- new sensor systems, using technologies in novel or unintended ways,
- new data storage or transmission solutions sending data from the field with LoRa, WIFI, GSM, or any other nifty approach,
- started initiatives (e.g., Open-Sensing.org) that facilitate the creation and sharing of novel sensors, data acquisition and transmission systems.
Connected a sensor to an Arduino or Raspberri Pi? Used the new Lidar in the new iPhone to measure something relevant for hydrology? 3D printed an automated water quality sampler? Or build a Cloud Storage system from Open Source Components? Show it!
New methods in hydrology, plant physiology, seismology, remote sensing, ecology, etc. are all welcome. Bring prototypes and demonstrations to make this the most exciting Poster Only (!) session of the General Assembly.
This session is co-sponsered by MOXXI, the working group on novel observational methods of the IAHS.
Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) is a well-established technology to determine water heights in reservoirs, rivers, and lakes. A big advantage of GNSS-IR over traditional level measurements is that it is a non-contact flood-proof method. So far, GNSS-IR has been applied through off-site processing, necessitating a good internet connection for near-real-time monitoring. In Africa, where the TEMBO project seeks to develop in situ monitoring of weather and water, such connections are often not available, especially in more remote river valleys. Although a live satellite uplink would be possible, these tend to be costly and very energy-hungry. For this reason, equipment was developed that allowed local processing (edge processing). The advantage is that only water levels and some system information need to be communicated, which can be done with a simple satellite modem at very moderate costs. Existing gnssrefl code (https://gnssrefl.readthedocs.io/), written in Python, was rewritten in Rust to facilitate running the code on a PICO 2. By reducing unneeded lines of code, the runtime was reduced from three minutes with the original Python code to less than three seconds. In all, energy use was minimized to avoid the need for large solar panels. With power cycling and uploads four times per day, the average power consumption was 44mW, which translates into a small solar panel of 1.2 W (66mm x 113mm). Water level measurement accuracy depended on integration time or, better, the number of satellites captured and was about 8cm when five or more satellites were captured. Total material costs, excluding the satellite modem, were about EU 50. The satellite modem and antenna were, at EU 360, the most expensive parts.
TEMBO Africa: The work leading to these results has received funding from the European Horizon Europe Programme (2021-2027) under grant agreement n° 101086209. The opinions expressed in the document are of the authors only and in no way reflect the European Commission’s opinions. The European Union is not liable for any use that may be made of the information.
How to cite: van de Giesen, N., De Laere, T., van Driel, J., van der Bijl, W., and Loen, S.: A Low-Cost Flood-Proof Water Level Measurement System, Using GNSS Reflectrometry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-75, https://doi.org/10.5194/egusphere-egu26-75, 2026.
Wells and boreholes have long served as critical sources of freshwater in the semi-arid and arid regions of Africa. Despite their importance, effective monitoring of these water points remains limited due to the high cost of establishing and maintaining dedicated observation wells, resulting in sparse and unreliable datasets. This study explores a cost-effective approach to groundwater monitoring by equipping operational wells and boreholes with low frequency acoustic sensors integrated into a scalable wireless sensor network. The system enables continuous acquisition of time-series data on water levels, discharge rates, and recharge dynamics. The major innovation here is that we use existing and operational water infrastructure as monitoring points. The presentation will demonstrate the principles, advantages, and obstacles that still need to be overcome. The proposed method improves data availability and supports more sustainable groundwater management across data-scarce regions in Africa.
How to cite: Geofrey, A., Hut, R., and van de Giesen, N.: Acoustic Sensor–Based Borehole Monitoring in Semi-Arid African Regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1566, https://doi.org/10.5194/egusphere-egu26-1566, 2026.
Palmes diffusion tubes are widely used as a low-cost method for measuring ambient nitrogen dioxide (NO2) air pollution. Based on the principle of molecular diffusion, ambient NO2 accumulates as nitrite at the closed end of the tube. After a typical four-week exposure period, the tubes are returned to a laboratory, where the nitrite is dissolved in water, reacted with a colorimetric reagent, and quantified by measuring the resulting color change using a spectrophotometer.
