Abstract Understanding the dynamics of heat transfer mechanisms is critical for forecasting the effects of climate change on arctic river temperatures. Climate influences on arctic river temperatures can be particularly important due to corresponding effects on nutrient dynamics and ecological responses. It was hypothesized that the same heat and mass fluxes affect arctic and temperate rivers, but that relative importance and variability over time and space differ. Through data collection and application of a river temperature model that accounts for the primary heat fluxes relevant in temperate climates, heat fluxes were estimated for a large arctic basin over wide ranges of hydrologic conditions. Heat flux influences similar to temperate systems included dominant shortwave radiation, shifts from positive to negative sensible heat flux with distance downstream, and greater influences of lateral inflows in the headwater region. Heat fluxes that differed from many temperate systems included consistently negative net longwave radiation and small average latent heat fluxes. Radiative heat fluxes comprised 88% of total absolute heat flux while all other heat fluxes contributed less than 5% on average. Periodic significance was seen for lateral inflows (up to 26%) and latent heat flux (up to 18%) in the lower and higher stream order portions of the watershed, respectively. Evenly distributed lateral inflows from large scale flow differencing and temperatures from representative tributaries provided a data efficient method for estimating the associated heat loads. Poor model performance under low flows demonstrated need for further testing and data collection to support the inclusion of additional heat fluxes.
The Pecora 22 conference occurred 24–27 October 2022 in Denver, Colorado. Hundreds of remote sensing experts, practitioners, and end users convened in the same location to share their research, tools, and experiences with the larger community. While session themes spanned a suite of scientific and engineering disciplines, a common thread across all sessions underscored how basic and applied scientists can use remote sensing to identify heterogeneous and dynamic environments at unprecedented spatial and temporal scales. While the conference highlighted the breadth of remote sensing developments and applications, there were several sessions focusing on how remote sensing can further our understanding of water quantity and quality, bathymetry, as well as broadening participation in the remote sensing community. Below, we highlight the topics discussed in five Pecora sessions that pertained to various facets of remote sensing of aquatic systems. By highlighting these sessions, we hope to further bridge remote sensing developments and limnology, thereby expediting cross-pollination between these fields and encourage members of the ASLO community to contact presenters regarding their specific talks (https://pecora22.org/program/). Among the talks centered on remote sensing of aquatic systems, Pecora 22 hosted related sessions that focused specifically on cutting edge advances in remote sensing of water quality and quantity. Together, these sessions spanned a range of topics, including calibration and validation of aquatic surface reflectances, detection of chlorophyll and cyanobacterial presence within and across aquatic systems, use of altimetry data to evaluate surface water dynamics, and macroscale syntheses of lake water quality trends. A common goal of these sessions was to highlight the breadth of remote sensing developments that enable more accurate measurements of surface water dynamics and water quality constituents. Here, we detail the range of topics discussed within two of the sessions. This session highlighted the half-century of Landsat satellite sensor observations and what these data have enabled with respect to developing, testing, and validating novel methodologies for studying aquatic ecosystems worldwide. Typically, these advances have included assessments of optically relevant water quality indicators—such as sediment, pigments, and dissolved organic matter—as well as water color. In many cases, the Landsat mission's data has also contributed to advance the characterization and mapping of coral and seagrass assemblages in marine environments, as well as the detection of surface algae and emergent vegetation in freshwater systems. Through Landsat's consistent multi-decadal thermal measurements and the derived high-quality surface temperature products, identifying trends and changes in water surface temperature due to climate variability and extreme weather patterns have also been made possible. Mirroring the diversity of projects that the Landsat mission has empowered, this session emphasized how Landsat data providers and curators are working to correct Landsat reflectance data for aquatic environments, thereby increasing the accuracy of remotely sensed water quality constituents. Beyond data products, this session also showcased how macroscale ecological questions and management applications are already within reach using existing products. In particular, talks focused