Abstract
Rivers in the Mediterranean region often exhibit an intermittent character. An understanding and classification of the flow regimes of these rivers is needed, since flow patterns control both physicochemical and biological processes. This paper reports an attempt to classify flow regimes in Mediterranean rivers based on hydrological variables extracted from discharge time series. Long-term discharge records from 60 rivers within the Mediterranean region were analysed in order to classify the streams into different flow regime groups. Hydrological
indices (HIs) were derived for each stream and principal component analysis (PCA) then applied to these indices to identify subsets of HIs describing the major sources of variations, whilst simultaneously minimising redundancy. PCA was performed for two groups of streams (perennial and temporary) and for all streams combined. The results show that whereas perennial streams are mainly described by high flow indices, temporary streams are described by duration, variability and predictability indices. Agglomerative cluster analysis based on hydrological indices identified six groups of rivers classified according to differences in intermittency and variability. A methodology allowing such a classification for ungauged catchments was also tested. Broad-scale catchment characteristics based on digital elevation, climate, soil and land-use data were derived for each long-term station where these data were available. By using stepwise multiple regression analysis, statistically significant relationships were fitted linking the three selected hydrological variables (mean annual number of zero flow days, predictability and flashiness) to the catchment characteristics. The method provides a means of simplifying the complexity of river systems and is thus useful for river basin management.
indices (HIs) were derived for each stream and principal component analysis (PCA) then applied to these indices to identify subsets of HIs describing the major sources of variations, whilst simultaneously minimising redundancy. PCA was performed for two groups of streams (perennial and temporary) and for all streams combined. The results show that whereas perennial streams are mainly described by high flow indices, temporary streams are described by duration, variability and predictability indices. Agglomerative cluster analysis based on hydrological indices identified six groups of rivers classified according to differences in intermittency and variability. A methodology allowing such a classification for ungauged catchments was also tested. Broad-scale catchment characteristics based on digital elevation, climate, soil and land-use data were derived for each long-term station where these data were available. By using stepwise multiple regression analysis, statistically significant relationships were fitted linking the three selected hydrological variables (mean annual number of zero flow days, predictability and flashiness) to the catchment characteristics. The method provides a means of simplifying the complexity of river systems and is thus useful for river basin management.
Original language | English |
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Pages (from-to) | 4666-4682 |
Journal | Hydrological Processes |
Volume | 29 |
Issue number | 22 |
Early online date | 10 Jun 2015 |
DOIs | |
Publication status | Published - 30 Oct 2015 |
Keywords
- Hydrology