RESEARCH ARTICLE
Isotope hydrology and water sources in a heavily urbanized
stream
Christian Marx
1,2
| Dörthe Tetzlaff
2,3,4
| Reinhard Hinkelmann
1
|
Chris Soulsby
1,2,4
1
Chair of Water Resources Management and
Modeling of Hydrosystems, Technische
Universität Berlin, Berlin, Germany
2
Leibniz Institute of Freshwater Ecology and
Inland Fisheries, Berlin, Germany
3
Department of Geography, Humboldt-
Universität zu Berlin, Berlin, Germany
4
Northern Rivers Institute, University of
Aberdeen, St. Mary's Building, Kings College,
Old Aberdeen, Scotland, UK
Correspondence
Christian Marx, Chair of Water Resources
Management and Modeling of Hydrosystems,
Technische Universität Berlin, Gustav-Meyer-
Allee 25, 13355 Berlin, Germany.
Email: [email protected]
Funding information
Deutsche Forschungsgemeinschaft, Grant/
Award Number: Urban Water Interfaces (GRK
2032/2); Einstein Stiftung Berlin, Grant/Award
Number: EVF-2018-425; Leverhulme Trust,
Grant/Award Number: ISOLAND (RPG-
2018-425)
Abstract
Complex networks of both natural and engineered flow paths control the hydrology
of streams in major cities through spatio-temporal variations in connection and dis-
connection of diverse water sources. We used spatially extensive and temporally
intensive sampling of water stable isotopes to disentangle the hydrological sources
of the heavily urbanized Panke catchment (220 km
2
) in the north of Berlin,
Germany. The isotopic data enabled us to partition stream water sources across the
catchment using a Bayesian mixing analysis. The upper part of the catchment
streamflow is dominated by groundwater (75%) from gravel aquifers. In dry summer
periods, streamflow becomes intermittent in the upper catchment, possibly as a
result of local groundwater abstractions. Storm drainage dominates the responses to
precipitation events. Although such events can dramatically change the isotopic com-
position of the upper stream network, storm drainage only accounts for 10%–15% of
annual streamflow. Moving downstream, subtle changes in sources and isotope sig-
natures occur as catchment characteristics vary and the stream is affected by differ-
ent tributaries. However, effluents from a wastewater treatment plant (WWTP),
serving 700,000 people, dominate stream flow in the lower catchment (90% of
annual runoff) where urbanization effects are more dramatic. The associated increase
in sealed surfaces downstream also reduces the relative contribution of groundwater
to streamflow. The volume and isotopic composition of storm runoff is again domi-
nated by urban drainage, though in the lower catchment, still only about 10% of
annual runoff comes from storm drains. The study shows the potential of stable
water isotopes as inexpensive tracers in urban catchments that can provide a more
integrated understanding of the complex hydrology of major cities. This offers an
important evidence base for guiding the plans to develop and re-develop urban
catchments to protect, restore, and enhance their ecological and amenity value.
KEYWORDS
ecohydrology, end member mixing analysis, isotopes, urban hydrology, wastewater
Received: 26 April 2021 Revised: 6 September 2021 Accepted: 6 September 2021
DOI: 10.1002/hyp.14377
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2021 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.
Hydrological Processes. 2021;35:e14377. wileyonlinelibrary.com/journal/hyp 1of20
https://doi.org/10.1002/hyp.14377
1|INTRODUCTION
With over 50% of the world's and 70% of Europe's population now
living in cities, many key global challenges revolve about the sustain-
able management of urban water (United Nations, 2019). This is likely
to lead to different priorities for urban water management, with vari-
ous stakeholders, such as water supply and sewage disposal agencies,
industrial users and local citizens having competing demands that local
governance agencies have to mediate to maintain the quantity and
quality of urban water bodies (Brears, 2016). However, quantitative
understanding of the complex water sources and flow paths that sus-
tain urban water bodies is often lacking compared to other environ-
ments. Urban streams and other water bodies are variously used as
sources of water supply and a means of drainage and disposal of efflu-
ents (Gücker et al., 2006; House et al., 1993; Paul & Meyer, 2001); as
well as being perceived as a potential hazard in terms of flood risk and
pollution from effluents (Kundzewicz et al., 2014). Consequently,
urban water systems are usually heavily managed with a range of
complex infrastructure to control abstractions, stormwater drainage
and effluent disposal. Further, in older cities, urban water has often
been subject to an evolutionary history over centuries of ever-
changing management decisions as societal needs and priorities have
varied (Hassan, 2011; Winiwarter et al., 2016).
The inevitable decrease in catchment permeability –as built-up
areas expand –leads to higher surface runoff in urban streams, mostly
routed via stormwater drains and combined sewers, therefore reduc-
ing net-infiltration, and, thus, groundwater recharge (Arnold &
Gibbons, 1996), mobilizing pollutants on roads and other urban sur-
faces (Brinkmann, 1985). This often increases connectivity with
untreated wastewater in combined sewers that leads to episodic pol-
lution from organic waste and pharmaceuticals (Klein et al., 2015;
Komínková et al., 2016; Launay et al., 2016). However, the exact
sources of pollutants, from either combined sewers or wastewater
treatment plants (WWTPs) can be difficult to identify (Lee
et al., 2010). In addition, urban infrastructure also includes other less
obvious zones of subsurface connectivity via trenches carrying utility
cables and pipelines, giving analogies to natural dual-flow hydrological
systems and use of the term “urban karst”(Bonneau et al., 2017).
Urban catchments can thus be conceptualized as a complex “spider's
web”of highly connected water sources, combined with more discon-
nected areas in often extensive areas of urban green space
(e.g., parks, gardens, urban forests, urban wetlands, etc.). Understand-
ing the integrated interaction between different components of the
engineered system and natural flow paths in urban green spaces is
thus fundamental to understanding urban hydrology in an holistic way
(Gessner et al., 2014).
Improving hydrological process understanding in urban areas
requires integrating tools that provide insight into both large- and
small-scale spatio-temporal variability in catchment function. In this
regard, stable isotopes offer outstanding potential as natural tracers in
urban hydrology (Ehleringer et al., 2016). The use of stable isotopes
ratios of
2
H/
1
H and
18
O/
16
O within the water molecule has been
applied in many investigations to trace precipitation through different
types of hydrological systems and at different scales to understand
flow paths and the mixing dynamics of precipitation with water
already stored in the catchment (Birkel et al., 2011; Soulsby
et al., 2011; Soulsby et al., 2015a). Although urban studies are notably
underrepresented in the isotope hydrology literature, this is rapidly
changing. Recent studies have used isotopes to assess how urbaniza-
tion affects the age distribution and travel times of runoff (Dimitrova-
Petrova et al., 2019; Grande et al., 2020; Morales & Oswald, 2020;
Soulsby et al., 2014; Soulsby et al., 2015b) and the dynamic influence
of different water sources on the urban hydrograph (Jefferson
et al., 2015; Pellerin et al., 2008). Additionally, Jefferson et al. (2015)
used stable isotopes to investigate stormwater control measures and
to assess their effects on event contributions.
The composition of tracers in streams and potential source waters
can be used to separate the hydrograph into relative contributions
from different sources with contrasting tracer characteristics
(e.g., recent rainfall, groundwater and others). This was formalized in
end member mixing analysis (EMMA) (Christophersen &
Hooper, 1992) which, alongside other means of hydrograph separa-
tion, have proved valuable tools in isotope hydrology that have been
widely used (He et al., 2020; Klaus & McDonnell, 2013). Preliminary
studies have shown potential for source apportionment in urban
areas: with tracers variously being used to disentangle tap water
sources on a national scale (Bowen et al., 2007; West et al., 2014), or
locally within a state or city (Jameel et al., 2016; Sánchez-Murillo
et al., 2020; Tipple et al., 2017), providing a viable method for water-
works to understand their distribution system (Jameel et al., 2016).
