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H2020Staff exchange2016–2022

HiFreq · Smart high-frequency environmental sensor networks for quantifying nonlinear hydrological process dynamics across spatial scales

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2016-12-01 → 2022-02-28
EU contribution
€2,115,000
Participants
24
Scheme
MSCA-RISE

Lines connect the coordinator with its partners. CORDIS does not always give exact coordinates for projects before 2014. These points are placed at city or country level.

Results in brief

Smart high-frequency environmental sensor networks for quantifying nonlinear hydrological process dynamics across spatial scales

Regulators and industries are challenged by the difficulty to analyse and predict the impact of nonlinear environmental processes on short-term and long-term responses of ecosystems to environmental change. Until very recently, the development of conventional monitoring, forecasting and prediction tools has been based on the assumption of stationary environmental systems. In the context of global change, these tools are increasingly pushed towards and even beyond their design limits. This project follows the rationale that only novel, high-frequency/high-resolution monitoring and predictive modelling will yield new process understanding of ecosystem functioning. Technological progress offers as many opportunities as it triggers challenges: what are needed now are new strategies to generate, manage and analyse BIG DATA at unprecedented spatial and temporal resolution. Innovation can only stand as a synonym for ‘significant positive changes’ if [a] we manage to clearly state the challenges (global change & non-stationarity) and problems (generating and managing high-frequency information) and [b] transform them into solutions. The timely outcomes of this project will hence be of great relevance for the scientific community, regulators, and the private sector. The key aim of HiFreq project is to drive innovation in high-frequency environmental sensor network technologies and modelling, in particular, to quantify non-linear process dynamics in ecohydrological, biogeochemical and ecosystem monitoring. The wide-ranging activities of the action led not only to innovation in sensor and monitoring technologies but also support conclusions about the applicability of new sensor networks in operational contexts as well as the BIG DATA challenges going along with the development of large data quantities and their analysis. Solutions developed in this action particularly advance our ability to sense water pollution in-situ at higher frequency and accuracy than previously possible. Data science solutions include edge-processing algorithms for data reduction before transmission.

Data: CORDIS, © European Union

Project objective

Regulators and industries are challenged by the difficulty to analyse and predict the impact of nonlinear environmental processes on short-term and long-term responses of ecosystems to environmental change. Until very recently, the development of most conventional monitoring, forecasting and prediction tools has been based on the assumption of stationary environmental systems. In the context of global change these tools are increasingly pushed towards and even beyond their design limits (the latter resulting in the first line from the prevailing limitations in spatial and temporal resolution of environmental observations).For this project, we propose a rationale stating that only novel, high-frequency/high-resolution environmental monitoring and predictive modelling will yield new process understanding of ecosystem functioning. Technological progress offers as many opportunities as it triggers challenges: what is needed now are new strategies to generate, manage and analyse BIG DATA at unprecedented spatial and temporal resolution. Innovation can only stand as a synonym for ‘significant positive changes’ if [a] we manage to clearly state the challenges (global change & non-stationarity) and problems (generating and managing high-frequency information) and [b] transform them into solutions, i.e. the quantification and prediction of environmental responses to global change as a prerequisite for designing and implementing adaptation and/or mitigation strategies wherever needed.The timely outcomes of this research project will hence be of great relevance for the scientific community, regulatory agencies, and the private sector.

Original text from CORDIS.

Participants

  • THE UNIVERSITY OF BIRMINGHAM · BirminghamCoordinatorUnited Kingdom
  • AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS · MadridSpain
  • CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisFrance
  • EVVOS SA · HesperangeLuxembourg
  • FORSCHUNGSVERBUND BERLIN EV · BerlinGermany
  • GFZ HELMHOLTZ-ZENTRUM FUR GEOFORSCHUNG · POTSDAMGermany
  • HYDRORESEARCH SAM JOHANSSON AB · TabySweden
  • ISARDSAT SL · BarcelonaSpain
  • LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY · Esch Sur AlzetteLuxembourg
  • NATURALEA CONSERVACIO, SL · Castellar Del VallesSpain
  • NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY · SocorroUnited States
  • NEW ZEALAND INSTITUTE FOR EARTH SCIENCE LIMITED · AUCKLANDNew Zealand
  • NORTHWESTERN UNIVERSITY CORPORATION · EVANSTONUnited States
  • RS HYDRO LTD · BromsgroveUnited Kingdom
  • SETUR - INGENIERIE - AUDIT - CONSEIL · Chartres-De-BretagneFrance
  • SILIXA LTD · Elstree HertfordshireUnited Kingdom
  • SVERIGES LANTBRUKSUNIVERSITET · UppsalaSweden
  • Simon Fraser University · BurnabyCanada
  • THE GOVERNORS OF THE UNIVERSITY OF ALBERTA · EdmontonCanada
  • THE NATIONAL UNIVERSITY CORPORATION SHINSHU UNIVERSITY · MatsumotoJapan
  • THE TRUSTEES OF INDIANA UNIVERSITY · BloomingtonUnited States
  • The Flinders University of South Australia · AdelaideAustralia
  • UNITED STATES GEOLOGICAL SURVEY · RestonUnited States
  • UVDYNE LIMITED · SalisburyCity levelUnited Kingdom

Links

Data: CORDIS, © European Union