Thermal Signal Research Articles

13C-Formate as an indirect low-temperature 1H lineshape polarimeter

1H polarization quantification is important for dissolution-dynamic nuclear polarization (dDNP) but can be cumbersome due to the requirement of acquiring thermal equilibrium signals and measurements that are complicated by large background signals. 1H nuclear magnetic resonance (NMR) spectra can also be deleteriously influenced by line distortions linked with radiation damping from 1H DNP and cannot be used for accurate calculation of 1H polarization. Determining 1H polarization via immediate 13C lineshape analysis of a simple molecule removes such complications. We present 13C-sodium formate as a straightforward system for indirect 1H polarimetry. The 13C NMR spectra acquired under dDNP conditions have distinct features that are readily reproduced with 13C lineshape simulations. 1H polarizations built-up during 1H DNP were indirectly inferred by fitting simulations to 13C lineshapes. We provide the MATLAB scripts used for 13C lineshape analysis in order that the method can be readily implemented in other laboratories.

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs2LiYCl6:Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6Li(n,α) and 35Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252Cf source, an array of EJ-309 organic liquid scintillators, and a 6Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

Towards the Automation of Non-destructive Fault Recognition: Enhancement of Robustness and Accuracy Through AI Powered Acoustic and Thermal Signal Analysis in Time, Frequency- and Time-Frequency Domains

AbstractNon-destructive inspection and analysis techniques are crucial for quality assessment and defect analysis in various industries. They enable for screening and monitoring of parts and products without alteration or impact, facilitating the exploration of material interactions and defect formation. With increasing complexity in microelectronic technologies, high reliability, robustness and thus, successful failure analysis is essential. Machine learning (ML) approaches have been developed and evaluated for the analysis of acoustic echo signals and time-resolved thermal responses for assessing their ability for defect detection. In the present paper different ML architectures were evaluated, including 1D and 2D convolutional neural networks (CNNs) after transforming time domain data into the spectral- and wavelet domains. Results showed that 2D CNNs processing data in wavelet domain representation performed best, however at the expense of additional computational effort. Furthermore, ML-based analysis was explored for lock-in thermography to detect and locate defects in the axial dimension based on thermal emissions. While promising, further research is needed to fully realize its potential.

A novel mechanical design of a bolometric array for the CROSS double-beta decay experiment

The CROSS experiment will search for neutrinoless double-beta decay using a specific mechanical structure to hold thermal detectors. The design of the structure was tuned to minimize the background contribution, keeping an optimal detector performance. A single module of the structure holds two scintillating bolometers (with a crystal size of 45 × 45 × 45 mm and a Ge slab facing the crystal's upper side) in the Cu frame, allowing for a modular construction of a large-scale array. Two designs are released: the initial Thick version contains around 15% of Cu over the crystal mass (lithium molybdate, LMO), while this ratio is reduced to ∼ 6% in a finer (Slim) design. Both designs were tested extensively at aboveground (IJCLab, France) and underground (LSC, Spain) laboratories. In particular, at LSC we used a pulse-tube-based CROSS facility to operate a 6-crystal array of LMOs enriched/depleted in 100Mo. The tested LMOs show high spectrometric performance in both designs; notably, the measured energy resolution is 5–7 keV FWHM at 2615 keV γs, nearby the Q-value of 100Mo (3034 keV). Due to the absence of a reflective cavity around LMOs, a low scintillation signal is detected by Ge bolometers: ∼ 0.3 keV (150 photons) for 1-MeV γ(β) LMO-event. Despite that, an acceptable separation between α and γ(β) events is achieved with most devices. The highest efficiency is reached with light detectors in the Thick design thanks to a lower baseline noise width (0.05–0.09 keV RMS) when compared to that obtained in the Slim version (0.10–0.35 keV RMS). Given the pivotal role of bolometric photodetectors for particle identification and random coincidences rejection, we will use the structure here described with upgraded light detectors, featuring thermal signal amplification via the Neganov-Trofimov-Luke effect, as also demonstrated in the present work.

