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Sustainable water supply in Swedish coastal areas – possibilities and challenges

Sustainable water supply in Swedish coastal areas – possibilities and challenges. Bosse Olofsson Royal Institute of Technology, KTH NGL Annual Meeting at Äspö 2013-11-07. 50% of the world’s population concentrates to a 60km wide coastal zone

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Sustainable water supply in Swedish coastal areas – possibilities and challenges

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  1. Sustainable water supply in Swedish coastal areas – possibilities and challenges Bosse Olofsson Royal Institute of Technology, KTH NGL AnnualMeeting at Äspö 2013-11-07

  2. 50% of the world’s population concentrates to a 60km widecoastalzone • Huge water stress along the coastalzone • Swedish coaststretches >2400km

  3. Climatechange(IPCC 2013) • Locallyhigherprecipitation • >2oC increase in temperature to 2100 • Dry periods occurmoreoften • Longerdry periods • Mostenergy stored in sea • Sea levelrise (>3.2 mm/year) (IPCC 2013)

  4. Swedish climatechanges? Model for precipitation and temperaturechangesuntil 2100 Source: Rossby Center, SMHI 2012 There are severalmodelscenariespointingtowardssimilardirection

  5. Climatechange in Sweden 2050- • Increasedprec.(but at leastbigger variations) • Increasedevapotranspiration • Longer vegetation season • Longer periods of drought • Increasedcompetition of water • Increasedcosts for water treatment

  6. Changednumber of days per year with drough to 2100 Days/year Källa: SMHI 2013

  7. Wewillneed to store water for muchlonger periods than today The question is where?.....

  8. Swedish specificcoastal problems 200 m Bare rock outcrops Small reservoirs Concentration of houses High hydraulicheterogeneity Bad existingsewage systems Rapid flows Water chemical problems (Cl, Rn, U, F) Increasing water demand Fertilization Pollution Attractiveenvironment Coastal erosion

  9. Areas with scarcity of groundwater in sweden (for water supply with sufficientquantity and quality) Clay Till Sand Rock Sand and gravel (SGU 2009)

  10. A bedrock with high storagecapacitybut sensitive to seawaterintrusion

  11. From top • From side Shearfracture, partlycoated with minerals • The flow possibility of eachfracturedepends on its • genesis • weatheringconditions • mineral filling • rock stresses

  12. Kinematicporosity in different units Bedrock (0.001-0.05%) Well Clay (0.01-0.1%) Well Till (3-5%) Sand (10-40%) Water (100%) Shear fractures 0.001 - 0.05%

  13. Usually we have limited amount of data, especially high quality data • Uses data from • SGU • SMHI • Lantmäteriet

  14. Example of method for increasing the storage Groundwaterrecharge Drainingtubes Bentonite or plastic liner Dug or drilled well Bedrock Clay Till or sand and gravel called”groundwaterdams”

  15. Development of methods to clarifysuitableplaces for localization of subsurface dams Figure 10. Vulnerable zones (encircled) of Boda-Kalvsvik. Based on water balances and aquiferdeliniation in GIS Topographic Wetness Index (TWI) of Boda-Kalvsvik.

  16. Shortage of groundwater, often leads to deteriorationof groundwater quality • Natural geologicalconditions (e.g. metals, pH, radon, alkalinity…) • Inducedchanges(e.g. salinization) • Pollutants (e.g. cadmium) NO3- Rn Na+ Bacteria Cl- Baltic Sea Rn Cl- Na+ Na+ Cl-

  17. Älgö – Stockholm archipelago Water supply Sewage What is the impact from sewage infiltration?

  18. Soilvolume for infiltration for 1 family (ca 500 l/d) Sand (1-2 m3/d) Till (15-20 m3/d) => big problems in exploitational areas. Howcanwe get turnover time of 60 days? Bedrock (1500-2000 m3/d)

  19. Example 1: Nitrate and ammonium Development of a risk assessment scenario at e.gTynningö Ramsö Tynningö

  20. Vulnerability of nitrate pollution of wells

  21. Example 2: Radon, radium and uranium N=5666 Stockholm county

  22. A high correlationobservedbetweenmedian radon concentration and median RV- value. Testing of method(2209 wells) RV-value (median value) Each point is representative of an area of 25 x 25 km2

  23. Prediction of radon content in drilled wellsusing GIS RV-method Prediktion 2209 wells FRV > 0 : Low risk -5 < FRV < 0 : Medium risk FRV < -5 : High risk

  24. Example 3: Predictionof groundwaterquality in private wells at Gotland (Pirnia & Olofsson 2013)

  25. Prediction of groundwaterquality Based on statisticalanalysis (ANOVA, PCA) usingchemical data, geological and topographical data (Pirnia & Olofsson 2013)

  26. Future research needrelated to water supply in hard rock areas There is a strong need for robust assessmentmethods for planning and decision support locally and regionally • How to estimatestorageand capacitywithoutextensive drilling • How to get a measure of heterogeneity and anisotropywithout extensive test pumping • How to characterizegroundwaterchemicalquality, origin and turnover time with limitedamount of data • How to deliniatebedrockaquifer extension and set boarderconditionswith sparce of data • How to differentiateorigin of compounds with many different sources(chloride, radon, lead, arsenic)

  27. Concludingstrategy • We are convinced that the best way to developmodels and techniques for generalizedestimations of groundwaterresourcesusingsparce of data is to develop and test suchmodelswherethere are lots of data available, such as the NGL (a.o stored in SICADA)

  28. SWICA Sustainable Water in Coastal Areas Thanks

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