meteo-interp

Meteorological data interpolation tool for SWAT/SWAT+ hydrological models. Fetches weather data from DWD (German Weather Service) or custom sources and interpolates values to watershed subbasin centroids using Inverse Distance Weighting (IDW).

Features

• Data Sources: DWD Open Data API or custom xlsx files
• Interpolation: Inverse Distance Weighting (IDW) with configurable power parameter
• Precipitation Correction: Optional Richter (1995) correction for systematic precipitation measurement errors
• Output Formats: SWAT and SWAT+ climate file formats
• Parameters: Temperature (max/min), precipitation, humidity, wind speed, solar radiation

Workflow

---
config:
  theme: default
  look: classic
  layout: dagre
---
flowchart TB
 subgraph Input["📁 Input Files"]
        A1["watershed.xlsx<br>Subbasin locations"]
        A2["interpolation_parameters.xlsx<br>Settings &amp; dates"]
        A3["richter_parameters.xlsx<br>Correction coefficients"]
  end
 subgraph Loop["🔁 For Each Subbasin"]
        G{"Apply Richter<br>Correction?"}
        F["Fetch meteorological values<br>precipitation, temp, humidity,<br>wind, solar radiation"]
        H["Richter 1995 Correction<br>Correct precipitation<br>based on temperature"]
        I["Skip correction"]
        J{"Data Format?"}
        K1["Parse long format<br>parameter column"]
        K2["Parse wide format<br>parameter columns"]
        L["IDW Interpolation<br>for each parameter &amp; date"]
        M["Store interpolated<br>values in memory"]
  end
 subgraph SWAT["📤 SWAT Files"]
        P1["tmp###.txt<br>Temperature"]
        O1["SWAT Output"]
        P2["pcp###.txt<br>Precipitation"]
        P3["rh###.txt<br>Humidity"]
        P4["wind###.txt<br>Wind Speed"]
        P5["solar###.txt<br>Solar Radiation"]
        P6["Climate list files<br>tmp.txt, pcp.txt, etc."]
  end
 subgraph SWATPLUS["📤 SWAT+ Files"]
        Q1["tmp###.tmp<br>Temperature"]
        O2["SWAT+ Output"]
        Q2["pcp###.pcp<br>Precipitation"]
        Q3["rh###.hmd<br>Humidity"]
        Q4["wind###.wnd<br>Wind Speed"]
        Q5["solar###.slr<br>Solar Radiation"]
        Q6["Climate list files<br>tmp.cli, pcp.cli, etc."]
  end
    A1 --> B{"Data Source?"}
    A2 --> B
    A3 --> B
    B -- "is_dwd = 1" --> C1["DWD API<br>wetterdienst"]
    B -- "is_dwd = 0" --> C2["Custom xlsx<br>stations.xlsx + values.xlsx"]
    C1 --> D1["Fetch KL stations<br>by distance"] & D2["Fetch Solar stations<br>by rank"]
    D1 --> E1["Combine stations"]
    D2 --> E1
    E1 --> F
    C2 --> E2["Load custom station data"]
    E2 --> E3["Calculate distances<br>using Haversine formula"]
    E3 --> F
    F --> G
    G -- "apply_richter = 1" --> H
    G -- "apply_richter = 0" --> I
    H --> J
    I --> J
    J -- Long format --> K1
    J -- Wide format --> K2
    K1 --> L
    K2 --> L
    L --> M
    M --> N{"Output Format?"}
    N -- "swatplus = 0" --> O1
    N -- "swatplus = 1" --> O2
    O1 --> P1 & P2 & P3 & P4 & P5 & P6
    O2 --> Q1 & Q2 & Q3 & Q4 & Q5 & Q6

