This module requires Gfortran and should be run on a UNIX based OS. If you are on Ubuntu, you can install some utilities like this:

    sudo apt-get install build-essential gfortran wget

1. Create new venv and Install all the dependencies:

    conda create -n testsoilapis python=3.7
    conda activate testsoilapis
    pip install -r https://raw.githubusercontent.com/eusojk/soil_apis/master/requirements.txt

2. Fix GDAL's build errors with conda-forge:

    conda install -c conda-forge gdal

3. Finally install module:

    pip install https://github.com/eusojk/soil_apis/blob/master/soilapis.zip?raw=true

4. Clone this project:

    git clone https://github.com/eusojk/soil_apis/

5. Run the executable to compile the required fortran scripts:

    bash compilef90.sh 

6. Still in your soil_apis directory, download the soilproperties file and unzip it:

    wget https://www.dropbox.com/s/41acfpzh782a2kh/soilproperties.zip
    unzip soilproperties.zip

7. The hierarchy of the soilproperties directory should like this:

The countries currently supported are:

• Cambodia (KHM)
• Laos (LAO)
• Myanmar (MNM)
• Thailand (THA)
• Vietnam (VNM)

Make sure your virtual python environment is installed and activated before proceeding

1. Go to the project directory if not there already
2. Run the script by providing the name of country of interest:

    python make_static_soil_db.py --country Thailand

P.S. Running the script above would take some time!

3. Examples of some simulations run in visual code:

   3.a. After successful iterations of .SOLD, you will get a .SOL at the end *

   3.b. Some countries are not natively supported: *

4. How do I run make_static_soil_db.py for the other countries (e.g. KHM, LAO, etc.)?

   Remember the soilproperties directory from above? Model the structure of the folder and create/add the individual GTiff directory for additional countries.

   4.1. Prepare your layer: extracting from a global GTiff file:

   For example, to extract GTiff for Cambodia from the global organic GTiff life:

       python soilapis/get_tiff_from_global.py -c Cambodia -g ../organic_60cm.tif
   

   The output will be:

   extraction terminated. Output: /pathto/soil_apis/KHM_organic_60cm.tif

   4.2. After preparing all your layers using the script above. Copy them to the soilproperties directory like we did for "THA".

Make sure your virtual python environment is installed and activated before proceeding

from soilapis.calculator import SoilConnector

• extract the total available water (TAW) value from soil layers. E.g:

soil_conn = SoilConnector(path/to/soilproperties)
soil_taw = soil_conn.get_total_available_water(103.84, 15.76, 500, 3)
print(soil_taw)

• create appropriate dynamic or static soil database (.SOL) as an input for DSSAT

soil_conn = SoilConnector(path/to/soilproperties, path/to/output)
soil_dssat = soil_conn.get_soil_property(103.84, 15.76, 500, 3, "dssat")
print(soil_dssat)

Make sure your virtual python environment is installed and activated before proceeding

1. Go to the location of the script

cd /path/to/soil_apis/soilapis

2. Main usage:

summary_soil_property.py [-h] --lon LON --lat LAT --win WIN --depth DEPTH  [--format FORMAT]

3. To get help:

summary_soil_property.py -h

4. For example, to get TAW file needed to to run the soil water balance:

python path/to/summary_soil_property.py --lon=103.84 --lat=15.76 --win=3 --depth=350

5. For example, To retrieve the .SOL file needed to to run DSSA:

python summary_soil_property.py --lon=103.84 --lat=15.76 --win=3 --depth=500 --format=dssat

The SoilTAW[Depth]mm.csv output file contains three entries needed for Soil Water Balance:

• codeID: this is just a unique ID for the TAW value. It's an integer
• Soil type: This is used by the water balance model to link a computational unit with the data. Possible values are: SiltLoam, SAND, SiltClayL, Loam, ClayLoam, SandyLoam, etc...
• TAW: this is a float value corresponding to the TAW calculated by the script. This value is in mm

• Output .SOL file as json