Journal article
Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling
Remote sensing of environment, Vol.156, pp.551-560
01/2015
DOI: 10.1016/j.rse.2014.10.024
Abstract
Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hs are examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless, considering a GDEM2 hs-derived wind sheltering potential improved the modeled lake temperature root mean square error for non-forested lakes by 0.72°C compared to a commonly used wind sheltering model based on lake area alone. While results from this study show promise, the limitations of near-global GDEM2 data in timeliness, temporal and spatial resolution, and vertical accuracy were apparent. As hydrodynamic modeling and high-resolution topographic mapping efforts both expand, future remote sensing-derived vegetation structure data must be improved to meet wind sheltering accuracy requirements to expand our understanding of lake processes.
•Vegetative canopy wind sheltering influences lake-level wind shear and heat fluxes.•We examined the value of ASTER GDEM2 data at improving hydrodynamic lake modeling.•Sheltering height and wind shear were estimated at 76,000 Wisconsin lakes.•GDEM2 tended to underestimate sheltering height, which led to increased wind shear.•Including GDEM2 sheltering height significantly improved modeled lake temperature.
Details
- Title: Subtitle
- Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling
- Creators
- Jamon Van Den Hoek - Biospheric Sciences Laboratory, Code 618.0, NASA Goddard Space Flight Center, 8800 Greenbelt Rd., Greenbelt, MD 20711 USAJordan S Read - Center for Integrated Data Analytics, U.S. Geological Survey, 8505 Research Way, Middleton, WI 53562 USALuke A Winslow - Center for Integrated Data Analytics, U.S. Geological Survey, 8505 Research Way, Middleton, WI 53562 USAPaul Montesano - Sigma Space Corp., Lanham, MD 20706, USACorey D Markfort - IIHR-Hydroscience and Engineering, Department of Civil and Environmental Engineering, The University of Iowa, C. Maxwell Stanley Hydraulics Laboratory, 300 S. Riverside Dr., Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Remote sensing of environment, Vol.156, pp.551-560
- Publisher
- Elsevier Inc
- DOI
- 10.1016/j.rse.2014.10.024
- ISSN
- 0034-4257
- eISSN
- 1879-0704
- Grant note
- DOI: 10.13039/100006225, name: Oak Ridge Associated Universities; name: U.S. Geological Survey Center for Integrated Data Analytics; DOI: 10.13039/100009823, name: Wisconsin Department of Natural Resources; name: Federal Aid in Sport Fish Restoration, award: F-95-P; name: National Science Foundation, award: DEB-0941510
- Language
- English
- Date published
- 01/2015
- Academic Unit
- Civil and Environmental Engineering; Mechanical Engineering
- Record Identifier
- 9983991972802771
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