Research | Project | Data | Model | CREST | CREST-iMAP | CREST-VEC | SLIDE | Groups | Annual Profile

The coupled routing and excess storage (CREST)
Distributed Hydrological Model

Description

The Coupled Routing and Excess STorage model (CREST, jointly developed by the University of Oklahoma and NASA SERVIR) is a distributed hydrological model developed to simulate the spatial and temporal variation of land surface, and subsurface water fluxes and storages by cell-to-cell simulation. CREST’s distinguishing characteristics include: (1) distributed rainfall–runoff generation and cell-to-cell routing; (2) coupled runoff generation and routing via three feedback mechanisms; and (3) representation of sub-grid cell variability of soil moisture storage capacity and sub-grid cell routing (via linear reservoirs). The coupling between the runoff generation and routing mechanisms allows detailed and realistic treatment of hydrological variables such as soil moisture. Furthermore, the representation of soil moisture variability and routing processes at the sub-grid scale enables the CREST model to be readily scalable to multi-scale modelling research at local, regional and global scopes.

Executable File Download and User Manual

 

Version Windows Mac Linux Documents Example Contact
V3.0 Github Github Github User Manual Download Dr. Hong
V2.1
(Fortran)		 Download Download RedHat/CentOS
Ubuntu		 User Manual
Workshop		 Download Dr. Hong
V2.1
(MATLAB)		 CREST
Dependency		 CREST
Dependency		 CREST
Dependency		 User Manual Download Dr. Hong
Lumped
(MATLAB)		 Download Download Download User Manual Download Dr. Hong

Family Tree for CREST Related Models

 

EF5 v0.1c CREST v1.6c CREST v2.0 CRESLIDE CREST-iMap SLIDE

 

News

Version 3.0 (C++)

  1. Add a conceptual groundwater module (similar to National Water Model)
  2. Multi-model ensemble framework

Version 2.1 (Matlab)

  1. For the cell-to-cell routing scheme in CREST we proposed a fully distributed LRR method (FDLRR) to replace the existing quasi- distributed LRR (QDLRR) method.
  2. As a result, CREST v2.1 does not underestimate the discharge at arbitrary spatial and temporal resolutions.
  3. Calibration of CREST v2.1 is significantly easier than previous versions and the final NSCE is generally higher.
  4. Instead of generating discontinuous and bumpy discharge values along the river network, the FDLRR in CREST v2.1 produces a ?continuous and basically monotonic discharge?from upstream to downstream.

Version 2.0 (Fortran)

  1. A modular design framework to accommodate research, development and system enhancements (see Fig. 2(a) in Xue et al. (2013))
  2. Inclusion of the optimization scheme SCEUA to enable automatic calibration of the CREST model parameters (see Fig. 2(a) in Xue et al. (2013))
  3. All the parameters in CREST v1.6c were classified into three types: Initial Conditions, Physical Parameters ( to be derived by a-priori parameter method and/or be calibrated) and conceptual parameters (to be calibrated), some of the parameters were omitted (more details in user manual)
  4. Model implementation with options of either spatially uniform, semi-distributed, or distributed parameter values
  5. A multi-site cascading calibration framework was used to calibrate the model using multi-site gauge data from upstream to downstream (Users should manually prepare the data)
  6. Enhancement of the computation capability using matrix manipulation to make the model more efficient
  7. Project file was used to replace the original control file, and users can pass the project file to the CREST model instead of putting the crest model executable file and the control file in the same path. More than that, the statements in the project file can be in any order and more flexible
  8. Model can output all the variables in any time (spatial data) and any locations results (Time series)
  9. Some bugs were fixed

Version 1.6c (Fortran)

  1. Coupled Routing and Excess STorage (CREST) model was developed jointly by the University of Oklahoma and NASA SERVIR
  2. Distributed rainfall–runoff generation and cell-to-cell routing
  3. Coupled runoff generation and routing via three feedback mechanisms
  4. Representation of sub-grid cell variability of soil moisture storage capacity and sub-grid cell routing (via linear reservoirs)
  5. The coupling between the runoff generation and routing mechanisms allows detailed and realistic treatment of hydrological variables such as soil moisture

References

  1. Xinyi Shen, Yang Hong, Ke Zhang?and Zengchao Hao, “Refine a Distributed Linear Reservoir Routing Method to Improve Performance of the CREST Model”?Journal of Hydrologic Engineering. (Description of CREST v2.1, submitted in 2014). [PDF]
  2. Xue X., Y. Hong, A. S. Limaye, et al. (2013), Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins?[J]. Journal of Hydrology, 499(0): 91-99. doi: 10.1016/j.jhydrol.2013.06.042.[PDF] [WebLink]?(Introduction of CREST v2.0)
  3. Wang. J., Y. Hong, L. Li, J.J. Gourley, K. Yilmaz, S. I. Khan, F.S. Policelli, R.F. Adler, S. Habib, D. Irwn, S.A. Limaye, T. Korme, and L. Okello, 2011: The Coupled Routing and Excess STorage (CREST) distributed hydrological model. Hydrol. Sciences Journal, 56, 84-98. [PDF] [WebLink]?(Detailed Description of CREST v1.x)

Additional References

  1. Zhang, Y., Y. Hong, et al., 2014: Hydrometeorological Analysis and Remote Sensing of Extremes: Was the July 2012 Beijing Flood Event Detectable and Predictable by Global Satellite Observing and Global Weather Modeling Systems? Journal of Hydrometeorology, doi:10.1175/JHM-D-14-0048.1. [WebLink]
  2. Khan, S. I., P. Adhikari, Y. Hong, H. Vergara, T. Grout, R. F. Adler, F. Policelli, D. Irwin, T. Korme, and L. Okello, 2011: Observed and simulated hydroclimatology using distributed hydrologic model from in-situ and multi-satellite remote sensing datasets in Lake Victoria region in East Africa, Hydrol. Earth Syst. Sci. Discuss., 7, 4785-4816, doi:10.5194/hessd-7-4785. [PDF] [WebLink]
  3. Khan, S. I., Y. Hong, H. J. Vergara, et al. (2012), Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins, Geoscience and Remote Sensing Letters, IEEE, 9(4), 663-667. [PDF] [WebLink]
  4. Khan, S. I., Y. Hong, J. Wang, K.K. Yilmaz, J.J. Gourley, R.F. Adler, G.R. Brakenridge, F. Policelli, S. Habib, and D. Irwin, 2011: Satellite Remote Sensing and Hydrologic Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins, IEEE Transactions on Geosciences and Remote Sensing, 49(1), 85-95, Jan. 2011, doi: 10.1109/TGRS.2010.2057513. [PDF] [WebLink]
  5. Shen, X., Hong, Y., Zhang, K., Hao, Z., and Wang, D. (2014) “CREST v2. 1 Refined by a Distributed Linear Reservoir Routing Scheme.” Proc., AGU Fall Meeting, H33G-0918.

Links

NASA SERVIR GLOBAL (CREST Fortran (v2.0 and above) Applications in NASA) : https://www.servirglobal.net/default.aspx