Furthermore, Houhou et al. (2010) and Kracht (2007) used distinct
stable isotope signatures to identify sources within wastewater
sewers, while Grimmeisen et al. (2017) used isotopes to understand
groundwater contamination due to leaking sewers. Still, how the
wider urban hydrological cycle is affected by integration of natural
runoff sources, urban drainage and treated effluents is rarely investi-
gated quantitatively through tracers (Follstad Shah et al., 2019;
Kuhlemann et al., 2021b; Torres-Martínez et al., 2020).
Similarly, estimating metrics of water ages, such as mean transit
times (MTTs), has proven insightful in isotope hydrology as a tool for
assessing flow paths and mixing interactions in catchments. This is
based on using the damping and lagging of the precipitation isotope
time series in the rainfall-runoff transformation with lumped convolu-
tion integral models (McGuire & McDonnell, 2006; Tetzlaff
et al., 2018), ensemble hydrograph separation (Kirchner, 2019) or
more sophisticated tracer-aided hydrological models that track water
and solute fluxes and their associated ages (Birkel & Soulsby, 2015;
Douinot et al., 2019; Kuppel et al., 2018). Urban streams can integrate
very young waters (<1 day old) as rainfall is routed via storm drains in
rainfall events (Soulsby et al., 2015b), together with much older water
(>decades) that recharges groundwater through urban green spaces
(Gillefalk et al., 2021; Kuhlemann et al., ; Nouri et al., 2019). However,
in urban areas where significant volumes of effluents are introduced
into streams, there are conceptual difficulties in defining water ages,
especially if wastewaters are derived from local sources and have sim-
ilar isotopic signatures (Kuhlemann et al., 2021b). In such cases,
2of20 MARX ET AL.
assessing the influence of recent rainfall in streamflow is possible by
estimating the contribution of the young water fraction (YWF) to run-
off (Kirchner, 2016a, 2016b). This is a simple method for quantifying
the quick flow response of catchments based on the YWF, which is
the contribution of water less than 2 months old to the stream
hydrograph. The method provides only a relatively coarse metric of
complex age distributions, though it gives insight into the dynamics of
catchment runoff responses and provides an index for inter-
comparison studies (von Freyberg et al., 2018).
The motivation for this study is to apply isotopic methods in a
complex, heavily urbanized catchment to understand the spatio-
temporal dynamics of water sources contributing to streamflow. For
this, we focus on the Panke catchment in Berlin, the capital city of
Germany. The catchment has a long and ongoing history of urban
development and a highly engineered water management system.
However, the way in which this interacts with undeveloped areas in
the catchment is poorly understood. Also, although the catchment is
well-monitored hydrometrically and most effluent discharges are
known, complex groundwater-surface water interactions affect the
catchment water balance in a spatially variable way. Thus, tracers
offer a means to disentangle effects of natural discharge, storm
sewers and effluents. To do this, we collected daily precipitation and
stream samples over 15 months, in conjunction with seasonal, spa-
tially distributed synoptic sample surveys. This provided the data to
achieve the following specific aims:
1. To characterize the short-term hydrological dynamics of outflow
from the Panke catchment and its isotopic composition in relation
to time-variant sources of streamflow.
2. To characterize the spatial and temporal variation in the isotopic
composition of the stream network in relation to changes in the
dominant sources of streamflow.
Our results also highlight more general insights into the opportu-
nities and challenges for using isotopes in urban hydrological studies.
2|STUDY SITE
The Panke catchment (220 km
2
; Figure 1) is located in the State of
Brandenburg and Berlin in northeast Germany and forms the domi-
nant surface water drainage of the northern part of the city of Berlin
(Figure 1a,b). Much of the catchment is urban (Table 1). The Panke
drains a fairly flat area that naturally ranges from 35 to 90 m a.s.l. with
an average slope of 1.8%. Climatic conditions reflect both maritime
and continental influences: the average annual precipitation is
590 mm and the mean annual temperature is 9.5C (1981–2010)
(DWD & (Deutscher Wetterdienst), 2020). Rainfall is fairly evenly dis-
tributed between winter and summer, though the winter is dominated
by longer low-intensity frontal rain, whilst summer experiences more
high intensity, convectional storms. The region is drought-sensitive
and in 2018, Berlin only received 420 mm of rainfall. During 2019
and 2020, annual precipitation was 589 mm and 513 mm, respectively
(DWD, 2021).
The Panke is an effluent-impacted tributary of the River Spree,
which flows into the River Havel downstream of Berlin (Kuhlemann
et al., 2020). The river morphology class according to the German
Water Framework Directive is between 5 and 7 (where 1 is least
impacted and 7 is most heavily impacted) (Senate Department for
Urban Development and the Environment, 2012). The Panke origi-
nates in the North and flows 30 km in a south-westerly direction to
the Spree. The catchment's headwaters are located on the northern
edge of the Warsaw-Berlin glacial spillway which drained from Poland
to the River Elbe (Figure 1c). The geology consists of >100 m of Qua-
ternary deposits (Limberg & Thierbach, 2002). These form a series of
aquifers in Berlin and the surrounding area; the aquifer terminology
used is the same as Limberg and Thierbach (2002). For the Panke
catchment, two main geological units form the shallow aquifer (AQ1)
(Figure 1c). AQ1.1 is the sub-aquifer in the Barnim plateau (in the
East) which is partially confined by an overlying ground moraine. The
shallow “Panke aquifer”(AQ1.2), dominates the main river valley and
is unconfined and characterized by sands and gravels above an
aquitard of glacial till. The main aquifer beneath Berlin is AQ2, which
is confined below the aquitard in the Panke (Limberg et al., 2007). The
general direction of groundwater flow is south-west along the slope
of the Barnim plateau, the main recharge area. Once the main glacial
valley is reached, the groundwater flow is oriented to the South
(Senate Department for Urban Development and Housing, 2019a).
Berlin and Brandenburg's aquifers have been investigated using long-
residence time tracers such as tritium and helium, showing decadal to
centuries old water dominating the upper storage of unconfined aqui-
fers, whilst deeper waters could be millennial (Bednorz & Brose, 2017;
Massmann et al., 2009).
The North of the catchment has around 30% urban cover
(Table 1) but is unaffected by large effluent discharges (Figure 1d).
Typical for such lowland areas in northern Germany, streamflow gen-
eration is primarily groundwater dominated (Smith et al., 2021) with
seasonally varying inflows from headwater tributaries with non-urban
(forested and agricultural) land use. During our investigation, the
stream was observed to emerge from a managed urban-wetland and
lake. Despite this, flows can be intermittent in the upper reaches of
the stream network during the summer which might reflect seasonal
variation in storage and effects of local groundwater abstractions for
garden irrigation (Jasechko et al., 2021; Kleine et al., 2021). In this
area, there is one waterworks with three main well galleries taking
groundwater from the deeper confined AQ2 aquifer. It assumed by
local government that this does not affect flows in the headwaters
due to the confining layer (Figure 1d).
Within the lower catchment, the more densely urbanized area is
characterized by increasing densities of roads and stormwater drains
that discharge during rainfall events (Figure 1d, Table 1). Around
26.5 km
2
of the Panke catchment is connected to Berlin's rainwater
drainage system; this includes 13.6 km
2
of sealed surface (Senate
Department for Urban Development and Housing, 2018). The
MARX ET AL.3of20
stormwater overflows (SWOs) result in estimated 3.1 Million m
3
/y
rainwater discharge as direct runoff into the Panke (Senate Depart-
ment for Urban Development and Housing, 2019b). Some of the
built-up areas (17.8%) are drained by combined sewer systems, with
the remainder mostly having standard separations between wastewa-
ter and stormwater (Senate Department for Urban Development and
Housing, 2018). In the South of the Panke, combined stormwater
overflows dominates the drainage infrastructure (Möller &
Burgschweiger, 2008). Sewer runoff is partially influenced by reverse
gradients which are controlled by a discharge threshold and only acti-
vate in larger storms. Mixed, untreated wastewater with storm runoff
can also be discharged into the Panke from a pumping station close to
the WWTP (Figure 1d).
