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 for iPhone to an Arduino or Raspberri Pi? 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.

Co-organized by BG3/GI1/SSS11
Convener: Rolf Hut | Co-conveners: Theresa Blume, Elisa CoraggioECSECS, Flavia TauroECSECS, Andy WickertECSECS
| Attendance Mon, 04 May, 16:15–18:00 (CEST)

Files for download

Download all presentations (106MB)

Chat time: Monday, 4 May 2020, 16:15–18:00

D1 |
Valerio Baiocchi, Roberta Onori, Felicia Monti, and Francesca Giannone

High and very high resolution satellite images are now an irreplaceable resource for earth observation in general and for the extraction of hydrogeological information in particular. In order to use them correctly and compare them with previous surveys and maps, they must be treated geometrically to remove the distortions introduced by the acquisition process. Orthorectification is not a simple georeferencing because the process must take into account the three-dimensional acquisition geometry of the sensor. For this reason orthorectification must be performed within specific commercial software with additional costs compared to image acquisition which, in some cases, is currently free of charge.
Some orthorectification algorithms, mainly based on the RPC approach, are available in open source GIS software such as QGIS. OTB (Orpheus toolbox) for QGIS contains some of these algorithms but its interfaces are not clear and there are some incomprehensible limitations such as the impossibility to input three-dimensional ground control points (GCPs). This severely limits the final achievable accuracy because it does not allow to correctly estimate the influence of different ground morphologies on the acquisition geometry. To get around these limitations you can make a "pseudo DEM" and other expedients to complete the whole process obtaining absolute results comparable if not better than those of commercial software.
The proposed procedure may not be the fastest but it can be a valid alternative for those who use satellite images as a tool in their research work.


How to cite: Baiocchi, V., Onori, R., Monti, F., and Giannone, F.: How to circumvent the limitations of open source software and orthorectify how (or better) than with commercial software, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8316, https://doi.org/10.5194/egusphere-egu2020-8316, 2020.

D2 |
Robert Wagner and Tobias Goblirsch

The conservation and long-term protection of our environment require a better understanding of ecosystems through cross-domain integration of data and knowledge from different disciplines. Current methods used in applied environmental research and scientific surveys are not sufficient to address the heterogeneity and dynamics of ecosystems appropriately. To this end, an urgent need is seen in introducing new technology and methods for a service-oriented and holistic in-situ monitoring with increased spatio-temporal resolution and cutting edge functionalities. Recent developments in the field of digital information processing, the internet of things (IoT) or the the analysis of complex datasets are opening up new possibilities for data-based environmental research. This rapidly developing fields are calling for a disruptive paradigm shift towards a service-oriented earth observation (smart monitoring). To this end, future earth observation approaches will have a much stronger coupling between the modeling and the data acquisition. The development, implementation and evaluation of such an interface is one of the overall objectives of this project. To achieve this goal, a basic data model and a special hardware architecture must be defined. A realistic application scenario will be used to demonstrate the advantages of developing a monitoring strategy that is no longer based on static data collection but on the coupling of modeling and empiricism using integrated sensors for an advanced modeling. Since current methods have so far failed to allow a holistic assessment of varying, large-scale environmental phenomena there is a corresponding need for capable hardware which is specialized for exactly this purpose.

The project aims to introduce an integrated sensor system for advanced modeling of turbidity and dissolved organic matter using miniaturized optical sensors in the ultraviolett and infrared range. Moreover, a data-driven, open-source architecture for service-oriented observation methods and in-stream process modeling close to real-time was developed. In addition to the hardware-related requirements of such a sensor system, the creation of an interface between the physical environment (sensor level) or abstracted model assumption (model level) is a particular focus of the research project. A sampling theorem, the predictive object specific exposure (POSE), is introduced as an underlying measurement paradigm and data model. This allows to consider not only the measured value in the evaluation but also accompanied parameters, which is called the context of a measurement. The development and provision of a first adaptive sensor concept resulted in promising prototype enabling the possibility to record environmental data depending on decision criteria such as location, time or context. Thus, the project is representing an interesting practical contribution to Digital Earth.

How to cite: Wagner, R. and Goblirsch, T.: A data-driven open-source architecture for service-oriented observation methods and in-stream process modeling of turbidity and dissolved organic matter, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21587, https://doi.org/10.5194/egusphere-egu2020-21587, 2020.

