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Automated in situ oxygen profiling at aquatic-terrestrial interfaces Tanja Brandt, Michael Vieweg, Gerrit Laube, Robert Schima, Tobias Goblirsch, Jan H. Fleckenstein, and Christian Schmidt Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b01482 • Publication Date (Web): 11 Aug 2017 Downloaded from http://pubs.acs.org on August 13, 2017

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Automated in situ oxygen profiling at aquatic-terrestrial interfaces

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Tanja Brandt*1, Michael Vieweg1, Gerrit Laube1, Robert Schima2,3, Tobias Goblirsch4, Jan H.

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Fleckenstein1, Christian Schmidt1

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Department of Hydrogeology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, 04318, Germany

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Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research – UFZ, Leipzig,

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04318, Germany

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Chair of Ocean Engineering, University of Rostock, Rostock, 18059, Germany

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Faculty of Economics and Management Science, Chair of Information Management, University of Leipzig, Leipzig, 04109,

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Germany

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Corresponding author:

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Tanja Brandt

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Helmholtz Centre for Environmental Research – UFZ

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Permoserstr. 15, 04318 Leipzig, Germany

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Phone +49 341 235 1996

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Email:[email protected]

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Abstract

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Optical sensing technologies provide opportunities for in situ oxygen sensing capable of capturing the whole range of spatial

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and temporal variability. We developed a miniaturized Distributed Oxygen Sensor (‘mDOS’) specifically for long-term in

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situ application in soil and sediment. The mDOS sensor system enables the unattended, repeated acquisition of time series of

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in situ oxygen profiles at a sub-cm resolution covering a depth of up to one meter. Compared to existing approaches, this

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provides the possibility to reveal highly variable and heterogeneous oxygen dynamics at a high, quasi-continuous resolution

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across both scales. The applicability of the mDOS to capture both, intra- and inter-day, fine-scale variability of spatio-

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temporal oxygen dynamics under varying hydrological conditions is exemplarily demonstrated. We specifically aim at

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estimating the dependency between oxygen dynamics and hydrologic conditions along the measured profiles. The mDOS

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system enables highly detailed insights into oxygen dynamics in various aquatic and terrestrial environments and in the

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inherent transition zones between them. It thus represents a valuable tool to capture oxygen dynamics to help disentangling

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the coupling between underlying hydrological and biogeochemical process dynamics.

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Oxygen (O2) is one of the key parameters governing biogeochemical processes in terrestrial and aquatic environments. This

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is particularly relevant for aquatic and terrestrial interfaces, where O2 dynamics and interlinked biogeochemical processing

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exhibit a high degree of temporal and spatial variability. Pronounced transitions between water-saturated and –unsaturated

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conditions in a sediment matrix can facilitate the occurrence of elevated turnover rates of O2 and nutrients. Examples for

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such transitions include water table fluctuations in wetlands, riparian zones and riverbanks 1,2 as well as drying and rewetting

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of soils and sediments3,4. A vital precondition for ultimately disentangling and quantifying O2-associated turnover rates lies

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in the adequate description of in situ spatio-temporal O2 dynamics and their inherent variability and heterogeneity in soils

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and sediments.

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Optical oxygen sensing has become the standard technology particularly for in situ applications with numerous optode-based

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oxygen sensors being commercially available. Spot optodes feature an oxygen-sensitive coating at the tip of an optical fiber

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and have been applied extensively in situ and ex situ due to their robustness and long-term stability in challenging and harsh

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environmental and medical applications5. Instead of combining multiple single-point measurements provided by spot

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optodes, two-dimensional measurements can be achieved by means of planar optodes and provide the 2D O2 distribution

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across a given area6,7. Since they utilize a camera-based system for illumination and reading, planar optodes have been

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primarily applied in

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illumination of the whole optode area. In situ applications of planar optodes include coastal9,10 and deep sea sediments11

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using benthic lander systems. It should be noted that the introduction of such a transparent feature may change the soil or

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sediment structure and thus, may not reflect the actual conditions within the interior7. However, an in situ comparison

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between planar optodes and microprofilers revealed a good agreement for benthic lander systems11. Microprofilers provide

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another potential solutions for spatially resolved in situ applications and employ the motorized immersion of a microneedle

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into the matrix of interest, commonly spanning a few cm in length at very high resolutions in the µm range12–15. Both, planar

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optodes and microprofiling systems are restricted to fine-grained, unconsolidated sediments and shallow O2 penetration

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depths (few cm-dm)16,17.