In the downstream half of the Panke, the stream is increasingly
regulated, and flow control structures can divert water into and out of
the catchment (Figure 1). WWTP effluents can be either discharged
FIGURE 1 Overview of site locations. (a) and (b) show the location in Germany and related to Berlin, respectively (c) Geology map
(LBGR, 2020) showing groundwater (GW) monitoring wells related to aquifers (AQ); (d) Land use map of the Panke catchment (modified
Basemaps: (Landesvermessung und Geobasisinformation Brandenburg (LGB), 2020; Umweltatlas Berlin/ALKIS, 2020); stream sampling locations
of the regular stream isotopic surveys upstream the wastewater treatment plant (WWTP) (UP1, UP2, UP3), downstream the WWTP (DS), and
discharge gauges. WWTP is wastewater treatment plant
4of20 MARX ET AL.
directly into the Panke, or transported out of the catchment via the
Nordgraben. The WWTP serves a population of 700,000 with a dry
weather discharge capacity of 105,000 m
3
/d (Möller &
Burgschweiger, 2008). About 86,400 m
3
/d (mean 1 m
3
/s, from
0.83 m
3
/s up to a maximum of 2.7 m
3
/s (Kade, 2020)) of the treated
wastewater are directly discharged into the Panke. The rest is drained
into the Nordgraben and is usually transferred to the neighbouring
Tegeler catchment (Figure 1), where other waterworks for drinking
water treatment are supplied by river bank filtration. A proportion of
peak flows can also be diverted out of the catchment via the Nor-
dgraben to reduce flood risk. The adjustable weirs that regulate flows
are not automated but are manually controlled, most notably in
advance of heavy rainfall events, depending on the forecast of a flood
risk model (Kade, 2020). Other weir operations were observed during
the study period to alter the input of treated effluents to enhance
base flows in the Panke. A small proportion of treated effluents are
also discharged for maintaining a former sewage-irrigation farm which
is now a wetland and forested area on the north-west side of the
catchment, which is drained by forested stream just upstream of the
WWTP (Figure 1a) (INKA BB, 2014; Kade, 2020; Lischeid et al., 2015).
The Panke stream is morphologically altered along its length,
though in some places limited restoration has been proposed and
undertaken (Lange et al., 2015; Wasser- und Bodenverband
“Finowfließ”, 2011). The last three kilometres of stream length are
heavily canalized, with steel piling and almost no visible bed sediment
due to walling of the channel boundary (Senate Department for the
Environment, Transport and Climate Protection (SenUVK), 2019). The
latter might limit groundwater–surface water exchange processes as
described in (Lewandowski et al., 2019).
3|DATA AND METHODS
The locations and frequency of sampling as well as the sources of
external data are summarized in Table S1. The German Weather Ser-
vice (DWD) climate station (at Buch) in the catchment was used for
precipitation and temperature data (Figure 1). Daily precipitation
samples for isotope analyses were collected at the Urban Eco-
hydrological Observatory at Steglitz 10 km south of the catchment
where continuous precipitation isotope samples have been collected
since the beginning of 2019 (Kuhlemann et al., ). Samples collected
from Buch in summer 2020 were very similar to those from Steglitz
which we use here for the longer time series. Samples were protected
against evaporation with a 3 mm Paraffin layer (IAEA/GNIP, 2014).
Stream discharge and water level data for sites on the Panke
(Figure 1d) were provided by the Senate Department for the Environ-
ment,Transport and Climate Protection (Senate Department for the
Environment, Transport and Climate Protection (SenUVK), 2021b) in
15 min intervals (Senate Department for the Environment, Transport
and Climate Protection (SenUVK), 2021a). Daily WWTP volumes
draining into either the Nordgraben or Panke were provided by the
Berlin Water Works (Berliner Wasserbetriebe, BWB) and their subcon-
tractor (Umweltvorhaben-Berlin Brandenburg, U-BB) (BWB, 2021;
Kade, 2020). Daily stable isotope samples were collected from the
catchment outlet (OL) near the most downstream gauging station
(Figure 1d). Gaps occurred at the end of December 2019 and due to a
reduced sampling frequency (2–3 times weekly) during COVID19
lockdown (Mid of March –End of April 2020).
At six locations along the Panke (Figure 1d), grab samples of
stream water for stable isotope analysis were taken from October
2019 to December 2020. Initially samples were collected monthly
(January–April 2020) and thereafter every two weeks. Three sites
(UP1, UP2, UP3) were upstream of the WWTP inflow, one was sam-
pled from the WWTP outflow, just upstream of its confluence with
the Panke (WWTP), one site was downstream (DS) of the WWTP
inflow and one at the catchment outlet (OL) (Figure 1d). At all loca-
tions, the fortnightly sampling captured a diverse range of hydro-
climatic conditions and discharge levels. In addition, four seasonal
synoptic surveys (October and December 2019, April and July 2020)
were undertaken along the Panke, including its major tributaries,
encompassing 30 grab sampling locations, to investigate the isotopic
transformation and seasonality within the stream and their tributaries.
Groundwater was sampled for isotope analysis on a monthly basis
from January to October 2020 (except for COVID19 gaps in April)
TABLE 1 Aggregated land use for the Panke sub-catchments (as shown in Figure 1) for the individual sampling sites (upstream of the
wastewater treatment plant WWTP: UP1, UP2, UP3, downstream of the WWTP: DS and at the catchment outlet OL) (modified.
Landesvermessung und Geobasisinformation Brandenburg (LGB), 2020; Umweltatlas Berlin/ALKIS, 2020)
Sub-catchment area Urbanized
a
Road coverage
b
Forested and peatland Green-spaces
c
Agri-culture Diverse
d
Site km
2
km
2
%km
2
%km
2
%km
2
%km
2
%km
2
%
UP1 26.5 6.0 22.7 2.0 7.6 2.4 9.0 0.5 2.0 14.8 55.9 0.7 2.7
UP2 46.9 14.8 31.6 4.6 9.9 3.5 7.5 1.0 2.1 22.1 47.1 0.9 1.9
UP3 and DS 114.0 23.8 20.9 8.5 7.5 42.5 37.3 2.7 2.4 34.6 30.3 1.9 1.7
OL 216.3 53.5 24.7 20.3 9.4 49.2 22.8 15.0 6.9 74.8 34.6 3.5 1.6
Note: % is related to the upstream-subcatchment.
a
Housing (incl. private gardens), industry.
b
Incl. railroads, streets, roads, squares.
c
Incl. recreation areas, allotments and cemeteries.
d
Incl. mining, landfills and water bodies.
MARX ET AL.5of20
from seven wells across the Panke catchment capturing different shal-
low aquifer systems within AQ1 and AQ2 (Figure 1c). We purged the
wells through pumping for 30–90 min, to ensure that at least twice
the exchange volume was removed and water quality determinants
such as pH, electric conductivity, and oxygen concentration were
measured until they stabilized using a WTW Multi probe 3630.
All isotope samples were decanted and filtered (0.2 μm cellulose
acetate) into 1.5 mL vials in the field and refrigerated until laboratory
analysis. They were analysed for water stable isotopes (δ
18
O and δ
2
H)
by Cavity Ring-Down Spectroscopy with a L2130-I Isotopic Water
Analyser (precision: ±0.025 δ
18
O and ±0.1‰δ
2
H, (Picarro, Inc., Santa
Clara, USA, 2020)). Isotope values are described in delta-notation
using four standards and reference to Vienna Standard Mean Ocean
Water (VSMOW) from the International Atomic Energy Agency (IAEA)
for calibration. Data correction was performed by the “Chem Correct”
software from Picarro to identify potential organic contaminants
(Picarro, Inc., Santa Clara, USA, 2018).
