7/30/2019 Leg Leiter a Gu 12 Poster

1/1

Poster H31E-1158

Mapping gravel bed river bathymetry from spaceCarl J. Legleiter and Brandon T. Overstreet

Department of Geography, University of Wyoming

1. Introduction and research objectives

2. Methods: study areas and field data

3. Methods: remotely sensed data andspectrally-based depth retrieval

5. Results: bathymetric mapping

6. Conclusions and future work

6. Acknowledgements

7. Contact information: Carl J. LegleiterDepartment of GeographyUniversity of Wyoming1000 E. University AvenueLaramie, WY 82071

E-mail: Carl.Legleiter@uwyo.edu Office: 307-766-2706Mobile: 307-760-8369Fax: 307-766-3294

Financial support was provided by the Office of Naval Research (Grant #N000141010873). The National ParkService allowed us to conduct this study in Grand Teton and Yellowstone National Parks, and the UW-NPSResearch Center and Yellowstone Ecologica l Research Center provided logistical support. The NavalResearch Lab and USGS loaned field equipment. Gregory Miecznik of DigitalGlobe coordinated WV2 imageacquisition. C.L. Rawlins and Floyd Legleiter assisted with field work. The editor, associate editor, and threeanonymous reviewers for JGR-Earth Surface provided valuable comments on a paper summarizing this study.

Understanding river form and behavior requires an efficient means of measuringchannel morphology. Similar ly, a synoptic perspective is needed to characterize fluvialsystems across larger watershed extents. Conventional field methods are inadequatefor this task, but remote sensing has emerged as a viable alternative. This study usedfield measurements and satellite images to evaluate the potential for mapping thebathymetry of gravel bed rivers from space. Depth information is valuable for manydifferent purposes, including estimation of discharge, parameterization of hydraulicmodels, assessment of habitat qualit y, and inferenc e of sediment transport rates frommorphologic changes. Previous research has demonstrated the potential utility of remote sensing for depth retrieval in certain types of rivers. Whereas prior work hasfocused on aerial images, this study assessed the feasibility of measuring gravel bedriver depths from a satellite platform. Our research objectives were to: (1) characteri zethe inherent optical properties of the water column; (2) establish relationships betweendepth and reflectance based on field spectra; and (3) evaluate different approaches forcalibrating image-derived quantities to flow depth; and (4) assess the accuracy of depthestimates produced from various types of satellite image data.

We examined two clear-flowing gravel bed streams, the Snake River and Soda ButteCreek (SBC), that feature complex morphology and highly dynamic behavior that allbut necessitate a remote sensing approach for effective mapping and monitoring.

depth measurements obtained via wading on SBC and shallow portions of the Snake,with locations defined via RTK GPS. For deeper areas of the Snake, depths wererecorded by an echo sounder and an acoustic Doppler current profiler deployed from acataraft and kayak, respectively. To estimate pixel-scale mean depths from these pointmeasurements, we used geostatistical techniques including coordinate transformationto a channel-centered frame of reference, variogram modeling, and ordinary blockkriging . To quantify the optical characteristi cs of these streams, we measuredreflectance spectra from above the water surface on transects across Rusty Bend andat discrete points on SBC. Water column attenuation was characterized by measuringthe downwelling spectral irradiance at various depths and using these data to calculatethe diffuse attenuation coefficient K d . In addition, a WET Labs ac-9 was used to directlymeasure two inherent optical properties of the water column: the absorption and

attenuation coefficients a and c. Ancillar y data included turbidity and water samplesanalyzed for suspended sediment concentration (SSC). These optical data allowed usto examine two important constraints on remote sensing of bathymetry: the precisionof depth estimates and the maximum depth detectable by an imaging system.

Understanding of river morphodynamics has been hindered by the difficulty of measuring channel form and behavior via conventional field methods. T his studyexplored the potential to map river bathymetry from passive optical satellite images.Our results indicate that water depths in clear-flowing, mid- to large-sized gravel bedrivers can be estimated reliably from high resolution (2 m pixel) multispectral data.We made direct measurements of water column optical properties to quantifyconstraints on depth retrieval: depending on sensor radiometric resolution,bathymetric precision was on the order of 0.05 m and maximum detectable depthsvaried spectrall y from >5 m in the green to