Introduction

studies incorporating transparent vessels like flumes8, mesocosms7 or well plates6 that allow

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The challenge remains: to combine the robustness of spot optodes in situ with the spatial resolution provided by planar

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optodes or 1D microprofiling. The most straightforward approach entails the combination of different sensor types, e.g.

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micro-sensors and oxygen optodes or in situ logging with hand held sensors18,19. Options to add the spatial dimension have

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been based on either combining multiple single spot optodes, e.g. by spatial distribution along the length of the designated

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profile1,20 or arranged through multiplexing21. A promising recent approach that has been originally developed for highly

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conductive, i.e. coarse, sediments, is based on combining two sensing principles in one device: planar optodes and spot fiber

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optic cables 22. Still, certain shortcomings prevail and render existing methods impractical for long-term in situ application:

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limited possibilities for unattended monitoring as well as the size of instrumentation potentially disturbing the soil or

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sediment structure if sensors need to be moved for conducting spatially resolved measurements, e.g. by (repeated) insertion

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of planar optodes or microprofilers.

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We have developed a sensor for automated profiling of the oxygen distribution at a sub-centimeter resolution, which we

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refer to as miniaturized Distributed Oxygen Sensor (“mDOS”). The mDOS system has been designed to automatically

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capture both, short-term, i.e. intra-day, as well as long term (inter-day) oxygen variability in situ. A novel tubular sensing

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element and a motorized side-firing polymer optical fiber (POF) form the core element of the system, which is controlled by

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a microcontroller. This setup enables the fully automated acquisition of oxygen profiles with the capability for conducting

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unattended time series alongside a substantial size reduction of the sensing element to 5 mm in diameter compared to

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previous work22. In the following, we focus on presenting our new method including a discussion of its advantages and

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current limitations. As a proof of concept, we provide two illustrative application examples in the hyporheic zone (HZ) of

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two different streams: intra-day dynamics in a perennial stream subject to hydropeaking as well as inter-day variability of an

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intermittent stream during annual flow cessation.

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2.1

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The mDOS system consists of five key components: a fiber optic oxygen transmitter (Fibox 3 LCD trace, Presens GmbH,

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Regensburg, Germany), a tubular sensing element, a side-firing polymer optical fiber (POF), a motor unit and a control unit

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(Fig. 1a). The latter is based on an Arduino microcontroller board and manages the interactions between the transmitter and

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the motor unit to acquire time series of oxygen profiles by repeated, automated measurements. The concept of utilizing a

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side-firing POF has been adapted from a common principle employed in medical imaging, i.e. radial endomicroscopy23.

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Emission and excitation light is transmitted to and from the transmitter by the side-firing POF inserted into the sensing

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element. Briefly, single oxygen profiles are obtained by the uniform motion of the POF up- and downwards the tubular

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sensing element while illuminating single evenly distributed spots of the outer oxygen-sensitive coating of the tubular

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sensing element (Figure 1b).

Material and methods

Concept of the sensor

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Figure 1 The mDOS oxygen profiling system: Conceptual sketch of the miniaturized Distributed Oxygen Sensor (‘mDOS’) with (a)

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the side-firing Polymer Optical Fiber (POF) within the tubular sensing element and motor unit (to scale), control unit, fiber optic

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oxygen transmitter and power supply (not to scale) with (b) detailed view of signal transmission by side-firing POF within the

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tubular sensing element (not to scale) and (c) photograph of installed motor unit and tubular sensing element.

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2.1.1

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The tubular oxygen sensing element is made from PMMA tubes with an outer diameter of 5mm and a wall-thickness of 1

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mm. Individual tubes of about 70 cm length, yielding a final sensing length of approximately 55 cm, were dip-coated with

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the sensor cocktail. The sensor cocktail was prepared by dissolving 20 mg of the O2-sensitive dye PtTFPP (Porphyrin

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Systems GbR, Lübeck, Germany) and 2.0 g of polystyrene (Carl Roth, Karlsruhe, Germany) in 10 ml of toluene

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(chemsolute, Renningen, Germany). The custom-made dip coating unit consisted of a glass vial with a hole cap and Viton

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septum (Viton, DuPont) and a motor unit placed above the glass vial (Figure S1). For the coating procedure, the top part of a

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single tube was placed into the glass vial through a 4.5 mm hole punched into the septum. The diameter of the punched hole

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was chosen to be slightly smaller than the diameter of the tube in order to seal the vial once a tube is placed inside while still

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enabling the tube being pulled through. Approximately 1.5 ml of the sensor cocktail were added to the vial and deposited

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onto the tube during constant upward withdrawal of tubes at a speed of 0.25 cm s-1 to yield homogenous thin sensor films

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with a thickness of approximately 20 µm. To do so, tubes were connected to the winch of the motor unit by a thin thread.

