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  - Villarreyes, Carlos Andres Rivera
A1  - Baroni, Gabriele
A1  - Oswald, Sascha
T1  - Inverse modelling of cosmic-ray soil moisture for field-scale soil hydraulic parameters
JF  - European journal of soil science
N2  - We used inverse modelling techniques and soil moisture measured by the cosmic-ray neutron sensing (CRS) to estimate root-zone soil hydraulic properties at the field scale. A HYDRUS-1D model was developed for inverse modelling and calibrated with parameter estimation software (PEST) using a global optimizer. Integral CRS measurements recorded from a sunflower farm in Germany comprised the model input. Data were transformed to soil water storage to enable direct model calibration with a HYDRUS soil-water balance. Effective properties at the CRS scale were compared against local measurements and other inversely estimated soil properties from independent soil moisture profiles. Moreover, CRS-scale soil properties were tested on the basis of how field soil moisture (vertical distribution) and soil water storage were reproduced. This framework provided good estimates of effective soil properties at the CRS scale. Simulated soil moisture at different depths at the CRS scale agreed with field observations. Moreover, simulated soil water storage at the CRS scale compared well with calculations from point-scale profiles, despite their different support volumes. The CRS-scale soil properties estimated with the inverse model were within the range of variation of properties identified from all inverse simulations at the local scale. This study demonstrates the potential of CRS for inverse estimation of soil hydraulic properties.
Y1  - 2014
U6  - https://doi.org/10.1111/ejss.12162
SN  - 1351-0754
SN  - 1365-2389
VL  - 65
IS  - 6
SP  - 876
EP  - 886
PB  - Wiley-Blackwell
CY  - Hoboken
ER  -