D3 |
Vladimir Divić, Morena Galešić, Mariaines Di Dato, Marina Tavra, and Roko Andričević

The monitoring of water bodies, specifically complex ones such as estuaries, has been historically limited. Various research efforts were hindered due to the gaps in the technology implementation and accompanied by the price of developed solutions (usually as a black box for the end-user). However, thanks to the growing trend of open source solutions both in hardware and software domain, it has become more available to apply the DIY (do it yourself) approach and build the equipment that one might need. As all frugal innovations tend to emerge from a problem that had an existing commercial solution but was too demanding on resources, the floating measurement system presented in this study was designed to get surface water properties simultaneously in multiple points. Using multiple commercial probes to do such measurements was too expensive. Therefore, we have developed an innovative low-cost drifter based on the Arduino platform as an alternative. Our device is designed to measure position, temperature, and electrical conductivity in multiple drifter realisations or short-term moored measurements. The system consists of a floating container equipped with the following components: an Arduino Mega development board, a power management module, an SD card logging module, a Bluetooth module, a temperature measuring module, a global positioning satellite (GPS) position module, and a newly developed module for measuring electrical conductivity (EC). The applicability was tested at the estuary of River Jadro near Split (Croatia) and obtained spatial data (velocity, temperature, electrical conductivity and salinity) was analysed and compared with analytical models. All used tools are open-source and greatly supported by the worldwide community. Furthermore, we consider this prototype to be one of the first steps toward development of various DIY monitoring systems with a potential for a broader range of applications. We present our work with a purpose to initiate a dialogue with more collaborators interested in developing different variations of custom-built sensors for water properties.

How to cite: Divić, V., Galešić, M., Di Dato, M., Tavra, M., and Andričević, R.: DIY approach to measuring surface water properties in the estuary, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6102, https://doi.org/10.5194/egusphere-egu2020-6102, 2020.

D4 |
Evangelos Skoubris and George Hloupis

River floods occupy a respectable percentage among all natural disasters, are presenting high risk, and usually cause great damage. Important tools in managing and preventing river floods are the Early Warning Systems (EWS), which are usually consisted both by a hardware infrastructure (sensors, communication network) and a relevant software infrastructure (data logging, signal processing, modeling, risk detection).

In the current work we are presenting preliminary results from a novel, low-cost and low-power hardware system, part of a EWS aimed for river floods. The system consists of multiple sensing nodes, each to be strategically positioned at certain points along the route of river Evros, Greece. Each sensing node will bear a low-cost and high-quality ultrasonic water level sensor, along with an embedded microcomputer to control its functionality. An additional novelty of the proposed work is the design and utilization of a private low-power wide-area wireless network (LPWAN), taking advantage of IoT technologies and especially the LoRaWAN implementation. This way, the proposed system will have even lower power demands, together with greater expandability by allowing many nodes to be simultaneously connected and measuring, and having the ability to utilize crowd-sensing techniques. The power supply is battery based and autonomously recharged with the aid of small solar panel. Each node will measure the water level of the river, and upload the data to a cloud server at variable time intervals, depending on the actual water level variation and the system’s power consumption optimization.

Future upgrades of the system will involve extra sensors, allowing the nodes to measure water quality parameters i.e. suspended solids, pH, etc. Although of secondary importance, these parameters might prove to be important in the development of the risk detection and alarm issuing algorithms.

How to cite: Skoubris, E. and Hloupis, G.: Low Cost Sensor Node for Monitoring River Floods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20175, https://doi.org/10.5194/egusphere-egu2020-20175, 2020.

D5 |
Panagiotis Argyrakis, Theodore Chinis, Alexandra Moshou, and Nikolaos Sagias

Several stations (seismological, geodetical, etc.) suffer from communications problems, such problems create data gaps in real-time data transmission, also excess humidity and temperatures further than manufacturer limits, usually make components and circuitry, of expensive instruments, failure, and results to unaffordable service or unrepairable damage.

We create a low-cost opensource device that will raise the reliability of the stations and secure the instruments from severe damage, such a device installed as prototype at UOA (University of Athens) seismological station KARY (Karistos Greece) for a year and the reliability of the station raised tremendously, since then the device upgraded to provide wireless connection and IoT GUI (mobile app). A local server was built to serve all the devices uninterrupted and provide a secured network.

The software is fully customizable and multiple inputs can provide addon sensors capability, for example, gas sensor, humidity sensor, etc., all the data are collected to a remote database for real-time visualization and archiving for further analysis.

The shell which covers the circuitry is 3D-printed with a high temperature and humidity-resistant material and it’s also fully customizable by the user. 

How to cite: Argyrakis, P., Chinis, T., Moshou, A., and Sagias, N.: Multipurpose IoT network watchdog device with capability of add on sensors for multi instrument field stations., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-83, https://doi.org/10.5194/egusphere-egu2020-83, 2020.

