HS1.2.1 | The MacGyver session for innovative and/or self made tools to observe the geosphere, including frontiers in river flow monitoring
The MacGyver session for innovative and/or self made tools to observe the geosphere, including frontiers in river flow monitoring
Co-organized by BG2/GI1
Convener: Rolf Hut | Co-conveners: Theresa Blume, Marvin Reich, Andy Wickert, Salvador Peña-Haro, Gabriel Sentlinger, Christoph Sommer
Posters on site
| Attendance Mon, 24 Apr, 16:15–18:00 (CEST)
Hall A
Posters virtual
| Attendance Mon, 24 Apr, 16:15–18:00 (CEST)
vHall HS
Mon, 16:15
Mon, 16:15
The MacGyver session focuses on novel sensors made, or data sources unlocked, by scientists. All geoscientists are invited to present:
- 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.

The MacGyver session this year teams up with the Frontiers in river flow monitoring session. The 'author in attendance' blocks are in the early morning and late afternoon. In between those two block we organize a field session with hands-on on different state of the art hydrometry techniques. Bring your own measurement system and show case it, or join us to see others demonstrate their devices! Details on this field trip:

Monday, 24th of April, 10:30 to 16:00 hrs
Departure by bus at 10:30 hrs from AVC Center
Platz der Vereinten Nationen close to underground station Kaisermühlen VIC
Lunch and beverages will be provided

If you are interested please send us an email: pena@photrack.ch

This session is co-sponsered by MOXXI, the working group on novel observational methods of the IAHS.

Posters on site: Mon, 24 Apr, 16:15–18:00 | Hall A

The on-site MacGyver session
Mathias Hoffmann, Wael Al Hamwi, Matthias Lück, Marten Schmidt, and Maren Dubbert

Determining greenhouse gas (GHG) fluxes, water (ET) fluxes and their interconnectivity within the soil-plant-atmosphere-intersphere is crucial, not only when aiming to find solutions for current agricultural systems to mitigate the global climate crises but also to adapt them to related challenges ahead, such as more frequent and severe droughts. In a first attempt for a better understanding, often laboratory and/or greenhouse pot experiments are performed, during which gas exchange is predominately measured using especially manual closed chamber systems. Commercially available systems to determine gas exchange in terms of CO2 and ET are, however, costly and measurements itself labour-intensive. This limits the amounts of variables to be studied as well as possible repetitions during a study. Additionally, it resulted in the long-term focus on agroecosystems of the northern hemisphere while agroecosystems of sub-Saharan Africa as well as Southeast Asia are still being underrepresented.

We present an inexpensive (<1.000 Euro), Arduino based, multi-chamber system to semi-automatically measure 1) CO2 and 2.) ET fluxes. The systems consists of multiple, self-sufficient, closet-shaped PVC “coffins”. The “coffins” a closed by a frontal door and periodically ventilated through a sliding window. Relays connected to the microcontroller are used to steer closure/opening (linear actuator) and ventilation (axial fans). CO2 and ET fluxes are determined through the respective concentration increase during closure by a low-cost NDIR CO­2 (K30FR; 0-10,000 ppm, ± 30 ppm accuracy) and rH sensor (SHT-41). Parallel measurements of relevant environmental parameters inside and outside the “coffins” are conducted by DS18B20 (temperature) and BMP280 (air pressure) sensors. Sensor control, data visualization and storage, as well as steering closure/opening and ventilation is implemented in terms of a wifi and bluetooth enabled, socket powered (9V), compact microcontroller (D1 RS32) based logger unit. Here, we present the design, and first results of the developed, low-cost multi-chamber system. Results were validated against results of customized CO2 and ET measurement systems using regular scientific sensors (LI-COR 850) and data logger components (CR1000), connected to each “coffin” by a multiplexer.  Flow-meter were used for measurement synchronization.

How to cite: Hoffmann, M., Al Hamwi, W., Lück, M., Schmidt, M., and Dubbert, M.: A low cost multi-chamber system (“Greenhouse Coffins”) to monitor CO2 and ET fluxes under semi-controlled conditions: Design and first results, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11777, https://doi.org/10.5194/egusphere-egu23-11777, 2023.

