Accounting for Non-Represented Heterogeneity in Soil Water Flow by Estimating Miller Scaling Fields with Ensemble Kalman Filter

Monday, 14 December 2015
Poster Hall (Moscone South)
Hannes Bauser1,2, Stefan Jaumann1,2 and Kurt Roth3, (1)University Heidelberg, Heidelberg, Germany, (2)HGS MathComp, Heidelberg, Germany, (3)University of Heidelberg, Heidelberg, Germany
The Ensemble Kalman Filter (EnKF) is a widely used data assimilation method in soil hydrology to estimate states and parameters, incorporating uncertainties in measurements and all model components.
Of these components not only states and parameters, but also the representation of small scale heterogeneities of different soil layers suffers from large uncertainties. This is particularly severe when measuring soil water content, which reflects the soil’s local texture and is typically discontinuous across heterogeneity boundaries. To address this challenge we enhance the EnKF to simultaneously also estimate a Miller scaling field for each soil layer.
The enhanced EnKF is tested with a one-dimensional water content data set based on time domain reflectometry (TDR) measurements and leads to an improved consistency of model and measurements.