Debates—The future of hydrological sciences: A (common) path forward? A call to action aimed at understanding velocities, celerities and residence time distributions of the headwater hydrograph

McDonnell, Jeffrey J.; Beven, Keith

doi:10.1002/2013wr015141

Cited by 381 publications

(424 citation statements)

References 73 publications

(74 reference statements)

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“…This paper focuses on steady-state solutions of RTD. While some of the limitations related to the steady-state assumption are discussed in section 5, a companion paper fully addresses the topic of transient RTDs which have received more attention in the recent years (Duffy, 2010;McDonnell and Beven, 2014;Rinaldo et al, 2015). The article is organized into three main sections, each of which is designed to be useful on its own.…”

Section: Steady-state Analytical Rtdsmentioning

confidence: 99%

Residence time distributions for hydrologic systems: Mechanistic foundations and steady-state analytical solutions

Leray

Engdahl

Massoudieh

et al. 2016

Journal of Hydrology

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Steady-state analytical RTDs contaminant transport, and ecosystem preservation. Analytical solutions are often adopted as a model of the RTD and a broad spectrum of models from many disciplines has been applied. Although these solutions are typically reduced in dimensionality and limited in complexity, their ease of use makes them preferred tools, specifically for the interpretation of tracer data. Our review begins with the mechanistic basis for the governing equations, highlighting the physics for generating a RTD, and a catalog of analytical solutions follows. This catalog explains the geometry, boundary conditions and physical aspects of the hydrologic systems, as well as the sampling conditions, that altogether give rise to specific RTDs. The similarities between models are noted, as are the appropriate conditions for their applicability. The presentation of simple solutions is followed by a presentation of more complicated analytical models for RTDs, including serial and parallel combinations, lagged systems, and non-Fickian models. The conditions for the appropriate use of analytical solutions are discussed, and we close with some thoughts on potential applications, alternative approaches, and future directions for modeling hydrologic residence time.

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Section: Steady-state Analytical Rtdsmentioning

confidence: 99%

Residence time distributions for hydrologic systems: Mechanistic foundations and steady-state analytical solutions

Leray

Engdahl

Massoudieh

et al. 2016

Journal of Hydrology

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“…In this way it is possible to estimate the average time travel and the consequent parameter k. However, such formulation is applied in a lumped way for a given sub-catchment. As reported in McDonnell and Beven (2014) more reliable and distributed models should be used to reproduce the spatial variability of the residence times within the catchment over the time. That is why, in the advanced version of the model implemented by AAWA, in each catchment (e.g.…”

Section: Hydrological Modellingmentioning

confidence: 99%

“…In fact, the variability of residence time is considered according to Rodríguez-Iturbe et al (1982) by assuming the surface velocity as a function of the effective rainfall intensity (Kumar et al, 2002). In addition, the correct estimation of the residence time should derived considering the latest findings reported in McDonnell and Beven (2014). In case of Q sub and Q g the value of k is calibrated comparing the observed and simulated discharge at Vicenza as previously described.…”

Section: Hydrological Modellingmentioning

confidence: 99%

Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrological and Hydraulic Models

Mazzoleni¹

2017

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“…The amount of time water remains in a catchment is one of the key parameters controlling biogeochemical functioning and can vary in small catchments from a few days to millennia (McDonnell and Beven, 2014;Moldan and Černỳ, 1994;Rodhe et al, 1996;Frisbee et al, 2013). As it is impractical to measure the whole travel time distribution using injected hydrological tracers (but see Rodhe et al, 1996), different approaches, such as lumped parameter models, particle-tracking, and direct age simulation, have been developed to estimate travel time …”

Section: Time Distribution Terms and Conceptsmentioning

confidence: 99%

“…The amount of time water remains in a catchment is one of the key parameters controlling biogeochemical functioning and can vary in small catchments from a few days to millennia (McDonnell and Beven, 2014;Moldan and Černỳ, 1994;Rodhe et al, 1996;Frisbee et al, 2013). The mean transit time, or the average amount of time a water molecule stays within the watershed boundaries, is an integrated measure of catchment residence time (e.g.…”