D6 |
Rolf Becker

The collective term ‘Internet of Things’ (IoT) encompasses a variety of technologies and methods providing novel opportunities for data acquisition and control in environmental sciences. Availability of cost effective components as well as support of large open source communities allow scientists to gain more flexibility and control over their experimental setups. However quality of measurements, stability of instruments as well as real costs for development and maintenance are often underestimated challenges. The presentation introduces current best practices of IoT principles in scientific applications. Examples of low cost sensors, low power electronics, wireless data transmission protocols, time series databases as well as real-time visualization are presented and discussed. Furthermore light is shed on non-technological issues of the ‘do-it-yourself’ or ‘maker’ approach such as social and psychological aspects. The ‘make-share-learn’ paradigm of the maker culture can be utilized to raise awareness. It provides significant opportunities for environmental education and community building which constantly gain more importance in the context of climate and environmental change.

How to cite: Becker, R.: ‘Internet of Things’ for environmental sciences and education, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19810, https://doi.org/10.5194/egusphere-egu2020-19810, 2020.

D7 |
Daniel Beiter, Tobias Vetter, Markus Morgner, Carlo Seehaus, Stephan Schröder, and Theresa Blume

In the course of the Helmholtz MOSES initiative two monitoring systems are being developed which consist of the same key components and thus functionality but with very different scopes of application. One is a stationary data logger with a classic measurement routine (on/off duty cycle) and support for various hardware interfaces (2xSDI12, 1xRS485, 2xUART, amongst others). The other is a drifting data logger that stays idle until a flood event activates the logger and carries it downstream. On-board are turbidity, EC and temperature sensors, a GPS and an inertial measurement unit (IMU) monitoring turbulence.

Advancements in electronics driven by automotive, mobile and IoT applications led to the development of very powerful, small and low power microcontrollers. This is why we decided to leave the realms of ATMega 8-bit systems (such as Arduino) and move towards ARM Cortex 32-bit systems. More precisely we used the Teensy 3.5 microcontroller development system as the core for the two systems. It is superior to Arduino in terms of performance while its developing team tries to maintain compatibility to Arduino in terms of programming vocabulary. This allows easier migration but comes also with restrictions regarding the capabilities of the hardware.
The other key component is the FiPy which supports five different wireless network types (WiFi, Bluetooth, LoRa, Sigfox, LTE-M) in one module. In comparison to most other hardware it runs MicroPython which adds more complexity to the project. Even though it is a microcontroller and features also several hardware interfaces, power consumption is far from low power, which is why it is used here only for remote communication and data transmission. In addition, several design decisions were made regarding power path routing and jumper configuration to improve the systems’ overall versatility, debugging capabilities and low power functionality, which are often key to the feasibility of a remote monitoring system.

How to cite: Beiter, D., Vetter, T., Morgner, M., Seehaus, C., Schröder, S., and Blume, T.: Microcontrollers beyond Arduino: a stationary and a mobile environmental monitoring system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3032, https://doi.org/10.5194/egusphere-egu2020-3032, 2020.

D8 |
| Highlight
Núria Martínez-Carreras, François Barnich, Jean François Iffly, Oliver O'Nagy, and Andrei Popleteev

Field deployable and portable automatic water samplers are common tools in hydrology. They allow the unattended collection of water samples at predetermined times or triggered by external sensors, reducing personnel labour and costs. Several automated water samplers have been described in the literature. However, the vast majority of these samplers are not commercialised and their use is very limited or restricted to research applications. We can broadly classify these samplers in three groups: in situ samplers, sequential precipitation samplers and siphon automatic samplers. The latest are commonly used by hydrologists, environmental monitoring agencies and in wastewater treatment plants. They were first patented and commercialized in the 1980s by Teledyne-ISCO (Lincoln, NE, USA). They use a peristaltic pump to transfer water into several containers. However, the siphon automatic samplers are large, heavy and typically collect a maximum of 24 samples of 0.5 or 1 L. Here, we present a new automatic water sampler that has a larger and variable storage capacity (from 64 to 400) of smaller containers (from 2 to 40 mL). We argue that for many applications large sample volumes are no longer required due to the improvement of chemical analytic techniques. Standard laboratory storage boxes are filled with standard laboratory containers and directly placed inside the sampler, reducing the processing time once the samplers are back in the laboratory. Containers remain always closed with a septum cap to prevent evaporation. The sampler allows tub rinsing between sample collection to prevent contamination and memory effects. It is portable, has a low-power consumption and is robust for its use under field conditions. We tested the prototype in the laboratory and in the field. We will present the sampler mechanical functioning, the results of the tests (e.g. sample preservation and memory effects) and the user-friendly interface to define sampling schemes.

How to cite: Martínez-Carreras, N., Barnich, F., Iffly, J. F., O'Nagy, O., and Popleteev, A.: A high capacity, automatic and small-volume water sampler, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18989, https://doi.org/10.5194/egusphere-egu2020-18989, 2020.

