T101 Remote Sensing Applications in Hydrology and Geology

Monday, 26 September 2016
8:00 AM - 12:00 PM
Room 502

APPLICATION OF REMOTELY-SENSED SURFACE-WATER INUNDATION DATA TO CALIBRATE A COUPLED GROUNDWATER SURFACE-WATER MODEL OF THE GREAT DISMAL SWAMP IN VIRGINIA AND NORTH CAROLINA, USA

Paper number: T101-3
Program: Technical Sessions
Time: 8:30 AM – 8:45 AM

Authors

Abstract

Remote-sensing data products describing surface-water inundation were used to calibrate a hydrologic model of the Great Dismal Swamp, a forested wetland in southeastern Virginia and northeastern North Carolina. The MODFLOW-based hydrologic model simulated groundwater levels that were then used to calculate surface inundation, important information for refuge managers managing water resources and restoring historic wetland ecosystems in the swamp. The two remote-sensing data products were the Dynamic Surface Water Extent (DWSE) (Jones, 2015) and output from SAR/InSAR backscattering analysis (Kim and others, 2016). The DWSE product, derived from Landsat satellite imagery, provides estimates of open water area as well as standing water under vegetation where allowed by vegetation canopy characteristics. Intervals between Landsat image collections vary between 8 and 16 days, provided sufficiently clear skies at the time of satellite overpass. Although available for years 1985 to present, DSWE data from 2005 to 2015 were used in this analysis. The SAR/InSAR data product was developed from 1998-2008 Radarsat-1 C-band data and 2006-2011 ALOS PALSAR L-band data and uses InSAR coherence (double-bounce backscattering) to determine inundated areas at intervals of about two weeks, corresponding to SAR flyover. Differences between remotely-sensed and modeled areas of inundation were incorporated into automated calibration of the hydrologic model, using PEST parameter estimation software. Hydrologic model cell resolution, 152 m, was coarser than that of either remote sensing dataset, (e.g., 30 m for DSWE), necessitating a five-fold upscaling of the remotely-sensed data. The remotely-sensed inundation data improved accuracy of simulated water levels in the hydrologic model and provided additional confidence in model results, particularly for the many inaccessible areas of the Great Dismal Swamp. The inundation data provide a new type of calibration data for coupled groundwater surface-water hydrologic models of wetlands and periodically flooded areas. Depending on systematic coverage and archive availability, they may be applicable over wide areas that can be inaccessible for traditional observations of groundwater levels in wells.

Geological Society of America Abstracts with Programs. Vol. 48, No. 7

doi: 10.1130/abs/2016AM-286194

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