SAN francisco BAY and estuary (SFB) is highly impacted by human populations through agriculture, urbanization, and climate change. IT holds tremendous economic and commercial value for the millions of…

This is a $427,795 grant awarded by the National Aeronautics and Space Administration (NASA) to the Northwest Indian College Foundation, a nonprofit organization and fundraising arm for Northwest Indian College. The grant supports research to develop enhanced algorithms for remote sensing of harmful algal blooms (HABs) in the San Francisco Bay and Estuary region. The goals are to identify cyanobacterial hotspots, statistically model environmental drivers, build a forecasting model, and apply the approach to Bellingham Bay, Washington. The project includes stakeholder workshops and dissemination of findings through platforms like the San Francisco Estuary Institute website. This aligns with NASA's 2016 Research Opportunities in Space and Earth Sciences (ROSES) call focused on remote sensing for water quality and HAB monitoring. There is no set-aside designation for this contract, which runs from February 2018 through January 2022.

SAN francisco BAY and estuary (SFB) is highly impacted by human populations through agriculture, urbanization, and climate change. IT holds tremendous economic and commercial value for the millions of people who utilize its resources. The SFB region is ideal for evaluating new remote-sensing algorithms to detect cyanohabs. The BAY proper is physically large enough for traditional remote sensing to be used (e.g. the NOAA cyanobacterial index, CI applied to modis and meris), but is surrounded by waterways and lakes that require high spatial resolution (e.g. OLI, MSI). IT has rich historical remote sensing (hyspiri airborne campaign, prism) and in-water (USGS, sfei) observations, and there are management partners ready and willing to support the effort. This effort is well-aligned with the 2016 NASA roses a.30 call for remote sensing of water quality, section 2.4: enhanced algorithms for HAB monitoring. We specifically propose that enhanced algorithms requires integration of HAB detection into a predictive modeling and management framework, thus enhancing the utility of next-generation remote sensing capabilities. The major goals of this proposed work are to: (1) identify cyanobacterial hot spots near SFB using satellite imagery and already developed cyanobacterial algorithm indices; (2) statistically identify environmental drivers for the proliferation of cyanohabs using a previously collected data set; (3) build a predictive forecasting model to disseminate information through the SAN francisco estuary institute (sfei) to state and regional partners, and (4) apply the modeling framework to a similar ecosystem, bellingham BAY WA, to demonstrate applicability beyond SFB, so as to disseminate the information and work collaboratively with populations that are most negatively affected by cyanohabs. The intent of this proposed project is to then be able to disseminate the information to the public, through already available platforms for SFB, such as the cchab network, and SAN francisco estuary institute website, while building a similar platform in bellingham BAY to inform the public. Our proposal also includes two regional workshops in year 2, one to inform stakeholders and managers in SFB, and a smaller workshop to engage local and tribal government and managers in bellingham BAY, WA. While this is perhaps ambitious for a two-year project we believe IT is realistic given that (a) we are testing algorithms already developed for the region (e.g. AMI, SLH) that have not yet been routinely applied to satellite data, and (b) we already have the extensive in-water data necessary to build robust statistical models. This proposal addresses roses a.30 subtask 2.4 the topic of algorithm refinement to assess harmful algal blooms across north america by directly assessing the inclusion of satellite algorithms for cyanobacterial indices into an environmental predictive model to determine if IT increases the quality and predictive capability of the model. The remote sensing data used for this proposal will be directly linked to 5+ years of in-situ data from SFB, and 7+ years of inland data from pinto lake, CA. Our findings from that dataset will be applied to a case study - bellingham BAY, WA which has many of the same warning signs (eutrophication, drought, and warming temperatures) that we see in SFB and is equally at risk for cyanohabs crossing from the freshwater to the marine land/sea boundary, applying a regional model to a similar case study. Furthermore, our proposed products include workshops for stakeholders in managerial practices in both SFB and bellingham BAY including: local, state, and tribal government agencies, researchers, fisheries and water resource managers, k-16 students, graduate students, publically available data-dissemination platforms, and peer-reviewed research articles