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Tubes were dried for approximately 12 hours until complete evaporation of toluene.

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2.1.2

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The excitation and emission light between the fiber optic oxygen transmitter and the tubular sensing element is guided by an

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insulated side-firing POF (2/2.8 mm, PMMA, POFNetz GmbH, Hille, Germany) to divert the guided light 90°. This

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configuration enables the side-wise illumination of the outer oxygen-sensitive coating of the tubular sensing element from

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within (Figure 1b). The motorization of the POF enables quasi-continuous profile measurements along the tubular sensing

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element.

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The POF is incorporated into a motor unit comprised of a 12V DC gear motor. Here, the POF is tightly placed between two

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rubber-metal buffers (REIFF GmbH, Reutlingen, Germany), one of which is directly connected to the motor serving as

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driving wheel. The motor unit itself is mounted directly at the bottom of the main housing and spatially separated from the

Preparation of tubular sensing element

Motor unit and control unit

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upper cable compartment to avoid entangling of the POF with the motor unit. The moving of the POF up- and downwards

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the sensing element during measurements requires repeated winding and un-winding, i.e. fiber bending, within the upper

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cable compartment. The inner dimensions of the housing were set in compliance with the minimal bending radius of the used

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POF (35 mm) to reduce fiber bending and inherent loss of signal 24. The spatial resolution of individual profiles is defined by

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the selected sampling frequency of the transmitter and the feed speed of the POF determined by the drive voltage of the

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motor. All measurements were taken at a sampling frequency of 1 Hz and a feed speed of approximately 5 mm/s at 12 V

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drive voltage, resulting in a step size equal to the spatial resolution of approx. 5 mm.

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The control unit controls the excitation and detection of the optical signals by the transmitter and the motion of the motor

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with regard to speed and direction. To control the positioning of the POF along profiles, i.e. the coated length of the tubular

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sensing element, the raw optical signals is read from the transmitter through an analogue output. Here, a marked reduction

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the raw signal amplitude below a certain threshold value marks the upper or lower end of the profile and triggers a reversal

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of the POF motion between single profiles. Profiles are acquired bi-directionally and considered as independent technical

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replicates. The whole mDOS system is put to sleep mode with the transmitter switched off between measurement runs to

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minimize power consumption. A detailed sketch of the wiring as well as the operating script can be found in the supporting

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information (Figure S3).

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2.2

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To acquire the necessary fitting parameters for final oxygen calculations, we determined the response to a) eight different O2

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saturations between 0 and 100 % air saturation (% airsat) at a fixed temperature of 20 °C and b) over a temperature range of

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environmentally relevant temperatures ranging from 15 to 35°C at two fixed oxygen concentrations of 0 and 100% airsat.

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The slope of the latter is used as input parameter for temperature compensation of oxygen values which shows a different

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extent at 0 and 100 % airsat (eq. 1, Table S1). The fitted slope of the former is used to acquire the necessary fitting

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parameters 22 as well as the Stern-Vollmer constant (KSV) of the used two-site quenching model25 (eq. 2, Table S1), with KSV

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indicative of the detection sensitivity S over the full dynamic range of O2 concentrations (0-100 % airsat)5. To do so, a

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tubular sensing element was placed in a tempered bioreactor (Sixfors, Infors AG, Basel, Switzerland) to define the

Calibration and sensor performance

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temperature and oxygen saturation accordingly. Prior to field installation, all tubular optodes were calibrated according to the

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instructions of the transmitter company: a two-point calibration at 0 and 100 % airsat. According to their manual, we placed

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each sensing element in a non-transparent 1 inch-bottom-sealed tube. For calibration at 100 % airsat, we placed a moist cloth

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at the bottom of the tube, sealed the top with parafilm to minimize evaporation and let the sensing element equilibrate at

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humid air for at least 15 min. For calibration at 0% airsat we placed each tube in de-oxygenated water and let it equilibrate

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which took about 15 min. We found calibrations values for each batch of tubular optodes to be very comparable between

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single tubes so that one set of calibration values was applied to all tubes of the batch. All calibrations were performed in the

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dark to minimize interference from ambient light.

