Applying Climate Change Risk Management Tools to Integrate Streamflow Projections and Social Vulnerability

Saia, Sheila M.; Suttles, Kelly M.; Cutts, Bethany B.; Emanuel, R. E.; Martin, Katherine L.; Wear, David N.; Coulston, John W.; Vose, James M.

doi:10.1007/s10021-019-00387-5

Cited by 6 publications

(2 citation statements)

References 42 publications

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“…Ferreira and Ghimire, 2012; Di Baldassarre et al, 2013Baldassarre et al, , 2014Baldassarre et al, , 2016Wilhelmi and Morss, 2013;Braden et al, 2014;O'Connell and O'Donnell, 2014;Schumann and Nijssen, 2014;Viglione et al, 2014;Chang and Huang, 2015;Chen et al, 2016;Grames et al, 2016;Hazarika et al, 2016;Ward and Winter, 2016;Camargo, 2017;Ciullo et al, 2017;Mostert, 2017;Yu et al, 2017;Horn and Elagib, 2018;Robinne et al, 2018;Shelton et al, 2018;Tellman et al, 2018;Abadie et al, 2019;Abebe et al, 2019aAbebe et al, ,b, 2020Barendrecht et al, 2019;Bojórquez-Tapia et al, 2019;Caprario and Finotti, 2019;Haer et al, 2019;Viero et al, 2019;Devkota, 2020;Dziubanski et al, 2020;Haeffner and Hellman, 2020;Hossain et al, 2020;Huang et al, 2020;Lee and Kang, 2020;Michaelis et al, 2020;Ridolfi et al, 2020a,b;Saia et al, 2020;Sarmento Buarque et al, 2020;Sawada and Hanazaki, 2020;Song et al, 2020;Zhao and Mo, 2020;…”

Section: Water Components Used In Primary Studiesmentioning

confidence: 99%

A Systematic Review of Spatial-Temporal Scale Issues in Sociohydrology

et al. 2021

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Sociohydrology is a recent effort to integrate coupled human-water systems to understand the dynamics and co-evolution of the system in a holistic sense. However, due to the complexity and uncertainty involved in coupled human-water systems, the feedbacks and interactions are inherently difficult to model. Part of this complexity is due to the multi-scale nature across space and time at which different hydrologic and social processes occur and the varying scale at which data is available. This systematic review seeks to comprehensively collect those documents that conduct analysis within the sociohydrology framework to quantify the spatial-temporal scale(s) and the types of variables and datasets that were used. Overall, a majority of sociohydrology studies reviewed were primarily published in hydrological journals and contain more established hydrological, rather than social, models. The spatial extents varied by political and natural boundaries with the most common being cities and watersheds. Temporal extents also varied from event-based to millennial timescales where decadal and yearly were the most common. In addition to this, current limitations of sociohydrology research, notably the absence of an interdisciplinary unity, future directions, and implications for scholars doing sociohydrology are discussed.

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Section: Water Components Used In Primary Studiesmentioning

confidence: 99%

A Systematic Review of Spatial-Temporal Scale Issues in Sociohydrology

et al. 2021

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“…Thus, it is a relevant index for evaluating societal disparities in the siting of hazardous or polluting infrastructure. Geospatial indices of social vulnerability are already used to study societal disparities related to healthcare, flood risk, and other areas (e.g., Flanagan et al, 2018;Saia et al, 2020). For EJ evaluations of pipeline networks, such indices can shed light on a community's ability to cope with risks and threats associated with spills and leaks, explosions, structural failures, construction impacts, and other factors.…”

Section: Accepted Articlementioning

confidence: 99%

Natural Gas Gathering and Transmission Pipelines and Social Vulnerability in the United States

et al. 2021

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Midstream oil and gas infrastructure comprises vast networks of gathering and transmission pipelines that connect upstream extraction to downstream consumption. In the United States (US), public policies and corporate decisions have prompted a wave of proposals for new gathering and transmission pipelines in recent years, raising the question: Who bears the burdens associated with existing pipeline infrastructure in the US? With this in mind, we examined the density of natural gas gathering and transmission pipelines in the US together with county-level data on social vulnerability. For the 2,261 US counties containing natural gas pipelines, we found a positive correlation between county-level pipeline density and an index of social vulnerability. In general, counties with more socially vulnerable populations have significantly higher pipeline densities than counties with less socially vulnerable populations. In particular, counties in the top quartile of social vulnerability tend to have pipeline densities that are much higher than pipeline densities for counties in the bottom quartile of social vulnerability. The difference grows larger for counties at the upper extremes of pipeline density within each group.

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