Displays

The extent and the fluid dynamics of the vadose zone (VZ) of an aquifer have a direct impact on the aquifer recharge, the water quality and the pollutants transfer from the soil to the groundwater. The water – rock interactions and mass and heat transfers under the impact of microbial processes and agricultural practices could undergoes significant changes in the chemical composition of the water flowing throughout the VZ, which may induce pollution of groundwater.

The growing dependence on groundwater for potable water supplies draws attention to protect the quality of groundwater resources at national and international levels to the need. It is important to detect the contamination risk of aquifers and develop an integrated water management methodology based on innovative environmental monitoring tools and sophisticated numerical models to protect groundwater resources and guarantee their good quality for domestic, agricultural and industrial needs. For this reason, the monitoring of VZ dynamics has become essential to study the transfer mechanisms of mass (water, gas and contaminants) and heat from the soil to the groundwater. This should allow rapid detection of the pollutants migration through an aquifer and take relevant measures to protect groundwater before the contaminants reach the water table.

In this context, an Observatory of transfers in the vadose zone (O-ZNS) is being developed at Villamblain (Orléans, France) in an agricultural field. The O-ZNS project consists of a well with a diameter of 4 m and a depth of 20 m which will allow access to the entire VZ of the Beauce aquifer. The main target of the O-ZNS platform is to acquire original and unique data on the reactive transfers of fluids and heat in the VZ, in order to follow in situ and in real time the highly coupled physical, chemical, and biological processes taking place over the long term. The O-ZNS project also aims to assess the performance of all types of instrumentation dedicated to non-destructive measurement or local sampling of fluids, rocks, and microbs in the VZ for long duration.

To meet these objectives, a myriad of innovative monitoring tools (e.g.,environmental sensors, fiber optic sensors, geophysical imaging, ….) will be deployed in the O-ZNS from the soil surface to the aquifer (from 0 to 20 m deep) using the well and the surrounding boreholes. Also, note that to date, there are still difficulties in the instrumentation of rock materials and relevant solutions must be developed. These environmental monitoring techniques will allow to generate a huge quantity of data on the physical, chemical, and microbiological coupled processes.

How to cite: Abbar, B., Jodry, C., Isch, A., Laurent, G., and Azaroual, M.: Monitoring of the mass and heat transfers through a heterogeneous karstic limestone vadose zone of an agricultural field (Beauce Aquifer, Orleans, France), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5294, https://doi.org/10.5194/egusphere-egu2020-5294, 2020.

Solar Ultraviolet (UV) radiation has significant impacts on human health (e.g., skin cancer) and the environment (e.g., agricultural production and plant litter decomposition). Reductions in UV-absorbing stratospheric ozone resulting from climate change and the anthropogenic emission of ozone depleting substances raised concerns regarding future levels of surface UV radiation. Responding to this potential threat, the U.S. Department of Agriculture (USDA) investigated the need for UV monitoring across the U.S. in 1991 and established the UV-B Monitoring and Research Program (UVMRP) headquartered in Natural Resource Ecology Laboratory at Colorado State University later in 1992. The UVMRP is tasked with providing information on the geographical distribution and temporal trends of UV radiation and studying the effects of UV radiation on a wealth of agricultural interests including crop plants, rangelands, and forests. The UVMRP currently consists of 37 climatological monitoring sites and 4 research sites, most of which are distributed across the U.S., with an additional site in Canada and another in New Zealand. Collectively, these sites encompass 20 ecoregions. Each UVMRP site is equipped with four primary irradiance instruments including the: 1) UV MultiFilter Rotating Shadowband Radiometer (UV-MFRSR), 2) visible MFRSR, 3) UVB-1 broadband meter, and 4) Photosynthetically Active Radiation (PAR) sensor. The UV-MFRSR measures total horizontal, diffuse horizontal, and direct normal irradiance at nominal 300, 305, 311, 317, 325, 332, and 368 nm at 2 nm FWHM (full-width half-maximum). The VIS-MFRSR measures the same three irradiance components at nominal SiC, 415, 500, 610, 665, 860, and 940 nm at 10 nm FWHM. PAR and UVB-1 sensors measure broadband irradiances over the 400-700 nm and 280-320 nm ranges, respectively. All these observations are sampled every 15 or 20 seconds and stored as an average value every three minutes. The raw data measurements are processed following a variety of Quality Control (QC) and calibration procedures to ensure the quality of the data. The primary data products (i.e., irradiances) as well as the derived products (e.g., UV Index and weighted daily/hourly sums) are distributed through the UVMRP website (http://uvb.nrel.colostate.edu). In this poster, we present a UV climatology study that explores long-term trends of erythemal irradiance at eight locations across the U.S. derived from 8-11 years of UVMRP measurements.

How to cite: Gao, W., Janson, G., Corr, C., and Chen, M.: USDA UV-B Monitoring and Research Program, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6196, https://doi.org/10.5194/egusphere-egu2020-6196, 2020.

Streamflow is of fundamental importance to hydrology and water resources management, but it is difficult and/or expensive to measure directly in a continuous manner. Consequently, continuous measurements mostly make use of stage recording, with the values of stage being converted into those of streamflow by means of rating curves (or a digital counterpart). Historically, a major practical advantage of a one input – one output stage-discharge relationship was its straightforward handling in the form of a diagram, but that is no longer relevant. Thus, there is little reason why streamflows should be inferred from stage only, provided an additional input variable proves useful and can easily (and inexpensively) be recorded continuously.

Electrical conductivity (EC) appears as a potentially powerful candidate to serve as a further input variable improving streamflow estimates, and artificial neural networks (ANNs) are well suited to handle more than one input. In alpine streams EC has been reported to be a viable alternative to water level as predictor variable in streamflow estimation (Weijs et al., 2013). The approach advocated here differs from that just cited by using EC in addition to, not in lieu of stage as predictor variable. That way, it is believed that the field of potential application should be wider. In the work reported here, stage and EC data were used to develop a multilayer perceptron type ANN (2-4-1) to estimate flow in a small Austrian stream (Mödling) with a catchment of fairly mixed composition (forested, agricultural and urbanized areas). While the alpine catchment studied by Weijs et al.(op. cit.) probably is at the upper end of EC usefulness in streamflow estimation, the Mödling catchment offers less favourable conditions, with EC being potentially subject to some influence of human activities. In spite of these modest (but not unusual) conditions, the research reported documents that EC improved streamflow estimates. An analysis of the data with the aid of a network interpretation diagram, Garson's algorithm (Garson, 1991) and a sensitivity analysis performed on the two input variables (stage and EC, resp.) shows EC to be a useful additional predictor, with its relative 'importance' amounting to roughly one third of that of stage in this catchment.

