Redd and Carcass database provided as a courtesy by CDFW and USBR. These data are provisional. Subsequent review may result in significant revisions. These data are furnished with the understanding that the California Department of Fish and Wildlife (CDFW) makes no warranties concerning the accuracy, reliability, or suitability for any particular purpose. The datasets were not designed for this type of use. The aerial redd dataset in particular is limited due to is susceptibility to turbid water and other environmental characteristics that can make viewing the redd locations difficult to impossible. It is important to understand these limitations when used in this modeling application.
Smoothing attempts to allocate the redds or carcasses more realistically in time. Since redds and carcasses are surveyed intermittently, the true timing of these events is lost. This process distributes any non-zero count of redds on a particular day back in time uniformly to the previous non-zero count day. The first day with non-zero counts is distributed back in time 6 days.
Under specific user selections for Fish Model: Spawning to Migration, the program includes the River Assessment for Forecasting Temperature (RAFT) model planning mode predicted Daily Average Temperature, assuming USBR operations using mean from 25 member ensemble of meteorology. The RAFT model is a one-dimensional heat budget model for the Sacramento River. In planning mode, RAFT takes output from various planning scenarios and predicts water temperatures for the entire temperature management season (February through November). RAFT was developed with funding from NASA Applied Sciences and the details of the RAFT model are described in Pike et al. 2013. For more information, please refer to Central Valley Temperature Mapping and Prediction (CVTEMP).
Anderson, James J. 2018. Using river temperature to optimize fish incubation metabolism and survival: a case for mechanistic models. bioRxiv. DOI 10.1101/257154. Available 9 March 2018 from: https://www.biorxiv.org/content/early/2018/02/05/257154
Beacham, T.D., C.B. Murray. 1990. Temperature, egg size, and development of embryos and alevins of five species of Pacific salmon: A comparative analysis. Transactions of the American Fisheries Society. 119(6):927-945.
Beer, W.N., J. Anderson. 1997. Modelling the growth of salmonid embryos. Journal of Theoretical Biology. DOI 10.1006/jtbi.1997.0515
CFS. 2010. A Revised Sacramento River Winter Chinook Salmon Juvenile Production Model. Cramer Fish Sciences. Available 9 May 2016 from: http://deltacouncil.ca.gov/sites/default/files/2014/11/November-2010-A-Revised-Sacramento-River-Winter-Chinook-Salmon-Juvenile-Production-Model.pdf
Jensen J. O. T., Jensen M. E., Aquaculture Assoc. of Canada S. A. N. B., Waddy S. 1999. IncubWin: A new Windows 95/98/NT computer program for predicting embryonic stages in Pacific salmon and steelhead trout Contributed Papers - Aquaculture Canada '99 Victoria BC, 28 pp.
Martin, B., (four other authors). 2016a. Modeling temperature dependent mortality of winter-run Sacramento River Chinook salmon. Available 20 June 2017 from: http://www.westcoast.fisheries.noaa.gov/publications/Central_Valley/Water%20Operations/nmfs_concurrence_on_the_bureau_of_reclamation_s_sacramento_river_temperature_management_plan-_june_28__2016.pdf
Martin, B., (six other authors). 2016b. Phenomenological vs. biophysical models of thermal stress in aquatic eggs. Ecology Letters. DOI 10.1111/ele.12705
NOAA/SWFSC Fisheries Ecology Division. (2017). RAFT Predicted Daily Average Temperature. (Temp_50) [Data file]. Available from http://oceanview.pfeg.noaa.gov/erddap/tabledap/cvtempLandscape.html
Oppenheim, B. 2014. Juvenile Production Estimate (JPE) Calculation and Use/Application of Survival Data from Acoustically-tagged Chinook Salmon Releases. Report prepared for the 2014 Annual Science Panel Review Workshop, November 6-7.
Pike, A., E. Danner, D. Boughton, F. Melton, R. Nemani, B. Rajagopalan, and S. Lindley. 2013. Forecasting river temperatures in real time using a stochastic dynamics approach. Water Resources Research 49(9):5168-5182. DOI: 10.1002/wrcr.20389
Zeug, S., P. Bergman, B. Cavallo, and K. Jones. 2012. Application of a Life Cycle Simulation Model to Evaluate Impacts of Water Management and Conservation Actions on an Endangered Population of Chinook Salmon. Environmental Modeling and Assessment. DOI 10.1007/s10666-012-9306-6.
SacPAS: Central Valley Prediction & Assessment of Salmon, University of Washington, Columbia Basin Research, www.cbr.washington.edu/sacramento/