Andrea Butturini and Jordi Fonollosa

Monitoring dissolved methane in aquatic ecosystems contributes significantly to advancing our understanding of the carbon cycle in these habitats and capturing their impact on methane emissions. Low-cost metal oxide semiconductors (MOS) gas sensors are becoming an increasingly attractive tool to perform such measurements, especially at the air-water interface. However, the performance of MOS sensors in aquatic environmental sciences has come under scrutiny because of their cross-sensitivity to temperature, moisture, and sulfide interference. In this study, we evaluated the performance and limitations of a MOS methane sensor when measuring dissolved methane in waters. A MOS sensor was encapsulated in a hydrophobic ePTFE membrane to impede contact with water but allow gas perfusion. Therefore, the membrane enabled us to submerge the sensor in water and overcome cross-sensitivity to humidity. A simple portable, low-energy, flow-through cell system was assembled that included an encapsulated MOS sensor and a temperature sensor. Waters (with or without methane) were injected into the flow cell at a constant rate by a peristaltic pump. The signals from the two sensors were recorded continuously with a cost-efficient Arduino UNO microcontroller.. Our experiments revealed that the lower limit of the sensor was in the range of 0.1-0.2 uM and that it provided a stable response at water temperatures in the range of 18.5-28oC. More information at Butturini, A., & Fonollosa, J. (2022). Use of metal oxide semiconductor sensors to measure methane in aquatic ecosystems in the presence of cross‐interfering compounds. Limnology and Oceanography: Methods20(11), 710-720.

How to cite: Butturini, A. and Fonollosa, J.: Metal oxide semiconductor (MOS) sensors to measure methane in aquatic ecosystems. An eficient DIY low  cost application., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1221, https://doi.org/10.5194/egusphere-egu23-1221, 2023.

Francesco Renzi, Flavio Cammillozzi, Giancarlo Cecchini, Alessandro Filippi, and Riccardo Valentini

The air quality monitoring is a core topic for European environmental policies and worldwide. At the same time technologies such as electrochemical or NDIR gas sensors became affordable and easy to implement in a customized design. A highly flexible monitoring station has been designed and build in order to obtain a customizable and affordable device. It is composed of two boards, one in charge of connectivity and processing while the other allows to insert up to 11 gas sensors. Such number is achieved through the use of three multiplexers that allow to spare input pins of the processor. Moreover the flexibility at the moment is achieved using sensors with the same form factor but adapters are under development to increase the adaptability of the system, both hardware and software. An Arduino MKR zero runs the application that can be run in three different modes: single measurement, time driven or position driven. The last feature is obtained through an optional on-board U-blox GNSS module that allows to georeference the performed measurements. This mode is mainly used when the measurement cell is applied on moving object, such as drones. The system is able to send the data collected and receive commands using MQTT protocol (HiveMQ broker) through a NB-IoT connection and interact with the user from an online dashboard created using Thingsboard. The use of the MQTT protocol allows to send the data to multiple endpoints if the data should be provided also to third parties. Moreover, the data and some parameters are also saved on a sd card. All the system is built on stand alone boards to achieve easy maintaince of the system and to allow a rapid change in the used technology (a plug and play LoRaWan module is under development). Being a multi-application platform, price of the device is of course highly dependent on the chosen set of sensors thus, in the end, on the application itself (i.e. Air pollution or gas emission in barns). To sum up, the device described is a possible solution for an affordable gas concentration measurement system that can be adapted to fit a large variety of use cases combining software and hardware solutions.

How to cite: Renzi, F., Cammillozzi, F., Cecchini, G., Filippi, A., and Valentini, R.: Design of an affordable and highly flexible IoT station for multiple gas concentration monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17527, https://doi.org/10.5194/egusphere-egu23-17527, 2023.

Soheil Zehsaz, João L. M. P. de Lima, M. Isabel P. de Lima, Jorge M. G. P. Isidoro, and Ricardo Martins

This study presents a technique based on the use of quinine as a fluorescent tracer, to estimate sheet flow velocities over various surface coverings (e.g., bare; mulched; vegetated; paved) in low luminosity conditions (e.g., night; twilight; shielded environments). Quinine glows when exposed to UVA light and in the concentrations used is not harmful to the environment. Experimental work was conducted for studying sheet flows in the i) laboratory (using a soil flume), over bare and mulched surfaces, and ii) field, over vegetated and paved surfaces. Flow velocities were estimated based on the injection of a quinine solution into the water flow.  In these experiments, dye and thermal tracer techniques were used as a benchmark for assessing the performance of the quinine tracer. Optical and infrared cameras were used to record the movement of the tracers’ plumes in the flow. The surface velocity of the flow was estimated by tracking the tracers’ plumes leading-edge and calculating their travel distance over a certain time lapse. Overall, the visibility of the quinine tracer was better in comparison to the dye tracer. However, under some circumstances, lower than the visibility of the thermal tracer. Nonetheless, the results show that all three tracers yielded similar estimations of the flow velocities. Therefore, when exposed to UVA light the quinine tracer can be useful to estimate sheet flow velocities over a wide variety of soil and urban surfaces in low luminosity conditions. Despite some inherent limitations of this technique (e.g., invisible under bright light conditions or heavy mulched/vegetated cover; need of a UVA lamp), its main advantage is the high visibility of the quinine fluorescent tracer under UVA light for fade light conditions (e.g., night; twilight; shielded environments such as close conduits), which creates new opportunities for tracer-based surface flow velocity measurements in surface hydrology studies.