D9 |
Christoff Andermann, Torsten Queißer, Markus Reich, Bijaya Puri, Niels Hovius, and Dirk Sachse

With global climate change, one of the largest short-term threats to our societies comes from changes in the hydro-meteorological cycle: droughts, flooding and potentially increasing extreme rain events may have far greater direct impact on humans than rising temperatures alone. These changes often have sever consequences and widespread impact on society and ecosystems, yet they are difficult to track, trace and measure in order to fully understand the underlying process of delivering moisture and recharging water reservoirs. Only through the comprehensive monitoring of precipitation waters in space and time can we improve our process understanding and better predict the direction and magnitude of future hydro-meteorological changes, in particular on regional spatial scales. However, no commercial automated sampling solution exists, which fulfills the quality criteria for sophisticated hydrochemical water analysis. Here, we present an advanced prototype automatic precipitation water sampler for stable water isotope analysis of precipitation. The device is designed to be highly autonomous and robust for campaign deployment in harsh remote areas and fulfills the high demands on sampling and storage for isotope analysis (i.e. sealing of samples from atmospheric influences, no contamination and preservation of the sample material). The sampling device is portable, has low power consumption and a real-time adaptable sampling protocol strategy, and can be maintained at distance without any need to visit the location. Furthermore, the obtained water samples are not restricted to isotope analysis but can be used for any type of environmental water analysis. The current configuration can obtain 165 discrete rainwater samples with a minimum timely resolution of 5min or volume wise 2mm of rainfall. Our lab tests with dyed waters and waters with strongly differing isotopic signature demonstrate that the device can obtain, store and conserve samples without cross contamination over long periods of time. The device has been tested so far under several conditions, e.g. heavy summer thunderstorms with more than 50mm/24h of rainfall, sustained winter rainfall and in cold conditions involving melting of snow. This automated rainwater sampler provides an economic and sophisticated technological solution for monitoring moisture pathways and water transfer processes with the analytical quality of laboratory standard measurements on a new level of temporal and spatial resolution.

How to cite: Andermann, C., Queißer, T., Reich, M., Puri, B., Hovius, N., and Sachse, D.: Automated high resolution rain water sampler for stable water isotope monitoring , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13711, https://doi.org/10.5194/egusphere-egu2020-13711, 2020.

D10 |
| Highlight
Meghan Troup, David Barclay, and Matthew Hatcher

Benthic surveys in very shallow water (< 1 meter) are often carried out by remote sensing methods such as LiDAR, satellite imagery, and aerial photography, or by written observations paired with GPS point measurements and underwater video. Remote sensing can be helpful for large scale mapping endeavors, but the optical methods commonly used are limited in their effectiveness by cloud cover and water clarity. In situ surveys are often carried out manually and can therefore be quite inefficient. A proposed alternative method of small scale, high resolution mapping is an autonomous, amphibious hovercraft, fitted with high frequency single-beam and side-scan sonar instruments. A hovercraft can move seamlessly from land to water which allows for convenient and simple deployment. The sonar instruments are attached to a boat-shaped outrigger hull that can be raised and lowered automatically, enabling data collection in water as shallow as 10 cm. These data are used to extract seafloor characteristics in order to create detailed maps of the research area that include information such as sediment type, presence and extent of flora and fauna, and small-scale bathymetry.

How to cite: Troup, M., Barclay, D., and Hatcher, M.: Developing an Autonomous Hovercraft for Benthic Surveying in Very Shallow Waters, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3141, https://doi.org/10.5194/egusphere-egu2020-3141, 2020.

D11 |
| Highlight
Allison Chua, Aaron MacNeill, and Douglas Wallace

In comparison to the ocean’s immense volume and diversity of research areas, the number of sensors required to make the majority of desired measurements is quite small. This inequality of supply and demand elevates prices, adding further barriers for developing nations or fledgling research programs with smaller budgets attempting ocean science. Our work aims to demonstrate the potential of combining commercially available, open-source products to create inexpensive, configurable, and user-friendly platforms that can be adapted for underwater navigation and integration with most commercial oceanographic sensors.

Specifically, we will highlight modifications made to a Blue Robotics BlueROV2, which we have configured for various missions including vertical profiling of a coastal fjord and three-dimensional mapping of crude oil spills. The BlueROV2 offers an easily modified platform for physical mounting of sensors and streaming of sensor data via its onboard computer, a Raspberry Pi. Our custom circuit board is “sensor-agnostic”, powering sensors from a common source (the ROV battery) and using an Arduino that accepts analog or digital sensor inputs, allowing us to choose from a wide range of sensors. Physical modifications make use of inexpensive, readily available materials, and range from simple plastic brackets for small sensors to a skid for a sensor with half the ROV’s original weight, which utilizes pop bottles for buoyancy.