Section: Time Distribution Terms and Conceptsmentioning

confidence: 99%

Constitution of a catchment virtual observatory for sharing flow and transport models outputs

Thomas

Rousseau-Gueutin

Kolbe

et al. 2016

Journal of Hydrology

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Accepted ManuscriptConstitution of a catchment virtual observatory for sharing flow and transport models outputs Zahra Thomas, Pauline Rousseau-Gueutin, Tamara Kolbe, Benjamin W. Abbott, Jean Marçais, Stefan Peiffer, Sven Frei, Kevin Bishop, Pascal Pichelin, Gilles Pinay, Jean-Raynald de Dreuzy PII:S0022-1694(16)30260-8 DOI:http://dx.doi.org/10.1016/j.jhydrol.2016.04.067 Reference:HYDROL 21237To appear in: Journal of HydrologyPlease cite this article as: Thomas, Z., Rousseau-Gueutin, P., Kolbe, T., Abbott, B.W., Marçais, J., Peiffer, S., Frei, S., Bishop, K., Pichelin, P., Pinay, G., de Dreuzy, J-R., Constitution of a catchment virtual observatory for sharing flow and transport models outputs, Journal of Hydrology (2016), doi: http://dx.doi.org/10.1016/j.jhydrol. 2016.04.067This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. The mean transit time and whole stream residence time distribution are powerful metrics of catchment functioning, providing synoptic hydrological information such as water renewal time, heterogeneity of flowpaths, and overall water volume (Godsey et al., 2010;Hrachowitz et al., 2010; Marçais et al., 2015;McGuire and McDonnell, 2006;Van der Velde et al., 2012) . These hydrological parameters influence catchment biogeochemistry (Ocampo et al., 2006;Oldham et al., 2013;Pinay et al., 2015;Tetzlaff et al., 2007), further increasing their value as Constitution of a catchment virtual observatory for sharing flow and transport modelsObservatory for sharing models outputs Thomas et al. 4 indicators and predictors of catchment-scale water quality and chemistry. Because these parameters are of great general interest they feature prominently in the inputs and outputs of many models (e.g. McGuire et al., 2005;Tetzlaff et al., 2009a (Bishop et al., 2008). Small catchments express a wide diversity of subsurface flow configurations (Eberts et al., 2012;Gburek and Folmar, 1999;Sophocleous, 2002;Winter, 1999) depending on geological and topographical structures, distribution and timing of recharge, characteristics of the vadose zone, and free surface dynamics of the underlying aquifer (Bresciani et al., 2014;Schumann et al., 2010;Freer et al., 2002;Montgomery and Dietrich, 1989;O'loughlin, 1981;Šimŭnek et al., 2003;Voeckler et al., 2014; Dages et al., 2009; de Vries and Simmers, 2002;Scanlon et al., 2002).Observatory for sharing models outputs Thomas et al. 6 Perhaps most importantly in regards to catchment hydrology, small catchments are a convenient and powerful experimental unit. Compared to large catchments, there are fewer processes influencing behaviour of small catchments and collecti...

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Debates—The future of hydrological sciences: A (common) path forward? A call to action aimed at understanding velocities, celerities and residence time distributions of the headwater hydrograph

Abstract: Key Points Celerity is faster than velocity Watershed models are evaluated only against celerity Velocity must be addressed in future watershed models

Cited by 381 publications

References 73 publications

Residence time distributions for hydrologic systems: Mechanistic foundations and steady-state analytical solutions

Residence time distributions for hydrologic systems: Mechanistic foundations and steady-state analytical solutions

Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrological and Hydraulic Models

Constitution of a catchment virtual observatory for sharing flow and transport models outputs

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