Abstract
Abstract. The two-parameter recursive digital filter method (Eckhardt) and the conductivity mass balance (CMB) method are two widely used baseflow separation methods favored by hydrologists. Some divergences in the application of these two methods have emerged in recent years. Some scholars believe that deviation of baseflow separation results of the two methods is due to uncertainty of the parameters of the Eckhardt method and that the Eckhardt method should be corrected by reference to the CMB method. However, other scholars attribute the deviation to the fact that they contain different transient water components. This study aimed to resolve this disagreement by analyzing the effectiveness of the CMB method for correcting the Eckhardt method through application of the methods to 26 basins in the United States by comparison of the biases between the generated daily baseflow series. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a “false” calibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The baseflow sequence generated by the Eckhardt method usually includes slow interflow and bank storage return flow, whereas that of the CMB method usually includes high-conductivity water flushed from swamps and depressions by rainfall, but not low-conductivity interflow and bank storage return flow. This difference results in obvious peak misalignment and periodic deviation between the baseflow sequences obtained by the two methods, thereby preventing calibration. However, multi-component separation of streamflow can be achieved through comparison. Future research should recognize the deviations between the separation results obtained by the different methods, identify the reasons for these differences, and explore the hydrological information contained therein.
Highlights
Streamflow usually contains components originating from different sources, such as surface runoff, interflow, groundwater runoff, bank storage return flow, and water flushed out from wetlands or depressions by rainfall (Cartwright et al, 2014; Schwartz, 2007; McCallum et al, 2010; Lin et al, 2007)
Yang et al.: Can the two-parameter recursive digital filter baseflow separation method temporal resolutions of these components is a prerequisite for accurately predicting hydrological processes and protecting the river ecosystem (Duncan, 2019)
The present study evaluated the effectiveness of calibrating the Eckhardt method against the conductivity mass balance (CMB) method for 26 basins in the United States by comparing biases between the daily baseflow sequences generated by the two methods and attempted to resolve the confusion resulting from the combined application of the two methods from a new perspective
Summary
Streamflow usually contains components originating from different sources, such as surface runoff, interflow, groundwater runoff, bank storage return flow, and water flushed out from wetlands or depressions by rainfall (Cartwright et al, 2014; Schwartz, 2007; McCallum et al, 2010; Lin et al, 2007). These components from different sources are usually characterized by different residence times and chemical and isotopic characteristics (Cartwright et al, 2018). Yang et al.: Can the two-parameter recursive digital filter baseflow separation method temporal resolutions of these components is a prerequisite for accurately predicting hydrological processes and protecting the river ecosystem (Duncan, 2019)
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