For data processing and analyses, R (Version R version 4.0.3
“Bunny-Wunnies Freak Out”(2020-10-10)) was used. All isotope
samples were referenced to the deviation of the Local Meteorological
Water Line (LMWL) for Berlin (Kuhlemann et al., ) as line-conditioned
excess (lc-excess) as described by Landwehr and Coplen (2006):
LMWL :δ2H¼7:76 δ18Oþ5:66
lcexcess ¼δ2H7:76 δ18O5:66
To identify different streamflow sources, we applied the Bayesian
EMMA using MixSIAR (version 3.1.12) for the different stream sites
along the Panke. MixSIAR is an open-source Bayesian model for R,
using a Gibbs sampler, allowing the use of prior distributions. For cal-
culation, a Markov Chain Monte Carlo (MCMC) method was used for
estimation of probability density functions (Stock et al., 2018; Stock &
Semmens, 2016). For each site, one EMMA was applied with three
tracers (δ
2
H, δ
18
O as well as lc-excess) to characterize different poten-
tial streamflow components. Although the lc-excess is dependent on
both stable water isotopes, a particularly marked and useful negative
lc-excess signal was introduced by the WWTP as a source, while
groundwater generally only had positive or close to zero values, and
hence, could lc-excess acted as an additional tracer. Despite this, the
integration of the LMWL of precipitation in the lc-excess calculation
provides a separate signal of variation that can differentiate end
members.
We separated the data set for each site into seasonal data
(Winter: December–February; Spring: March–May; Summer: June–
August; Autumn: September–November, Northern Hemisphere) cate-
gories for the analysis. We assumed that open water fractionation
within the stream was negligible and that the tracers behaved conser-
vatively in the channel. For the outlet, the complete dataset (biweekly
and daily data) was used. The end member mixing analysis provides
two internal statistics to evaluate model performance. The Gelman-
Rubin-test should be <1.05 for calculating the chain, though a value
of <1.1 is still acceptable and close to 1 is needed for a convergent
model, but must be >1 to allow calculation (Gelman et al., 2014;
Stock & Semmens, 2016). The Geweke test is a two-sided z-test, high
z-scores give a basis for model rejection. Less than 5% of rejected
values for the model is considered as favourable (Stock et al., 2018;
Stock & Semmens, 2016) (details in Table S2).
In the mixing analysis, the stream was considered a potential mix
of groundwater, recent precipitation (routed by storm drains), waste-
water effluent (where present) and any streamwater inflow from
upstream. This means that the regularly sampled stream sites (UP1 to
3), and DS (except WWTP) were also used as end members in
MixSIAR for sites further downstream. For groundwater, AQ1.1
(Barnim aquifer) and AQ1.2 (Panke aquifer) were kept separate due to
the potential higher intra-annual variability of the unconfined AQ1.1.
The WWTP was only applied as a potential source for DS and
OL. Standard deviations for the different sources were calculated to
assess the variability of each source contribution for the given
endmember. EMMA provides a distribution of the source contribu-
tion, which we used as quantification of variability and uncertainty.
The higher the standard deviation is, the higher the variability of the
source contribution over time and the more uncertain is the result.
We also estimated the young water fraction (YWF) contribution
to stream flow at all sites to assess the influence of urban storm run-
off. YWF is a simple but useful measure to estimate the contribution
of water younger than around two months to streamflow
(Kirchner, 2016b). As the seasonal cycle of precipitation is damped
due to storage and mixing processes, it gives insights into overall
catchment function in terms of young water contributions to
streamflow (Kirchner, 2016b; von Freyberg et al., 2018). A robust esti-
mation was derived from the ratio between the sinusoidal regressions
of seasonal variations in precipitation and stream isotopes. The ratio
between the amplitude of the sinusoidal regressions of stream and
precipitation is the YWF. The calculation was performed via an itera-
tive re-weighted least squares (IRLS) R script which was used to mini-
mize the outliers. The script was that provided by von Freyberg
et al. (2018). We used a discharge weighting for the YWF from the OL
site. As goodness-of-fit measures between the regression and
observed stable isotopes we used the coefficient of determination
(R
2
), residual standard error (RSE) and the hypothesis significance test-
ing (p-value, (Fischer, 1925)).
4|RESULTS
4.1 |Rainfall-runoff characteristics of the Panke
catchment
Overall, the sampling period was characterized by relatively dry condi-
tions. After initial rainfall in October, the winter of 2019/20 exhibited
frequent, but low amounts (<5 mm) and intensities of daily rainfall
inputs, with February being the wettest month (Figure 2a). March and
April were then relatively dry, but early summer was characterized by
wetter conditions, particularly with some regular heavy convectional
rainstorms. Late summer was again dry, though late September saw
6of20 MARX ET AL.
the highest daily rainfall of the year with a relatively dry early winter
2020/21 following.
Flows in the upper catchment were measured at UP2 and were
unaffected by WWTP discharge, but showed the characteristic sea-
sonality of a groundwater-dominated stream with higher winter base-
flows (Figure 2b). However, the stream was responsive to storm
events even after prolonged dry antecedent baseflows conditions in
summer 2020. Between UP2 and UP3, a water level gauge (not
shown) followed the general dynamics of UP2, though comparison of
long-term flow data between the two sites suggest losing conditions
during summer (Zeilfelder, 2021, pers. communication). Flows from
the WWTP enter between the UP3 and DS sampling points
(Figure 2c) and flows at DS were strongly influenced by weir opera-
tions. The WWTP effluents also showed diurnal variations and other
changes which were still evident at the Panke outlet OL (Figure 2d).
While runoff peaks generated by urban storm drains in the lower
catchment were also evident in DS and OL (Figure 2c,d), a proportion
of runoff peaks were transferred out of the catchment between these
two points via weirs at the Nordgraben.
Flows at OL showed a flashy discharge response, typical of an
urban catchment, to all substantial precipitation events (Figure 2d).
Such abrupt, transient increases in flow were followed by rapid reces-
sions once rainfall stopped. Similarly abrupt, but more persistent
changes in discharge were related to the weir operations, causing
FIGURE 2 Time series of
(a) Precipitation amount and isotopes;
(b) Discharge in UP2 and δ
2
Hin
streamwater in UP1 and UP2;
(c) Discharge in DS and WWTP as well as
δ
2
H in streamwater in UP3, WWTP and
DS; (d) Discharge and δ
2
Hin
streamwater at OL; (e) Daily
groundwater levels with colours
respective and representative of the
aquifers in meter below ground level
(m b. g. l.) and δ
2
H in groundwater at the
4 AQs 1.1, 1.2, 2, 2.1. Precipitation and
stream isotopes are plotted at different
scales
MARX ET AL.7of20
increases and decreases in baseflows which could range from 0.3 to
1.4 m
3
/s. From higher flows in early October 2019 until the beginning
of February 2020, discharge generally decreased from baseflows of
1m
3
/s to 0.5 m
3
/s. After a wet February 2020, flows recovered
to 0.8–1m
3
/s and declined again during a very dry April. The dry
weather sub-daily flow variation during these conditions showed the
effect of diurnal changes in WWTP effluents. This was followed by a
step change in flows where the volume of wastewater effluent
flowing into the river was increased during the drier summer via weir
operations to enhance baseflows. Conversely, during wetter periods
in October 2019 and 2020 flows were diverted out of the catchment
into the Nordgraben to reduce flood risk.
In Figure 2e, daily groundwater levels are shown for selected
wells in the Panke catchment that were also sampled for isotopes. In
the partly confined AQ(1.1) aquifer, the water table is 4–5 m below
the ground surface, and around 2–3 m in the unconfined AQ(1.2).
Artesian conditions prevail in AQ(2) below the confining later. After
the dry periods of 2018 and 2019, groundwater levels increased by
around 0.1m until March 2020 for AQ(1.1), and by 0.25–1m in
AQ(1.2). Only small differences in the synchronicity of seasonal water
level variations were observed, though the AQ(2) aquifer responded
later to recharge. During the summer period after the dry April, water
levels fell until September, where they stabilized, except in AQ1.1,
which had lower levels by about 0.1 m compared to the year before
(Senate Department for Urban Development and Housing, 2010).
