|Title||Preserving heterogeneity and consistency in hydrological model inversions by adjusting pedotransfer functions|
|Publication Type||Conference Paper|
|Year of Publication||2015|
|Authors||Schaap M, Zhang Y, Xu C, Levi M, Rasmussen C, Larsen J|
|Conference Name||3rd Brazilian Soil Physics Meeting|
|Conference Location||Curitiban, Parana, Brazil|
|ARIS Log Number||321884|
Numerical modeling is the dominant method for quantifying water flow and the transport of dissolved constituents in surface soils as well as the deeper vadose zone. While the fundamental laws that govern the mechanics of the flow processes in terms of Richards' and convection-dispersion equations are relatively simple in principle, the practical implementation and parametrization of realistic “problems” remains difficult and fraught with many uncertainties. Besides defining appropriate boundary conditions (e.g., atmospheric forcing by rain and evapotranspiration as well as groundwater fluctuations), the practitioner must decide upon the dimensionality, space and time discretization and the internal structure of the problem (e.g., pedological structure and stratigraphy) and assign realistic hydraulic and chemical properties (water retention and unsaturated hydraulic conductivities and absorption coefficients) to all elements in the numerical grid. It is well-known that hydraulic properties are difficult to measure, making it virtually impossible to completely cover the variability within the simulated domain. Instead, inversion methods are often deployed which allows the determination of effective parameters by optimizing hydraulic parameters on observed time-series of moisture contents or matric potentials. Similar to laboratory measurements, field monitoring is expensive and problems with non-uniqueness of the inversion results often limits the level of detail that can be resolved in the subsurface. Without additional data or methods, lab measurements nor model inversions can completely characterize all the heterogeneity present at a site and the resulting model may therefore not be able to provide reliable flow estimates.