NASA Ames DEVELOP Interns Collaborate with the South Bay Salt Pond Restoration Project to Monitor and Study Restoration Efforts using NASA's Satellites

In the past, natural tidal marshes in the south bay were segmented by levees and converted into ponds for use in salt production. In an effort to provide habitat for migratory birds and other native plants and animals, as well as to rebuild natural capital, the South Bay Salt Pond Restoration Project (SBSPRP) is focused on restoring a portion of the over 15,000 acres of wetlands in California's South San Francisco Bay. The process of restoration begins when a levee is breached; the bay water and sediment flow into the ponds and eventually restore natural tidal marshes. Since the spring of 2010 the NASA Ames Research Center (ARC) DEVELOP student internship program has collaborated with the South Bay Salt Pond Restoration Project (SBSPRP) to study the effects of these restoration efforts and to provide valuable information to assist in habitat management and ecological forecasting. All of the studies were based on remote sensing techniques -- NASA's area of expertise in the field of Earth Science, and used various analytical techniques such as predictive modeling, flora and fauna classification, and spectral detection, to name a few. Each study was conducted by a team of aspiring scientists as a part of the DEVELOP program at Ames

Hyperspectral Biofilm Classification Analysis for Carrying Capacity of Migratory Birds in the South Bay Salt Ponds

Tidal marshes are highly productive ecosystems that support migratory birds as roosting and over-wintering habitats on the Pacific Flyway. Microphytobenthos, or more commonly 'biofilms' contribute significantly to the primary productivity of wetland ecosystems, and provide a substantial food source for macroinvertebrates and avian communities. In this study, biofilms were characterized based on taxonomic classification, density differences, and spectral signatures. These techniques were then applied to remotely sensed images to map biofilm densities and distributions in the South Bay Salt Ponds and predict the carrying capacity of these newly restored ponds for migratory birds. The GER-1500 spectroradiometer was used to obtain in situ spectral signatures for each density-class of biofilm. The spectral variation and taxonomic classification between high, medium, and low density biofilm cover types was mapped using in-situ spectral measurements and classification of EO-1 Hyperion and Landsat TM 5 images. Biofilm samples were also collected in the field to perform laboratory analyses including chlorophyll-a, taxonomic classification, and energy content. Comparison of the spectral signatures between the three density groups shows distinct variations useful for classification. Also, analysis of chlorophyll-a concentrations show statistically significant differences between each density group, using the Tukey-Kramer test at an alpha level of 0.05. The potential carrying capacity in South Bay Salt Ponds is estimated to be 250,000 birds

Scenario Modeling of Potential Climate Change Effects in California Reservoirs

Appropriate water supply scenario modeling, that is, modeling techniques that capture the fullest range of dynamics observed in real hydrological systems, will be an essential tool in meeting 21st century water management challenges. This is especially salient in regions such as California, with large, water-dependent populations, agriculture and industry; complex water delivery systems; highly variable precipitation regimes; extended and pervasive droughts; and uncertainty in future water supply estimates associated with the potential effects of climate change. While scenario modeling is crucial, current methods often have limited incorporation of long-run forms of persistence, multi-year extremes, and a range of potential climate change effects. This dissertation addresses these applied research issues to improve historical water supply scenario modeling and highlight potential risks associated with climate change for inflows to the important Shasta/Trinity and Oroville Reservoirs of California. The goals of this dissertation were to: (1) identify and characterize long-run persistence in inflows; (2) incorporate this persistence, especially in the forms of hydrologic extremes, into water supply scenario modeling; (3) generate a range of potential hydrological futures under climate change for these inflows; and (4) examine supply reliability challenges and the role of scenario modeling in California water agencies. Key findings indicate that: (1) long-run persistence, related to large-scale climate oscillations such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), contribute to a significant portion of inflow variability; (2) use of an innovative hybrid Empirical Mode Decomposition (EMD)-Matalas modeling framework overcomes some of the limitations of traditional models to more accurately model modes of long-run persistence and multi-year extremes; (3) climate change presents potentially broad shifts and high uncertainty in future hydrological inflows where increased variance affects the frequency, duration, and intensity of floods and droughts; and (4) under this large uncertainty a water supply agency might wish to consider their risk profile and potential barriers to change