4.2 |Isotope dynamics in the Panke catchment
Stable isotopes in precipitation showed a high variability (SD =3.6
and 26.9‰for δ
18
O and δ
2
H, respectively, Table 2); as expected,
there was pronounced seasonality with samples enriched in heavy
isotopes during summer and depleted during winter months. How-
ever, day-to-day variability can be high in both seasons (Figure 2a).
Isotope sampling at UP1 was not always possible when the
stream had dried out completely; for example, the 26/08/2020 sam-
ple was the first possible sampling following a rain event after a pro-
longed dry period (Figure 2b). During this late August period, UP1 and
UP2 showed the most enriched isotope values of 57.0‰and
50.65‰for δ
2
H respectively, whilst winter values reached around
64.0‰for δ
2
H at both sites. The sample sites UP3, WWTP and DS
all showed broadly similar isotopic dynamics but UP3 was generally
more depleted, WWTP was more enriched. DS was usually between
both site signatures at high flows, but was more strongly influenced
by the WWTP (Figure 2c). Standard deviations for all sites are given in
Table 2. The WWTP introduced a variable isotope signal during
events probably from the mixed stormwater received in the WWTP
and discharged within hours or days.
The daily stream samples at the catchment outlet showed that
the seasonal variation of the inputs was greatly damped (SD =0.45
and 3.6‰for δ
18
O and δ
2
H, respectively, Table 2), but the rainfall sig-
nal was translated to the stream during storm events, with the effect
more pronounced in the larger events (Figure 2d). Consequently, sea-
sonal variations in rainfall were also evident in the stream, with more
enriched and depleted values in summer and winter, respectively.
Usually, the rainfall signal only remained apparent in the stream for a
day, but in the case of larger events, the effect could persist over sev-
eral following days.
Isotopic signatures in groundwater (Figure 2e) showed some sea-
sonal variability in AQ1.1 and AQ1.2, though this was very damped
(SDs of 0.46 and 3.93‰for AQ1.1 and 1.00 and 4.95‰for δ
18
O and
δ
2
H AQ1.2, respectively) compared to precipitation or stream signa-
tures. The isotopic composition of water in the deeper and confined
AQ2 showed even less change and was the most depleted. Thus, AQ1
TABLE 2 Summary of isotopic compositions of precipitation, the different stream sampling locations and groundwater aquifers
δ
18
Oδ
2
H lc-excess
nMax Median Min SD Max Median Min SD Median
[—]‰‰‰‰‰‰‰ ‰‰
Precipitation 138 0.29 7.67 17.31 3.60 12.19 52.59 131.33 26.90 0.17
Sampling sites UP1 28 6.98 8.21 9.28 0.61 51.93 58.40 65.14 3.13 0.03
UP2 26 5.85 8.41 9.17 0.58 44.48 59.01 64.40 2.90 0.68
UP3 30 4.83 7.91 9.53 0.78 34.54 56.41 68.42 5.47 0.96
DS 32 6.68 7.28 9.40 0.49 48.72 54.04 71.01 3.76 2.87
OL 370 5.16 7.35 9.53 0.45 34.54 54.46 69.96 3.60 2.96
WWTP 31 6.85 7.18 9.49 0.50 50.28 53.55 72.67 2.90 3.25
Ground-water AQ(1.1) 9 7.90 8.67 9.46 0.47 54.06 59.91 66.92 3.93 1.31
AQ(1.2) 43 5.31 8.19 8.62 1.00 44.18 58.24 62.09 4.95 0.16
AQ(2) 15 8.84 9.02 0.22 0.10 62.4 63.3 64.1 0.54 0.66
Note: Arrow represents stream direction.
Abbreviations: n, number of samples; SD, standard deviation.
8of20 MARX ET AL.
showed a higher variability compared to AQ2, suggesting the greater
influence of near-surface flow pathways, and mixing. Groundwater
from the main unconfined Panke valley (AQ1.2) was quite homoge-
neous, except for a wetland-influenced groundwater well (the most
enriched GW-well in Figure 2e and located upstream of UP3 adjacent
to the outflow of a wetland/forested tributary, Figure 1) which
showed some inter-annual variability. The highest variability in isoto-
pic signatures was measured for the Barnim aquifer (AQ 1.1), with the
most enriched groundwater isotopes in March, and most depleted in
July. Comparison with UP2, which is close to this particular AQ1.1
well often showed an overlapping isotope signature possibly implying
surface water connectivity.
4.3 |Spatial variability in isotopes
The isotopic signatures of the different sampling sites and potential
source waters showed some clear differences in ranges and deviations
from the LMWL when plotted in dual-isotope space (Figure 3). Precip-
itation had the highest variability, and less than half of this variability
was observed in the stream during events, while during baseflow con-
ditions almost no variation occurred (cf. Figures 2d and 3a). At OL,
enriched stormflow samples during summer events plotted almost
directly along the LMWL, while during winter a slight offset was
apparent. The relative stability of most groundwater samples was evi-
dent, plotting mostly along the LMWL. An exception was the previ-
ously mentioned well in AQ1.2 which received wetland drainage and
plotted distinctly below with a more enriched and fractionated signal.
Importantly, the groundwater signal was very similar to the stream
signature at UP1 and UP2 throughout the year. The stream became
progressively more enriched between UP2 and UP3, probably caused
by enriched inflows from the north bank tributary draining forested
and wetland areas (Figures 1d and 3b) where surface evaporation is
likely (Kuhlemann et al., 2020; Sprenger et al., 2017). However, below
the WWTP, similar isotopic signatures in the lower stream system
showed a strong influence of effluent waters. The samples from
downstream of the WWTP plotted parallel to the LMWL and were
very similar to samples in OL, indicating minimal influence from tribu-
taries or other sources downstream of the WWTP.
Urban inflows were those streams flowing through urbanized
areas, while peri-urban pass more agriculture-dominated sub-catch-
ments. The main forested stream has its confluence with the Panke
about 2 km upstream of UP3, while urban headwater tributaries can
be found along the whole catchment. The peatland inflow is between
UP2 and UP3, south of the forested stream, close to the wetland-
lakes. Samples from the urban and peri-urban tributaries showed
higher isotopic variation than the forested stream or the peatland
inflows (Figure 3b). The peatland inflow showed the most enriched
and fractionated signatures of any tributary (mean lc-excess: 4.79‰
(Table 3)).
The results of the seasonal synoptic surveys are shown in
Figure 4, where the regular sample sites are also shown for orienta-
tion. Throughout all seasons, the north of the catchment (i.e., UP1–
UP3) was characterized by more depleted isotopic signals being
mostly similar to those of groundwater (Figure 4a). However, the most
upstream synoptic sampling site flowed from a lake which became
enriched during summer. The October samples still showed evidence
of such enriched water sources, but during December 2019 and April
FIGURE 3 Dual isotope plots with respective violin plots for (a) precipitation, lumped groundwater samples from AQs 1.1, 1.2, 2, 2.1,
regularly sampled streamsites (UP1-3, DS), treated wastewater (WWTP), daily and sub-daily samples (from OL), inset shows the complete range
to cover precipitation variation. The enriched and fractionated GW samples are from AQ1.2 and a wetland influenced well. (b) Samples from the
synoptic surveys for inflowing tributaries along the Panke catchment related to the WWTP inflow. Inset “zooms in”to better distinguish the sites.
Local Meteorological Water Line (LMWL) is for Steglitz, Berlin; Global Meteorological Water Line (GMWL)
MARX ET AL.9of20
2020, the entire northern part of the catchment exhibited depleted
isotopic signatures. The July 2020 sampling showed more enriched
isotopic signatures again, especially at the most upstream lake site.
Further downstream, below the WWTP seasonal variability became
larger, with December 2019 most depleted and October 2019 most
enriched.
