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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Effects of EMF Emissions from Cables and Junction Boxes on Marine Species

Studies have shown that diverse aquatic species are electrosensitive. Many fishes, and marine mammals, can either detect, navigate by, or are affected by electromagnetic fields (EMF) with various sensitivities, and their behavior may be impacted by unnatural EMF emissions in the water column. Sharks, rays and skates are known to have the highest sensitivity to electric fields. Electric field emissions in the range 0.5–100 micro volt/m appear to attract them, and emissions over 100 micro volt/m to repulse them. A marine hydrokinetic MHK device will have multiple components and associated multiple submarine cables on the seafloor and running through the water column and would potentially increase the level of EMF emissions to which the marine species at the site may be exposed to. There are therefore concerns amongst stakeholders that EMF emissions associated with MHK devices and their components may act as barriers to species migration, cause disorientation, change community compositions and ecosystems, and that they may attract sharks, leading to a local increase in the risk of shark attacks. However, field data to validate and model potential relationships between observed responses and the EMF emissions in situ are sparse. A program of experimental field surveys were conducted off the coast of South Florida, USA to characterize the electromagnetic field (EMF) emissions in the water column from a submarine cable, and to monitor for responses of local aquatic species. The field surveys were conducted at the South Florida Ocean Measurement Facility (SFOMF) off Fort Lauderdale, which is a cabled offshore in-water navy range. It consists of multiple active submarine power cables and a number of junction boxes, with the capability to transmit AC/DC power at a range of strength and frequencies. The site includes significant marine life activities and community structure, including highly mobile species, such as sharks, stingrays, mammals and turtles. SFOMF therefore typifies a setting representative of an offshore location where a MHK device may be sited. Background electromagnetic field (EMF) levels and EMF emissions due to submarine cables were measured using a custom E-field sensor and a commercial magnetometer deployed from an autonomous underwater vehicle (AUV) at various fixed altitudes above the seafloor. EMF signatures detected from power cables and junction boxes are contrasted against ambient background levels and other EMF sources. The potential responses of local marine species were observed at selected representative locations using divers on SCUBA, complemented with fixed cameras on the sea bottom and by a set of video cameras mounted on the AUV. The objectives of the study were: 1) to characterize the EMF emission levels associated with submarine cables 2) to monitor potential responses of aquatic animals to the emissions and 3) to develop an associated database of field observations. As control, observations of EMF levels and in situ marine species were conducted with power in the cable turned off. Good quality measurements of EMF emissions were obtained using the mobile AUV platform and the data from the surveys were used to develop contour maps of the EMF levels in the water column above the live cable as well as to provide information about how the field decays away from the cable. The measurements show good agreement with theoretical models of the how EMF levels decay away from the cable in deep and shallow water environment. Electric fields in excess of 200µV/m were measured in the vicinity of the cable during the power on state. Quarterly surveys by SCUBA divers were conducted, using point and transect count methods, over a period of one year at three locations, one at a shallow site where the water depth is approximately 5m, and the other at the Barracuda Reef where the water depth is approximately 10m. The sampling results were analyzed to determine if the presence of an SFOMF generated EMF alters: (1) abundance, species richness, and assemblage structure of coral reef fishes, (2) the behavior of fishes including elasmobranchs, and (3) the distribution of marine turtles and mammals. Diver observations were also used in attempt to discern if there were any noticeable organismal responses during the transitional period between ambient OFF to energized AC or DC power states, and video footage was intended to augment the in-situ visual survey data and aid in interpretation of the results. Comparisons are provided between observation datasets between the three sites and between the point and transect count methods. Presence of several individual elasmobranch species, including sharks and stingrays, were recorded during the surveys. No apparent effect on richness could be discerned between the power on and off states. No apparent sudden animal movements were observed during transitions between power states.

16 TIDAL AND WAVE POWER↗
NASA NTRS2025

Hilo Bay Water Resources: Monitoring Water Quality in Hilo Bay, Hawaii to Support Future Community Planning

