1 / 24

Parallel Computation of River Basin Hydrologic Response Using DHM

Parallel Computation of River Basin Hydrologic Response Using DHM. Reports Environmental Hydrology Team: NCSA Alliance All-Hands meeting May 23-25, 2001 Urbana, Illinois Baxter E.Vieux Daniel Weber Fekadu G. Moreda Henry Neeman Zhengtao Cui Contact: bvieux@ou.edu www.coe.ou.edu/emgis.

grant
Download Presentation

Parallel Computation of River Basin Hydrologic Response Using DHM

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Parallel Computation of River Basin Hydrologic Response Using DHM Reports Environmental Hydrology Team: NCSA Alliance All-Hands meeting May 23-25, 2001 Urbana, Illinois Baxter E.Vieux Daniel Weber Fekadu G. Moreda Henry Neeman Zhengtao Cui Contact: bvieux@ou.edu www.coe.ou.edu/emgis University of Oklahoma, Norman, Oklahoma

  2. Overview • Objectives • The Distributed Hydrologic Model • Preparing the existing model for parallel computing • Parallelization • Time of computation • Coupling the model with ARPS

  3. Objectives • Near term • Couple atmospheric model and surface runoff model for flood forecasting • Improve computational efficiency of surface runoff model • Long term • Integrate model into EH system

  4. Runoff Simulation Watershed Runoff Simulation Finite Elements Connectivity Grid Cell Resolution Rainfall Runon Runon Infiltration Runoff • * Rainfall excess • at each cell • - Soil infiltration rate • - Rainfall rate • - Runon from upslope Flow Characteristics Channel Characteristics - Cross-Section Geometry - Slope - Hydraulic Roughness Stream Overland Direction

  5. Digital Watershed

  6. Arc.water.fea Forecast Location

  7. Model components • Time static (Preprocessing) • Importing DEM • Watershed delineation • Setup specific experiment • Time Dynamic • Extraction • Simulation • Routing

  8. Preparing The Model for Parallel Computing • Optimizing the existing code (rewrite in C++) • Isolate the I/O operations

  9. Parallelization • MPI • Load balancing algorithm

  10. Load Balancing Algorithm Processes (Descending loads) Basin Proc Processor assigned in an alternate fashion

  11. Illinois River Basin, In Okllahoma and Arkansas Illionois river at Tahek

  12. Computation based on Subbasins

  13. Load Balancing

  14. Distribution of loads (16 Processors)

  15. Distribution of load (4 Processors)

  16. Time of computation 9 h 5 h 3 h 1h:30min 01:00:00

  17. Prototype Operational Domain • Illinois River Basin • Area: 2400km2 • Resolution 30m x 30m • #Subbasins 370 • 7 days of monitoring • Timestep = 2sec Prediction: better load balancing

  18. Coupling DHM with ARPS • Output of ARPS (Rainfall) -> Input to the surface runoff model • Flows at subbasin and river streams are predicted • Interface to run both models from web • Visualization of results (VisAD)

  19. ARPS: Rainfall prediction:01h

  20. ARPS: Rainfall prediction:02h

  21. ARPS: Rainfall prediction:03h

  22. ARPS: Rainfall prediction:04h

  23. Flow Prediction

  24. Discussion

More Related