Assessing distributed mountain block recharge in semiarid environments
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Assessing distributed mountain-block recharge in semiarid environments. Huade Guan and John L. Wilson GSA Annual Meeting Nov. 10, 2004. Precipitation. Soil. Soil water. Surface Fault Trace. FS. Bedrock. Distributed MBR depends on across the soil-bedrock interface. DS. FR.

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Assessing distributed mountain-block recharge in semiarid environments

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Assessing distributed mountain block recharge in semiarid environments

Assessing distributed mountain-block recharge in semiarid environments

Huade Guan and John L. Wilson

GSA Annual Meeting

Nov. 10, 2004


What is distributed mbr

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


What controls percolation to the bedrock

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)


Assessing distributed mountain block recharge in semiarid environments

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


What controls percolation to the bedrock1

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


Assessing distributed mountain block recharge in semiarid environments

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


What controls percolation to the bedrock2

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


Assessing distributed mountain block recharge in semiarid environments

Study areas

1

2

  • Jemez Mountains

  • Southern part of Sangre de Cristo Mountains


Why study these two sites

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.


Approaches for distributed mbr

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


Assessing distributed mountain block recharge in semiarid environments

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


Assessing distributed mountain block recharge in semiarid environments

Mid-slope

Top-slope

Percolation=f(PET/P) HYDRUS sim.

Bedrock=tuff

Slope =0.2

Slope =0.1 (not to scale)


Assessing distributed mountain block recharge in semiarid environments

0.1 slope

Percolation=f(PET/P)HYDRUS sim.

Bedrock=granite

Bedrock=tuff


Assessing distributed mountain block recharge in semiarid environments

Percolation=f(PET/P)HYDRUS sim.

Bedrock=granite

Bedrock=tuff

Percolation = f1(PET/P)

Percolation = f2(PET/P)


How is pet p obtained

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


Assessing distributed mountain block recharge in semiarid environments

Spatial trend

Elevation

Slope aspect and prevailing wind

Precipitation mapping: ASOADeK

and de-trended kriging

Sum of 12 monthly precipitation


Assessing distributed mountain block recharge in semiarid environments

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


Assessing distributed mountain block recharge in semiarid environments

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


Assessing distributed mountain block recharge in semiarid environments

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)


Assessing distributed mountain block recharge in semiarid environments

Maps of PET

Jemez Mountains

Sangre de Cristo Mountains


Assessing distributed mountain block recharge in semiarid environments

Maps of potential distributed MBRat hypothetical northern NM mountains

Jemez Mountains

Sangre de Cristo Mountains

Min: 0 Max: 193

Mean: 47Median: 42

Min: 0 Max: 113

Mean: 16Median: 0.44

Unit: mm/yr


Conclusion

Conclusion

Mtns.Previous studies This study

(Total MBR)(Max. rate of distributed MBR)

Sangre’s50-100 mm/yr16 mm/yr

Jemez/47 mm/yr

San Juan200 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.


Assessing distributed mountain block recharge in semiarid environments

ain

Thank you!


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