References

Garson, G.D.: Interpreting neural-network connection weights. Artif. Intell. Expert, 6, 47-51, 1991.

Weijs, S.V., Mutzner, R., Parlange, M.B.: Could electrical conductivity replace water level in rating curves for alpine streams? Water Resour. Res 49, 343-351, 2013.

How to cite: Schmid, B. H.: Enhanced flow rating using neural networks with water stage and electrical conductivity as predictors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1804, https://doi.org/10.5194/egusphere-egu2020-1804, 2020.

Through Remote Sensing of Irish Surface Water (INFER) project, we are validating the algorithms to measure the  water quality using Sentinel 2 imagery, which comprises of two European Space Agency (ESA) terrestrial satellites with combined temporal resolution of 5 days. The project is focused on selection of optimal algorithms that will be applicable in Irish context in relation to the high cloud cover and relatively small sizes of the water bodies. The current procedure entails collection of reflectance data from the lakes during the Sentinel overpass as it helps to identify the correct atmospheric correction algorithm. Field radiometry tasks were carried out using TRIOS RAMSES radiometers. Standard field procedures were employed for acquiring glint free reflectance from the water bodies.

Historical data collected from the 11 lakes, which had field bathymetry survey data, were analysed in order to determine the influence of environmental conditions on the quality of samples. Based on the analysis, recommendations to collect field samples from areas deeper than 10 m and 30 m away from the shoreline were provided in order to avoid the reflectance from the bottom and the surrounding topography. A site selection process was undertaken during the spring of 2019 to shortlist appropriate sites for field validation of satellite-derived products. A total of fifteen lakes were identified for field validation based on several criteria so as to ensure lakes with varying size, depth, trophic status and Water Framework Directive (WFD) status . In addition, a timetable for proposed sampling was established by drawing up a timetable of satellite passes starting from summer of 2019. C2RCC and Acolite processors are being used to compute the chlorophyll and turbidity from identified lakes. Considering the fast changing weather condition of Ireland, it was difficult to obtain the exact overlap between the sentinel overpass and the field sampling. In order to address this issue, the field samples collected within 10 days from the sensor overpass were considered for the field validation. Study of the satellite derived water chemistry data showed that the data collected outside of that time window may not represent the natural fluctuation that occurs in the water bodies.

The end product of this project is the web platform with the access to Sentinel 2 MSI data products where users can visualize the water quality products for Ireland. This platform will promote the use of earth observation data for inland water quality monitoring and would enable sustainable utilization of the water resources.

How to cite: Karki, S., French, K., McCarthy, V., Hanafin, J., Jennings, E., Delaney, C., Veerkamp, V., Golden, A., McKinstry, A., and Ahmed, M.: In-Situ Validation of Water Quality Algorithms and Monitoring of Irish Lakes using Sentinel 2 Imagery , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2223, https://doi.org/10.5194/egusphere-egu2020-2223, 2020.

Lakes and water reservoirs are important ecosystems providing such services as drinking water, recreation, support for biodiversity as well as regulation of carbon cycling and climate. There are about 117 million lakes worldwide and a high need for regular monitoring of their water quality. European Union Water Framework Directive (WFD) stipulates that member states shall establish a programme for monitoring the ecological status of all water bodies larger than 50 ha, in order to ensure future quality and quantity of inland waters. But only a fraction of lakes is included in in-situ monitoring networks due to limited resources. In Latvia, there are 2256 lakes larger than 1 ha covering 1.5% of Latvian territory, and approximately 300 lakes are larger than 50 ha, but only 180 are included in Inland water monitoring program, in addition, most of them are monitored once in three to six years. Besides, local municipalities are responsible for the management of lakes, and they are also interested in the assessment of ecological status and regular monitoring of these valuable assets. 

Satellite data is a feasible way to monitor lakes over a large region with reasonable frequency and support the WFD status assessment process. There are several satellite-based sensors (eg. MERIS, MODIS, OLCI) available specially designed for monitoring of water quality parameters, however, they are limited only to use for large water bodies due to a coarse spatial resolution (250...1000 m/pix). Sentinel-2 MSI is a space-borne instrument providing 10...20 m/pix multispectral data on a regular basis (every 5 days at the equator and 2..3 days in Latvia), thus making it attractive for monitoring of inland water bodies, especially the small ones (<1 km²). 

Development of Sentinel-2 satellite data-based service (SentiLake) for monitoring of Latvian lakes is being implemented within the ESA PECS for Latvia program. The pilot territory covers two regions in Latvia and includes more than 100 lakes larger than 50 ha. Automated workflow for selecting and processing of available Sentinel-2 data scenes for extracting of water quality parameters (chlorophyll-a and TSM concentrations) for each target water body has been developed. Latvia is a northern country with a frequently cloudy sky, therefore, optical remote sensing is challenging in or region. However, our results show that 1...4 low cloud cover Sentinel-2 data acquisitions per month could be expected due to high revisit frequency of Sentinel-2 satellites. Combination of C2X and C2RCC processors was chosen for the assessment of chl-a concentration showing the satisfactory performance - R² = 0,82 and RMSE = 21,2 µg/l. Chl-a assessment result is further converted and presented as a lake quality class. It is expected that SentiLake will provide supplementary data to limited in situ data for filling gaps and retrospective studies, as well as a visual tool for communication with the target audience.

How to cite: Jakovels, D., Brauns, A., Filipovs, J., and Soomets, T.: SentiLake - Sentinel-2 satellite data-based service for monitoring of Latvian lakes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7133, https://doi.org/10.5194/egusphere-egu2020-7133, 2020.

