Climate Resilience

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Now showing 1 - 6 of 6
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    Rural Resilience: Economic Development, Water Resources, and Infrastructure
    Hychka, Kristen (New York State Water Resources Institute, 2019)
    The Syracuse University Environmental Finance Center (Syracuse EFC) provides technical assistance and training to rural communities in New York State and Puerto Rico for integrated water, wastewater, stormwater, and rural infrastructure resiliency planning; models for sustainable economic development through infrastructure finance; watershed management; flood and drought resiliency; and disaster preparedness. This program includes technical training and individualized assistance to rural communities focused on conducting planning for infrastructure resiliency.
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    CRP 3072/5072 Land Use/Environmental Planning/Urban Design Field Workshop for Fall 2019
    Frantz, George (New York State Water Resources Institute, 2019)
    The CRP 3072/5072 Land Use & Environmental Planning field workshop in the Fall 2018 semester conducted scenic resource inventories and prepared draft reports with recommendations for the Town of Marlborough, and Town of Lloyd in Ulster County. A third team of students, in response to feedback from the community, reviewed and revised the methodology section of the draft scenic resource inventory for the City of Poughkeepsie, Dutchess County, that was completed and delivered Fall 2017 semester. Public presentations of the drafts surveys and recommendations were made by the student teams to the Town of Marlborough Planning Board and City of Poughkeepsie Open Space Committee in December 2018. In addition, during the Spring 2019 semester, faculty and student assistants completed revisions to the Town of Cornwall draft scenic resources inventory completed in the Fall 2017 semester, focusing on minor adjustments to the methodology.
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    Climate justice and flood governance: Are New York’s flood-governance networks equipped to succeed?
    Staples, Clifton; Zemaitis, Libby; Rahm, Brian G.; LoGiudice, Elizabeth (Cornell University Department of Global Development, 2019)
    Climate justice is a social movement linking social justice to the fight against climate change, the effects of which can exacerbate social inequality. Disadvantaged groups are disproportionately impacted by sea-level rise, extreme precipitation, extreme heat, and drought. The rising threat of flooding is particularly concerning in the Northeast U.S. Flooding, like many natural hazards, overburdens historically marginalized communities such as black, indigenous, people of color, low-income, and the elderly. In the U.S., climate injustice can be traced back to unequal land access stemming from policies and practices that pushed groups to live on marginal lands (e.g. wetlands and floodplains). Furthermore, mainstream environmental movements have historically failed to recognize the perspectives of non-white people, particularly black, indigenous, and immigrant peoplev, resulting in a landscape of natural hazards management and climate change preparedness in which the interests of marginalized groups are significantly underrepresented
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    Scenic Resource Protection Guide for the Hudson River Valley
    Frantz, George (New York State Water Resources Institute, 2019)
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    Establishing Baseline and Comparative Frameworks of Flood Risk Awareness, Adaptation, and Mitigation in Troy and Kingston (Phase III)
    Blakely-Armitage, Robin; Kay, David; Williams, Lindy; Zinda, John; Alexander, Sarah (New York State Water Resources Institute, 2019)
    In 2019, the CaRDI-based team accomplished two main objectives. (1) We designed a household survey questionnaire for implementation in Troy and Kingston. We finalized the survey instrument and identified the sampling design in consultation with the Hudson River Estuary Program and Cornell’s Survey Research Institute (the survey was implemented in late spring 2020, with a delay due to the COVID-19 pandemic). (2) The team has also analyzed data from focus group discussions and interviews and presented initial results from qualitative work at four conferences. Qualitative data analysis activities have included coding of focus group and interview transcripts, analyzing and contextualizing core themes in participants’ statements about flood risk and resilience measures, presenting initial findings for feedback, and starting to compose a journal article. These analyses have raised questions about flood insurance and attitudes toward local government that we have incorporated into the household survey questionnaire. Based on this work the research team has secured federal and state funding in 2020 to expand our work to other locales.
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    Shifts in Hudson River Valley Flood Frequency Following Eastern Hemlock Loss and Succession
    Singh, Kanishka; Knighton, James; Todd Walter, Todd (New York State Water Resources Institute, 2019)
    Hydrologic models are often used to predict flooding risk driven by land surface features and meteorology. These models can be useful in estimating the consequences of the intersection of two ongoing events in the Catskill region: increased precipitation extremes and the rapid dieback of Eastern hemlock, a foundation tree species. However, simulation of transpiration in these models tends to be erroneous, with storage of water in the plants emerging as a cumbersome process to simulate. In order to improve the fidelity of modeled plant hydraulics, it is important to avoid errors originating from the simplification of the storage of water within plants. Research has found that simulating tree water storage improves model calibration. We investigate water storage in four common conifers as captured by StorAge Selection (SAS) functions generated via a machine learning-based model. We generate model inputs through stable water isotope-tracer based experiments conducted in both growth chamber and field site settings, examining how key environmental variables drive changes in SAS functions. We integrate the SAS framework, enhanced by our experimental data, into a hydrologic model, and assess whether model performance is improved. Finally, we utilize this model to simulate hydrological impact of hemlock loss under different climate scenarios.