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Sustainable water supply in Swedish coastal areas – possibilities and challenges Bosse Olofsson Royal Institute of Technology, KTH NGL Annual Meeting at.

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Presentation on theme: "Sustainable water supply in Swedish coastal areas – possibilities and challenges Bosse Olofsson Royal Institute of Technology, KTH NGL Annual Meeting at."— Presentation transcript:

1 Sustainable water supply in Swedish coastal areas – possibilities and challenges Bosse Olofsson Royal Institute of Technology, KTH NGL Annual Meeting at Äspö

2 50% of the world’s population concentrates to a 60km wide coastal zone Huge water stress along the coastal zone Swedish coast stretches >2400km

3 Climate change (IPCC 2013) Locally higher precipitation >2 o C increase in temperature to 2100 Dry periods occur more often Longer dry periods Most energy stored in sea Sea level rise (>3.2 mm/year) (IPCC 2013)

4 Model for precipitation and temperature changes until 2100 Source: Rossby Center, SMHI 2012 There are several model scenaries pointing towards similar direction Swedish climate changes?

5 Climate change in Sweden Increased prec.(but at least bigger variations) Increased evapotranspiration Longer vegetation season Longer periods of drought Increased competition of water Increased costs for water treatment

6 Changed number of days per year with drough to 2100 Källa: SMHI 2013 Days/year

7 We will need to store water for much longer periods than today The question is where?.....

8 200 m Small reservoirs Concentration of houses Bad existing sewage systems Rapid flows Increasing water demand Attractive environment Swedish specific coastal problems Fertilization Pollution Coastal erosion Water chemical problems (Cl, Rn, U, F) Bare rock outcrops High hydraulic heterogeneity

9 Areas with scarcity of groundwater in sweden (for water supply with sufficient quantity and quality) (SGU 2009) Rock TillClay Sand Sand and gravel

10 A bedrock with high storage capacity but sensitive to seawater intrusion

11 Shear fracture, partly coated with minerals From side From top The flow possibility of each fracture depends on its genesis weathering conditions mineral filling rock stresses

12 Bedrock ( %) Till (3-5%) Clay ( %) Water (100%) Sand (10-40%) Well Shear fractures Kinematic porosity in different units %

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

14 Till or sand and gravel Draining tubes Dug or drilled well Bedrock Clay Bentonite or plastic liner Groundwater recharge Example of method for increasing the storage called”groundwater dams”

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16 Figure 10. Vulnerable zones (encircled) of Boda-Kalvsvik. Topographic Wetness Index (TWI) of Boda-Kalvsvik. Development of methods to clarify suitable places for localization of subsurface dams Based on water balances and aquifer deliniation in GIS

17 Na + Cl - Na + NO 3 - Rn Bacteria Baltic Sea Shortage of groundwater, often leads to deterioration of groundwater quality Natural geological conditions (e.g. metals, pH, radon, alkalinity…) Induced changes(e.g. salinization) Pollutants (e.g. cadmium)

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

19 Bedrock ( m3/d) Till (15-20 m3/d) Sand (1-2 m3/d) => big problems in exploitational areas. How can we get turnover time of 60 days? Soil volume for infiltration for 1 family (ca 500 l/d)

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

21 Vulnerability of nitrate pollution of wells

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

23 Testing of method (2209 wells) Each point is representative of an area of 25 x 25 km 2 A high correlation observed between median radon concentration and median RV- value. RV-value (median value)

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

25 Example 3: Prediction of groundwater quality in private wells at Gotland (Pirnia & Olofsson 2013)

26 Based on statistical analysis (ANOVA, PCA) using chemical data, geological and topographical data Prediction of groundwater quality (Pirnia & Olofsson 2013)

27 Future research need related to water supply in hard rock areas How to estimate storage and capacity without extensive drilling How to get a measure of heterogeneity and anisotropy without extensive test pumping How to characterize groundwater chemical quality, origin and turnover time with limited amount of data How to deliniate bedrock aquifer extension and set boarder conditions with sparce of data How to differentiate origin of compounds with many different sources (chloride, radon, lead, arsenic) There is a strong need for robust assessment methods for planning and decision support locally and regionally

28 Concluding strategy We are convinced that the best way to develop models and techniques for generalized estimations of groundwater resources using sparce of data is to develop and test such models where there are lots of data available, such as the NGL (a.o stored in SICADA)

29 Thanks

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