DRAFT STUDY PLAN TURLOCK IRRIGATION DISTRICT AND … · 7/11/2016 · The Turlock Irrigation...

DRAFT STUDY PLAN

TURLOCK IRRIGATION DISTRICT AND

MODESTO IRRIGATION DISTRICT

LA GRANGE HYDROELECTRIC PROJECT FERC NO. 14581

Reservoir Transit Study

July 2016

1.0 Background The Turlock Irrigation District (TID) and Modesto Irrigation District (MID) (collectively, the Districts) own the La Grange Diversion Dam (LGDD) located on the Tuolumne River in Stanislaus County, California. LGDD was constructed from 1891 to 1893 to replace Wheaton Dam, which was built by other parties in the early 1870s. The LGDD raises the level of the Tuolumne River to permit the diversion and delivery of water by gravity to irrigation systems owned by TID and MID. The Districts’ irrigation systems currently provide water to over 200,000 acres of prime Central Valley farmland and drinking water to the City of Modesto and the community of La Grange. Built in 1924, the La Grange hydroelectric plant is located approximately 0.2 miles downstream of LGDD on the east (left) bank of the Tuolumne River and is owned and operated by TID. The powerhouse has a capacity of slightly less than five megawatts (MW). The La Grange Project operates in a run-of-river mode. The LGDD provides no flood control benefits, and there are no recreation facilities associated with the La Grange Project or the La Grange pool. LGDD is 131 feet high and is located at river mile (RM) 52.2 at the exit of a narrow canyon, the walls of which contain the pool formed by the diversion dam. Under normal river flows, the pool formed by the diversion dam extends for approximately one mile upstream. When not in spill mode, the water level above the diversion dam is between elevation1 294 feet and 296 feet approximately 90 percent of the time. Within this 2-foot range, the pool storage is estimated to be less than 100 acre-feet of water. The drainage area of the Tuolumne River upstream of LGDD is approximately 1,550 square miles. Tuolumne River flows upstream of LGDD are regulated by four upstream reservoirs: Hetch Hetchy, Lake Eleanor, Cherry Lake, and Don Pedro. The Don Pedro Hydroelectric Project (FERC No. 2299) is owned jointly by the Districts, and the other three dams are owned by the City and County of San Francisco (CCSF). Inflow to the La Grange pool is the sum of releases from the Don Pedro Project, located 2.6 miles upstream, and very minor contributions from two small intermittent streams downstream of Don Pedro Dam. 1 All elevations in this document are referenced to 1929 National Geodetic Vertical Datum (NGVD 29).

La Grange Hydroelectric Project

Reservoir Transit Study 2 Draft Study Plan July 2016 FERC Project No. 14581

As part of the Integrated Licensing Process (ILP) for the La Grange Project, the Districts are completing a phased, two-year Fish Passage Facilities Alternatives Assessment (Assessment) to identify and develop potentially viable, concept-level alternatives for upstream and downstream passage of Chinook salmon and steelhead at the La Grange and Don Pedro dams. Specific objectives of the Assessment are to: Obtain available information to establish existing baseline conditions relevant to

impoundment operations and siting passage facilities,

Obtain and evaluate available hydrologic data and biological information for the Tuolumne River to identify potential types and locations of facilities, run size, fish periodicity, and the anticipated range of flows that correspond to fish migration,

Formulate and develop preliminary sizing and functional design for select, alternative potential upstream and downstream fish passage facilities, and

Develop Class-V opinions of probable construction cost and annual operations and maintenance (O&M) costs for select fish passage concept(s).

