Jim McKean

Remote Sensing of Channels and Riparian Zones with a Narrow-Beam Aquatic-Terrestrial LIDAR

The high-resolution Experimental Advanced Airborne Research LIDAR (EAARL) is a new technology for cross-environment surveys of channels and floodplains. EAARL measurements of basic channel geometry, such as wetted cross-sectional area, are within a few percent of those from control field surveys. The largest channel mapping errors are along stream banks. The LIDAR data adequately support 1D and 2D computational fluid dynamics models and frequency domain analyses by wavelet transforms. Further work is needed to establish the stream monitoring capability of the EAARL and the range of water quality conditions in which this sensor will accurately map river bathymetry.

Geomorphic controls on salmon nesting patterns described by a new, narrow‐beam terrestrial–aquatic lidar

Riverine aquatic biodiversity is rapidly being lost worldwide, but preservation efforts are hampered, in part because studies of these dynamic environments are limited by cost and logistics to small local surveys. Full understanding of stream ecosystems requires precise, high-resolution mapping of entire stream networks and adjacent landforms. We use a narrow-beam, water-penetrating, green lidar system to continuously map 10 km of a mountain stream channel, including its floodplain topography, and wavelet analyses to investigate spatial patterns of channel morphology and salmon spawning. Results suggest the broadest fluvial domains are a legacy of approximately 15 000 years of post-glacial valley evolution and that local pool–riffle channel topography is controlled by contemporary hydraulics operating on this broad template. Salmon spawning patterns closely reflect these hierarchical physical domains, demonstrating how geomorphic history can influence modern distributions of aquatic habitat and organisms. The new terrestrial–aquatic lidar could catalyze rapid advances in understanding, managing, and monitoring of valuable aquatic ecosystems through unprecedented mapping and attendant analyses.

Improving Stream Studies With a Small‐Footprint Green Lidar

Technology is changing how scientists and natural resource managers describe and study streams and rivers. A new generation of airborne aquatic-terrestrial lidars is being developed that can penetrate water and map the submerged topography inside a stream as well as the adjacent subaerial terrain and vegetation in one integrated mission. A leading example of these new cross-environment instruments is the Experimental Advanced Airborne Research Lidar (EAARL), a NASA-built sensor now operated by the U.S. Geological Survey (USGS) [Wright and Brock, 2002]. n nStandard airborne terrestrial lidars, which currently produce the highest-resolution maps of extensive land areas, use reflected near-infrared laser pulses to make millions of point measurements of ground and vegetation elevations. However, near-infrared energy is absorbed by water, which limits the use of these systems to mapping features outside of water bodies. EAARL uses a narrow-beam green, rather than near-infrared, laser with a footprint of only 15 centimeters from the nominal flying height (for system technical specifications, see Table S1 in the electronic supplement to this Eos issue (http://www.agu.org/eos_elec/).

Effects of bathymetric lidar errors on flow properties predicted with a multi‐dimensional hydraulic model

New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi-dimensional fluid dynamics model of a small mountain stream. Random point elevation errors were introduced into the lidar point cloud, and predictions of water surface elevation, velocity, bed shear stress, and bed mobility were compared to those made without the point errors. We also compared flow model predictions using the lidar bathymetry with those made using a total station channel field survey. Lidar errors caused <u20091u2009cm changes in the modeled water surface elevations. Effects of the point errors on other flow characteristics varied with both the magnitude of error and the local spatial density of lidar data. Shear stress errors were greatest where flow was naturally shallow and fast, and lidar errors caused the greatest changes in flow cross-sectional area. The majority of the stress errors were less than ±u20095u2009Pa. At near bankfull flow, the predicted mobility state of the median grain size changed over ≤u20091.3% of the model domain as a result of lidar elevation errors and ≤u20093% changed mobility in the comparison of lidar and ground-surveyed topography. In this riverscape, results suggest that an airborne bathymetric lidar can map channel topography with sufficient accuracy to support a numerical flow model.

Evaluation of natural color and color infrared digital cameras as a remote sensing tool for natural resource management

Digital cameras are a recent development in electronic imaging that provide a unique capability to acquire high resolution digital imagery in near real-time. The USDA Forest Service Nationwide Forestry Applications Program has recently evaluated natural color and color infrared digital camera systems as a remote sensing tool to collect resource information. Digital cameras are well suited for small projects and complement the use of other remote sensing systems to perform environmental monitoring, sample surveys and accuracy assessments, and update geographic information systems (GIS) data bases.

Effects of habitat quality and ambient hyporheic flows on salmon spawning site selection

Understanding the role of stream hydrologic and morphologic variables on the selection of spawning sites by salmonid fishes at high resolution across broad scales is needed for effective habitat restoration and protection. Here we used remotely sensed meter-scale channel bathymetry for a 13.5 km reach of Chinook salmon spawning stream in central Idaho to describe habitat quality and set boundary conditions for a two-dimensional surface water model coupled with a three-dimensional hyporheic flux model. Metrics describing ambient hyporheic flow intensity and habitat quality, which is quantified as a function of stream hydraulics and morphology, were compared to the locations of nests built by female salmon. Nest locations were predicted most accurately by habitat quality followed by channel morphology (i.e., riffles location). As a lesser degree than habitat quality, water surface curvature was also a good indicator of spawning location because its intensity can identify riffle morphology. The ambient hyporheic flow predicted at meter-scale resolution was not a strong predictor of redd site selection. Furthermore, the study suggests direct morphological measurements obtained from easily measured channel bathymetry data could enable effective and rapid assessments of salmon spawning channels across broad areas.