Changes in Plant Phenology and Physiology under Climate Change and Related Impacts on Regional Water Resources

Transkript

1 Changes in Plant Phenology and Physiology under Climate Change and Related Impacts on Regional Water Resources Fred F. Hattermann, Frank Wechsung, Shaochun Huang & Valentina Krysanvoa Potsdam Institute for Climate Impact Research

2 Outline Introduction Data and Methods The model system Data Results Changes in plant phenology Changes in plant physiology Combined effects Conclusions

3 Why is it important to consider vegetation processes under climate change? Flow regime is entirely driven by temperature / Evapotranspiration evapotranspiration! Avarage [mm] Precipitation 20.0 Runoff month Hydrological Regime in a Central European River Basin

4 Introduction Evapotranspiration temperate climate = F(temperature, vegetation) Temperature increase Vegetation dynamics Evapotranspiration Runoff

5 Introduction Three main vegetation processes: 1. Phenology (seasonal timing) 2. Physiology (e.g. stomata processes) 3. Land use change (e.g. intensification)

6 Introduction How important are CO 2 related effects under climate change for water resources management? -> Contradicting results: Gedney et al. 2006, Nature: Global change: The water cycle freshens up -> water using efficiency increased over the last century due to increase in CO 2 concentrations Gerten et al. 2008, Geophys. Res. Letters: Causes of change in 20th century global river discharge -> CO 2 effect overestimated, other plant related effects and precipitation more important

7 Introduction How important are phenological processes under climate change for water resources management? Frankfurt, FAZ: In 2008, for the first time in history two grain harvests within one year have been recorded in Germany (1 st July 3, 2 nd December 11). Farmer: I had a look into my calendar and thought, yes, a second harvest is possible!"

8 How important is land use change? By 2060, 9 billion people, increasing welfare, bio-fuel production competes with food production (Müller et al Gl Biogeochem Cyc)

9 Outline Introduction Data and Methods The model system Data Results Changes in plant phenology Changes in plant physiology Combined effects Conclusions

10 PIK Model System

11 SWIM: - is based on SWAT 1992, was further developed by Valentina Krysanova for investigation of climate and land use change impacts; - Vegetation processes are simulated using the EPIC approach (Williams et al. 1984); - CO 2 effects are simulated following Krysanova and Wechsung 2002, changed to account also for natural vegetation; - Cropping management has been changed to allow for optimization under climate change (increase of the vegetation period); - Climate change and land use scenarios were derived following Hattermann et al

12 Model regions Arable land Forest Grassland Elbe basin Ems basin Gauge stations

13 Data 1 climate data Acrobat-Dokument Mean precipitation Trend in precipitation Data: Wodinski, Gerstengarbe and Werner, PIK Potsdam

14 DATA 2 spatial data Soils -> BUEK 1000 (2007): ~144 soil types; climate regions; forest soils -- disturbed soils; Land use -> Corine LandUse classification: originally 44 land use classes; Aggregated to 15 classes; Elevation -> resolution ~100 m; Subbasins -> UBA 2004;

15 Calibration 1 avarage river discharge Ems observed simulated Elbe observed simulated m 3 /s m 3 /s Average day Average day Huang, Hattermann, Krysanova 2009 (see presentation by S. Huang)

16 Calibration 2 crop yields Average crop yield in the districts (Statistics) Average potential crop yield (Simulation) <40 dt/ha

17 Outline Introduction Data and Methods The model system Data Calibration Results Impacts without changes in plant processes Changes in plant phenology Changes in plant physiology Combined effects Conclusions

18 Results without changing vegetation processes Climate change impact on Elbe flow (refence , scenario , 100 realizations) Discharge [m 3 s -1 ] Mean day Hattermann et al. 2008, see also presentation by S. Huang on Friday

19 Changes in flow regime (seasonality) under climate change With increase in temperature Discharge Without increase in temperure Jan. Mar. May Jul. Sep. Nov.

