diff --git a/01 InfoWorks ICM/03 Python/0006 ARR climate change/ICM_ARR_ClimateChange.mp4 b/01 InfoWorks ICM/03 Python/0006 ARR climate change/ICM_ARR_ClimateChange.mp4
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Binary files /dev/null and b/01 InfoWorks ICM/03 Python/0006 ARR climate change/ICM_ARR_ClimateChange.mp4 differ
diff --git a/01 InfoWorks ICM/03 Python/0006 ARR climate change/ICM_ARRv4p2_CC.py b/01 InfoWorks ICM/03 Python/0006 ARR climate change/ICM_ARRv4p2_CC.py
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+import shutil
+import os
+import zipfile
+import tkinter as tk
+from tkinter import filedialog, ttk
+import pandas as pd
+import io
+import re
+
+# Constants for SSP options and file/section names
+SSP_OPTIONS = ["SSP1-2.6", "SSP2-4.5", "SSP3-7.0", "SSP5-8.5"]
+SECTION_END_PREFIX = "[END_"
+ARR_DATA_HUB_FILENAME = "ArrDataHub.txt"
+BOM_IFDS_FILENAME = "BomIfds.csv"
+
+# ---------------- UI ----------------
+DESIGN_YEARS = ["2030", "2040", "2050", "2060", "2070", "2080", "2090", "2100"]
+
+
+def _build_ssp_selector(parent):
+ tk.Label(parent, text="Select Shared Socioeconomic Pathway (SSP)").pack(pady=5)
+ ssp_var = tk.StringVar()
+ dropdown = ttk.Combobox(parent, textvariable=ssp_var, values=SSP_OPTIONS, state="readonly", width=20)
+ dropdown.pack(pady=5)
+ dropdown.current(0)
+ return ssp_var
+
+
+def _build_year_selector(parent):
+ tk.Label(parent, text="Select Design Year").pack(pady=5)
+ year_var = tk.StringVar()
+ dropdown = ttk.Combobox(parent, textvariable=year_var, values=DESIGN_YEARS, state="readonly", width=10)
+ dropdown.pack(pady=5)
+ dropdown.current(0)
+ return year_var
+
+
+def get_user_choices():
+ root = tk.Tk()
+ root.title("Select Options")
+ ssp_var = _build_ssp_selector(root)
+ year_var = _build_year_selector(root)
+ tk.Button(root, text="Submit", command=root.quit).pack(pady=10)
+ root.mainloop()
+ ssp, year = ssp_var.get(), year_var.get()
+ root.destroy()
+ return ssp, year
+
+# ---------------- Parsers ----------------
+def _extract_value_from_parts(parts, year, ssp, target_idx):
+ """Extract numeric value from a row (parts) for given year/SSP; used by loss and temperature parsers."""
+ if not parts or parts[0] != str(year):
+ return None
+ if target_idx is None:
+ try:
+ pos = SSP_OPTIONS.index(ssp)
+ candidate = pos + 1
+ except ValueError:
+ candidate = 1
+ if candidate >= len(parts):
+ return None
+ val_str = parts[candidate]
+ else:
+ val_str = parts[target_idx] if target_idx < len(parts) else parts[-1]
+ m = NUMERIC_PATTERN.search(val_str)
+ return float(m.group()) if m else None
+
+
+def _parse_rainfall_row(parts, year):
+ """Extract up to 10 numeric values from a rainfall row for the given year."""
+ if not parts or parts[0] != str(year):
+ return None
+ vals = []
+ for tok in parts[1:]:
+ m = NUMERIC_PATTERN.search(tok)
+ if m:
+ vals.append(float(m.group()))
+ return vals[:10] if vals else None
+
+
+def parse_rainfall_ccf(txt_content, ssp, year):
+ """Parse rainfall CCF list (10 values) from the [SSP...] section for the chosen year."""
+ lines = txt_content.splitlines()
+ inside = False
+ for line in lines:
+ if line.strip() == f"[{ssp}]":
+ inside = True
+ continue
+ if not inside:
+ continue
+ if line.startswith(SECTION_END_PREFIX):
+ break
+ parts = [p.strip() for p in line.split(",")]
+ result = _parse_rainfall_row(parts, year)
+ if result is not None:
+ return result
+ return None
+
+def _parse_section_table(txt_content, section_header, ssp, year):
+ """Parse a [SectionName] table and return the numeric value for the given ssp/year row."""
+ lines = txt_content.splitlines()
+ inside = False
+ header = None
+ target_idx = None
+ for line in lines:
+ if line.strip() == section_header:
+ inside = True
+ header = None
+ target_idx = None
+ continue
+ if not inside:
+ continue
+ if line.startswith(SECTION_END_PREFIX):
+ break
+ if header is None:
+ if line.strip():
+ header = [h.strip() for h in line.split(",")]
+ target_idx = next((j for j, h in enumerate(header) if ssp in h), None)
+ continue
+ parts = [p.strip() for p in line.split(",")]
+ val = _extract_value_from_parts(parts, year, ssp, target_idx)
+ if val is not None:
+ return val
+ return None
+
+
+def parse_loss_factor_table(txt_content, section_name, ssp, year):
+ """Parse [Climate_Change_INITIAL_LOSS] or [Climate_Change_CONTINUING_LOSS] table."""
+ return _parse_section_table(txt_content, f"[{section_name}]", ssp, year)
+
+
+def parse_temperature_change(txt_content, ssp, year):
+ """Parse TEMPERATURE_CHANGES table and return the temperature change value for SSP/year."""
+ return _parse_section_table(txt_content, "[TEMPERATURE_CHANGES]", ssp, year)
+
+# ---------------- Apply rainfall factors ----------------
+DURATION_MAP = {
+ 1.0: 0, 1.5: 1, 2.0: 2, 3.0: 3, 4.5: 4,
+ 6.0: 5, 9.0: 6, 12.0: 7, 18.0: 8, 24.0: 9,
+}
+DURATIONS_SORTED = sorted(DURATION_MAP.keys())
+
+
+def _factor_for_duration(dur_hr, factors):
+ """Return the interpolation factor for a given duration in hours."""
+ if dur_hr in DURATION_MAP:
+ return factors[DURATION_MAP[dur_hr]]
+ if dur_hr < 1.0:
+ return factors[0]
+ if dur_hr > 24.0:
+ return factors[-1]
+ lower = max(d for d in DURATIONS_SORTED if d < dur_hr)
+ upper = min(d for d in DURATIONS_SORTED if d > dur_hr)
+ li, ui = DURATION_MAP[lower], DURATION_MAP[upper]
+ f_lower, f_upper = factors[li], factors[ui]
+ return f_lower + (f_upper - f_lower) * ((dur_hr - lower) / (upper - lower))
+
+
+def _scale_row_values(df, idx, row, factor):
+ """Scale numeric columns in row by factor; skip Duration columns."""
+ for col in df.columns:
+ if col in ("Duration", "Duration in min"):
+ continue
+ try:
+ val = float(row[col])
+ df.at[idx, col] = round(val * factor, 2)
+ except (ValueError, TypeError):
+ pass
+
+
+def apply_factors_to_csv(csv_bytes, factors):
+ """
+ Adjust BomIfds.csv rainfall depths according to provided factors.
+ factors: list of 10 floats: [<=1h,1.5h,2h,3h,4.5h,6h,9h,12h,18h,>=24h]
+ """
+ text = csv_bytes.decode("utf-8").splitlines()
+ header_index = next(i for i, l in enumerate(text) if l.startswith("Duration,Duration in min"))
+ header_lines = text[:header_index]
+ data_lines = text[header_index:]
+ df = pd.read_csv(io.StringIO("\n".join(data_lines)))
+
+ for idx, row in df.iterrows():
+ dur_hr = float(row["Duration in min"]) / 60.0
+ factor = _factor_for_duration(dur_hr, factors)
+ _scale_row_values(df, idx, row, factor)
+
+ out = io.StringIO()
+ for line in header_lines:
+ out.write(line + "\n")
+ df.to_csv(out, index=False)
+ return out.getvalue().encode("utf-8")
+
+# ---------------- Apply loss factors ----------------
+def _apply_loss_line_factor(line, factor):
+ """Replace first number in line with value scaled by factor; return updated line."""
