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Published online 26 May 2006
Published in Vadose Zone J 5:742-750 (2006)
DOI: 10.2136/vzj2005.0112
© 2006 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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Incorporating Parametric Uncertainty in the Design of Alternative Landfill Covers in Arid Regions

Michael H. Younga,*, William Albrightb, Karl F. Pohlmanna, Greg Pohllb, Walter H. Zachritzc, Stephen Zitzerd, David S. Shafere, Irene Nesterf and Layi Oyelowog

a Div. of Hydrologic Sciences, Desert Research Inst., Las Vegas, NV
b Div. of Hydrologic Sciences, Desert Research Inst., Reno, NV
c National Park Service, Chesapeake Watershed Cooperative Ecosystems Studies Unit, Frostburg, MD
d Div. of Earth and Ecosystem Sciences, Desert Research Inst., Las Vegas, NV
e Center for Environmental Remediation and Monitoring, Desert Research Inst., Las Vegas, NV
f Tybrin Corp., Edwards AFB, CA
g Environmental Management, Edwards AFB, CA

Figure 1
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  		Fig. 1. Time series of potential plant transpiration (PT) for a 10-yr period, assuming 30% ground cover.

 

Figure 2
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  		Fig. 2. Probability distribution functions (PDF) of lognormalized Ks (saturated hydraulic conductivities) for (a) surface soils and (b) underlying grus.

 

Figure 3
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  		Fig. 3. The relationship between shape parameter {alpha} and Ks (saturated hydraulic conductivity) for 1000 randomly sampled values for Surface Soil 2.

 

Figure 4
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  		Fig. 4. Nomogram showing average flux for 10-yr simulations. Units are centimeters per year for all three graphs.

 

Figure 5
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  		Fig. 5. Deep flux as functions of plant cover percentage and cover thickness for Surface Soil 1.

 

Figure 6
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  		Fig. 6. Nomogram showing the coefficient of variation on flux for 10-yr simulations. Units are in percent for all three graphs.

 

Figure 7
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  		Fig. 7. Relationship between mean annual flux and the standard deviation of flux for each of the three soil types.

 




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