Integrated response and transit time distributions of watersheds by combining hydrograph separation and long-term transit time modeling

Roa-García, María Cecilia; Weiler, Markus

doi:10.5194/hess-14-1537-2010

Cited by 81 publications

(40 citation statements)

References 35 publications

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“…Transit time estimations based on lumped convolution modelling approaches have been carried out in various studies, reviewed by McGuire and McDonnell (2006), and subsequent studies such as Soulsby and Tetzlaff (2008), Tetzlaff et al (2009b), Hrachowitz et al (2010), Roa-García and Weiler (2010), Lyon et al (2010), Soulsby et al (2011), Heidbüchel et al (2012), and Capell et al (2012). Lumped convolution modelling approaches are based on the convolution of an input signal with a transfer function (TF) to obtain an appropriate output signal.…”

Section: Introductionmentioning

confidence: 99%

Reevaluation of transit time distributions, mean transit times and their relation to catchment topography

Seeger

Weiler

2014

Hydrol. Earth Syst. Sci.

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158

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Abstract. The transit time of water is a fundamental property of catchments, revealing information about the flow pathways, source of water and storage in a single integrated measure. While several studies have investigated the relationship between catchment topography and transit times, few studies expanded the analysis to a wide range of catchment properties and assessed the influence of the selected transfer function (TF) model. We used stable water isotopes from mostly baseflow samples with lumped convolution models of time-invariant TFs to estimate the transit time distributions of 24 meso-scale catchments covering different geomorphic and geologic regions in Switzerland. The sparse network of 13 precipitation isotope sampling sites required the development of a new spatial interpolation method for the monthly isotopic composition of precipitation. A pointenergy-balance based snow model was adapted to account for the seasonal water isotope storage in snow dominated catchments. Transit time distributions were estimated with three established TFs (exponential, gamma distribution and two parallel linear reservoirs). While the exponential TF proved to be less suitable to simulate the isotopic signal in most of the catchments, the gamma distribution and the two parallel linear reservoirs transfer function reached similarly good model fits to the fortnightly observed isotopic compositions in discharge, although in many catchments the transit time distributions implied by equally well fitted models differed markedly from each other and in extreme cases, the resulting mean transit time (MTT) differed by orders of magnitude. A more thorough comparison showed that equally suited models corresponded to agreeing values of cumulated transit time distributions only between 3 and 6 months. The short-term ( < 30 days) component of the transit time distributions did not play a role because of the limited temporal resolution of the available input data. The long-term component (> 3 years) could hardly be assessed by means of stable water isotopes, resulting in ambiguous MTT and hence questioning the relevance of an MTT determined with stable isotopes. Finally we investigated the relation between MTT estimates based on the three different TF types as well as other transit time properties and a range of topographical catchment characteristics. Depending on the selected transfer model, we found a weak correlation between transit time properties and the ratio between flow path length over the flow gradient, drainage density and the mean discharge. The catchment storage derived from MTTs and mean discharge did not show a clear relation to any catchment properties, indicating that in many studies the mean annual discharge may bias the MTT estimates.

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Section: Introductionmentioning

confidence: 99%

Reevaluation of transit time distributions, mean transit times and their relation to catchment topography

Seeger

Weiler

2014

Hydrol. Earth Syst. Sci.

Self Cite

158

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“…One of the reasons is that this non-stationarity is not accounted for in the models commonly used in catchment TT research. In the last 5 years, an ever-growing number of studies has transferred its focus to assessing dynamic TT distributions (Hrachowitz et al, 2010(Hrachowitz et al, , 2013Roa-García and Weiler, 2010;Rinaldo et al, 2011;Cvetkovic et al, 2012;Heidbüchel et al, 2012Heidbüchel et al, , 2013McMillan et al, 2012;Tetzlaff et al, 2014;Birkel et al, 2015;Benettin et al, 2015;Harman, 2015;Klaus et al, 2015a;Kirchner, 2015). Most of these studies agreed on the importance of considering storage dynamics, because the RT distribution of storage water and the TT distribution of water transiting at the outlet of the catchment are likely to be very different.…”