How to cite: Zehsaz, S., de Lima, J. L. M. P., de Lima, M. I. P., Isidoro, J. M. G. P., and Martins, R.: Estimating sheet flow velocities using quinine as a fluorescent tracer in low luminosity conditions: laboratory and field experiments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-515, https://doi.org/10.5194/egusphere-egu23-515, 2023.

Seven innovative sensors: The TEMBO Africa project
Nick van de Giesen, Hessel Winsemius, Frank Annor, Tomáš Fico, Eugenio Realini, Remko Uijlenhoet, and Salvador Peña-Haro
Wouter Buytaert

Hydrology is still one of the most data scarce natural sciences. The large number of variables to measure, their extreme spatiotemporal gradients, and the often harsh and hostile environmental conditions all contribute to this issue. This challenge is even more pronounced in remote and extreme environments such as the tropics, and mountain regions, where the need for robust data is most acute.

Many new and emergent technologies can help with building more cost-effective, robust, and versatile hydrological monitoring systems. However, the speed at which these new technologies are being incorporated in commercially available systems is slow and dictated by commercial interests and bottlenecks.

An alternative solution is for scientists to build their own systems using off the shelf components. Open-source hardware and software, such as the Arduino and Raspberry Pi ecosystems, make this increasingly feasible. As a result, a plethora of global initiatives for open-source sensing and logging solutions have emerged.

But despite these new technologies, it remains a major challenge to build open-source solutions that equal the reliability and robustness of the high-end commercial systems that are available on the market. Sharing experiences, best practices, and evidence on the real-world performance of different designs may help with overcoming this bottleneck.

In this contribution, I summarize the experience gained from developing and operating over 300 open-source data loggers, built around the Riverlabs platform. This platform is mostly a compilation of existing open-source hardware and software components and solutions, which were refined further and tweaked for robustness and reliability in extreme environments. Our loggers have been installed in locations as diverse as Arctic Norway, the high Andes of Peru and Chile, the Nepalese and Indian Himalayas, the Somali desert, and the Malaysian rainforest, providing a wide range of real-world test-cases and performances.

How to cite: Buytaert, W.: Towards a robust, open-source logging platform for environmental monitoring in challenging environments: the Riverlabs toolbox, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15989, https://doi.org/10.5194/egusphere-egu23-15989, 2023.

Field validation and measurement of vegetation spectral indices using low cost microcontroller-based NDVI sensor in the Philippines and Southern Benin
Rinan Bayot, Reena Macagga, Pearl Sanchez, Leonce Geoffroy Sossa, and Mathias Hoffmann
Andrew D. Wickert, Katherine R. Barnhart, William H. Armstrong, Matías Romero, Bobby Schulz, Gene-Hua Crystal Ng, Chad T. Sandell, Jeff D. La Frenierre, Shanti B. Penprase, Maximillian Van Wyk de Vries, and Kelly R. MacGregor

We developed automated ablation stakes to measure colocated in-situ changes in ice-surface elevation and climatological drivers of ablation. The designs implement open-source hardware, including the Margay data logger, which records information from a MaxBotix ultrasonic rangefinder as well as a sensor to detect atmospheric temperature and relative humidity. The stakes and sensor mounts are assembled using commonly available building materials, including electrical conduit and plastic pipe. The frequent (typically 1–15 minute) measurement intervals permit an integral approach to estimating temperature-index melt factors for ablation. Regressions of ablation vs. climatological drivers improve when relative humidity is included alongside temperature. We present all materials required to construct an automated ablation stake, alongside examples of their deployment and use in Alaska (USA), Ecuador, Patagonia (Argentina), and the Antarctic archipelago.


a: Alaska, 2012
b: Alaska, 2013
c: Ecuador, 2016
d: Argentina, 2020
e: Antarctica, 2021

How to cite: Wickert, A. D., Barnhart, K. R., Armstrong, W. H., Romero, M., Schulz, B., Ng, G.-H. C., Sandell, C. T., La Frenierre, J. D., Penprase, S. B., Van Wyk de Vries, M., and MacGregor, K. R.: Automated ablation stakes to constrain temperature-index melt models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11411, https://doi.org/10.5194/egusphere-egu23-11411, 2023.

