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Install

To install the package, open Julia and run:

using Pkg
Pkg.add(url="https://github.com/gabo-di/AquaCrop.jl")

Basic Run

To maintain compatibility, we support the same input file formats used by the original implementation of AquaCrop (v7.2). To specify that this format should be used, call the NormalFileRun function:

using AquaCrop
runtype = NormalFileRun()

Next we must specify where these input files are found. In this case, we use the files in the test directory:

parentdir = AquaCrop.test_dir #".../AquaCrop.jl/test/testcase"
endswith(parentdir, "test/testcase")

Now we are ready to use the basic_run function:

outputs = basic_run(; runtype=runtype, parentdir=parentdir);


isequal(size(outputs[:dayout]), (892, 89))

# output
true

All model results are stored in a collection of dataframes. For example, we can see the harvest dataframe via:

outputs[:harvestsout]

# output
14×11 DataFrame
 Row │ RunNr  Nr     Date        DAP    Interval   Biomass           Sum(B)    ⋯
     │ Int64  Int64  Date        Int64  Quantity…  Quantity…         Quantity… ⋯
─────┼──────────────────────────────────────────────────────────────────────────
   1 │     1      0  2014-05-21      0      0.0 d      0.0 ton ha⁻¹      0.0 t ⋯
   2 │     1      1  2014-07-13     54     54.0 d  4.78668 ton ha⁻¹  4.78668 t
   3 │     1      2  2014-08-31    103     49.0 d  3.08189 ton ha⁻¹  7.86857 t
   4 │     1   9999  2014-11-01      0      0.0 d      0.0 ton ha⁻¹  9.17245 t
   5 │     2      0  2015-05-01      0      0.0 d      0.0 ton ha⁻¹      0.0 t ⋯
   6 │     2      1  2015-06-20     51    232.0 d  5.69329 ton ha⁻¹  5.69329 t
   7 │     2      2  2015-07-26     87     36.0 d  3.44309 ton ha⁻¹  9.13638 t
   8 │     2      3  2015-08-30    122     35.0 d  1.62555 ton ha⁻¹  10.7619 t
   9 │     2   9999  2015-10-25      0      0.0 d      0.0 ton ha⁻¹  11.9474 t ⋯
  10 │     3      0  2016-05-07      0      0.0 d      0.0 ton ha⁻¹      0.0 t
  11 │     3      1  2016-06-15     40    235.0 d  5.05947 ton ha⁻¹  5.05947 t
  12 │     3      2  2016-07-20     75     35.0 d  3.81457 ton ha⁻¹  8.87405 t
  13 │     3      3  2016-08-29    115     40.0 d  2.28277 ton ha⁻¹  11.1568 t ⋯
  14 │     3   9999  2016-10-29      0      0.0 d      0.0 ton ha⁻¹  12.5786 t
                                                               5 columns omitted

Similarly with the daily output dataframe outputs[:dayout], the result of the whole season dataframe outputs[:seasonout], the information for the evaluation dataframe outputs[:evaldataout], and the logger information in outputs[:logger]. Note the output dataframes correspond to output files in a run of AquaCrop Fortran.

You can write the output in csv file using the write_out_csv function

io = IOBuffer() 

write_out_csv(io, outputs[:seasonout]) # instead of io  you can use a filename like "example.csv"

io

# output
IOBuffer(data=UInt8[...], readable=true, writable=true, seekable=true, append=false, size=925, maxsize=Inf, ptr=926, mark=-1)

Using TOML files

If you prefer to use TOML and CSV files for configuring the input, then use the function TomlFileRun, as in the following example:

runtype = TomlFileRun();
parentdir = AquaCrop.test_toml_dir  #".../AquaCrop.jl/test/testcase/TOML_FILES"

outputs = basic_run(; runtype=runtype, parentdir=parentdir);

isequal(size(outputs[:dayout]), (892, 89))

# output

true

For more detailed examples, see the user guide.