Section: Introductionmentioning

confidence: 99%

Time series of tritium, stable isotopes and chloride reveal short-term variations in groundwater contribution to a stream

Duvert

Stewart

Cendón

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract.A major limitation to the assessment of catchment transit time (TT) stems from the use of stable isotopes or chloride as hydrological tracers, because these tracers are blind to older contributions. Yet, accurately capturing the TT of the old water fraction is essential, as is the assessment of its temporal variations under non-stationary catchment dynamics. In this study we used lumped convolution models to examine time series of tritium, stable isotopes and chloride in rainfall, streamwater and groundwater of a catchment located in subtropical Australia. Our objectives were to determine the different contributions to streamflow and their variations over time, and to understand the relationship between catchment TT and groundwater residence time. Stable isotopes and chloride provided consistent estimates of TT in the upstream part of the catchment. A young component to streamflow was identified that was partitioned into quickflow (mean TT ≈ 2 weeks) and discharge from the fractured igneous rocks forming the headwaters (mean TT ≈ 0.3 years). The use of tritium was beneficial for determining an older contribution to streamflow in the downstream area. The best fits between measured and modelled tritium activities were obtained for a mean TT of 16-25 years for this older groundwater component. This was significantly lower than the residence time calculated for groundwater in the alluvial aquifer feeding the stream downstream (≈ 76-102 years), emphasising the fact that water exiting the catchment and water stored in it had distinctive age distributions. When simulations were run separately on each tritium streamwater sample, the TT of old water fraction varied substantially over time, with values averaging 17 ± 6 years at low flow and 38 ± 15 years after major recharge events. This counterintuitive result was interpreted as the flushing out of deeper, older waters shortly after recharge by the resulting pressure wave propagation. Overall, this study shows the usefulness of collecting tritium data in streamwater to document short-term variations in the older component of the TT distribution. Our results also shed light on the complex relationships between stored water and water in transit, which are highly non-linear and remain poorly understood.

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“…They pursued a storage mixing approach to deal with the inclusion of preevent water into the tracer event response. Roa-Garc ıa and Weiler [2010] also acknowledged the difference between hydrologic response and particle response and determined hydrologic response functions and transit time distributions for five individual precipitation events. They explained apparent variability with differences in event characteristics, antecedent conditions and land cover.…”

Section: Introductionmentioning

confidence: 99%

The master transit time distribution of variable flow systems

Heidbüchel

Troch

Lyon

et al. 2012

Water Resources Research

164

241

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[1] The transit time of water is an important indicator of catchment functioning and affects many biological and geochemical processes. Water entering a catchment at one point in time is composed of water molecules that will spend different amounts of time in the catchment before exiting. The next water input pulse can exhibit a totally different distribution of transit times. The distribution of water transit times is thus best characterized by a time-variable probability density function. It is often assumed, however, that the variability of the transit time distribution is negligible and that catchments can be characterized with a unique transit time distribution. In many cases this assumption is not valid because of variations in precipitation, evapotranspiration, and catchment water storage and associated (de)activation of dominant flow paths. This paper presents a general method to estimate the time-variable transit time distribution of catchment waters. Application of the method using several years of rainfall-runoff and stable water isotope data yields an ensemble of transit time distributions with different moments. The combined probability density function represents the master transit time distribution and characterizes the intraannual and interannual variability of catchment storage and flow paths. Comparing the derived master transit time distributions of two research catchments (one humid and one semiarid) reveals differences in dominant hydrologic processes and dynamic water storage behavior, with the semiarid catchment generally reacting slower to precipitation events and containing a lower fraction of preevent water in the immediate hydrologic response.

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Integrated response and transit time distributions of watersheds by combining hydrograph separation and long-term transit time modeling

Cited by 81 publications

References 35 publications

Reevaluation of transit time distributions, mean transit times and their relation to catchment topography

Reevaluation of transit time distributions, mean transit times and their relation to catchment topography

Time series of tritium, stable isotopes and chloride reveal short-term variations in groundwater contribution to a stream

The master transit time distribution of variable flow systems

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