Kirk Martinez, Jane Hart, Sherif Attia, Graeme Bragg, Marcus Corbin, Michael Jones, Christian Kuhlmann, Elliot Weaver, Richard Wells, Ioannis Christou, and Emily James

Glacier movement has been measured over the years using commercial units such as those from Leica. The aim is to measure point movements on the glacier surface in order to capture fine-grained data about its movement. This can also help to calibrate satellite-based approaches which have much lower resolution. Commercial dGPS recorders cost thousands of Euros so our project is creating a solution using new lower cost dGPS boards which could enable their use by more earth scientists.

The u-blox Zed-F9P based boards from Sparkfun can be used as a base station to send dGPS corrections to “rover” units on the glacier via a radio link. Each measurement is accurate to about 2cm depending on conditions. In our design the radio is used by the rovers to forward good fixes back to the base station, which then uses off-site communications to send the data home. Two types of internet link have been enabled: using a nano-satellite board (by SWARM) and a more traditional GSM mobile phone board (for locations with coverage). Both these boards are also available from Sparkfun – making most of the modules off-the-shelf. However our power supply is optimised to save power and charge the lithium ion battery from a solar panel. A real-time clock chip is used to wake up the system to take readings and transmit data, so the sleep power is only 0.03 mW enabling a year-long lifetime. The whole system is controlled by a Sparkfun Thing Plus SAMD51 which provides the required four serial connections and a circuitpython  environment. The full system will be installed in Iceland in the summer of 2023 and replace the previous prototype based on Swift Piksi Multi units which had shown the measurement principle to be sound.

How to cite: Martinez, K., Hart, J., Attia, S., Bragg, G., Corbin, M., Jones, M., Kuhlmann, C., Weaver, E., Wells, R., Christou, I., and James, E.: A low cost real-time kinematic dGPS system for measuring glacier movement, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2681, https://doi.org/10.5194/egusphere-egu23-2681, 2023.

David Higgins, Renata Correia, Hooi Siang Kang, Lee Kee Quen, Tan Lit Ken, Andre Vollering, Stijn Pinson, Thaine H. Assumpção, and Thomas Mani

Understanding the transport behaviour of mismanaged plastic waste in riverine and estuarine environments is growing. However, many studies to date focus on the surface layer transport while a limited number look to measure the vertical distribution of plastic waste within these systems. Factors such as density, shape, the influence of wind and flow velocity can determine the vertical distribution of the plastic waste in a river, but many knowledge gaps remain. With this, and as technology developers move to create innovative river surface focused interception solutions to extract plastic waste, a greater understanding of the transport behaviour of sub-surface plastic debris is required. Here, we present a comprehensive overview of the development stages required to build and deploy a low-cost depth trawl tool designed to sample plastic waste at a depth of up to 5m in a heavily polluted river in Malaysia. Topics covered include tool design concepts, manufacturing methods, onsite testing, river deployment learnings and sampling results. Field data is compiled from over 60 sampling surveys conducted over 14 days in several locations along the Klang River, Malaysia. The depth trawl is mounted to a locally available fishing boat (sampan) and consists of two steel horizontal arms, a steel frame, two winches, cables, weights, five nets, and is operated manually with the assistance of a solar-powered motor. The dimensions of each net are 30cm (W) x 50cm (H) x 100cm (L) with a mesh size of 30mm x 30mm. To ensure that the nets remain aligned vertically during deployment, a weight of 15kg is tied to the bottom of the net system on both sides. Samples were collected every 1 metre to a depth of 5 metres. Each sampling was conducted for 15 minutes, six times per day with an interval of 1 hour between samples to allow for changes in the tide and river flow direction. An ADCP was deployed in parallel to the depth trawl to provide measurements of flow velocity variation at the river surface and with depth. In addition, this paper reviews the depth trawl system’s capabilities and recommendations for further studies and applications in the field.

