HIFREQ - Smart High-Frequency environmental sensor networks for quantifying nonlinear hydrological process dynamics across spatial scales

Regulators and industries are challenged by the difficulty to analyze 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. In this context we need to [a] 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.

We therefore propose an ambitious methodological approach within HiFreq that pioneers new sensor technologies and distributed sensor networks and adaptive modeling approaches that provide the unique opportunity to: (1) Analyse which environmental conditions, and combinations thereof, trigger nonlinear process behaviour of complex environments; (2) Investigate how and when hydrological, biogeochemical or ecological hot spots and hot moments impact large-scale and long-term environmental process dynamics; (3) Explore the effects of high-variability in water, energy, solute and sediment fluxes and ecosystem structure on environmental hot spots and hot moments; (4) Identify how innovative high-frequency/resolution monitoring technology can help the public and private sector to quantify non-linear environmental processes (5) Develop predictive tools that allow regulators and decision makers to establish large-scale/long-term impacts of short-term, small-scale environmental processes (6) Develop strategies for an alarm index that directly translates highfrequency/ resolution BIG DATA into environmental management practice. Our research methodology is designed to [a] support innovation, [b] share knowledge, [c] bring ideas from research to the market (and vice-versa) and [d] generate scientific and technological progress through innovation in highfrequency/ resolution environmental monitoring and modeling.


Theresa Blume
Dr. Theresa Blume
Gebäude C 4, Raum 2.25
14473 Potsdam
+49 331 288-1512
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