DSSAT

The Decision Support System for Agrotechnology Transfer (DSSAT) is a software application program that comprises dynamic crop growth simulation models for more than 42 crops. In Aclimate, DSSAT is used to simulate corn and wheat crops. Like the Oryza component, its inputs are the climatic scenarios of the resampling process and the configuration files of each scenario to be simulated. These configurations are imported (explained in Importing data).

A configuration is a set of files (soil, cultivar, geographic information) linked to a set of climatic scenarios (station/location). For each configuration, a number n of days is simulated. In the case of wheat and maize for Ethiopia, 25 days are simulated at a frequency of 3. That is, 9 days in total are simulated per configuration.

The process begins by loading the identifiers of the station/location, cultivar, soil and the frequency of the simulations. It defines the input directories of the station/location weather settings and scenarios, as well as the output directories. Load the coordinates of the location/station and translate the climate scenarios into the format that the DSSAT models understand. Proceed to copy the configuration files with the climate scenarios and run the simulations. Once the simulations for all days are complete, the final simulation files are used to calculate the risk of water stress and land preparation days. The latter are indicators that have recently been added to the DSSAT crops module.

Finally, the simulation data for each simulated day is extracted and written to a csv file as crop simulation statistics based on planting dates. So there will be a csv file for each configuration.

The following diagram describes the process mentioned above:

The csv file mentioned has the following columns:

CSV columns

Column	Meaning
weather_station	station/location id
soil	soil id
cultivar	cultivar id
start	simulation start date
end	simulation end date

For the ‘measure’ column, the following values are available:

Measure column

Measure	Meaning
yield_0	yield
d_dry	dry days
prec_acu	accumulated precipitation
bio_acu	accumulated biomass
t_max_acu	accumulated maximum temperature
t_min_acu	accumulated minimum temperature
st_ger_boo_w	water stress germination to booting
st_boo_ant_w	water stress booting to anthesis
st_beg_end_gf_w	water stress beginning to end of grain filling
st_ger_boo_n	nitrogen stress germination to booting
st_boo_ant_n	nitrogen stress booting to anthesis
st_beg_end_gf_n	nitrogen stress beginning to end of grain filling
land_pre_day	land preparation days

For each measure the next colums are calculated:

CSV columns statistics

Column	Meaning
avg	average
median	median
min	minimum value
max	maximum value
quar_1	quartile 1
quar_2	quartile 2
quar_3	quartile 3
conf_lower	lower confidence interval limit
conf_upper	upper confidence interval limit
sd	standard deviation
perc_5	5th percentile
perc_95	95th percentile
coef_var	coefficient of variation

Below is an example of what the CSV looks like in Excel:

Below is an example of what the CSV looks like in a plain text viewer: