ALGAL BLOOMS IN THE GREAT LAKES OF NORTH AMERICA

DATA PRODUCTION

Climate impact indicators
Global essential climate variables/indicators used

Daily precipitation, maximum and minimum temperature from 19 GCMs from CMIP5 (historical period , early, mid and late century periods, RCPs 4.5 and 8.5), downloadable from the CDS catalogue.

Regional/local indicators used and produced

Precipitation and temperature
Flow and water quality (sediment and nutrient export)
Algual bloom severity index

Global data to regional/local scale

Step 1: Daily precipitation, maximum and minimum temperature from 19 GCMs from CMIP5, downloadable from the CDS catalogue, were downscaled using a spatial interpolation method. Then data were bias-corrected.

Step 2: The two hydrological models used were calibrated and verified to historical data. Their performances were compared and evaluated  in simulating flow, sediments, and nutrients (nitrogen and phosphorus) in Lake Erie watersheds. Different land/agricultural management scenarios were created.

Step 3: Local primary CIIs, which constitute the main forcing input data for the models were derived directly from the downscaled, bias-corrected and analysed GCMs data available from step1.

Step 4: Local secondary CIIs (stream discharge, nutrient and sediment exports) were produced using the hydrological models.

Step 5: Flow, sediment, nutrient, and climate data were linked to algal bloom models. The extent of harmful algal bloom in the Lake Erie western basin at the climate and landscape management scenarios used were predicted.

Step 6: The impact of nutrient and sediment load reduction efficiencies of the landscape management scenarios used at difference climate scenarios on the local secondary CIIs were assessed.

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