Designated as an impaired body of water by both state and federal water quality standards, Hilo Bay, Hawaiʻi is highly susceptible to brown water, a condition where the water becomes murky and is associated with excess levels of bacteria, contaminants, and nutrients. A breakwater in Hilo Bay, which was established to protect Hilo town from tsunamis, interferes with water circulation and prolongs the presence of brown water in the bay. The State of Hawaiʻi issues brown water advisories (BWAs) following flash flood warnings, sewage spills, and other events to indicate a public health concern for those who use Hilo Bay for recreation, cultural purposes, and fishing. Due to the elevated public health risk and ecosystem disturbance that brown water poses to Hilo Bay, we partnered with the Hawaiʻi County Office of Sustainability, Climate, Equity, and Resilience (OSCER) to examine the feasibility of using Earth observations (EO) to monitor water quality in the Hilo Bay region. We leveraged data from Sentinel-2 Multispectral Instrument (MSI), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, and Aqua and Terra Moderate Resolution Imagine Spectroradiometer (MODIS) instruments to identify and assess spatial and temporal patterns of two main water quality parameters, turbidity and chlorophyll-a, during BWAs. We used the Optical Reef and Coastal Area Assessment (ORCAA) tool in Google Earth Engine to process EO data and generate water quality maps and time series. Our study found that increased turbidity levels can be identified by EO data during BWAs. In addition, our map products indicated the presence of several turbidity plumes along the coast, with the highest concentration of turbidity found within Hilo Bay. While chlorophyll-a levels were relatively flat within our study region during BWAs, we found that regional chlorophyll-a patterns could be derived from MODIS chlorophyll-a data in NASA Worldview. Our study’s multi-sensor approach provided valuable insights for how water quality in the Hilo Bay region can be monitored in the future.

remote sensing↗
NASA NTRSDate not supplied

CyanoSCape: Freshwater Phytoplankton and Floating Aquatic Vegetation Biodiversity

In Southern Africa, the impacts of anthropogenic activities on biodiversity and ecosystem services are exacerbated by the climate crisis. Rapid land use change and the lack of emphasis on environmentally sustainable agricultural practices has hindered hydrological processes and compromised riverine and aquatic ecosystems. This poses obvious risks to natural/indigenous aquatic biodiversity and long-term ecosystem sustainability. Phytoplankton serve as the foundation of the freshwater food web with zooplankton as consumers, which feed fish, invertebrates, and so on up the food chain that comprises the biodiversity of the freshwater system that serves as habitat for biodiversity as well. The diversity of phytoplankton (microscopic organisms) includes photosynthesizing bacteria (cyanobacteria), plant-like diatoms, dinoflagellates, and green algae. Nutrient run-off from agricultural fertilizers and urban overflows, warm temperatures, abundant light availability and compromised hydrological systems provide an ideal environment for cyanobacteria to flourish. Increased prevalence of cyanobacteria, due to both natural and anthropogenic causes, can incur significant effects on the biodiversity of the overall phytoplankton assemblage. These bloom forming algae can significantly outcompete other phytoplankton classes in warmer and eutrophic waters where they are quick to dominate the freshwater system. Eutrophication and toxic cyanobacteria blooms (cyanoHABs) in the inland waters of the Greater Cape Floristic Region (GCFR) incur significant effects on the biodiversity of the overall phytoplankton assemblage and provide a favorable environment forthe overgrowth of floating aquatic vegetation (FAV), which is often invasive and associated with reduced aquatic biodiversity. The algal biodiversity of the GCFR’s freshwater systems is not well characterized. Hyperspectral optical observations are expected to facilitate the improvement of current phytoplankton functional type retrievals significantly, as the sensitivity is sufficient that the distinctive, fine spectral features of different phytoplankton groups can be detected. This will enable testing emerging algorithms and inform the development of new algorithms for use with upcoming hyperspectral satellite missions in this decade. Innovations in optical sensor sensitivity and next generation machine learning capabilities considerably enhance the potential for accurate and rapid detection of phytoplankton, namely the presence, extent, and diversity of cyanobacteria present in cyanoHABs and additionally, invasive FAV. Upcoming hyperspectral satellite missions such as NASA’s Surface Biology and Geology (SBG), Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and the European Space Agency’s Copernicus Hyperspectral Imaging Mission (CHIME) will provide imagery with unprecedented spectral and spatial resolution which will further enable the discovery of linkages between the seasonality and dynamics of HABs and FAV. The overarching goal of this project is to utilize hyperspectral data, with recently developed and next-generation algorithms, to determine the biodiversity of freshwater systems phytoplankton assemblage with emphasis on genus level distinction, as well as monitor the prevalence and diversity of FAV.

