TY  - JOUR
A1  - Baroni, Gabriele
A1  - Tarantola, S.
T1  - A general probabilistic framework for uncertainty and global sensitivity analysis of deterministic models: A hydrological case study
JF  - Environmental modelling & software with environment data news
N2  - The present study proposes a General Probabilistic Framework (GPF) for uncertainty and global sensitivity analysis of deterministic models in which, in addition to scalar inputs, non-scalar and correlated inputs can be considered as well. The analysis is conducted with the variance-based approach of Sobol/Saltelli where first and total sensitivity indices are estimated. The results of the framework can be used in a loop for model improvement, parameter estimation or model simplification. The framework is applied to SWAP, a 113 hydrological model for the transport of water, solutes and heat in unsaturated and saturated soils. The sources of uncertainty are grouped in five main classes: model structure (soil discretization), input (weather data), time-varying (crop) parameters, scalar parameters (soil properties) and observations (measured soil moisture). For each source of uncertainty, different realizations are created based on direct monitoring activities. Uncertainty of evapotranspiration, soil moisture in the root zone and bottom fluxes below the root zone are considered in the analysis. The results show that the sources of uncertainty are different for each output considered and it is necessary to consider multiple output variables for a proper assessment of the model. Improvements on the performance of the model can be achieved reducing the uncertainty in the observations, in the soil parameters and in the weather data. Overall, the study shows the capability of the GPF to quantify the relative contribution of the different sources of uncertainty and to identify the priorities required to improve the performance of the model. The proposed framework can be extended to a wide variety of modelling applications, also when direct measurements of model output are not available.
KW  - Global sensitivity analysis
KW  - Non-scalar input factors
KW  - Hydrological model
KW  - Multi-variables
Y1  - 2014
U6  - https://doi.org/10.1016/j.envsoft.2013.09.022
SN  - 1364-8152
SN  - 1873-6726
VL  - 51
SP  - 26
EP  - 34
PB  - Elsevier
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Baroni, Gabriele
A1  - Schalge, Bernd
A1  - Rakovec, Oldrich
A1  - Kumar, Rohini
A1  - Schüler, Lennart
A1  - Samaniego, Luis
A1  - Simmer, Clemens
A1  - Attinger, Sabine
T1  - A Comprehensive Distributed Hydrological Modeling Intercomparison to Support Process Representation and Data Collection Strategies
JF  - Water resources research
N2  - The improvement of process representations in hydrological models is often only driven by the modelers' knowledge and data availability. We present a comprehensive comparison between two hydrological models of different complexity that is developed to support (1) the understanding of the differences between model structures and (2) the identification of the observations needed for model assessment and improvement. The comparison is conducted on both space and time and by aggregating the outputs at different spatiotemporal scales. In the present study, mHM, a process‐based hydrological model, and ParFlow‐CLM, an integrated subsurface‐surface hydrological model, are used. The models are applied in a mesoscale catchment in Germany. Both models agree in the simulated river discharge at the outlet and the surface soil moisture dynamics, lending their supports for some model applications (drought monitoring). Different model sensitivities are, however, found when comparing evapotranspiration and soil moisture at different soil depths. The analysis supports the need of observations within the catchment for model assessment, but it indicates that different strategies should be considered for the different variables. Evapotranspiration measurements are needed at daily resolution across several locations, while highly resolved spatially distributed observations with lower temporal frequency are required for soil moisture. Finally, the results show the impact of the shallow groundwater system simulated by ParFlow‐CLM and the need to account for the related soil moisture redistribution. Our comparison strategy can be applied to other models types and environmental conditions to strengthen the dialog between modelers and experimentalists for improving process representations in Earth system models.
KW  - hydrological models
KW  - assessments
KW  - monitoring strategies
KW  - improvements
Y1  - 2019
U6  - https://doi.org/10.1029/2018WR023941
SN  - 0043-1397
SN  - 1944-7973
VL  - 55
IS  - 2
SP  - 990
EP  - 1010
PB  - American Geophysical Union
CY  - Washington
ER  -