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Merged
mabesa merged 2 commits into from
Oct 15, 2025
Merged

Switch to 20252026 season #19

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bd417ec
status before claude code
mabesa Oct 15, 2025
cdcf17f
no codes, no kyg gauges
mabesa Oct 15, 2025
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146 changes: 98 additions & 48 deletions mcass-dashboard.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,7 @@ def read_snow_situation_file(filepath):
df = pd.read_csv(filepath)
# Make sure the Date column is of type datetime
df['date'] = pd.to_datetime(df['date'])
print(f"read_snow_situation_file: df.head: \n{df.columns}\n{df.head()}")
# print(f"read_snow_situation_file: df.head: \n{df.columns}\n{df.head()}")
return df

def read_basin_geometry(filepath):
Expand All @@ -66,6 +66,32 @@ def read_basin_geometry(filepath):
#gdf = gpd.read_file('www/CA-discharge_basins_for_viz.gpkg') # No overlaps
gdf = gpd.read_file(filepath) # With overlaps

# Print column names and head of the geodataframe
print(f"read_basin_geometry: gdf.head: \n{gdf.columns}\n{gdf.head()}")

# Print unique values of gauges_COUNTRY
print(f"read_basin_geometry: unique values of gauges_COUNTRY: {gdf['gauges_COUNTRY'].unique()}")

# Drop basins of the country of Kyrgystan or don't have a country reference
gdf = gdf[gdf['gauges_COUNTRY'] != 'KYG']
gdf = gdf[gdf['gauges_COUNTRY'] != 'None']

# Further drop selected basins like 16936
gdf = gdf[gdf['CODE'] != '16936']

# Also drop the river with name "Kulduk"
gdf = gdf[gdf['gauges_RIVER'] != 'Kulduk']

# And drop the rivers with name "Karadarya" and "Chatkal"
gdf = gdf[gdf['gauges_RIVER'] != 'Karadarya']

# Now we drop transboundary rivers in the south of the Ferghana valley
#gdf = gdf[gdf['gauges_RIVER'] != 'Isfara']
gdf = gdf[gdf['CODE'] != '16175'] # River Koksu

# Drop Kyzylsu West river
gdf = gdf[gdf['gauges_RIVER'] != 'Kyzylsu West']

# Convert Multipolygons to Polygons, keeping the largest polygon
gdf['geometry'] = gdf['geometry'].apply(
lambda x: max(x.geoms, key=lambda a: a.area) if x.geom_type == 'MultiPolygon' else x)
Expand All @@ -88,35 +114,48 @@ def read_basin_geometry(filepath):
# Replace gauges_RIVER=='None' with 'Name unknown'
gdf['gauges_RIVER'] = gdf['gauges_RIVER'].replace('None', '<river name unknown>')

# Create a column with labels for the basins
gdf['label'] = gdf['CODE'] + ' - ' + gdf['gauges_RIVER']
# Create a display_name column with river name and basin area
gdf['display_name'] = gdf.apply(
lambda row: f"{row['gauges_RIVER']} ({int(row['area_km2'])} km²)"
if pd.notna(row['area_km2'])
else row['gauges_RIVER'],
axis=1
)

# Create a column with labels for the basins (used for map hover)
gdf['label'] = gdf['display_name']

# Sort rows by area_km2 in descending order (plot smallest last)
gdf = gdf.sort_values('area_km2', ascending=False)

# Read subbasins snow situation file
# Currently, not operational. The file shows snow situation data from end of
# March 2024.
df = read_snow_situation_file('data/subbasins_merged_data.csv')

# Merge columns 'swe_threshold' and 'hs_threshold' from df into gdf by 'CODE'
gdf = gdf.merge(df[['basin_id', 'swe_threshold', 'hs_threshold']],
left_on='CODE', right_on='basin_id', how='left')

# Read the regional snow situation file
df_regional = read_snow_situation_file('data/regions_merged_data.csv')
# Rename the swe and hs threshold columns to avoid conflicts
df_regional = df_regional.rename(columns={'swe_threshold': 'swe_threshold_regional',
'hs_threshold': 'hs_threshold_regional'})
# Merge columns 'swe_threshold_regional' and 'hs_threshold_regional' from
# df_regional into gdf by 'REGION'.
# We need to do a fuzzy merge because the 'REGION' column in gdf contains
# the full name of the region, while the 'REGION' column in df_regional
# contains the abbreviation of the region.
# Split the values in 'REGION' in gdf by '_' and take the first part
gdf['REG'] = gdf['REGION'].str.split('_').str[0]
gdf = gdf.merge(df_regional[['basin_id', 'swe_threshold_regional', 'hs_threshold_regional']],
left_on='REG', right_on='basin_id', how='left')

# Only merge subbasins_merged_data.csv if it exists and contains current year data
subbasins_file = 'data/subbasins_merged_data.csv'
if os.path.exists(subbasins_file):
try:
df = read_snow_situation_file(subbasins_file)
# Check if current year is present in the data
current_year = dt.datetime.now().year
if (df['date'].dt.year == current_year).any():
gdf = gdf.merge(df[['basin_id', 'swe_threshold', 'hs_threshold']],
left_on='CODE', right_on='basin_id', how='left')
except Exception as e:
print(f"Warning: Could not merge {subbasins_file}: {e}")

