In [1]:

%load_ext autoreload

%load_ext autoreload

SWAT+ Model Simulation with pySWATPlus¶

This notebook demonstrates how to use the pySWATPlus library to interact with SWAT+ models, modify input files, and run simulations. We'll cover the following steps:

• Loading the necessary libraries.
• Initializing the TxtinoutReader to interact with the SWAT+ model.
• Reading and modifying input files (e.g., plants.plt).
• Running the SWAT+ simulation and analyzing results.
• Running multiple simulations in parallel.

Let’s get started!

---

1. Importing Required Libraries¶

First, we import the pySWATPlus module.

In [2]:

from pySWATPlus import TxtinoutReader

from pySWATPlus import TxtinoutReader

---

2. Setting Up the SWAT+ Model¶

To work with a SWAT+ model, we need to specify the path to the txtinout folder. This folder contains all the input files required for the simulation, including the SWAT+ executable.

In [3]:

# Path to the SWAT+ model folder
txtinout_folder = '/mnt/c/Users/joans/OneDrive/Escriptori/icra/muga_windows'
filename =  'plants.plt'

# Path to the SWAT+ model folder txtinout_folder = '/mnt/c/Users/joans/OneDrive/Escriptori/icra/muga_windows' filename = 'plants.plt'

---

3. Initializing the TxtinoutReader¶

The TxtinoutReader class is used to interact with the SWAT+ model. It allows us to read, modify, and run simulations.

In [4]:

# Initialize the TxtinoutReader
# Note: The folder must contain a .exe file to run the simulation.
reader = TxtinoutReader(txtinout_folder)

# Initialize the TxtinoutReader # Note: The folder must contain a .exe file to run the simulation. reader = TxtinoutReader(txtinout_folder)

---

4. Reading Input Files¶

We can read specific input files, such as plants.plt, using the register_file method. This method returns a FileReader object that allows us to manipulate the file.

In [5]:

# Read the 'plants.plt' file
plants_reader = reader.register_file(
    filename, 
    has_units=False,  # Indicates if the file has units information
    index='name'      # Use the 'name' column as the index
)

# Display the header of the file
plants_reader.header_file

# Read the 'plants.plt' file plants_reader = reader.register_file( filename, has_units=False, # Indicates if the file has units information index='name' # Use the 'name' column as the index ) # Display the header of the file plants_reader.header_file

Out[5]:

'plants.plt: written by SWAT+ editor v2.2.0 on 2023-09-25 11:54 for SWAT+ rev.60.5.4\n'

---

5. Exploring the Input Data¶

The plants.plt file contains information about different plant species used in the SWAT+ model. Let’s take a look at the data.

In [6]:

# Display the first few rows of the 'plants.plt' file
plants_reader.df.head()

# Display the first few rows of the 'plants.plt' file plants_reader.df.head()

Out[6]:

	name	plnt_typ	gro_trig	nfix_co	days_mat	bm_e	harv_idx	lai_pot	frac_hu1	lai_max1	...	rt_st_end	plnt_pop1	frac_lai1	plnt_pop2	frac_lai2	frac_sw_gro	aeration	wnd_dead	wnd_flat	description
agrc	agrc	cold_annual	temp_gro	0.0	110.0	40.0	0.40	4.0	0.05	0.05	...	0.0	0.0	0.0	0.0	0.0	0.5	0.0	0.0	0.0	agricultural_land_close_grown
agrl	agrl	warm_annual	temp_gro	0.0	110.0	50.0	0.45	3.0	0.15	0.05	...	0.0	0.0	0.0	0.0	0.0	0.5	0.0	0.0	0.0	agricultural_land_generic
agrr	agrr	warm_annual	temp_gro	0.0	110.0	50.0	0.50	3.0	0.15	0.05	...	0.0	0.0	0.0	0.0	0.0	0.5	0.0	0.0	0.0	agricultural_land_row
alfa	alfa	perennial	temp_gro	0.5	0.0	50.0	0.90	5.0	0.15	0.01	...	0.0	0.0	0.0	0.0	0.0	0.5	0.0	0.0	0.0	alfalfa
almd	almd	perennial	temp_gro	0.0	0.0	50.0	0.05	1.2	0.05	0.05	...	0.0	0.0	0.0	0.0	0.0	0.5	0.0	0.0	0.0	almond

5 rows × 54 columns

---

6. Modifying Input Parameters¶

We can modify the input parameters directly in the DataFrame. For example, let’s change the bm_e (biomass-energy ratio) for the agrc plant.

In [7]:

# Modify the 'bm_e' value for the 'agrc' plant
plants_reader.df.loc['agrc', 'bm_e'] = 40

# Save the changes back to the file
plants_reader.overwrite_file()

# Modify the 'bm_e' value for the 'agrc' plant plants_reader.df.loc['agrc', 'bm_e'] = 40 # Save the changes back to the file plants_reader.overwrite_file()

---

7. Running the SWAT+ Simulation¶

Now that we’ve modified the input file, let’s run the SWAT+ simulation. We can also specify additional parameters, such as the simulation period and warmup period.

In [8]:

# Set the beginning and end years for the simulation
reader.set_beginning_and_end_year(2009, 2011)

# Set the warmup period (in years)
reader.set_warmup(1)

# Enable the 'channel_sd' object in the 'print.prt' file for daily output
reader.enable_object_in_print_prt(obj='channel_sd', daily=True, monthly=False, yearly=False, avann=False)

# Set the beginning and end years for the simulation reader.set_beginning_and_end_year(2009, 2011) # Set the warmup period (in years) reader.set_warmup(1) # Enable the 'channel_sd' object in the 'print.prt' file for daily output reader.enable_object_in_print_prt(obj='channel_sd', daily=True, monthly=False, yearly=False, avann=False)

Handling Simulation Output¶

To avoid cluttering the notebook with long simulation output:

• Set show_output=False to suppress all output.
• Use %%capture to store the output and print only a portion (e.g., the first 20 lines).

In [9]:

%%capture captured_output
simulation_path = reader.run_swat(show_output=True)

%%capture captured_output simulation_path = reader.run_swat(show_output=True)

In [10]:

# Print the first 20 lines of the output
print("Simulation Output (First 20 Lines):")
print("\n".join(captured_output.stdout.splitlines()[:20]))

# Print the first 20 lines of the output print("Simulation Output (First 20 Lines):") print("\n".join(captured_output.stdout.splitlines()[:20]))

Simulation Output (First 20 Lines):
SWAT+
Revision 60.5.7
Soil & Water Assessment Tool
PC Version
Program reading . . . executing
Date of Sim   3/23/2025 Time  19:59: 1
reading from precipitation file         Time  19:59: 1
reading from temperature file           Time  19:59: 1
reading from solar radiation file       Time  19:59: 2
reading from relative humidity file     Time  19:59: 2
reading from wind file                  Time  19:59: 2
reading from wgn file                   Time  19:59: 3
reading from wx station file            Time  19:59: 3
Original Simulation        1   1  2009 Yr    1 of    3 Time  19:59: 4
Original Simulation        1   2  2009 Yr    1 of    3 Time  19:59: 4
Original Simulation        1   3  2009 Yr    1 of    3 Time  19:59: 4
Original Simulation        1   4  2009 Yr    1 of    3 Time  19:59: 5
Original Simulation        1   5  2009 Yr    1 of    3 Time  19:59: 5
Original Simulation        1   6  2009 Yr    1 of    3 Time  19:59: 5
Original Simulation        1   7  2009 Yr    1 of    3 Time  19:59: 5

---

8. Reading Simulation Results¶

After running the simulation, we can read the results from the output files. For example, let’s read the daily channel output (channel_sd_day.txt).