on detection and chlorophyll and cyanobacterial presence from local-to-national spatial scales and echoed how remotely sensed water quality data can benefit a suite of end users, ranging from lake associations through federal agencies. This session emphasized the multifaceted developments of remote sensing of water quality, particularly among members of the U.S. Geological Survey's (USGS) Remote Sensing Research and Development Project as well as Colorado State University. The session included talks focused on data product development, such as the creation of the "Potentially Resolvable Waterbodies Dataset" (Hafen and Ducar 2021), as well as the bias-corrected Landsat 8 aquatic surface temperature data product, in addition to presentations expanding on ecological analysis of limnological processes at various scales. At regional scales, presenters demonstrated how they used remote sensing to track trends in chlorophyll concentration across lakes in Colorado and Wyoming (United States) as well as reservoirs in Oklahoma and Texas (United States). Finally, at macroscales, presenters showcased how they used remote sensing imagery to understand beaded stream dynamics across boreal environments, which can be important for mapping endemic species habitat, and to evaluate spatial and temporal trends in lake trophic state across the contiguous United States. Altogether, this session highlighted the true power and promise of how remote sensing can aid managers and researchers alike by offering insights into how lakes, reservoirs, and streams change intensively within individual systems as well as extensively across spatial and temporal scales. Recent interest in remote sensing retrieval of shallow-water satellite-derived bathymetry (SDB) is being driven by the availability of multispectral and stereo satellite imagery, altimetry, and Synthetic Aperture Radar (SAR) satellite data at the global scale and with increased spatial and temporal resolution. Collectively, these datasets and techniques can be combined to map large regions of the littoral zone to help fill critical data gaps not acquired by traditional mapping systems. This session included talks focused on inferring inherent water optical properties from Landsat 8 and 9, ICESat-2, and stereo WorldView satellite imagery to derive SDB. The USGS is currently researching deep-water pixels to derive inherent water optical properties to compute diffuse attenuation in the water column. For shallow water, subsequent non-linear optimization is performed to compute SDB. The ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data, Version 5 (ATL13) is an example of ICESat-2 bathymetry data deliverables for inland and coastal waters. A collaboration between USGS and NASA produced the Satellite Triangulated Sea Depth module (SaTSeaD), which uses stereo satellite imagery to derive seamless topo-bathymetry without external bathymetric calibration. A multi-modal depth retrieval using deep learning, ICESat-2 data, and multispectral imagery to derive SDB was presented by TCarta. The session closed with an assessment of satellite-based observations of bathymetric change, a collaboration between Oregon State University and OregonView/AmericaView Consortium. A common theme among presenters was that identifying areas of bathymetric change is more important than having a single high-quality snapshot of a waterbody's bathymetry. This session included projects focused on marine and freshwater ecosystems with the common theme of conserving living marine and freshwater resources for the benefit of society. Presentations focused on the integral role of Earth observations and how the tools and products provided to stakeholders benefit management and conservation decisions. The NASA Ecological Conservation Applications Program, among others, encourages the use of Earth observations to provide a research foundation and the development of products and tools for stakeholders to use for decision-making. Presentations focused on how multivariate and multiscale satellite data are used in the modeling of plankton composition and extents of biofilms in wetlands; modeling wetland change over landscape scales; the extent and dynamics of polynyas in Antarctica; using remote sensing and population analyses to conserve native trout populations, and to understand and track biogeographic changes in coastal and open ocean ecosystems. The presentations generated discussion on the translation of tools and theory from land to water; how scales of change across different systems necessitate the integration of in situ, airborne, and satellite assets; and how ecologists working across these systems are preparing for the next generation of hyperspectral sensors. Emphasizing diversity, equity, inclusivity, justice, and accessibility (DEIJA) is essential for creating a conference environment in which new ideas and collaborations can grow. The fields of remote sensing and Earth observation have a history of academic and scientific gatekeeping, especially at the academic publishing level (Joyce et al. 2022), which can have clear ties to conference participation. This gatekeeping has the