CyanoSCape↗
DOE OSTI2026

Data Interfaces for Automated Vehicle Services - A Municipality Perspective

As Automated Vehicle (AV) services proliferate, data sharing between AV operators and municipal agents is assuming greater importance. Information on the dynamic nature of the road system such as incidents to avoid, weather hazards (such as flooding), construction and detours, as well as active safety concerns (e.g. - riots) is important for AV operators. Such information cannot be directly sensed from a vehicle's sensor array, but instead must be communicated in a timely and trustworthy channel. Municipalities are interested in pushing this information to AV operators to support emergency response efforts, reduce traffic in construction zones, and generally improve operation of the system. Similarly, information on vehicle safety such as disengagements, as well as critical information on the use of roadway system (trips, origin and destination patterns) are important performance factors for municipalities to understand utilization and plan for appropriate infrastructure. As mobility shifts to on-demand options, the need for safe and coordinated pick-up and drop-off zones will increase (potentially reducing parking needs). For all of these reasons, communication flows between AV operators and municipalities are becoming increasingly important. This paper investigates the functions, emerging practices and protocols for sharing of such critical data, and identifies gaps in and challenges in existing practices. Additionally, case studies are used to highlight the impacts of data sharing between AV operators and municipalities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2009

Land-Use and Land-Cover Change around Mobile Bay, Alabama from 1974-2008

This document summarizes the major findings of a Gulf of Mexico Application Pilot project led by NASA Stennis Space Center (SSC) in conjunction with a regional collaboration network of the Gulf of Mexico Alliance (GOMA). NASA researchers processed and analyzed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL between 1974 and 2008. Our goal was to create satellite-based LULC data products using methods that could be transferable to other coastal areas of concern within the Gulf of Mexico. The Mobile Bay National Estuary Program (MBNEP) is the primary end-user, however, several other state and local groups may benefit from the project s data products that will be available through NOAA-NCDDC s Regional Ecosystem Data Management program. Mobile Bay is a critical ecologic and economic region in the Gulf of Mexico and to the entire country. Mobile Bay was designated as an estuary of national significance in 1996. This estuary receives the fourth largest freshwater inflow in the United States. It provides vital nursery habitat for commercially and recreationally important fish species. It has exceptional aquatic and terrestrial bio-diversity, however, its estuary health is influenced by changing LULC patterns, such as urbanization. Mobile and Baldwin counties have experienced a population growth of 1.1% and 20.5% from 2000-2006. Urban expansion and population growth are likely to accelerate with the construction and operation of the ThyssenKrupp steel mill in the northeast portion of Mobile County. Land-use and land-cover change can negatively impact Gulf coast water quality and ecological resources. The conversion of forest to urban cover types impacts the carbon cycle and increases the freshwater and sediment in coastal waters. Increased freshwater runoff decreases salinity and increases the turbidity of coastal waters, thus impacting the growth potential of submerged aquatic vegetation (SAV), which is critical nursing ground for many Gulf fish species. A survey of Mobile Bay SAV showed widespread decreases since the 1940s. Prior to our project, coastal environmental managers in Baldwin and Mobile counties needed more understanding of the historical LULC for properly assessing the impacts of urbanization. In particular, more information on the location and extent of changing urbanization LULC patterns was needed to aid LULC planning and to assess predictions of future LULC patterns. Our products will assist the coastal environmental managers and land-use planners in making better community growth planning decisions. Our project also will help to establish a historical baseline of LULC distributions, which is a fundamental need in any stewardship plan. The primary research objective of our project was to produce historic and current geospatial LULC change products across a 34-year time frame. A multi-decadal coastal LULC change product was the major project deliverable. The geographic extent and nature of change was quantified and assessed for the upland herbaceous, barren, open water, urban, upland forest, woody wetland, and non-woody wetlanddominated land cover types. We focused on regional analyses of decadal-scale urban expansion and watershed-scaled analyses of LULC change for multiple areas of concern to the Mobile Bay NEP (Figure A). We used the following dates to derive LULC classification products from Landsat data: 1974, 1979, 1984, 1988, 1991, 1996, 2001, 2005, and 2008. We assessed the accuracy of our products using randomly sampled locations and digital geospatial reference data including field survey data, high resolution orthorectified aerial photography, high resolution multispectral and panchromatic satellite data displays (from QuickBird and Corona sensors), digital elevation model data, and National Wetlands Inventory wetland cover type data. NOAA s Coastal Change Assessment Program s (C-CAP) and National Land Cover Database (NLCD) procts were used for qualitative comparison in assessing map accuracy. We calculated an average overall classification accuracy of 87% with similar overall accuracies for the older (MSS) and newer (TM and ETM) Landsat LULC products.

