How to construct recursive digital filters for baseflow separation

Abstract

Abstract:Recursive digital filtering of hydrographs is a baseflow separation method that can easily be automated and has been recommended for providing reproducible results. In the past, different formulations of the most simple filter type, the so-called one-parameter filter, have been proposed. In this paper, a theoretical framework is developed for filter algorithms that were constructed under the assumption that the outflow from an aquifer is linearly proportional to its storage. It is shown that these one-parameter filters describing an exponential baseflow recession are all special cases of a two-parameter filter whose equation is specified. Its parameters are the recession constant-which can be objectively determined by a recession analysis-and BFI max , the maximum value of the baseflow index that can be modelled by the algorithm. This introduces a subjective element into the baseflow calculation, since BFI max is not measurable. A preliminary analysis based on the results of conventional separation techniques shows that it might be possible to find typical BFI max values for classes of catchments that can be unequivocally distinguished by their hydrological and hydrogeological characteristics.

Applicability Assessment of Estimation Methods for Baseflow Recession Constants in Small Forest Catchments

“…The baseflow index in the forest catchment is generally in the range of 58 to 78% [28,34]. When the baseflow separation was conducted with the recession constants of CR, AR(1), and VK as the filter parameters, the range of BFI was 0.64 to 0.69, which is within the range of the preceding research.…”

“…In perennial streams and porous aquifers, as found in the GC and GD forest catchments, a BFI max value of 0.8 was suggested [28].…”

“…The baseflow was separated from the streamflow hydrograph with the recession constant. In order to separate the baseflow from the long-term streamflow data, with about 30 years of records, digital filtering, which separated the baseflow with an automated algorithm, was used [3,20,28]. In many digital filtering methods, the filter introduced by Eckhardt [28] was selected, as it describes forest catchment characteristics well.…”

Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrological and Hydraulic Models

“…In order to estimate the observed quickflow it is necessary to filter the base flow information from the streamflow. To this end, the equation proposed by Eckhardt (2005) is used, in a fashion similar to Corzo and Solomatine (2007), where such equation is employed for building an optimal committee of neural network models to estimate separately base-and excess flow.…”

HYDROLOGICAL PROPERTIES OF BRIBIN UNDERGROUND RIVER SYSTEM (Experience learned for Seropan River System Project)

“…The diffuse flow separation and the calculation of conduit flow proportion in this study is approached by automated base flow separation by digital filtering method (Eckhardt, 2005). The key of this method is to calculate the digital filtering in every cave based on the constant recession within the one-year hydrograph and the definition of baseflow indices (BFI) within karst aquifer, by formula:…”