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Publication - Dr Ross Woods

    A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data

    Citation

    Knoben, WJ, Woods, RA & Freer, JE, 2018, ‘A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data’. Water Resources Research, vol 54., pp. 5088-5109

    Abstract

    Classification is essential in the study of natural systems, yet hydrology has no formal way to structure the climatic forcing that underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might need. This work presents a hydrologically informed way to quantify global climates, explicitly addressing the shortcomings in earlier climate classifications. In this work, causal factors (climate) and hydrologic response (streamflow) are separated, meaning that our classification scheme is based only on climatic information and can be evaluated with independent streamflow data. Using gridded global climate data, we calculate three dimensionless indices per grid cell, describing annual aridity, aridity seasonality, and precipitation-as-snow. We use these indices to create several climate groups and define the membership degree of 1,103 catchments to each of the climate groups, based on each catchment's climate. Streamflow patterns within each group tend to be similar, and tend to be different between groups. Visual comparison of flow regimes and Wilcoxon two-sample statistical tests on 16 streamflow signatures show that this index-based approach is more effective than the often-used Köppen-Geiger classification for grouping hydrologically similar catchments. Climate forcing exerts a strong control on typical hydrologic response and we show that at the global scale both change gradually in space. We argue that hydrologists should consider the hydroclimate as a continuous spectrum defined by the three climate indices, on which all catchments are positioned and show examples of this in a regionalization context.

    Full details in the University publications repository