in snow cover duration
between 25% warmest and 25% coldest years +1.7°C
Catchment elevation (m.a.s.l)
Catchment elevation (m.a.s.l)
D
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t
i
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n
m
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t
h
barb2right -40 %
Magnitude difference
100(Warmest - Coldest)/Coldest
barb2right -37 days
Mean yearly maximum snowmelt rate
Timing difference
between 25% warmest and 25% coldest years
+1.7°CCatchment elevation (m.a.s.l)
Catchment
/media/ces/Crochet_Philippe_CES_2010.pdf
• MetNo-HIRLAM-HadCM3,
• SMHI-RCA3-BMC with the SRES A1B.
The climate model results were downscaled using
statistical downscaling method:
Sennikovs, J. and Bethers, U. 2009. Statistical downscaling
method of regional climate model results for hydrological
modeling. 18th World IMACS / MODSIM Congress, Cairns,
Australia 13-17 July 2009 http://mssanz.org.au/modsim09
Observed, modeled
/media/ces/Kurpniece_Liga_CES_2010.pdf
100
15 17 19 21 23 25
Mean annual peak runoff (mm/day)
P
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g39g72g79g87g68g3g70g75g68g81g74g72g3
g40g80g83g76g85g76g70g68g79g3g68g71g77g88g86g87g80g72g81g87
Percentage change in 200-year flood
Uncertainty – Relative magnitude of
sampled s urces
N = 115
GCM/RCM = 50
EA/DC = 38
HBV = 27
• Differences in GCM/RCM
tend to be more significant
in inland
/media/ces/Lawrence_Deborah_CES_2010.pdf
............................................................................... 20
Räisänen, J.
Probability distributions of monthly-to-annual mean temperature and precipitation in a changing climate ......... 22
Nikulin, G., Kjellström, E., Hansson, U., Strandberg G. and Ullerstig A.
Nordic weather extremes as simulated by the Rossby Centre Regional Climate Model: Model evaluation and
future projections
/media/ces/ces-oslo2010_proceedings.pdf
of market organisation alternatives
26.8.2011Adriaan Perrels/IL 10
Cost-benefit analysis – the basics 3
Simple example: despite positive IRR still cash flow challenge years 1 - 8
CBA example - initial investment 100; interest and discount 5%;
operational cost +5%/y; benefits +10%/y; IRR = 7.4%
-20
-10
0
10
20
30
40
50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
years
m
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y
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it
s
writing off
finance
/media/loftslag/Perrels-CBA.pdf
for widespread adoption in the water sector. Environmental Policy and Governance. DOI:
10.1002/eet.590
Kaner S (2007) Facilitator’s Guide to Participatory Decision-Making. Jossey-Bass: San Francisco.
Cooke B, Kothari U (2007) Participation: the new tyranny? (4th edition) Zed Books: New York.
Daniell KA, White I, Ferrand N, Ribarova IS, Coad P, Rougier J-E, Hare MP, Jones NA, Popova A, Rollin D
/media/vedurstofan/PhD_course-Programme_26Aug2011-final.pdf
and our intention is to run these models dur-
ing times of hazardous events and even on a daily
basis to further improve monitoring.
Avalanche monitoring has progressed. The em-
phasis is now on improving our services, especially
to the Icelandic Road and Coastal Administration
with regard to transport. The reason is that com-
munity structure has changed considerably in recent
years and the need
/media/vedurstofan/utgafa/arsskyrslur/VED_AnnualReport-2013_screen.pdf
a systematic com-
parison of results to observed precipitation has been carried out. Un-
dercatchment of solid precipitation is dealt with by looking only at
days when precipitation is presumably liquid or by considering the
occurrence and non-occurrence of precipitation. Away from non-
resolved orography, the long term means (months, years) of observed
and simulated precipitation are often
/media/ces/Paper-Olafur-Rognvaldsson_92.pdf
and possibly the stake-
holders at different phases of the modelling project.
Many QA guidelines exist such as Middlemis (2000) and
Van Waveren et al. (1999). The HarmoniQuA project (Schol-
ten et al., 2007; Refsgaard et al., 2005a) has developed a com-
prehensive set of QA guidelines for multiple modelling
domains combined with a supporting software tool, MoST
(downloadable via http
/media/loftslag/Refsgaard_etal-2007-Uncertainty-EMS.pdf