20 Runoff under scenario conditions: maritime climate (river Ems) reference phys phen phen_phys Discharge m 3 s Average runoff summer (J,A,S) in m 3 s original phys phen phen_phys Average day

21 Runoff under scenario conditions: continental climate (river Elbe) reference phys phen phen_phys Discharge m3 s Average runoff summer (J,A,S) in m 3 s original Average day phys phen phen_phys

22 Changes in phenology ( compared to currend condtions) LAI future LAI current conditions LAI Share of arable land having two yields [%] year

23 Outlook: land use change Evapotranspiration Groundwater recharge [mm] ETa ETint ref ETa EText lib [mm] GWRint ref GWRext lib month month Effects of land use change on water resources: intensification versus extensification (Elbe basin)

24 Summary and conclusions The increasing water use efficiency of the vegetation in Central Europe due to higher CO 2 concentrations cannot compensate the climate change impact on the water resources under continental conditions; However, land use efficiency can increase because of changes in plant phenology (longer vegetation period) in areas, where water availability is sufficient; The results differ from region to region mostly because of the regional specific manifestation of climate change; More investigations on feedbacks climate hydrology vegetation are necessary!

25 Thank you very much!

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28 PIK Modellsystem Land use change Climate change Regional Partners 1 ECHAM5 Global Climate STAR / CCLM Regional Climate Models Regional Global Water Resources Management Agro- forestry 2 SWIM 1) Wasserresourcen und Extremereignisse 2) Changes in Vegetation dynamics Multiple Realizations Landscape

29 Gliederung Einführung Daten und Methoden Das Modellsystem Datengrundlage Erste Ergebnisse Modellkalibrierung und -analyse Wasserhaushalt unter Szenariobedingungen Ausblick

30 Naturräume in der Elbe

31 Das Modell SWIM (Soil and Water Integrated Model) Climate: solar radiation, temperature, & precipitation Klima: Strahlung, Temperatur & Niederschlag Hydrological cycle Soil profile A Shallow groundwater B C Crop/vegetation growth LAI Biomass Roots Wasserkreislauf Bodenprofil Pflanzenwachsum Nitrogen cycle B LAI C Biomasse Flaches Wurzeln Grundwasser N-NO 3 N o-ac N o-st N Tiefes res Grundwasser A Landbedeckung Landnutzung Phosphorus cycle P lab P m-ac P m-st Stickstoffkreilauf N-NO 3 N o-ac N o-st N res Phosphorkreislauf P lab P m-ac P m-st P org P res Deep groundwater P org P res Elbe River Basin Brandenburg Land use pattern & land management for application in river basins and at the regional scale

32 Gliederung Einführung Daten und Methoden Das Modellsystem Datengrundlage Erste Ergebnisse Modellkalibrierung und -analyse Wasserhaushalt unter Szenariobedingungen Ausblick

33 Kombination von Wasserdargebot und Wassermanagement SWIM: Wasserdargebot WBalMo: Wassermanagement Bilanzprofile Fluesse Seen Bundeslaender Feuchtgebiete Module Mulde Saale Bode Droemling Weisse Elster Elbeschlauch Schwarze Elster Havel Untere Elbe (Conradt et al. 2006) (Koch et al. 2009)

34 Änderungen im Abfluss der Boode im Szenario A1b Periode Periode

35 Räumliche disaggregation in SWIM Einzugsgebiet Teileinzugsgebiete Hydrotope Flusslauf (Wasser, N, P, Sedimente) Wasser-, N-, P- Kreisläufe, Pflanwachstum Zusammen- Führung der lateralen Flüsse

36 Lokale Wasserbilanz in Potsdam: Niederschlag in Potsdam ~600mm Verdunstung in Potsdam ~500mm Der Rest (~100 mm) fließt über die Flüsse zum Meer Daraus folgt: eine Niederschlagsänderung von 10% des Niederschlags oder der Verdunstung entspricht ca. 50% des Abflusses. (25mm/a Niederschlag / Verdunstung entsprechen ~110m 3 /s Abfluss am Elbepegel Neu Darchau)

37 Beobachtete Klimatrends in den letzten Jahrzehnten: Großwetterlagen in Europa Häufigkeit Häufigkeit (11-Jahre gleitendes Mittel) der Großwetterlagen vom Typ West-Zonal und Nord, Ost, Nordost, Südost für Dez. & Jan., Westerly-zonal (normalerweise feucht) North, East, Northeast, Southeast (normalerweise trocken) (Bárdossy, personal communication, s. Bronstert & Kundzewicz 2007)