Abstract
These papers (part I and part II) emphasize the need for sensitivity and uncertainty analyses. A number of techniques are applied, e.g. latin hypercube sampling, impact response surfaces and Sobol-analyses. Five examples are presented, four of them concerning the numerical model SWAP. The data generation and analysis is performed with standard R packages. Although the computations can be made on any computer, the most time-consuming examples in this paper have been run on a High Performance Computer Cluster. With the relatively simple Impact Response Surface technique it is shown that variation of the saturated hydraulic conductivity has far less impact than changing the moisture content at saturation. Analyses according to the Sobol-Jansen method show that when the soil physical relationships are described according to Damiano, then the parameter b has a very large influence on the results. If the well-known Mualem - Van Genuchten equations are applied, most variation can be explained by the parameter n.
Highlights
Climate change and a growing demand of water for agriculture and urban development cause an increasing pressure on fresh water resources
A global sensitivity analysis of an earlier version of SWAP has been presented by Wesseling et al (1997)
The objective of the research presented in this paper was threefold: (i) show the influence of the soil physical parameters on the output of unsaturated zone models; (ii) investigate the usability of standard R packages to perform sensitivity and uncertainty analyses on models and (iii) show the advantages of a High Performance Computer Cluster
Summary
Climate change and a growing demand of water for agriculture and urban development cause an increasing pressure on fresh water resources. A global sensitivity analysis of an earlier version of SWAP has been presented by Wesseling et al (1997) These authors concluded that knowledge of the boundary conditions was more important than knowledge of the soil parameters. The objective of the research presented in this paper was threefold: (i) show the influence of the soil physical parameters on the output of unsaturated zone models; (ii) investigate the usability of standard R packages to perform sensitivity and uncertainty analyses on models and (iii) show the advantages of a High Performance Computer Cluster. In the accompanying paper (part II) the results are presented and discussed
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