The Assessment consists of two phases. Phase 1 (conducted in 2015) involved collaborative information gathering and evaluation of facility siting, sizing, general biological and engineering design parameters, and operational considerations. Phase 2 (conducted in 2016) will involve the development of preliminary functional layouts and site plans, estimation of preliminary capital and O&M costs, and identification of any additional significant information needs for select passage alternatives. As detailed in FERC’s May 27, 2016 determination on requests for study modifications and new study, a proposed modification of the Assessment’s Phase 1 and Phase 2 implementation schedule was approved by extending Phase 1 an additional year to 2016 and completing Phase 2 in 2017 to allow for further coordination with licensing participants on gathering necessary information to ensure that the fish passage facility design basis and resulting cost estimates reflect reliable and defensible information. As part of this determination, FERC also noted the Districts’ proposal to develop an anadromous fish reservoir transit study plan and provide it to licensing participants by July 2016, to advance the necessary planning and permitting to conduct such a study during Phase 2 in spring 2017, should the Phase 1 results indicate that such a study is necessary.

2.0 Study Area

The Reservoir Transit study area will include the mainstem of the upper Tuolumne River from Lumsden (RM 96) downstream to Don Pedro Dam (RM 54.8) including Don Pedro Reservoir. 3.0 Study Goals The goal of the Reservoir Transit Study is to evaluate the biological feasibility of downstream (juvenile) movement of anadromous fish through Don Pedro Reservoir. Evaluating reservoir passage efficiency is one component of assessing overall fish passage performance, and results



of this study will be used to help inform feasibility of a potential downstream passage facility. There is no existing information regarding migration and migration success rates of juvenile salmonids through Don Pedro Reservoir, as there are no anadromous populations occurring upstream. The purpose of the Reservoir Transit Study is to evaluate juvenile salmonid reservoir passage efficiency through the Don Pedro Project Reservoir by determining estimates of reach specific migration success.

4.0 Study Methods Permitting and Study Fish Availability Scientific Collector Permit Amendments will be required for this study to be conducted and applications for the amendments will be submitted during summer 2016. The use of hatchery fish will also be required for this study, and a request will be submitted to California Department of Fish and Wildlife (CDFW) in July 2016 for hatchery origin Chinook salmon to be allocated for this study during spring 2017. This request will be for spring-run Chinook salmon in a size range representing large young-of-the-year smolts and/or yearlings (95-120 mm). While spring-run Chinook salmon are preferred, it is recognized that these fish may not be available for a variety of reasons. Alternatively, fall-run Chinook salmon of a similar size could be used for this study as a surrogate to spring-run Chinook salmon (SJRRP 2011). Releases of hatchery origin steelhead juveniles were also considered in development of the study design, but are not proposed due to the potential uncertainties that would be introduced related to the fact that the steelhead fish obtained would not actually be smolting, but simply of smolt-size. Therefore, these fish may not have the urge to sustain downstream migration behavior. While fish that moved upstream following release would be excluded from analyses of migration success, there is no guarantee that a juvenile steelhead that initially moves downstream for some distance does not stop migrating to take up temporary or permanent residence in the river or reservoir (Del Real et al. 2011, Plumb et al. 2006). A key assumption of the study design is that study fish will continue to try to migrate downstream through the river and reservoir. Due to potential sample losses due to upstream movement and/or temporary or permanent residency in the river or reservoir, compounded with the possibility of low migration success through many of the study reaches, including steelhead in the study was deemed infeasible. Acoustic Telemetry VEMCO acoustic technology (tags and receivers) likely represents the best technology given the study objectives and study site. Autonomous acoustic receivers (model VR2W – 180 kHz) are self-powered for 8 months and record and decode data automatically. Each receiver is capable of storing up to 1.6 million records. Under optimal acoustic conditions (e.g., no boat traffic and calm water), 180 kHz tags can be detected up to 250 m away (about 820 ft). However, it should be noted that in areas (near marinas or boat ramps) or periods (on weekends) with high boat traffic, detection range could be considerably less. Therefore, detection range testing will be performed to evaluate the appropriate spacing and configuration of receivers within arrays.



Tagging Methods A total of 960 hatchery reared juvenile Chinook salmon will be surgically implanted with VEMCO acoustic transmitters. Chinook salmon, with average size ranging from 95-120 mm, will be implanted with V4-180 kHz tags (0.24 g). All tagging will be performed by experienced personnel following standard implantation procedures (Adams et al. 1998, Martinelli et al. 1998). The tag to body weight ratio will not exceed 5%. Eight groups of 60 tagged juvenile Chinook salmon will be released at each of two release sites during the study period. Release sites have been identified at Lumsden (RM 96) and Wards Ferry (RM 78.5), as these are the only accessible sites near or upstream of the reservoir. While there is a preference to select a release location that ensures that fish travel through riverine habitat prior to entering the reservoir (e.g., Lumsden), there is also a desire to minimize loss of tagged fish prior to entering the reservoir by making releases near the head of the reservoir (e.g., Wards Ferry). Following release of study fish, a combination of fixed and mobile receivers will be used to document movement of juvenile Chinook salmon through the Don Pedro Project Reservoir. Fixed receivers will be deployed near proposed locations of potential downstream fish collection facilities (Table 4-1; TID/MID 2016) to document travel time and reach specific migration success. Mobile tracking may be used to document locations of tagged fish between acoustic receiver locations. Table 4-1. Proposed locations of acoustic receivers.

Site No. Location River Mile Max Depth (ft)1 Max Width (ft)1

Release Lumsden 96 -- -- Release Wards Ferry 78.5 -- --

1 Abv. Wards Ferry 79 30 250 2 Below Wards Ferry 78 80 400 3 Abv. Moccasin Point 73.3 180 650 4 Jacksonville Rd. Bridge 72.5 200 1200 5 Railroad Canyon 70 280 1000 6 East Bay 60 330 1300 7 Abv. DP Dam 55 530 2000

1 Maximum depth and width assume that Don Pedro Reservoir is at full pool (830’), based on bathymetry data from Don Pedro relicensing. Array Design The entire Don Pedro Reservoir acoustic array will consist of single- and double-gated arrays as shown in Figure 4-1. This particular arrangement of acoustic receivers will provide valuable information on the movement, migration success, and movement direction of tagged fish as well as the detection efficiency of specific locations and the entire array. Proposed array locations provide finer scale resolution near the head of reservoir to provide more information on movement patterns and migration success within this area.



Figure 4-1. Proposed release and acoustic array locations in the upper Tuolumne River and

Don Pedro Reservoir.



Based on the approximate dimensions of each monitoring site (shown in Table 4-1), the number of receivers per site will vary from 1 to 8 (Table 4-2). This proposed number at each site is based on the assumption of a detection range of about 330 ft, and allows for some overlap between detection fields of each receiver. Therefore, based on results from detection range testing, the actual number of receivers may differ (e.g., if detection range is reliably > 330 ft, potentially one less receiver could be used per array). An additional consideration for the number of receivers is the water level in Don Pedro Reservoir at the time of the study. If water level in the reservoir is significantly reduced from the assumed full pool (used to estimate dimensions), the number of receivers could be reduced further. Table 4-2. Proposed number of acoustic receivers and number of arrays at each site (based on

assumption of 330 ft detection range). Site No. Location River Mile No. of Arrays No. of Receivers Release Lumsden 96 - - Release Wards Ferry 78.5 - -

1 Abv. Wards Ferry 79 1 1 2 Below Wards Ferry 78 2 1 3 Moccasin Point 73.3 2 2 4 Jacksonville Rd. Bridge 72.5 1 3 5 Railroad Canyon 70 2 4 6 East Bay 60 1 6 7 DP Dam 55 2 8

