Modelling the chloride signal at Plynlimon, Wales, using a modified dynamic TOPMODEL incorporating conservative chemical mixing (with uncertainty)

Page, Trevor; Beven, Keith; Freer, Jim; Neal, Colin

doi:10.1002/hyp.6186

Cited by 96 publications

(74 citation statements)

References 49 publications

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“…Neal et al, 1988), stream water Cl − flux typically exceeds the precipitation Cl − flux. This apparent disequilibrium was previously shown to be caused by occult and dry deposition Page et al, 2007), previous land use change, such as deforestation (Oda et al, 2009;Guan et al, 2010) or biochemical cycling (Bastviken et al, 2007). Further, plants require Cl − and thus take up Cl − stored in the root zone at varying rates (e.g.…”

Section: Hydrological and Geochemical Datamentioning

confidence: 99%

“…Uhlenbrook and Sieber, 2005;Vaché and McDonnell, 2006;Iorgulescu et al, 2007;McGuire et al, 2007;Page et al, 2007;Fenicia et al, 2010;Lindström et al, 2010;Lyon et al, 2010b;Birkel et al, 2011a,c;Arheimer et al, 2012;Capell et al, 2012b;Bertuzzo et al, 2013). For example, Dunn et al (2007Dunn et al ( , 2010) used a conceptual model in the context of virtual experiments (cf.…”

Section: Hrachowitz Et Al: What Can Flux Tracking Teach Us About mentioning

confidence: 99%

“…Vogel et al, 2008;Stumpp and Maloszewski, 2010), partial mixing is rarely considered in conceptual modeling studies (e.g. Page et al, 2007;Van der Velde et al, 2012). Here, partial mixing is conceptualized as instantaneous, partial mixing between S a and S p (cf.…”

Section: Hrachowitz Et Al: What Can Flux Tracking Teach Us About mentioning

confidence: 99%

“…Lovett et al, 2005), it was in the cool Scottish climate, also in the absence of suitable data warranting the inclusion of this process, considered negligible as individual process in the models (cf. Kirchner et al, 2000;Page et al, 2007;Shaw et al, 2008) due to low transpiration rates (and thus limited sap flow) and limited organic matter turnover in the Heather moorland vegetation and the coniferous forests of the study catchments (cf. Liu et al, 2004).…”

Section: Dynamic Partial Mixingmentioning

confidence: 99%

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What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

Hrachowitz

Savenije

Bogaard

et al. 2013

Hydrol. Earth Syst. Sci.

270

443

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Abstract. The complex interactions of runoff generation processes underlying the hydrological response of streams remain not entirely understood at the catchment scale. Extensive research has demonstrated the utility of tracers for both inferring flow path distributions and constraining model parameterizations. While useful, the common use of linearity assumptions, i.e. time invariance and complete mixing, in these studies provides only partial understanding of actual process dynamics. Here we use long-term (< 20 yr) precipitation, flow and tracer (chloride) data of three contrasting upland catchments in the Scottish Highlands to inform integrated conceptual models investigating different mixing assumptions. Using the models as diagnostic tools in a functional comparison, water and tracer fluxes were then tracked with the objective of exploring the differences between different water age distributions, such as flux and resident water age distributions, and characterizing the contrasting water age pattern of the dominant hydrological processes in the three study catchments to establish an improved understanding of the wetness-dependent temporal dynamics of these distributions.The results highlight the potential importance of partial mixing processes which can be dependent on the hydrological functioning of a catchment. Further, tracking tracer fluxes showed that the various components of a model can be characterized by fundamentally different water age distributions which may be highly sensitive to catchment wetness history, available storage, mixing mechanisms, flow path connectivity and the relative importance of the different hydrological processes involved. Flux tracking also revealed that, although negligible for simulating the runoff response, the omission of processes such as interception evaporation can result in considerably biased water age distributions. Finally, the modeling indicated that water age distributions in the three study catchments do have long, power-law tails, which are generated by the interplay of flow path connectivity, the relative importance of different flow paths as well as by the mixing mechanisms involved. In general this study highlights the potential of customized integrated conceptual models, based on multiple mixing assumptions, to infer system internal transport dynamics and their sensitivity to catchment wetness states.

