Estimating biozone hydraulic conductivity in wastewater soil-infiltration systems using inverse numerical modeling.
During operation of an onsite wastewater treatment system, a low-permeability biozone develops at the infiltrative surface (IS) during application of wastewater to soil. Inverse numerical-model simulations were used to estimate the biozone saturated hydraulic conductivity (K(biozone)) under variably saturated conditions for 29 wastewater infiltration test cells installed in a sandy loam field soil. Test cells employed two loading rates (4 and 8cm/day) and 3 IS designs: open chamber, gravel, and synthetic bundles. The ratio of K(biozone) to the saturated hydraulic conductivity of the natural soil (K(s)) was used to quantify the reductions in the IS hydraulic conductivity. A smaller value of K(biozone)/K(s,) reflects a greater reduction in hydraulic conductivity. The IS hydraulic conductivity was reduced by 1-3 orders of magnitude. The reduction in IS hydraulic conductivity was primarily influenced by wastewater loading rate and IS type and not by the K(s) of the native soil. The higher loading rate yielded greater reductions in IS hydraulic conductivity than the lower loading rate for bundle and gravel cells, but the difference was not statistically significant for chamber cells. Bundle and gravel cells exhibited a greater reduction in IS hydraulic conductivity than chamber cells at the higher loading rates, while the difference between gravel and bundle systems was not statistically significant. At the lower rate, bundle cells exhibited generally lower K(biozone)/K(s) values, but not at a statistically significant level, while gravel and chamber cells were statistically similar. Gravel cells exhibited the greatest variability in measured values, which may complicate design efforts based on K(biozone) evaluations for these systems. These results suggest that chamber systems may provide for a more robust design, particularly for high or variable wastewater infiltration rates.
Bumgarner
Johnathan R
JR
Department of Geological Sciences, The University of Texas at Austin, 1 University Place, Austin, TX, USA.
McCray
John E
JE
D005374:Filtration; D007700:Kinetics; D008962:Models, Theoretical; D012987:Soil; D012989:Soil Pollutants / Q000032:analysis*; D014865:Waste Disposal, Fluid / Q000379:methods*; D014867:Water / Q000737:chemistry*; D014872:Water Movements; D014873:Water Pollutants / Q000032:analysis*
D012987:Soil; D012989:Soil Pollutants; D014873:Water Pollutants; D014867:Water