High-resolution parameter maps


All hydrological models are simplifications of a complex reality and therefore need to be calibrated to obtain satisfactory streamflow simulations. Here we present high-resolution (0.05°) optimized parameter maps for the conceptual hydrological model HBV covering the entire land surface including ungauged regions.

The maps were produced using a novel parameter regionalization approach that involves the optimization of transfer equations linking model parameters to climate and landscape characteristics. The optimization was performed in a fully spatially distributed fashion at high resolution, instead of at lumped catchment scale, using an unprecedented database of daily observed streamflow from 4229 small catchments worldwide.
The regionalized parameters resulted in a median Kling-Gupta Efficiency (KGE) improvement of +0.29 (relative to uncalibrated parameters) in 4229 fully independent validation catchments. Improvements were obtained for 88 % of the validation catchments. Substantial improvements were obtained even for validation catchments located far from the catchments used for optimization, underscoring the value of the derived parameters for poorly gauged regions. For more information, see the following open-access publication:


The latest version (0.8) of the parameter maps, including the HBV model code used to derive the maps, can be downloaded here. If the dataset forms a key component of your research, we kindly ask that you give us the opportunity to comment on your results prior to publication. The data and code are released under the CC BY-NC 4.0 license and thus may not be used for commercial purposes. By using the data in any publication you agree to cite the corresponding paper.


The following organizations are thanked for providing streamflow and/or catchment boundary data: the United States Geological Survey (USGS), the Global Runoff Data Centre (GRDC), the Brazilian Agencia Nacional de Aguas, EURO-FRIEND-Water, the European Commission Joint Research Centre (JRC), the Water Survey of Canada (WSC), the Australian Bureau of Meteorology (BoM), and the Chilean Center for Climate and Resilience Research (CR2, CONICYT/FONDAP/15110009).


Runoff projections from HBV with regionalized parameters are probably in most cases more reliable than those from HBV with unoptimized parameters. The following caveats should, however, be kept in mind. First, since the regionalized parameters were optimized to produce better runoff simulations, they do not necessarily represent hydrological processes more realistically. Secondly, the validity of the regionalized parameters, which were optimized using historic climate conditions, may be less under significantly different future climate conditions. See Vaze et al. (2010) and Fowler et al. (2020) for further discussion.

The ten sets of global parameter maps represent different cross-validation folds, meaning they were derived from slightly different (but overlapping) subsets of catchments. All ten sets of parameter maps are equally uncertain and therefore should produce equally “good” simulations. Ideally, all ten sets of parameter maps would be used in an ensemble modeling framework to obtain an ensemble of outputs, the spread of which provides an indication of the parameter uncertainty. See McIntyre et al. (2005) and Yang et al. (2011) for more discussion on ensemble modeling.

Interactions between model parameters and simulation results are generally highly complex and nonlinear. The outputs of a low-resolution model with resampled parameter maps will therefore likely significantly differ from the resampled outputs of a high-resolution model with 0.05° parameter maps. Thus, we do not recommend using the parameter maps at other spatial resolutions. See Beven (1995), Kling and Gupta (2009), and Freund et al. (2020) for further discussion.