Probabilistic simulations and predictions of hydrological processes over North America

Abstract:

As part of the Global Water Futures program, an initiative is underway to improve probabilistic simulations and predictions of hydrological processes across North America. This presentation will summarize recent progress in this effort, focusing on recent work to: (1) develop a new probabilistic meteorological forcing dataset for North America; (2) develop model-agnostic workflows to configure hydrological and land models across large geographical domains; (3) develop a comprehensive model benchmarking system, including synthetic test cases to check the equations are implemented properly, process-based model evaluation to evaluate the fidelity of model simulations and identify model weaknesses, and benchmarks to quantify the information content in data and models; (4) improve the numerical implementation of land models; (5) improve continental-domain network routing models, including parallelization of hierarchal river networks, incorporation of lakes and reservoirs, and developing capabilities for multi-scale simulation; (6) advance capabilities for parameter estimation and data assimilation; and (7) understand the predictability of streamflow, including the elasticity of predictability, to understand the benefits that will arise from improving specific components of probabilistic streamflow forecasting systems, in order to guide science investments. This model development work is targeted toward water security assessments, applications in streamflow forecasting, and improving the representation of hydrologic processes in Earth System models.