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ET Comparison: ESPAM2 vs. METRIC Mike McVay ESHMC Meeting 12/12/2011

ET Comparison: ESPAM2 vs. METRIC Mike McVay ESHMC Meeting 12/12/2011. Could differences in modeled spring discharge ( 2006-2008) be the result of ESPAM2 underestimation of ET? Compare Bill Kramber’s METRIC ET analysis of western limb to ESPAM2 ET estimates.

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ET Comparison: ESPAM2 vs. METRIC Mike McVay ESHMC Meeting 12/12/2011

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  1. ET Comparison: ESPAM2 vs. METRIC Mike McVay ESHMC Meeting 12/12/2011

  2. Could differences in modeled spring discharge (2006-2008) be the result of ESPAM2 • underestimation of ET? • Compare Bill Kramber’s METRIC ET analysis of western limb to ESPAM2 ET estimates. • Implicit assumption that METRIC is our best estimate of ET.

  3. The Kramber Analysis • Analysis investigated the Northside and AFRD2 irrigated lands. • Bill used irrigated land layers for 2002, 2006, and 2008 which have been developed from CLU data. • 2000 irrigated land layer developed via refinement of 2002. • Irrigated land rasters “clipped” to AFRD2, Northside and Overlap shapefiles. • METRIC rasters for 2000, 2002, 2006 and 2008. • Calculated METRIC ET on the irrigated land.

  4. The ESPAM2 Analysis • Analysis investigated the Northside and AFRD2 irrigated lands. • Model uses irrigated land layers for 2002 and 2006 which have been developed from CLU data. • 2000 irrigated land layer developed from crop classification of Landsat. • 2008 is a repeat of 2006 • Used irrigated land rasters “clipped” to Kramber’s AFRD2, Northside and Overlap shapefiles to construct .IAR file. • METRIC ET for 2000 and 2006 basis for adjustment factors. • Ran MKMOD8.

  5. Edge-effect ET • The Kramber ET estimate and the ESPAM2 ET estimate cannot be compared directly because ESPAM2 employs a global coefficient to incorporate edged effects from irrigation. • Edge effects can be due to advection of heat into the irrigated lands as well as overspray and runoff from the irrigated lands. • Development of the global coefficient employed the GIS analysis of ET on buffers extending 70 m and an additional 200 m beyond the irrigated land layers.

  6. The Buffer Analysis • Analysis investigated the Northside and AFRD2 irrigated lands. • Performed Kramber METRIC analysis on ESPAM2 buffer. • Used the Kramber irrigated land layers for 2000, 2002, 2006, and 2008. • 70 m and additional 200 m buffers created to calculate irrigation edge-effect ET. • Wetland areas removed from buffers as was done for ESPAM2. • Calculated ET volume on 70 Buffer (70_METRIC ET Depth x 70 m Buffer Area). • Calculated “background” ET volume using 200 m buffer (200_METRIC ET Depth x 70 m Buffer Area). • Subtract background ET volume from 70 m Buffer ET volume to yield edge- effect ET volume. • Add edge-effect ET volume to irrigated land ET volume.

  7. Kramber analysis employed irrigated land different from ESPAM2 input for 2000 and 2008.

  8. 2000 2002 2006 2008

  9. Could ET still be a factor in the spring discharge mismatch? • Could differences in modeled spring discharge (2006-2008) be the result of ESPAM2 • misrepresentation of ET slope? • ESPAM2 calibrated ET exhibits a +0.02% slope. • If the true slope of ET over time is steeper, the model may compensate by adjusting • spring discharge.

  10. The slope of ESPAM2 ET estimates over time is increased during calibration.

  11. What can cause ET to increase over time? • Climate change. • Increase potential ET. • Increase growing season • Crop mix changes. • More consumptive crops. • Cultivar changes. • Higher yield per crop, higher consumptive use. • Efficiency changes. • More efficient practices optimize yield, increase consumptive use. • Practice changes. • Better technology, change in fertilizer, etc.

  12. Climate does not appear to add much trend to ET. Note: ETI NWS Trend is 0.16 in/yr for the model period.

  13. If climate change is not adding significant slope to ET? • Difficult to quantify the remaining suspects. • Crop mix changes – voluntary reporting and adjusted to “hide” largest producers. • Cultivar changes – Even if ET differences between cultivars is determined, • changes over time may not be knowable. • Efficiency changes – The model incorporates sprinkler percentage, • but effects of efficiency not well constrained. • Practice changes – Likely unknowable.

  14. Discussion.

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