Abstract
Land surface, hydrological, and groundwater modelling communities all have expertise in simulating the hydrological processes at play in the land system, but these communities have largely remained distinct with limited collaboration between disciplines. In order to address key societal questions regarding the future availability of water resources and the intensity of extreme events such as floods and droughts in a changing climate, these communities must build on the strengths of one another. The development of a common modelling infrastructure, a framework, can contribute to stimulating cross-fertilisation between them. By allowing (parts of) their existing models to be coupled together, improved land system models can be built to better understand and simulate the terrestrial hydrological cycle. This paper presents a Python implementation of such a framework named the Unified Framework for Hydrology (unifhy). The framework aims to provide the technical infrastructure required to couple models, taking into account the specific needs of a land system model. Its conceptual design and technical capabilities are outlined first, before its usage and useful characteristics are demonstrated through case studies. The limitations of the current framework and necessary future developments are finally presented as a road map for later versions and/or other implementations of the framework.
Highlights
This paper presents a Python implementation of such a framework named the Unified Framework for Hydrology
Land surface models have historically been developed as a lower boundary condition to atmospheric models which, to this day, partially explains the shortcomings in the representation of hydrological processes in land surface models
The resolution of the land system coupled with the atmosphere has typically been too coarse to adequately represent the spatial structures of the dominant hydrological processes, while the focus on vertical exchanges between the land and the atmosphere has limited the development of the critical lateral redistribution of 20 water on and below the ground
Summary
The Earth’s atmosphere and land surface are deeply interconnected systems. Given this, hydrological knowledge is as critical to 15 atmospheric scientists as meteorological knowledge is to hydrologists. Interconnected modelling components would provide the flexibility required in the spatial discretisation of the land system while preserving the existing coupling approaches with atmospheric models Such modularity would contribute to developing and comparing alternative representations of the real-world land system and assessing their impacts on hydrological and atmospheric predictions alike. The technologies used to combine such modelling components range from integrated coupling frameworks such as ESMF (Collins et al, 2005) or CPL7 (Craig et al, 2012), 45 where existing modelling components require code refactoring to comply with a set of organising and interfacing requirements, to couplers such as OASIS-MCT (Valcke, 2013; Craig et al, 2017), or YAC (Hanke et al, 2016), where existing modelling components require minimal additions to expose their variables to the coupler While these two families of frameworks vary in the level of intrusiveness into the existing code, they both offer access to essential functionalities such as I/O, parallelism, flexible spatial discretisation, remapping, and so on.
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