Ridges to Reefs: Water Quality and Us Moderated by Hugo Tagholm, CEO, Surfers Against Sewage
Cliff Kapono University of California, San Diego
THE SURFER BIOME PROJECT Photo: @john_hook Cliff Kapono Global Wave Conference 2018 Santa Cruz, California
What does a relationship with nature look like?
How do we communicate this complex idea?
Nature s fingerprints on humans?
Who are the best guinea pigs? THE Surfers SURFER COMMUNITY
SAN DIEGO, USA Photo: @thesaltygiant_ PORTHLEVEN, ENGLAND Photo: @bosssurfboards
Mahalo Nui
Dr. Ali Boehm Stanford University
Oceans and human health Alexandria Boehm Dept. Civil & Environmental Engineering Stanford University aboehm@stanford.edu 20
https://www.nrdc.org/onearth/science-sea-spray Water Sea spray Sand 10 6 bacteria per ml 10 7 viruses per ml
Pathogens in the beach microbiome 42 40 Presence/ Absence of Salmonella spp. Punalu u Adv Entero Noro I Noro II Latitude 38 36 Ma ili ili Ma ile Ka elepulu 34 Pacific Ocean Wai alae -124-122 -120-118 Longitude
Where do pathogens come from? Bather shedding Sewage outfalls Septic tanks via submarine groundwater discharge Runoff (storm, agricultural, and urban) Wildlife and humans feces Environmental reservoirs Wrack can harbor pathogens Wrack can harbor pathogens Runoff dyed with Rhodamine at Huntington 23
Swimmer epidemiology studies Does swimming in the ocean make you sick? Does swimmer illness correlate with fecal indicator bacteria concentrations? 1) Swimmers are at increase risk of illness compared to non-swimmers 2) Risk correlates to fecal indicator bacteria concentrations àdo results apply to surfers? (more exposure, more immunity) àdo results from one beach apply to other beaches?
Fecal indicator bacteria: E. coli and enterococci Risk of illness in swimmers Concentration of water quality indicator Correlate to risk of illness, used worldwide to assess beach water quality, basis of regulations
Over 20,000 beach closures and advisories in the US each year 26
Environmental variables affect beach water quality
http://www.beachapedia.org Seasons and El Nino
Lunar cycles At 50/61 beaches examined in southern California, spring tides coincide with elevated ENT levels ENT = enterococci, MPN = most probable number
nasa.gov Solar modulation Data from Huntington Beach, CA (mpn/100 ml) 100 9 8 7 6 5 4 3 2 TC = total coliform E EC = E. coli ENT = enterococci TC FC ENT 10 00:00 06:00 12:00 18:00 Time of Day https://www.californiabeaches.com/
Future challenges and opportunities Striking lack of global data on coastal water quality Better measurement targets and methods Green infrastructure
Contact info Alexandria Boehm aboehm@stanford.edu
Ryan Searcy Heal The Bay
The NowCast System Predicting Water Quality to Protect Surfer Health
Why Predict Water Quality? 35
SCCWRP (Arnold et al., 2017)
37
NowCast: Predicting Water Quality at California Beaches Rip Check NowCast Prediction NowCast 15 min ago Doheny State Beach https://i.ytimg.com/vi/u4kep9lssxc/maxresdefault.jpg
Creating NowCast Models 39
Initial Research Thoe et al., 2014
HYPERION SHORELINE BACTERIA SAMPLES DATA 41 CDIP
NowCast 15 min ago https://magicseaweed.com/photo/375765/album/a9d5cdced077e918cd3ab840137d4846/
Summer 2017 Beaches 43
Cowell Beach 124 Additional Predictions Beyond Sampling http://www.traceythompson.com/surfing/2009/11/negative-tide-at-cowells/ 44
Redondo Beach Pier 151 Additional Predictions Beyond Sampling
http://www.thesurfchannel.com/news/20140604/doheny-surf-festival-returns-june-28-29/ Doheny State Beach 163 Additional Predictions Beyond Sampling
Looking Forward Launch Website and App Aim: Memorial Day 2018 Add More Beaches to System Including Popular Surf Spots Future Research Modeling Data-Poor Beaches Forecasting Expand NowCast System Internationally Credit: Rude Boy Nick Sadrpour
Ryan Searcy Beach Water Quality Modeler 310-451-1500 x 111 rsearcy@healthebay.org Contact Info Acknowledgements: Dr. Ali Boehm - Stanford Dr. Mitzy Taggart - HTB Dr. Mark Gold - UCLA Dr. Wai Thoe - Hong Kong EPD CA State Water Resources Control Board Credit: Keo Publications available upon request
Dr. Ed Atkin ecoast
Remote Sensing, Classification and Management Guidelines for Surf Breaks of National and Regional Significance Ed Atkin 1,2, Terry Hume 3, Shaw Mead 1, Karin Bryan 2 and Jordan Waiti 4 1 ecoast, Raglan, New Zealand email: e.atkin@ecoast.co.nz 2 University of Waikato, Hamilton, New Zealand 3 Hume Consulting Ltd, Hamilton, New Zealand 4 Maori Health and Development, Raglan, New Zealand Global Wave Conference V Santa Cruz, March 5 th 2018 Maori Health & Development