Despite their effectiveness and affordability, Palmes diffusion tubes are still rarely used in Africa. A major reason is that tube preparation and analysis are typically must be carried out in laboratories outside the continent. One key barrier to establishing local Palmes laboratories is the high upfront cost of spectrophotometers required for sample analysis.
While conventional spectrophotometers can measure absorbance across a wide range of wavelengths, most reagent-based colorimetric analyses require only a single wavelength. For Palmes tube analysis, absorbance is measured at 540 nm, corresponding to the maximum absorption of the Griess reagent. Since green LEDs emit light within a narrow waveband close to this absorption peak, they offer a low-cost alternative light source.
We present and will live-demonstrate a simple device that replaces the spectrophotometer in the Palmes tube analysis workflow. The device consists of a 3D-printed light-tight cuvette holder housing a green LED for illumination and a photodiode to measure transmitted light. Measurement results are displayed directly on the device. The system can determine nitrite concentrations with an accuracy of 3 µg/L, corresponding to approximately 0.1 µg/m3 of ambient NO2 for a four-week exposure period—well below the intrinsic uncertainty of the Palmes diffusion method.
Costing only a fraction of a conventional spectrophotometer, this device has the potential to greatly expand in-situ monitoring of NO2 pollution in sub-Saharan Africa without substantially increasing costs. Moreover, it provides a promising proof of concept for developing similar low-cost instruments for other air and water quality applications based on colorimetric measurements.
How to cite: Mijling, B. and Hut, R.: Low-cost spectrophotometer for measuring nitrogen dioxide (NO2) air pollution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12528, https://doi.org/10.5194/egusphere-egu26-12528, 2026.
Measuring open-channel hydraulics is crucial, for example, for deriving discharges from stage observations, estimating travel times for pollutant plumes, and assessing riverbed dynamics. State-of-the-art surveying approaches are typically conducted along predefined cross-sections of the river course, either manually using a flow meter or with instrumented boats. The latter are technologically advanced platforms equipped with electric propulsion, ADCP sensors, and high-precision RTK-GPS and may cost several tens of thousands of US dollars (or euros). To fill data gaps between cross-sections, surveys often rely on longitudinal boat campaigns, which are generally feasible only in larger streams without hydraulic barriers.
To support water authorities with limited budgets, particularly to survey smaller streams, we developed MONIKA, a low-cost surveying catamaran. In accordance with its acronym, MONIKA is comprised of three primary functions: MO - Monitoring (continuous tracking of water parameters), NI - Navigation (movement along and across the stream), and KA - Kartography (mapping of the riverbed morphology). The platform is equipped with a castable sonar, GPS, and two CTD (Conductivity-Temperature-Depth) dataloggers. As an additional payload, a commercial high-precision inclination sensor is deployed to monitor the water surface slope. All data-processing steps are implemented in an object-oriented framework within an open-source Python package.
After extensive testing and design optimization, the engine-less boat can be deployed in two operational modes: (1) bank-guided operation using an aluminum rod and snap hook, and (2) free-floating operation in which the boat is retrieved with a net installed at the downstream end of the study reach. The free-floating mode is particularly suited for surveying riverbed slope, as it avoids operator-induced interference with inclination measurements.
As an initial application, MONIKA, was deployed at two sections of the Spree River (Germany) to support the placement of new sampling stations downstream of a river confluence. MONIKA was used to determine the minimum downstream distance required for complete mixing. Future applications will extend this approach to open-channel surveys in small rivers, with a particular emphasis on data-scarce catchments.
How to cite: Nixdorf, E., Böhmeke, M., and Gatzke, F.: Development of a low-cost water vehicle for surveying river bed elevation and chemo-physical changes along the river course , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4963, https://doi.org/10.5194/egusphere-egu26-4963, 2026.
Reliable radon-222 measurements are essential for a wide range of hydrological, geological, and environmental applications, including the study of surface water - groundwater interactions and the quantification of groundwater discharge. Despite the widespread use of 222Rn detectors, routine verification of instrument performance and measurement stability remains limited, particularly in laboratories with constrained financial and technical resources. This study presents the development and evaluation of a cost-effective rock sample unit designed to support quality control, calibration checks, and inter-laboratory comparison of 222Rn measurements.
The system is based on acidic plutonic igneous rock purchased from commercial suppliers, selected for their naturally elevated and stable 222Rn production. The rocks were enclosed in a simple, airtight container assembled using readily available components, including a standard garden filter and plastic tubing. This configuration allows 222Rn generated within the rock matrix to accumulate in a closed volume and be circulated through commonly used 222Rn detectors without the need for specialized or commercial equipment. Equal amounts of material were placed in each rock sample unit, which were then sealed and stored for 21 days to allow 222Rn to reach secular equilibrium with its parent radionuclides. Initial characterization of the rock units was performed at the IAEA Isotope Hydrology laboratory. Each unit was analysed three times using a standardized protocol consisting of six measurement cycles of 30 minutes each. Measurements were conducted using RAD7 and RAD8 222Rn detectors from Durridge, which are widely applied in environmental and hydrological studies. The results demonstrated stable and reproducible 222Rn concentrations across repeated measurements, confirming the suitability of the rock units as reference sources for quality control purposes.
Following this initial validation, the previously measured rock sample units were distributed to participating laboratories in Argentina, France, Malaysia, and Morocco. Each laboratory applied the same measurement protocol and used their routinely operated 222Rn detectors (RAD7 and RAD8).
To support the interpretation of the observed variability, contextual information was considered, including the age of the instrument, the date of last recalibration, the intensity of use, the type of water typically analysed (saline or non-saline; surface water or groundwater), and the range of 222Rn concentrations normally encountered. This approach enabled the assessment of the significance of deviations under different operating conditions and allowed the evaluation of the robustness of measurements obtained with calibrated versus non-calibrated instruments.
This exercise showed that even simple comparison of 222Rn responses obtained from the rock units provides valuable insight into the performance of the instrument and detect the potential measurement drift related to the lack of calibration. The results demonstrate that these cost-effective rock sample units represent a practical and accessible tool for strengthening 222Rn measurement quality assurance. Their simplicity, low resource requirements, and reproducibility make them particularly suitable for routine checks, contributing to the improved comparability of 222Rn data.
How to cite: Huneau, F., Grondona, S., Santoni, S., Poh, S. C., El Ghali, T., Terzer-Wassmuth, S., and Vital, M.: A cost-effective rock sample unit for quality control and intercomparison of 222Rn measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5086, https://doi.org/10.5194/egusphere-egu26-5086, 2026.
The terrestrial water and nutrient cycle is of crucial importance, influencing the climate, ecosystems, and related services. In many climates, non-rainfall water inputs (NRWIs) play a significant role in the water cycle. These inputs stem from various processes, including dew, fog, and soil water vapour adsorption. Weighable lysimeters are ideal tools for quantifying such water inputs to ecosystems, as their surfaces are either plant- or soil-covered, which is relevant for their formation processes, compared to devices with artificial surfaces. However, the nutrient inputs from dew and fog, apart from wet and dry deposition, are yet to be overlooked, as it is difficult to monitor these hidden nutrient inputs to ecosystems without adequate sampling devices.
We present a newly developed dew collector for the regular collection and analysis of dew samples, for example for stable isotopes, nutrients, and other substances. The lack of automated methods for collecting dew samples represents a significant bottleneck to account for these hidden nutrient inputs. Using a comprehensive measurement setup with weighable lysimeters, wet and dry deposition, and dew and fog water collectors, we show how NRWIs introduce nutrients into ecosystems with different land uses (grassland and cropland) in a temperate climate.
How to cite: Groh, J., Lücke, A., Pütz, T., Engels, F., Funk, R., Sitnikow, A., Beysens, D., and Amelung, W.: Automated sampling of dew water to identify hidden nutrient inputs to ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11522, https://doi.org/10.5194/egusphere-egu26-11522, 2026.
One of the Earth's natural physical fields is the geoelectric field. The conductivity of subterranean medium and the locations of pollution sources, among other things, may be examined by tracking variations in the geoelectric field signal over time. The success rate of resource exploration and the accuracy of geological structure inversion are closely correlated with signal quality. Conventional geoelectric field measurement techniques use electrochemical non-polarizing electrodes to detect the potential difference between two electrodes that are far apart in order to acquire the geoelectric field signal. The potential difference value that exists between the electrodes for their own causes is called the "range difference." Environmental conditions will influence the electrodes' range difference, and the range difference variation amplitude will be greater than the amplitude of the actual geoelectric field signal. Non-polarizing electrodes must be buried deep below during the actual measuring procedure, and electrolyte solutions must be poured to lower the grounding impedance. The electrolyte solution is prone to evaporation or loss in unique environments like deserts and the Gobi, which might result in an abrupt rise in the grounding impedance of the non-polarizing electrodes. This will impact the precision of the geoelectric field signal measurement findings.
This design, which is based on the charge induction principle, aims to create a new kind of electric field sensor that can continuously measure the geoelectric field signal without range differences and does not require the electrodes to be buried. The viability of this sensor is confirmed using physical models and circuit simulations, as well as by contrasting the geoelectric field signal measurement findings of the physical product with those of solid non-polarizing electrodes.
How to cite: Lei, D. and Zhen, Q.: A novel geophysical electric field sensor design and testing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16212, https://doi.org/10.5194/egusphere-egu26-16212, 2026.
Nitrate contamination of surface and groundwater is a serious environmental and public health issue. Identifying the source of this pollutant is an important step in addressing the problem. Nitrogen and oxygen isotopes (δ15N and δ18O values) are a powerful tool for tracing the source(s) of nitrate and understanding processes that impact its cycling in the environment. Traditionally nitrate isotopes are measured via isotope ratio mass spectrometry (IRMS) but in recent years laser spectroscopy has become a practical option.
We evaluated Picarro’s new PI5131-i isotopic and gas concentration analyser for determining bulk δ15N and δ18O values of N2O converted from dissolved nitrate using the Titanium III chloride method. The PI5131-i analyser is based on a robust mid-infrared, laser-based cavity ring-down spectrometry (CRDS) technology. This system when combined with Picarro’s Sage gas autosampler allowed us to analyse the isotopic composition of dissolved nitrate to a level matching IRMS precision and at concentrations as low as 0.05 mg/L NO3-N.
In 40 mL reaction vials, Ti (III) chloride was added to 10 mL sample at a 1:20 ratio (v/v, reagent to sample). After 24 hours of reaction time enough N2O was produced for laser spectroscopy analysis. Prior to analysis, the headspace N2O was transferred into 12 mL exetainers to fit in the Sage autosampler. We compared a direct transfer protocol where 2 mL N2O from the reaction vial is injected into exetainers and a 2-steps protocol where the N2O is injected into purged exetainers (evacuated and pressurized with synthetic air).
Both transfer methods performed well in a blind nitrate intercomparison exercise (NICO). The direct transfer workflow required fewer preparation steps but required a blank correction, whereas the two-step protocol was more labour-intensive due to the purge and fill process.
How to cite: McKay, J., Douence, C., Hofmann, M., Woźniak, J., and Bhattacharya, J.: Analysis of Nitrate Stable Isotopes by Cavity Ring-Down Spectroscopy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18536, https://doi.org/10.5194/egusphere-egu26-18536, 2026.
Rewetted peatlands exhibit strong small-scale, spatio-temporal variability in their greenhouse gas (GHG; CO₂, CH₄ and N₂O) emissions. Those are shaped by water table dynamics, vegetation structure, and microclimate. Capturing “hotspots” and “hot moments” across heterogeneous peatlands typically requires dense instrumentation. However, conventional monitoring solutions remain expensive, difficult to scale, and often depend on commercial, vendor-locked systems. We present the Environmental Variables Explorer (EVE) as a low-cost, modular, open-source alternative that enables researchers to build, repair, adapt, and self-host their monitoring stack without vendor lock-in.
EVE is a platform blueprint rather than a single device. It combines low-power microcontroller nodes with power-saving duty cycling and two interoperable end-to-end, full user controlled workflows. The first, offline workflow, provides robust timestamped local storage (RTC + FRAM) with Bluetooth retrieval via a custom Android app - suited for remote sites. The second, online workflow, uses an ESP32 IoT node to upload measurements via Wi-Fi to a self-hosted PHP/MySQL backend that provides a web dashboard, API access, data visualization and data export (as CSV file) on inexpensive shared hosting. Critically, the offline-online duality provides a “fallback” logic for intermittently connected peatland environments and supports gradual scaling from single devices to multi-site networks.
Building on EVE’s user-controlled pipeline, we present a pathway toward transferable near-real-time analytics by adding chamber-based GHG modules (low-cost CO₂/CH₄ sensing and chamber automation/sampling workflows. Integrating data-driven models (Random Forest and related methods) to estimate flux dynamics and annual budgets across 2-3 sites. Explicitly comparing high-end versus minimal low-cost inputs. By releasing hardware designs, firmware, backend code, and build documentation, this work aims to lower barriers for peatland and other scientists to deploy reproducible monitoring networks and to move toward shared, community-driven approaches for scalable GHG observation and modeling.
How to cite: Kretzschmar, M. S., Dubbert, M., Lück, M., Asante, M., Sossa, G., and Hoffmann, M.: EVE: a low-cost, modular, end-to-end monitoring pipeline for environmental variables and GHG in rewetted peatlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19260, https://doi.org/10.5194/egusphere-egu26-19260, 2026.
Water quality monitoring networks face an inherent trade-off between measurement precision and spatial-temporal coverage. We present an open-source smart water quality buoy designed to explore the potential of maximising deployment density and sampling frequency through low-cost instrumentation combined with AI-enhanced analytics.
The stable buoy enclosure was developed using computational fluid dynamics, water flume validation, and extensive field testing. Initially designed for 3D-printing, it houses three sensors (temperature, turbidity and conductivity) with an ATmega328P microcontroller, real-time clock, flash logging, and/or LoRaWAN connectivity. Laboratory calibration established measurement reliability suitable for network-scale deployment.
Field deployments have demonstrated autonomous operation with a relatively light monthly maintenance protocol. This platform enables novel monitoring approaches that leverage density over individual sensor accuracy. Initial Machine Learning models trained on national databases (millions of observations) convert basic sensor measurements into estimates of complex parameters — nutrients, dissolved oxygen, and bacteria — with encouraging accuracy. The high-frequency data from dense sensor networks enables automated pollution detection by analyzing concentration dynamics and comparing them against patterns learned from a large database of water quality measurements.
By combining accessible hardware with AI analytics, we investigate whether prioritising spatial-temporal resolution can advance water quality monitoring capabilities, particularly for early pollution detection and regulatory compliance in under-resourced catchments.
How to cite: Rowan, T., Noriega Gimenez, J., Jia, Y., Tang, Y., Howard, B., Kelleher, L., Tumelty, L., Packman, A., Paschalis, A., Krause, S., and Buytaert, W.: Low-Cost Water Quality Buoys: Open-Source Design and AI-Enhanced Monitoring , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21344, https://doi.org/10.5194/egusphere-egu26-21344, 2026.
The emergence of Unmanned Aerial Systems (UAS) has revolutionized environmental monitoring by bridging the gap between stationary ground-based stations and coarse-resolution satellite imagery. However, integrating high-fidelity sensors into lightweight platforms remains a challenge due to strict Size, Weight, and Power (SWaP) constraints. This study presents the development and deployment of an advanced, portable sensing payload designed for high-resolution environmental data collection.
The integrated payload consists of a suite of low-cost yet calibrated sensors capable of measuring Isme PM2.5, CO2, NH4, Smoke and O3 at high temporal frequencies. To ensure data integrity, the system incorporates an onboard microprocessor for real-time data fusion, GPS-tagging, and active aspiration systems to mitigate the effects of rotor wash and thermal interference.
Preliminary field campaigns were conducted across two locations (Dehradun, Uttarakhand and New Delhi) to evaluate the system’s performance. Results indicate that the payload provides vertical and horizontal spatial resolutions previously unattainable with traditional methods. This work highlights the potential of modular UAS payloads to provide actionable insights into boundary layer dynamics and pollutant dispersion in complex terrains.
To ensure data integrity, the platform integrates active aspiration systems designed to decouple sensor readings from the effects of rotor wash and localized thermal artifacts. Initial experiments demonstrate that the payload achieves high-granularity in vertical and horizontal spatial resolutions.
How to cite: Natoo, A.: Developing a Lightweight UAS sensing Payload for Environmental Data collection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21545, https://doi.org/10.5194/egusphere-egu26-21545, 2026.
Grassed waterways (GWW) are a nature-based solution in agricultural catchments to reduce surface runoff and soil erosion. However, continuous measurements of surface runoff in a GWW remain challenging, limiting knowledge of how to construct a measurement station to obtain reliable data. Furthermore, these limitations restrict our understanding of hydrological processes and the effectiveness of GWWs. In this study, we present a monitoring station designed to measure surface runoff and quantify soil erosion from a 6 ha agricultural sub-catchment, and discuss the opportunities and limitations of monitoring runoff, sediments, and nutrients in a managed GWW. This study is part of the overall 66 ha catchment at the HOAL (Hydrological Open-Air Laboratory), Austria.
We developed an H-Flume-like structure that reliably quantifies flow without disturbing the GWW’s function. Non-contact radar probes measure the height and velocity of runoff in the structure, allowing discharge calculations during runoff events. When a specified runoff height is detected, an automatic water sampler collects water for further analysis, such as sediment quantification. Thermal and optical cameras are mounted on the structure to capture images from upslope, the structure itself, and downslope, providing several perspectives for visual documentation of runoff processes and sediment transport.
While complementary measurements and modelling support the understanding of the overall effectiveness of the GWW in the HOAL catchment, this station provides valuable information on the timing of runoff, peak flow reduction, and catchment connectivity. The integrated sensor network at this station and throughout the HOAL - including rain gauges, soil moisture sensors, and additional runoff stations - enables a process-based understanding of how grassed waterways affect surface runoff, pluvial floods, and sediment and nutrient transport towards the stream.
This methodology remains under active development, and we encourage community input on improvements to the current methodologies and suggestions for additional observations. This presentation aims to share our current design, present preliminary results, and foster collaborative discussion on advancing monitoring of vegetated, nature-based erosion control structures.
How to cite: Konzett, M., Strauss, P., Thoma, C., Marjanovic, D., Szeles, B., Blöschl, G., and Schmaltz, E.: In a Grassed Waterway the grass is always greener – and surface runoff a challenge to measure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23048, https://doi.org/10.5194/egusphere-egu26-23048, 2026.
Water sampling is essential for assessing the quality of rural and urban water systems. As part of the NERC-NSFGEO SMARTWATER project we aim to diagnose pollution “hot spots” and “hot moments” within watersheds defined as locations and times of pollution transport. To understand and diagnose pollutant dynamics we are forming a smart monitoring network consisting of offline and online sensors, low-cost proxy sensor measurements, and event-based sample collection using autosamplers.
To address existing autosampler constraints, we have developed a smart online autosampler that can be triggered either by a float switch or remotely through a LoRa network. The system is optimised for low-power operation using 12V electronics, light and smaller lithium-based batteries, power optimised Arduino controller, LoRa shield, commercial solenoid values and relays. Laboratory testing has validated the system operation and effective flushing of water between sampling bottle fills. Field deployment along our urban observatory, the Birmingham Urban River Observatory, a UNESCO Intergovernmental Hydrological Programme site, demonstrated performance comparable to standard systems.
This open-source design enables scalable, cost-effective monitoring of river water quality, facilitating improved spatial and temporal assessment across multiple catchments. SMARTWATER: https://www.smart-water.org.uk/
How to cite: Kelleher, L. and Khamis, K. and the SMARTWATER Team: SMARTWATER: low-cost, open-source portable water autosampler for environmental monitoring, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23272, https://doi.org/10.5194/egusphere-egu26-23272, 2026.