The spatial influence of inputs from the WWTP on the DS and
OL sites were clearer for lc-excess, though with some seasonal varia-
tion (Figure 4b). The seasonal patterns for lc-excess in the lower
catchment were more complex than for δ
2
H, with slightly lower values
being estimated in winter, showing greater fractionation effects in the
effluent waters. The lc-excess varied between 4‰and 4.5‰
during November–March and –2.5‰to –3‰from April to
October.
The spatial surveys in December, April and July revealed some
of the more subtle influences of tributary streams on the Panke,
especially in the central part of the catchment where the WWTP
discharge enters (Figure 4, insets). For example, throughout the
year, and even in winter, the outflow of the wetland and forest
stream upstream of the WWTP inflow was enriched and contribut-
ing to flows which resulted in enriched signatures and low lc-excess
values compared to the mainstream. Spatially, the WWTP inflow
provided an enriched signal. Overall, downstream of the WWTP sig-
natures remained similar along the stream for all sampling occasions
with more enriched and fractionated values than upstream
the WWTP.
4.4 |Temporal variability in streamflow sources
The end member mixing analysis helped to constrain the sources of
flow in the Panke and quantify their contributions to the mainstream
(Figure 5; Table 4). Tables S2 and S3 provide model performance sta-
tistics, which were good for both metrics. The Gelman-Ruby test
resulted in values below 1.05 showing all models converged and
showed no multimodal posterior distribution, while the Geweke diag-
nostics only rejected a maximum of 13% of the variables for the
MCMC chains, indicating good model performance.
UP1 was dominated by groundwater, with roughly similar (though
the standard deviations in Table 4 uncertain) contributions from
AQ1.2 and AQ1.1 accounting for around 70% of the flow for most of
the year (Figure 5a). However, the overall contribution of precipitation
from urban storm drains was also the highest of all sample sites, being
greatest in autumn and winter, though still only accounting for around
30%–40% of runoff, in this time period. At UP2, the groundwater con-
tribution again had similar inflows from AQ1.1 and AQ1.2, though
overall contributions from upstream (UP1) accounted for around 44%
of flows (Figure 5b). These were lower in summer when the
streamflow became intermittent. This leakage from the upper catch-
ment may also explain why the modelled contribution from rainfall
was also lower, as summer inflows from storm drains leak into the
aquifer before reaching UP2. At UP3 (Figure 5c), a broadly similar pic-
ture was evident, though the estimated contributions from upstream
were only around 21% of flows, and AQ1.2 appeared to become the
dominant source of streamwater, presumably reflecting inputs from
the north bank forested tributary. The proportions from upstream
(UP2) were relatively low, especially during summer suggesting losing
conditions occurred. Precipitation generally contributed 10%,
though this increased in summer, in response to greater storm influ-
ence and inflows from drains.
There was an abrupt change in contributions downstream of the
WWTP. The sampling point DS had a relatively constant, very high
contribution of WWTP effluents (with low uncertainty, see Table 4)
accounting for around 83% (Winter) –96% (Summer) (mean: 86%) of
discharge (Figure 5d, Table S3). Here, the seasonal variability of con-
tributions was also low compared to the other sites, indicating the
overall dominance of WWTP throughout the year. The slightly higher
WWTP contribution during summer compensated low flow conditions
in UP3. Groundwater and precipitation each contributed around 5%
and 3% to annual runoff, respectively with low uncertainty. A similar
distribution of sources was evident at the OL sampling point, with
over 90% of contribution originating from DS, and with low variability
(Figure 5e). The highest DS contribution of about 96% and 89% was
during summer and autumn, respectively.
In summer, most urban tributaries dried out and the peri-
urban tributaries had low water levels, while in autumn with the
TABLE 3 Summary of isotopic composition of the synoptic surveys regarding their tributaries
δ
18
Oδ
2
H lc-excess
nMax Median Min SD Max Median Min SD Median
[—]‰‰‰‰‰‰‰‰‰
Upstream WWTP 117 4.83 8.22 11.88 0.84 34.54 58.48 81.63 5.18 0.37
Downstream WWTP 124 4.65 7.44 9.40 0.56 34.97 54.85 71.01 3.97 2.79
Forested stream 4 6.82 7.14 7.74 0.43 51.40 53.30 56.68 2.40 3.56
Peatland inflow 3 6.43 6.72 6.94 0.26 49.44 51.27 52.24 1.58 4.79
Periurban inflow 6 7.27 7.85 8.60 0.53 52.96 56.47 61.85 3.39 1.18
Urban inflow 11 6.90 7.64 9.31 0.81 51.39 55.71 64.58 4.17 2.09
Abbreviations: n, number of samples; SD, standard deviation.
10 of 20 MARX ET AL.
longest rainfall events during the sampling period, precipitation
had the highest contribution of 5%, which is related to prolonged
rain over several days driving variability in the hydrograph. How-
ever, in general, precipitation and groundwater both made small
contributions to the stream. Although low, the groundwater
contribution was also at its minimum during the summer months
at OL, consistent with the seasonally minimum groundwater
storage.
Figure 6 summarizes the average flux contributions from each
source to each sampling site as a Sankey plot. The overall means from
FIGURE 4 Results of the four seasonal surveys for (a) δ
2
H, and (b) lc-excess. Tributaries have been sampled close to their confluence with the
main stem. Regular sample sites are shown for reference. Background map: ALKIS (land use in black and white). WWTP: wastewater treatment
plant with further distance. Background map: ALKIS (land use in black and white) see for legend: Figure 1
MARX ET AL.11 of 20
the end member mixing are plotted for the whole study period.
Groundwater, particularly AQ1.2, dominates UP1-3 showing the sig-
nificance of stream flow generation processes in addition to
precipitation from urban storm drains. The low GW contributions at
OL reflect the disconnection of the surrounding landscape in the
lower catchment and effluent dominance.
FIGURE 5 EMMA results for
regular sampling locations across the
four seasons. Lc-excess was applied
as tracer information. Plots are shown
following downstream from top left
(a) UP1 (Upstream 1), to right (c) UP3
(Upstream 3) to (d) DS (Downstream)
where WWTP (waste water
treatment plant) is discharging into.
(e) OL (outlet). GW sources are:
Barnim Aquifer AQ(1.1) and Panke
Aquifer AQ(1.2). Error bars indicate
SD's as a measure of variability
source contribution within one
season
TABLE 4 EMMA results showing the % contribution of the different stream sources for the respective sites (lc-excess, δ
2
H and δ
18
Oas
tracer). SD's from source distribution
Spring Summer Autumn Winter Annual
Endmember Source Mean SD ± Mean SD ± Mean SD ± Mean SD ± Mean
UP1 AQ(1.1) 35% 19% 30% 22% 30% 15% 45% 21% 35%
AQ(1.2) 54% 19% 50% 29% 30% 14% 22% 16% 39%
Precip 10% 6% 20% 10% 40% 12% 33% 11% 26%
UP2 AQ(1.1) 27% 15% 32% 18% 37% 15% 25% 17% 7%
AQ(1.2) 12% 11% 28% 22% 16% 11% 10% 10% 17%
Precip 4% 3% 14% 7% 9% 5% 9% 7% 9%
UP1 57% 18% 26% 14% 39% 13% 57% 21% 44%
UP3 AQ(1.1) 9% 10% 10% 10% 12% 9% 14% 13% 11%
AQ(1.2) 57% 19% 44% 22% 60% 11% 61% 15% 55%
Precip 5% 4% 28% 12% 9% 5% 7% 6% 12%
UP2 29% 21% 18% 18% 20% 12% 18% 13% 21%
DS AQ(1.1) 2% 3% 2% 2% 3% 3% 3% 3% 2%
AQ(1.2) 4% 5% 2% 3% 5% 4% 5% 5% 4%
Precip 2% 2% 2% 2% 2% 2% 2% 3% 2%
UP3 7% 9% 5% 5% 7% 6% 6% 6% 6%
WWTP 85% 10% 90% 6% 83% 7% 85% 7% 86%
OL AQ(1.1) 2% 2% 1% 1% 2% 2% 2% 2% 1%
AQ(1.2) 5% 5% 1% 2% 4% 5% 4% 4% 3%
DS 91% 6% 96% 3% 90% 6% 93% 5% 93%
Precip 3% 2% 2% 2% 5% 4% 1% 1% 3%
Note: Arrow represents stream direction.