How to cite: Higgins, D., Correia, R., Kang, H. S., Quen, L. K., Ken, T. L., Vollering, A., Pinson, S., H. Assumpção, T., and Mani, T.: Trials and design iterations experienced developing a low-cost depth trawl to sample macroplastic through the water column of a tidal river., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4878, https://doi.org/10.5194/egusphere-egu23-4878, 2023.

Sophia Burke, Arnout van Soesbergen, and Mark Mulligan

FreeStations are mature low-cost, networked, DIY environmental sensors and data loggers, developed since 2014  and now deployed around the world.  Build instructions are open source at www.freestation.org and based on high availability, low cost but accurate and robust components (with builds typically 3% the parts-cost of an equivalent proprietary monitoring systems).  This allows investment in a network of environmental loggers at the cost of a single, proprietary logger.  

FreeStations have been widely deployed in the DEFRA Natural Flood Management (NFM) national trials in the UK, and analytical methods developed to examine the performance of leaky dams, retention ponds, regenerative agricultural practices and other nature based solutions in mitigating flood risk at downstream assets.

These deployments usually consist of FreeStation weather stations: recording rainfall volume, rainfall intensity, air temperature, humidity and pressure as well as solar radiation, wind speed and direction.  The rainfall volume and instantaneous intensity are the most important for NFM studies.  Alongside weather stations, FreeStation sonar-based stage sensors are used, alongside river profile scan from a FreeStation LIDAR, to monitor change in river discharge due to an NFM intervention, relative to discharge at a downstream asset at risk.  Readings are taken at 10-minute intervals over multiple years.

A series of web based methods have been built as part of the FreeStation //Smart: platform to monitor and manage data from deployments and to analyse data to better understand flood mitigation by the key types of intervention.  In testing at more than 10 sites in the UK over a period of 2-3 years per site, large volumes of data have been collected at low cost and in support of local stakeholders during the H2020NAIAD and H2020ReSET projects.  

The data indicate the importance of careful design in leaky debris dams, the limited impact of inline retention ponds and the significant capacity of low-till farming methods to mitigate downstream flooding.  The effectiveness of NFM depends upon the number and scale of interventions, the proportion of the discharge at the downstream asset at risk which they affect (i.e. the downstream proximity of the asset at risk) and the capital and maintenance costs of the interventions. 

Low-cost approaches to environmental monitoring will be critical for developing the evidence base needed to better understand what nature based solutions work, where for water.  Low cost, internet-connected devices are easy to monitor and maintain, low risk and capable of extensive deployment to address the challenge of geographical variability which means that the impacts of specific NFM interventions are highly site specific. 

How to cite: Burke, S., van Soesbergen, A., and Mulligan, M.: Effectiveness-assessment of nature-based flood mitigation using networked, low cost DIY environmental monitoring from FreeStation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5922, https://doi.org/10.5194/egusphere-egu23-5922, 2023.

Nikita Aigner, Christine Moos, and Estelle Noyer

Forests play a crucial role in regulating the water content of soils and thus influence runoff formation, but also the susceptibility to drought or forest fires. However, the extent to which forests influence soil moisture is difficult to quantify and depends on several parameters, such as precipitation intensity and duration, and terrain or soil properties. To capture the temporal and spatial variability of soil moisture in forests, large-scale and long-term measurements are necessary. Currently, such measurements are relatively expensive and complex and thus generally lacking or restricted to agricultural areas.  

Our current work focuses on the development of a low-cost soil moisture sensor that uses off the shelf parts and can be deployed at scale to provide continuous long-term measurements. To increase adoption and ensure the digital sustainability of our concept, the project will be released open source to the general public.  

The sensor design is based around an ESP32 microcontroller to manage measurements with capacitive soil moisture sensors. For communication, we leverage the LoRa protocol and use infrastructure provided by the Things Network (TTN). Herein, we present the soft- and hardware architecture of a sensor prototype and results obtained from a proof-of-concept deployment. In addition, we discuss the calibration procedure and evaluation of capacitive soil moisture sensors (in comparison to time-domain reflectometry (TDR) sensors). Finally, we provide an outlook on future developments of our measurement system. The final goal of this project is to deploy sensors in several areas of interest that will allow for gathering data for a better understanding of the interaction of forests and soil moisture content.  

How to cite: Aigner, N., Moos, C., and Noyer, E.: Developing a smart sensor network for soil moisture monitoring in forests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8165, https://doi.org/10.5194/egusphere-egu23-8165, 2023.

