Improving Environmental Flow Methods Used in California FERC Relicensing

Year: 
2011
Abstract: 

California faces a wave of licensing of dams for power production, with approximately half of the dams scheduled to be licensed over the next 15 years. The number of projects, the cost of the licensing process, and the increased appreciation of the complexity of stream ecosystems, highlight the need for better methods for determining how much water should to be left in the streams, using Environmental Flow Methodologies. The authors examined the range of methods available assessing environmental flows in relation to Federal Energy Regulatory Commission (FERC) licensing processes in California. We specifically sought to integrate insights from allied fields not usually applied to environmental flow methodologies. A particular goal was to see if environmental flow methodologies in use in California are consistent with generally accepted practice in the scientific community, especially in their statistical approaches to problems. The researcher’s basic findings include: (1) environmental flow methodologies used most frequently in California are seriously flawed, including their underlying statistical foundations; (2) alternatives are available (e.g., using Bayesian Networks) that are both more effective and likely less costly; (3) The fish assemblages of California streams have a complex relationship to flows but it is possible to manage regulated streams to favor desired fish assemblages (e.g., endemic fishes); (4) Required monitoring programs for Federal Energy Regulatory Commission projects are generally inadequate and, as a result, have a high probability of leading to erroneous conclusions about the effects of projects on fish populations. The overall results of this research indicate that the efficiency and effectiveness of environmental flow evaluations can be increased, while reducing their costs and providing benefits to both fish and water users. Specific suggestions for improving environmental flow methodologies are provided. 

Author(s): 

Moyle, P.B., J.G. Williams, and J.D. Kiernan

Category: