Woldemeskel et al. (2025) Assessment of JULES Land Surface Model Coupled With CaMa ‐Flood for an Operational Streamflow Forecasting Across Australia

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Hydrological Processes
• Year: 2025
• Date: 2025-11-27
• Authors: Fitsum Woldemeskel, Christoph Rüdiger, Dai Yamazaki, Siyuan Tian, Huqiang Zhang, Toby R. Marthews, Jiawei Hou, Wendy Sharples, Chun‐Hsu Su, Martin Best, Elisabetta Carrara
• DOI: 10.1002/hyp.70345

Research Groups

Not explicitly stated in the abstract, but the study involves research groups focused on hydrological modeling and operational forecasting in Australia, potentially collaborating with international climate modeling centers given the use of JULES and ERA5-Land.

Short Summary

This study implemented the Catchment-based Macro-scale Floodplain (CaMa-Flood) model across Australia and evaluated its performance when coupled with various land surface models (JULES, AWRA-L) and reanalysis datasets (BARRA-R2, ERA5-Land) for operational streamflow forecasting. It found that offline JULES and AWRA-L performed well but with regional biases, while reanalysis products largely underestimated runoff, and all models struggled in ephemeral catchments.

Objective

• To implement the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to simulate river hydrodynamics across Australia.
• To evaluate the performance of land surface models (JULES, AWRA-L) and reanalysis datasets (BARRA-R2, ERA5-Land) coupled with CaMa-Flood in simulating streamflow for an operational forecasting service.

Study Configuration

• Spatial Scale: Continental scale across Australia, with analyses performed against 452 topographically and hydro-climatically diverse catchments.
• Temporal Scale: Daily and monthly timescales.

Methodology and Data

• Models used: Catchment-based Macro-scale Floodplain (CaMa-Flood), JULES (Joint UK Land Environment Simulator), AWRA-L (Australian Water Resources Assessment Landscape model).
• Data sources: BARRA-R2 (reanalysis dataset), ERA5-Land (reanalysis dataset). Implied: Observed streamflow data for 452 catchments for evaluation.

Main Results

• Offline JULES and AWRA-L models showed very good results at both daily and monthly timescales across Australia.
• Offline JULES tended to overestimate runoff in central Australia.
• AWRA-L tended to overestimate runoff in Southeast Australia and Eastern Tasmania.
• BARRA-R2 and ERA5-Land reanalysis datasets showed large underestimations of runoff across the country.
• All models exhibited their lowest performances in ephemeral catchments.
• Differences in runoff generation processes and forcings were identified as contributors to the observed performance differences among models.
• A sensitivity analysis of CaMa-Flood topographic parameters indicated that the default configuration generally produces reliable simulations, though fine-tuning could achieve further improvements in specific locations.

Contributions

• First implementation and evaluation of the CaMa-Flood model for simulating river hydrodynamics across the Australian continent.
• Comprehensive assessment of the performance of multiple land surface models (JULES, AWRA-L) and reanalysis products (BARRA-R2, ERA5-Land) when coupled with CaMa-Flood for operational streamflow forecasting in Australia.
• Identification of specific regional biases and limitations of the evaluated models, particularly their reduced performance in challenging ephemeral catchments characteristic of Australia.
• Sensitivity analysis of CaMa-Flood's topographic parameters, providing insights for model configuration and potential improvements in the Australian context.

Funding

Not mentioned in the abstract.

Citation

@article{Woldemeskel2025Assessment,
  author = {Woldemeskel, Fitsum and Rüdiger, Christoph and Yamazaki, Dai and Tian, Siyuan and Zhang, Huqiang and Marthews, Toby R. and Hou, Jiawei and Sharples, Wendy and Su, Chun‐Hsu and Best, Martin and Carrara, Elisabetta},
  title = {Assessment of <scp>JULES</scp> Land Surface Model Coupled With <scp>CaMa</scp> ‐Flood for an Operational Streamflow Forecasting Across Australia},
  journal = {Hydrological Processes},
  year = {2025},
  doi = {10.1002/hyp.70345},
  url = {https://doi.org/10.1002/hyp.70345}
}