While products such as Pixhawk, Raspberry Pi, Arduino, and BlueROV have inspired hobbyists and youth around the world, they paradoxically have not been as widely embraced in the academic community, who perhaps remain unaware of their research potential. Thus, while there has yet to be an analogous push to develop inexpensive, small, power-efficient, and open-source sensors, these platforms offer exciting opportunities to build a new generation of oceanographic tools with measurement abilities far exceeding those of their predecessors. We are at an ocean technology tipping point, and, as MacGyver says, “With a little bit of imagination, anything is possible.”

How to cite: Chua, A., MacNeill, A., and Wallace, D.: Democratizing ocean technology: low-cost innovations in underwater robotics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10190, https://doi.org/10.5194/egusphere-egu2020-10190, 2020.

D12 |
James Dietrich, Mark Fonstad, and Aaron Zettler-Mann

Most river system analyses use either intensive, small-area surveys, or extensive, low-resolution surveys. Recent research trends have shown that both high-resolution and river-extent information are necessary to understand fundamental questions of river processes including patterns of critical habitat, sediment links, and river instability. As part of a larger NSF-funded research project, we have developed an open-source, boat-based mapping approach to measure river geometry, sediment size patterns, hydraulic habitats, and riverbank erosion patterns. The custom catamaran design we have developed integrates off-the-shelf, lower-cost sensors including high-resolution RTK/PPK GPS, inertial measurement (IMU), side-scan sonar, single-beam sonar, temperature, and a multi-camera array for 3D mapping above and below water. The design is meant to be “garage build friendly”, utilizing a minimum number of common tools and basic construction techniques. The sensor package will be user-friendly enough for non-expert use, allowing the boat to be deployed for citizen-science based data collection by loaning it to groups like watershed councils or volunteer conservation organizations. This will allow data to be collected over larger areas in less time than would be possible by “expert” researchers. The boat designs and software are developed as an open-source project and all hardware and software and will be made public as our testing and validation progress.

How to cite: Dietrich, J., Fonstad, M., and Zettler-Mann, A.: Open-source surface watercraft for Riverscape mapping, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4291, https://doi.org/10.5194/egusphere-egu2020-4291, 2020.

D13 |
Cristèle Chevalier and Guillaume Koenig

Beauty may sometimes lie in the eyes of the beholder, but in science it always lies in simplicity. We tested a very simple concept to get drifting platforms  that we could track and equip with sensors. We equipped an available floating device with a commercial GPS tracking system.  We tested this in several campaigns ( Italia, New-Caledonia, Tunisia and Guadeloupe) to study surface drifts. Later, we added chemical sensors to collect of lagrangian measurements. Here we present  the general setting of the drifter and the results of the first tests, which proved its efficiency and robustness despite its cheapness and its simplicity to use. We also discuss possibility of adding various kinds of sensors.

How to cite: Chevalier, C. and Koenig, G.: Drifting away from reality : A cheap way to get lagrangian measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9114, https://doi.org/10.5194/egusphere-egu2020-9114, 2020.

D14 |
Hessel Winsemius, Andreas Krietemeyer, Kirsten Van Dongen, Ivan Gayton, Frank Annor, Christiaan Tiberius, Marie-Claire Ten Veldhuis, Hubert Samboko, Rolf Hut, and Nick Van de Giesen

Detailed elevation is a prerequisite for many hydrological applications. To name a few, understanding of urban and rural flood hazard and risk; understanding floodplain geometries and conveyance; and monitoring morphological changes. The accuracy of traditional Global Navigation Satellite System (GNSS) chipsets in smart phones is typically in the order of several meters, too low to be useful for such applications. Structure from Motion photogrammetry methods or Light Detection and Ranging (LIDAR), may be used to establish 3D point clouds from drone photos or lidar instrumentation, but even these require very accurate Ground Control Point (GCP) observations for a satisfactory result. These can be acquired through specialised GNSS rover equipment, combined with a multi-frequency GNSS base station or base station network, providing a Real-Time (RTK) or Post-Processing Kinematics (PPK) solution. These techniques are too expensive and too difficult to maintain for use within low resource settings and are usually deployed by experts or specialised firms.

Here we investigate if accurate positioning (horizontal and vertical) can be acquired using a very recently released low-cost multi-constellation dual-frequency receiver (ublox ZED-F9P), connected with a simple antenna and a smart phone. The setup is remarkably small and easy to carry into the field. Using a geodetic (high-grade) GNSS antenna and receiver as base station, initial results over baselines in the order of a few km with the low-cost receiver revealed a positioning performance in the centimeter domain. Currently, we are testing the solution using a smart phone setup as base station within Dar es Salaam, to improve elevation mapping within the community mapping project “Ramani Huria”. We will also test the equipment for use in GCP observations within the ZAMSECUR project in Zambia and TWIGA project in Ghana. This new technology opens doors to affordable and robust observations of positions and elevation in low resource settings.

