2.4 Digital filtering method for separating base flow
The digital filtering method is based on signal analysis and processing
technology, whose principle is to decompose daily flow data into high-
and low-frequency signals. It is believed that surface flow is a
high-frequency signal while the base flow is a low-frequency signal,
thus fast flow and base flow can be separated accordingly (Nathan and
McMahon, 1990). In this paper, Lyne Hollick filtering method (Eqs. and )
was adopted to separate.
where is the surface flow (fast flow) at time t , while and is the
total flow and base flow at the current time t respectively. is
the filtering parameter, with the value of 0.925 (Chapman, 1991).
By applying the baseflow separation methods to daily streamflow, daily
streamflow are schematically partitioned into separate fast flow and slow
flow time series, as shown in Figure 1 (a). Processes
controlling fast flows are surface runoff generation and routing. The
variability of fast flows is governed by stochastic characteristics of
the sequences of storm events experienced by the catchment and the
properties of surface soils and topography. Processes controlling slow
flow include subsurface flow and groundwater discharge. The variability of
slow flows strongly reflects climate seasonality and the underlying
geology of the aquifer system. In this paper, the total flow, fast flow
and slow flow series were normalized with the value of average daily
total flow, average daily fast flow and average daily slow flow
respectively. In addition, a normalized time series (i.e. daily flow
divided by long-term average daily flow) was used to construct the
empirical duration curve: TFDC, FFDC and SFDC (Yokoo & Sivapalan,
2011), as demonstrated in Figure 1 (b).