Loading

Installation

# Clone the repository
git clone https://github.com/4farid/meteo-interp.git
cd meteo-interp

# Install dependencies
pip install pandas numpy openpyxl wetterdienst

Project Structure

meteo-interp/
├── main.py                 # Main script
├── src/
│   ├── dwd.py             # DWD data fetching
│   ├── idw.py             # IDW interpolation
│   ├── richter.py         # Richter precipitation correction
│   └── write_swat_output.py  # SWAT/SWAT+ file writers
└── data/
    ├── watershed.xlsx              # Subbasin definitions
    ├── interpolation_parameters.xlsx   # Configuration
    ├── richter_parameters.xlsx     # Richter correction coefficients
    ├── stations.xlsx               # Custom station data (if is_dwd=0)
    ├── values.xlsx                 # Custom weather data (if is_dwd=0)
    ├── interpolated_swat/          # Output: SWAT files
    └── interpolated_swatplus/      # Output: SWAT+ files

Input Files

watershed.xlsx

Defines the subbasin centroids for interpolation.

Column	Description
Subbasin	Subbasin ID
Lat	Latitude (decimal degrees)
Long	Longitude (decimal degrees)
Elevation	Elevation (m)

interpolation_parameters.xlsx

Configuration parameters for the interpolation.

Column	Description
start_date	Start date for data fetching
end_date	End date for data fetching
radius_kl	Search radius for stations (km)
swatplus	Output format: 1 = SWAT+, 0 = SWAT
is_dwd	Data source: 1 = DWD API, 0 = custom xlsx
apply_richter	Richter correction: 1 = apply, 0 = skip

richter_parameters.xlsx

Richter (1995) precipitation correction coefficients.

Column	Description
T_Snow	Temperature threshold for snow (°C)
T_Mix	Temperature threshold for mixed precipitation (°C)
b_Snow, epsilon_Snow	Snow correction coefficients
b_Mix, epsilon_Mix	Mixed precipitation coefficients
b_Summer, epsilon_Summer	Summer rain coefficients
b_Winter, epsilon_Winter	Winter rain coefficients
Summer_month_Start	First month of summer season
Winter_month_Start	First month of winter season
maximum_changes	Maximum correction factor

stations.xlsx (when is_dwd=0)

Custom weather station metadata.

Column	Description
station_id	Unique station identifier
latitude	Station latitude
longitude	Station longitude

values.xlsx (when is_dwd=0)

Custom weather data in wide format.

Column	Description
station_id	Station identifier
date	Observation date
precipitation_height	Daily precipitation (mm)
temperature_air_max_2m	Daily max temperature (°C)
temperature_air_min_2m	Daily min temperature (°C)
humidity	Relative humidity (decimal)
wind_speed	Wind speed (m/s)
radiation_global	Solar radiation (MJ/m²)

Usage

python main.py

The script will:

1. Read configuration from xlsx files
2. Fetch weather data (DWD or custom). Solar radiation does not use the distance method; it takes 3 nearest stations
3. Calculate distances from each subbasin to nearby stations
4. Apply IDW interpolation for each parameter
5. Optionally apply Richter precipitation correction
6. Write output files in SWAT or SWAT+ format

Output Files

SWAT (swatplus=0)

• pcp001.txt, pcp002.txt, ... - Precipitation
• tmp001.txt, tmp002.txt, ... - Temperature (max, min)
• rh001.txt, rh002.txt, ... - Relative humidity
• wind001.txt, wind002.txt, ... - Wind speed
• solar001.txt, solar002.txt, ... - Solar radiation
• pcp.txt, tmp.txt, etc. - Station list files

SWAT+ (swatplus=1)

• pcp001.pcp, pcp002.pcp, ... - Precipitation
• tmp001.tmp, tmp002.tmp, ... - Temperature (max, min)
• hmd001.hmd, hmd002.hmd, ... - Humidity
• wnd001.wnd, wnd002.wnd, ... - Wind
• slr001.slr, slr002.slr, ... - Solar radiation
• *.cli - Climate list files

References

• Richter, D. (1995). Ergebnisse methodischer Untersuchungen zur Korrektur des systematischen Meßfehlers des Hellmann-Niederschlagsmessers. Berichte des Deutschen Wetterdienstes 194.
• DWD Open Data: https://opendata.dwd.de/
• Gutzmann, B., & Motl, A. Wetterdienst: Open weather data for humans. https://github.com/earthobservations/wetterdienst

License

See LICENSE file.