# Only merge regions_merged_data.csv if it exists and contains current year data
regions_file = 'data/regions_merged_data.csv'
if os.path.exists(regions_file):
try:
df_regional = read_snow_situation_file(regions_file)
current_year = dt.datetime.now().year
if (df_regional['date'].dt.year == current_year).any():
df_regional = df_regional.rename(columns={'swe_threshold': 'swe_threshold_regional',
'hs_threshold': 'hs_threshold_regional'})
gdf['REG'] = gdf['REGION'].str.split('_').str[0]
gdf = gdf.merge(df_regional[['basin_id', 'swe_threshold_regional', 'hs_threshold_regional']],
left_on='REG', right_on='basin_id', how='left')
except Exception as e:
print(f"Warning: Could not merge {regions_file}: {e}")

print(gdf.head())

Expand All @@ -131,10 +170,10 @@ def get_basin_selector_names_in_list(gdf):
gdf (geodataframe) basin geometry

Return:
list of basin codes and basin names
list of display names (river names with basin area, no CODEs)
"""
gdf_for_names = gdf.sort_values(['REGION', 'CODE'], ascending=[True, True])
options_list = list(gdf_for_names['label'].values)
gdf_for_names = gdf.sort_values(['REGION', 'gauges_RIVER'], ascending=[True, True])
options_list = list(gdf_for_names['display_name'].values)
return options_list

def get_region_selector_names_in_list(gdf):
Expand All @@ -160,13 +199,13 @@ def update_gdf_with_selected_basin(selected_basin, view_option):

Arguments:
gdf (geodataframe): GeoDataFrame with basin geometries
selected_basin (list): list of the selected basins
selected_basin (list): list of the selected basins (display names for sub-basin, region names for regional)

Return:
geodataframe with updated selected column
"""
#print("DEBUG: calling update_gdf_with_selected_basin with selected_basin: ", selected_basin)
#print("DEBUG: calling update_gdf_with_selected_basin with view_option: ", view_option)
print("DEBUG: calling update_gdf_with_selected_basin with selected_basin: ", selected_basin)
print("DEBUG: calling update_gdf_with_selected_basin with view_option: ", view_option)
try:
if selected_basin is not None and len(selected_basin) > 0:
if view_option == 'Regional':
Expand All @@ -177,8 +216,11 @@ def update_gdf_with_selected_basin(selected_basin, view_option):
else:
# Set all basins to False
gdf['selected'] = False
# Set the selected basin to True only if it is not empty
gdf.loc[gdf['label'] == selected_basin[0], 'selected'] = True
# Convert display name to CODE for matching
basin_code = display_name_to_basin_code.get(selected_basin[0])
if basin_code:
# Set the selected basin to True only if it is not empty
gdf.loc[gdf['CODE'] == basin_code, 'selected'] = True
return gdf
except Exception as e:
print(f'Error in update_gdf_with_selected_basin: \n {e}')
Expand Down Expand Up @@ -223,10 +265,10 @@ def get_subbasin_code_from_tap(x, y):
# Get the polygon with the minimum distance
clicked = gdf_projected.iloc[clicked_polygon_index]
#output.object=output.object+f'\nclicked: {clicked}'
#print("DEBUG: clicked['label']: ", clicked['label'])
basin_code = clicked['label']
#basin_name = clicked['BASIN']
return basin_code
#print("DEBUG: clicked['display_name']: ", clicked['display_name'])
# Return the display name (river name with basin area)
display_name = clicked['display_name']
return display_name
return None

def get_region_from_tap(x, y):
Expand Down Expand Up @@ -275,7 +317,7 @@ def read_current_data_for_basin(basin_code):
delimiter='\t')
# Make sure the Date column is of type datetime
dfcurrent['date'] = pd.to_datetime(dfcurrent['date'])
print(f"read_current_data_for_basin: dfcurrent.head: \n{dfcurrent.columns}\n{dfcurrent.tail()}")
#print(f"read_current_data_for_basin: dfcurrent.head: \n{dfcurrent.columns}\n{dfcurrent.head()}")
return dfcurrent
except Exception as e:
return f'Error in read_current_data_for_basin: \n {e}'
Expand All @@ -295,6 +337,7 @@ def read_previous_year_data_for_basin(basin_code):
# Add the difference in years between the first date in dfcurrent and
# the first date in dfprevious to the dates in dfprevious
dfprevious['date'] = dfprevious['date'] + pd.DateOffset(years=dfcurrent['date'].dt.year.values[0] - dfprevious['date'].dt.year.values[0])
print(f"read_previous_year_data_for_basin: dfprevious.head: \n{dfprevious.columns}\n{dfprevious.head()}")
return dfprevious
except Exception as e:
return f'Error in read_previous_year_data_for_basin: \n {e}'
Expand All @@ -315,6 +358,7 @@ def read_climate_data_for_basin(basin_code):
# Add the difference in years between the first date in dfcurrent and
# the first date in dfclimate to the dates in dfclimate
dfclimate['date'] = dfclimate['date'] + pd.DateOffset(years=dfcurrent['date'].dt.year.values[0] - dfclimate['date'].dt.year.values[0])
print(f"read_climate_data_for_basin: dfclimate.head: \n{dfclimate.columns}\n{dfclimate.head()}")
return dfclimate
except Exception as e:
return f'Error in read_climate_data_for_basin: \n {e}'
Expand All @@ -330,9 +374,13 @@ def read_climate_data_for_basin(basin_code):
basins_list = get_basin_selector_names_in_list(gdf)
regions_list = get_region_selector_names_in_list(gdf)

