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Updated: Jul 29, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
The Grande Ronde Model Watershed: Integrating Science into Restoration Implementation and Adaptive Management
Phil Roni1,2, Jesse Steele3, Kayla Morinaga4
1Watershed Science Lab, Cramer Fish Sciences, 1125 12th Avenue NW, Issaquah, WA, 98027, USA. phil.roni@fishsciences.net.
Abstract:
Watershed conservation groups throughout the Pacific Northwest coordinate and implement watershed and habitat restoration to recover Pacific salmon Oncorhynchus spp. Many watershed organizations struggle with implementing an adaptive management process that integrates monitoring data and the latest science into their restoration programs. We describe the evolution and lessons learned from the Grande Ronde Model Watershed (GRMW), one of the longest running watershed organizations coordinating fish habitat restoration projects. Since 1992, the GRMW has initiated nearly 300 habitat restoration projects and their partners more than 600 projects. These projects have evolved from an opportunistic approach, focusing on small-scale riparian fencing and instream structures to a data driven, collaborative processes for identifying, ranking, and implementing large process-based floodplain projects using the latest science. The GRMW recently developed an adaptive management process to assess restoration goals and priorities, and a multi-scale monitoring program that leverages the extensive data collected by partners, and periodic collection of LiDAR to evaluate past, current, and future restoration projects. These recently developed components, which are based on the collective history of the GRMW, provide important lessons for other watershed restoration organizations. These include partnering with local organizations to collect monitoring data; use of a transparent multi-scale process for prioritizing restoration; development of a stepwise process for design and implementation of priority projects; a formal adaptive management process with a designated lead to use the latest science to modify goals, priorities, project selection, and design; and use of remotely sensed data to assist with multi-scale monitoring of project success.
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