Cheat Water Resources: Assessing Climatology and Land Cover Trends and Evaluating Flood Risk of the Cheat River
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Fire Island National Seashore has experienced damaging effects as a result of coastal erosion. Erosion has become an increasingly damaging problem that has led to the destruction of park and community infrastructure, contributed to rising groundwater tables, and posed a serious threat to a globally rare holly maritime forest. Beach nourishment project efforts have been made to mitigate damage, but dredging is expensive and can be thwarted by high rates of erosion. The NASA DEVELOP team partnered with the National Park Service and Fire Island National Seashore and used imagery from Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), and Sentinel-2 MultiSpectral Instrument (MSI) to analyze turbidity and sediment dynamics through surface reflectance data from 2000-2021. Imagery was atmospherically corrected using Atmospheric Correction for OLI Lite (ACOLITE) and visualized in SeaWiFS Data Analysis Systems (SeaDAS). Additionally, shoreline change was analyzed using high-resolution imagery from WorldView-2 acquired from Maxar for pre-Hurricane Sandy on July 25th, 2010 and post-Hurricane Sandy on December 18th, 2019. The results of this analysis showed that turbidity is highest in the winter seasons. The shoreline analysis estimated total shoreline loss of about 62 acres on the ocean side, and 11 acres on the bay side of the island. These results will be used to better inform future partner-designed shoreline management projects in the face of further erosion and sea level rise.
Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.
Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.
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Explore the source record for details and available documents.
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The Gulf of Maine has a history of harmful algal blooms (HABs) that have been increasing in frequency and intensity in recent years, raising concerns in the community. Specifically, the Pseudo-nitzschia genus possesses harmful toxins that can induce food-borne illnesses and infect humans through ambient water. We observed in-situ data from known 2016 and 2020 Pseudo-nitzschia blooms as case studies to test the feasibility of using satellite data to track bloom events. In order to map the frequency and distribution of Pseudo-nitzschia bloom events, we used satellite data from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-3 Ocean and Land Colour Instrument (OLCI). We utilized Earth observation data to calculate normalized fluorescence line height (nFLH) and absorption by phytoplankton (aph443), which are satellite products that more accurately depict phytoplankton reflectance. We compared these products with in-situ observations in order to analyze ocean color differences and distinguish diatomic algal particles from other organic and inorganic particles.
In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and negatively impacting the ecosystem. This release greatly affected the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WYDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming–Montana Water Science Center, this project utilized satellite imagery and precipitation data to examine turbidity patterns in the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. We used PlanetScope satellite images to assess changes in surface reflectance of the river in response to precipitation events and Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) precipitation data to estimate the lag time between rainfall events and increased turbidity. The National Land Cover Dataset (2019) was used to identify the main land cover types within each sub-basin. The end products included a turbidity analysis, land cover analysis, and precipitation analysis that provided the partners with a better understanding of sediment dynamics in the river. The results demonstrated the feasibility of using PlanetScope data to examine turbidity spatially along small rivers. Sediment plumes from tributaries were visually identified for multiple high turbidity events, and we calibrated an equation that translated reflectance to turbidity, accurately representing plume extent. Inconsistent spectral quality of PlanetScope data, however, limited our ability to assess the relative sediment contribution of the tributaries.
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The Potomac River Basin (PRB) is responsible for providing drinking water to over 5 million residents and plays a significant role in the health of the Chesapeake Bay. Therefore, it is important to understand the relationship between water quality, landcover, and the hydrological cycle within the PRB. The National Park Service (NPS) has monitored 37 streams within the National Park Units in Maryland, Virginia, West Virginia and Washington, D.C. This project aimed to help the NPS better understand trends in water quality to supplement their ability to monitor changes in the National Capital Region Network (NCRN). Google Earth Engine, ArcGIS Pro, R, and Python were used for data retrieval, visualization, and analysis. Earth observations included Landsat 5 TM and Landsat 8 OLI/TIRS imagery. Ancillary data included the USDA Cropland Data Layer, Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS), and soil moisture data from the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). We compared Land use/land cover (LULC), Normalized Difference Vegetation Index (NDVI), precipitation and soil moisture data to water quality data provided by the NPS at a watershed level. LULC change maps were also generated for the PRB between 2008 and 2022. We found significant correlations between precipitation, soil moisture, NDVI, and water quality. Correlations were found between certain land use types and water quality metrics, but findings varied greatly between watersheds. These insights emphasize the imperative of strategic watershed management in preserving the integrity of key aquatic systems.
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In the Platte River Basin, wetlands provide ecosystem services such as flood mitigation and wildlife habitat. However, increasing urban development in the area has impacted natural floodplain processes, leading to a decline in wildlife habitat and an elevated flood risk for nearby communities. To address this issue, Audubon Great Plains’ Urban Woods and Prairies (UWP) Initiative focuses on restoring vital habitats within urban areas to protect bird species and reduce flood hazards. Our project used remotely sensed data, including Landsat 8 Operational Land Imagery (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR), to assess land use and land cover from 2013 to 2023, as well as flood extent. Broad-scale analysis of the LULC showed some changes in land use patterns across the Central Platte River Basin, with the most notable being a decrease in Agricultural land coverage and an increase in Vegetation and Grassland coverage. Land use changes varied across 13 focal cities across the entire basin. In particular, developed land in Grand Island, NE, nearly tripled from 2019 to 2023, making it a good possible candidate for restoration efforts. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under UWP. This data will inform Audubon Great Plains in identifying potential restoration sites in key cities.
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The State of Alaska has a rather unique electric power system, as it has two larger transmission grids (Railbelt and Southeast Alaska) and over 150 islanded stand-alone power systems that are serving remote rural communities. In 2010, the Alaska legislature enacted a non-binding goal for 50% of renewable electricity generation by 2025. With the expected increase in wind and solar generation in the future, the role of energy storage becomes increasingly important. Considering the specific power system characteristics in Alaska, energy storage technologies that can supply electricity over an extended period of time, such as pumped storage hydropower (PSH), may play a key role in enabling the reliability and resiliency of both integrated and rural power systems. The overarching objective of the subject study of this presentation is to investigate the prospects and opportunities for PSH in Alaska.