EGU 2014 invited talk (mostly on simulation of ecohydrology) - by Giacomo Bertoldi et al
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This contains the description of the use of GEOtop 2.0 in simulating the ecohydrology of a mountain environment
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Semelhante a EGU 2014 invited talk (mostly on simulation of ecohydrology) - by Giacomo Bertoldi et al
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EGU 2014 invited talk (mostly on simulation of ecohydrology) - by Giacomo Bertoldi et al
- 1. Process-based modeling in alpine catchments Giacomo Bertoldi, Stefano Della Chiesa, Michael Engel, Georg Niedrist, Johannes G. Brenner , Stefano Endrizzi, Matteo Dall’Amico, Emanuele Cordano, Ulrike Tappeiner, Riccardo Rigon. EGU 2014, Vienna, Austria, 28 April – 2 May 2014 Institute for Alpine Environment
- 3. Coupled process based modelling in mountain areas LWatm V D0VI LWsurr 1V SWsurr 1V sTs 4 Shortwave radiation (yellow) Longwaveradiation (red) SWrefl Complex topography Bertoldi et al., J of Hydromet, 2006. s Snow module Endrizzi et al., GMDD, 2014 Zanotti et al., Hydrol Proc, 2004 Water budget Rigon et al., J of Hydromet, 2006. Figures adapted from VIC model (Liang et al., 1994) Energy budget Bertoldi al., Ecohydrol, 2010. Vegetation dynamics Della Chiesa et al., Ecohydrol., 2014 From SHE model (Abbot et al., 1986)
- 4. The GEOtop 2.0 – DV model Rigon et al., JHM, 2006; Endrizzi et al. GMDD, 2014. Processes Dynamic vegetation model (for grasslands) From Montaldo et al., 2005; Della Chiesa et al., 2014
- 6. Application 1: modelling along an elevation gradient Motivation In dry inner‐alpine regions, managed grasslands are irrigated. Climate change raises issues about future water availability. Which are the effects of the elevation gradient on SWE, SWC, ET, grassland productivity? Della Chiesa et al., Modeling changes in grassland hydrological cycling along an elevational gradient in the Alps, Ecohydrology, 2014 .
- 9. Elevation gradient: resultsB2000 mB1500 mB1000 m Simulation extension to 20 year Coupling snow – veg – ET ‐ SWC Water limitation below 1500 m SWC along the year
- 10. Elevation gradient: resultsB2000 mB1500 mB1000 m Coupling snow – veg – ET ‐ SWC SWC along the year Irrigation below 1500 m
- 12. Application 2: land surface temperature Motivation LST is a key variable of the surface energy budget. Improving its estimation in energy budget models can improve fluxes partitioning estimation. Which are the factors controlling LST in mountain environments (i.e. elevation, solar radiation, land cover, soil moisture)? Bertoldi et al., Topographical and ecohydrological controls on land surface temperature in an Alpine catchment, Ecohydrology, 3, 189 – 204, 2010. t E wLSTETLSTHwLSTGLSTR ssn ),()(),()( 4
- 13. Modeling land surface temperature Stubai Valley experimental area (Tyrol, Austria) (Institute of Ecology Innsbruck University) •257 km2, elevation 1000 ‐ 3500 m. • Humid inner‐alpine climate. • Comparison with 60 m LANDSAT LST TIR ETM+ map (13 September 1999, 10.50 AM). • Parameters from field data (Hammerle et al. 2007) and literature for different land cover types (Findell et al. 2007). • One year model spin‐up to reach equilibrium. • Model validation against ground observations. • Leaf Area Index (LAI); Roughness length (z0).
- 20. GEOtop is an Open Source collaborative project and others are invited to bring into new components. https://code.google.com/p/geotop/ Main model developers: Università di Trento; Zurich University (Now Quebec University); Mountain‐eering S.r.l; EURAC research; University of Augsburg KIT. Creating a community. Try it!