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Jeff Conaway

Publications and source records attributed to Jeff Conaway.

6 recordsLinked to original sources

Refinement of a framework for Moving Aircraft River Velocimetry (MARV) and application to particle tracking along Alaskan rivers

Information on river velocities enhances understanding flood hazards, evaluating habitat conditions, and predicting the transport of floating materials. In this follow-up study, we used data from two new sites, one with a more complex morphology and the other with a lower suspended sediment concentration, to provide further evidence that Moving Aircraft River Velocimetry (MARV) can yield accurate velocity estimates ( R 2 up to 0.87 when compared to field measurements) for long segments of large, turbid rivers. The MARV workflow is packaged in freely available software and is robust to implementation details; neither buffering to mitigate edge effects nor a new approach to aggregating velocity vectors improved performance. MARV was not sensitive to parameters used to establish overlapping image sequences, but combining a long window with a short jump between consecutive windows was the optimal configuration. Although accuracy varied from one cross section to the next, agreement between remotely sensed velocities and those measured in the field was independent of position within a frame range. As an initial step toward application of the approach to help address practical problems, we showed how MARV can drive particle tracking models. Our first-order simulations suggest that channel morphology and flow velocity are the primary controls on travel time and particle fate, with diffusive processes playing a lesser role. Although MARV can be used to characterize an instantaneous flow field, a more comprehensive framework that accounts for other physical processes would be required to model specific types of events like oil spills.

Alaska

A comparison of contemporary and historical hydrology and water quality in the foothills and coastal plain of the Arctic National Wildlife Refuge, Arctic Slope, northern Alaska

The Arctic National Wildlife Refuge is a unique landscape in northern Alaska with limited water resources, substantial biodiversity of rare and threatened species, as well as oil and gas resources. The region has unique hydrology related to perennial springs, and the formation of large aufeis fields—sheets of ice that grow in the river channels where water reaches the surface in the winter and freezes. This work aims to update our understanding of water resources and water quality in the springs, streams, rivers, and lakes of this region, returning to sites sampled by the U.S. Geological Survey in the 1970s. We resampled eight streams, four springs, and six lakes for hydrological metrics, water quality, and macroinvertebrates, and recalculated flood-frequency metrics for rivers using updated data and modern techniques. Aufeis field melt rates were also assessed for the past several decades. Although the available data preclude trend determinations in most cases, our analysis and comparison to the historical sampling indicates an increase in dissolved ions for streams and springs, faster and earlier aufeis melt, and similar macroinvertebrate populations.

Alaska

Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River

Information on velocity fields in rivers is critical for designing infrastructure, modeling contaminant transport, and assessing habitat. Although non-contact approaches to measuring flow velocity are well established, these methods assume a stationary imaging platform. This study eliminates this constraint by introducing a framework for moving aircraft river velocimetry (MARV). The workflow takes as input images acquired from an airplane and involves orthorectification, frame overlap analysis, image enhancement, particle image velocimetry (PIV), and aggregation of the resulting velocity vectors onto a prediction grid. We also use new metrics to quantify the agreement between image-derived and field-measured velocity vectors in terms of both orientation and magnitude. The potential of MARV was evaluated using data from two Alaskan rivers: a large, highly turbid channel and its smaller, clearer tributary. Sediment boil vortices on the mainstem provided natural features trackable via PIV and estimated velocities corresponded closely with field measurements ( R 2 up to 0.911). We compared an exhaustive approach that evaluates overlap for all frame combinations to a simpler rolling window implementation and found that the more efficient algorithm did not compromise accuracy. Sensitivity analysis suggested that the method was robust to window parameterization. Comparing PIV output from different flying heights and imaging systems indicated that larger pixels led to higher accuracy and that a more advanced dual-camera system provided superior performance. Results from the tributary were less encouraging, presumably due to a lack of trackable features in visible images. Testing across a range of rivers is needed to assess the generality of MARV.

Water Resources Research

Comparison of historical water temperature measurements with landsat analysis ready data provisional surface temperature estimates for the Yukon River in Alaska

Water temperature is a key element of freshwater ecological systems and a critical element within natural resource monitoring programs. In the absence of in situ measurements, remote sensing platforms can indirectly measure water temperature over time and space. The Earth Resources Observation and Science (EROS) Center has processed archived Landsat imagery into analysis ready data (ARD), including Level-2 Provisional Surface Temperature (pST) estimates derived from the Landsat 4–5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Thermal Infrared Sensor (TIRS). We compared in situ measurements of water temperature within the Yukon River in Alaska with 52 instances of pST estimates between June 2014 and September 2020. Agreement was good with an RMSE of 2.25 °C and only a slight negative bias in the estimated mean daily water temperature of −0.47 °C. For the 52 dates compared, the average daily water temperature measured by the USGS streamgage was 11.3 °C with a standard deviation of 5.7 °C. The average daily pST estimate was 10.8 °C with a standard deviation of 6.1 °C. At least in the case of large unstratified rivers in Alaska, ARD pST can be used to infer water temperature in the absence of or in tandem with ground-based water temperature monitoring campaigns.

Alaska

Remote sensing of river flow in Alaska—New technology to improve safety and expand coverage of USGS streamgaging

The U.S. Geological Survey monitors water level (water surface elevation relative to an arbitrary datum) and measures streamflow in Alaska rivers to compute and compile river flow records for use by water resource planners, engineers, and land managers to design infrastructure, manage floodplains, and protect life, property, and aquatic resources. Alaska has over 800,000 miles of rivers including the Yukon River, the third longest river in the United States. These rivers are home to rare and important ecosystems and are used for recreation, hydropower generation, commercial fishing, and transportation. River flow measurements are essential for wise and safe development and use of Alaska rivers.

Alaska

Near-field remote sensing of Alaskan Rivers

The U.S. Geological Survey (USGS) Geomorphology and Sediment Transport Laboratory (GSTL), in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL), acquired remotely sensed data from several Alaskan rivers in 2017 and 2018 with the goal of developing a methodology for measuring streamflow from a helicopter. CRREL operates a custom airborne lidar system that can be deployed in a helicopter-based pod (HeliPod). Data were collected with the HeliPod near existing USGS streamflow information stations on the Knik, Matanuska, Chena, and Salcha Rivers in both 2017 and 2018. Sites on the Tanana and Snow Rivers were added in 2018. In 2018, the HeliPod was modified to accommodate both a thermal infrared and a visible camera. The cameras were integrated with the flight management software to simultaneously acquire imagery with lidar. The Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) in the HeliPod were used to compute trajectories with precise position and orientation information needed for image orthorectification. The HeliPod sensors provide data for measuring river channel characteristics. Lidar can map the elevation of the water surface and thus be used to measure water-surface slopes and return intensity can be used to delineate the extent of the wetted river channel. Various approaches are currently being evaluated to estimate surface flow velocity from visible and thermal image time series. In this paper, we examine and compare water-surface elevation returns and slopes derived from the HeliPod lidar and found good agreement with measurements made using conventional field-based techniques.

Alaska