How to cite: Winsemius, H., Krietemeyer, A., Van Dongen, K., Gayton, I., Annor, F., Tiberius, C., Ten Veldhuis, M.-C., Samboko, H., Hut, R., and Van de Giesen, N.: Low-cost, high accuracy Global Navigation Satellite System positioning for understanding floods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8446, https://doi.org/10.5194/egusphere-egu2020-8446, 2020.

D15 |
Simon Thomsen and Kai Jensen

For the understanding of the carbon cycle in terrestrial ecosystems as well as of plant stress responses to drought and hypoxia, the study of fine root dynamics plays an important role. However, the number of relevant studies is still limited, which may be due, among other things, to the high costs of commercial minirhizotron systems. Here, we present an affordable (<500 €) and fully automated minirhizotron system, utilizing new developments in low-cost electronics and 3D-printing. The camera system is based on a Raspberry Pi and can be controlled by the user via a Python-based GUI. The open source character of the program also allows it to be adapted to the needs of the user or other requirements. The camera is controlled automatically by a stepper motor, which allows the precise recording of images at defined depths. The highest possible resolution is 3280 x 2464 pixels (8 MP) for an image area of about 2.5 cm x 2.5 cm, thus allowing the imaging of even root hairs and fungal hyphae. The structural components were manufactured using 3D printing. To protect against moisture, the camera and drive system are installed in a waterproof acrylic tube (60 mm diameter), which in turn is inserted into the rhizotron tubes (70 mm diameter) used in the field, making it possible to use the system in humid ecosystems.

How to cite: Thomsen, S. and Jensen, K.: An affordable, fully-automated minirhizotron system for observing fine-root dynamics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22448, https://doi.org/10.5194/egusphere-egu2020-22448, 2020.

D16 |
Bernd Wiese, Wolfgang Weinzierl, Peter Pilz, Tobias Raab, and Cornelia Schmidt-Hattenberger

Cheap and efficient groundwater pressure monitoring is a standard task in subsurface hydrology. We present application experience from a tube based pressure monitoring system that is applied to the Svelvik field laboratory for CO2  storage, Norway. In total 13 monitoring points were installed in depths between 51 and 89 m below ground level.

The pressure sensor is located above ground. It is temperature compensated to reduce measurement errors due to temperature variations. The pressure sensor is connected to a downhole low diameter tube that has a perforation in the respective measurement depth. The tubes are installed as smart casing installations, i.e. in the borehole annulus. This allows to keep the borehole open during installation of other monitoring devices.

Clean pumping of the well was not possible. Some filters were protected with fleece, while others were just perforated tubes. During installation, all tubes had hydraulic contact to the groundwater. After settling of the mud 3 of 4 fleece protected filters show sufficient communication, while all 9 filters that were just perforated were clogged and not usable for pressure monitoring.

The system has following advantages: (i) the downhole material is robust and cheap, allowing for multiple measurement points; (ii) has a small diameter (6 mm in the present case); (iii) since the static pressure is removed, a smaller sensor range is required; (iv) the sensors are located at the top of the borehole and can be retrieved after the campaign. Further, it can be installed without downhole metal parts.

The system has two disadvantages by design compared to submerged pressure sensors. (i) The absolute pressure can only be approximately determined, limited by the accuracy of the fluid density inside the tube. (ii) Pressure decreases can only be measured up to about 1 bar below piezometric head when the tube is filled with water.

The upper metres, that may be exposed to temperatures below 0 °C are filled with antifreeze. The choice of antifreeze allows for a certain static pressure correction. Minimum weight liquid is pure ethanol with a density of about 0.8 kg, allowing to measure pressure up to 2.8 bars below piezometric head for e.g. the 89 m deep measurement.


This work has been produced with support from the SINTEF-coordinated Pre-ACT project (Project No. 271497) funded by RCN (Norway), Gassnova (Norway), BEIS (UK), RVO (Netherlands), and BMWi (Ger-many) and co-funded by the European Commission under the Horizon 2020 programme, ACT Grant Agreement No 691712. We also acknowledge the industry partners for their contributions: Total, Equinor, Shell, TAQA. We thank the SINTEF-owned Svelvik CO2 Field Lab (funded by ECCSEL through RCN, with additional support from Pre-ACT and SINTEF) for assistance during installation and for financial support.

How to cite: Wiese, B., Weinzierl, W., Pilz, P., Raab, T., and Schmidt-Hattenberger, C.: Tiny diameter downhole pressure monitoring , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5584, https://doi.org/10.5194/egusphere-egu2020-5584, 2020.