# Create mapping dictionaries for CODE <-> display name conversion
basin_code_to_display_name = dict(zip(gdf['CODE'], gdf['display_name']))
display_name_to_basin_code = dict(zip(gdf['display_name'], gdf['CODE']))

# Create a StaticText widget
basin_code_widget = pn.widgets.StaticText(name='Basin Code', value='')
output = pn.pane.Str("Default message. Prints: Basin code and name upon click on a basin.")
basin_code_widget = pn.widgets.StaticText(name='Basin name', value='')
output = pn.pane.Str("Default message. Prints: Basin name upon click on a basin.")

# Toggle variable in a widget
variable_options = pn.widgets.RadioButtonGroup(
Expand Down Expand Up @@ -491,9 +539,8 @@ def update_basin_selection_widget_with_region_selection(view_option):
basin_selection.param.value)
def plot_subbasin_data(variable, basin):
try:
# Read the basin code
#basin_code = get_subbasin_code(x, y)
basin_code = basin[0].split(' - ')[0]
# Read the basin code from display name
basin_code = display_name_to_basin_code.get(basin[0])
# Read the current data for the basin
dfcurrent = read_current_data_for_basin(basin_code)
# Get forecast data for the basin
Expand Down Expand Up @@ -529,7 +576,7 @@ def plot_subbasin_data(variable, basin):
dfforecast, vdims=['Q50_SWE'], label='Forecast',
kdims=['date']).opts(line_dash='dashed',
color=current_year_color, tools=['hover'])
title_str = f'SWE situation for basin of river {river_name} (gauge {basin_code})'
title_str = f'SWE situation for basin of river {river_name}'
ylabel_str = 'SWE (mm)'
elif variable == 'HS':
# Create an empty hv.curve object
Expand Down Expand Up @@ -559,7 +606,7 @@ def plot_subbasin_data(variable, basin):
dfforecast, vdims=['Q50_HS'], label='Forecast',
kdims=['date']).opts(line_dash='dashed',
color=current_year_color, tools=['hover'])
title_str = f'HS situation for basin of river {river_name} (gauge {basin_code})'
title_str = f'HS situation for basin of river {river_name}'
ylabel_str = 'HS (m)'
else:
area_climate = hv.Area(
Expand All @@ -582,7 +629,7 @@ def plot_subbasin_data(variable, basin):
dfforecast, vdims=['Q50_ROF'], label='Forecast',
kdims=['date']).opts(line_dash='dashed',
color=current_year_color, tools=['hover'])
title_str = f'Melt situation for basin of river {river_name} (gauge {basin_code})'
title_str = f'Melt situation for basin of river {river_name}'
ylabel_str = 'SM (mm)'
fig = (area_climate * curve_previous * curve_current * curve_forecast)\
.opts(
Expand Down Expand Up @@ -611,14 +658,17 @@ def plot_region_data(variable, basin):
basin_code = basin[0].split(' - ')[0]
# Read the current data for the basin
dfcurrent = read_current_data_for_basin(basin_code)
print(f"current data for basin {basin_code}: dfcurrent.head: \n{dfcurrent.columns}\n{dfcurrent.head()}")
# Get forecast data for the basin
dfforecast = dfcurrent[dfcurrent['FC'] == True]
dfcurrent = dfcurrent[dfcurrent['FC'] == False]
#output.object=f'\n\n{dfcurrent.head()}'
# Read previous year data for the basin
dfprevious = read_previous_year_data_for_basin(basin_code)
print(f"previous year data for basin {basin_code}: dfprevious.head: \n{dfprevious.columns}\n{dfprevious.head()}")
# Read the climate data for the basin
dfclimate = read_climate_data_for_basin(basin_code)
print(f"climate data for basin {basin_code}: dfclimate.head: \n{dfclimate.columns}\n{dfclimate.head()}")
#output.object=output.object+f'\n\n{dfclimate.head()}'
# Adapt the name of the river basin for the title
if basin_code == 'AMU_DARYA':
Expand Down Expand Up @@ -790,7 +840,7 @@ def get_snow_plot(value, variable, basin):
variable_options,
pn.pane.Markdown("<b>Select granularity of view:</b>\nRegional view: Show snow development in a regional basin.\nSub-basin view: Show snow development in a sub-basin."),
view_options,
pn.pane.Markdown("<b>Search for sub-basin by hydropost code:</b>"),
pn.pane.Markdown("<b>Search for sub-basin by river name:</b>"),
basin_selection,
pn.pane.Markdown(""),
refs],
Expand Down