Pseudo-noise pulse-compression thermography: A powerful tool for time-domain thermography analysis

Pulse-compression is a correlation-based measurement technique successfully used in many nondestructive evaluation applications to increase the signal-to-noise ratio in the presence of huge noise, strong signal attenuation or when high excitation levels must be avoided. In thermography, the pulse-compression approach was firstly introduced in 2005 by Mulavesaala and co-workers [1], and then further developed by Mandelis and co-authors that applied to thermography the concept of the thermal-wave radar developed for photothermal measurements [2-3]. Since then, many measurement schemes and applications have been reported in the literature by several groups by using various heating sources, coded excitation signals, and processing algorithms. The variety of such techniques is known as pulse-compression thermography or thermal-wave radar imaging.Even despite the continuous improvement of these techniques during these years, the advantages of using a correlation-based approach in thermography are still not fully exploited and recognized by the community. This is because up to now the reconstructed thermograms' time sequences after pulse-compression were affected by the so-called sidelobes, i.e. the temperature time trends of the pixels exhibit oscillations, especially in the cooling stage, so that they do not reproduce the output of a standard thermography measurement. This is a severe drawback since it hampers an easy interpretation of the data and their comparison with other thermography techniques.To overcome this issue and unleash the full potential of the approach, this paper shows how it is possible to implement a pulse-compression thermography procedure capable of suppressing any sidelobe by using a pseudo-noise excitation and a proper processing algorithm.At the end of the procedure, time-sequences of thermograms are reconstructed that correspond to the sample response to a well-defined virtual excitation, namely a rectangular pulse, making the pulse-compression procedure “transparent”. This allows the analysis of pixel time trends by using thermal theory-driven processing such as thermal signal reconstruction, pulsed-phase thermography, etc. Moreover, by tuning the characteristic of the pseudo-noise excitation, it is possible to pass from simulating a very short excitation pulse, retrieving results analogous to pulsed-thermography, to simulating long-pulse excitation to match the sample spectral characteristics maximizing the signal-to-noise ratio. This makes the procedure very flexible and extremely attractive in many applications such as high-attenuating materials, characterization of fast thermal phenomena, and inspection of fragile samples inspection, e.g. paintings or other artworks, etc.

Thermal regime of High Arctic tundra ponds, Nanuit Itillinga (Polar Bear Pass), Nunavut, Canada

Abstract. This study evaluates the seasonal and inter-seasonal temperature regime of small tundra ponds ubiquitous to an extensive, low-gradient wetland in the Canadian High Arctic. Pond temperatures can modify evaporation and ground thaw rates, impact losses of greenhouse gases, and control the timing and emergence of insects and larvae critical for migratory-bird feeding habits. We focus our study on thaw ponds with a range of hydrologic linkages and sizes across Nanuit Itillinga, formerly known as Polar Bear Pass (PBP), Bathurst Island, and compare their thermal signals to other Arctic ponds. Pond temperatures and water levels were evaluated using temperature and water level loggers and verified by regular manual measurements. Other environmental data collected included microclimate, frost table depths, and water conductivity. Our results show that there is much variability in pond thermal regimes over seasons, years, and space. Cumulative relative pond temperatures were similar across years, with ponds normally reaching 10–15 °C for short to longer periods, except in 2013, which experienced a cold summer season during which pond temperatures never exceeded 5 °C. Pond frost tables and water conductivities respond to variable substrate conditions and pond thermal patterns. This study contributes to the ongoing discussion on climate warming and its impact on Arctic landscapes.

Anti-Inflammatory, Antinociceptive, and LC-MS Metabolic Profile from Pseudotrimezia juncifolia (Klatt) Lovo & A. Gil.