Ellis, Jean↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Brigham City Hydro Generation Project

Brigham City owns and operates its own municipal power system which currently includes several hydroelectric facilities. This project was to update the efficiency and capacity of current hydro production due to increased water flow demands that could pass through existing generation facilities. During 2006-2012, this project completed efficiency evaluation as it related to its main objective by completing a feasibility study, undergoing necessary City Council approvals and required federal environmental reviews. As a result of Phase 1 of the project, a feasibility study was conducted to determine feasibility of hydro and solar portions of the original proposal. The results indicated that the existing Hydro plant which was constructed in the 1960’s was running at approximately 77% efficiency or less. Brigham City proposes that the efficiency calculations be refined to determine the economic feasibility of improving or replacing the existing equipment with new high efficiency equipment design specifically for the site. Brigham City completed the Feasibility Assessment of this project, and determined that the Upper Hydro that supplies the main culinary water to the city was feasible to continue with. Brigham City Council provided their approval of feasibility assessment’s results. The Upper Hydro Project include removal of the existing powerhouse equipment and controls and demolition of a section of concrete encased penstock, replacement of penstock just upstream of the turbine inlet, turbine bypass, turbine shut-off and bypass valves, turbine and generator package, control equipment, assembly, start-up, commissioning, Supervisory Control And Data Acquisition (SCADA), and the replacement of a section of conductors to the step-up transformer. Brigham City increased the existing 575 KW turbine and generator with an 825 KW turbine and generator. Following the results of the feasibility assessment Brigham City pursued required environmental reviews with the DOE and the U.S. Fish and Wildlife Services (USFWS) concurring with the National Environmental Policy Act of 1969 (NEPA) It was determined that Brigham City’s Upper Hydroelectric Power Plant upgrade would have no effect to federally listed or candidate species. However Brigham City has contributed a onetime lump sum towards Bonneville cutthroat trout conservation in the Northern Bonneville Geographic Management Unit with the intention to offset any impacts from the Upper Hydro Project needed to move forward with design and construction and is sufficient for NEPA compliance. No work was done in the river or river bank. During construction, the penstock was disconnected and water was diverted through and existing system around the powerhouse and back into the water system. The penstock, which is currently a 30-inch steel pipe, would be removed and replaced with a new section of 30-inch pipe. Brigham City worked with the DOE and was awarded a new modification and the permission to proceed with Phase III of our Hydro Project in Dec. 2013; with the exception to the modification of the award for the construction phase. Brigham City developed and issued a Request for Proposal for Engineer and Design vendor. Sunrise Engineering was selected for the Design and throughout the Construction Phase of the Upper Hydroelectric Power Plant. Brigham City conducted a Kickoff Meeting with Sunrise June 28, 2013 and received a Scope of Work Brigham City along with engineering firm sent out a RFP for Turbine, Generator and Equipment for Upper Hydro. We select Turbine/Generator Equipment from Canyon Industries located in Deming, WA. DOE awarded Brigham City a new modification and the permission to proceed with Phase III Construction of our Hydro Project. Brigham City Crews removed existing turbine/generator and old equipment alone with feeder wires coming into the building basically giving Caribou Construction an empty shell to begin demolition. Brigham City contracted with Caribou Construction from Jerome, Idaho for the Upper Power Plant construction. A kickoff meeting was June 24, 2014 and demolition was immediately started on building. Because of a delivery delay of Turbine, Generator and Equipment from Canyon Brigham City had to request another extension for the final date of completion. DOE awarded modification (.007) to Brigham City with a new completion date of August 1, 2015. The Turbine has had a few adjustments to help with efficiency; but the Generator had a slight vibration when generator got hot so Canyon Industries had U S Motor’s that manufactured the generator come to check out the issue. The other Equipment seems to be running normal. Brigham City, Sunrise Engineering and Canyon Industries met to determine what the vibration in the generator was and how to solve the issue Us Motor’s found some welds that failed: they have been repaired. U S Motor’s delivered the repaired generator Feb. 17, 2015. Canyon Industries arranged for a crane to installed generator in Power Plant. U S Motor’s balanced and wired generator. Plant Operators put the generator back on line. Canyon Industries returned and gave their approval to keep Hydro online. After Hydro was put back into operations it kept going off line because of overheating issues. Canyon Industries returned and replaced sensors and adjusted them to the proper settings for normal operations. Brigham City added additional steel screens to windows to increase air flow in Power Plant Building. After construction phase of the Upper Hydro Plant some landscaping has been restored around the building additional gravel brought in and leveled out and the road that was cut through for conduits to run wires. A retaining wall was installed to protect penstock. The Upper Hydro Plant is complete and in full operations. The final reimbursement was submitted.

13 HYDRO ENERGY↗