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Tonya DelSontro Eawag & ETH Zurich , Switzerland PowerPoint Presentation
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Tonya DelSontro Eawag & ETH Zurich , Switzerland

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  1. Whatcanbedonewithechosounderbubblefluxes in a lakeorreservoir: Spatiotemporalvariabilityandatmosphericemissions Tonya DelSontro Eawag & ETH Zurich, Switzerland

  2. The Bible Helge Balk and Alex Rynskiy

  3. Simrad EY60/EK60 split-beam echosounder with 120 kHz, 7° beam angle transducer Woh Wohlensee, Switzerland Lake Kariba, Zambia/ Zimbabwe

  4. Bubble Size Calibration

  5. How an echosoundercanhelpillustratethespatiotemporalvaribilityofebullition • Howatmosphericechosounderfluxes, whicharedependent on bubblesizeand a dissolutionmodel, comparewithothermethods

  6. Lake Kariba (Zambia/Zimbabwe) • Subtropical • Oligotrophic • Monomictic • Anoxichypolimnion • 3 yearres. time • Level ± 4 m • Oneofworld‘slargestreservoirs • 5250 km2, 280 km long • 100 m maxdepth • Dendritic • 2100 km ofshoreline 1) Howimportantisebullition in a large reservoir? 2) Large-scalespatialvariability relatedtoriverinflows? DelSontro et al. (2011) ES&T 45: 9866-9873

  7. Methodology • Comparingebullitiondynamics in bayswithriverinflowswithbayswithout • Echosounderandsurfacechambersurveys Hydroacousticprocessingnote: - Erased all non-bubbletargets - Estimatedflux in 5 m segments

  8. Ebullitiondynamics in riverbays Frequency Magnitude • Data richness & newaspects traditional methodscannotreveal

  9. Small-scalespatialvariability in a hotspot • Can makegeneralizationsthatitisrelatedtobathymetry, sedimentationdynamics, or ??

  10. Large-scalevariability in surfaceemissionsandmethodcomparison • River deltas do emitmore CH4, mostly via ebullition • Ebullitionhotspots (riverdeltas) moreobvious via acoustics

  11. Large-scalevariability in surfaceemissionsandmethodcomparison Surface Chambers EchosounderSurfaceFlux • Echosoundercoverage an orderofmagnitudemorethanchambercoverage • Chambers integrateover all fluxes, eventhelowones – • But methodsarewithinerror

  12. Wohlensee (Lake Wohlen), Switzerland • Run-of-river reservoir • 2.5 km2 • Meandepth, 10 m • 2 dayres. time • Waterlevel ± 10 cm

  13. Methodology • Reverseditforbubbledensity in thepresenceoffish (all non-bubbletargets) • Segment divisionbased on bubble-to-non-bubbleratios (nostandard bin length)

  14. Spatiotemporalemissionvariabilityin a localizedhotspot • Obviousdifferenceseven on consecutivedays

  15. Bubble sizevariability per segment • Meanbubblediameterillustratesonepossiblecauseforfluxvariability

  16. Bubble sizedistribution • Larger bubblescontributemoreto total gas volume • Variability in meanbubblesizedistribution per segment, but preferredsizerangeis 4-6 mm diameter

  17. Surfaceemissionmethodcomparison • Surfacefluxcalculatedfromhydroacoustics – high variabilitywith median between 100 and 1000 mg m-2 d-1 • Surfacefluxesfromhydroacoustics (H) andchambers (C) on same day • Chamberfluxeshigher – integratingoverlowfluxes

  18. Eddy covariance Hydroacoustics Temporal variabilitycomparison • Ebullitioncorrelatedwith time ofday, mostlikely due towaterlevelfluctuations Chambers

  19. Spatiallimitationsof all methods AdaptedfromEugster et al. (2011) Biogeosciences 8: 2815-2831

  20. Spatiotemporalvariabilityofsurfaceebullitionfluxvia hydroacoustics • Surfacefluxesaveragedfrom all surveysandcontouredoverbathymetry • Standard deviationshowswheremost variable fluxareascanbefound

  21. Conclusions • Echosoundingcanhelpefficientlysurvey larger areas • Expandingthespatialcoverageof traditional methodsandhelpingtoidentify large-scalevariabilty • Per segmentanalysisthenhelpsidentifysmall-scalespatialvariabilitywithinobservedebullitionhotspots • Thus aiding in futureresearchforcausesof such variability • Bubble sizemaybeimportantcauseforobservedvariability • Echosoundercalibrationsallowforbubblesizedetermination • Surfacefluxcalculationsaredependent on bubblesizeandthedissolutionmodel • Thenhydroacousticmethodscanbeappliedandcomparedwithotheratmosphericemissiontechniques

  22. Thanksto I. Ostrovsky, D. McGinnis, W. Eugster, D. Senn, M. Kunz, T. Diem, A. Zwyssig, M. Schurter, C. Dinkel, H. Balk, A. Rynskiy, J. Wüest, B. Wehrli Zimbabweancrew, ZRA, BKW Swiss National Science Foundation

  23. CH4 emissions from Basin IV Surface CH4 concentrations 3 other deltas = avg 3 measured Vertical CH4 profile near dam Ebullition emits 100x more CH4 than other pathways

  24. L. Kariba relative to other tropical reservoirs • Rough upscaling shows ebullition remains most important • Higher than that in other tropical reservoirs • Dam emissions highest in other reservoirs • Total CH4 emission comparatively low • Due to dam release of CH4-poor epilimnion water Total CH4 emissions from tropical reservoirs 1Abril et al., 2005; 2Kemenes et al., 2007; 3Bambace et al., 2007; 4dos Santos et al., 2006

  25. Ebullition areas < 11% of lake area CH4 emission from Lake Kariba • Dam: 170 t y-1 • Diffusion: 540 t y-1 • Ebullition: 60,000 t y-1 • Total: 10 t km-2 y-1 • Less than all recorded tropical reservoirs

  26. Chap. 6 – KARIBA Acoustics