Pseudotrimezia juncifolia (Klatt) Lovo & A. Gil (Iridaceae) is a popularly known species with primarily ornamental economic interest. It has traditional uses as purgative, in conditions related to the menstrual cycle, for blood purification, as wound healing, and as anti-inflammatory. The anti-inflammatory and antinociceptive activities of the decoction from its aerial stems, corms, and stamens are described here with dereplication studies on LC-MS/MS supported by the GNPS platform, where phenolic compounds were annotated and correlated with its biological activity. The decoction was evaluated in chemical (formalin and capsaicin) and thermal (hot plate) induced nociception or carrageenan-induced inflammation in mice. Decoction (at 10, 30, or 100 mg/kg doses) significantly reduced formalin- or capsaicin-induced nociception. All doses also demonstrated an antinociceptive effect in the hot plate model increasing the time the animal spent in responding to thermal signal. Naloxone partially reversed the antinociceptive effect. An anti-inflammatory effect was observed since a reduction in cell migration, protein extravasation interleukin-1, and tumor necrosis factor production induced by carrageenan in the subcutaneous air pouch was quantified. Metabolomic analyses showed a predominance of phenolic substances, mainly flavonoids and chlorogenic acids. The literature showed that these two groups have significant anti-inflammatory and analgesic activity, and chemical data corroborate the pharmacological results observed.

ISLAND: Interpolating Land Surface Temperature using land cover

Cloud occlusion is a common problem in the field of remote sensing, particularly for retrieving Land Surface Temperature (LST). Remote sensing thermal instruments onboard operational satellites are supposed to enable frequent and high-resolution observations over land; unfortunately, clouds adversely affect thermal signals by blocking outgoing longwave radiation emission from the Earth’s surface, interfering with the retrieved ground emission temperature. Such cloud contamination severely reduces the set of serviceable LST images for downstream applications, making it impractical to perform intricate time-series analysis of LST. In this paper, we introduce a novel method to remove cloud occlusions from Landsat 8 LST images. We call our method ISLAND, an acronym for Interpolating Land Surface Temperature using land cover. Our approach uses LST images from Landsat 8 (at 30m resolution with 16-day revisit cycles) and the NLCD land cover dataset. Inspired by Tobler’s first law of Geography, ISLAND predicts occluded LST through a set of spatio-temporal filters that perform distance-weighted spatio-temporal interpolation. A critical feature of ISLAND is that the filters are land cover-class aware, making it particularly advantageous in complex urban settings with heterogeneous land cover types and distributions. Through qualitative and quantitative analysis, we show that ISLAND achieves robust reconstruction performance across a variety of cloud occlusion and surface land cover conditions, and with a high spatio-temporal resolution. We provide a public dataset of 20 U.S. cities with pre-computed ISLAND LST outputs. Using several case studies, we demonstrate that ISLAND opens the door to a multitude of high-impact urban and environmental applications across the continental United States.

Cortical Coding of Gustatory and Thermal Signals in Active Licking Mice.

Eating behaviors are influenced by the integration of gustatory, olfactory, and somatosensory signals, which all contribute to the perception of flavor. Although extensive research has explored the neural correlates of taste in the gustatory cortex (GC), less is known about its role in encoding thermal information. This study investigates the encoding of oral thermal and chemosensory signals by GC neurons compared to the oral somatosensory cortex. In this study, we recorded the spiking activity of more than 900 GC neurons and 500 neurons from the oral somatosensory cortex in mice allowed to freely lick small drops of gustatory stimuli or deionized water at varying non-nociceptive temperatures. We then developed and used a Bayesian-based analysis technique to assess neural classification scores based on spike rate and phase timing within the lick cycle. Our results indicate that GC neurons rely predominantly on rate information, although phase information is needed to achieve maximum accuracy, to effectively encode both chemosensory and thermosensory signals. GC neurons can effectively differentiate between thermal stimuli, excelling in distinguishing both large contrasts (14°C vs. 36°C) and, although less effectively, more subtle temperature differences. Finally, a direct comparison of the decoding accuracy of thermosensory signals between the two cortices reveals that while the somatosensory cortex showed higher overall accuracy, the GC still encodes significant thermosensory information. These findings highlight the GC's dual role in processing taste and temperature, emphasizing the importance of considering temperature in future studies of taste processing.

