Abstract
Estimates of a low flow index in ungauged catchments calculated by a regional regression model and a regional hydrological model were compared for a study region southwestern Norway. The regression method was based on a relationship between the low flow index and an optimal set of catchment descriptors, established using stepwise linear regression for homogeneous subregions. Subregions were distinguished according to the season in which the lowest flow occurs, summer (May to October) or winter (November to April), and the average July temperature was found to be the best index for determining the low flow season for ungauged catchments. Catchment descriptors characterising the presence of lakes and bogs, in addition to catchment length and indicators of climatic conditions, were found to be important in the regression models. A cross-validation procedure was used to evaluate the predictive performance of the model in ungauged catchments. A gridded version of HBV, a daily rainfall-runoff model was also applied as a regional hydrological model and was calibrated using the average Nash–Sutcliffe coefficient for log-transformed streamflow as the calibration criterion. A comparison of the two methods in 21 independent catchments indicates that the regression method generally gives better estimates of Qc in ungauged catchments than does the HBV model, particularly in those catchments with the lowest Qc values.
Highlights
Information about low flows is required in water resources management, for example to estimate hydropower energy production, to design abstraction schemes for public water supply, fish farming and irrigation and to estimate dilution of effluents
Estimates of a low flow index in ungauged catchments calculated by a regional regression model and a regional hydrological model were compared for a study region southwestern Norway
The regression method was based on a relationship between the low flow index and an optimal set of catchment descriptors, established using stepwise linear regression for homogeneous subregions
Summary
Information about low flows is required in water resources management, for example to estimate hydropower energy production, to design abstraction schemes for public water supply, fish farming and irrigation and to estimate dilution of effluents. Low flows are often characterized by indices, i.e. single numbers describing an aspect of the low flow behaviour at a site or in a region. Often the low flow indices are needed for ungauged river basins or at sites where data are incomplete, and regionalisation techniques are essential in operational hydrology. The Norwegian Water Resources Act requires estimation of a specific low flow index, the “common low flow”, QC, if a hydropower plant is to be constructed. This index is often used as a starting point to set residual flow in the licensing procedure. It can be shown that for a sample of iid values, the rth order statistics pr is asymptotically normally distributed (David and Nagaraja, 2003): pr
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