PROGNOS: PREDICTING IN-LAKE RESPONSES TO CHANGE USING NEAR REAL TIME MODELS

Lakes and reservoirs are under continuous pressure from urbanization and agricultural intensification, and from changes in climate, including an increasing occurrence of extreme climatic events. These pressures can reduce water quality by promoting the occurrence of nuisance algal blooms and higher levels of dissolved organic carbon (DOC), two issues that can substantially increase the costs for water treatment. To monitor such changes in water quality, automated high frequency (HF) monitoring systems are increasingly being adopted for lake and reservoir management across Europe. These HF data are mostly used to provide near real time (NRT) information on the present lake state. An even more valuable tool for water management, however, would be to use HF data to run computer models that forecast the probability of a change in lake state in the coming weeks or months. In PROGNOS, we will develop an integrated approach that couples HF lake monitoring data to dynamic water quality models to forecast short-term changes in lake water quality. More

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Last Updated August 27, 2019, 14:17 (UTC)
Created November 21, 2018, 10:00 (UTC)
acronym PROGNOS
funder
organizations1 dundalk-institute-of-technology
organizations10
organizations2 marine-institute
organizations3 aarhus-university
organizations4 israel-oceanographic-and-limnological-research
organizations5
organizations6
organizations7
organizations8
organizations9
partner pierson-donald
partner1 eleanor-jennings
partner10
partner2 elvira-de-eyto
partner3 erik-jeppesen
partner4 gideon-gal
partner5
partner6
partner7
partner8
partner9
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