Monday, 7 November 2005 - 10:45 AM
25-5

Using Water Quality Data to Evaluate Fort Hood Bmps: a Decade of Measurement and Observation.

Dennis Hoffman1, June Wolfe III1, and Wesley Rosenthal2. (1) Texas Agricultural Experiment Station, Blackland Research Center, 720 East Blackland Road, Temple, TX 76502, (2) Texas Agricultural Experiement Station, Blackland Res. Cntr./TAES, 720 E. Blackland Rd., Temple, TX 76502

Water quality issues may be associated with intensive training activities on military installations. Military maneuvering damages and destroys vegetation resulting in soil compaction, runoff channelization and gully development. This situation leads to severe training area erosion, sedimentation of streams and lakes, and training disruptions. We have been monitoring sediment and related water quality parameters on Fort Hood sites since 1995 to determine the effectiveness of ITAM and NRCS implemented BMPs. Sites are instrumented with rain gauges, stream level loggers and stormwater sampling equipment. Samples are collected during storm water events to evaluate the effectiveness of the BMPs implemented to reduce sediment loading. Additionally, monthly grab samples are collected to establish a base line water quality index for the area. Analyses of the samples are conducted in our laboratory using EPA-approved laboratory procedures. NRCS and ITAM land managers have implemented numerous erosion-reducing BMPs across the base, including the use of sediment retention structures, riparian areas, gully plugs, and contour soil ripping. Storm runoff water quality data have proven to be useful indicators for tracking land conditions affected by training activities at Fort Hood. BREC has been determining water volumes and sediment loads associated with storm runoff in several key Fort Hood watersheds over the past decade in order to evaluate the effectiveness of the BMPs. Sediment concentrations are combined with storm flow volumes to calculate event-specific sediment loads. The differences in storm flow and sediment loads between events over time can be evaluated to discern land conditions and observe trends.

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