Paul Vandôme, Crystele Leauthaud, Simon Moinard, Insaf Mekki, Abdelaziz Zairi, and Gilles Belaud

Mediterranean agriculture is facing the challenge to produce sustainably with a water resource under pressure. As irrigated areas expand in response to increasing vulnerability to drought, it is essential to support water users towards better agricultural water management. We set up two Fab Labs on the shores of the Mediterranean (France and Tunisia) to bring together water users around a collective project: co-constructing innovations to address local water management issues. A range of low-tech, low-cost and open source IoT-based sensors emerged from this process. The technologies were tested with users during the 2022 irrigation season. The aim of this study is to provide feedback on this participatory method as a facilitator for creating and sharing innovation in rural territories and to discuss the opportunities, benefits and limitations related to the use of these new technologies. We believe that this work contributes to make the measurement of water flows - and thus their understanding and better management - more accessible to the agricultural sector.     

How to cite: Vandôme, P., Leauthaud, C., Moinard, S., Mekki, I., Zairi, A., and Belaud, G.: Water user Fab Labs: co-design of low-tech sensors for irrigated systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12622, https://doi.org/10.5194/egusphere-egu23-12622, 2023.

Seunghyun Hwang, Jinwook Lee, Jeemi Sung, Hyochan Kim, Beomseo Kim, and Changhyun Jun

This study proposes a novel method for rainfall intensity estimation from acoustic and vibration data with low-cost sensors. At first, a precipitation measurement device was developed to collect sound and touch signals from raindrops, composed of Raspberry Pi, a condenser microphone, and an accelerometer with 6 degrees of freedom. To figure out whether rainfall occurred or not, a binary classification model with the XGBoost algorithm was considered to analyze long-term time series of vibration data. Then, high-resolution acoustic data was used to investigate the main characteristics of rainfall patterns at a frequency domain for the period when it was determined that rainfall occurred. As a result of the Short Time Fourier Transform (STFT), the highest frequency, mean and standard deviation of amplitudes were selected as representative values for minute data. Finally, different types of regression models were applied to develop the method for rainfall intensity estimation from comparative analysis with other precipitation measurement devices (e.g., PARSIVEL, etc.). It should be noted that the new device with the proposed method functions reliably under extreme environmental conditions when the estimated rainfall intensity was compared with measured data from ground-based precipitation devices. It shows that low-cost sensors with sound and touch signals from raindrops can be effectively used for rainfall intensity estimation with easy installation and maintenance, indicating a strong possibility of being considered in a wide range of areas for precipitation measurement with high resolution and accuracy


This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022R1A4A3032838).

How to cite: Hwang, S., Lee, J., Sung, J., Kim, H., Kim, B., and Jun, C.: Precipitation Measurement from Raindrops’ Sound and Touch Signals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13072, https://doi.org/10.5194/egusphere-egu23-13072, 2023.

Linus Fässler, Natalie Ceperley, Peter Leiser, and Bettina Schaefli

River networks in the Alps are very complex and hold many unanswered research questions. For example, various assumptions must be made to when studying tributaries and small rivers. Namely, there is not a widely accepted tool to measure streamflow in small, mountain streams that can overcome their specific challenges affordably without large installations. For example, alteration between extremely high and no discharge volume is characteristic of intermittent rivers and ephemeral streams (IRES). Conventional measuring devices all require streambed installation, which exposes them to displacement or destruction by abruptly rising water levels. One solution, thus, is to remove the sensor from the streambed and measure from a distance. We have experimented with an acoustic sound recorder mounted above the stream as an alternative tool to assess water level. We designed a low-cost audio sensor powered by a microcontroller with an audio shield specifically for recording IRES. To ensure reproducibility, we used Arduino for programming the Teensy 3.2. Images of the water level in an IRES were simultaneously captured when possible (daylight) and used for calibration. The water level visible in the images correlated well with that determined from the audio recordings from our self-developed audio sensor (R2 = 95%). Based exclusively on the audio recording of an IRES, we can obtain a time series of the water level, at least when water was present. We are currently unable to determine consistently whether water is present nor state with certainty when the streambed is dry based solely on acoustic data. Nevertheless, this new sensor allows us to measure an alpine channel network at more locations and over longer time periods than previously feasible.

How to cite: Fässler, L., Ceperley, N., Leiser, P., and Schaefli, B.: Monitoring an ephemeral stream with a Teensy 3.2 + audio shield to determine water level only from the noise of a stream, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14370, https://doi.org/10.5194/egusphere-egu23-14370, 2023.