D17 |
Adrian Heger, Volker Kleinschmidt, Alexander Gröngröft, Lars Kutzbach, and Annette Eschenbach

We applied the low-cost non-dispersive infrared sensor module K33 (ICB, Senseair, Sweden) for measurements of soil CO2 concentration. We integrated the sensor module in a new soil probe suitable for in situ measurements of soil gas CO2 concentration. Therefore, we covered the sensor module with epoxy resin. For continuous measurements, we connected our soil CO2 probe to a microcontroller (MEGA 2560 Rev3, Arduino.cc, Italy) equipped with a data logging shield (Adalogger FeatherWing, Adafruit, USA). In a laboratory experiment, we evaluated the accuracy and precision of our soil CO2 probe at changing temperature and humidity by comparison with the often used CO2 probe GMP343 (Vaisala, Finland) as a reference. In a field experiment, we buried our soil CO2 probe to test its performance under natural environmental conditions.

The result of the laboratory experiment is that our soil CO2 probe compares well with the GMP343, even at maximum relative humidity. The accuracy (<0.1 % CO2) was below the accuracy given by the manufacturer. The field experiment demonstrated that our soil CO2 probe provides high-quality measurements of soil CO2 concentrations under in situ soil conditions. After retrieving it, it still measured with the same accuracy and precision as before.

In summary, we used the sensor module K33 for the first time to measure in situ soil CO2 concentrations by integrating it into a newly developed probe. The cost-efficient availability of our CO2 probe opens up the opportunity to carry out continuous soil CO2 measurements over long time periods with simultaneously high spatial resolution.

How to cite: Heger, A., Kleinschmidt, V., Gröngröft, A., Kutzbach, L., and Eschenbach, A.: Application of a low-cost NDIR sensor module for measurements of in situ soil CO2 concentration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5819, https://doi.org/10.5194/egusphere-egu2020-5819, 2020.

D18 |
| Highlight
Ran N. Nof, Angela I. Chung, Horst Rademacher, and Richard M. Allen

Most operational earthquake early warning systems (EEWS) consider earthquakes to be point-sources and have difficulty providing imminent and robust source locations and magnitudes, especially at the edge of the seismic network or where seismic stations are sparse. Mini-arrays have the potential to estimate reliable hypocentral locations by beam forming (FK-analysis) techniques. They can also characterize the rupture dimensions and account for finite-source effects, leading to more reliable estimates of ground motions for large magnitude earthquakes. In the past, the high price of multiple seismometers has made creating arrays cost- prohibitive. Here, we present a setup of two mini-arrays of a new low-cost (<$150) seismic acquisition unit based on a high-performance MEMS accelerometer around conventional seismic stations. The expected benefits of such an approach include decreasing alert-times, improving real-time shaking predictions and mitigating false alarms.

We will present our new 24-bit device details, benchmarks, and results from two MAMAs deployed at the UC Berkeley and Humboldt State University campuses. The new device shows lower noise levels than the currently available off-the-shelf 16-bit sensors, commonly used by several citizen-science projects (e.g. QCN, CSN, MyShake, etc.). This lower noise level enables us to record and process lower magnitude events. We show examples of back-azimuth calculations of M>=2.5 events at a range of <100km from the MAMA center and discuss some of the limitations and considerations of the MAMA deployments.

How to cite: Nof, R. N., Chung, A. I., Rademacher, H., and Allen, R. M.: MEMS Accelerometers Mini-Array (MAMA) - initial results and lessons learned, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10966, https://doi.org/10.5194/egusphere-egu2020-10966, 2020.

D19 |
Adrian Butler, Tom Rowan, and Alex Colyer

The work sets out a method and evaluates the accuracy of a 3D printed turbine flow meter for open channel and pipe flow; that can be optimised for different situations.  The motivation for this project was to create flow meters that are low cost and available to community groups and interested individuals, this work was conducted as part of the CAMELLIA project (Community Water Management for a Liveable London).  The flowmeters have been trialled in a number of locations by users with different skill sets and technical know-how.  Hall effect sensors have been coupled with consumer grade electronics to develop the most opensource system possible.  This work has taken advantage of recent advances in DLP printing, allowing for greater resolution at a lower cost than previous generations of 3D printers.  This is combined with work developed by the Open Prop software team, has enabled user customisable sensors to be built.  

The presented work aims to create an opensource, low cost and easy to use solution to some flow monitoring problems.  This paper details the lessons learnt and successes of this approach; it aims to create a basis for which further development and deployment of these sensors can be achieved.  

How to cite: Butler, A., Rowan, T., and Colyer, A.: On the development of low cost, optimizable, 3D printed turbine flow meters for pipe and open channel applications, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21929, https://doi.org/10.5194/egusphere-egu2020-21929, 2020.

