1. How well does the NARR data simulate recharge to groundwater?
Lindsey Gulden
Surface Water Hydrology
April 26, 2005

2. Point of comparison for NARR recharge: Keese et al., 2005
Results: average annual recharge
1-D recharge simulations
Unsaturated-zone model (UNSAT-H)
Keese et al., 2005

3. Define “recharge” in NARR as NARR “BGRUN” (baseflow)

4. Methods… FORTRAN! VBA! 144 GRIB Files Myriad data conversion steps
Evaporation
144 GRIB
Files
containing
NARR
monthly data
(baseflow, precip.,
surface runoff,
and evaporation)
Myriad data conversion steps
Baseflow
FORTRAN!
VBA!
Precipitation
NCL!
Blood, sweat
tears
ArcGIS grids, polygons

5. NARR-Noah avg. annual baseflow (mm/yr) 1979-90

6. NARR-Noah avg. annual precipitation (mm/yr) 1979-90

7. NARR-Noah average percent of precipitation that becomes recharge

8. Normalize baseflow data to precipitation

9. Intersect study-region polygons with NARR baseflow data

13. Preliminary conclusion
“Recharge” calculated by NARR is approximately half that calculated by UNSAT-H
Baseflow is moderately correlated between NARR and UNSAT-H

14. Soil hydrology Keese et al.’s of Noah LSM UNSAT-H
Many (~100), variably spaced layers
Precise Ψ, K calculations based on soil texture
Implicit surface runoff
3-dimensional variation in soil texture
4 soil layers
Coarse calculations of Ψ, K
Explicit surface runoff scheme
Homogeneous soil across each 32-km grid cell
Both calculate soil moisture transfer according to the richard’s equation
Both calculate ET using Penman Monteith methods

15. Next steps . . .
Recalculate Keese et al.’s recharge for the overlapping time period (’79-’90)
Continue to analyze reasons for discrepancy
Propose modifications to Noah LSM that will improve vadose-zone moisture transport

16. Thanks!