Unravelling molecular interactions in various alcohol-water binary mixtures using femtosecond laser-induced thermal lens spectroscopy

The FTLS (femtosecond laser-induced thermal lens spectroscopy) technique was utilized to explore the photothermal response and heat transfer dynamics in various water-based binary mixtures containing monohydric and polyhydric alcohols. Our results highlight the significant influence of intermolecular hydrogen bonding interactions and the molecular properties of the mixture constituents on the photothermal behavior of both pure solvents and their binary mixtures. Notably, we observed distinct effects of water inclusion on the heat transfer characteristics of monohydric alcohols (such as methanol and ethanol) compared to polyhydric alcohols (such as ethylene glycol (Etg) and glycerol (Gly)). This discrepancy can be attributed to the formation of unique molecular structures via hydrogen bonding interactions, which effectively hinders the natural molecular dynamics of short-chain length alcohols. Conversely, polyhydric alcohols like Etg and Gly exhibit contrasting photothermal characteristics due to their extensive intermolecular hydrogen bonding. Our investigations reveal that molecular attributes, such as chain length and the number of hydroxyl (-OH) groups, play a crucial role in altering the heat transfer mechanisms and thermal lens signal characteristics of the mixtures. These findings emphasize the sensitivity of FTLS as a probe for understanding the effects of intermolecular hydrogen bonding interactions on the molecular dynamics and thermo-optical properties of aqueous-alcoholic solutions.

Single-Shot MRI in parahydrogen hyperpolarized samples

The site-specific signal enhancement provided by parahydrogen induced polarization (PHIP) may be combined with magnetic resonance imaging (MRI) to study chemical and biomolecular processes. However, imaging of hydrogen nuclei (1H) is hampered by background signals arising from the presence of thermally polarized nuclei. Additionally, fast imaging sequences are commonly based on multiple radio-frequency pulses, where the signals resulting from PHIP oscillate due to the evolution with a J-coupling Hamiltonian. In this article, an innovative imaging scheme for single-scan MRI is presented that effectively detects hyperpolarized components while simultaneously canceling out thermal contributions. This method is based on the quenching of inherent oscillations of PHIP-originated signals due to J-couplings during the multipulse sequence and the suppression of thermal signals by spin dynamics and a tailored restructuring of the k-space. A series of numerical simulations on specific two- and three-spin systems serve to support the feasibility of the approach. Furthermore, this theoretical study demonstrates the potential of combining hyperpolarization and long-lived states (PHIP and LLS) in the selected molecules, which could be seen as a preliminary step towards the development of fast imaging techniques, for example in the field of biomolecular research.

A study of expansion force propagation characteristics and early warning feasibility for the thermal diffusion process of lithium-ion battery modules

Research on thermal runaway warning and thermal propagation mechanism is of great importance for improving the thermal safety of lithium-ion batteries. This article focuses on the battery modules and examines the feasibility of using expansion force as thermal runaway warning signals. Results show that the utilization of the expansion force can detect battery failure 1314.61 s earlier and provide thermal runaway warnings 26 s earlier compared to that of temperature. This suggests that the use of the expansion force at the battery module level still shows good feasibility. In addition, the fluctuation mechanism of the expansion force during thermal propagation is further discussed by conducting experiments on the thermal propagation of modules with different sizes. Experimental results show that the superposition effect of adjacent battery expansion forces is the main influencing factor causing expansion force changes with two peaks. The fluctuation mechanism of expansion force can characterize the gas discharge behaviors of thermal runaway at different stages, such as the opening of pressure relief valves and multi-stage gas discharge during thermal runaway.

Active Control of Temperature‐Sensitive GaN‐Graphene van der Waals Heterojunctions Integrated Metasurfaces: A Platform for Multifunctional Micro–Nanophotonic Devices

AbstractVan der Waals (vdW) heterojunctions composed of GaN/graphene have high transmittance and excellent carrier transport properties. The combination of multidimensional hybrid heterojunctions with metasurfaces can open up many fascinating prospects for novel optical components over a broad range of the electromagnetic spectrum. This work experimentally demonstrates a multifunctional temperature‐sensitive meta‐device based on GaN/graphene vdW heterojunctions integrated with a metasurface. Notably, it is discovered that the conductivity of the vdW heterojunctions increases rapidly when it is excited by a thermal signal, resulting in a significant change in the relative phase retardation as well as amplitude modulation of an incident THz wave. Then a continuous wavelet transform is used instead of the traditional Fourier transform, and the two‐dimensional wavelet coefficient card is built to achieve fast detection over a wider range of temperature. Simultaneously, the variation of temperature dynamically controls the contributions of the multipoles, eventually determining the active switching of exotic anapoles with extreme non‐radiative confinement to highly radiative electric dipoles. This work offers the possibility of designing novel chip‐scale multifunctional thermal tuning devices and promotes the potential application of active micro‐nanophotonic devices in temperature sensors, terahertz modulators, and dynamic near‐field imaging.

