Land surface hydrological modeling: do we really need complex model formulations?

Land Surface Models (LSM) grounded on physically-based mathematical models for energy and water balance can be characterized by various levels of complexity, especially when they integrate numerous processes. Diverse mathematical models (i.e., sub-models) can sometimes be formulated for some processes, due to different assumptions made during the system conceptualization stage. Therefore, running LSMs require (i) selection of a set of processes and related mathematical formulations that will be used and (ii) estimation of the corresponding parameters. A convenient way to guide model (and parameter) choice is to rely on global sensitivity analysis. In this work, we analyze sensitivity of 3 common hydrological outputs (evaporation, transpiration, and groundwater recharge fluxes) to models and parameters involved in typical LSMs. The global sensitivity analysis relies on random (Monte Carlo) sampling of values of parameters associated with each of the different formulations considered for the sub-models embedded in the LSM. This enables us to quantify the relative importance of process formulation and ensuing parameters. Three diverse indices based on (i) the whole (sample) probability density function (pdf) of the model output (Borgonovo et al., 2011) and (ii) the first and second moment of the pdf (corresponding to the moment-based sensitivity indices introduced by Dell’Oca et al. (2017)) are used. The joint use of these metrics is exemplified upon relying on realistic field conditions (in terms of, e.g., climate, vegetation, and soil type) associated with two watersheds in the Vosges region (France). Results show that sensitivity analysis plays a crucial role in identifying sub-models and parameters that contribute significantly to the uncertainty of model outputs. It is found that the main characteristics of the soil comprising the litter layer and root zone play an important role in the evaluation of the evaporation and groundwater recharge fluxes. As such, our results strengthen the need for targeted studies on the characterization of flow in these layers.

 

Borgonovo et al., https://doi.org/10.1111/j.1539-6924.2010.01519.x, 2011.

Dell’Oca et al., https://doi.org/10.5194/hess-21-6219-2017.