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    Evaluation of Sub-Selection Methods for Assessing Climate Change Impacts on Low-Flow and Hydrological Drought Conditions


    Golian, Saeed and Murphy, Conor (2021) Evaluation of Sub-Selection Methods for Assessing Climate Change Impacts on Low-Flow and Hydrological Drought Conditions. Water Resources Management, 35 (1). pp. 113-133. ISSN 0920-4741

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    Official URL: https://doi.org/10.1007/s11269-020-02714-1


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    Abstract

    A challenge for climate impact studies is the identification of a sub-set of climate model projections from the many typically available. Sub-selection has potential benefits, including making large datasets more meaningful and uncovering underlying relationships. We examine the ability of seven sub-selection methods to capture low flow and drought characteristics simulated from a large ensemble of climate models for two catchments. Methods include Multi-Cluster Feature Selection (MCFS), Unsupervised Discriminative Features Selection (UDFS), Diversity-Induced Self-Representation (DISR), Laplacian score (L Score), Structure Preserving Unsupervised Feature Selection (SPUFS), Non-convex Regularized Self-Representation (NRSR) and Katsavounidis–Kuo–Zhang (KKZ). We find that sub-selection methods perform differently in capturing varying aspects of the parent ensemble, i.e. median, lower or upper bounds. They also vary in their effectiveness by catchment, flow metric and season, making it very difficult to identify a best sub-selection method for widespread application. Rather, researchers need to carefully judge sub-selection performance based on the aims of their study, the needs of adaptation decision making and flow metrics of interest, on a catchment by catchment basis

    Item Type: Article
    Additional Information: Cite as: Saeed Golian, Conor Murphy, Robert L. Wilby, Tom Matthews, Seán Donegan, Dáire Foran Quinn, Shaun Harrigan. (2022) Dynamical–statistical seasonal forecasts of winter and summer precipitation for the Island of Ireland. International Journal of Climatology 77. Crossref
    Keywords: Climate change; General circulation models (GCMs); Subs-selection; Uncertainty; Drough;
    Academic Unit: Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 15760
    Identification Number: https://doi.org/10.1007/s11269-020-02714-1
    Depositing User: Saeed Golian
    Date Deposited: 31 Mar 2022 11:09
    Journal or Publication Title: Water Resources Management
    Publisher: Taylor & Francis online
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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