Validation and Projections of Climate Characteristics in the Saginaw Bay Watershed, MI, for Hydrologic Modeling Applications

Fundamental differences in the nature of climate and hydrologic models make coupling of future climate projections to models of watershed hydrology challenging. This study uses the NCAR Weather Research and Forecast model (WRF) to dynamically downscale climate simulations over the Saginaw Bay Watershed, MI and prepare the results for input into semi-distributed hydrologic models. One realization of the bias-corrected NCAR CESM1 model's RCP 8.5 climate scenario is dynamically downscaled at a spatial resolution of 3 km by 3 km for the end of the twenty-first century and validated based on a downscaled run for the end of the twentieth century in comparison to ASOS and NWS COOP stations. Bias-correction is conducted using Quantile Mapping to correct daily maximum and minimum temperature, precipitation, and relative humidity for use in future hydrologic model experiments. In the Saginaw Bay Watershed the end of the twenty-first century is projected to see maximum and minimum average daily temperatures warming by 5.7 and 6.3°C respectively. Precipitation characteristics over the watershed show an increase in mean annual precipitation (average of +14.3 mm over the watershed), mainly due to increases in precipitation intensity (average of +0.3 mm per precipitation day) despite a decrease in frequency of −10.7 days per year. The projected changes have substantial implications for watershed processes including flood prediction, erosion, mobilization of non-point source and legacy contaminants, and evapotranspirative demand, among others. We present these results in the context of usefulness of the downscaled and bias corrected data for semi-distributed hydrologic modeling.

How Many Ciscoes are Needed for Stocking in the Laurentian Great Lakes?

Historically, Cisco Coregonus artedi and deepwater ciscoes Coregonus spp. were the most abundant and ecologically important fish species in the Laurentian Great Lakes, but anthropogenic influences caused nearly all populations to collapse by the 1970s. Fishery managers have begun exploring the feasibility of restoring populations throughout the basin, but questions regarding hatchery propagation and stocking remain. We used historical and contemporary stock-recruit parameters previously estimated for Ciscoes in Wisconsin waters of Lake Superior, with estimates of age-1 Cisco rearing habitat (broadly defined as total ha ≤ 80 m depth) and natural mortality, to estimate how many fry (5.5 months post-hatch), fall fingerling (7.5 months post-hatch), and age-1 (at least 12 months post-hatch) hatchery-reared Ciscoes are needed for stocking in the Great Lakes to mimic recruitment rates in Lake Superior, a lake that has undergone some recovery. Estimated stocking densities suggested that basin-wide stocking would require at least 0.641-billion fry, 0.469-billion fall fingerlings, or 0.343-billion age-1 fish for a simultaneous restoration effort targeting historically important Cisco spawning and rearing areas in Lakes Huron, Michigan, Erie, Ontario, and Saint Clair. Numbers required for basin-wide stocking were considerably greater than current or planned coregonine production capacity, thus simultaneous stocking in the Great Lakes is likely not feasible. Provided current habitat conditions do not preclude Cisco restoration, managers could maximize the effectiveness of available production capacity by concentrating stocking efforts in historically important spawning and rearing areas, similar to the current stocking effort in Saginaw Bay, Lake Huron. Other historically important Cisco spawning and rearing areas within each lake (listed in no particular order) include: (1) Thunder Bay in Lake Huron, (2) Green Bay in Lake Michigan, (3) the islands near Sandusky, Ohio, in western Lake Erie, and (4) the area near Hamilton, Ontario, and Bay of Quinte in Lake Ontario. Our study focused entirely on Ciscoes but may provide a framework for describing future stocking needs for deepwater ciscoes.

Mapping Invasive Phragmites australis Using Unoccupied Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar

Invasive plant species are an increasing worldwide threat both ecologically and financially. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for invasive Phragmites australis is particularly challenging due to limited accessibility in wetland environments. Unoccupied aircraft systems (UAS) are a popular choice for invasive species management due to their ability to survey challenging environments and their high spatial and temporal resolution. This study tested the utility of three-band (i.e., red, green, and blue; RGB) UAS imagery for mapping Phragmites in the St. Louis River Estuary in Minnesota, U.S.A. and Saginaw Bay in Michigan, U.S.A. Iterative object-based image analysis techniques were used to identify two classes, Phragmites and Not Phragmites. Additionally, the effectiveness of canopy height models (CHMs) created from two data types, UAS imagery and commercial satellite stereo retrievals, and the RADARSAT-2 horizontal-horizontal (HH) polarization were tested for Phragmites identification. The highest overall classification accuracy of 90% was achieved when pairing the UAS imagery with a UAS-derived CHM. Producer’s accuracy for the Phragmites class ranged from 3 to 76%, and the user’s accuracies were above 90%. The Not Phragmites class had user’s and producer’s accuracies above 88%. Inclusion of the RADARSAT-2 HH polarization caused a slight reduction in classification accuracy. Commercial satellite stereo retrievals increased commission errors due to decreased spatial resolution and vertical accuracy. The lowest classification accuracy was seen when using only the RGB UAS imagery. UAS are promising for Phragmites identification, but the imagery should be used in conjunction with a CHM.