March 7, 2024
Research Highlight

A Comprehensive Calibration Procedure for Earth System Model Water Cycle

Disentangling the hydrological and hydraulic controls of streamflow variability over the world’s largest wetland in a fully coupled Earth system model

Photo of a seashore

Researchers found that subsurface runoff is the most important factor for streamflow variability, while floodplain storage effect and main-channel roughness have significant impacts on streamflow variability through the river-routing process.

The Science

Current streamflow simulations in Earth system models are faced with considerable uncertainties, necessitating parameter calibration to constrain the results. Although both hydrological and hydrodynamic processes play crucial roles in influencing streamflow variability, previous studies focus on calibrating only one process to improve streamflow simulation. However, in this study, researchers found that calibrating only one process resulted in unrealistic parameter values and poorly constrained model sensitivity to climate change and significant biases in other components in the water cycle. To address this issue, researchers proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydrodynamic processes on streamflow.

The Impact

Streamflow is a crucial freshwater resource with profound significance for humanity, yet it is susceptible to the impacts of climate change. Earth system models (ESMs) serve as valuable tools for projecting changes in streamflow under warmer climate conditions. These projections, when accurate, empower policymakers to make informed adaptations. In this study, researchers introduced a robust calibration procedure designed to enhance the performance of ESMs in simulating streamflow. This calibration process contributes to more reliable projections, instilling a higher level of confidence in the model's ability to capture the dynamics of streamflow under changing climatic conditions.

Summary

Streamflow variability plays a crucial role in shaping the dynamics and sustainability of Earth's ecosystems, which can be simulated and projected by ESMs. However, the simulation of streamflow is subject to considerable uncertainties, primarily arising from two related processes: runoff generation (hydrological process) and river routing (hydraulic process). While both processes have impacts on streamflow variability, previous studies only calibrated one of the two processes to reduce biases. Calibration focusing only on one process can result in unrealistic parameter values to compensate for the bias resulting from the other processthus, other water-related variables remain poorly simulated. In this study, researchers performed several experiments with the Energy Exascale Earth System Model (E3SM) over the Pantanal region of South America to disentangle the hydrological and hydraulic controls of streamflow variability. Our results show that the generation of subsurface runoff is the most important factor for streamflow variability contributed by the runoff generation process. In addition, the floodplain storage effect and main-channel roughness have significant impacts on streamflow variability through the river-routing process. Researchers further propose a two-step procedure to robustly calibrate the two processes together, which may be adopted by ESM developers to improve modeling of streamflow.

Contact

Funding

  • This work was supported by the Earth System Model Development program area of the U.S. Department of Energy, Office of Science, Biological and Environmental Research program as part of the multi-program, collaborative Integrated Coastal Modeling project.
  • Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Biological and Environmental Research program at Pacific Northwest National Laboratory.

Published: March 7, 2024

Xu, D., et al: “Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region,” Geoscientific Model Development, 17, 1197–1215, [doi.org/10.5194/gmd-17-1197-2024, 2024]