Hydrol. Earth Syst. Sci., 24, 849–867, 2020 https://doi.org/10.5194/hess-24-849-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions Michael Stoelzle1,*, Tobias Schuetz2, Markus Weiler1, Kerstin Stahl1, and Lena M. Tallaksen3 1Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany 2Department of Hydrology, Faculty VI Regional and Environmental Sciences, University of Trier, Trier, Germany 3Department of Geosciences, University of Oslo, Oslo, Norway *Invited contribution by Michael Stoelzle, recipient of the EGU Outstanding Student Poster Awards 2015. Correspondence: Michael Stoelzle ([email protected]) Received: 14 May 2019 – Discussion started: 28 May 2019 Revised: 18 November 2019 – Accepted: 20 January 2020 – Published: 25 February 2020 Abstract. Understanding components of the total streamflow the primary contribution, whereas below 800 m groundwa- is important to assess the ecological functioning of rivers. Bi- ter resources are most likely the major streamflow contri- nary or two-component separation of streamflow into a quick butions. Our analysis also indicates that dynamic storage in and a slow (often referred to as baseflow) component are of- high alpine catchments might be large and is overall not ten based on arbitrary choices of separation parameters and smaller than in lowland catchments. We conclude that the also merge different delayed components into one baseflow DFI can be used to assess the range of sources forming catch- component and one baseflow index (BFI). As streamflow ments’ storages and to judge the long-term sustainability of generation during dry weather often results from drainage streamflow. of multiple sources, we propose to extend the BFI by a delayed-flow index (DFI) considering the dynamics of mul- tiple delayed contributions to streamflow. The DFI is based on characteristic delay curves (CDCs) where the identifica- 1 Introduction tion of breakpoint (BP) estimates helps to avoid rather sub- jective separation parameters and allows for distinguishing During dry weather, sustained streamflow modulates aquatic four types of delayed streamflow contributions. The method- ecosystem functioning and is important for groundwater– ology is demonstrated using streamflow records from a set of surface-water interactions (Sophocleous, 2002), the variabil- 60 mesoscale catchments in Germany and Switzerland cov- ity of water temperature (Constantz, 1998) or the dilution of ering a pronounced elevation gradient of roughly 3000 m. contaminants (Schuetz et al., 2016). Estimates of the amount We found that the quickflow signal often diminishes earlier or timing of baseflow or of the baseflow index (BFI) quan- than assumed by two-component BFI analyses and distin- tify catchments’ freshwater availability during dry weather. guished a variety of additional flow contributions with de- The BFI is the proportion of baseflow to total streamflow, lays shorter than 60 d. For streamflow contributions with de- i.e. higher BFI values are interpreted as an indicator of more lays longer than 60 d, we show that the method can be used water being provided from stored sources (Tallaksen and to assess catchments’ water sustainability during dry spells. van Lanen, 2004). Total streamflow is composed of quick- Colwell’s predictability (PT), a measure of streamflow peri- and baseflow. Quickflow is the portion of total streamflow odicity and sustainability, was applied to attribute the identi- originating directly from precipitation input (also termed di- fied delay patterns to dynamic catchment storage. The small- rect runoff or stormflow). In contrast, baseflow has com- est dynamic storages were consistently found for catchments monly been considered “as the portion of flow that comes between approx. 800 and 1800 m a.s.l. Above an elevation from groundwater storage or other delayed sources” (Hall, of 1800 m the DFI suggests that seasonal snowpack provides 1968), i.e. water that has previously infiltrated into the soil and recharged to aquifers but can also originate from other Published by Copernicus Publications on behalf of the European Geosciences Union. 