Water Surface Slope Time Series

Download as ASCII

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 46208

# Download Water Surface Slope Time Series in ASCII format
response = dahiti.download_water_surface_slope_ascii(dahiti_id)

# Download Water Surface Slope Time Series in ASCII format and write response to file
response = dahiti.download_water_surface_slope_ascii_to_file(dahiti_id,'/tmp/46208_wss.txt')

Output of ASCII response:

2023-07-27 15:14:04 323.680 19.08
2023-07-31 04:36:14 332.980 19.32
...
2025-09-06 15:02:02 323.680 19.08
2025-09-16 13:24:17 323.680 19.08

Download as JSON

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 46208

# Download Water Surface Slope Time Series in JSON format
response = dahiti.download_water_surface_slope_json(dahiti_id)

# Download Water Surface Slope Time Series in JSON format and write response to file
response = dahiti.download_water_surface_slope_json_to_file(dahiti_id,'/tmp/46208_wss.json')

Output of JSON response:

[
     {'datetime': '2023-07-27 15:14:04', 'wss': 323.68, 'wss_u': 19.08},
     {'datetime': '2023-07-31 04:36:14', 'wss': 332.98, 'wss_u': 19.32},
     ...
     {'datetime': '2025-09-06 15:02:02', 'wss': 323.68, 'wss_u': 19.08},
     {'datetime': '2025-09-16 13:24:17', 'wss': 323.68, 'wss_u': 19.08}
]

Download as CSV

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 46208

# Download Water Surface Slope Time Series in CSV format
response = dahiti.download_water_surface_slope_csv(dahiti_id)

# Download Water Surface Slope Time Series in CSV format and write response to file
response = dahiti.download_water_surface_slope_csv_to_file(dahiti_id,'/tmp/46208_wss.csv')

Output of CSV response:

datetime;wss;wss_u
2023-07-27 15:14:04;323.680;19.08
2023-07-31 04:36:14;332.980;19.32
...
2025-09-06 15:02:02;323.680;19.08
2025-09-16 13:24:17;323.680;19.08

Download as NetCDF

# Import package
from dahitiapi.DAHITI import DAHITI

# Initialize DAHITI Class
dahiti = DAHITI()

# Select DAHITI target by DAHITI id
dahiti_id = 46208

# Download Water Surface Slope Time Series in NetCDF format and write to file
response = dahiti.download_water_surface_slope_netcdf_to_file(dahiti_id,'/tmp/46208_wss.nc')

Content of NetCDF file:

netcdf \46208_wss {
dimensions:
    time = 61 ;
variables:
    string datetime(time) ;
        datetime:standard_name = "UTC Datetime (YYYY-MM-DD HH:MM:SS)" ;
        datetime:valid_min = "2023-07-27 15:14:04" ;
        datetime:valid_max = "2025-09-16 13:24:17" ;
    float wss(time) ;
        wss:standard_name = "Water surface slope from SWOT" ;
        wss:unit = "mm/km" ;
        wss:valid_min = 323.68 ;
        wss:valid_max = 371.49 ;
    float wss_u(time) ;
        wss_u:standard_name = "Water surface slope uncertainty" ;
        wss_u:unit = "mm/km" ;
        wss_u:valid_min = 18.06 ;
        wss_u:valid_max = 19.65 ;

// global attributes:
    :dahiti_id = "46208" ;
    :dataset = "water-surface-slope" ;
    :target_name = "Regen, River" ;
    :location = "None" ;
    :country = "Germany" ;
    :continent = "Europe" ;
    :longitude = 12.4971 ;
    :latitude = 49.1942 ;
    :software = "10.0" ;
    :institution = "DGFI-TUM" ;
    :source = "DAHITI" ;
    :url = "https://dahiti.dgfi.tum.de/46208/" ;
    :creation_date = "2025-10-24 12:33:51" ;

data:

datetime = "2023-07-27 15:14:04", "2023-07-31 04:36:14",
    "2023-08-06 13:36:22", "2023-09-07 08:44:16", "2023-09-10 22:06:25",
    ...
    "2025-09-06 15:02:02", "2025-09-16 13:24:17" ;

wss = 323.68, 332.98, 328.43, 345.36, 335.18, 323.68, 357.11, 350.77,
    355.62, 371.49, 362.37, 365.57, 358.52, 366.49, 367.34, 366.49, 370.25,
    ...
    323.68, 323.68, 323.68, 337.33, 323.68, 323.68, 323.68, 323.68 ;

wss_u = 19.08, 19.32, 19.21, 19.55, 19.36, 19.08, 19.65, 19.61, 19.64,
    19.06, 19.62, 19.56, 19.65, 19.53, 19.5, 19.53, 18.53, 19.26, 19.36,
    ...
    19.08, 19.08 ;
}