Towards scalable global hydrological modeling

Abstract:

Accurately modeling hydrology and groundwater at large, or even global, scales is challenging. When the elements of a model, such as the cells of a digital landscape, are independent, a model can process the elements efficiently in parallel. However, hydrological models do not have this feature: extended chains of causal dependency seemingly prevent efficient computation. More complex models incorporating standing surfacewater and groundwater only exacerbate this problem.

Here, I synthesize recent developments, showing how they collectively resolve many of the challenges to large-scale hydrological modeling and discuss challenges that have not yet been solved.

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