Tuesday, May 12
10:30 am
Location:
GLERL,
Lake Superior Lecture Hall
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Title: "Estimation
of overlake precipitation and basin runoff uncertainty in the Great
Lakes"
Speakers:
Qiang Dai
Department of Civil and Environmental Engineering, University of
Michigan, Ann Arbor, Michigan
Mary E. Mello
Cooperative Institute for Limnology and Ecosystem Research, University
of Michigan, Ann Arbor, Michigan
Dr. Carlo DeMarchi
Department of Geological Sciences, Case Western Reserve University,
Cleveland, Ohio
Abstract:
The Net Basin Supply (NBS) for one of the Great Lakes represents
the net amount of water entering the lake, not counting the supply
of water from upstream lakes and can be computed as the sum of the
actual inputs (over-lake precipitation, runoff from the drainage
basin, and net groundwater flux) and outputs (evaporation) to/from
each lake, but not the connecting-channel flows or change in storage.
The reliability of NBS is a key parameter for managing Great Lakes
water balance and for understanding long-term trends in the hydrological
conditions of the Lakes. As part of the International Upper Great
Lakes Study, we analyzed the algorithm used by NOAA (GLERL) to estimate
tributary flow to the Great Lakes and evaluated its uncertainty
using a Monte Carlo technique. We also computed over-lake precipitation
by merging an operational multisensor product combining radar-based
precipitation estimates and rain gage data, the National Centers
for Environmental Prediction Multisensor Precipitation Estimates
(MPE) with data from a larger network of rain gages for 2002-2007
and we analyzed the differences with the GLERL estimates for over-lake
precipitation.
Results indicate that runoff uncertainty is relatively small for
Lake Erie and Lake Michigan, but quite larger for lakes Superior,
Huron, Saint Clair, and Georgian Bay. Further, GLERL estimates seem
affected by a small bias (2 to 7%). Due to limitations of MPE, the
comparison of overlake precipitation is limited to lakes Ontario,
Erie, Michigan, and Huron. For these lakes, the Lake version of
GLERL estimates show a better agreement with our results than the
Land version of GLERL estimates. For the former product, no substantial
bias is detected, while monthly uncertainty is limited for the smaller
lakes, but substantial for the larger lakes.
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