What is CREST?
A distributed hydrologic model designed to exploit 4-D remote-sensing data — deployable at global, regional, or basin scale. It fully couples runoff generation with cell-to-cell routing on a regular grid, simulating water and energy fluxes and storage.
17 parameters · 3 soil layers
Inside the model: coupled runoff & routing
Runoff generation (variable infiltration + 3 soil layers) is fully coupled with cell-to-cell routing — the defining idea of CREST since v1.0 (Wang & Hong et al., 2011).
Milestones & key publications
Click a milestone to see a key figure — then click the figure to open the paper ↗
First satellite-driven global runoff simulation framework
Hong et al. · Water Resour. Res.Near-real-time satellite rainfall for global flood & landslide hazard
Hong, Adler, Negri & Huffman · Nat. HazardsCoupled routing + excess storage; sub-grid soil-moisture variability
Wang, Hong et al. · Hydrol. Sci. J.Distributed parameters, SCE-UA auto-calibration, parallel computing
Xue et al. · J. HydrologyCascading flood–landslide hazard forecasting (CREST + SLIDE)
He et al. 2016; Zhang et al. · HESSRefined distributed linear-reservoir routing scheme
Shen et al. · J. Hydrol. Eng. ↗Operational ensemble flash-flood system for the U.S. (NOAA/NSSL)
Gourley et al. · BAMSFully coupled hydrologic–hydraulic 2-D inundation mapping
Chen et al. · J. Hydrometeorol.Vector-based routing (MizuRoute) + lake module; continental scale
Li et al. · Geosci. Model Dev.Groundwater module; CONUS-wide calibration & validation
Chen et al. · J. HydrologyLLM agent to operate & auto-calibrate CREST in plain language
Yan et al. · arXivLake module + elevation-based temperature resampling
HyDROS Lab · hydro.ou.eduOne core, many applications
Operational flash-flood early warning for the U.S. National Weather Service (NOAA/NSSL).
Gourley et al. 2017 · Flamig et al. 2020Cascading flood-and-landslide hazard forecasting (CREST + SLIDE slope stability).
He et al. 2016 · Zhang et al. 2016Fully coupled hydrologic–hydraulic 2-D inundation mapping & prediction.
Li et al. 2021 · Chen et al. 2021/2022Vector routing + lakes for efficient continental-to-global simulation.
Li et al. 2022, GMDGroundwater module with CONUS-wide calibration & validation.
Chen et al. 2023, J. Hydrol.LLM agent — operate & auto-calibrate CREST in plain language.
Yan et al. 2025/2026Future opportunities
Real-time coupling of physical models with multi-source observations.
Explainable, physics-constrained ML hydrology & the CREST-AI agent.
Robust prediction where no streamflow records exist.
Ensemble, uncertainty-aware flood forecasts.
Seamless atmosphere-to-streamflow prediction.
Community datasets & reproducible evaluation.
Thank you
HyDROS Lab — Hydrometeorology & Remote Sensing Laboratory
Selected key references
- Wang, Hong et al. (2011). The Coupled Routing and Excess Storage (CREST) distributed hydrological model. Hydrological Sciences Journal 56, 84–98.
- Xue et al. (2013). TRMM-based evaluation over the Wangchu Basin (CREST v2.0). J. Hydrology 499, 91–99.
- Shen et al. (2017). Refining a distributed linear-reservoir routing method for CREST (v2.1). J. Hydrol. Eng. 22.
- He et al. (2016) / Zhang et al. (2016). Coupled flood–landslide forecasting (iCRESLIDE / iCRESTRIGRS). J. Hydrology / HESS.
- Gourley et al. (2017). The FLASH Project (EF5). BAMS 98, 361–372.
- Li et al. (2021). CREST-iMAP v1.0. Environ. Modelling & Software 141, 105051.
- Li et al. (2022). CREST-VEC. Geosci. Model Dev. 15, 6181–6196.
- Chen et al. (2023). CONUS-wide calibration for CREST v3.0. J. Hydrology 626, 130333.
- Yan et al. (2025). AQUAH: Automatic Quantification and Unified Agent in Hydrology. arXiv:2508.02936.