Transcript Prezentace aplikace PowerPoint

DECISSION SUPPORT SYSTEM
PERUN
lecture
AGRIDEMA – Vienna
2005
Miroslav Trnka
Contributions from: Martin Dubrovský, Joseph
Eitzinger, Jan Haberle, Zdeněk Žalud
PERUN based applications:
PERUN – decision support system
seasonal analysis (1 location, 1 crop)
multi-seasonal analysis at one location
+
multi-site analysis
sensitivity analysis – weather, soil, crop etc.
probabilistic yield forecasting
climate change impact analysis
PERUN sensitivity analysis:
PERUN sensitivity analysis:
Sensitivity analysis:
3 parameters are varied: soil - station - RDmax
PERUN
probabilistic seasonal crop yield
forecasting
seasonal crop yield forecasting
1. construction of weather series
seasonal crop yield forecasting
2. running the crop model
weather forecast is given in terms of:
a) expected values valid for the forthcoming days
(e.g., first day/week: 12±2 °C, second day/week: 7±3 °C, …)
b) increments with respect to long-term means
(1st day/week/decade:
2nd
temperature = + 2 C above normal;
precipitation = 80% of normal;
day/week/decade: ….., …. )
crop yield forecasting at various days of the year
probabilistic forecast <avg±std> is based on 30 simulations
input weather data for each simulation =
[obs. weather till D−1] + [synt. weather since D ~ mean climatology)
a) the case of good fit between model and
observation
crop
year
emergence day
maturity day
observed yield
model yield
=
=
=
=
≈
≈
spring barley
1999
122
225
4700 kg/ha
4600 kg/ha
(simulated with
obs. weather series)
enlarge >>>
crop yield forecasting at various days of the year
a) the case of good fit between model and observation
crop yield forecasting at various days of the year
b) the case of poor fit between model and observation
indicators
task for future research: find indicators of the crop
growth/development (measurable during the growing
period) which could be used to correct the simulated
characteristics, thereby allowing more precise crop
yield forecast
Spatial assessment – regional level :
Regional yield forecast
Climate change
impact on crop growth
Mean yields in the
CR:
a) potential yields
b) water-limited yields
WATER LIMITED YIELD
CO2 = present
[indirect effect of CO2]
CSIRO(hi)-333
HadCM(hi)-333
present-333
ECHAM(hi)-333
NCAR(hi)-333
Mean yields in the
CR:
a) potential yields
b) water-limited yields
Water limited yield: combined effect of CO2
now~333L
now~535L
A-hi~535L
E-hi~535L
H-hi~535L
N-hi~535L
PERUN based applications:
Now:
description of the PERUN interface (Martin)
distribution of the instalation CDs
Afternoon session:
seasonal analysis (1 location, 1 crop)
multi-seasonal analysis at one location
sensitivity analysis – weather, soil, crop etc.
probabilistic yield forecasting
climate change impact analysis
Need help?
We will be around during lunch….
OR at– [email protected]