Pull Request Summary

docs/changelog.md

@@ -1,5 +1,12 @@
 # Release Notes
 
+## Version 1.3.0 (not released yet)
+
+- Introduced the `pySWATPlus.Calibration` class for parameter calibration using multi-objective optimization, evolutionary algorithms, and parallel computing.
+
+- Added the `pySWATPlus.SensitivityAnalyzer.simulation_and_indices` method to compute sensitivity indices directly against observed data without saving detailed simulation results.
+
+
 ## Version 1.2.0 (October 13, 2025)
 
 - All SWAT+ simulations with modified parameters are now configured through the `calibration.cal` file, eliminating the need to read and modify individual input files.
@@ -31,7 +38,6 @@
     - Renamed `set_begin_and_end_date` to `set_simulation_period` for better consistency.
 
 
-
 ## Version 1.1.0 (August 26, 2025)
 
 - Added a new class `pySWATPlus.SensitivityAnalyzer` to support sensitivity simulations with two main methods:

docs/userguide/model_calibration.md

@@ -33,15 +33,16 @@ the calibration interface offers flexible options for optimizing model parameter
 
 
 The interface provides a [`Calibration`](https://swat-model.github.io/pySWATPlus/api/calibration/) class that must be initialized with the required parameters.
-This class includes the `parameter_optimization` method, which performs parameter optimization using multi-objective algorithms, evolutionary strategies, and parallel computation.
+This class includes the [`parameter_optimization`](https://swat-model.github.io/pySWATPlus/api/calibration/#pySWATPlus.Calibration.parameter_optimization) method,
+which performs parameter optimization using multi-objective algorithms, evolutionary strategies, and parallel computation.
 
 The following code provides an example of optimizing flow discharge for both daily and monthly time-series data using multi-objective evolutionary computation.
 The usage of both daily and monthly flow discharge is just for illustrative purposes on how multi-objective optimization can be performed. Users should replace monthly flow
 discharge by nitorgen or phosporus concentration according to their needs.
 
 
 ```python
-# Calibration parameter space
+# Define parameter space
 parameters = [
     {
         'name': 'esco',
@@ -84,7 +85,7 @@ observe_data = {
 }
 
 # Objective configuration
-objectives = {
+objective_config = {
     'channel_sd_day.txt': {
         'sim_col': 'flo_out',
         'obs_col': 'discharge',
@@ -105,7 +106,7 @@ if __name__ == '__main__':
         txtinout_dir=r"C:\Users\Username\project\Scenarios\Default\TxtInOut",
         extract_data=extract_data,
         observe_data=observe_data,
-        objectives=objectives,
+        objective_config=objective_config,
         algorithm='NSGA2',
         n_gen=2,
         pop_size=5

docs/userguide/sensitivity_interface.md

@@ -130,4 +130,81 @@ output = pySWATPlus.SensitivityAnalyzer().parameter_sensitivity_indices(
     indicators=['KGE', 'RMSE'],
     json_file=r"C:\Users\Username\sensitivity_indices.json"
 )
+```
+
+
+## Integrated Simulation and Sensitivity
+
+To compute sensitivity indices directly for multiple outputs against observed data and skip saving the detailed simulation results, use the following interface:
+
+
+```python
+# Define parameter space
+parameters = [
+    {
+        'name': 'esco',
+        'change_type': 'absval',
+        'lower_bound': 0,
+        'upper_bound': 1
+    },
+    {
+        'name': 'perco',
+        'change_type': 'absval',
+        'lower_bound': 0,
+        'upper_bound': 1
+    }
+]
+
+
+# Extract data configuration
+extract_data = {
+    'channel_sd_day.txt': {
+        'has_units': True,
+        'apply_filter': {'name': ['cha561']}
+    },
+    'channel_sd_mon.txt': {
+        'has_units': True,
+        'ref_day': 1,
+        'apply_filter': {'name': ['cha561']}
+    }
+}
+
+# Observe data configuration
+observe_data = {
+    'channel_sd_day.txt': {
+        'obs_file': r"C:\Users\Username\observed_folder\discharge_daily.csv",
+        'date_format': '%Y-%m-%d'
+    },
+    'channel_sd_mon.txt': {
+        'obs_file': r"C:\Users\Username\observed_folder\discharge_monthly.csv",
+        'date_format': '%Y-%m-%d'
+    }
+}
+
+# Metric configuration
+metric_config = {
+    'channel_sd_day.txt': {
+        'sim_col': 'flo_out',
+        'obs_col': 'discharge',
+        'indicator': 'NSE'
+    },
+    'channel_sd_mon.txt': {
+        'sim_col': 'flo_out',
+        'obs_col': 'mean',
+        'indicator': 'RMSE'
+    }
+}
+
+# Sensitivity indices
+if __name__ == '__main__':
+    output = pySWATPlus.SensitivityAnalyzer().simulation_and_indices(
+        parameters=parameters,
+        sample_number=1,
+        sensim_dir=r"C:\Users\dpal22\Desktop\swat_run\experiment_dominant_hru\empty_dir",
+        txtinout_dir=r"C:\Users\dpal22\Desktop\swat_run\experiment_dominant_hru\txtinout_copy",
+        extract_data=extract_data,
+        observe_data=observe_data,
+        metric_config=metric_config
+    )
+    print(output)
 ```