GWC IV Messages: 1. The collection of data is imperative to surf break management and protection: With the latest video editing techniques and a crack team working round the clock
GWC IV Messages:
GWC IV Messages: 1. The collection of data is imperative to surf break management and protection: CLOSURE 2. A new project to study surf breaks in New Zealand
Remote Sensing, Classification and Management Guidelines for Surf Breaks of National and Regional Significance Ed Atkin 1,2, Terry Hume 3, Shaw Mead 1, Karin Bryan 2 and Jordan Waiti 4 1 ecoast, Raglan, New Zealand email: e.atkin@ecoast.co.nz 2 University of Waikato, Hamilton, New Zealand 3 Hume Consulting Ltd, Hamilton, New Zealand 4 Maori Health and Development, Raglan, New Zealand Global Wave Conference V Santa Cruz, March 5 th 2018 Maori Health & Development
Observations/Impetus There is a requirement in sustainable and adaptive management to have a clear and holistic understanding of the physical environment. Little to no data pertaining to the existing wave quality, breaking patterns, physical drivers, and the socioeconomic importance of New Zealand s surf breaks Managing coastal activities / impacts on the surf breaks, is extremely difficult. Resource managers struggling to give effect to the Resource Management Act 1991 and effectively uphold the intent of the NZCPS.
Remote Sensing, Classification and Management Guidelines for Surf Breaks of National and Regional Significance Funded By: Ministry Of Business, Innovation And Employment Fund: Targeted Research Priority: Enhanced Environmental Decision Making And Behaviour Change Project Components: 1. Study site selection 2. Collation of local and existing knowledge 3. Physical data collection 4. Data Analysis 5. Dissemination of data 6. Development of guidelines.
7 Study sites Representative of the New Zealand s Surf Break demographic: Boulder points Exposed west coast beach Learner/nursery ETD bar Focussing breaks Reef/Sand complex 1. Study Site Selection
Stakeholder Workshops Local/non-local Surfer/non-surfer Business owners etc. Māori and Pākehā Surveys, posters Geomorphological Assessments Literature Review: Journal articles Community group webpages Technical reports etc. 2. Collation of Local and Existing Knowledge
2. Collation of Local and Existing Knowledge Real and Perceived Threats Increased of sand into the bay Sand locked up in the dunes Marina construction and maintenance dredging Port expansion and dredge disposal Boat ramps and breakwaters Runway extensions Water quality (land use / sewage) Sharing of space (other users) How the voice of local surfers is heard during decision making processes. Runway Extension Airport Rights
3/4. Physical Data Collection/Analysis Remote video imaging systems
3/4. Physical Data Collection/Analysis Remote video imaging systems Image Courtesy of POL Image Courtesy of POL
3/4. Physical Data Collection/Analysis Remote video imaging systems Georectification Measurement of features: Shoreline change Rip current occurrence Sandbar morphology Wave propagation characteristics New analysis techniques to determine surfing wave quality - peel angle. (courtesy of Harrison, 2015)
3/4. Physical Data Collection/Analysis Remote video imaging systems Georectification Measurement of features New analysis techniques to determine surfing wave quality - peel angle Quantifying big wave surfing height for Guinness Book of Records Frank Quirarte/Billabong.com (courtesy of Harrison, 2015)
3/4. Physical Data Collection/Analysis Hydrographic Surveys
3/4. Physical Data Collection/Analysis Hydrographic Surveys
3/4. Physical Data Collection/Analysis Numerical Modelling The influence of offshore features Ride lengths Break intensity Peel angle
3/4c. GPS Surfer Ride Data 21 Watches > Stakeholders Spatial definitions Model validation Combine with image analysis
5. Dissemination of Data Website Online Data Portal Journal Articles and Technical Reports 6. Develop Guidelines Provide Methods: Quantification of Surf Breaks Establishing Tolerance Levels How to Assess Potential Threats Mitigation Options Specify Minimum Study Requirements Case Studies Councils NGOs/Environmental Groups Developers Prospectors etc.
Thanks For Listening Kia Ora www.surfbreakresearch.org www.ecoast.co.nz www.waikato.ac.nz Maori Health & Development Acknowledgments: Steering Committee: Department of Conservation, Landcare Research, Surfbreak Protection Society, Surf Life Saving New Zealand, Waikato Regional Council, Auckland Council, and Lincoln University; all stakeholders for their input; and our sponsors Rip Curl and Vodafone