As the succeeder of the Geostationay Ocean Color Imager (GOCI), the world first geostationary ocean monitoring satellite, the second GOCI (GOCI-II) will be launched in 2020. GOCI-II has 12 narrow bands of 380~865nm center wavelength for earth observation and an broadband band for star observation. The main goals of this GOCI series are to monitor ocena short-term/long-term phenomena like red-tide blooming, floating algae movements, tidal movements, low sea surface salinity variation, sea surface currents, primary productivity, etc. GOCI-II is able to obtain 10 images for the area around Korean peninsula and an image for the full-disk area in everyday during its 10 years lifetime. To handle this huge GOCI-II data, we have to develop the dedicated GOCI-II Ground Segment (G2GS) system with data acquisition antenna and GOCI-II operating infrastructure. G2GS have good performance like the data distribution output delay within 60 minutes, the 99% system operability with redundancy, etc. G2GS also generates 26 level-2 data products and provides all data with dedicated software program like GOCI-II plug-in of SNAP framework. 

How to cite: Han, H.-J., Heo, J.-M., Yang, H., Choi, W.-C., Choi, H.-M., and Park, Y.-J.: Introduction to the second Geostationary Ocean Color Imager (GOCI-II) and its ground segment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7813, https://doi.org/10.5194/egusphere-egu2020-7813, 2020.

Atmospheric water vapor plays a key role in weather and climate. Knowledge about its variability, diurnal and seasonal cycles, as well as its long-term trend is necessary to improve our understanding of the hydrological cycle. H2O total columns are measured by the two remote sensing techniques, ground-based solar absorption FTIR spectroscopy and a GPS (Global Positioning System) receiver, over a site in central Mexico. The Altzomoni Atmospheric Observatory (3989 m a.s.l., 19.32ºN, 98.65ºW) is a high altitude station located within the Izta-Popo national park, 60 km SE from Mexico City. The time series of GPS and FTIR show a high correlation between coincident hourly means. Both techniques are complementary since despite that GPS works throughout day and night and also in cloudy and rainy weather conditions, the FTIR data provides in addition altitude-resolved information about the atmospheric water vapor and permits to distinguish different isotopes.

In this study, we show water vapor columns in the 2013 to 2019 period for this region retrieved from FTIR and GPS measurements and preliminary results about their isotopic composition (H216O, H218O and HD16O). We discuss the opportunity to study the hydrological cycle in central Mexico using the relationship between light and heavy isotopes, a relationship that gives valuable information about the sources and transport pathways.

How to cite: Zuber, A., Stremme, W., Grutter, M., Adams, D., Blumenstock, T., Hase, F., and Schneider, M.: Water vapor measurements in central México using two remote sensing techniques: FTIR spectroscopy and GPS, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10409, https://doi.org/10.5194/egusphere-egu2020-10409, 2020.

The collection of hydrological measurement data comprises a broad range of challenges beyond the development and deployment of sensing devices. Especially the transmission of the collected (raw) data to central data servers may be a challenging task depending on the available infrastructure.

In our presentation we will discuss the applicability of Internet of Things (IoT) technologies to enable a lightweight data collection workflow relying on the Message Queuing Telemetry Transport (MQTT) protocol as well as the SensorThings API standard of the Open Geospatial Consortium (OGC). These standards are especially optimised to reduce communication overheads, to be viable via resource constrained communication links, and to support a seamless plug-and-play integration of new measurement devices.

As part of this presentation, we will introduce the communication patterns and messages used by the data collection mechanism. This will be combined with a discussion how these IoT standards can be coupled to existing sensor hardware and which types of communication link can be used. Afterwards, we will also discuss the design of a data management server that integrates the collected measurement data. This comprises on the one hand connectors to the IoT data streams but on the other hand also data management and storage functionality, as well as interoperable interfaces for sharing the collected data.

For the validation of the presented concept, a pre-operational deployment at the Wupperverband, a regional water management association in Germany, will be shown. This comprises not only the practical experiences gained during the operation but also recommendations on future challenges such as semantic interoperability (e.g. vocabularies) as well as the efficient management of large amounts of incoming time series data (e.g. via dedicated database concepts).

Thus, in summary our contribution aims to contribute to the discussion on how IoT technologies may help to facilitate the collection of hydrological measurement data and to support the sharing of such data.

How to cite: Drost, S., Speckamp, J., Hollmann, C., Malewski, C., Rieke, M., and Jirka, S.: Internet of Things Technologies for the Efficient Collection of Hydrological Measurement Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10452, https://doi.org/10.5194/egusphere-egu2020-10452, 2020.

How to cite: Munke, J., Götz, A., Heller, H., Hachinger, S., Laux, D., Goussev, O., Handschuh, J., Wüst, S., Bittner, M., Mair, R., Wittmann, B., Rehm, T., Beck, I., and Neumann, M.: Connecting data streams with On-Demand Services in the Alpine Environmental Data Analysis Centre, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10660, https://doi.org/10.5194/egusphere-egu2020-10660, 2020.

There are many networks of sensors for earth system science. Most networks are local or regional in scale (eg mesonets). National weather services maintain networks for meeting stakeholder needs and responsibilities to the WMO Global Observing System. These systems are comprised of single task rigid sensors generally attached to logger systems. Sage [1] is a project which will deliver a cyberinfrastructure network allowing multi-tenant, multi-tasked sensor packages. In addition to traditional meteorological instrumentation and advanced static and pan-tilt-zoom cameras Sage nodes have powerful compute infrastructure allowing machine learning based phenomenology detection at the edge. This allows science question-based reconfiguration of sensor operation. A well described Application Programming Interface (API) will allow new algorithms to be pushed to the edge and new sensor packages to be added including those that have complex configuration spaces like LIDAR and Radar. This presentation will introduce Sage and present early example results such as using cameras for cloud classification, inundation caused by heavy rainfall and early wildfire ignition detection. 

[1]  https://www.research.northwestern.edu/world-watchers/

How to cite: Collis, S., Beckman, P., Kelly, E., Catlett, C., Sankaran, R., Altintas, I., Olds, J., Ferrier, N., Park, S., Kim, Y., and Papka, M.: Introducing Sage: Cyberinfrastructure for Sensing at the Edge., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12320, https://doi.org/10.5194/egusphere-egu2020-12320, 2020.

Atmospheric observatories in the remote areas represent the primary infrastructure for the state-of-the-art meteorological and climate research and play a crucial role in Climate Change comprehension. However, the World Meteorological Organization Global Atmosphere Watch (WMO-GAW) states in their 2018 final report that “the fate of the next generation of monitoring stations will be dramatically modified by the breakthroughs of new low-cost sensor (LCS) technologies.”. The development and improvement of low-cost technologies are proving notable applications and today LCSs are already playing a crucial role in fields such as model or emission validation and spatial variability of pollution[1]. Upcoming earth observation programmes, applications, services and support in citizen inclusion in earth monitoring are pushing the European Union (EU) in funding R&D to assess low-cost technologies, thus making the introduction of basic and applied research imperative.
PIONEER* aims at establishing a low-cost wireless sensor network (LCS-WSN) for the study of transboundary transport phenomena of air pollutants. Given its highly relevance for the Earth climate, ecosystems, and human health, primary endeavor will be directed towards the study of tropospheric ozone to obtain quantitative, reproducible in-situ measurements. Tropospheric ozone is one of the most important atmospheric gases involved in photochemical reactions[2], it plays a central role in the radiative budget of the atmosphere and it is the third greenhouse gas in the troposphere[3]. Also, surface ozone is a dangerous secondary pollutant causing harm to human health and ecosystems[4]. Since the troposphere is a very complex system the goal is to develop and deploy a reliable LCS-WSN, along the trail Munich-Venice, to be used by scientists as well as citizen engineers in remote areas, where the needs of reliable dense spatial data to model the transport phenomena and Climate Change effects is decisive. 
PIONEER will exploit the existing open source technologies and commercial low-cost sensors to provide a LCS-WSN systems for long term climate data collection, a cloud-assisted database for time series collection and management, a web portal for uploading, displaying, performing statistical analysis and downloading records and metadata in a fully open access fashion, a comprehensive open source repository with tools, guidelines and application developed. The software will be open-source and released under copyleft license, thus allowing the complete reproducibility of all the developed devices and tools. 

*Individual Global Fellowships granted by the Research Executive Agency. 
Grant Agreement number: 844526 — PIONEER — H2020-MSCA-IF-2018

[1] Lewis, Alastair, W. Richard Peltier, and Erika von Schneidemesser. "Low-cost sensors for the measurement of atmospheric composition: overview of topic and future applications." (2018).

[2] Crutzen, P.J., Lawrence, M.G., Poschl, U.,“On the background photochemistry of tropospheric ozone”, Tellus AB 51, 123–146 (1999).

[3] Forster, Piers, et al. "Changes in atmospheric constituents and in radiative forcing. Chapter 2." Climate Change 2007. The Physical Science Basis. 2007.

[4] Cooper, Owen R., et al. "Global distribution and trends of tropospheric ozone: An observation-based review." (2014).

[5] Young, P. J., et al. "Pre-industrial to end 21st century projections of tropospheric ozone from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)." Atmospheric Chemistry and Physics 13.4 (2013): 2063-2090.

How to cite: Dallo, F., Zannoni, D., de Blasi, F., Gabrieli, J., Barbante, C., Bonasoni, P., Cristofanelli, P., Calzolari, F., Fjaeraa, A. M., Bäcklund, A., and Bauman, F.: PIONEER: open wireless sensor network for smart environmental monitoring of remote areas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15913, https://doi.org/10.5194/egusphere-egu2020-15913, 2020.

Over the past decade, the global proliferation of cyanobacterial harmful algal blooms (CyanoHABs) have presented a major risk to the public and wildlife, and ecosystem and economic services provided by inland water resources. As a consequence, water resources, environmental, and healthcare agencies are in need of early information about the development of these blooms to mitigate or minimize their impact. Results from various components of a novel multi-cloud cyber-infrastructure for initial detection and continuous monitoring of spatio-temporal growth of CyanoHABs is highlighted in this study. The novelty of this CyanoTRACKER framework is the integration of community reports, remote sensing data and digital image analytics to differentiate between regular algal blooms and CyanoHABs. Individual components of CyanoTRACKER include a reporting website, mobile application (App), remotely deployable solar powered enabled automated hyperspectral sensor (CyanoSense), and a cloud-based satellite data processing and integration tool. All components of CyanoTRACKER provided important data related to CyanoHABs assessments for regional and global waterbodies. Reports and data received via social cloud including the mobile App, Twitter, Facebook, and CyanoTRACKER website, helped in identifying the geographic locations of CyanoHABs infested waterbodies. A significant increase (124.92%) in tweet numbers related to CyanoHABs was observed between 2011 (total relevant tweets = 2925) and 2015 (total relevant tweets = 6579) that reflected an increasing trend of the harmful phenomena across the globe as well as increased awareness about CyanoHABs among Twitter users. The CyanoHABs infested geographic locations extracted via social cloud were utilized for the deployment of CyanoSense at smaller waterbodies and analysis of satellite data for larger waterbodies. CyanoSense was able to differentiate between ordinary algae and CyanoHABs through the use of their characteristic absorption feature at 620nm. The results and products from this infrastructure can be rapidly disseminated via CyanoTRACKER website, social media, and direct communication with appropriate management agencies for issuing warnings and alerting lake managers, stakeholders and ordinary citizens to the imminent dangers posed by these environmentally harmful phenomena.

How to cite: Mishra, D.: CyanoTRACKER: A cloud-based integrated multi-platform architecture for global observation of cyanobacterial harmful algal blooms , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10822, https://doi.org/10.5194/egusphere-egu2020-10822, 2020.

The presented work is fully practical. Hydrogeological (water) well logging is very different from a petroleum well logging in terms of equipment and budget. A water uplift well cost is quite low, and it is not make a big economic sense to use automatic well logging systems for it. Hence, a lot of engineers are trying to "invent" their own resistivity logging tools or just use a conventional AMNB equipment for surface electrical prospecting to explore the water wells. It is feasible, because a water depth and, consequently, the logging cable length is usually limited by 200 m, it is not hard to pull the cable manually. Such a solution is very cheap and easy to implement. However, the process of logging take time and includes hundreds of steps. So, errors in the process is often.

The aim of this work is to adapt electric resistivity imaging system SibEr for well logging, simplify the logging process and create the possibility for a well drilling team to make the well logging themselves, including the recommendation of the filter installation depth.

The solution includes:

- Hardware: well logging cable with 32 (24) takeouts at the bottom hole end with 20 cm spacing;

- Embedded software for resistivity and induced polarization data acquisition;

- Data processing software to create the logging report with diagrams and suggested filter intervals.

How to cite: Manstein, Y. and Alsynbaev, K.: Water well logging and automatic log interpretation technology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19513, https://doi.org/10.5194/egusphere-egu2020-19513, 2020.

In the past decades, space-based Earth Observations (EO) have been rapidly advancing in monitoring the global water cycle, in particular for the variables related to precipitation, evapotranspiration and soil moisture, often at (tens of) kilometre scales. Whilst these data are highly effective to characterise water cycle variation at regional to global scale, they are less suitable for sustainable management of water resource, which needs more detailed information at local and field scale due to inhomogeneous characteristics of the soil and vegetation. To effectively exploit existing knowledge at different scales we thus need to answer the following questions: How to downscale the global water cycle products to local scale using multiple sources/scales of EO data? How to explore and apply the downscaled information at the management level for understanding soil-water-vegetation-energy processes? And how to use such fine-scale information to improve the management of soil and water resources? An integrative information aqueduct (iAqueduct) is proposed to close the gaps between global satellite observation of water cycle and local needs of information for sustainable management of water resources. iAqueduct aims to accomplish its goals by combining Copernicus satellite data (with intermediate resolutions) with high resolution Unmanned Aerial System (UAS) and in-situ observations to develop scaling functions for soil properties and soil moisture and evapotranspiration at high spatial resolution scales.

How to cite: zeng, Y. and the iAqueduct Team: An Integrative Information Aqueduct to Close the Gaps between Global Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources (iAqueduct), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9782, https://doi.org/10.5194/egusphere-egu2020-9782, 2020.

Rupture processes comprehension and dynamics of slope movements have been studied for several decades through surface observations of unstable objects (INSAR, LIDAR, geomorphological...) and very punctually in the slid masses (inclinometric survey). That kind of observations usually requires heavy amenities that are energy-consuming, vulnerable, and very expensive. We have developed within a public-private partnership a new generation of connected sensors. In this paper, we present a set of displacement data collected on active landslides located in the Alpes-Maritimes region of France. This is a region subject to intense climatic forcing, in areas of high vulnerability, and potentially a hotspot of climate change in the coming years. This climate, referred as North Mediterranean, is defined by intense rainfall (>100mm/day). This territory is particularly vulnerable due to its abrupt pre-Alps reliefs, which are located very close to the sea, and also constrained by strong urban pressure.

The acquisition of good-quality observational data and the installation of sensors on this type of landslide remain a difficult scientific challenge which is full of compromises in an attempt to obtain, in the long term, effective warning systems. The accessibility of the study site, its lithologic and hydrogeological complexities, and the management of the installed sensors (energy resource, location representative of the mass, cost ...) are issues to the development of these systems.

Two sites instrumented during 2019 suffered from heavy weather during autumn (cumulative rainfall of more than 800 mm over 2 months), causing an acceleration of the displacements, and allowing us to watch the transition from the latency phase to the gravitational paroxysm. This period of severe weather is part of a succession of climatic events that we call "Mediterranean events", producing cumulative rainfall in a few hours/days/weeks higher than the yearly normals.

The data set presented and discussed consists of (1) meteorological observations (with a focus on rainfall accumulation), (2) piezometric observations (subsurface ground water level and conductivity), (3) borehole inclinometer measurements, (4) GNSS displacement observations (daily solutions), (5) displacement observations between two points using laser rangefinders, and (6) surface clinometric observations.

This new generation of sensors increases the frequency of measurement, which makes it possible to visualize the “life of the slope” and thus to refine the knowledge of the transition phases. These dormant phases, or saturation, are key moments in the transition from a stable state to an unstable state, and reveal the “breathing” of the slope.

This communication will be made in the framework of a PhD funded by the socio-economic partner Azur Géo Logic, and the Provence-Alpes-Côte d'Azur region.

How to cite: Chochon, R., Lebourg, T., Martin, N., Vidal, M., Hernandez, M., Besso, R., and Drouillas, Y.: New generation of sensors for landslide observation: first results, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16541, https://doi.org/10.5194/egusphere-egu2020-16541, 2020.

The information of water amount in soil is essential in many fields (e.g. agriculture, forestry, hydrology). Methods to determine water content (WC) can be classified as direct and indirect. Direct methods are connected with the destruction of a sample, are time-consuming and impractical for the measurements in the crop fields. Indirect methods ensure non-destructive and in situ measurements and depend on monitoring a dielectric soil property which is a function of WC. The soil dielectric permittivity is one of the used properties which may be determined by time domain reflectometry (TDR) or frequency domain reflectometry (FDR) techniques. TDR probes are expensive and can be easily damaged at multiple insertions to soil. The open-ended (OE) probes, well-known for their application in the measurements of the complex dielectric permittivity of materials in broadband frequency range, are more resistant to mechanical damage but they are characterized by low penetration depth of electromagnetic waves. Therefore, there is a need to develop sensors able to measure bigger volumes and at the same time sufficiently durable for multiple insertions in soil.     

The objective of this work was to test the performance of an open-ended dielectric probe with an antenna (OE-A) in the frequency range 1 MHz – 6 GHz for two mineral soils using vector network analyzer (VNA) one port (reflective) measurements. Firstly, numerical simulations of the probe using Ansys HFSS software were performed. Secondly, the probe calibration was done on the reference materials (air, distilled water and ethanol). Thirdly, the soils measurements were done to check the possibility to determine soil moisture.   

