Improvements in Performance of the Hillslope Link Model in Iowa using a
Non-linear Representation of Natural and Artificially Drained Subsurface
Flows
Abstract
This evaluates the potential for a newly proposed non-linear subsurface
flux equation to improve the performance of the hydrological Hillslope
Link Model (HLM). The equation contains parameters that are functionally
related to the hillslope steepness and the presence of tile drainage. As
a result, the equation allows a better representation of hydrograph
recession curves, hydrograph timing, and total runoff volume. The
authors explore the new parameterization’s potential by comparing a set
of diagnostic and prognostic setups in HLM. In the diagnostic approach,
they configure 12 different scenarios with spatially uniform parameters
over the state of Iowa. In the prognostic case, they use information
from topographical maps and known locations of tile drainage to
distribute parameter values. To assess performance improvements, they
compare simulation results to streamflow observations during a 17-year
period (2002–2018) at 140 U.S. Geological Survey (USGS) gauging
stations. The operational setup of the HLM model used at the Iowa Flood
Center (IFC) serves as a benchmark to quantify overall model
improvement. In particular, the new equation provides better
representation of recession curves and the total streamflow volumes.
However, when comparing the diagnostic and prognostic setups, the
authors find discrepancies in the spatial distribution of hillslope
scale parameters. The results suggest that more work is required when
using maps of physical attributes to parameterize hydrological models.
The findings also demonstrate that the diagnostic approach is a useful
strategy to evaluate models and assess changes in their formulations.