Laserfiche WebLink
d� <br /> KEZ-P91-0202 .R7 <br /> March 18, 1993 <br /> Page 2 <br /> whether ground water is threatened, and to what extent, by a given <br /> source of contamination. SESOIL is also capable of simulating <br /> contaminant transport in washload at the soil surface and volatili- <br /> zation rates to the atmosphere. The SESOIL model output is time- <br /> varying and is produced for each month of simulation. <br /> The SESOIL model is one module of a larger software package called <br /> PCGEMS. PCGEMS was developed by the General Sciences Corporation <br /> for the Environmental Protection Agency (EPA) . This software was <br /> developed to provide an information management tool for use in <br /> exposure assessment studies. <br /> The State of California Water Resources Control Board (CWRCB) <br /> Leaking Underground Fuel Tank (LUFT) Field Manual also references <br /> the SESOIL model. Appendix E of the California LUFT manual <br /> describes in detail how the SESOIL model was used for general risk <br /> appraisal. <br /> SESOIL VADOSE ZONE COMPUTER MODEL <br /> KEI generated SESOIL models to appraise the risk of hydrocarbon <br /> soil contamination impacting the local ground water as a result of <br /> activities associated with the above referenced Unocal service <br /> station facility. Three different simulations were performed, each <br /> of which is described in greater detail below: <br /> 1. Simulation #1 <br /> The first simulation was conducted with a number of extremely <br /> conservative "worst case" assumptions as a first attempt to <br /> assess the likelihood and degree of impact of contamination to <br /> the local ground water . The input data were divided into four <br /> general categories which included climate, soil, pollutant <br /> characteristics, and application parameters . <br /> The climate data that was used for Simulation #1 was chosen <br /> from the SESOIL climate data base. The climate data used was <br /> from the Sacramento area, which from the available data was <br /> closest both in proximity and characteristics to the Lodi <br /> area. <br />