Range Testing Estimating the range of detection through range testing will be an important first step in determining the spacing and configuration of receivers within acoustic arrays (Kessel et al. 2013). As noted above, detection range can vary by site, and through time within a site. A variety of factors can cause changes in detection range including, weather, boats, conductivity, temperature, depth, or temperature gradients, among others (Kessel et al. 2013). To conduct range testing, up to 8 receivers will be deployed at 100 ft increments away from a test tag(s). A test tag emits an acoustic pulse or signal every 30 seconds. Therefore, if a receiver 100 ft away was detecting at 100%, the number of detections in an hour for that tag should equal 120 (i.e., 2 pulses per minute * 60 = 120). Receivers close to the test tag should typically detect the tag with high detection rates, and then at increasing distance away from the tag, detection rates will decrease. The range test will be conducted for one week prior to the study and ideally represent typical ambient conditions at each site. After the range test is completed, the number of detections on an hourly or daily basis will be plotted against distance away from the tag. Typically, the rate at which tag detection decreases with increasing distance follows a logistic function (Figure 4-2; from Figure 2 of Kessel et al. 2013). Using Figure 4-3 as an example, in order to achieve 50% detection probability, the receivers should be deployed approximately 1000 m apart (since the detection range represents the radius of a ~500 m circle around the receiver). A similar method will be used to determine the appropriate spacing for the receivers in each array in this study.



Figure 4-2. Conceptual diagram of collected data from range tests and method to determine

appropriate spacing of receivers. From Figure 2 of Kessel et al. 2013. Deployment Methods / Equipment For deployments in the reservoir, acoustic receivers will be affixed to a mooring and buoy system, subject to approval by Don Pedro Recreation Agency and consistent with existing rules and regulations. Moorings will be constructed of concrete and weigh approximately 100 lbs each. The cabling will be secured to the underside of the buoy to minimize tampering. Acoustic receivers will be secured to 3/8” stainless steel cable with stainless steel hose clamps and will be deployed approximately 10 ft from the water surface to prevent tampering or loss from the public. Receivers deployed near the surface will be oriented to face downwards to maximize the detection range in the upper portion of the water column. In the deeper portions of the lake (Railroad Canyon, East Bay, and at Don Pedro Dam), two acoustic receivers will be deployed on the same mooring system. These will face upwards and will be deployed so that they are approximately 10 ft from the substrate. Data Analysis The proposed study design will determine, for any given study reach, the proportion of fish that migrated successfully to pass into the next downstream reach. The mechanisms via which any fish failed to arrive at the next reach will not be identified by this study but may include the following: some fish may have died, taken up residence, moved up into a tributary, turned around, or had a failed tag. Detection data will be analyzed using a Cormack-Jolly-Seber (CJS) framework and the commonly accepted CJS formulation (see Lebreton et al. 1992). A similar method was used by Skalski (1998), and the specific method was later described as a ‘Single Release-Recapture Model’ (Giorgi et al. 2010). These models simultaneously allow the estimation of detection probability at each receiver array, and the probability of successful passage between each array. Multiple detection arrays are required in order to tease-apart the effects of passage-success and detection-probability. Since no arrays exist downstream of the



last one, the detection efficiency of the last array cannot be determined, and because of that, the effects of successful passage and successful detection cannot be teased-apart in the last reach.

The Single Release-Recapture Model does not allow for handling effects to be controlled. Thus any latent handling related effects that manifest in a given study reach will contribute to the failure of some fish to reach the next detection point, and hence will be attributed as a loss to the reach itself. While a Paired Release-Recapture Model would avoid this issue (see Giorgi et al. 2010), these models require more tagged fish for releases to be made at the top of each study reach and a priori knowledge of reach-specific transit times which are not available. In this study, we propose to release fish at Lumsden, i.e., far enough upstream of the reservoir as to maximize the probability that any handling related effects are fully manifest by the time the tagged fish enter the first reach of interest at Wards Ferry. Since there is no available information to predict how many of these fish will survive to Wards Ferry or migrate successfully through each of the reservoir reaches, releases will also be made at Wards Ferry with the intent of bolstering the sample size of fish reaching the downstream reaches (i.e., the fish released at Wards Ferry will not have fully expressed any potential handling-related mortality to be useful for estimation of passage success through their first study reach, but if subsequent detection probabilities and passage success rates are comparable to those of the Lumsden fish, both release groups may be pooled for increased sample size in the lowest reaches).