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We evaluated the performance of our new sensor design with regard to response time, detection sensitivity and limit of

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detection (LOD). The response time t90 was defined as the time for reaching 90 % of the true O2 value upon a change of O2

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concentration from 100 to 0 % airsat at a constant temperature of 20.0 °C. We calculated the limit of detection (LOD) as

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three times the standard deviation of the calculated oxygen concentration across a sensing length of 50 cm under anoxic

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conditions.

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2.3

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The installation procedure as of now has been primarily developed for applications with no or only shallow water level of up

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to approximately 5cm at the time of installation to avoid water intrusion during the assembly of the motor unit and tubular

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sensing element. As these units of the mDOS system are very closely exposed to potential water intrusion, all connections

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between single parts of the PVC housing of the motor unit are tightly sealed by screws and additional rubber tubing. All

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connections between single units as well as cable outlets are also tightly sealed by screw caps. Once completely assembled,

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this waterproof design of the mDOS system allows measurements in permanently waterlogged environments such as

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streambeds, lake or marine sediments as well as to withstand temporary waterlogging, e.g. during flooding or rewetting

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events.

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First, the tubular sensing element is installed using a method adapted from the “lost cone” technique, 26 which utilizes a steel

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casing with a removable drive point at the bottom. Both are driven into the sediment with a sledgehammer until the pointed

Experimental setup, installation and measurement procedure

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tip reaches the desired depth of the profile. The tubular sensing element is carefully inserted into the casing to remove the

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drive point and held in place while the steel casing is carefully removed. The described procedure can be omitted in soft and

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fine-grained sediments where the tubular sensing element can be slowly pushed in directly in the sediment. Following initial

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installation, the tubular sensing element is left for several hours to ensure sufficient equilibration and resettling of the

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surrounding matrix. For the duration of experiments the tubular sensing element remains permanently installed in situ and

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thus, in equilibration with the surrounding environment. Second, the motor unit is mounted on top of the tubular sensing

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element and fixed to a solid steel rod. A few cobbles and gravel were placed underneath the motor unit to support the weight

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of the motor unit and shield the exposed part of the tubular sensing element from ambient light. The presence of these

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cobbles and gravels should only induce minor effects on the local flow field in very coarse and gravelly sediments due to the

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natural heterogeneity of the sediment surface with regard to height and structure. Additionally, the sediment surface

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underneath the motor unit was not visibly elevated compared to the natural, i.e. undisturbed, sediment surface in proximity

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of the sensor system location. The installation height of the motor unit above the sediment surface can be adjusted to

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minimize disturbance of (expected) surface water flow caused by the presence of the motor unit. Third, the other parts of the

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mDOS system, i.e. control unit, transmitter and 12V battery, are packed into a waterproof box or casing, which is then

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placed on an elevated location nearby the measurement location. Finally, the profiling is done manually a few times to check

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and correct the respective threshold values used for automated measurements.

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To correct O2 measurements for temperature, the mDOS installation was coupled to a depth-resolved temperature monitoring

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covering the same profiling depth. Here, we use a multilevel temperature sensor (MLTS, Umwelt- and Ingenieurtechnik

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GmbH, Dresden, Germany)

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sediment depth and 5 cm above the sediment surface. The MLTS was installed in the same morphological unit and within

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half a meter distance of the mDOS to minimize horizontal temperature deviation. Previous investigations revealed only

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minimal horizontal temperature differences up to 0.5 °C for distances of several meters within a similar morphological unit

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in the same reach 22. We applied a cubic spline interpolation to estimate spatially continuous temperature profiles between

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the eight temperature sensors distributed along the MLTS. We did not correct any oxygen measurements for varying

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hydrostatic pressures as pressure-related differences of phase angles are typically negligible under shallow depths of oxygen

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which features eight circuited temperature sensors placed at 0, 15, 17, 20, 25, 35 and 55 cm

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penetration1. All calculations for calibration and post-processing of raw data were performed using MATLAB (version

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2010a, The Mathworks Inc., USA).

