A Quantitative Framework to Derive Robust Characterization of Hydrological Gradients |
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Authors: | T. J. Brummer A. E. Byrom J. J. Sullivan P. E. Hulme |
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Affiliation: | 1. Bioprotection Research Centre, Lincoln University, Lincoln, New Zealand;2. Landcare Research, Lincoln, New Zealand;3. Lincoln University Agriculture and Life Sciences, Lincoln, New Zealand |
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Abstract: | If ecological management of river ecosystems is to keep pace with increasing pressure to abstract, divert and dam, we must develop general flow–ecology relationships to predict the impacts of these hydrologic alterations. Regional flow gradient analyses are a promising tool to quickly reveal these functional relationships, but there are considerable uncertainties in this method because of variability in the historical extent of flow data across different rivers, combined with multiple indices characterizing the ecological attributes of flow regimes. In response, we outline an objective framework for analysing spatial hydrologic gradients that addresses three major sources of uncertainty: robust estimation of flow indices, the potential for temporal trends to confound spatial variation in flow regimes and the statistical robustness to detect underlying hydrological gradients. The utility of our framework was examined in relation to flow regimes across multiple braided river catchments in Canterbury, New Zealand. We found that a subset of flow indices could be robustly estimated using only 10 years of flow data, although indices that captured flow ‘timing’ required longer time series. Temporal trends were unlikely to confound conclusions from a spatial hydrologic gradient analysis, and there were three statistically supported hydrologic gradients related to flow magnitude, flow variability and low flow events. The widespread application of robust spatial flow gradient analyses has the potential to further our understanding of how altered flow regimes affect the ecology of freshwater and riparian ecosystems, thereby providing the evidence base to inform river management. Copyright © 2016 John Wiley & Sons, Ltd. |
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Keywords: | ecohydrology uncertainty flow regime hydrologic alteration time series factor analysis IHA ELOHA |
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