+ m = NUMERIC_PATTERN.search(line)
+ if not m or not factor:
+ return line
+ orig = float(m.group())
+ newv = round(orig * factor, 2)
+ return line[:m.start()] + str(newv) + line[m.end():]
+
+
+def _process_losses_line(line, inside_losses, init_factor, cont_factor):
+ """Process one line inside [LOSSES]; return (updated_line, still_inside_losses)."""
+ stripped = line.strip()
+ if stripped.lower().startswith("storm initial losses"):
+ line = _apply_loss_line_factor(line, init_factor)
+ elif stripped.lower().startswith("storm continuing losses"):
+ line = _apply_loss_line_factor(line, cont_factor)
+ return line, inside_losses
+
+
+def apply_factors_to_losses(txt_content, init_factor, cont_factor):
+ """Update [LOSSES] section values."""
+ lines = txt_content.splitlines()
+ new_lines = []
+ inside_losses = False
+ for line in lines:
+ stripped = line.strip()
+ if stripped.upper() == "[LOSSES]":
+ inside_losses = True
+ new_lines.append(line)
+ continue
+ if inside_losses and stripped.startswith("[") and not stripped.upper().startswith("[LOSSES"):
+ inside_losses = False
+ new_lines.append(line)
+ continue
+ if inside_losses:
+ line, _ = _process_losses_line(line, inside_losses, init_factor, cont_factor)
+ new_lines.append(line)
+ return "\n".join(new_lines)
+
+# ---------------- Main ----------------
+SKIP_ZIP_ENTRIES = (BOM_IFDS_FILENAME, ARR_DATA_HUB_FILENAME, "old_BomIfds.csv", "old_ArrDataHub.txt", "adjustment_info.txt")
+
+
+def _ask_zip_path():
+ root = tk.Tk()
+ root.withdraw()
+ path = filedialog.askopenfilename(title="Select a ZIP file", filetypes=[("ZIP files", "*.zip")])
+ root.destroy()
+ return path
+
+
+def _base_name_from_filename(filename):
+ fname_lower = filename.lower()
+ if fname_lower.endswith(".arr.zip"):
+ return filename[:-8]
+ if fname_lower.endswith(".zip"):
+ return filename[:-4]
+ base, _ = os.path.splitext(filename)
+ return base
+
+
+def _versioned_copy_path(folder, base, ssp, year):
+ copy_path = os.path.join(folder, f"{base}_{ssp}_{year}.arr.zip")
+ v = 1
+ final_copy = copy_path
+ while os.path.exists(final_copy):
+ v += 1
+ final_copy = copy_path.replace(".arr.zip", f"_v{v}.arr.zip")
+ return final_copy
+
+
+def _read_zip_contents(zf):
+ try:
+ arr_txt_bytes = zf.read(ARR_DATA_HUB_FILENAME)
+ except KeyError:
+ print(f"ERROR: {ARR_DATA_HUB_FILENAME} not found inside the zip.")
+ return None
+ try:
+ original_csv = zf.read(BOM_IFDS_FILENAME)
+ except KeyError:
+ print(f"ERROR: {BOM_IFDS_FILENAME} not found inside the zip.")
+ return None
+ return arr_txt_bytes, arr_txt_bytes.decode("utf-8"), original_csv
+
+
+def _write_updated_zip(zf, copy_path, arr_txt, arr_txt_bytes, original_csv, ssp, year,
+ rainfall_factors, init_loss, cont_loss, temp_change):
+ temp_zip = copy_path + ".tmp"
+ updated_arr_txt = apply_factors_to_losses(arr_txt, init_loss, cont_loss)
+ with zipfile.ZipFile(temp_zip, "w") as new_zip:
+ for item in zf.infolist():
+ if item.filename in SKIP_ZIP_ENTRIES:
+ continue
+ new_zip.writestr(item, zf.read(item.filename))
+ new_zip.writestr("old_BomIfds.csv", original_csv)
+ new_zip.writestr("old_ArrDataHub.txt", arr_txt_bytes)
+ if rainfall_factors is None:
+ print(f"WARNING: rainfall CCFs not found for the chosen SSP/year; {BOM_IFDS_FILENAME} will not be adjusted.")
+ new_zip.writestr(BOM_IFDS_FILENAME, original_csv)
+ else:
+ new_zip.writestr(BOM_IFDS_FILENAME, apply_factors_to_csv(original_csv, rainfall_factors))
+ new_zip.writestr(ARR_DATA_HUB_FILENAME, updated_arr_txt.encode("utf-8"))
+ adj_lines = [
+ f"SSP: {ssp}", f"Design Year: {year}",
+ f"Rainfall CCF count: {len(rainfall_factors) if rainfall_factors else 'N/A'}",
+ f"Initial loss factor: {init_loss}", f"Continuing loss factor: {cont_loss}",
+ f"Temperature change (°C): {temp_change}"
+ ]
+ new_zip.writestr("adjustment_info.txt", ("\n".join(adj_lines)).encode("utf-8"))
+ return temp_zip, updated_arr_txt
+
+
+def copy_and_update_zip():
+ file_path = _ask_zip_path()
+ if not file_path:
+ print("No file selected.")
+ return
+
+ ssp, year = get_user_choices()
+ folder, filename = os.path.split(file_path)
+ base = _base_name_from_filename(filename)
+ copy_path = _versioned_copy_path(folder, base, ssp, year)
+
+ shutil.copy2(file_path, copy_path)
+ print(f"Copied to: {copy_path}")
+
+ with zipfile.ZipFile(copy_path, "r") as zf:
+ contents = _read_zip_contents(zf)
+ if contents is None:
+ return
+ arr_txt_bytes, arr_txt, original_csv = contents
+
+ rainfall_factors = parse_rainfall_ccf(arr_txt, ssp, year)
+ init_loss = parse_loss_factor_table(arr_txt, "Climate_Change_INITIAL_LOSS", ssp, year)
+ cont_loss = parse_loss_factor_table(arr_txt, "Climate_Change_CONTINUING_LOSS", ssp, year)
+ temp_change = parse_temperature_change(arr_txt, ssp, year)
+
+ print(f"Parsed rainfall factors count: {len(rainfall_factors) if rainfall_factors else 0}")
+ print(f"Initial loss factor: {init_loss}")
+ print(f"Continuing loss factor: {cont_loss}")
+ print(f"Temperature change (°C): {temp_change}")
+
+ temp_zip, updated_arr_txt = _write_updated_zip(
+ zf, copy_path, arr_txt, arr_txt_bytes, original_csv, ssp, year,
+ rainfall_factors, init_loss, cont_loss, temp_change)
+
+ os.replace(temp_zip, copy_path)
+ print(f"✅ Updated ARR ZIP created: {copy_path}")
+
+ for line in updated_arr_txt.splitlines():
+ low = line.lower()
+ if low.startswith("storm initial losses") or low.startswith("storm continuing losses"):
+ print(line)
+ print(f"Temperature change for {ssp} / {year}: {temp_change} °C")
+
+ extract_folder = copy_path[:-4]
+ os.makedirs(extract_folder, exist_ok=True)
+ with zipfile.ZipFile(copy_path, "r") as zf:
+ zf.extractall(extract_folder)
+ print(f"📂 Extracted contents to: {extract_folder}")
+
+if __name__ == "__main__":
+ copy_and_update_zip()
+
+
+
diff --git a/01 InfoWorks ICM/03 Python/0006 ARR climate change/README.md b/01 InfoWorks ICM/03 Python/0006 ARR climate change/README.md
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--- /dev/null
+++ b/01 InfoWorks ICM/03 Python/0006 ARR climate change/README.md
@@ -0,0 +1,125 @@
+# ARR Climate Change Adjustment Tool
+
+The `ICM_ARRv4p2_CC.py` script applies climate change factors to Australian Rainfall and Runoff (ARR) version 4.2 rainfall data files. This tool adjusts rainfall intensities and loss parameters based on selected Shared Socioeconomic Pathway (SSP) scenarios and design years, enabling climate change impact assessments for InfoWorks ICM models.
