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Uncertainty in elevation data and sensitivity to a sea-level rise estuary habitat model: Costs and benefits of high precision
Citation:
Saarinen, J. A., D. REUSSER, H. LEE, II, AND C. Janousek. Uncertainty in elevation data and sensitivity to a sea-level rise estuary habitat model: Costs and benefits of high precision. Presented at 2011 Coastal GeoTools Meeting, Myrtle Beach, SC, March 21 - 24, 2011.
Impact/Purpose:
Understanding the threats of sea-level rise (SLR) to ecosystem services in key estuarine habitats is a high priority for Pacific Northwest coastal biologists, fish and wildlife managers, and shellfish growers.
Description:
Understanding the threats of sea-level rise (SLR) to ecosystem services in key estuarine habitats is a high priority for Pacific Northwest coastal biologists, fish and wildlife managers, and shellfish growers. The utility of decision support systems for understanding potential effects of these changes is dependent on many factors including the quality of inputs. Our objective is to measure uncertainty of modeled input elevation data for the Sea Level Affecting Marsh Model (SLAMM). Many formulations in SLAMM are based on values referenced from a defined digital elevation model (DEM). The accuracy and precision of the source data used to develop the DEM are important factors to consider when evaluating SLAMM outputs for management decisions. Multiple DEMs developed from LIDAR, airborne Interferometric Synthetic Aperture Radar (IFSAR), National Elevation Data (NED), and National Wetlands Inventory (NWI) were developed for a tributary in Yaquina bay along the central Oregon coast. The DEMS were incorporated with current habitat maps and local parameters into SLAMM simulations to project the future distribution of habitat. DEM values were compared with precise GPS measurements to gauge uncertainty. Comparing simulation results with DEM specification and procurement expense shows there is less elevation uncertainty in intertidal areas with more expensive data. Elevation datasets that specified areas within intertidal regions, resulted in more accurate modeled elevations and increased confidence in projected habitat distribution. Accounting for uncertainty in DEMs for estuarine habitat modeling can aid managers and scientists in their decisions about model approaches, limitations and the resources required for desired results.