850 M. Stoelzle et al.: Beyond binary baseflow separation: a delayed-flow index sources of delayed flow (e.g. snowmelt). Dingman (2015) adapted to the typical rainfall regime in the UK) and would understands baseflow as water maintaining streamflow be- have to be recalibrated for other climates as demonstrated tween water input events. Different sources such as ground- e.g. for seasonal snow regimes by Tallaksen (1987) or for in- water, melt water from snow, glaciers or ice; water from termittent streams by Aksoy et al. (2008). Accordingly, other lakes, riverbanks, floodplains, wetlands or springs; or return studies have discussed the limitations of the BFI and two- flow from irrigation can contribute to the “baseflow” com- component baseflow separation due to e.g. arbitrary separa- ponent of streamflow (Smakhtin, 2001). Considering these tion parameters or the mixture of different delayed sources different potential sources requires consideration of the dif- into one baseflow component (Hellwig and Stahl, 2018; Kro- ferent delayed contributions that may maintain streamflow nholm and Capel, 2015; Parry et al., 2016a; Partington et al., during prolonged dry weather and are thus important to as- 2012). Meyer et al. (2011) applied different baseflow sepa- sess the vulnerability of aquatic ecosystems, e.g. due to cli- ration methods, i.e. the IH-UK, the Wittenberg and the De- matic change (e.g. Olden et al., 2011). Therefore, the various muth procedure (Wittenberg and Sivapalan, 1999; Demuth, contributions from different sources to the “baseflow” com- 1993; Demuth and Kulls, 1997), demonstrating that differ- ponent need to be better distinguished, in particular across ent procedures of quick- and baseflow separation lead to dif- different climates and streamflow regimes. ferent BFI values with a consistent ranking across the pro- The question is whether we can identify and quantify cedures (i.e. Demuth < IH-UK < Wittenberg). The authors different delayed contributions to streamflow. Tradition- found for rainfall-dominated catchments in Switzerland re- ally, conceptual methods use reservoir algorithms to repre- liable relationships between BFI and catchment character- sent multiple contributions to streamflow (Schwarze et al., istics such as groundwater availability or soil properties. 1989; Wittenberg, 2003). Stoelzle et al. (2015) have shown In general, BFI and mean catchment elevation were nega- that baseflow modelling can be improved by using infor- tively correlated (below 1500 m a.s.l.), but between 1500 and mation about the geology to select appropriate groundwa- 3000 m a.s.l. (i.e. snowmelt-dominated catchments) their re- ter model structures. However, instead of using parameter- sults indicated generally higher BFI values, an indication of ized box models with assumptions about their drainage be- additional delayed contributions, and a much weaker corre- haviour, the observed hydrograph can also be consulted di- lation between BFI and elevation, an indication of the impor- rectly. Hydrometric- or tracer-based hydrograph separation tance of specific catchment characteristics. allow for decomposing different streamflow contributions to To improve our understanding of different streamflow gain a quick- and baseflow component (Smakhtin, 2001). components, we propose to extend common binary base- Hydrograph-based separation has a long history, but it has flow separation (resulting in BFI) into a hydrograph sepa- been also criticized for ambiguous results compared to ap- ration considering multiple delayed contributions to stream- proaches based on chemical or isotopic tracers (Klaus and flow. The objectives of our study are: McDonnell, 2013). A general assumption is that the latter approaches are physically more meaningful and allow for as- 1. to develop a delayed-flow separation procedure with the sessing the water age, the mixing of the water (e.g. pre-event ability to quantify multiple delayed streamflow contri- and event water) and the sources of different water contribu- butions (i.e. the delayed-flow index; DFI) and tions. However, isotope or chemical data sets are often not 2. to evaluate the reliability and applicability of this proce- available or have limitations regarding the spatial extent, res- dure by linking delayed-flow contributions to catchment olution or the period of record. Furthermore, von Freyberg et characteristics and dynamic catchment storage. al. (2018) recommend developing hydrograph separation be- yond the traditional separation of event and pre-event water For this purpose, the DFI is tested for a set of catch- (i.e. quick- and baseflow) to eventually identify many differ- ments covering a pronounced elevation gradient acting as a ent sources of streamflow. proxy for different streamflow regimes, catchment character- In the past, two-component hydrograph separation such as istics and climate characteristics (e.g. rainfall- or snowmelt- recursive digital filtering (Lyne and Hollick, 1979; Nathan dominated catchments). Accordingly, we hypothesize that and McMahon, 1992) or separation based on progressively multiple delayed streamflow contributions with specific sig- identified streamflow minima in the IH-UK (Institute of Hy- nals (e.g. stormflow, snowmelt or groundwater contributions) drology, UK) baseflow separation method