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Section: Hydrological and Geochemical Datamentioning

confidence: 99%

Section: Hrachowitz Et Al: What Can Flux Tracking Teach Us About mentioning

confidence: 99%

Section: Hrachowitz Et Al: What Can Flux Tracking Teach Us About mentioning

confidence: 99%

Section: Dynamic Partial Mixingmentioning

confidence: 99%

See 2 more Smart Citations

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

Hrachowitz

Savenije

Bogaard

et al. 2013

Hydrol. Earth Syst. Sci.

270

443

View full text Add to dashboard Cite

show abstract

“…Since chlorides are known to be nonreactive, the apparent imbalance between input and output is to be first addressed. This is a classical problem when dealing with chlorides [Neal et al, 1988] and can be caused by a set of different reasons such as dry and occult deposition [McMillan et al, 2012;Page et al, 2007], presence of forested areas [Guan et al, 2010;Oda et al, 2009] or BENETTIN ET AL. : CHLORIDES CATCHMENT TRANSPORT evapoconcentration during dry seasons.…”

Section: Case Study: the Hupsel Brook Catchmentmentioning

confidence: 99%

Chloride circulation in a lowland catchment and the formulation of transport by travel time distributions

Benettin

Velde

Zee

et al. 2013

Water Resources Research

118

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[1] Travel times are fundamental catchment descriptors that blend key information about storage, geochemistry, flow pathways and sources of water into a coherent mathematical framework. Here we analyze travel time distributions (TTDs) (and related attributes) estimated on the basis of the extensive hydrochemical information available for the Hupsel Brook lowland catchment in the Netherlands. The relevance of the work is perceived to lie in the general importance of characterizing nonstationary TTDs to capture catchment transport properties, here chloride flux concentrations at the basin outlet. The relative roles of evapotranspiration, water storage dynamics, hydrologic pathways and mass sources/sinks are discussed. Different hydrochemical models are tested and ranked, providing compelling examples of the improved process understanding achieved through coupled calibration of flow and transport processes. The ability of the model to reproduce measured flux concentrations is shown to lie mostly in the description of nonstationarities of TTDs at multiple time scales, including short-term fluctuations induced by soil moisture dynamics in the root zone and long-term seasonal dynamics. Our results prove reliable and suggest, for instance, that drastically reducing fertilization loads for one or more years would not result in significant permanent decreases in average solute concentrations in the Hupsel runoff because of the long memory shown by the system. Through comparison of field and theoretical evidence, our results highlight, unambiguously, the basic transport mechanisms operating in the catchment at hand, with a view to general applications.

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Developing a consistent process‐based conceptualization of catchment functioning using measurements of internal state variables

Birkel

Soulsby

Tetzlaff

2014

Water Resources Research

109

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We use isotope data in addition to discharge and groundwater level data to conceptualize the internal processes of runoff generation and tracer transport in a low parameter coupled flow-tracer model that could predict the runoff response and isotopic composition of an upland stream. We used sensitivity analysis to assess the effect of these data on model calibration in terms of parameter identifiability and the model's ability to predict the stream's runoff response, isotopic composition and water age. The results showed that the incorporation of tracer data in particular, clearly increased parameter identifiability and improved the predictive power of models for simulating both streamflow and isotopes. This also resulted in a more consistent process-based conceptualization of catchment functioning. We could also show that using models as learning tools can guide sampling campaigns toward measurements with increased information content for further modeling. We conclude that this is a promising approach for assessing dominant processes in coupled flow-tracer models. This is of value when such models are being used to test hypotheses about the hydrological functioning of catchments, particularly in relation to pollutant transfers.

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Modelling the chloride signal at Plynlimon, Wales, using a modified dynamic TOPMODEL incorporating conservative chemical mixing (with uncertainty)

Cited by 96 publications

References 49 publications

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

Chloride circulation in a lowland catchment and the formulation of transport by travel time distributions

Developing a consistent process‐based conceptualization of catchment functioning using measurements of internal state variables

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