Improving seepage measurements in the Truckee Canal and developing a framework for data collection, modeling and assessment of unlined canal seepage

Project ID: 19144
Principal Investigator: Evan Lindenbach
Research Topic: Condition Assessment
Funded Fiscal Years: 2019 and 2020
Keywords: None

Research Question

How will the evaluation of diffuse and point seepage increase the reliability of the Truckee Canal operations model? Can this be tied to other seepage monitoring work in the Truckee Canal? How can a full seepage model for a canal be developed using a variety of monitoring techniques? What is the optimum type of monitoring system for other water conveyance or storage projects?

Need and Benefit

Need:
Accurate understanding of seepage through Reclamation's canals is critical for operations and water budgeting. This
project will directly fulfill needs identified by LBAO for use in their operations model. This will also facilitate a
technology transfer to the LBAO and the TSC for use on other Reclamation projects.
The work currently being performed to monitor diffuse seepage out of the Truckee Canal is providing high quality initial
results but a data gap has been identified: quantification of the point seepage. This work will fill that gap and allow for
both types of data to be collected in the same season. The results of this work will create an accurate, full-scale
evaluation of seepage out of the Truckee Canal. Reclamation will learn directly from the USGS how to collect both
types of data (diffuse seepage is on-going), how to analyze the data, and how to incorporate the data into seepage
models.
The scoping level report will seek to incorporate all data collected during the FY19 irrigation season. A number of
projects are proposed to be going that year (depending on the funding) which will generate a great deal of data. This
report will detail a proposed method for incorporating all data into one model for use at the Truckee Canal, and will
detail a roadmap for how to collect/use seepage data at other canals. The goal is to incorporate Artificial Neural
Networks data processing to look at how all the collected data can be used to accurately predict seepage and
optimize operational models.
Benefit:
The direct benefit is for the LBAO Operational and Planning models of the Truckee and Carson Basins as they rely on
Truckee Canal Loss estimates from previous studies which are likely oversimplifications of the complex subsurface
characteristics. Currently, the models use a set of regression equations that often do not match observed loss rates.
This project will enhance seepage and loss estimates, improve model accuracy, and ultimately allow for more efficient
operation of the Truckee and Carson Basins.
This project will leverage an on-going S&T project where TRODs were installed to monitoring subsurface temperature
changes due to seepage out of the canal. This proposal seeks to continue monitoring the existing equipment for
another irrigation season as well as quantify seepage losses out of point sources. If this monitoring is pushed to
another year, it would require reinstallation of the TROD systems at a cost of about $70,000. Continued use of the
existing equipment coupled with installation of the additional monitoring systems represents a cost effective way to
gather additional data and close identified gaps.
The PI will incorporate the results of this research into data collected as part of an ongoing S&T project (Truckee
Canal Seepage Study) to generate a complete data set, thereby advancing the canal seepage science. The results of
this work will then be disseminated to all other Reclamation regions through the PI's connections in the S&T Canal
Operations Workshop. This project has significant in-kind contributions from the USGS allowing the S&T program to
leverage funds efficiently.
The development of a roadmap for seepage data collection and modeling will standardize how Reclamation can most
efficiently collect and reduce seepage data from other canals and water storage features.

Contributing Partners

Contact the Principal Investigator for information about partners.

Research Products

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Last Updated: 4/4/17