Journal Article

FZJ-2022-02909

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Assimilation of Groundwater Level and Soil Moisture Data in an Integrated Land Surface‐Subsurface Model for Southwestern Germany

Hung, C. P. (Corresponding author)FZJ* ; Schalge, B. ; Baroni, G. ; Vereecken, H.FZJ* ; Hendricks Franssen, H.-J.FZJ*

2022
Wiley [New York]

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Please use a persistent id in citations: http://hdl.handle.net/2128/31640  doi:10.1029/2021WR031549

Abstract: Integrated terrestrial system models predict the coupled water, energy and biogeochemical cycles. Simulations with these models are affected by uncertainties of model parameters, initial and boundary conditions, atmospheric forcings and the biophysical processes. Data assimilation (DA) can quantify and reduce the uncertainty. This has been tested intensively for single compartment models, but far less for integrated models with multiple compartments. We constructed a virtual reality (VR) with a coupled land surface-subsurface model under the Terrestrial Systems Modeling Platform, which mimics the Neckar catchment in southern Germany. Soil moisture and groundwater level (GWL) data extracted from the simulated VR are used as measurements to be assimilated with state-only/state-hydraulic parameter estimation. Soil moisture DA improves soil moisture characterization in the vertical profile and the neighboring grid cells, with a 40 ∼ 60% reduction of root mean square error (RMSE) over the observation points. In spite of a small ensemble size of 64 members, assimilating soil moisture data improved saturated hydraulic conductivity estimation around the measurement locations. The characterization of evapotranspiration and river discharge only show limited improvements (1% at observation points and less than 0.1% in RMSE at 3 selected gauge locations respectively). GWL DA not only improves the GWL characterization (76 ∼ 88% RMSE reduction at observation locations) but also soil moisture for some cases. In addition, a clear improvement in GWL characterization is observed up to 8 km from the observations, and updating the model states of the saturated zone only instead of the complete domain gives better performance.

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217) (POF4-217)
2. DFG project 243358811 - FOR 2131: Datenassimilation in terrestrischen Systemen (243358811)

Appears in the scientific report 2022

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; Current Contents - Engineering, Computing and Technology ; DEAL Wiley ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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