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"1 <br />~I~ ~I~~I~~~~~~~~~~~ <br />STATE OF COLORADO RICHARD D. L4MM. Gov e,nrv 999 <br />DEPARTMENT OF NATURAL RESOURCES <br />D. Monte Pascoe, Executive Director <br />MINED LAND RECLAMATION <br />423 Centennial Building, 1313 Sherman Street <br />Denver, Colorado 80203 Tel. (303) 866-3567 <br />David C. Shelton - <br />Director <br />2C): Sandy Emrich <br />FROM: Jerry Zimpfer °~~ <br />RE: Foidel Creek Underground Mine, Surface Water Hydrology Adequacy <br />Review (Rules 2.04.7 and 2.05.6(3)). <br />DRTE: November S, 1982 <br />I have completed my preliminary adequacy review of the surface water items <br />submitted in response to Rules 2.09.7 and 2.05.6(3) of the State Regulations. <br />The applicant's submittal of baseline hydrologic information, except for the <br />spring su;~vey,is very good. However, the discussion of probable hydrologic <br />consequences (Rule 2.05.6(3)) is qualitative and fails to address several <br />possible hydrologic effects of the proposed operation. The discussion of <br />probable hydrologic consequences should be expanded and quantified •sn that <br />the Division has a clear understanding of just what effect this mining <br />operation would have on the existing hydrologic system. <br />The applicant should submit additional information for the following areas <br />of concern. <br />1. Rule 2.04.7(2)(a) - The applicant relies upon published U.S.G.S. data <br />for their spring survey. Normally, U.S.G.S. studies are regional, <br />and are not as intensive as those surveys performed by mine permit <br />applicants themselves (e.g. ARCO's Mt. Gunnison application). In <br />addition, the applicant has submitted only one water quality sample and <br />flowrmeasurement for each of the two springs identified. This is not <br />sufficient to show the seasonal variations in water quality and quantity, <br />or even to identify the flow regime of the springs. The applicant <br />should perform his own spring survey for the permit area and adjacent <br />area, and provide sufficient data to identify seasonal variations <br />in quality and quantity. <br /> <br />