Sunyaev-Zeldovich signatures from non-thermal, relativistic electrons using CMB maps

Relativistically energetic, non-thermal population of electrons can give rise to unique CMB spectral distortion signatures which can be significantly different from thermal Sunyaev-Zeldovich signal or y-distortion. These signatures depend upon the spectrum of non-thermal electrons, therefore, a detection can inform us about the existence and abundance of non-thermal electrons in our universe. Using public CMB maps and data, we derive upper limits on non-thermal y-parameter for a relativistic, power-law electron distribution. With future CMB experiments, we may be in a position to detect or put significantly tighter constraints on these signals which can affect our understanding of non-thermal electron distributions in our universe.

Nugget and corona bond size measurement through active thermography and transfer learning model

Resistance spot welding (RSW) is considered a preferred technique for joining metal parts in various industries, mainly for its efficiency and cost-effectiveness. The mechanical properties of spot welds are pivotal in ensuring structural integrity and overall assembly performance. In this work, the quality attributes of resistance spot welding, such as both nugget and corona bond sizes, are assessed by analyzing the thermal behavior of the joint using a physical information neural network (PINN). Starting from the thermal signal phase gradient and amplitude gradient maps, a convolutional neural network (CNN) estimates the size of nuggets and corona bonds. The CNN architecture is based on the Inception V3 architecture, a state-of-the-art neural network that excels in image recognition tasks. This study suggests adopting a new methodology for automatic RSW quality control based on thermal signal analysis.

Cyclone‐Like Features Within the Stratospheric Polar‐Night Vortex

AbstractDistinctive synoptic‐scale (∼1,500 km) flow features are identified within the core of the stratospheric polar‐night vortex at stratopause altitudes (∼50 km). Typically they comprise a train or a complex pattern of transient vortices, each characterized by enhanced values of potential vorticity (PV) and relative vorticity but with a weaker thermal signal. In the MERRA‐2 (and two other) reanalysis fields these cyclone‐like features persist for several days, occur episodically, and form essentially within the core of the polar‐night vortex itself. Their origin is plausibly linked to a form of barotropic instability associated with a radiatively‐induced annular ring of enhanced PV. Moreover, their ubiquity and dynamics carries possible implications for: ‐ the structure of the larger‐scale polar vortex and its preconditioning ahead of a Sudden Stratospheric Warming event; the distribution of trace‐constituents within the core; and the features representation in extended range/seasonal prediction and climate models.

Analysis of Transient Current and Heat Flow during Voltage Holds: For Relaxed and Unrelaxed G/NMC811 Cells

This study investigates the transient heat flow during voltage holds for multi-layer pouch G/NMC811 lithium-ion cells. When applying a voltage hold to estimate the amount of parasitic side reactions, there is first a transient phase followed by a steady state. According to the literature, reversible processes mainly influence the transient phase, while the steady state presents the side reaction current. This work investigates the contributions to the transient behavior, evaluating the thermal and electrical signals and deconvoluting the different parasitic side reactions. In addition, a comparison between relaxed and unrelaxed states is performed, analyzing different temperatures and voltages. The results show that the relaxed graphite cells quickly reached a constant parasitic heat flow value with minimal transient effects. In contrast, the unrelaxed cells presented increased transient effects in the parasitic heat flow signal that can last more than 300 h. The electric transient originates mainly from anode overhang effects and SEI regrowth, while the thermal transient consists predominantly of SEI regrowth. Overall, the thermal signals stabilize faster than the electrical signals, giving calorimetry an advantage for faster estimation of parasitic side reactions.

