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U-M Water Research Round-Up: November 2017

U-M Water Research Round-Up: November 2017

Burton Memorial TowerFrom the November 2017 Water Center Newsletter

U-M Water Research Round-Up

Project: Overcoming Social and Technical Barriers for the Broad Adoption of Smart Stormwater Systems

U-M Research Team: Branko Kerkez, College of Engineering, (Principal Investigator), Joan Nassauer, School for Environment and Sustainability, and Noah Webster, Institute for Social Research.
External Team Members: University of Virginia, University of Tennessee, and EmNet, LLC

Description: The team is investigating how smartwater technologies will be perceived by residents and decision makers, and how these technologies may help improve the safety and efficiency of our water infrastructure by offering new solutions to combat flooding and water quality problems.


Project: Human and Environmental Effects on Great Lakes Coastal Ecosystems

Research Team: Laura L. Bourgeau-Chavez (lead PI) David Hyndman, William Currie (lead U-M co-PI), Deborah Goldberg (U-M co-PI), Kenneth Elgersma, Anthony Kendall, Jason Martina, Sherry Martin, Nancy H.F. French, and Bruno Basso. Michigan Technological University, Michigan State University, University of Michigan, University of Northern Iowa, and Texas A&M University.

Description:The goal of this project is to quantify the historical and likely future impacts of changes in land use, management practices, and climate on ecosystem structure and function at land/water interfaces within the Great Lakes drainage basin mediated through altered deliveries of water and nutrients from the landscape and resulting plant invasions. To meet this goal, we use a mechanistic approach that models the underlying ecological and hydrological processes and explicitly couples models across these traditionally distinct disciplines.

See: Abstract

Project:RAISE: Water Quality, Public Trust, and Health in Mexico City

Research Team:Elizabeth FS Roberts (PI), Richard D. Gonzalez, Belinda L. Needham, Deborah J. Watkins, Jaclyn Michelle Goodrich, Brisa N. Sanchez, Branko Kerkez, Krista Wigginton
Description:The goal of this project is to develop tools to understand neighborhoods as social-technical-biological systems. Our team will build on and expand selected information about social-scientific, environmental engineering, and epidemiology to improve understanding of dynamic and interlinked water, public trust, and human health systems.

Project:Water level forecasts: Improving water level models for shipping and commerce

Research Team: Branko Kerkez (UM-CEE), Drew Gronewold (NOAA GLERL)

Description:In support of the International Joint Commission’s (IJC) need for understanding water levels and future water supplies in the Great Lakes, we will create a robust historical dataset for each Great Lake that explains changes in observed water levels based on the relative importance of each component of the water balance (runoff, over-lake evaporation, over-lake precipitation, and connecting channel flows). We will also develop a new model that efficiently and accurately simulates water levels and connecting channel flows in the Great Lakes system given user-specified net basin supply (NBS) scenarios.


Project:Coordination & leadership of the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS)

Research Team: Hongyan Zhang (UM-SEAS, CIGLR), Felix Martinez (NOAA NOS), Ed Rutherford (NOAA GLERL), Rochelle Sturtevant (Great Lakes Sea Grant)

Description:The goal of this project is to update, improve, and enhance NOAA’s Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS) to better inform managers of current and future threats from nonindigenous species. In the course of providing the most current information on ANS, we will synthesize research data to improve understanding of current and potential impacts of ANS to the Great Lakes ecosystems.


Project:Improving Lake-Effect Snow and Cloud Forecast Capability for the Great Lakes Region

Research Team: Ayumi Fujisaki-Manome (UM-CLaSP, CIGLR), Philip Chu (NOAA GLERL)

Description:This project aims to provide National Weather Service (NWS)/Weather Forecast Office (WFO) forecasters with improved lake effect snow forecasts, ice predictions, and visibility forecasts by reducing uncertainties of numerical forecast models through rigorous validation and improvement of model-simulated turbulent heat fluxes, lake ice conditions, lake surface temperature, and heat flux calculation algorithms. This project will lead to timely and accurate forecasts that improve the preparedness for severe winter weather events.


Project:Great Lakes Long-term Ecological Research Program

Research Team: Tom Johengen (UM-SEAS, CIGLR), Al Steinman (GVSU), Henry Vanderploeg (NOAA GLERL), Ashley Elgin (NOAA GLERL), Ed Rutherford (NOAA GLERL)

Description:CIGLR will collaborate with NOAA GLERL to continue the collection of long-term ecological data and conduct targeted fundamental research on ecosystem processes critical to understanding ecosystem structure and function for managing water quality, fisheries, and other ecosystem services in the Great Lakes. In addition, CIGLR is conducting ecological research within each of the other four Great Lakes on a rotational basis in support of the U.S. EPA led Coordinated Science Monitoring Initiatives (CSMI).


Project:HABs Monitoring, Forecasting and Genomics for the Great Lakes

Research Team: Tom Johengen (UM-SEAS, CIGLR), Eric Anderson (NOAA GLERL), Hank Vanderploeg (NOAA GLERL)

Description:The project is focused on the operational development of the Lake Erie and Saginaw Bay harmful algal bloom (HAB) forecasts and direct monitoring of microcystin concentrations within these ecosystems. Project goals: 1) determine whether significant amounts of the HAB toxin, microcystin (MC), are entering the drinking water supplies, 2) elucidate the main drivers determining the timing and extent of bloom development, and the subsequent bloom movements through the western and central basins of Lake Erie, 3) post field sampling results to a publically-accessible website, and 4) share field sampling results with NOAA NOS to improve the Lake Erie HAB Bulletin.


Project:Advancement of Mobile, In-situ HAB Toxin Warning and Genomic Observation for Great Lakes Decision Support Tools

Research Team: Tom Johengen (UM-SEAS, CIGLR), Steve Ruberg (NOAA GLERL), Chris Scholin (MBARI), James Birch (MBARI)

Description:A project team including the Monterey Bay Aquarium Research Institute (MBARI) will develop new mobile, in-situ harmful algal bloom (HAB) detection technology to facilitate toxin forecasting and genomic observations to support informed decision making. Engineering advances for a third-generation environmental sample processor (3G ESP) underway at MBARI include miniaturizing the in-situ sample processing capabilities. The resulting 3G ESP-LRAUV (“eAUV”) prototype will enable adaptive biological sampling over weeks-long targeted missions.