Egu talk on EcoHydrology by Brenner et al.

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Modeling impacts of climate change on evapotranspiration and soil
moisture spatial patterns in an alpine catchment.

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Egu talk on EcoHydrology by Brenner et al.

  1. 1. Modeling impacts of climate change on evapotranspiration and soil moisture spatial patterns in an alpine catchment. Johannes Brenner1,2, Giacomo Bertoldi1, Stefano Della Chiesa1, Georg Niedrist1, Ulrike Tappeiner1,3, and Axel Bronstert2 1Institute for Alpine Environment, EURAC research, Bolzano, Italy. 2Institute for Earth and Environmental Sciences, University of Potsdam, Germany. 3Institute of Ecology, University of Innsbruck, Austria 1
  2. 2. Introduction General Motivation • Mountains Region are considered particularly vulnerable to CC 1, esp. considering the alterations of the water cycle 2 • Complex topography  scale vs. computational effort Aims • temporal & spatial investigation of climate change impact on evapotranspiration and soil moisture in a dry alpine valley • Identify topographic/landcover characteristics of esp. vulnerable regions 1 Brunetti et al. (2006). Temperature and precipitation variability in Italy in the last two centuries from homogenised instrumental time series. International Journal of Climatology, 26(3), 345–381. 2 Bates et al. (2008). Climate Change and water. IPCC Technical Paper VI (p. 214). Geneva, Switzerland: IPCC Secretariat. Retrieved from http://www.ipcc.ch 2
  3. 3. Study area 3
  4. 4. Study Area - Climate Climate Diagrams for the period 1990-2010 • Dry inner-alpine valley • Climate zones: Temperate – boreal - polar/alpine • No precipitation station above 2100 m 4
  5. 5. Methods • RCM ensemble based on SRES A1B (ESEMBLES project)1 • Ctrl: 1990-2010, Scen2100: 2080-2100 • ∆ approach (30 day moving average) • ∆ change signals at daily scale for air temperature and precipitation Downscale Technique TopoSUB Tool GEOtop Model Simulation set-up 1 Van der Linden, P., & Mitchell, J. (2009). ENSEMBLES: Climate change and its impacts at seasonal, decadal and centennial timescales (p. 160). Exeter, UK. Retrieved from http://ensembles-eu.metoffice.com/docs/Ensembles_final_report_Nov09.pdf 5
  6. 6. Methods Downscale Technique TopoSUB1 Tool GEOtop Model Simulation set-up 1 Fiddes, J., & Gruber, S. (2012). TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales. Geoscientific Model Development Discussions, 5(5), 1245–1257. 2 Hartigan, J. A., & Wong, M. A. (1979). A K-Means Clustering Algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), 100–108. Clustering • sampling of most important aspects of land surface heterogeneities and land cover • K-Means clustering algorithm 2 • based on 20m grids GEOtop • 1-dimensional simulations for cluster centroids Mapping • Crisp memberships 6
  7. 7. Methods • Distrubuting meterological input • Energy and mass conservation • Soil Volumetric Water Content • Actual Evapotranspiration • Snow Accumulation & Snow melt • Application in Mountain Areas Downscale Technique TopoSUB Tool GEOtop1,2 Model Simulation set-up 1 Rigon et al. (2006). GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets. Journal of Hydrometeorology, 7(3), 371–388. 2 Endrizzi et al. (2013). GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects. Geoscientific Model Development Discussions, 6(4), 6279–6341. 7
  8. 8. Methods • Simulation calibration/performance • 2010/2011 (Altitudinal Transect) • Multiple Point Simulation (300 cluster centroids) • baseline simulation 1990-2010 • 7 scenario simulation 2080-2100 Downscale Technique TopoSUB Tool GEOtop Model Simulation set-up 8