The obtained results show that the tested probe can be applied for fast moisture measurement with minimal soil disturbance. The real part of dielectric permittivity (ε’) obtained for the tested soils was connected with their moisture and the relation between ε’ and volumetric water content was determined. Additionally, the effect of the sample volume was considered and the relation between the high-frequency limit and diameter of the sample was determined.     

Acknowledgement:

This research was supported by the National Centre for Research and Development (BIOSTRATEG/343547/8/NCBR/2017).

How to cite: Woszczyk, A., Szerement, J., Lewandowski, A., Kafarski, M., Szypłowska, A., Wilczek, A., and Skierucha, W.: A modified dielectric probe for increased measurement volume of soil water content, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17909, https://doi.org/10.5194/egusphere-egu2020-17909, 2020.

Pipeline leakage inevitably occurs in the long-distance water transmission process. If a leak cannot be identified and processed promptly, it can cause severe economic losses or environmental pollution. This paper proposes a method to evaluate pipeline leakages in long-distance water transmission. The pipeline located in Liaoning Province was selected; it is 63.97-km long and runs from west Shenyang to Liaoyang city. Flowrate time-series data were obtained from two flowrate stations; the data were measured using ultrasonic flowmeters. The variance and mean values of flowrate time-series data were determined and used to evaluate whether pipeline leakage occurs. A Chi-Square test was used to test if the variance of a flowrate time-series was equal to a specified value. The results indicate the following: (1) the method of variance test can be used to evaluate whether the pipeline operation is abnormal or not; (2) when the variance test on time series data of flowrate is abnormal for more than two days, the pipeline leakage situation can be evaluated; (3) the combination of the variance test and the mean value analysis can help locate the leak position, which provides a reference for site personnel. The method proposed in this paper can detect pipeline leakage in a timely manner, and further ensure normal water transmission operation in many cities downstream.

How to cite: Li, F., Fan, J., and Chen, J.-C.: Detecting Pipeline Leakage in Long-Distance Water Transmission: Case Study in Liaoning Province, China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20889, https://doi.org/10.5194/egusphere-egu2020-20889, 2020.

In recent years, extend periods of drought have been affecting the water quality and availability in  the Flanders region in Belgium. Especially the coastal region experienced an increased salinization of ground and surface water. The Flemish government therefore decided to invest in a dense IoT water quality monitoring network aiming to deploy 2500 water quality sensors  primarily in surface water but also in ground water and sewers. The goal of this "Internet of Water" project is to establish an operational state of the art monitoring and prediction system in support of future water policy in Flanders. 

Since Flanders is a relatively small region (13,522 km²), placing this many sensors will result in one of the most dense surface water quality sensor networks in the world. Each sensor will continuously measure several indicators of water quality and transmit the data wirelessly. This allows us to continuously monitor the water quality and build a big enough data set to be able to use a more data driven approach to predicting changes  in water quality. However, as with any sensor system, the quality of the data can vary in time due to problems with the sensors, incorrect calibration or unforeseen issues. Real-time data quality control is crucial to prevent unsound decisions due to faulty data.

This contribution will give a general overview of the network and it’s specifications, but mainly focus on the implementation of the data stream as well as methods that are implemented to guarantee good data quality. More specifically the architecture and setup of a real-time data quality control system is described. Which will add quality control flags to measurements.  This system is  integrated with the NGSI API introduced by FIWARE, which forces us to make specific design decisions to acommodate to the NGSI API.

How to cite: Maeyens, M., Pagán, B., Seuntjens, P., Maiheu, B., Desmet, N., van Loo, M., and van Hoey, S.: Real time data quality control applied on an IOT sensor water quality network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18903, https://doi.org/10.5194/egusphere-egu2020-18903, 2020.

In the research project Iot.H2O, which is funded under the Water JPI Joint Call 2017 IC4WATER, the potential of the Internet of Things concept is investigated for monitoring and controlling water distribution systems. Smart sensors are used which send data via LoraWAN to gateways which are connected to the Internet. The aim of the project is to use low-cost sensors and open-source software.

In the presentation, a prototype on a laboratory scale will be shown. The design of the monitoring system will be explained in detail and compared to the design of standard SCADA systems. Results on a pump test rig based on a laboratory scale will be shown as well as first results of field tests in a real water distribution system in Germany.

The presentation will also detail how data gathered through the smart sensors will be integrated into software modelling and optimization of water distribution systems. Combined with the new data, such tools offer a range of applications of practical relevance, such as the identification of optimal locations of micro-turbines for energy recovery in water distribution networks and the estimation of water demand throughout the network.

How to cite: Roclawski, H., Krätzig, T., Dewals, B., Vercouter, L., Saliba, A., Theis, A., Pirard, T., Donancio, H., Archambeau, P., and Erpicum, S.: Low-cost sensor system based on LoraWAN for monitoring water distribution systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18824, https://doi.org/10.5194/egusphere-egu2020-18824, 2020.

Monitoring critical drinking water points in the water distribution system of Barcelona (Catalonia, Spain) is an increasing concern. The control of several quality parameters as free chlorine, total organic carbon (TOC), conductivity, turbidity, temperature, colour, pressure and flow are necessary to ensure a supply of safe and clean drinking water to consumers.

The aim of this project is to investigate the consequences of alterations detected in the water distribution system, to find the focus of occurrences and controlling them to provide a better drinking water quality to Barcelona citizens.

Barcelona procures drinking water to its citizens via two main water sources: Ter and Llobregat Rivers. They have intrinsic quality differences and they must be treated in different ways. With the purpose of controlling and investigating how these differences impact the water quality supplies, two s::can sensor systems were installed in the Poblenou District (Barcelona). The first one (nano::station) was installed in a drinking water distribution pipe, and the second one (pipe::scan) was installed in a domestic water supply network. Both systems were situated in the same drinking water confluence sector in order to compare the data recorded and to visualise water quality changes. More than 20 events were recorded, analysed and classified according to whether the alteration was due to an occasional event in the domestic water supply or to an external incident from the water distribution system. Some detected events were related to an increase of temperature, a rise of water demand, the water origins or changes in pressure.

One important event recorded by the installed probes was an increase of temperature, directly associated with an augment of total organic matter (TOC) at the beginning of summer (June 2018). A great rise of TOC would be the causer of high consumption of free chlorine that it could be hazardous for human health if there is not enough chlorine dissolved in water. Due to this temperature increment (from 15°C to 23°C in a few days), the minimum level of chlorine (less than 0.2 mg/L) was registered in the Poblenou Sector.

Nano::station and pipe::scan sensor systems are excellent tools as on-line water quality controllers. These kinds of sensors can record variations occurring every two minutes, giving a great perception of the events that are happening at different points of the drinking water city-wide network.

How to cite: Plà-Castellana, M., Roselló-Cano, J., Maestro, A., Raich-Montiu, J., and Paraira, M.: Detection and understanding of water quality deviation events in the drinking water supply network of the Poblenou Sector (Barcelona), Spain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20102, https://doi.org/10.5194/egusphere-egu2020-20102, 2020.

An instantaneous assessment of the chemical status of surface water bodies provides the ability to better predict the water quality, react in time, and be able to backtrack sources. Also, it is widely accepted that knowledge of the natural chemistry of surface waters is fundamental for identifying anthropogenic pollution (Menzie et al., 2009). The chemical composition of water bodies is controlled by various factors (i.e. atmospheric, geological, biological, etc.). However, the main impact beside anthropogenic pollution is the geological background (e.g. Filella et al., 2014).

To monitor and understand the chemical status it is necessary to measure, with the best possible reliability, a wide spectrum of inorganic analytes. Inductively coupled plasma mass spectrometry (ICP-MS) is widely-accepted as versatile instrument in trace element determination due to its low detection limits, fast multi-element ability and wide dynamic range. The appearance of various polyatomic interferences, low analyte abundance and low sensitivity due to high ionization energy are major challenges in accomplishing precise, routine suitable, multi-element analysis to quantify all target elements which often requires complex pre-measurement treatments. The triple quadrupole ICP-MS (ICP-QQQ-MS; resp. ICP-MS/MS) is a promising tool to overcome some of these limitations. Therefore, our aim was to create a multi-element method with about 65 major and trace elements for surface water. In contrast to existing ICP-MS methods, a single-run-measurement of all analytes is envisaged, including also challenging elements like B, C, P, S, Hg, and REE without a pre-concentration or matrix removal step. The development exhibits very low Limits of Quantification for Rhine and Moselle river water (e.g. REE < 10 ppt).

Our method is based on certified reference material, single element standards (traceable to NIST) and samples from the Rhine and Moselle rivers (Germany). Single element optimized methods were adjusted to the multi-element monitoring purpose. We optimized different collision/reaction cell modes (O₂, He, H₂) to eliminate isobaric, polyatomatic and/or double charged interferences and the multi-element calibration cross check for memory effects and uncertainties. Hence, we developed a powerful method for surface water quality monitoring and hydro-chemical fingerprinting adaptable to the specific user requirements.

Filella, M., Pomian-Srzednicki, I., Nirel, P.M., 2014. Development of a powerful approach for classification of surface waters by geochemical signature. Water Res 50, 221-228.

Menzie, C.A., Ziccardi, L.M., Lowney, Y.W., Fairbrother, A., Shock, S.S., Tsuji, J.S., Hamai, D., Proctor, D., Henry, E., Su, S.H., 2009. Importance of considering the framework principles in risk assessment for metals. Environ. Sci. Technol. 43, 22, 8478-8482.

How to cite: Schmitt, V., Schroeder, H., Belkouteb, N., Arndt, J., Wiederhold, J., and Duester, L.: Development of a multi-element method using an ICP-QQQ-MS to characterize the chemical status of surface water bodies , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20499, https://doi.org/10.5194/egusphere-egu2020-20499, 2020.

Soil complex dielectric permittivity is frequency dependent. At low frequencies soil dielectric spectrum exhibits relaxation effects mainly due to interfacial phenomena caused by water strongly bounded to solid phase particles surfaces, double-layer effects and Maxwell-Wagner effect. At frequencies of several GHz and above, the influence of dielectric dispersion of free water dipoles can be observed.  Since dielectric soil moisture meters operate at frequencies from kHz up to several GHz, their output can be affected by these phenomena.

Currently, there is a variety of commercial sensors that operate at various frequencies from kHz up to several GHz. Most popular are TDR sensors with frequency band up to 1-2 GHz and capacitance/impedance sensors that operate at a single frequency usually from the range
1-150 MHz. Therefore, the knowledge of the broadband complex dielectric permittivity spectrum can help to improve the existing and develop new methods and devices for soil moisture and salinity estimation. Also, accurate characterization of complex dielectric permittivity spectrum of porous materials in the broadband frequency range is required for modeling of dielectric properties of materials in terms of moisture, salinity, density, mineralogy etc.

The aim of the study was to measure the complex dielectric permittivity of glass beads with 5% talc moistened with distilled water and saline water (electrical conductivity of 500, 1000, 1500 mS/m). The experiment was carried out using a seven-rod probe connected to an impedance analyzer (IA) and a vector network analyzer (VNA) using a multiplexer in the frequency range from 40Hz to 110MHz (IA) and 10MHz to 500MHz (VNA). The glass beads (90-106 µm, Fuji Manufacturing Industries, Japan) with 5% talc (Sigma Aldrich) in 4 different moisture and 4 different salinity values were examined. The results obtained from the IA and the VNA were combined and modeled with complex conductivity and dielectric permittivity model. The influence of water content and electrical conductivity on broadband complex dielectric spectra and the fitted model parameters was examined.

The work has been supported by the National Centre for Research and Development, Poland, BIOSTRATEG3/343547/8/NCBR/2017.

How to cite: Szerement, J., Saito, H., Furuhata, K., Yagihara, S., Szypłowska, A., Kafarski, M., Lewandowski, A., Wilczek, A., Woszczyk, A., and Skierucha, W.: Combined vector network analyzer and impedance analyzer for broadband determination of complex permittivity spectrum of glass beads with talc, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21613, https://doi.org/10.5194/egusphere-egu2020-21613, 2020.

Software has been elaborated enabling to numerically simulate both the irradiance of the reservoir surface from total (direct and diffused) solar radiation with λ = 280 - 800 nm under various conditions (season, zenith angle, cloud cover, aerosol parameters, etc.) and the radiation propagation processes in the aquatic environment including the irradiance of water layers at various depths.
The numerical model employs the discrete ordinate method, implemented in a series of software packages that are in the public domain (DISORT, libRadtran, etc.), as well as the corresponding databases of atmospheric and underlying surface parameters.
To simulate the propagation processes of the solar radiation in aquatic environment, a special database has been developed, containing reference data, orbital observations, and data obtained from instrumental monitoring of surface reservoirs in Belarus maintained by the National Ozone Monitoring Research and Education Center of the Belarusian State University (NOMREC BSU) over many years as part of national environmental studies.
The program combines atmospheric and water modules being able to function both jointly and separately thus allowing one to use spectral irradiance or integrated signals experimentally measured by ground-based devices and immersion photometric systems to validate the results of numerical calculations and model calibration.
Special attention was paid to the propagation of biologically active solar radiation (that is UV-B, UV-A and PAR) in the aquatic environment.
Irradiance of water layers by UV radiation and estimation of the corresponding doses of the main biological effects, in particular DNA, are of special interest due to poor knowledge in this field.
Moreover, in the UV range (if compared with the visible range), under significant radiation scattering and absorption by the turbid aquatic environment of surface water bodies, the interpretation and numerical simulation of the transmission function appear to be not quite a trivial task.
A theoretical research on this problem was added with special laboratory and field experiments.
An experimental study of the irradiation levels of various deep-water layers was conducted in the Naroch group lakes (Naroch, Myastro, Malye Shvakshty, Bolshye Shvakshty, Beloye, and Batorino) using a PionDeep immersion photometer designed at NOMREC BSU.
The results showed the presence of well detected UV-B radiation intensities in the lake of Naroch at sufficiently large depths of ~ 15 m.
 “Immersion” measurements were also carried out at various points in the waters of the Myastro, Malye Shvakshty, Bolshye Shvakshty, Beloye, and Batorino lakes.
The measurements were made under various cloud cover and water surface conditions. Distances from the coast varied within 200−2200 m.
To refine the model parameters a series of laboratory measurements of the transmission of natural and model water  samples in a spectral range of λ = 200–700 nm was conducted. At that the absorption spectra of natural and model water bodies, both full-scale and at various stages of filtration, were analyzed.
The numerical simulation exploiting the refined model of UV transparency and irradiances of water layers at various depths was in a good agreement with experimental data.

How to cite: Darozhka, N., Dziomin, V., Bruchkouski, I., Svetashev, A., Turishev, L., Umreika, S., and Barodka, S.: Simulating irradiance of water layers of natural reservoirs by solar radiation in various spectral ranges, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21899, https://doi.org/10.5194/egusphere-egu2020-21899, 2020.

Increased concerns about regional and global climate change in recent decades has led to a significant expansion of monitoring, observational, and experimental sites in remote areas of the world. During this same time, advances in technology and availability of low-power equipment, have allowed increasingly sophisticated measurements with an increasingly wide variety of instruments, sensors, and sensor networks. However, the deployment and use of these technologies in remote locations is restricted not only by harsh environmental conditions, but by the availability of electrical power and communication options. With this presentation we would like to share our experience of designing and building hybrid energy (solar and wind) module that can be used to provide power and communication capabilities for remote installations.

How to cite: Krassovski, M., Riggs, J., Tavino, C., Wullschleger, S., and Heinz, S.: Hybrid energy module for experiments and studies in remote locations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20453, https://doi.org/10.5194/egusphere-egu2020-20453, 2020.

Environmental field conditions are highly variable in three-dimensions and unsuitable to be probed by a single sensor or weather station. In PLANTENNA, a team of electronics, precision and microsystems engineers and plant and environmental scientists collaborate to develop and implement 3D-sensor networks that measure plant and environmental parameters at high resolution and low cost. A first problem we aim to tackle in the field is 3D-monitoring of fruit farms for detection and mitigation of fruit frost damage. The objectives are two-fold:

- To quantify the time-dependent effects of frost mitigation measures on the 3D temperature profile, and to determine the resulting plant-physiological response to get a better understanding of the underlying mechanisms leading to frost damage.

- To develop low-cost, low power, wireless, distributed sensor networks, with automated mathematical data handling to give real-time visualization of subzero temperature regions as decision support system for the farmer.

Field implementation: A fruit farm will be equipped with optical fibre cables for Distributed Temperature Sensing, along horizontal and vertical profiles in the field. This will reveal how cooling penetrates the canopy as a function of time, and how this is influenced by changing atmospheric conditions and mitigation efforts. Detailed temperature monitoring is related to spatio-temporal physiological monitoring at the level of individual trees.

In a next step, the cables will be replaced by a 3D-network of  temperature sensors. The aim is to develop an accurate (±0.5°C accuracy with a resolution << 0.1°C), low cost sensor with ultra-low power consumption (~ 100 nW). The sensor is based on a PCB-based node that consists of a PV module to collect solar energy, a power management integrated circuit (PMIC), a supercapacitor to store energy, a temperature sensor, a microcontroller (µC), a timing control unit (TCU) to enable/disable the system, and a radio frequency IC (RFIC) + antenna to transmit data to the network. To reduce energy consumption, it should operate in low-power “sleep mode” as much as possible, while still being able to capture sudden temperature changes as by ventilator activation: the sensor must decide when to “wake up” and how frequently to measure. The often “power-hungry” MCU and RF radio should operate in an event-driven mode and only “awakened” when the sensor detects a temperature change above a certain threshold.
We chose LoRa for its low power consumption and long-distance capability, which is a perfect match with our application.

How to cite: Ten Veldhuis, M.-C., Van de Wiel, B., Fan, Q., and Steeneken, P.: PLANTENNA: 3D-sensor networks monitoring plant environment. An application for fruit frost protection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3639, https://doi.org/10.5194/egusphere-egu2020-3639, 2020.