Yen- Chang Chen and Wu-Hsien Hsiao

Hydrological data, especially water stage and discharge, is very important for water resources planning and development, hydraulic structure design, and water resources management. Thus the hydrological data has to be observed and collected regularly and continuously. The hydrological data can be affected by many factors such as people, instruments, and climate. Therefore, the collected hydrological data still need to be subject to quality control and inspection to eliminate unreasonable data to ensure the accuracy and reliability. Traditionally, the quality control and inspection of stream water-stage is mainly manual. The verification of water stage data needs experienced hydrologists to judge the correctness of the data, and cannot be processed automatically. It is time consumed, costly, and labor intensive to process the quality control of stream water stage. Therefore, it is necessary to develop a feasible model to automatically check stream water-stage for providing reliable and accurate hydrological data.

This study applies Hilbert-Huang Transform (HHT) to process stream water-stage. The HHT is composed of Empirical Mode Decomposition (EEMD) and Hilbert transform (HT). The EEMD decomposes stream water-stage into many intrinsic mode functions (IMFs) and a residual. The first IMF component is used for Hilbert transform conversion to obtain the time amplitude energy relationship diagram. The amplitude fluctuation of the corresponding component of the stream water-stage, the amplitude value of the outliers can be revealed. When the amplitude value is larger than usual, there may be outliers, and vice versa. It depends on the threshold that is established in this study as the basis for filtering the incorrect water-stage. Therefore automatically inspecting the water-stage data can be achieved. The model for automatic inspecting procedure developed by this study will greatly reduce the manual quality control, not only shorten the checking time, save manpower, but also provide reliable and correct river water stage data.

How to cite: Chen, Y.-C. and Hsiao, W.-H.: Quality control of stream water-stage using Hilbert-Huang Transform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4844, https://doi.org/10.5194/egusphere-egu23-4844, 2023.

yixuan wang

The development of artificial reservoirs plays a considerable role in regulating the spatial and temporal distribution of irrigated rainfall and guaranteeing sustainable agricultural development. Many studies have used the area-storage relationship to obtain the storage capacity of on-farm reservoirs (OFRs), but it does not work for OFRs with persistent water surface area. In this study, we proposed an effective method to estimate the water storage of irrigated OFRs by combining multi-source remote sensing data and ground observation. We quickly derived the location of irrigated OFRs by using seasonal characteristics of irrigated OFRs and obtained high-precision water surface area using an object-oriented segmentation. We estimated water storage of irrigated OFRs by combining three different ways (i.e., Lidar-based, ground observation-based (photos), and surface area-based). The method performs well in three aspects, i.e., identifying on-farm reservoirs, extracting water surface area, and calculating water storage. The accuracy of identification reaches 94.1%, and the derived water area agrees well with the surveyed results, i.e., an overall accuracy of 97.8%, the root mean square error (RMSE) and the mean absolute errors (MAE) are 962 m2 and 766 m2, respectively. The obtained water storage is reliable using three different ways (i.e., the area-storage, Lidar-based, and photo observations-based methods), with accuracy of 98.8%, 95.2%, and 94.1%, respectively. The proposed method enables monitoring of the storage of multiple types of irrigated OFRs, particularly the photo observation-based method can deal with the storage of OFRs with persistent water areas, showing huge potential to promote irrigated water resource utilization efficiency.

How to cite: wang, Y.: Monitoring water storage of on-farm reservoirs using remote sensing and ground observation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15372, https://doi.org/10.5194/egusphere-egu23-15372, 2023.

Utku Berkalp Ünalan, Onur Yüzügüllü, and Ayşegül Aksoy

Monitoring the depth changes in lakes is crucial to understanding hydrological dynamics and water quality changes. In developed countries, the authorities monitor the lake depths regularly; however, it might be different in developing and underdeveloped countries. In this study, we aim to develop a near-real-time SAR-based depth change monitoring system for lakes by focusing on shoreline pixels. For this purpose, we developed a framework using the Sentinel-1 GRD and Sentinel-2 Dynamic World land cover datasets available on the Google Earth Engine. Sentinel-1 data provides us with the necessary temporal resolution for frequent monitoring. For the initial development phase, we consider five ground monitoring stations in Sweden and one in Turkey. The approach starts by detecting water bodies within a selected area of interest using Sentinel-1. Then it extracts shoreline pixels to calculate the change in the VV and VH sigma naught and VV-VH and VV+VH Pauli vectors. Extracted differences are further classified according to the temporally closest Dynamic World data to handle the temporal difference for each land cover type. Next, we eliminate outlier values based on the percentiles, and from the remaining data, we sample each landcover class for modeling. From many of the tested frameworks, we obtained an R2 of 0.79 with Gaussian Process Regression. Currently, in this framework, we observed an underestimation of higher values and an overestimation of lower values within a range of ±0.4 cm. Furthermore, considering the chosen six lakes, we observed a negative correlation between depth change and polarimetric features obtained from samples taken from land covers of grass and flooded vegetation, which is typical for natural lakes. In the second step of the development, we will increase the number of samples by including lakes from Switzerland and further develop the model.

