1 / 13

Alan Rea

Estimating Hydropower Potential Using EDNA Stage 1B Data: Arkansas-White-Red River Basin Pilot Study. Alan Rea. Overview. Project Goal: Estimate Hydropower potential on each stream reach and total Hydropower potential in U.S. (Cooperator: INEEL/U.S. Department of Energy)

idola-yang
Download Presentation

Alan Rea

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. Estimating Hydropower Potential Using EDNA Stage 1B Data: Arkansas-White-Red River Basin Pilot Study Alan Rea

  2. Overview • Project Goal: Estimate Hydropower potential on each stream reach and total Hydropower potential in U.S. (Cooperator: INEEL/U.S. Department of Energy) • Data Needed: Drainage Area, Avg. Ann. Precip, Temp, Mean Ann. Flow, Elevation (head) change on each reach • Pilot Study Area: Arkansas-White-Red River Basin (Hydrologic Region 11)

  3. Basic Approach • Compute catchment characteristics • Extract node elevations for synthetic streams • Append catchments, synthetic streams for Ark, White, Red Rivers • For each catchment, trace upstream network, select polygons, aggregate basin characteristics • Compute flow, power potential estimates on synthetic streams

  4. Stream Reach Flow Estimation • EDNA catchments were overlaid with climate data from the Oregon State University PRISM Dataset • Mean annual precipitation • Mean annual temperature • Stream flow regression equation from: Vogel, Wilson, and Daly (1999), “Regional Regression Models of Annual Streamflow for the United States”: Journal of Irrigation and Drainage Engineering, May/June 1999, p. 148-157

  5. Stream Reach Flow Estimation (Cont.) Stream Flow Regression Equation Arkansas White Red Region Q11 = e-18.627A0.96494P3.8152T-1.9665 where • Q is the mean flow for a site in Region 11 (A-W-R), in cubic meters per second • A is drainage area, in square kilometers • P is mean annual precipitation, in mm/yr • T is mean annual temperature, in degrees Fahrenheit times 10

  6. Basic Approach (one gory detail) • Node elevations: Two Approaches • Node elev from Filled DEM • Min elev (orig DEM) within 3-cell buffer of nodes (Grid FOCALMIN function)

  7. Results • Processed, computed estimates for 78,993 catchments • Flow and drainage areas compared for 283 stream gages. D.A.’s mostly differ by < 5% • Hydropower estimate: 5.5 million KW • Fill vs. Focalmin-based power estimates differ by < 1 % for Arkansas, White, < 3% for Red

  8. Caveats: • Flow equation valid range: 25 – 44,000 sq. mi. • EDNA Stage 1B errors • Synthetic stream network errors • Mismatches between EDNA tiles • Noncontributing areas connected • Flow reductions in High Plains

  9. Conclusions • We can do some very useful analyses with EDNA Stage 1B data • You have to be careful with the results • Many errors cancel out or self-correct as you go downstream

More Related