The impact of hidden parameters and multiscale parameter regionalization on hydrologic fluxes in the 
land-surface model Noah-MP

abstract:

"Land surface models incorporate a large number of processes, described by physical, chemical and 
empirical equations. The process descriptions contain fixed, hard-coded numbers in the computer code, 
which are not identified as model parameters. Here we searched for hard-coded parameters in the 
computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the 
importance of the fixed values on restricting the model’s agility during parameter estimation. 
We performed a Sobol’ global sensitivity analysis of Noah-MP to variations of the standard and 
hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff 
as well as their component fluxes were evaluated. Noah-MP’s hydrologic output fluxes are sensitive to 
two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in 
the formulation of soil surface resistance for evaporation.

Moreover, these process descriptions are usually derived from point measurements but are scaled to much 
larger resolutions in applications that range from about 1 km in catchment hydrology to 100 km in 
climate modelling. A fundamental criterion for the physical consistency of land-surface simulations 
across scales is that a flux estimated over a given area is independent of the spatial model resolution 
(i.e., the flux-matching criterion). A promising approach to improve the flux-matching condition is the 
Multiscale Parameter Regionalization
(MPR) technique, which consists of two steps: first, it applies transfer functions directly to 
high-resolution data (such as 100 m soil maps) to derive high-resolution model parameter fields. 
Second, it upscales these high-resolution parameter fields to the model resolution. Overall, we 
improved the flux-matching criterion for subsurface runoff at scales ranging from 3 km to 48 km.