How to cite: Ünalan, U. B., Yüzügüllü, O., and Aksoy, A.: Near Real-Time Depth Change Monitoring on Inland Water Bodies Using Sentinel-1 and Dynamic World Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-649, https://doi.org/10.5194/egusphere-egu23-649, 2023.

Posters virtual: Mon, 24 Apr, 16:15–18:00 | vHall HS

The virtual MacGyver Session
Ankit Singh, Hemant Kumar Dhaka, Pragati Prajapati, and Sanjeev Kumar Jha

The river discharge data is one of the most important pieces of information to regulate various water resources, including flood frequency analysis, drought and flood prediction, etc. The missing observer discharge data, even a short gap, influences the whole analysis and gives a totally different result. Filling data gaps in streamflow data is thus a critical step in any hydrological study. Interpolation, regression-based analysis, artificial neural networks, and modeling are all methods for generating missing data. While using the hydrological model to generate the data, we first need to calibrate the hydrological model. The single-site calibration of the hydrological model has its own limitations, due to which it does not correctly predict the streamflow at intermediate gauge locations. This is because, while calibrating the model for the final outlet, we tune the parameters that affect the results for the final outlet only and neglect the intermediate sites' output. In this study, we demonstrate the importance of multi-site calibration and use the calibrated hydrological model to generate the missing data at intermediate sites.

For this study, we selected the Godavari River basin and calibrated it at the final outlet (single-site calibration) and at 18 + 1 outlets (multi-site calibration). The whole basin is divided into 103 subbasins, and the Soil and Water Assessment Tool (SWAT) hydrological model is used for this study. After the successful multi-site calibration, we generated the missing data at 25 different gauging locations. The initial results from single-site calibration (NSE (0.57) and R2 (0.61)) show good agreement between observed and simulated discharge for the final outlet. The multi-site calibration analysis is in progress, and full results will be presented at the conference.

How to cite: Singh, A., Dhaka, H. K., Prajapati, P., and Jha, S. K.: Using the hydrological model for filling the missing discharge data by using multi-site calibration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1636, https://doi.org/10.5194/egusphere-egu23-1636, 2023.

Kwang-Hun Lee, Shahid Ali, Yena Kim, Ki-Taek Lee, Sae Yun Kwon, and Jonghun Kam

This study developed a synchronized mapping technique for water quantity and quality via an unmanned surface vehicle (USV). The USV with the acoustic doppler current profiler (ADCP) and the multiparameter sonde of water quality sensors (YSI EXO2) was used for identifying spatial and seasonal patterns of the Daljeon reservoir in South Korea. With this technique, we measured bathymetry and nitrate concentration from August 2021 through July 2022 at the high resolution spatial resolution and tested the sensitivity of estimated nitrate loads to spatial variations of input variables (water volumes and nitrate concentrations). Results showed that measured bathymetry and nitrate concentration varies over the water surface of the reservoir and time, which are associated with seasonal variations of temperature and precipitation. Despite weak spatial variations of the nitrate concentration, the water level of the reservoirs showed strong spatiotemporal variations depending on the topography of the reservoir and the  rainfall occurrence. Furthermore, we figured out using the mean for nitrate load was underestimated by -20% of the nitrate load estimates by considering spatial variation. High-resolution bathymetry measurement play a role in estimating nitrate loads with a minor impact of spatial variations of measured nitrate concentrations. We found that rainfall occurrences more likely increase estimated nitrate loads when it accounts for spatially variations of input variables, particularly water volumes. This study proved the potential utility of USV in simultaneously monitoring water quantity and quality for integrative water resource management for sustainably development of our communities.

How to cite: Lee, K.-H., Ali, S., Kim, Y., Lee, K.-T., Kwon, S. Y., and Kam, J.: Synchronized mapping of water quantity and quality of a reservoir through an unmanned surface vehicle: A case study of the Daljeon reservoir, South Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10497, https://doi.org/10.5194/egusphere-egu23-10497, 2023.