In [11]:

# Read the daily channel output
channel_sd = reader.register_file('channel_sd_day.txt', has_units=True)

# Display the first few rows of the results
channel_sd.df.head()

# Read the daily channel output channel_sd = reader.register_file('channel_sd_day.txt', has_units=True) # Display the first few rows of the results channel_sd.df.head()

Out[11]:

	jday	mon	day	yr	unit	gis_id	name	area	precip	evap	...	cbod_out	dox_out	san_out	sil_out	cla_out	sag_out	lag_out	grv_out	null.2	water_temp
0	1.0	1.0	1.0	2010.0	1.0	1.0	cha01	22.360	1521.00	119.30	...	869.100	278.100	0.0	0.0	0.0	0.0	0.0	0.0	10.74	10.74
1	1.0	1.0	1.0	2010.0	2.0	2.0	cha02	24.660	616.40	132.10	...	1.564	33.480	0.0	0.0	0.0	0.0	0.0	0.0	10.70	10.74
2	1.0	1.0	1.0	2010.0	3.0	3.0	cha03	2.618	133.50	14.14	...	5.037	23.630	0.0	0.0	0.0	0.0	0.0	0.0	10.53	10.74
3	1.0	1.0	1.0	2010.0	4.0	4.0	cha04	2.999	74.96	16.06	...	1.831	23.070	0.0	0.0	0.0	0.0	0.0	0.0	10.70	10.74
4	1.0	1.0	1.0	2010.0	5.0	5.0	cha05	8.043	160.90	43.47	...	84.530	7.442	0.0	0.0	0.0	0.0	0.0	0.0	12.29	10.74

5 rows × 66 columns

---

9. Running SWAT+ with Specific Modifications¶

Instead of modifying input files manually, you can directly specify the modifications when running the simulation. This is useful for quickly testing different scenarios.

Option 1: Modify Specific Values¶

You can specify the file, column, and value to modify. For example, let’s change the bm_e value for the agrc plant.

In [12]:

# Run the simulation with specific modifications
txtinout_path = reader.run_swat(
    params={'plants.plt': ('name', [('agrc', 'bm_e', 40)])}, 
    show_output=False
)
txtinout_path

# Run the simulation with specific modifications txtinout_path = reader.run_swat( params={'plants.plt': ('name', [('agrc', 'bm_e', 40)])}, show_output=False ) txtinout_path

Out[12]:

PosixPath('/mnt/c/Users/joans/OneDrive/Escriptori/icra/muga_windows')

Option 2: Use Regular Expressions¶

You can also use regular expressions to select rows for modification. For example, let’s modify the bm_e value for all plants whose names start with the letter "A".

In [13]:

# Run the simulation using a regular expression to select rows
txtinout_path = reader.run_swat(
    params={'plants.plt': ('name', [(r'^A.*', 'bm_e', 40)])}, 
    show_output=False
)
txtinout_path

# Run the simulation using a regular expression to select rows txtinout_path = reader.run_swat( params={'plants.plt': ('name', [(r'^A.*', 'bm_e', 40)])}, show_output=False ) txtinout_path

Out[13]:

PosixPath('/mnt/c/Users/joans/OneDrive/Escriptori/icra/muga_windows')

---

10. Running Multiple Simulations in Parallel¶

If you need to run multiple simulations with different parameters, you can use the run_parallel_swat method. This allows you to run simulations in parallel using multiple threads or processes.

In [14]:

#You can also run multiple simulations in parallel
txtinout_paths = reader.run_parallel_swat(params = [{'plants.plt': ('name', [('bana', 'bm_e', 45)])}, {'plants.plt': ('name', [('bana', 'bm_e', 40)])}], n_workers = 2, parallelization='threads')
txtinout_paths

#You can also run multiple simulations in parallel txtinout_paths = reader.run_parallel_swat(params = [{'plants.plt': ('name', [('bana', 'bm_e', 45)])}, {'plants.plt': ('name', [('bana', 'bm_e', 40)])}], n_workers = 2, parallelization='threads') txtinout_paths

Out[14]:

[PosixPath('/tmp/tmpa7a397py'), PosixPath('/tmp/tmpa227i7m4')]