Enhanced Baseflow Separation in Rural Catchments: Event-Specific
Calibration of Recursive Digital Filters with Tracer-Derived Data
Abstract
This study presents a comprehensive analysis of baseflow separation
techniques within a small rural catchment, focusing on the calibration
and application of three Recursive Digital Filters (RDFs): the Eckhardt,
Lyne and Hollick (LH), and Chapman and Maxwell (CM) filters. The
research aimed to refine baseflow estimation methods by calibrating the
BFImax and Beta parameters of the
Eckhardt’s and LH filters, respectively, using dissolved silica
concentration data to derive reference baseflow. A novel event-based
calibration approach was introduced, categorizing rainfall-runoff events
by their magnitudes to optimize filter parameters accordingly. The
findings reveal that the calibrated Eckhardt’s filter, incorporating
event-specific parameter values, provides the most accurate baseflow
estimations, closely aligning with observed data across various
performance metrics. The event-based calibration demonstrated
significant improvements in baseflow prediction accuracy, particularly
for the Eckhardt’s and LH filters, compared to the general calibration
approach. The study confirms the dynamic nature of the
BFImax and Beta parameters, which vary
with event magnitude, underscoring the importance of tailored
calibration strategies for precise baseflow separation. The CM filter,
while offering plausible baseflow hydrograph shapes and peak timings,
was limited by its lack of adjustable parameters, leading to consistent
underestimation of baseflow volumes. In contrast, the adjustable
parameters of the Eckhardt’s and LH models enabled a more accurate
representation of baseflow dynamics, particularly when calibrated for
specific event magnitudes. This research confirms the superior efficacy
of the Eckhardt’s filter in baseflow separation for small rural
catchments, advocating for its use with event-based calibration when
tracer data is available. Overall, the findings contribute valuable
insights into baseflow modeling, offering improved methodologies for
hydrologists and environmental scientists to enhance water resource
management and conservation strategies.