Detection arrays will be deployed at Wards Ferry, Moccasin Point, Jacksonville Road Bridge, Railroad Canyon, East Bay, and two arrays in the forebay of Don Pedro Dam (Figure 4-3). The double array in the Don Pedro Forebay will allow estimation of passage-success through the last study reach without dealing with non-estimable parameters. At various other key locations in the Reservoir, we propose that double arrays be deployed. There is no a priori knowledge of reach-specific passage success, which could be low enough in some reaches as to make it difficult for the model to separate the effects of passage-success and detection-probability. Thus, while not strictly required for the analysis, especially if passage success is good, double arrays will add value by helping to resolve the models under certain scenarios.

All modeling will be carried out in the R computing environment (R Development Core Team 2015) using the RMark package (Laake 2013) to construct and fit models in Program MARK (White and Burnham 1999). In Figure 4-3, model parameters are mapped onto a conceptualized image of the river and reservoir, where the waterways have been simplified for the sake of the illustration as a linear system. The parameters that will be estimated are listed and defined in Table 4-3.



Table 4-3. List of model parameters, and their definitions. Parameter Definition Φ L-W1 Probability of successfully passing between Lumsden and the first array at Wards

Ferry p W1 Probability of detection at the first array at Wards Ferry p W2 Probability of detection at the second array at Wards Ferry Φ W2-M1 Probability of successfully passing between the second array at Wards Ferry and

the first array at Moccasin Point p M1 Probability of detection at the first array at Moccasin Point p M2 Probability of detection at the second array at Moccasin Point Φ M2-J Probability of successfully passing between the second array at Moccasin Point

and Jacksonville Rd. Bridge p J Probability of detection at Jacksonville Rd. Bridge Φ J-R1 Probability of successfully passing between Jacksonville Rd. Bridge and the first

array at Railroad Canyon p R1 Probability of detection at the first array at Railroad Canyon p R2 Probability of detection at the second array at Railroad Canyon Φ R2-E Probability of successfully passing between the second array at Railroad Canyon

and East Bay p E Probability of detection at East Bay Φ E-D1 Probability of successfully passing between East Bay and the first array in the

Don Pedro forebay p D1 Probability of detection at the first array in the Don Pedro forebay λ D1-D2 Probability of both successfully passing between the two arrays in the Don Pedro

Forebay (Φ D1-D2) and being detected at the second array (p D2). The two effects cannot be disentangled, thus are represented by a single parameter, λ D1-D2

Note that passage success will be assumed to be 100% between paired arrays (where two sets of arrays are deployed together) at Wards Ferry, Moccasin Point and Railroad Canyon.



Figure 4-3. Model parameters mapped onto a simplified (conceptual) image of the river and

reservoir, shown for the sake of the illustration as a linear system. Yellow circles show detection arrays. Parameters associated with the Lumsden releases (R1) will be estimated separately from their equivalents (marked with an apostrophe) for the Wards Ferry releases (R2), unless data pooling is required or unless model results suggest separation is not parsimonious. Definitions of parameter symbols are shown in Table 4-3.

Lumsden (L)

Φ L-W1

Wards Ferry (W1)

Wards Ferry (W2)

Φ W2-M1

Moccasin Point (M1)

Moccasin Point (M2)

Φ M2-J

Jacksonville Rd. Bridge (J)

Φ J-R1

Railroad Canyon (R1)


Φ R2-E

East Bay (E )

Φ E-D1

Abv. DP Dam (D1)

Abv. DP Dam (D2)

p J

p R1 Φ R1-R2 = 1p R2

p E

p D1 λ D1-D2 = (Φ D1-D2)(p D2)

p W1 Φ W1-W2 = 1p W2

p M1 Φ M1-M2 = 1p M2

R1 Lumsden (L)

Φ L-W1

Wards Ferry (W1)

Wards Ferry (W2)

Φ' W2-M1

Moccasin Point (M1)

Moccasin Point (M2)