  9. 9. Altitudinal transect Station B20 - 2000 m Station B15 - 1500 m Station B10 - 1000 m Calibration Station Validation Station Validation Station 9
  10. 10. Results Calibration of soil parameters at B15 10 Station RMSE Θ5cm (vol %) RMSE Θ20cm (vol %) RMSE ETA (mm/month) B20 9 7 -- B15 9 11 16 B10 9 7
  11. 11. Results Climate Change Projections for the Venosta Valley 11 scen2100 DJF MAM JJA SON ∆P (%) +14 +1.7 -13 +16 ∆T (°C) +3.1 +3.3 +4.2 +3.2
  12. 12. Results Climate Change Impact – Snow Cover Duration Baseline Simulation ∆% (scen2100-ctrl) 12 Mean abs. change: -40 days Major impact in forest belt: -60 days (9 weeks)
  13. 13. Results Climate Change Impact – Evapotranspiration Baseline Simulation ∆abs (scen2100-ctrl) 13
  14. 14. Results Climate Change Impact – Evapotranspiration ∆abs (scen2100-ctrl) 14 ChangeinMeanAnnualETA(mm) Aspect Forest: South-east Major impact Pasture: East Bare Soil: South-east Grassland & Agriculture: No effect of aspect
  15. 15. Results Climate Change Impact – Seasonal Evapotranspiration Scen2100 ensemble meanBaseline mean 15
  16. 16. Results Climate Change Impact – Seasonal Evapotranspiration - Winter 4 14 + 250% 16
  17. 17. Results Climate Change Impact – Seasonal Evapotranspiration - Spring 48 69 + 43% 17
  18. 18. Results Climate Change Impact – Seasonal Evapotranspiration - Summer 131 149 + 12% 18
  19. 19. Results Climate Change Impact – Seasonal Evapotranspiration - Fall 53 62 + 17% 19
  20. 20. Results Climate Change Impact – Seasonal Evapotranspiration 4 14 + 250% 48 69 + 43% 131 149 + 12% 53 62 + 17% 20
  21. 21. Results Climate Change Impact – Soil Water Content – Severe Water Stress 1 Jasper et al. (2006). Changes in summertime soil water patterns in complex terrain due to climatic change. Journal of Hydrology, 327(3-4), 550–563. doi:10.1016/j.jhydrol.2005.11.061 21 Critical soil moisture level is refered to plant available water 1
  22. 22. Change in Nr. of days with Severe Water Stress in 20cm soil depth ChangeinActualEvapotranspiration(mm) Results Climate Change Impact – Soil Water Content – Severe Water Stress 22 1000 – 1400 m a.s.l South - East
  23. 23. Conclusion & Outlook 23 Conclusion • General decrease in snow cover duration which drive major increase in evapotraspiration in winter and spring • Specific sites, which are already characterized by water stress, show an increase in drought days Future work • Sensetivity of lateral water fluxes • Dynamic vegetation • Improve soil parameterization
  24. 24. Acknowledgment GEOtop is an Open Source collaborative project www.geotop.org Main model developers: Università di Trento; Zurich University; Mountain-eering S.r.l; EURAC research This study is mainly founded by the projects “HiResAlp” and “HydroAlp” from the South Tyrol research found. We hereby would like to thank: S. Endrizzi, University of Zurich, for the GEOtop model code development. 24
  25. 25. Results Climate Change Impact – Soil Water Content – Severe Water Stress 25 1100 – 1500 m
  26. 26. Results Climate Change Impact - Altitude Transect 26
  27. 27. Results Climate Change Impact - Altitude Transect 27
  28. 28. Results calibration at B15 – Evapotranspiration RMSE = 16.4mm/month, BIAS = -29mm, PBIAS = -5.3% 28
  29. 29. Results Calibration (B15) and Validation (B10, B20) – Vol. Soil Water Content RMSE = 0.09, BIAS = 0.04, inSD = 32% RMSE = 0.07, BIAS = -0.06, inSD = 37% RMSE = 0.09, BIAS = 0.02, inSD = 40% RMSE = 0.11, BIAS = -0.06, inSD = 50% RMSE = 0.09, BIAS = -0.02, inSD = 24% RMSE = 0.07, BIAS = -0.11, inSD = 19% VALIDATIONB20VALIDATIONB10CALIBRATIONB15 5cm Soil Depth Observation (±SD) & Simulation 20cm Soil Depth 29

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