+
+For detailed instruction please download and view [ICM_ARR_ClimateChange.mp4](https://github.com/trannguyen9911/Open-Source-Support/blob/main/01%20InfoWorks%20ICM/03%20Python/0006%20ARR%20climate%20change/ICM_ARR_ClimateChange.mp4)
+
+## Overview
+
+This script processes ARR rainfall data ZIP files (`.arr.zip`) by:
+
+- Applying rainfall Climate Change Factors (CCFs) to adjust rainfall depths for different durations
+- Adjusting initial and continuing loss parameters based on climate change projections
+- Extracting temperature change information for the selected scenario
+- Creating a new adjusted ZIP file with original files preserved as backups
+
+
+## Requirements
+
+- Python 3.x
+- Required packages:
+ - `pandas`
+ - `tkinter` (usually included with Python)
+ - Standard library: `shutil`, `os`, `zipfile`, `io`, `re`
+
+Install dependencies using:
+```bash
+pip install pandas
+```
+
+## Usage
+
+### Step 1: Generate a design storm in InfoWorks ICM
+
+An ARR design storm can be generated using ARR Storm Generator tool in InfoWorks ICM. Please take a look [here](https://help.autodesk.com/view/IWICMS/2026/ENU/?guid=GUID-4C08EAE3-4163-49C8-B91A-789CFF763457) for more details of how to create an ARR design storm.
+
+
+
+Navigate to the location of the ARR design storm data, these following files can be found in _.arr.zip_:
+ - BomIfds.csv file that contains IFD curves
+ - ArrDataHub.txt file that includes Climate Change Factors for different Shared Socioeconomic Pathway (SSP), Initial Loss and (IL), and Continuous Loss (CL)
+
+### Step 2: Run the Script
+
+Execute the script:
+```bash
+python ICM_ARRv4p2_CC.py
+```
+
+### Step 3: Select Input File
+
+A file dialog will appear. Select your ARR rainfall data ZIP file (`.arr.zip` format).
+
+### Step 4: Choose Climate Change Scenario
+
+A dialog window will appear with two dropdown menus:
+
+1. **Select Shared Socioeconomic Pathway (SSP)**:
+ - SSP1-2.6 (Low emissions scenario)
+ - SSP2-4.5 (Intermediate emissions scenario)
+ - SSP3-7.0 (High emissions scenario)
+ - SSP5-8.5 (Very high emissions scenario)
+
+2. **Select Design Year**:
+ - Available years: 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100
+
+Click "Submit" to proceed.
+
+### Step 5: Review Output
+
+The script will:
+- Create a new ZIP file named `[original_name]_[SSP]_[year].arr.zip`
+- If a file with the same name exists, it will append `_v2`, `_v3`, etc.
+- Extract the contents to a folder with the same name (without `.zip` extension)
+
+### Step 6: Update the design rainfall in InfoWorks ICM.
+
+ 
+
+- In InfoWorks ICM, open the design rainfall and select _ARR Storm Generator_
+- Select the new .arr.zip folder (with climate change factors updated) and click _Edit_
+- Select _Add from file..._ to update _ARR Data Hub Text File_ and _BOM Design Raifall_
+- Select _OK_ to save the changes
+
+## Output Files
+
+The adjusted ZIP file contains:
+
+- **BomIfds.csv**: Updated rainfall depths with climate change factors applied
+- **ArrDataHub.txt**: Updated loss parameters (initial and continuing losses)
+- **old_BomIfds.csv**: Backup of original rainfall data
+- **old_ArrDataHub.txt**: Backup of original ARR data hub file
+- **adjustment_info.txt**: Summary of applied adjustments including:
+ - Selected SSP scenario
+ - Design year
+ - Number of rainfall CCFs applied
+ - Initial loss factor
+ - Continuing loss factor
+ - Temperature change (°C)
+
+
+## Error Handling
+
+The script will display error messages if:
+- No file is selected
+- `ArrDataHub.txt` is not found in the ZIP file
+- `BomIfds.csv` is not found in the ZIP file
+- Rainfall CCFs are not found for the selected SSP/year combination (warning only, file still created)
+
+## Notes
+
+- The script preserves all other files in the original ZIP
+- Original files are always backed up before modification
+- The adjusted ZIP maintains the same structure as the original
+- Temperature change values are extracted but not directly applied to the model (for reference only)
+
+## Example
+
+If you select a file named `Sydney_ARR.arr.zip` with SSP2-4.5 and year 2050:
+- Output file: `Sydney_ARR_SSP2-4.5_2050.arr.zip`
+- Extraction folder: `Sydney_ARR_SSP2-4.5_2050.arr`
+
+## References
+
+This tool is designed to work with ARR v4.2 climate change data. For more information on ARR climate change factors, refer to the Australian Rainfall and Runoff guidelines.
+