Authors: Meghan Halabisky*, University of Washington, Se-Yeun Lee, University of Washington, Monika Moskal, University of Washington
Topics: Remote Sensing, Temporal GIS, Water Resources and Hydrology
Keywords: wetlands, conservation, remote sensing
Session Type: Paper
Start / End Time: 3:20 PM / 5:00 PM
Room: Bonaparte, Marriott, River Tower Elevators, 4th Floor
Presentation File: No File Uploaded
Wetland ecosystems are widely considered to be highly sensitive to climate change. However, scientific capacity to model climate impacts to wetlands has been hampered by the lack of accurate maps showing the spatial distribution of wetlands and data on their historical hydrological dynamics. For this project we used object based image analysis and a time series of Landsat satellite imagery to reconstruct hydrographs for thousands of individual wetlands. This remote sensing dataset detected fine scale changes (<30 m) in surface water using a sub-pixel technique called spectral mixture analysis. We then developed wetland specific regression models to understand the relationship between climate and wetland hydrological dynamics by comparing our remotely sensed dataset to soil moisture and groundwater variables simulated by the VIC hydrologic model. We used these regression models to project the impacts of climate change using global climate model scenarios for the 2080s. We found that wetlands within a similar geographic location may have drastically different hydrologic responses under climate change, not only in magnitude, but also in directionality, with some wetlands getting wetter and others getting drier.