Climate change and availability of water resources for Lima

Transkript

1 Climate change and availability of water resources for Lima András Bárdossy Lima Marzo

2 Engineers and the future Knowledge about Past Design for Future Lima Marzo

3 Engineers? Knowledge about Past Design for Future Lima Marzo

4 Climate Change and Engineers Knowledge about Past Design for Future For the anthropogenic system Future development can be forecasted using models For the natural system Past can be transferred to the Future statistically Water management strategies are based on this principle But this is not valid under climate change What to do now? Lima Marzo

5 Objective: Water supply for Lima for the future Future <> Past Demand due to increase in population Availability due to natural changes (CC) Research question: How much water will be available under climate change conditions? Lima Marzo

6 Discharge (m 3 /s) Annual cycle Sheque+Tamboraque Month Lima Marzo

7 Mean discharge (m 3 /s) Fluctuation of Annual and August means Lima Marzo

8 Who tells us the Future? Past through observed changes Continuing trends? (ex. Glaciers) General Circulation Models Developed from Weather Forecasting Models Rough resolution (space) Limited availability Mostly monthly values Selected time slices (e.g ) Lima Marzo

9 Stuttgart? Lima Marzo

10 Problems Resolution Cannot resolve small scale variability Rimac precipitation changes with elevation Scenario Assumptions on economic development Model accuracy Do models represent reality? Can models quantify the effects of changes? Lima Marzo

11 Climate change in Past and Future The changes will increase in the future. Changes depend on Emission scenarios. A2 A1B B1 1 0 No Emissions Lima Marzo

12 Real Emissionen versus Scenarios A2 B1 Present emissions are exceed all IPCC-Scenarios. Lima Marzo (Raupach 2007, PNAS, 104, )

13 Scales? Downscaling precipitation and temperature Rainfall runoff Modeling What is important for downscaling: Precipitation amounts Annual sums Annual cycle Gradient (W-E) Intense events (Landslides) Temperature Evapotranspiration Snow Lima Marzo

14 Precipitation Change (mm/day) CC and control precipitation 10 8 HADCM3 GFDL R30 CGCM ECHAM Month Lima Marzo

15 Precipitation Change (mm/day) Absolute changes 2 1 CGCM HADCM3 GFDL R30 ECHAM Month Lima Marzo

16 Precipitation Change (%) Relative changes CGCM HADCM3 GFDL R30 ECHAM Month Lima Marzo

17 Do we know the present conditions? Direct observations Few stations high variability Short series with missing data Global products GPCC GPCP University of Delaware datasets Assessment of the amounts using a combination Spatial considerations Interpolation Uncertainty assessment for modeling Lima Marzo

18 Modeling Using a monthly water balance model Spatial resolution according to available precipitation information Conceptualization according to information Use of Landsat images for vegetation cover MODIS (Aqua and Terra) for snow ice Should enable the calculation of different alternatives Management CC scenarios Lima Marzo

19 Conclusions The problem is similar everywhere even if the questions are different Work in progress We need more information of the catchments Precipitation Discharge GCMs disagree Downscaling of different scenarios Finding thresholds Lima Marzo

20 Thank you for your attention! Lima Marzo