ID:
publications-1894
Type:
Peer reviewed articles
Year:
2023
Authors:
Qi Tang; Hugo Delottier; Wolfgang Kurtz; Lars Nerger; Oliver S. Schilling; Philip Brunner
Title:
HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model
Venue/Journal:
eISSN:
DOI:
10.5194/gmd-2023-229
Research type:
Data Management & Analytics
Water System:
Water Distribution Networks
Technical Focus:
Abstract:
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.
Link with Projects:
858375
Link with Tools:
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