D20 |
Nick van de Giesen, John Selker, Koen Hilgersom, and Anna Solcerova

In the framework of the Small Reservoirs Project (www.smallreservoirs.org), evaporation in semi-arid areas from open water has been measured through water balances, floating evaporation pans, and eddy covariance measurements. Each method showed that the actual evaporation was 30%-50% less than the evaporation from open water as predicted by Penman. During daytime, this reduced evaporation may be due to the formation of a stable internal boundary layer over the reservoirs. One would expect that this evaporation reducing effect would at least partially be offset during the night when the warm water would induce strong turbulent transport through an unstable local boundary layer. Through detailed Distributed Temperature Sensing observation in ponds, lakes, and reservoirs in different parts of the world, it was observed that during cloudless nights with low wind speeds or no wind, the top layer (1cm-2cm) of the water was one to two degrees colder than the air immediately above it. Such a temperature difference would again set up a stable layer, hindering turbulent transport of heat and water vapor into the atmosphere. 


It was hypothesized that outward longwave radiation, which during cloudless nights can quickly reach 200 W/m2, would cause a thin layer of cold water on top of the warmer water body. Through conduction, this cold layer would grow until it would become unstable, at which point the surface would be (partially) refreshed through downward finger flow. Detailed numerical simulations of the heat transport in the water body were undertaken to test this hypothesis. The numerical results indeed showed the cooling of the top layer and formation of instabilities with characteristic length and time scales. To test these results and the general concept, a MacGyver-worthy laboratory set-up was built consisting of an insulated 20 liter bucket, covered by a double hemispheric dome of perspex. On the inside of the dome, a thermal camera was attached at the apex. The space between the inner and outer dome was filled with dry ice to create an inside surface temperature of about 230K. After the dry ice was added, surface cooling was observed, followed by the formation of zones with upwelling warm water and downwelling cold water. These circulation cells were comparable in size to the simulated ones. A detailed analysis of spatial and temporal scales of the laboratory and simulation results will be presented.

How to cite: van de Giesen, N., Selker, J., Hilgersom, K., and Solcerova, A.: Night-Time Cooling of Surface Water: Laboratory experiment and numerical simulation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2953, https://doi.org/10.5194/egusphere-egu2020-2953, 2020.

D21 |
John Arkwright, Eddie W Banks, Margaret Shanafield, and Anthony Papageorgiou

Most streambed heat tracer studies use vertical, ambient temperature profiles and a 1D analytical solution of the heat diffusion–advection equation to estimate hyporheic exchange fluxes (HEF). This approach has limited capacity in complex flow settings, which has led to the successful development of active heat pulse sensing to investigate the dynamic 3D flow fields in the near subsurface and to quantify HEF. At the scale of the hyporheic zone very small water level fluctuations drive changes in the hydraulic gradients across streambed bedform structures. Generally, hydraulic head gradients are measured with pressure sensors deployed in shallow monitoring wells, but such devices do not have the required vertical spatial resolution and precision to accurately evaluate these processes. New and novel research developed by the biomedical community for in-vivo medical devices can now be used in the geosciences field to measure temperature and pressure at a much higher spatial and temporal resolution to overcome these challenges. As part of this research we have developed a fibre optic, active heat pulse and pressure sensing instrument (formed from Fibre Bragg Grating sensor arrays) to determine small hydraulic gradients in the subsurface and to quantify the exchange fluxes. The instrument was tested in a controlled laboratory environment and in the field. Combining point-scale measurements from this novel instrument with near surface geophysical data and other hydrological observations (i.e. measurements with fibre optic distributed temperature sensing) can be used to upscale some of the key physical exchange processes to the stream reach and river scale.

How to cite: Arkwright, J., Banks, E. W., Shanafield, M., and Papageorgiou, A.: Novel methods for identifying and quantifying hyporheic exchange fluxes using Fibre Bragg Grating sensor arrays, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22195, https://doi.org/10.5194/egusphere-egu2020-22195, 2020.

D22 |
Shakir Ahmed and Jan Friesen

Satellite data for West Africa still struggle with local climate and farming practices. Despite the increasing data frequency, the rainy season in West Africa features such a dense cloud cover that many satellites cannot provide cloud free images. In addition, many farmers practice intercropping, where a single plot can be used to grow different crops such as maize and beans or even feature trees. Although the spatial resolution of satellites is ever increasing, this very small-scale intercropping still poses challenges for satellite data analysis. Yet, spatial data on vegetation status and distribution is required for running crop models.

Within the EU project TWIGA we therefore developed a smartphone app that allows farmers to collect vegetation data where it matters – on their plot!

Based on field trial that started in August 2019 we present vegetation metrics derived from smartphone photos as well as auxiliary data collected by test users in Ghana. The vegetation metrics are further combined with Sentinel 2A NDVI timeseries and fill a cloud cover caused data gap during the peak growing season.

How to cite: Ahmed, S. and Friesen, J.: Farmers see where the satellite is blind – using citizen science to fill satellite-derived vegetation data gaps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13145, https://doi.org/10.5194/egusphere-egu2020-13145, 2020.