Abstract
Groundwater modules are critically important to the simulation of low
flows in land surface models (LSMs) and rainfall-runoff models. Here, we
develop a Groundwater for Ungauged Basins (GrUB) module that uses only
physically-based properties for which data are widely available, thus
allowing its application without the need for calibration. GrUB is
designed to be computationally simple and readily adaptable to a wide
variety of LSMs and rainfall-runoff models. We assess the performance of
GrUB in 84 US watersheds by incorporating it into HBV, a popular
rainfall-runoff model. We compare predictions of low flows by the native
(calibrated) HBV groundwater module with those by the (uncalibrated)
GrUB module and find that GrUB generates error metrics that are
equivalent to (or superior to) those generated by the native HBV
groundwater module. To assess whether predictions by GrUB are robust to
changes in the structure and parameterization of the overlying
hydrologic model, we run tests for two artificial scenarios: Slow
Recharge with rates of percolation below 0.1 mm/day, and Fast Recharge
with rates of percolation of up to 1000 mm/day. GrUB proves to be robust
to these extreme changes, with mean absolute error (MAE) of predictions
of low flows only increasing by an average of up to 19%, while average
MAE increases by up to 157% when the same tests are performed on HBV
without the GrUB module. We suggest GrUB as a potential tool for
improving predictions of low flows in LSMs as well as rainfall-runoff
models where calibration data are unavailable.