Assessing distributed mountain-block recharge in semiarid environments

1. Assessing distributed mountain-block recharge in semiarid environments Huade Guan and John L. Wilson GSA Annual Meeting Nov. 10, 2004

2. Precipitation Soil Soil water Surface Fault Trace FS Bedrock Distributed MBR depends on across the soil-bedrock interface DS FR percolation DR FAULT FAULT MASTER FAULT OBLIQUEFAULT What is distributed MBR? Recharge that occurs on hill slopes in the mountain block Total MBR = distributed MBR + focused MBR Focused MBR occurs near and in stream channels and rivulets

3. What controls percolation to the bedrock? • Our first generic simulation study looks at • Net infiltration = Infiltration – Evapotranspiration (ET) • Bedrock permeability • Soil type and thickness • Slope steepness • Bedrock topography (HYDRUS steady-state simulations, ET was not modeled)

4. Fractured Granite Granite Two primary controls for percolation The results have shown that major controls are net infiltration & bedrock permeabilityslope, soil and bedrock topography are not important. Slope = 0.3 Depression index = 0.1 Soil = sandy loam

5. What controls percolation to the bedrock? • Our first generic simulation study, using model of the soil and bedrock (HYDRUS) suggested major controls by • Net infiltration (infiltration – ET) • Bedrock permeability • But what is “net infiltration”? • We then added ET modeling in the simulations coupled with a surface energy partitioning model (SEP4HillET) • Considering effects of vegetation, slope steepness and aspect on potential E and Potential T

6. Granite 2% 3% 4% 6% Soil and bedrock effects Percolation: in % of Precip 1% 4% 7% 0.3% Granite Tuff 16% 23% 31% 43% Aspect effect Aspect effect Tuff 17% 22% 1.8% 6% Vegetation control S N S N Annual P=565mm Vegetation cover=50% Annual P=565mm Vegetation cover=5% More controls for percolation Slope aspects, vegetation cover, soil thickness for given bedrocks (transient, HYDRUS) Soil Soil

7. What controls percolation to the bedrock? • Our first generic simulation study suggested major controls by • Net infiltration (infiltration – ET) • Bedrock permeability • Our second generic simulation study suggested: • Bedrock properties (not only saturated K) • Vegetation coverage • Slope aspect (steepness as well) • Soil thickness (types as well) • Now lets look at two sites in northern New Mexico

8. Study areas 1 2 • Jemez Mountains • Southern part of Sangre de Cristo Mountains

9. Why study these two sites？ Basin oriented water balances suggest: • Huntley (1979): total MBR ~200mm/yr =38% P in San Juan Mtns (volcanic rocks), and total MBR ~ 70mm/yr =14% P in Sangre de Cristo (granite and well-cemented sedimentary rock) • McAda and Masiolek (1988): total MBR 50~100 mm/yr in Sangre de Cristo • That is a lot recharge! But it is uncertain. Are these total MBR estimates reasonable? • We'll test them by calculating the amount of distributed MBR. It should be less than the total.

10. Approaches for distributed MBR • Find percolation as a function of PET/P Where PET is annul potential ET P is annual precipitation • Then, estimate PET and P maps for the study area • From these maps and Percolation--PET/P functions estimate distributed MBR

11. Some approximationsfor a hillslope in the mountains: • LANL 1994 water-year time series data set, ponderosa site • Macropore soil of uniform thickness (30 cm) • Uniform vegetation coverage • Uniform bedrock permeability for tuff (10-14 m2), and for fractured granite (10-14m2) • Only infiltration-excess runoff

12. Mid-slope Top-slope Percolation=f(PET/P) HYDRUS sim. Bedrock=tuff Slope =0.2 Slope =0.1 (not to scale)

13. 0.1 slope Percolation=f(PET/P)HYDRUS sim. Bedrock=granite Bedrock=tuff

14. Percolation=f(PET/P)HYDRUS sim. Bedrock=granite Bedrock=tuff Percolation = f1(PET/P) Percolation = f2(PET/P)

15. How is PET/P obtained ? • Next, we need spatial distributed annual precipitation (P) • Estimated by a geostatistic model ASOADeK • And spatial distributed annual PET • Estimated by Hargreaves 1985 and SEP4HillET

16. Spatial trend Elevation Slope aspect and prevailing wind Precipitation mapping: ASOADeK and de-trended kriging Sum of 12 monthly precipitation

17. PET mapping: Hargreaves 1985 + SEP4HillET Slope aspect & steepness Seasonal & altitudinal effects Ra: daily extraterrestrial solar radiation in equivalent depth of water Rais dependent of the slope steepness and aspect, solved using SEP4HillET model

18. M1 M12 M2 M11 M3 M10 M4 M9 M5 M8 M6 M7 Ratio of Raon sloped surface to that on flat surface (from SEP4HillET) N S N N S N Winter Summer

19. Temperature mapping Topographic corrected geostatistical interpolations of temperature Daily maximum temperature Daily minimum temperature Regression (Tmin~Z): M4,5,6,7,8,9 Kriging Tmin: M1,2,3, 10, 11, 12 Regression (Tmax~Z)

20. Maps of PET Jemez Mountains Sangre de Cristo Mountains

21. Maps of potential distributed MBRat hypothetical northern NM mountains Jemez Mountains Sangre de Cristo Mountains Min: 0 Max: 193 Mean: 47 Median: 42 Min: 0 Max: 113 Mean: 16 Median: 0.44 Unit: mm/yr

22. Conclusion Mtns. Previous studies This study (Total MBR)(Max. rate of distributed MBR) Sangre’s 50-100 mm/yr 16 mm/yr Jemez/ 47 mm/yr San Juan 200 mm/yr Distributed MBR << Total MBR Focused MBR, in stream channels and rivulets appears to be the most important component of MBR for these two mountain regions and both rock types. This is still a work in progress, and didn't use all spatial information on soil and vegetative cover, etc.

23. ain Thank you！