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Results:

• 31. Hare-2011-ParticipatoryModelling

  are labelled according to the geographical area of application. Examples such as Zürich and Hase II have already been reviewed and categorized in Hare et al. (2003) and Bots and van Daalen (2008), respectively. The entire Iskar process, of which Iskar (Phase I) is a part, has been categorized by Barreteau et al. (2010). All are included in this review to provide alternative analytical perspectives /media/loftslag/Hare-2011-ParticipatoryModelling.pdf

• 32. 2011_005

  in Appendix III. 4.2 Preferred layout of the network The Iceland CGPS network has been installed mostly through research grants of different projects with various collaborators. As a result the network coverage is uneven around the country. Areas outside of the active plate boundary have hardly any GPS stations and the network coverage is lacking for large part of the plate boundary, many /media/vedurstofan/utgafa/skyrslur/2011/2011_005.pdf

• 33. raisanen_ruosteenoja_CES_D2.2

  Model Institution BCCR-BCM2.0 Bjerknes Centre for Climate Research, Norway CGCM3.1 (T47) Canadian Centre for Climate Modelling and Analysis CGCM3.1 (T63) same as previous CNRM-CM3 Météo-France CSIRO-MK3.0 CSIRO Atmospheric Research, Australia ECHAM5/MPI-OM Max Planck Institute (MPI) for Meteorology, Germany ECHO-G University of Bonn and Model & Data Group, Germany; Korean Meteorological Agency GFDL /media/ces/raisanen_ruosteenoja_CES_D2.2.pdf

• 34. 2013_001_Nawri_et_al

  and a pressure of 1013.25 hPa. In the case of Iceland, the climate deviates significantly from these standard atmospheric conditions. Additionally, terrain elevation varies considerably across the island. Therefore, seasonal and annual differences in air density from the standard value, as well as spatial variability, need to be taken into account. Approximate air density can be calculated by assuming /media/vedurstofan/utgafa/skyrslur/2013/2013_001_Nawri_et_al.pdf

• 35. Huntjens_etal-2010-Climate-change-adaptation-Reg_Env_Change

  can be found in Huntjens et al. (2007), Chapter 4 of NeWater Deliverable 1.7.9a (http://www.newater.info). Climate change adaptation in European river basins 265 123 interactions, by private and public actors, to achieve adaptation and to enhance the capacity of processes, institutional arrangements and actors to adapt to future environmental changes (Huitema et al. 2009). Adaptive governance /media/loftslag/Huntjens_etal-2010-Climate-change-adaptation-Reg_Env_Change.pdf

• 36. ces-oslo2010_proceedings

  change over the North Atlantic and in some simulations also for Iceland. In all areas, including the North Atlantic and Iceland, a clear climate change signal compared to the spread between the simulations is seen. The standard deviation calculated from 17 of the simulations are less than 1°C in all areas apart from Iceland where it reaches between 1 and 2°C and in parts of the Barents Sea where /media/ces/ces-oslo2010_proceedings.pdf

• 37. Water_resources_man_Veijalainen_etal

  range 90% 93.15–93.29 93.27–93.36 75.43–75.56 94.59–94.71 2040–2069 range 90% 93.09–93.31 93.28–93.40 75.41–75.56 94.72–94.83 2070–2099 range 90% 93.02–93.32 93.24–93.43 75.38–75.61 94.79–94.91 Lowest water level (in the 30 year period) (m) Reference period 92.86 92.72 75.20 94.27 2010–2039 range 90% 92.62–92.91 92.96–93.13 75.24–75.33 94.47–94.59 2040–2069 range 90% 92.55–92.82 92.88–93.12 75.19 /media/ces/Water_resources_man_Veijalainen_etal.pdf

• 38. 2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343

  e in relatio n to climat echang eadapt ation .X ,X X ,XX X is a ge n era lguid eo n th e relativ e imp ortanc e leve lo fth e sourc es , alth oug h it mus tb e em phasise d tha tth e imp ortanc e o fth e indi vidua lsou rce s o fun certaint y is co n tex tspe cifi c St ep si n cl im at e ch an ge ad ap tat io n an al ys es (ch ain in u n ce rta in ty ca sc ad e, Fi g. 2) So ur ce s o fu n ce rta /media/loftslag/2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343.pdf

• 39. Public-Choice-2012---Teyssier---Inequity-and-risk-aversion-in-sequential-public-good-games

  individuals act like homo-œconomicus agents (see for example Andreoni 1988; Berg et al. 1995; Camerer 2003; Forsythe et al. 1994; Isaac et al. 1984). Recent developments in public-choice theory have taken a behavioral approach to broaden the analysis of collective action. The introduction of social preferences, such as altruism, inequity aversion or trust, may mean that optimal collective choices /media/loftslag/Public-Choice-2012---Teyssier---Inequity-and-risk-aversion-in-sequential-public-good-games.pdf

• 40. Daniell_etal-2010

  and evaluating impacts (see also Swallow et al. 2001, van Ast and Boot 2003). METHODS AND DATA This article is based on empirical data that originated from the analysis of the participatory exercise in the Dhuenn basin. The strong involvement of researchers from two research projects (NeWater[1] and ACER[2]) linked by a joint case study led to the variety of sources available for exploration, including /media/loftslag/Daniell_etal-2010.pdf