12 of 20 MARX ET AL.
The YWF at each site was used as an additional indicator of water
sources, by estimating the “younger water”(<2 months) contribution
to streamflow (Table 5), which primarily reflects the contributions of
urban storm drainage. The dynamics between δ
2
H and δ
18
O were sim-
ilar, however, they were slightly different regarding absolute values.
At almost all sites, statistically significant fits (p< 0.001) were
obtained. Despite the Panke being a heavily urbanized catchment, the
YWFs were low at all sites (Table 5). Between both upstream sites
UP1 and UP2, the YWF in δ
2
H decreased from about 13% to 7%,
respectively. At UP3, this increased to 11%. The estimated YWF of
the WWTP effluents was 7%, and 10% for DS and OL, with a similar
range of uncertainty of a residual standard error RSE of 0.12–0.24
(OL–DS/WWTP for δ
18
O). These results of YWF estimation are
broadly consistent with the rainfall estimates from the EMMA of each
site, the groundwater dominance at UP1-3 and effluent dominance at
DS and OL.
5|DISCUSSION
5.1 |Runoff sources in the Panke catchment
Our study demonstrated that we could successfully use isotopes to
identify the spatio-temporal dynamics of runoff sources in a complex,
highly managed urban catchment in a major city. The first aim was to
understand how well the short-term dynamics of isotopes at the
catchment outlet could track changing dominant runoff processes.
The daily isotope sampling at the outlet (OL) revealed a rapid
FIGURE 6 Estimated mean EMMA results over all seasons as a Sankey plot. Each stream sampling location represents 100%, link thickness
represents the source ratio in %
TABLE 5 Site specific young water
fractions (YWF) for δ
2
H and δ
18
O related
to their fitting diagnostics, with
coefficients of determination (R
2
) and
residual standard errors (RSE) as fitting
parameter
Site
δ
2
Hδ
18
O
YWF R
2
p-value RSE YWF R
2
p-value RSE
Precip [—] 0.33 5.80E-09 19.3 [—] 0.3 7.50E-09 2.52
UP1 0.14 0.52 2.00E-04 1.81 0.22 0.56 7.50E-05 0.33
UP2 0.06 0.2 8.00E-02 1.75 0.1 0.29 2.00E-02 0.27
UP3 0.1 0.33 4.00E-03 1.99 0.13 0.47 2.00E-04 0.25
WWTP 0.07 0.27 1.00E-02 1.61 0.05 0.11 1.90E-01 0.24
DS 0.09 0.35 2.00E-03 1.72 0.08 0.21 1.00E-02 0.22
OL 0.08 0.26 <2.2E-16 0.93 0.06 0.15 5.80E-14 0.12
MARX ET AL.13 of 20
translation of rainfall to runoff in most storm events, though this was
generally less dramatic –in terms of flow response (Figure 2d) –than
has been reported in other urban studies (Soulsby et al., 2015b). This
is the result of: (a) the relatively small proportion of the sealed sur-
faces in Berlin's urbanized areas being directly connected to the Panke
channel network; (b) the high outflows from the WWTP being the
dominant stream water source in the lower catchment and (c) storm
runoff from the upper catchment being transferred into the neigh-
bouring Tegeler catchment for flood mitigation.
The more distributed, catchment-scale synoptic sampling cam-
paigns achieved our second aim and allowed the complex spatio-
temporal dynamics of dominant streamflow sources in the Panke to
be identified. The lowland headwaters of the catchment, where
urbanization affects around 34% of the area, still reflects groundwater
dominance in streamflow generation, albeit strongly affected by urban
storm runoff. This resulted in the highest relative contributions of
rainfall (annual mean: 26%, Table 4) and young water (mean between
δ
18
O and δ
2
H 18%, Table 5) to streamflow in the catchment at UP1.
The spatial changes in runoff sources and stream-groundwater inter-
actions are shown conceptually in Figure 7. Whilst tributaries from
forested and wetland areas supplement flows in the catchment head-
water, limited recharge from sealed areas (Roy et al., 2015; Wenger
FIGURE 7 Conceptualized Panke river system showing main contributing sources and stream –groundwater interactions
14 of 20 MARX ET AL.
et al., 2009) and unregulated local groundwater abstractions (Benejam
et al., 2010; Jasechko et al., 2021; Vörösmarty & Sahagian, 2000) may
result in the stream “losing”in the summer and leaking into the under-
lying aquifer. Such intermittent streams are particularly vulnerable to
anthropogenic alterations (Brooks, 2009).
In the lower catchment, the dominant source of runoff is effluent
from the WWTP, and the stream can be classified as “effluent-domi-
nated”(i.e., where more than 50% of streamflow is comprised of efflu-
ent) (Hamdhani et al., 2020) (Figure 6). The isotopic composition of
the wastewater carries a fractionation signal that allowed its annual
contribution to streamflow (86%) to be estimated via end member
mixing. Some preliminary data indicates that this fractionation signal is
also evident in tap water (Marx unpublished), so most likely reflects
fractionated signals in Berlin's surface waters (lakes) that are
abstracted via bank filtration (cf Kuhlemann et al., 2020). The WWTP
contributions to the Panke are managed and reduced for flood risk
mitigation or increased for base flow enhancement, with weirs con-
trolling the volume and timing of transfers. Overall, however, this
dominant influence of WWTP effluents dictates that even in the
lower catchment, where the urbanization accounts for 40% of land
cover, storm drains are limited to providing only <10% of annual run-
off and low (<10%) young water fractions, at least part of which
seems also to be water routed through the WWTP. However, this
lower contribution of mixed storm runoff also partly reflects drainage
of some peak-flows directly from the WWTP into the Nordgraben
(median: 30% of total WWTP outflows) rather than the Panke, as
well as drainage from the Panke into the Nordgraben (median: 20% of
the Panke [OL] flow). It should be stressed, however, that the Panke is
unusual in such overwhelming dominance of treated wastewaters
throughout the year; in major German catchments only around 25%
of gauging stations have flows comprising >10% wastewater. How-
ever, at low flows, treated wastewater can comprise >60% of flows in
heavily developed rivers such as the Main and Rhine (Drewes
et al., 2018).
Although the isotopes helped resolve the “big picture”of spatio-
temporal variations in runoff sources in the Panke many uncertainties
remain that would need further work to resolve. For example, in the
upper catchment (UP1 and UP2) the groundwater sources of stream
flow are poorly constrained as a result of the similar isotopic composi-
tion of the AQ(1.1) and AQ(1.2) aquifer units. Linked to this, the
changing nature of groundwater-surface interactions that lead to the
stream drying remain unclear as is any role of the deeper confined
aquifer. Further resolution of these issues would be dependent upon
more intensive sampling and the use of other tracers. In the lower
catchment, uncertainties are lower, given the dominance of water
from the WWTP, which is broadly corroborated by hydrometric mea-
surements of stream flow and WWTP outflows (Table S3), though
these may be affected by groundwater leakage.
It is reassuring that the rainfall contributions estimated from the
EMMA are generally similar to the YWF that was derived indepen-
dently. Although the YWF are perhaps lower than expected given the
degree of urbanization (for reasons already outlined), they are similar
to other lowland catchments in Germany, such as the Demnitz Mill
Creek, south east of Berlin (Kleine et al., 2021) and the Bode catch-
ment in central Germany (0.05–0.2) (Lutz et al., 2018). These catch-
ments have lower YFW than the global median of 0.26 cited by
(Jasechko et al., 2016).
A final caveat on the results of the study is the representativeness
of the study year, given that rainfall levels were below average for
most months in the study, and it followed the extreme drought year
of 2018 (Kuhlemann et al., 2020). As such the contribution of rainfall
and the YWF might be depressed due to the combined effect of
smaller rainfall events and depleted catchment storage (Bansah &
Ali, 2019; Clow et al., 2018; Wilusz et al., 2017). This might have
increased the spatial extent and longevity of parts of the stream net-
work drying out. This also underlines the need for longer-term studies
to assess the role of hydroclimatic variability and extremes in control-
ling runoff sources and associated isotope dynamics (Kleine
et al., 2021).
5.2 |Using isotopes in urban hydrology
The hydrology of any city uniquely reflects the interaction of the built
urban fabric and the natural environmental characteristics. A particu-
larly influential component of this is the management of water sup-
plies, storm runoff and wastewater disposal. This in turn creates both
opportunities and challenges for using isotopes to understand hydro-
logical processes. For example, urban isotope hydrology in Berlin, or
any city operating a largely “closed”water management system, is
challenging due to the lack of isotopic differentiation between with-
drawals and wastewater returns as well as inter-basin transfers in
catchments like the Panke (Massmann et al., 2007). Fortunately, in
Berlin, wastewater carries a strong fractionation signal (Kuhlemann
et al., 2021b), so it can be differentiated from local groundwater and
rainfall as an end member in hydrograph separation and for estima-
tions of the young water fractions. The isotopes provided a basis for
tracking water source contributions to complement hydrometric mea-
surements of streamflow and effluent releases as reversals in local
groundwater –surface water interactions. As noted above, the latter
dictates that during summer, parts of the river become losing reaches
and leak into the underlying groundwater as observed in neighbouring
catchments (Kleine et al., 2021; Kuhlemann et al., 2021b). This,
together with weather-related transfers of water into and out of the
catchment, confound source attribution from hydrometric measure-
ments alone. In other urban areas with water supply imports, espe-
cially involving inter-basin transfers from distal areas, isotopic
differentiation of waste water from local surface and groundwater
sources is usually easier. This has been demonstrated in studies track-
ing diverse drinking water supplies from tap water analysis (Bowen
et al., 2007; Jameel et al., 2016; West et al., 2014), as well as investi-
gations of local groundwater intrusion into sewers carrying waste
waters (De Bondt et al., 2018; Kracht et al., 2007).
Because of the potential diversity of local and distal water
sources influencing urban waste water, using water ages is conceptu-
ally challenging in complex urban systems compared to other
MARX ET AL.15 of 20
catchments where the hydro-demographics of different water sources
(e.g., soils, groundwater, etc.) can be well-constrained (Sprenger
et al., 2019). Whilst identifying young water fractions from recent
rainfall or older groundwater from depleted isotope signatures or
other dating tracers (CFCs, tritium and others) is possible, effluents
are more problematic, both when they are derived from local and dis-
tant sources or from surface water and groundwater. Effluents com-
bine a range of water ages, that is, in mixing “old”groundwater,
surface water and “young”precipitation. For example, the calculated
YWF of the WWTP was in the Panke was between 5% and 7%. Simi-
lar to precipitation, wastewater from outwith a catchment might be
considered as “young”in terms of their release in the catchment,
although its original age on abstraction can be much older, and there-
fore interfere with common methods to describe water ages. Further,
infiltration and inflow to the sewer system from recent precipitation
might play a role in affecting water ages but we do not have any data
on this for this system.
Undoubtedly, in addition to stable isotopes, other geochemical or
anthropogenically-introduced tracers will help further constrain urban
end member assessment, identify particular runoff sources, and help
better conceptualize and constrain water ages. The wide range of
emerging pollutants from pharmaceutical metabolites is particularly
promising in this regard (Bradley et al., 2020). It is easy to envisage
that this will be a fruitful area in the coming years and will help
develop a more integrated understanding of urban hydrology in a
wide range of cities. This also has outstanding potential to help under-
stand urban water quality issues, particularly when these involve the
complex connectivity of the “urban karst”in the subsurface of large
conurbations (Bonneau et al., 2018). However, such tracer studies
may have most potential in understanding urban systems in poorer
countries where hydrometric and effluent data are less readily avail-
able (Oiro et al., 2018). This would help understand water resource
systems and their vulnerability to change (Ehleringer et al., 2016).
6|CONCLUSION
We combined temporally intensive and spatially extensive sampling to
monitor stable isotopes in rainfall, streamflow, groundwater, treated
wastewater and urban storm runoff in the 220 km
2
highly urbanized
Panke catchment in Berlin, Germany. The monitoring was aimed at
assessing the temporal dynamics and spatial patterns of the sources
of streamflow. This was achieved by using isotope data in Bayesian
approaches to end member mixing to assess contributions by contra-
sting sources of stream flow. The Panke has a lowland catchment that
is naturally groundwater dominated; however, urban surfaces cover
35% of the catchment and urban storm drains have an important
influence on runoff generation. In the upper catchment, groundwater
and urban storm drainage accounted for around 75% and 25% of
annual runoff, respectively. In the lower catchment, however, effluent
from a WWTP accounted for 80% of streamflow, with groundwater
and urban storm runoff each accounting for around 10%. Regulation
of sources in the Panke by artificial weirs increased WWTP contribu-
tions to augment summer baseflows to >90%, and reduced
contributions from urban storm drains during high flows as a flood
alleviation scheme diverted a portion of high flows into a neigh-
bouring catchment. We also estimated the contribution of the young
water fraction (i.e., water that is less than around 2 months old) of
streamflow, which was low throughout the catchment, varying
between around 10%–15%. However, age dating urban streams is
challenging due to the undefined age of wastewaters. The study
showed how isotopes can provide novel quantitative insights into
how managed urban water systems integrated with the more natural
hydrological processes in non-urban areas and urban green spaces.
Such understanding is vital to a comprehensive understanding of
urban hydrology needed to provide an evidence base for more sus-
tainable management of urban waters.
ACKNOWLEDGEMENTS
We thank D. Dubbert and A. Dahlmann for running the isotopic analy-
sis in the isotope laboratory of IGB. A. Smith is thanked for advice on
aspects of the analysis and comments on an earlier draft. Additionally,
we thank the Berliner Wasserbetriebe (BWB), and Berlin Senate for
constructive information, expert knowledge, feedback and provision
of data, as well as access to their groundwater wells. L. Kuhlemann
and L. Kleine are thanked for constructive feedback and discussion.
Funding from this study was through the project “Modelling surface
and groundwater with isotopes in urban catchments”(MOSAIC) pro-
vided by the Einstein Foundation and CM is associated with the
Research Training Group “Urban Water Interfaces”(UWI), GRK
2032/2 as a collegiate, financed by the German Research Foundation
(DFG). Contributions from CS were also funded by the Leverhulme
Trust's ISOLAND project. We also thank three anonymous reviewers
for their constructive reviews.
DATA AVAILABILITY STATEMENT
Stream data and groundwater level based in rating curves, pres-
ented in Figure 3b–e, are only available upon request from the
Berlin Senate, the same applies for the wastewater effluent data
which is available from the Berliner Wasserbetriebe (BWB). Pre-
cipitation data are available publicly from the Deutsche
Wetterdienst (DWD), station Buch. Precipitation and stream iso-
topes are available upon reasonable request. Discharge and
groundwater level data are available upon request from the Berlin
Senate/BWB.
ORCID
Christian Marx https://orcid.org/0000-0001-7648-1603
Dörthe Tetzlaff https://orcid.org/0000-0002-7183-8674
Chris Soulsby https://orcid.org/0000-0001-6910-2118
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How to cite this article: Marx, C., Tetzlaff, D., Hinkelmann, R.,
& Soulsby, C. (2021). Isotope hydrology and water sources in a
heavily urbanized stream. Hydrological Processes,35(10),
e14377. https://doi.org/10.1002/hyp.14377
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