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3

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3.1

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Based on the two-site quenching model we calculated a Stern-Volmer constant (KSV) = 0.0226 (figure S3a). We found a

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linear inverse relationship between temperature and measured phase shifts with ΔτKτ0-1 = -0.0703 at 0 % airsat and ΔτKτ100-1 =

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-0.1526 at 100 % airsat (Figure S3b). Measured calibration values in terms of raw phase angles varied only slightly and the

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degree of variability was comparable both between individual tubes of one batch as well as between batches (< 1.8 %

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relative deviation from respective mean values). The 90% response time of our sensor film upon a change in oxygen

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concentration was t90 = 22±2 s which is faster than approx. 60 s as reported for a similar, tube-based optode system22 and

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within the range of other PTTFPP-PS-based sensing systems20. The KSV, which defines the detection sensitivity S of the

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sensor system, is 0.0226 over the full dynamic, i.e. non-linear, calibration range (0-100 % airsat). The observed non-linearity

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in the relationship between the phase shifts in the absence and presence of O2 (τ0/τ) and oxygen concentration (Figure S3c)

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results in a varying sensitivity over the calibration range with increasing S towards lower O2 concentrations28. Here,

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sensitivity varied between Slow = 0.0144 (at 0-10 % airsat) and Shigh = 0.5599 (90-100 % airsat). The extent of variability in

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the sensitivity could be related to light interference affecting raw phase angles: First, the influence of ambient light due to the

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lack of a protective coating on the tubular sensing element. Second, the path for excitation and emission light likely induces

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some scatter when passing through the 1 mm acrylic wall of the tubular sensing element22. Both characteristics have not been

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investigated in the course of this study but should be considered in future applications. The calculated LOD of 0.25 % airsat

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lies within the range of other conceptually similar sensor systems 20,29–31. The maximum spatial resolution obtainable without

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signal smearing, i.e. overlapping illumination points, is theoretically equal to the size of a single illumination point which is

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estimated to be approx. 3 mm based on the diameter of the POF (2 mm) and the scattering of light through the 1mm wall of

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the tubular sensing element. However, it should be noted that this value should be considered merely theoretical as smearing

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of emission light between adjacent illumination points will not only reduce the actual resolution but moreover, affect

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measured signals and thus, calculated oxygen concentrations .

Results and discussion

Sensor calibration and temperature dependence, response time, sensitivity and limit of detection

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3.2

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Here, we present two illustrative applications to demonstrate the versatility of the mDOS to be used for intra- and inter-day

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oxygen profiling under contrasting hydrological conditions.

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3.2.1

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Morphological features in streams and rivers are considered hotspots for biogeochemical reactivity, which potentially

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account for the majority of in-stream metabolism. The spatio-temporal distribution of oxygen is of particular interest: as a

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potential proxy for aerobic respiration as well as an indicator for aerobic zonation which can define the potential for

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denitrification, which can only occur when most of the oxygen is consumed 32.

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We applied the mDOS at an instream gravel bar at the Selke River, a third-order stream located in the Harz Mountains,

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Germany (N51° 43′33.2″, E11°18′41.1″)32. The stream is subject to sub daily stage variations induced by an upstream water

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mill inducing stage variations of up to ~ 15 cm within 15 min33. We acquired a series of O2 profile measurements at a 60 min

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interval for a total duration of 18 hours that covered the period of night-day transition. Each measurement consisted of four

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single profiles, i.e. technical replicates. The total profile depth was 55 cm and the mDOS system was positioned to cover a

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sediment layer of 53 cm depth with the remaining 2 cm protruding above the sediment surface. An oxygen optode logger

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(miniDOT, PME, San Diego, USA) was installed directly in the main channel to measure dissolved oxygen in the surface

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water at a 5 min interval. We monitored pressure heads at a 5 minute interval in the main and side channel of the stream to

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estimate short-term variations of head differences and stream stage variability induced by regular hydropeaking. Our aim

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was to capture the response of the spatio-temporal O2 distribution to variation in stream stage and inherent vertical hydraulic

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head differences (Δh).

