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Model Description for the Sacramento River Winter-Run Chinook Salmon Life Cycle Model

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Model Description for the Sacramento River Winter-Run Chinook Salmon Life Cycle Model Model Description for the Sacramento River Winter-run Chinook Salmon Life Cycle Model Noble Hendrix1 Ann-Marie K. Osterback3,4 Eva Jennings2 Eric Danner3,4 Vamsi Sridharan3,4 Correigh M. Greene5 Steven T. Lindley3,4 1QEDA Consulting, LLC 4007 Densmore Ave N Seattle, WA 98103 2Cheva Consulting 4106 Aikins Ave SW Seattle, WA 98116 3Institute of Marine Sciences University of California, Santa Cruz 1156 High St Santa Cruz, CA 95064 4National Marine Fisheries Service Southwest Fisheries Science Center Fisheries Ecology Division 110 McAllister Way Santa Cruz, CA 95060 5National Marine Fisheries Service Northwest Fisheries Science Center 2725 Montlake Blvd. East Seattle, WA 98112-2097 May 16, 2019 1 I. Background and Model Structure Given the goals of improving the reliability of water supply and improving the ecosystem health in California’s Central Valley, NMFS-SWFSC is developing simulation models to evaluate the potential effects of water project operations and habitat restoration on the dynamics of Chinook salmon populations in the Central Valley. These life cycle models (LCMs) couple water planning models (CALSIM II), physical models (HEC-RAS, DSM2, DSM2-PTM, USBR river temperature model, etc.) and Chinook salmon life cycle models to predict how various salmon populations will respond to suites of management actions, including changes to flow and export regimes, modification of water extraction facilities, and large-scale habitat restoration. In this document, we describe a winter-run Chinook salmon life cycle model (WRLCM). In the following sections, we provide the general model structure, the transition equations that define the movement and survival throughout the life cycle, the life cycle model inputs that are calculated by external models for capacity and smolt survival, and the steps to calibrate the WRLCM. Winter-run Life Cycle Model (WRLCM) The WRLCM is structured spatially to include several habitats for each of the life history stages of spawning, rearing, smoltification (physiological and behavioral process of preparing for seaward migration as a smolt), outmigration, and ocean residency. We use discrete geographic regions of Upper River, Lower River, Floodplain, Delta, Bay, and Ocean (Figure 1). The temporal structure of winter-run Chinook is somewhat unique, with spawning occurring in the late spring and summer, the eggs incubating over the summer, emerging in the fall, rearing through the winter and outmigrating in the following spring (Figure 2). We capture these life-history stages within the WRLCM by using developmental stages of eggs, fry, smolts, ocean sub-adults, and mature adults (spawners). The goal of the WRLCM is consistent with that of Hendrix et al. (2014); that is, to quantitatively evaluate how Federal Central Valley Project (CVP) and California State Water Project (SWP) management actions affect Central Valley Chinook salmon populations. In 2015, the WRLCM was reviewed by the Center for Independent Experts (CIE). In response to recommendations from the CIE, the following modifications were implemented in the WRLCM: 1) divided the River habitat to encompass above Red Bluff Diversion Dam (Upper River) and below Red Bluff Diversion Dam (Lower River); 2) incorporated hatchery fish into the WRLCM; 3) used 95% of observed density as an upper bound for calculation of habitat capacity; 4) re-parameterized the Beverton-Holt function; 5) used appropriate spawner sex-ratios for model calibration to account for bias in Keswick trap capture; 6) modified the WRLCM to a state-space form to incorporate measurement error and process noise; and 7) designed metrics and simulation studies to evaluate model performance. Hendrix et al. (2014) indicated that future work would use DSM2’s enhanced particle tracking model to track salmon survival, which is currently being developed yet is not ready to incorporate into this version of the model. Additional comments received in the CIE review that have not been incorporated yet include: 1) expanding spatial structure for spring and fall-run; 2) tracking additional categories of juveniles (e.g., yearling) for applying an LCM to spring-run Chinook; 3) implementing shared capacity for fall and 2 spring-run Chinook; 5) tracking monthly cohorts through the model; and 6) evaluating multiple model structural forms. We are actively working on improving the WRLCM and developing the spring-run LCM (SRLCM) and fall-run LCM (FRLCM). Many of the CIE recommendations will be implemented with subsequent versions of these models. Figure 1. Geographic distribution of Chinook life stages and examples of environmental characteristics that influence survival. 3 Feb RBDD Feb Mar Mar Adults Apr Apr Enter Sacramento River Winter Chinook Based May Spawn May Butte Cr Jun Jun appearance of adults at Red Bluff Jul Jul Aug Emerge Aug Spawn Dam, winter chinook are believed Sep Sep The quantity and quality of rearing and Omcitg ratory habitat are viewed as key d Oricvt ers of reprEomduercgteion, San Francisco Bay between Nov Nov survival, and migration of freshwater life stages. Various life stages have velocity, depth , and and May. Spawning occurs Dec Dec temperature preferences and toleranceJsa,n a nd these factors are influenced byJ awna tYeoru npgr oojfe ct Ocean Feb Out Feb the Year April and July. oFpreyr aetimones ragned cilnim tahte. Age 2 Mar Migrate 17 Mar Out emigrate to the ocean during the Apr Ocean Apr Migrate May Age 2 May spring. Winter chinook become Jun Jun Jul Jul to ocean fisheF rigieurse 1to. wAgainrgd sconthven tion for F iAguugr e 2. Aging convention for Aug Sacramento River winter chinook. B Sutetpe Creek spring chinook Sep Yearling second calendar year of life as Oct Oct Out Nov Nov Migrate (Figure 1). Age incr Deemc enAtdsu ltos n Dec Dec Dec Jan Pass Jan Jan Jan unless fish enter the rFievbe r;RtBhDeD Feb FAegbe 2 Feb Mar Age 3 Mar Maerx itAdults Mar Age 2 intended to represent thAep rtime when Apr oAcperan Enter Apr exit Bas ed May Spawn May May ButStep Cawrn Age 3 May ocean majority of fishdestined to Jmuna ture in a Jun Jun (Age 2) Jun Redh aBvleuffle ft the ocean. J uUl nderthis Jul Jul Jul Aug Emerge Aug Aug Spawn Aug Spawn bfieslhie avered designated S eap s age 2 Sep Sep Sep (Age 2) O ct Oct Oct Emerge Oct bethweeye nemigrate to the N o vc ean, Nov Nov Nov Dec Dec Dec Dec othcceuyr asre still in their firJsant calendar Jan Jan Young of Jan Ocean F e b O ut Feb FAegbe 3the Year Feb emerge in the Age 2 M a r Migr ate Age 4 Mar Maerx it Out Mar Age 3 during the Apr O cAepar n o Ac per a nMigrate Apr exit May AMgea y2 M ay Spawn Age 4 May ocean beco me Jun Jun Jun (Age 3) Jun Creek SpringChinook S pJurling Jul Jul Jul towardsthe Aug Aug Aug Aug Spawn enter ButteCreek abo Suetp six weeks Sep Sep Yearling Sep (Age 3) odf oli feth ea spopulations Oocft Deer and Oct Oct Out Oct Nov Nov Nov Migrate Nov iCncrereemkse.n Ftsryo enmerge in the Dfaecl l and the Dec Dec Dec Jan Jan Jan Jan rivero; ft hjueveniles occurs pF erbim aArgiley 2in Feb FAegbe 4 Feb Age 3 Mar exit Mar Maerxit Age 2 Mar Age 4 atnimd eF ewbhreuna ry for youn Agp rof tohcea nyear Apr o Ac peran exit Apr exit mature in a May Spawn AMgea y3 May oScepanwn Age 5 May ocean September to May fo rJuyn earlings.( Age 2) Jun Jun (Age 4) Jun Under this Jul Jul Jul Jul convention is simila rA utgo that used Aug Spawn Aug Spawn chaingoeo 2k ,excepFtig utrhee 2. aTSegempep oorafl sftirsuchtu re of the winter-run Chinook S seaplm on, each co(hAogrte b2e)g ins in Marc hS eopf the brood ye(aAr.g eF i4gu ) re from Grov Oerc et t al. (2004). Oct Oct ocean, N ov Nov Nov on May 1, unless t hDeecy enter the Dec Hydrology (the amount and timing of flows) ismodeled with the California S iDmeuc lation Model II spacwalne.n dTahre y first appeJaarn in ocean Jan Jan (CALSIM F IeI)b. HyAdgrea u3 lics (depth and velocity) a nFdeb w ater qualityis modeled wi tFhe bt he Delta Simulation during June andA gJe u4 ly Moaf rtheirexit Mar Age 3 Mar Age 5 Model II A(DprS M2o)c eaannd its water quality sub-mo dAeplr QUALe, xtiht e Hydrologic Engin Aeperr ing Ceenxitt ers River calendar year of Alinfeal yasisM Sayygs tem 3 ( HfiEsCh-R SApSa )w , nt he U .S. BAugre a4u o fM Raey clamocaetaion n’s (USBR) Sacram eMnatyo Riovceera Wn ater Quality g Jun (Age 3 ) Jun Jun Age 5 CWT rMeocdoevl e(S rJRiueWl sQ Mha),v aend other temperature mod eJulsl . The enhanced particle trac Jkuiln g model (ePTM) six weeks makes u Asueg o f many of these DSM2 related pro Aduugc ts to calculSaptaew snu rvival of o Auutmg igrating smSoplatws n ocean fisheries bu tS enpo t in Sep (Age 3) Sep (Age 5) Deer and originati nOgc tf rom Lower River, Delta, and Flood Opclat in habitats. Many of the sta Ogcet transition equations surveys. Nov Nov and the describi nDge ct he salmon life cycle are directly or D iencd irectly functions of water quality, depth, or velocity,J tahne reby linking management actions Jtaon t he salmon life cycle. The combination of models primarily in Feb Age 4 Feb and the Mlinakr ages aexmit ong them form a framew oMrakr for aAngea l4y zing alternative management scenarios the year A pr ocean Apr exit (Figure 3M )a. y Spawn Age 5 May ocean yearlings. Jun (Age 4) Jun Jul Jul that used Aug Spawn of fish Sep (Age 4) Oct 4 enter the Nov Dec in ocean Jan Feb their Mar Age 5 Apr exit Central Valley Winter Run LCM Model Linkages Water and Habitat Management Scenario CVO sends CALSIM II, DSM2, SRWQM data from CH2MHill to SWFSC CALSIM II data DSM2 Hydro data SWFSC processes data SWFSC processes data for Newman delta survival model and habitat capacity model HEC-RAS Delta Habitat SWFSC runs HEC-RAS Capacity Model model SWFSC runs habitat capacity Output: hydraulic data model Output: delta habitat capacity River/Floodplain CV Winter Run Habitat Capacity Life Cycle Model SRWQM data Model SWFSC processes data Newman model QEDA (SWFSC) SWFSC runs model QEDA (SWFSC) runs Runs model, analyzes & Output: river Output: river/floodplain temperature Newman model prepares results habitat capacity Output: survival through Sends results to CVO delta Ocean Fisheries SQL Database Model Application CVO uses results to inform SWFSC organizes and manages data Model Outputs mgmt.
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