potential to limit the voices and engagement of scientists from traditionally underrepresented groups, thus limiting the possibility for new ideas and science to emerge. The presence and involvement in conference activities from remote sensing affinity groups, such as Ladies of Landsat, Sisters of SAR, Dames of Drones, Women in Geospatial+, GeoChicas, and many more, can help to create a conference atmosphere where early career researchers, students, and underrepresented scientists have a support system of other scientists and participants to champion their work both in front of and behind the scenes. At Pecora 22, Ladies of Landsat was active in creating a welcoming environment for all. They hosted a panel session, "Ladies of Landsat: Power of the Pixel," with remote sensing scientists from the government, industry, academia, and non-profit sectors to discuss opportunities and challenges with remote sensing and DEIJA as well as a coffee social, attended by the U.S. Department of Interior Assistant Secretary for Water and Science, Tanya Trujillo, to create a networking opportunity for conference participants. In addition to this dedicated session as well as the remote sensing for freshwater and marine environments sessions, DEIJA was emphasized in the breadth of career stages presenting, from students to late-career scientists, as well as the geographic spread of research presented. Following the Pecora 22 conference, there was an air of enthusiasm and energy with the rapidly progressing developments that are enabling cross-scale analyses of water. While Pecora largely attracted researchers and managers from the remote sensing-based sciences, the joint session conveners are convinced that these combined tools will benefit the limnological and oceanographic communities broadly. As we look forward to ASLO 2023 and skim through upcoming session descriptions, we are encouraged by the range of sessions that integrate remote sensing technologies, and we look forward to further collaborations between these communities.
The Missouri Department of Transportation (MoDOT) currently uses an Exposure Index (EI) formula to prioritize its more than 4000 highway/rail crossings for safety upgrades. The EI formula was developed in the 1970s and has not changed since then. This study evaluates the effectiveness of the EI formula and examines the possibility of adoption of an alternative formula for use in Missouri for prioritizing crossings for safety improvements. Seven models used by other states to prioritize rail-highway grade crossings were selected for study. A panel of officials associated with MoDOT, the U.S. Department of Transportation, and railroad companies was assembled to provide guidance to identify the most desirable models. Eight criteria, along with their relative importance, were identified to rank the models. After the models were analyzed and final indices developed, the panel of experts was assembled again to review and select a potential replacement model for the EI. The panel recommended the research team conduct sensitivity analyses on modifying the Kansas Design Hazard Rating Model for possible use in Missouri. Subsequent analyses were inconclusive in determining potential modifications to the Kansas Model. However, it is the finding of this study that consideration should be given to replacing the EI with a form of the Kansas Model and that further research be conducted on defining the necessary modifications to the Kansas Model.
Abstract Hyporheic exchange has the potential to significantly influence river temperatures in regions of continuous permafrost under low‐flow conditions given the strong thermal gradients that exist in river bed sediments. However, there is limited understanding of the impacts of hyporheic exchange on Arctic river temperatures. To address this knowledge gap, heat fluxes associated with hyporheic exchange were estimated in a fourth‐order Arctic river using field observations coupled with a river temperature model that accounts for hyporheic exchange influences. Temperature time series and tracer study solute breakthrough curves were measured in the main channel and river bed at multiple locations and depths to characterize hyporheic exchange and provide parameter bounds for model calibration. Model results for low‐flow periods from 3 years indicated that hyporheic exchange contributed up to 27% of the total river energy balance, reduced the main channel diel temperature range by up to 1.7 °C, and reduced mean daily temperatures by up to 0.21 °C over a 13.1‐km study reach. These influences are due to main channel heat loss during the day and gain at night via hyporheic exchange and heat loss from the hyporheic zone to the ground below via conduction. Main channel temperatures were found to be sensitive to simulated changes in ground temperatures due to changes in hyporheic exchange heat flux and deeper ground conduction. These results suggest that the moderating influence of hyporheic exchange could be reduced if ground temperatures warm in response to projected increases in permafrost thaw below rivers.
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