A generalized Damköhler number for classifying material processing in hydrological systems

Abstract

Abstract. Assessing the potential for transfer of pollutants and nutrients across catchments is of primary importance under changing land use and climate. Over the past decade the connectivity/disconnectivity dynamic of a catchment has been related to its potential to export material; however, we continue to use multiple definitions of connectivity, and most have focused strongly on physical (hydrological or hydraulic) connectivity. In contrast, this paper constantly focuses on the dynamic balance between transport and material transformation, and defines material connectivity as the effective transfer of material between elements of the hydrological cycle. The concept of exposure timescales is developed and used to define three distinct regimes: (i) which is hydrologically connected and transport is dominated by advection; (ii) which is hydrologically connected and transport is dominated by diffusion; and (iii) which is materially isolated. The ratio of exposure timescales to material processing timescales is presented as the non-dimensional number, N E , where N E is reaction-specific and allows estimation of relevant spatial scales over which the reactions of interest take place. Case studies within each regime provide examples of how N E can be used to characterise systems according to their sensitivity to shifts in hydrology and gain insight into the biogeochemical processes that are signficant under the specified conditions. Finally, we explore the implications of the N E framework for improved water management, and for our understanding of biodiversity, resilience and chemical competitiveness under specified conditions.

Riparian Corridors: A New Conceptual Framework for Assessing Nitrogen Buffering Across Biomes

“…Therefore, we are left with a paradox: multiscale and cross biome understanding is needed but comprehensive study of the different processes involved in riparian nitrogen cycling is only feasible at relatively small plot scales. Indeed, so far, the evaluation of the buffering capacity of riparian zones has focused on very detailed, small-scale hydrological and biogeochemical assessments, which revealed that removal capacity is intrinsically dependent on the ratio between the residence time of nitrate in the riparian zone and the denitrification rate (i.e., the Damköhler ratio; Sabater et al, 2003;Ocampo et al, 2006;Oldham et al, 2013;Pinay et al, 2015). Yet, simply examining the variability of a particular process (e.g., denitrification) at relatively small scales does not adequately quantify the potential of riparian corridors to buffer nitrogen inputs or supply nitrogen to stream food webs at catchment scale.…”

A paradigm shift in stormflow predictions for active tectonic regions with large-magnitude storms: generalisation of catchment observations by hydraulic sensitivity analysis and insight into soil-layer evolution

“…Approximations that neglect unsaturated flow have often been used for analysing water movement beneath the ground (Brutsaert, 2005), but the results from CB1 suggest that such an approximation should be rejected here because it is not fixed whether the saturated or the unsaturated flow has the larger effect on stormflow responses. The important role of hydrologic or hydraulic connectivity in catchment processes has already been discussed elsewhere (Michaelides and Chappell, 2009;Oldham et al, 2013), and HC, efficiently connecting the unsaturated and saturated flows, will be used as a key concept for the flow responses in this paper.…”

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

“…We propose that the comparison of travel time from catchments from differing biomes could lead to a more systematic understanding of catchment behaviour and general theory. Because biogeochemistry is tightly linked to residence time, a better understanding of the travel time distributions will improve the assessment of nutrient removal capacity (Pinay et al, 2015), climate change impacts on stream chemistry (Abbott et al, 2015;Goode, 1996;McGuire et al, 2005) and exposure time (Ginn, 1999;Frei et al, this issue;Oldham et al, 2013).…”

“…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 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.…”

“…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 …”