2.0 CRiSP's 2-D Nitrogen Model. The following comments were made about Shaw's proposed 2-D mixing model:
4.0 Unsteady Flow and Transport Model. Marshall Richmond presented the graphic output from the model he has developed for flow and gas transport on the Columbia and Snake Rivers. Currently it is a 1-D model, with Dworshak, Hell's Canyon Dam and Priest Rapids inputting gas into the system and output given up to the Snake-Columbia confluence. A 2-D near project hydrodynamic model is currently being developed with plans of adding a particle tracking simulation for 2-D mixing. Richmond also mentioned the use of these meteorological values: wind speed, temperature, relative humidity, and %-cloud cover but expressed concern over the lack of stations close enough to the regions of interest. Airport data is not a sufficient substitute for regions in the river canyon.
The goals for output of this model are: gas levels, velocities, and general hydrodynamics, particularly in the tailrace of the dams. Richmond also stated that he would coordinate with those on the CRiSP project to get the desired output in a usable form for their model. The variables of interest from this model for the CRiSP project including: gas levels, velocity, and river depth.
5.0 TDG Mass Transfer. Mike Schneider presented his analysis of gas/spill data. A linear fit of kcfs spilled and %-gas produced was shown at several dams. Day versus night spill plots showed the affects of different night and day spill patterns leading to different gas production curves. The variation around the fitted gas production curve was about 5%. The question was then raised as to the usefulness of predictive curves which are only accurate to within 5-10% , particularly considering the difference between 115% and 125% supersaturation. Carlson commented that this band of uncertainty may be too wide for this predictive curve to be used to evaluate alternative structural changes. A suggestion was made to use CRiSP in monte carlo mode to incorporate the uncertainty into survival analysis.
6.0 Biological Modeling. Larry Fidler discussed his progress on the development of new mortality models. He identified the following important parameters for mortality rates: fish species, fish length, exposure time, effective total gas pressure distributed over (x,y,z,t), water temperature, dissolved oxygen, and activity level. Fidler did an extensive literature search and review on Gas Bubble Trauma and then implemented neural nets to 1) do initial data screening of Gas Bubble Trauma data in the literature, and 2) Develop steady state mortality models. Fidler warned that when using mortality data from the literature, care is needed to not include mortality that was an artifact of the study design.
Time to mortality versus %-mortality was focussed on with the model parameters being: exposure time, species and PO2. Fidler commented that very little data for %-mortality exists for gas levels below 120% which makes it difficult to calibrate a model.
My own comments:
3.0 Spill. In the spill analysis by NMFS, transportation lead to the lower level of mortality compared to spill regimes. (See NMFS Biological Opinion). Carlson expressed concern over the margin of error in their analysis, specifically for the survival statistics. How do we operate under this uncertainty? Are the details of TDG not fine enough compared to this level of system uncertainty?
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