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We observed an oxygen zonation across the profile with an anoxic zone between 20 and 45 cm depth and oxic areas above

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and below this anoxic layer (Figure 2b and S4 for representative scatter plots). The extent and shape of this zonation was

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constant during night time and early morning hours which coincides with a stable water table. Higher O2 concentrations

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below a depth of 45cm suggest pronounced lateral flowpaths. The anoxic zone is potentially a result of a local colmation

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layer. However, extensive measurements of hydraulic conductivities at the site have not revealed a general trend of

Proof of concept in situ

Example 1 – short-term O2 dynamics in a gravel bar

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decreasing hydraulic conductivity with depths34. Local O2 depletion is known to be a result of longer travel times to the

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measurement points which may either be induced by small-scale heterogeneities of lower hydraulic conductivity and/or

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longer flowpaths35.

(a)

(b)

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Figure 2 (a) Pressure gradients and (b) oxygen distribution in an in-stream gravel bar of Selke river, Germany, during low flow

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conditions in summer 2016 including a hydropeak as indicated by a sharp drop followed by partial rise of water level. For oxygen

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data, the total profile depth was 55 cm at a spatial resolution of 5 mm with 0 cm corresponding to the sediment-air/water interface.

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Temporal resolution of oxygen input data is 60 minutes and missing data was linearly interpolated at 10 min intervals.

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O2 saturation in the surface water, monitored by a separate optode logger, varied around 80 % airsat at night and increased

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gradually up to 89 % airsat during the day (data not shown). With the beginning rise of the water level around 9 AM,

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indicative of a hydropeak, the anoxic zone was extended towards the stream surface by approximately 5 cm with the oxic-

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anoxic gradient becoming less sharp and more gradual instead. Simultaneously, oxygen saturation below the anoxic zone

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decreased from approx. 60 to below 40 % airsat. Considering the constant sediment temperature at this depth (Figure S5), the

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observed decrease can likely be explained by larger travel times caused by changes in stream water level and the resulting

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decrease in hydraulic gradients between the main and side channel surrounding the gravel bar as previously reported32,33. The 13

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presence of the oxic bottom layer can be attributed to predominantly lateral flowpaths, transporting oxic stream water into

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the gravel bar from a deeper section of the stream bed, as previously observed for another ISGB in the same stream 22. Here,

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the formation of such flowpaths is likely facilitated by stream water infiltration from a pool (of a pool-riffle structure)

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upstream of the ISGB. Several very narrow, less-oxygenated patches within generally oxygenated zones, e.g. at -18 cm,

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might represent heterogeneities of reduced flow in the sediment, likely caused by the presence of small physical structures

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like sand or stones. We consider these patches as real data as no irregularities or artefacts during calibration or measurements

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have been encompassed.

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The application of the mDOS revealed that O2 in the streambed is not simply a function of stream O2 variation but reveals

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spatial patterns driven by textural heterogeneities of the streambed. These patterns would not have been detected by single

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point observations. Besides identifying these zones, we could also observe the temporal dynamics of O2 variability not only

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during baseflow conditions but also during individual hydrologic events, i.e. hydropeaking. Both of these features and their

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inherent high degree of variability would not have been observed with only regular point or snapshot measurements.

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3.2.2

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Intermittent rivers (IRs) play an important role in aquatic biogeochemical cycling, which is particularly relevant in light of

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future climate change scenarios indicating intensified periods of drought and more extreme weather events

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commonly characterized by distinct hydrological phases of drying and rewetting leading to full or partial cessation of surface

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flow and thus, transitioning between terrestrial and aquatic phases. Recent studies indicate that the short-term transition

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between phases as well as pulsed rewetting events, e.g. by precipitation, might be particularly relevant as hot moments of

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biogeochemical activity and carbon processing

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and potential rewetting events to explore spatio-temporal patterns of oxygen dynamics and the role of the water level as

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potential primarily control of these patterns.

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A measuring program was carried out in the streambed of Fuirosos, a first order stream on the Iberian Peninsula

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(N41°42’16.38’’, E2°34’51.75’’). Oxygen profiles of 55cm length, covering a sediment depth of 50 cm, were measured

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repeatedly during summer 2015 (June and July) over a period of 36 days at two locations (‘upstream’ and ‘downstream’),

Example 2 – long-term O2 dynamics in an intermittent stream

3,38,39

36–38

. They are

. We acquired streambed O2 profiles over the course of flow cessation

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separated by a pool-cascade sequence within a 80 m reach40. The interval between sampling days was extended from one day

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at the beginning to four days towards the end of the measurement period (Figure 3b). We conducted two to three

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measurements per sampling day during daylight between 10 a.m. and 7 p.m., thus minimizing effects of diel biogeochemical

279

fluctuations39 due to the lack of automated measurements. Each measurement consisted of at least six single profiles, i.e.

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technical replicates, with an estimated spatial resolution of 6 mm. The data was obtained using a “first-generation” prototype

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of the mDOS without a control unit, thus only allowing manual measurements by means of a simple switch

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(“up/down/stop”) to control the POF movement up and down the tubular probe. Manual readings of the water level were

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carried out with an electric contact gauge in piezometer wells near each mDOS location. The annual drought period of

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Fuirosos stream in summer 2015 was characterized by stable dry conditions during the first three weeks at which the onset of

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surface flow cessation coincided with day one of measurements (Fig. 3c). During drought, hydrologic conditions switch

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from surface to subsurface flow corresponding to water-saturated to water-unsaturated sediment conditions. Several

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precipitation events with increasing intensities up to 25 mm/day occurred towards the end of the measurement period.

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(a)

(b)

(c)

288 289 290 291 292

Figure 3 Subsurface oxygen distribution during cessation of surface flow (transition from saturated to unsaturated conditions) in the streambed of Fuirosos stream (a) up- and (b) downstream of a pool-cascade sequence and (c) corresponding hydrologic conditions at both locations and local preicpitation (La Battloria, Spain). For oxygen data, the total profile depth was 55 cm at a spatial resolution of 5 mm with 0 cm corresponding to the sediment-air/water interface.

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Both locations showed a sharp, persistent oxygen transition zone from oxic to anoxic conditions of one or two cm. Absolute

294

depths of water level cannot be linked to respective oxygen profiles due to relative height differences of the sediment surface

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between oxygen and corresponding water level measurements. With the onset of precipitation events from day 28 onwards

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(Fig. 3c), the measurement locations showed deviating patterns for the spatio-temporal oxygen distribution. The ‘upstream’

297

location continued with the general trend of a decreasing anoxic zone while ‘downstream’, the oxic-anoxic transition zone

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shifted upwards remarkably by approx. 30 cm. In both locations, the transition from anoxic bottom to oxic top layers became 16

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more gradual and less sharp. This pattern might have been caused by a stimulation of microbial respiration in previously dry

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sediments that became rewetted, thus supplying water and solutes to microorganisms residing in drying sediments 41–43. Our

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results indeed indicate the water level as primary control of oxic-anoxic zonation, whose temporal and spatial dynamics

302

could be precisely captured by the mDOS system. This water level dependency was pronounced at both locations, as

303

reflected in a clear linear relationship (R2(upstream) = 0.9709 and R2(downstream) = 0.9578) between depth of water level and

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corresponding oxygen penetration throughout the whole drying phase (Figure S5). Interestingly, the slope deviates between

305

both locations: ‘downstream’ it is characterized by a slope of ~1, corresponding to equal rates of descending water levels and

306

oxygen penetration. In contrast, the ‘upstream’ location exhibits a slope of ~0.7, i.e. anoxic conditions prevail in the

307

unsaturated zone. This might likely be attributed to generally different hydrologic conditions between locations. In contrast

308

to the ‘downstream’ location, which was characterized by upwelling groundwater as reflected in the profound rise of water

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levels upon rewetting events (Figure 3c), the upstream location exhibited downwelling conditions40. We found that

310

constantly falling water levels during drying of intermittent streambeds significantly influenced the subsurface spatial O2

311

distribution as revealed by long-term time series. Moreover, these time series also provided novel information on sudden

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small-scale variability within the oxic-anoxic zonation upon rewetting events, accentuating the need for highly resolved

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spatio-temporal oxygen profiling as provided by the mDOS system.

314

3.3

315

Overall, the mDOS has proven its suitability for automated acquisition of O2 profiles in situ to capture both, intra- and inter-

316

day variability. It allows a completely unattended acquisition of oxygen profiles and the profiling depth as well as duration

317

and frequency of measurements can be easily tailored to the specific demands of other applications. The use of a side-firing

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fiber led to a substantial size reduction of the oxygen sensing element to 5 mm from previously 30 mm 22 which substantially

319

simplifies the installation process even in very coarse and gravelly sediments. Here, the disturbance of the natural flow field

320

by the presence of the tubular sensing element can be considered rather small since the sediment scale with regard to

321

sediment size is typically larger than the corresponding “sensing scale” referring to the diameter of the sensing element. The

322

current setup allows the motor unit to be installed sufficiently high to avoid obstruction of surface flow by the motor unit.

