, it was difficult to predict MTTs using single or groups of readily‐measured catchment attributes. The lack of readily‐identifiable correlations hampers the prediction of MTTs in adjacent catchments even where these have similar geology, land use, and topography. The long MTTs of the Australian headwater catchments are probably in part due to the catchments having high storage volumes in deeply‐weathered regolith, combined with low recharge rates due to high evapotranspiration. However, the difficulty in estimating storage volumes at the catchment scale hampers the use of this parameter to estimate MTTs. The runoff coefficient (the fraction of rainfall exported via the stream) is probably also controlled by evapotranspiration and recharge rates. Correlations between the runoff coefficient and MTTs in individual catchments allow predictions of MTTs in nearby catchments to be made. MTTs are shorter in high rainfall periods as the catchments wet up and shallow water stores are mobilized. Despite the contribution of younger water, the major ion geochemistry in individual catchments commonly does not correlate with MTTs, probably reflecting heterogeneous reactions and varying degrees of evapotranspiration. Documenting MTTs in catchments with high storage volumes and/or low recharge rates elsewhere is important for understanding MTTs in diverse environments.

Using water age to explore hydrological processes in contrasting environments

“…These are compounded by logistical challenges of sampling in often large, remote catchments. Cartwright et al (2020) used tritium dating of streamflow in a number of mesoscale catchments in Victoria to ascertain Mean Transit Times of base flows and to relate these to potential climatic and landscape controls.…”

Comment on “A comparison of catchment travel times and storage deduced from deuterium and tritium tracers using StorAge Selection functions” by Rodriguez et al. (2021)

“…Other lumped parameter models such as the gamma (GM) or dispersion (DM) models could also have been used; the GM(α = 3) and DM(D P = 0.22) models produce distributions that are closely equivalent to the EPM(f = 0.7) curve (Stewart et al, 2017). Cartwright et al (2018) also showed that numerical models that include dispersion yield similar curves; such models are independent of the lumped parameter model approach.…”

“…A recent summary of tritium results from Australian catchments illustrates the capacity of tritium to identify old water in SH catchments (Table 1, Cartwright et al, 2020;Duvert et al, 2016). These MTTs are much longer than could be estimated by stable isotopes, so they show that truncation is very much an issue.…”

Aplicações de trítio na determinação de tempos de residência no ciclo hidrológico

“…Aprimorando o trabalho descrito anteriormente, CARTWRIGHT et al (2020) expandiram para quatro o número de cabeceiras de bacias hidrográficas estudadas na região sudeste da Austrália, utilizando a mesma metodologia, resultando em 29 sub-bacias. Os autores explicitam a necessidade de incrementar os estudos relacionando o tempo médio de residência e as características das bacias, de modo a revelar as relações que controlam o sistema.…”