Preprints
https://doi.org/10.5194/gmd-2023-229
https://doi.org/10.5194/gmd-2023-229
Submitted as: development and technical paper
 | 
07 Dec 2023
Submitted as: development and technical paper |  | 07 Dec 2023
Status: this preprint is currently under review for the journal GMD.

HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model

Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner

Abstract. This article describes a modular ensemble-based data assimilation (DA) system, which is developed for an integrated surface-subsurface hydrological model. The software environment for DA is the Parallel Data Assimilation Framework (PDAF), which provides various assimilation algorithms like the ensemble Kalman filters, nonlinear filters, 3D-Var, and combinations among them. The integrated surface-subsurface hydrological model is HydroGeoSphere (HGS), a physically based modelling software for the simulation of surface and variably saturated subsurface flow, as well as, heat and mass transport. The coupling and capabilities of the modular DA system are described and demonstrated using an idealized model of a geologically heterogeneous alluvial river-aquifer system with drinking water production via riverbank filtration. To demonstrate its modularity and adaptability, both single- and multivariate assimilation of hydraulic head and soil moisture observations are demonstrated in combination with individual and joint updating of multiple simulated states (i.e., hydraulic heads and water saturation) and model parameters (i.e., hydraulic conductivity). The new DA system marks an important step towards achieving operational real-time management of coupled surface water-groundwater systems such as riverbank filtration wellfields based on integrated surface-subsurface hydrological models and data assimilation.

Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2023-229', Anonymous Referee #1, 09 Jan 2024
  • RC2: 'Comment on gmd-2023-229', Anonymous Referee #2, 21 Jan 2024
  • RC3: 'Comment on gmd-2023-229', Anonymous Referee #3, 31 Jan 2024
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner

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Short summary
We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model, its large selection of different assimilation algorithms and its modularity with respect to the combination of different types of observations, states and parameters.