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

M Hrachowitz,T A Bogaard,C Soulsby,D Tetzlaff,H Savenije

doi:10.5194/hess-17-533-2013

Abstract

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.

Highlights

The runoff generation process dynamics underlying observed stream flow responses are not yet well understood in most catchments (e.g. McDonnell et al, 2010; Beven, 2010)
To at least partially reconcile these different interpretations, we suggest a dynamic partial mixing mechanism with a dimensionless mixing coefficient complete mixing (CM),i that is controlled by the soil moisture content according to
Most of water entering the catchment leaves as runoff, in the model represented as overland flow (14 %) or preferential flow (68 %), while transpiration levels are rather low (15 %; Table 4)

Summary

Introduction

The runoff generation process dynamics underlying observed stream flow responses are not yet well understood in most catchments (e.g. McDonnell et al, 2010; Beven, 2010). The runoff generation process dynamics underlying observed stream flow responses are not yet well understood in most catchments McDonnell et al, 2010; Beven, 2010). While hydrologists often have good conceptual understanding of which processes are likely to be relevant McMillan et al, 2011; Fenicia et al, 2011), the spatio-temporal process heterogeneity in catchments generates considerable challenges to quantitative assessment (cf Savenije, 2009). Given the frequent absence of suitable data, the emphasis of many hydrological modeling studies on the stream flow response Fenicia et al, 2006; Clark et al, 2008; Seibert and Beven, 2009) rather than more integrated response measures, such as tracer data, is hampering efforts towards more fundamental understanding of catchment process. Hrachowitz et al.: What can flux tracking teach us about water age distribution patterns?

Objectives

Results

Conclusion