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Gewählte Publikation:

Laaha, G., Blöschl, G. .
(2006): Seasonality indices for regionalising low flows
HYDROL PROCESS, 20, 3851-3878; ISSN 0885-6087 FullText FullText_BOKU

In this study we examine three seasonality indices for their potential in regionalizing low flows. The indices are seasonality histograms (SHs) that represent the monthly distribution of low flows, a cyclic seasonality index (SI) that represents the average timing of low flows within a year, and the seasonality ratio (SR), which is the ratio of summer and winter low flows. The rationale of examining these indices is the recognition that summer and winter low flows are subject to important differences in the underlying hydrological processes. We analyse specific low flow discharges q(95), i.e. the specific discharge that is exceeded on 95% of all days at a particular site. Data from 325 subcatchments in Austria, ranging in catchment area from 7 to 963 km(2), are used in the analysis. In a first step, three seasonality indices are compared. Their spatial patterns can be interpreted well on hydrological grounds. In a second step, the indices are used to classify the catchments into two, three, and eight regions based on different combinations of the indices. In a third step, the value of the seasonality indices for low flow regionalization is examined by comparing the cross-validation performance of multiple regressions between low flows and catchment characteristics. The regressions make use of the three seasonality-based classifications. The results indicate that grouping the study area into two regions and three regions and separate regressions in each region gives the best performance. A global regression model yields the lowest performance and a global regression model that uses different calibration coefficients in each of the eight regions only performs slightly better. This suggests that separate regression models in each of the regions are to be preferred over a global model in order to represent differences in the way catchment characteristics are related to low flows. Copyright (c) 2006 John Wiley & Sons, Ltd.
Autor*innen der BOKU Wien:
Laaha Gregor

Find related publications in this database (Keywords)
low flows
regional regression
cluster analysis
seasonality index
cross validation
prediction of ungauged basins

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