USDA Forest Service
 

Pacific Southwest Research Station

 

Pacific Southwest Research Station
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Albany, CA 94710-0011

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Evaluating field and laboratory data for developing surrogate indicators to monitor fine sediment in the Tahoe Basin

Proposal [pdf]

Lead Researchers:

Alan Heyvaert, Desert Research Institute
John Reuter, Tahoe Environmental Research Center, University of California, Davis
Masoud Kayhanian, University of California, Davis
Nicole Beck, 2NDNATURE, LLC

Abstract

The Lake Tahoe Total Maximum Daily Load (TMDL) has determined that a 60–70% reduction in fine sediment particles will be needed to achieve a Lake Tahoe clarity target of 30 meters. Reliable and economical methods to monitoring and quantify the loading of fine sediment particles to the Lake are needed in order to track pollutant load reductions over time resulting from water quality improvement projects. The goal of this research is to provide basin management agencies with science-based final recommendations for analytical methods and surrogate indicators of particle concentrations and characteristics appropriate to regulatory purposes and relevant to improved measurement and tracking of fine particle loading in the Tahoe Basin. Agency representatives will work in close collaboration with the project scientists to evaluate the available data, determine the quality of existing relationships between surrogate quantification techniques and associated particle numbers, and then provide recommendations for field and laboratory assessment of particle numbers and suitable proxies. The project scientists assembled for this directed action have extensive experience in water quality sampling, particle size analysis, and fine particle data evaluation, having worked on the TMDL and its associated tools, as well as with several of the agencies and key stakeholders in the Tahoe Basin.

Relation to Other Research Including SNPLMA Science Projects

This project will provide information needed for the Pollutant Load Reduction Model (PLRM), the Lake Clarity Crediting Program, the Regional Stormwater Monitoring Program (RSWMP) and the Lake Tahoe TMDL Management System, all developed in support of lake and watershed restoration as programmed within the Environmental Improvement Program (EIP). This project will use information from previous monitoring and research projects in the Lake Tahoe Basin, including the Pilot TMDL Stormwater Monitoring Program, the PLRM Development Project, previous studies related to best management practice (BMP) evaluation, as well as the many research projects done since fine particles were first identified as a pollutant of concern. This project also will build upon information developed from other SNPLMA projects awarded to DRI, UC Davis, and 2NDNATURE, which were funded to assemble available particle size data and test analytical methods for developing preliminary protocols ("Tahoe Basin particle size analysis and protocol development"), and to acquire data on Characteristic Runoff Concentrations (CRCs) and Characteristic Effluent Concentrations (CECs) used in the PLRM ("Priority urban stormwater monitoring to directly inform the Pollutant Load Reduction Model (PLRM)"). Ongoing SNPLMA projects funded in Round 8 are in progress at UCD and DRI to determine sources of fine sediment in highway runoff ("Determining sources of highway runoff fine sediment in stormwater, streams, and Lake Tahoe using fingerprinting techniques"), and to help establish relationships between turbidity, fine sediment and natural removal mechanisms ("Potential of engineered flood plains and wetlands as fine-particle BMPs: case study of Trout Creek and the Upper Truckee River"). Information collected by these studies will help develop relationships between fine sediment particle numbers and other important water quality characteristics, such as turbidity, total and size fractionated suspended solids, and nutrients and metals loading associated with fine particles. This information will be needed for improved management models, performance monitoring, and pollutant crediting assessment.

Expected date of final products:

December 2013

Last Modified: Mar 28, 2013 02:52:08 PM