Applicability and future potential

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The current need of a solid steel rod for fixation of the motor unit could be overcome by placing the motor unit on a tripod as

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commonly employed for marine sediment profiling.

325

We also want to address current limitations and potential sources of error and uncertainty. First, the tubular sensing element

326

does not incorporate an appropriate protective layer which is troublesome for two reasons: photodegradation (bleaching) of

327

the probe itself and physical disturbance of the measurement by ambient light. Both may cause overall decreasing phase

328

angles leading to overestimated oxygen concentrations22. Among potential solutions, a thin top layer of black silicone seems

329

to be most promising5 but the integration into the manufacturing process of the tubular sensing element requires further

330

development. Previous laboratory tests revealed practical challenges, mainly to adjust the chemical composition of the

331

coating solution suitable for incorporation into the dip-coating process to yield a protective layer that is homogeneous, of

332

desired thickness and adhesive to the underlying sensing film – all while not re-dissolve the previously applied sensing layer.

333

Adhesion of a silicone-based sensing layer could be facilitated by emulsifying the polystyrene-based sensing layer with

334

silicone44. Second, optimizing the quality of the oxygen-sensitive coating of the tubular sensing element in terms of film

335

thickness and homogeneity will reduce spatial sensing variability during calibration and measurements and thus further

336

improve the overall robustness of the whole mDOS system in terms of sensing quality. Third, the current configuration of

337

the mDOS system requires regular maintenance approximately every other day for downloading of acquired data and

338

changing of batteries, depending on the chosen measurement interval. To overcome the latter, future designs will incorporate

339

an OEM board instead of the transmitter, thus allowing the integration of all components into a single architectural

340

framework. The implementation of a data model45 and an overarching cloud-based web service enables remote data access,

341

visualization and adjustments of the measurement routine close to real time. This is particularly powerful in light of recent

342

attempts to implement adaptive monitoring46 and automatic high frequency monitoring in lakes and rivers 47,48.

343

Also, we briefly want to discuss the potential of the mDOS concept for expansion to other analytes as well as the

344

combination of the system with other analytical methods. The mDOS has been designed as modular system to be potentially

345

adapted for other luminescent sensing parameters, e.g. CO2, pH or temperature (T). Additionally, it may even be expanded

346

towards the simultaneous determination of two or more analytes as reported for other optode-based systems5. Of potential

347

combinations, a dual O2/CO2 or O2/T mDOS system should be in the focus of future technical development as these are

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particularly relevant in many biological systems because of the strong coupling between oxygen and CO2 consumption and

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temperature effects. The principle of sandwich sensors to utilize a DGT gel as diffusive layer for the overlying optode

350

sensor49,50 could be theoretically combined with the mDOS system for simultaneous mapping of O2 and chemical species

351

dynamics, particularly trace metals and nutrients. This approach, with O2 serving as potential proxy for redox zonation, could

352

potentially expand our knowledge on the formation of biogeochemical hotspots and hot moments in soils 6,51 and streambeds

353

50,52

354

measurements of the main factors underlying oxygen dynamics in these environments, namely hydrology and diffusion, at

355

the same scale. Hydrologic conditions, e.g. in terms of travel times, can be estimated from variability of naturally occurring

356

tracers like electric conductivity33 or the Rn-222 isotope54 and coupled to oxygen concentration data to estimate aerobic

357

respiration rates.

358

4

359

We thank Peter Portius and Manuel Kositzke for the mechanical construction of the mDOS system and Astrid Harjung for

360

her valuable input and proofreading. The research was funded by the European Union's Seventh Framework for research,

361

technological development and demonstration under grant agreement no. 607150, within the Marie Curie Initial Training

362

Network “INTERFACES: Ecohydrological interfaces as critical hotspots for transformations of ecosystem exchange fluxes

363

and biogeochemical cycling".

, specifically with regard to depth-dependent high reactivity zones53. However, this requires adequate in situ

Acknowledgements

364 365

Supporting information. Details about the dip coating procedure, the control unit, equations and fitting parameters for

366

oxygen calculations, additional plots of oxygen and temperature data.

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