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CBEO Year 3 Planning. Rebecca Murphy Dec. 9, 2008. CBEO research. Interpolation methods Test and compare kriging methods in Bay 2D single depth (x,y) 2D along main stem (z,y) 3D kriging 3D kriging using water distance …3D (or 4D) kriging using travel time (extension project…)
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CBEO Year 3 Planning Rebecca Murphy Dec. 9, 2008
CBEO research • Interpolation methods • Test and compare kriging methods in Bay • 2D single depth (x,y) • 2D along main stem (z,y) • 3D kriging • 3D kriging using water distance • …3D (or 4D) kriging using travel time (extension project…) • Use water quality model as covariate in all of these • Analyze changing relationship of hypoxic volume to N load over 50 years. Hypotheses: • Artifact of interpolation method • Artifact of sampling density July 1-15, 2004 DO interpolated For use by others in CBEO science questions and network tools • Calculate and analyze Bay stratification: • Its relation to hypoxic volume • When, where and why changes in • stratification are occurring
Science Q: Why the shift in relationship between nutrient loading and hypoxia after 1980? Artifact: interpolation leads to miscalculation of hypoxia volume 1. 2D kriging main channel data: expand laterally to get 3D
1963: There were no samples taken south of the Potomac anywhere in the Bay from July-Aug. This means that there is large uncertainty in the statistical procedure in that region. Considering some methods of accounting for this, since we know the DO won’t be too low in the southern Bay.
Analysis of Hypoxic Volume • Shift in hypoxic volume related to N load does not appear to be an artifact of interpolation method • Early July appears to have the strongest increase in hypoxia/N of each 2 week period in the summer
Science Q: Why the shift in relationship between nutrient loading and hypoxia after 1980? Artifact: interpolation leads to miscalculation of hypoxia volume 1. 2D kriging main channel data: expand laterally to get 3D 2. 2D kriging at single depths: sum volumes from single depths to get 3D
Science Q: Why the shift in relationship between nutrient loading and hypoxia after 1980? Artifact: interpolation leads to miscalculation of hypoxia volume 1. 2D kriging main channel data: expand laterally to get 3D 2. 2D kriging at single depths: sum volumes from single depths to get 3D Artifact: interpolation leads to miscalculation of hypoxia volume 3. Sub-sample post-1984 data as if it was pre-1984 data and interpolate DO samples taken July 9-12, 1970
Process Hypothesis to Hypoxia Q: Change in Stratification Looking at: • Long term trends in volume of water below pycnocline in July • Long term trends in interpolated salinity and temperature data • Correlations between pycnocline volumes, DO, temp, salinity, flow upper and lower pycnocline
p-value = 0.06 p-value = 0.02 p-value = 0.14
Identify Locations with Temperature Change CB1.1 CB3.3C • Map shows significance level of non-zero slope in the regression for each station: Temperature = b0 + b1 Year + e (for surface temperature measurements from each early July, 1984-2006) • Increase in surface temperature appears to be in northern part of Bay
Summary: Hypoxia and Stratification • With improved interpolation, we still observe increased hypoxic volume per nitrogen load in recent years • Increase in hypoxic volume appears to be strongest in early July • Chesapeake Bay stratification is increasing in early July This could be a reason for the increased hypoxic volume • Surface water temperature appears to be increasing in early July, and is strongly correlated to hypoxic volume Temperature could be the reason stratification is increasing Temperature could be affecting hypoxic volume through stratification OR other means (solubility, increased phytoplankton growth rates, etc)
Year 3 Plan • 3D kriging/water distance • Investigate temperature and pycnocline changes and relations to hypoxic volume • Recent Climate Change Report for Bay (CBP STAC, Oct 08) • Analyze suspended sediment, clarity, and chlorophyll (ideas from student meeting) • Analyze lateral stratification and temperature • Pycnocline trends using 3D kriging • Model results and regressions • Collaborations with others, including: • Kemp, DiToro teams for ideas on pycnocline analysis • Jeremy: Interpolations of N, P • Jeremy: Analysis of model results • Jen: Interpolations of DO at benthic sites • Other CBEO support • Testbed organization/documentation/new data • GEON data and tool transfer • Spatial querying and creating user-friendly model data queries
Year 3 Plan • Possible CBEO-related papers: • Hypoxia trend with multiple interpolation methods and digging in more to post-1984 (possibly partner with analysis of N trend) • Interpolation comparisons/method development studies • One submitted • 3D kriging and water distance possible • Hypoxic volume trend relates to temperature and stratification