Groundwater dependent ecosystems: Classification, identification techniques and threats

Derek Eamus, Baihua Fu*, Abraham E. Springer, Lawrence E. Stevens

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    58 Citations (Scopus)

    Abstract

    This chapter begins by briefly discussing the three major classes of groundwater dependent ecosystems (GDEs), namely: (I) GDEs that reside within groundwater (e.g. karsts; stygofauna); (II) GDEs requiring the surface expression of groundwater (e.g. springs; wetlands); and (III) GDEs dependent upon sub-surface availability of groundwater within the rooting depth of vegetation (e.g. woodlands; riparian forests). We then discuss a range of techniques available for identifying the location of GDEs in a landscape, with a primary focus of class III GDEs and a secondary focus of class II GDEs. These techniques include inferential methodologies, using hydrological, geochemical and geomorphological indicators, biotic assemblages, historical documentation, and remote sensing methodologies. Techniques available to quantify groundwater use by GDEs are briefly described, including application of simple modelling tools, remote sensing methods and complex modelling applications. This chapter also outlines the contemporary threats to the persistence of GDEs across the world. This involves a description of the “natural” hydrological attributes relevant to GDEs and theprocesses that lead to disturbances to natural hydrological attributes as a result of human activities (e.g. groundwater extraction). Two cases studies, (1) Class III: terrestrial vegetation and (2) Class II: springs, are discussed in relation to these issues.

    Original languageEnglish
    Title of host publicationIntegrated Groundwater Management
    Subtitle of host publicationConcepts, Approaches and Challenges
    PublisherSpringer International Publishing Switzerland
    Pages313-346
    Number of pages34
    ISBN (Electronic)9783319235769
    ISBN (Print)9783319235752
    DOIs
    Publication statusPublished - 1 Jan 2016

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