A SCREENING MODEL FOR EFFECTS OF LAND-DISPOSED WASTES ON GROUNDWATER QUALITY


UNLU K., KEMBLOWSKI M., PARKER J., STEVENS D., CHONG P., KAMIL I.

JOURNAL OF CONTAMINANT HYDROLOGY, cilt.11, ss.27-49, 1992 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 11
  • Basım Tarihi: 1992
  • Doi Numarası: 10.1016/0169-7722(92)90032-a
  • Dergi Adı: JOURNAL OF CONTAMINANT HYDROLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.27-49
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This paper describes a screening model for evaluating the migration of organic and inorganic contaminants leached from land-disposed wastes. The model is composed of a waste-zone release submodel, an unsaturated-zone transport submodel and a saturated-zone transport submodel. The waste-zone submodel assumes steady one-dimensional vertical flow through a uniform waste zone treated as a "stirred tank reactor". Soluble inorganic contaminants are assumed to exhibit a constant concentration in the leachate until mass depletion occurs, while organic contaminants are assumed to exhibit leachate concentrations that are proportional to the mass fraction in the oily waste phase. Vertical, one-dimensional, unit-gradient flow is assumed in the unsaturated zone at a constant water content controlled by the net infiltration rate and the unsaturated soil permeability function. Transport occurs by convection and scale-dependent dispersion with linear adsorption and decay. In the saturated zone, flow is assumed to be planar, with three-dimensional convective-dispersive transport, adsorption and decay, with a rectangular horizontal source at the water table. The waste-zone submodel defines the boundary conditions for the unsaturated-zone submodel, which, in turn, defines the boundary conditions for the saturated-zone submodel. Because of the semi-analytical nature of the model, it can be executed very quickly, thus enabling rapid screening analyses and implementation in Monte Carlo analyses, which require a large number of model executions.