Karen Thorne, US Geological Survey, 2015-06-26, Water Monitoring Data, All Study Sites, 2011-2015: U.S. Geological Survey Data Release, 10.5066/F7SJ1HNC
Summary
To determine inundation patterns and calculate site-specific tidal datums, we deployed water level data loggers (Model 3001, Solinst Canada Ltd., Georgetown, Ontario, Canada and Model U-20-001-01-Ti, Onset Computer Corp., Bourne, MA, USA) at all sites over the study period. Each site had one or two loggers (n = 16). We placed loggers at the mouth and upper reaches of second-order tidal channels to capture high tides and determine seasonal inundation patterns. Water loggers collected water level readings every six minutes starting on the date of deployment and continuing to the present. We used data from the lowest elevation logger at each site to develop local hydrographs and inundation rates. We surveyed loggers with RTK GPS at the [...]
Summary
To determine inundation patterns and calculate site-specific tidal datums, we deployed water level data loggers (Model 3001, Solinst Canada Ltd., Georgetown, Ontario, Canada and Model U-20-001-01-Ti, Onset Computer Corp., Bourne, MA, USA) at all sites over the study period. Each site had one or two loggers (n = 16). We placed loggers at the mouth and upper reaches of second-order tidal channels to capture high tides and determine seasonal inundation patterns. Water loggers collected water level readings every six minutes starting on the date of deployment and continuing to the present. We used data from the lowest elevation logger at each site to develop local hydrographs and inundation rates. We surveyed loggers with RTK GPS at the time of deployment and at each data download that occurred quarterly, to correct for any vertical movement. We corrected all raw water level data with local time series of barometric pressure. For Solinst loggers, we deployed independent barometric loggers (Model 3001, Solinst Canada Ltd., Georgetown, Ontario, Canada); for Hobo water level loggers, we used barometric pressure from local airports (distance less than 10 miles). To determine tidal channel salinities, we deployed one conductivity logger at each site next to the lower elevation water level logger (Odyssey conductivity/temperature logger, Dataflow Systems Pty Limited, Christchurch, New Zealand). We converted specific conductance values obtained with the Odyssey loggers to practical salinity units using the equation from UNESCO (1983). We used water level data to estimate local tidal datums for all sites using procedures outlined in the NOAA Tidal Datums Handbook (NOAA, 2003). We only calculated local MHW and MHHW because the loggers were positioned in the intertidal, which is relatively high in the tidal frame, and therefore did not capture MLW or MLLW and could not be used to compute these lower datums. We estimated mean tide level (MTL) for each site by using NOAA’s VDATUM 3.4 software (vdatum.noaa.gov), except at Bandon where we used MTL directly from historic NOAA data. Many results in this report are reported relative to local MHHW calculated from local water data. Water level loggers deployed within marsh channels recorded variation in water levels and salinity throughout the study duration. Loggers often did not capture lower portions of the tidal curve because of their location in tidal marsh channels which frequently drain at lower tides. From peak water levels, we calculated site-specific tidal datums (MHW and MHHW), and information on the highest observed water level (HOWL) during the time series. Our site specific tidal datum calculations generally closely matched tidal datums computed at nearby NOAA stations (tidesandcurrents.noaa.gov). Differences likely reflect site-specific tidal and bathymetric conditions in local estuarine hydrology. We collected salinity data at all sites, however, due to equipment recalls and failure we do not have salinity data for the duration of the study. We report weekly maximum salinities since many of our salinity loggers were not submerged during the entire tidal cycle at all sites, except for Grays Harbor due to recalled loggers and loggers being washed away during storm events. We observed a high level of variation in salinity between and within sites. Siletz experienced the greatest variation in salinity during the study period, ranging from 0.8 to 32 ppt. Willapa was the freshest system, ranging from 12-15 ppt and had very little temporal variation. The largest variation in salinity at most sites occurred from September through December. All sites had salinity below 35 ppt throughout most of the year; however, the highest salinities were measured in August. See appendices for detailed site specific results.
At the state level, Washington and Oregon have highlighted coastal ecosystems as important areas susceptible to climate change and have prioritized research to assist in adaptation planning for resource management and ecosystem services. The information emerging from our CERCC network will provide local managers and decision makers with the information they need to address endangered and threatened species management, wetland conservation, anadromous fish and migratory bird management and habitat conservation and recovery plans while making informed decisions on habitat resiliency and land acquisition planning that effectively considers the effects of climate change. Our CERCC network is a research model that can be potentially transferred to other coastal regions throughout the US. The overarching goal of our research was to use site-specific data to develop local and regionally-applicable climate change models that inform management of tidal wetlands along the Pacific Northwest coast. Our overarching questions were: (1) how do tidal marsh site characteristics vary across estuaries, and (2) does tidal marsh susceptibility to SLR vary along a latitudinal gradient and between estuaries? We addressed these questions with three specific objectives: (1) measure topographical and ecological characteristics (e.g., elevation, tidal range, vegetation composition) for tidal marsh and intertidal mudflats, (2) model SLR vulnerability of these habitats, and (3) examine spatial variability of these projected changes along the latitudinal gradient of the Washington and Oregon coasts. The research was conducted at nine tidal marshes in coastal estuaries spanning the Washington and Oregon coastlines from Padilla Bay in northern Washington to Bandon located at the mouth of the Coquille River in southern Oregon (Figure 3). These sites are managed by local NGOs (non-governmental organization), Native American tribes and federal or state agencies. The sites were located in Padilla National Estuarine Research Reserve (hereafter Padilla), Port Susan Bay Preserve (hereafter Port Susan), Skokomish Estuary within lands of the Skokomish Indian Tribe (hereafter Skokomish), Nisqually National Wildlife Refuge in southern Puget Sound (hereafter Nisqually), Grays Harbor National Wildlife Refuge (hereafter Grays Harbor), Tartlatt Slough within Willapa Bay National Wildlife Refuge (hereafter Willapa), Siletz National Wildlife Refuge (hereafter Siletz), Bull Island within South Slough National Estuarine Research Reserve in Coos Bay (hereafter Bull Island), and Bandon National Wildlife Refuge on the Coquille Estuary (hereafter Bandon). Each study site comprised a portion of the tidal marsh and adjacent nearshore ecosystem. Although the entire Washington and Oregon coasts have a temperate climate, the sites spanned a broad range of hydrologic and oceanographic conditions. Overall tidal range decreased from northern Washington to southern Oregon.
