Trinity River Restoration Program: Integrated Assessment Plan Version 1.0 – September 22, 2009

The IAP has been under preparation for the last two years and has undergone considerable revision in response to reviews of version 0.90 by the Science Advisory Board (SAB), TMC and TAMWG in 2006, extensive comments from Program partners in 2007, and a final SAB review (www.trrp.net/science/IAP.htm) of IAP version 0.98 in October 2008. Over this time period three workshops attended by SAB members and invited experts were held to refine various components of the IAP. As assessments are conducted and additional information is gained, the IAP must adapt to this improved understanding. Therefore the IAP is intended to be a “living document” that will evolve as we learn more about the Trinity River.

The IAP proposes a sampling framework for conducting the major assessments across subsystems that are required at site, reach and system scales to fulfill the two purposes of the IAP (i.e., feedback to revise management actions; judging progress towards Program goals and subsystem objectives). The sampling framework proposed within the IAP should allow for comparable system-wide estimates generated using alternative approaches (e.g., census or sample). Ongoing assessments with scientifically established protocols will be maintained as long as they provide information at the appropriate scale and the sampling design is statistically sound. The proposed sampling framework allows assessments to fall into one of five different categories: 1) previously established valid protocols (census, sample, and model based); 2) census; 3) General Random Tessellation Stratified (GRTS) panel; 4) alternative sampling design (i.e., assessment requires a unique design); and 5) site-scale design (e.g., process-based study). The intent of this sampling framework is to provide an accepted base structure around which ongoing assessments and future RFPs can be developed and coordinated, and through which data can be combined across disciplines to elucidate cause-effect relations at a system scale.