Frequency Domain Thermal Analysis of Future Spacecraft and Systems

Future space telescopes require tight thermomechanical stability. The thermal analysis may be based on a nonlinear steady solution with a superimposed linear transient perturbation. This linearity allows frequency domain (FD) thermal solutions that retain high resolution when scaled. Linearity allows generality through superposition. Linear superelements can represent subsystems and thereby simplify interfaces. The (rare) prior spacecraft FD thermal analyses have been with N×N system matrices, converting lumped parameter (LP) time domain models to FD. This paper includes continuously distributed resistance and capacitance elements. Exact distributed element results differ greatly from LP renditions at higher frequency. Two FD methods are used together: a 2×2 matrix method with a bridge to an N×N matrix method. The 2×2 method allows the combination of elements in series/parallel configurations into overall elements. The 2×2 matrices can then be used in an N×N system matrix formulation. This paper includes FD analysis and programming methods, FD testing methods, and model to data comparisons. A thermal signal generator was developed for FD testing.

Land Surface Longwave Radiation Retrieval from ASTER Clear-Sky Observations

Surface longwave radiation (SLR) plays a pivotal role in the Earth’s energy balance, influencing a range of environmental processes and climate dynamics. As the demand for high spatial resolution remote sensing products grows, there is an increasing need for accurate SLR retrieval with enhanced spatial detail. This study focuses on the development and validation of models to estimate SLR using measurements from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. Given the limitations posed by fewer spectral bands and data products in ASTER compared to moderate-resolution sensors, the proposed approach combines an atmospheric radiative transfer model MODerate resolution atmospheric TRANsmission (MODTRAN) with the Light Gradient Boosting Machine algorithm to estimate SLR. The MODTRAN simulations were performed to construct a representative training dataset based on comprehensive global atmospheric profiles and surface emissivity spectra data. Global sensitivity analyses reveal that key inputs influencing the accuracy of SLR retrievals should reflect surface thermal radiative signals and near-surface atmospheric conditions. Validated against ground-based measurements, surface upward longwave radiation (SULR) and surface downward longwave radiation (SDLR) using ASTER thermal infrared bands and surface elevation estimations resulted in root mean square errors of 17.76 W/m2 and 25.36 W/m2, with biases of 3.42 W/m2 and 3.92 W/m2, respectively. Retrievals show systematic biases related to extreme temperature and moisture conditions, e.g., causing overestimation of SULR in hot humid conditions and underestimation of SDLR in arid conditions. While challenges persist, particularly in addressing atmospheric variables and cloud masking, this work lays a foundation for accurate SLR retrieval from high spatial resolution sensors like ASTER. The potential applications extend to upcoming satellite missions, such as the Landsat Next, and contribute to advancing high-resolution remote sensing capabilities for an improved understanding of Earth’s energy dynamics.

Recent advances in vertical temperature profiler instrumentation and flux estimation methods facilitate groundwater – Surface water exchange studies in environments with strong discharge zones

Groundwater fluxes to many surface water systems are spatially heterogeneous with discharge focused into discrete, high-flux zones. Quantifying fluxes in these preferential discharge zones is critical to a range of surface water habitat and water quality processes, but characterization can be difficult due to short-scale spatial and temporal variability. Passive heat-as-a-tracer methods employing vertical temperature profiler (VTP) data can provide the necessary spatial and temporal resolution, but upward fluid flow strongly attenuates the thermal signals used for estimating fluxes. In preferential discharge zones it becomes difficult to measure the signals in the subsurface and the flux parameter can become insensitive in the analysis models, leading to large uncertainties. We use data from a high-flux site of contaminant-loaded groundwater discharge to the Quashnet River on Cape Cod, Massachusetts, USA, to demonstrate how recent advances in VTP instrumentation that allow for the acquisition of high-resolution (0.001 °C) temperature data at short (1 cm) offsets near the ground surface, combined with advances in flux estimation methods that exploit the information content of the high-resolution data, facilitate heat-as-a-tracer approaches for characterizing groundwater-surface water exchanges and make it possible to obtain accurate and statistically robust results in a preferential discharge zone with a specific discharge of ∼1 m/d.