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PROBABILITY SURVEY DESIGN ALTERNATIVES FOR WATERSHED-BASED STREAM AND RIVER MONITORING PROGRAMS
Citation:
Olsen, A R. PROBABILITY SURVEY DESIGN ALTERNATIVES FOR WATERSHED-BASED STREAM AND RIVER MONITORING PROGRAMS. Presented at EMAP Symposium, Kansas City, MO, May 7-9, 2002.
Description:
National, state, and tribal nation monitoring programs are designed to address multiple objectives. One objective comes from Clean Water Act Section 305(b) and is to provide status and trend estimates of the number (or percent) of stream and river lengths that meet designated uses. A second objective derived from Section 303(d) is to prioritize all streams and rivers in terms of the likelihood of being impaired. A third objective is to determine if, and why, a stream is impaired. Those impaired are put on a 303(d) list. A fourth objective is to determine the Total Maximum Daily Load for an impaired stream and river waterbody. Each objective leads to potentially different conceptual models of streams and rivers. Streams and rivers may be viewed as a linear network where a monitoring site could be located at any point of the linear network. This view is consistent with the needs of 305(b) reporting. Another model is represented by the series of hydrologic unit maps created by USGS. Drainage basins underlie the construction of the HUCs (hydrologic unit codes) and at any level approximately half of the units are true watersheds. A third model is a collection of watersheds defined at some scale, e.g., all headwater watersheds or all Strahler 2nd order watersheds. Note that it is not possible to cover all streams and rivers with a collection of watersheds defined at a single scale. The purpose of this paper is to explore alternative probability survey designs appropriate for different objectives and conceptual models of streams and rivers. Designs will be illustrated using actual studies from EMAP, state Regional EMAP studies, Northwest Forest Plan Aquatic/Riparian Effectiveness Monitoring Program, and LIPS-MACS. All alternatives presented belong to the class of generalized random tessellation stratified (GRTS) survey designs.