Φ' M2-J

Jacksonville Rd. Bridge (J)

Φ' J-R1



Φ' R2-E

East Bay (E )

Abv. DP Dam (D1)

Abv. DP Dam (D2)p' D1 λ' D1-D2 = (Φ' D1-D2)(p' D2)

p W2

p' M1 Φ' M1-M2 = 1p' M2

p' J

p' R1 Φ' R1-R2 = 1p' R2

p' E

R2



5.0 Study Schedule Study Planning and Permitting ..................................................... May 2016 – December 2016 Draft Study Plan to Licensing Participants ................................................................ July 2016 Provide Interim Study Updates………………………………………....February – May 2017 Field Data Collection ..................................................................................... April – June 2017 Data Entry Processing, and QA/QC ........................................................ February –July 2017 Data Analysis………………………………………………………….....April – August 2017 Report Preparation .................................................................................... June - August 2017 Draft Report for 30-day Review ........................................................................... August 2017 Final Report Issuance ......................................................................................... October 2017

6.0 References Adams, N.S., Rondorf, D.W., Evans, S.D., and J.E. Kelly, 1998. Effects of surgically and

gastrically implanted radio tags on growth and feeding behavior of juvenile Chinook salmon: Transactions of the American Fisheries Society, v.127, p. 128-136.

Del Real, S. C., Workman, M., Merk, J. 2011. Migration characteristics of hatchery and natural-origin Oncorhynchus mykiss from the lower Mokelumne River, California. Environmental Biology of Fishes.

Giorgi, A., Skalski, J.R., Peven, C., Langeslay, M., Smith, S., Counihan, T., Perry, R. and Bickford, S. 2010. Guidelines for conducting smolt survival studies in the Columbia River. In: Tagging, Telemetry and Marking Measures for Monitoring Fish Populations—A compendium of new and recent science for use in informing technique and decision modalities. Pacific Northwest Aquatic Monitoring Partnership (PNAMP) Special Publication 2010-002. K.S. Wolf and J.S. O’Neal (eds). Chapter 3, pp. 47-48. (http://www.pnamp.org/node/2867).

Kessel, S.T., Cooke, S.J., Heupel, M.R., Hussey, N.E., Simpfendorfer, C.A., Vagle, S. and Fisk, A.T., 2014. A review of detection range testing in aquatic passive acoustic telemetry studies. Reviews in Fish Biology and Fisheries, 24(1), pp.199-218.

Laake, J.L. 2013. RMark: An R Interface for Analysis of Capture-Recapture Data with MARK. Alaska Fisheries Science Center Processed Report 2013-01.

Lebreton, J.D., K.P. Burnham, J. Clobert, and D.R. Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals - a unified approach with case studies. Ecological Monographs, 62: 67-118.

Martinelli, T.L., Hansel, H.C., and R.S. Shively, 1998. Growth and physiological responses to surgical and gastric radio tag implantation techniques in subyearling Chinook salmon: Hydrobiologia, v. 371/372, p. 79-87.



Plumb, J.M., Perry, R.W., Adams, N.S., Rondorf, D.W. 2006. The effects of river impoundment and hatchery rearing on the migration behavior of juvenile steelhead in the Lower Snake River, Washington. North American Journal of Fisheries Management, 26:438-452.

R Core Team. 2015. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/.

SJRRP. 2011. San Joaquin River Restoration Program Juvenile Salmonid Survival and Migration Preliminary Report. July 2011.

Skalski, J. R. 1998. Estimating season-wide survival rates of outmigrating smolt in the Snake River, Washington. Canadian Journal of Fisheries and Aquatic Sciences, 55: 761-769.

Turlock Irrigation District and Modesto Irrigation District (TID/MID). 2016. Fish Passage Facilities Alternatives Assessment Progress Report. Prepared by HDR, Inc. Appendix to La Grange Hydroelectric Project Initial Study Report. February 2016.

White, G.C. and K.P. Burnham. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study, 46 Supplement: 120-138.

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