README.md

+<<<<<<< HEAD
 # GlacierH2O
 
 
@@ -91,3 +92,6 @@ For open source projects, say how it is licensed.
 
 ## Project status
 If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
+=======
+# GLACIERH2O
+>>>>>>> new-main

analyze_glacier_data.py

+import pandas as pd
+import json
+# Generate visualizations and display them directly to the user using ace_tools
+import ace_tools as tools
+import matplotlib.pyplot as plt
+
+
+# Load the glacier data
+with open('/Users/hamza/glacier/data/glacier_data.json', 'r') as file:
+    glacier_data = json.load(file)
+
+# Load the GTN report data
+with open('/Users/hamza/glacier/data/gtn_report.json', 'r') as file:
+    gtn_report = json.load(file)
+
+# Convert to DataFrames for easier manipulation
+glacier_df = pd.DataFrame(glacier_data)
+gtn_df = pd.DataFrame(gtn_report)
+
+# Extract unique regions from glacier data
+unique_regions = glacier_df['region'].unique()
+
+# Mapping countries from GTN report to corresponding glacier regions manually
+region_country_mapping = {
+    "1_alaska": ["US - UNITED STATES"],
+    "2_western_canada_us": ["CA - CANADA", "US - UNITED STATES"],
+    "3_arctic_canada": ["CA - CANADA"],
+    "4_greenland": ["GL - GREENLAND"],
+    "5_iceland": ["IS - ICELAND"],
+    "6_svalbard_jan_mayen": ["SJ - SVALBARD AND JAN MAYEN"],
+    "7_scandinavia": ["NO - NORWAY", "SE - SWEDEN", "FI - FINLAND"],
+    "8_russian_arctic": ["RU - RUSSIAN FEDERATION"],
+    "9_siberia": ["RU - RUSSIAN FEDERATION"],
+    "10_central_asia": ["KZ - KAZAKHSTAN", "TJ - TAJIKISTAN", "UZ - UZBEKISTAN", "KG - KYRGYZSTAN"],
+    "11_himalaya": ["NP - NEPAL", "IN - INDIA", "CN - CHINA", "BT - BHUTAN", "PK - PAKISTAN"],
+    "12_caucasus_middle_east": ["GE - GEORGIA", "TR - TURKEY", "IR - IRAN"],
+    "13_southern_andes": ["CL - CHILE", "AR - ARGENTINA"],
+    "14_new_zealand": ["NZ - NEW ZEALAND"],
+    "15_africa": ["MA - MOROCCO"],
+    "16_antarctic": ["AQ - ANTARCTICA"],
+}
+
+# Assign regions to the GTN report based on country mapping
+def assign_region(country_code):
+    for region, countries in region_country_mapping.items():
+        if country_code in countries:
+            return region
+    return "Unknown"
+
+gtn_df['region'] = gtn_df['GRDCCOUNTRY'].apply(assign_region)
+
+# Merge glacier data with GTN report based on 'region'
+merged_df = pd.merge(glacier_df, gtn_df, on='region', how='inner')
+
+import ace_tools as tools; tools.display_dataframe_to_user(name="Merged Glacier and GTN Data", dataframe=merged_df)
+
+# Display the first few rows of the merged dataframe
+merged_df.head()
+
+
+
+# Plot 1: Glacier Mass Change vs Station Elevation
+fig1, ax1 = plt.subplots(figsize=(12, 8))
+ax1.scatter(merged_df['glacier_mass_change'], merged_df['station_elevation'], alpha=0.7, edgecolors='k', s=80)
+ax1.set_title('Glacier Mass Change vs Station Elevation', fontsize=14)
+ax1.set_xlabel('Glacier Mass Change (Gt)', fontsize=12)
+ax1.set_ylabel('Station Elevation (m)', fontsize=12)
+ax1.grid(True)
+
+# Plot 2: Average Glacier Mass Change by Region
+fig2, ax2 = plt.subplots(figsize=(14, 8))
+region_mass_change = merged_df.groupby('region')['glacier_mass_change'].mean().sort_values()
+region_mass_change.plot(kind='barh', ax=ax2, color='skyblue', edgecolor='black')
+ax2.set_title('Average Glacier Mass Change by Region', fontsize=14)
+ax2.set_xlabel('Average Mass Change (Gt)', fontsize=12)
+ax2.set_ylabel('Region', fontsize=12)
+ax2.grid(axis='x', linestyle='--', alpha=0.7)
+
+# Plot 3: Station Elevation vs Glacier Area
+fig3, ax3 = plt.subplots(figsize=(12, 8))
+ax3.scatter(merged_df['glacier_area'], merged_df['station_elevation'], alpha=0.7, color='green', edgecolors='k', s=80)
+ax3.set_title('Station Elevation vs Glacier Area', fontsize=14)
+ax3.set_xlabel('Glacier Area (km²)', fontsize=12)
+ax3.set_ylabel('Station Elevation (m)', fontsize=12)
+ax3.grid(True)
+
+# Display the plots to the user
+tools.display_dataframe_to_user(name="Merged Glacier and GTN Data", dataframe=merged_df)

app.py

+import dash
+from dash import dcc, html, Input, Output
+def trigger_event(event):
+    pass
+import plotly.express as px
+import plotly.graph_objects as go
+import pandas as pd
+import os
+import zipfile
+import numpy as np
+
+
+
+
+# Load and prepare data
+zip_path = "Glacier.zip"
+gtn_report_path = "GTN Report.xlsx"
+extract_dir = "glacier_data"
+
+# Extract glacier zip contents
+with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+    zip_ref.extractall(extract_dir)
+
+# Load regional glacier CSV files and assign approximate coordinates for visualization
+region_coordinates = {
+    '1_alaska': (64.2008, -149.4937),
+    '2_western_canada_us': (52.9399, -106.4509),
+    '3_arctic_canada_north': (75.0000, -100.0000),
+    '4_arctic_canada_south': (65.0000, -100.0000),
+    '5_greenland_periphery': (72.0000, -40.0000),
+    '6_iceland': (64.9631, -19.0208),
+    '7_svalbard': (78.0000, 16.0000),
+    '8_scandinavia': (60.0000, 15.0000),
+    '9_russian_arctic': (70.0000, 100.0000),
+    '10_north_asia': (60.0000, 90.0000),
+    '11_central_europe': (47.0000, 10.0000),
+    '12_caucasus_middle_east': (42.0000, 45.0000),
+    '13_central_asia': (43.0000, 75.0000),
+    '14_south_asia_west': (35.0000, 70.0000),
+    '15_south_asia_east': (27.0000, 85.0000),
+    '16_low_latitudes': (0.0000, -60.0000),
+    '17_southern_andes': (-40.0000, -70.0000),
+    '18_new_zealand': (-41.2865, 174.7762),
+    '19_antarctic_and_subantarctic': (-75.0000, 0.0000)
+}
+
+# Load glacier data into a combined DataFrame
+glacier_data = []
+region_files = [file for file in os.listdir(extract_dir) if file.endswith('.csv') and file != '0_global.csv']
+for file in region_files:
+    region_name = file.replace('.csv', '')
+    df_region = pd.read_csv(os.path.join(extract_dir, file))
+    df_region['region'] = region_name
+    df_region['latitude'], df_region['longitude'] = region_coordinates.get(region_name, (0, 0))
+    glacier_data.append(df_region)
+
+df_glacier_regions = pd.concat(glacier_data, ignore_index=True)
+
+# Simulate river discharge based on glacier melt trends
+def simulate_discharge(glacier_mass_loss):
+    max_discharge = 500  # Max discharge in cubic meters per second
+    normalized_loss = (glacier_mass_loss - glacier_mass_loss.min()) / (glacier_mass_loss.max() - glacier_mass_loss.min())
+    simulated_discharge = max_discharge * (1 - normalized_loss) + np.random.normal(0, 10, size=len(glacier_mass_loss))
+    return np.clip(simulated_discharge, 50, max_discharge)
+
+# Enhance DataFrame with simulated discharge
+df_glacier_regions['simulated_discharge'] = simulate_discharge(df_glacier_regions['combined_gt'])
+
+# Initialize Dash app
+app = dash.Dash(__name__)
+app.title = "Glacier Melt Impact on Water Resources - Interactive Visualization"
+
+# Layout with 3D globe map and a side chart for selected region details
+app.layout = html.Div([
+    html.H1("🌍 Glacier Melt and Water Resources Visualization",
+            style={'textAlign': 'center', 'fontSize': '28px', 'marginBottom': '20px', 'color': '#2C3E50'}),
+
+    html.Div([
+        dcc.Graph(id='world-map-visualization', style={'height': '75vh', 'width': '65%', 'display': 'inline-block'}),
+        dcc.Graph(id='region-detail-chart', style={'height': '75vh', 'width': '33%', 'display': 'inline-block', 'paddingLeft': '1%'})
+    ], style={'display': 'flex', 'justifyContent': 'center'}),
+
+    html.Div([
+        html.Label("⏩ Animation Speed:", style={'fontWeight': 'bold', 'fontSize': '16px'}),
+        dcc.Slider(
+            id='animation-speed',
+            min=50,
+            max=1000,
+            step=50,
+            value=300,
+            marks={50: 'Fast', 500: 'Medium', 1000: 'Slow'},
+            tooltip={"placement": "bottom", "always_visible": True}
+        )
+    ], style={'width': '60%', 'margin': 'auto', 'paddingTop': '20px'})
+])
+
+# Callback to update the 3D world map for smoother panning and zooming
+@app.callback(
+    Output('world-map-visualization', 'figure'),
+    [Input('animation-speed', 'value')]
+)
+def update_world_map(animation_speed):
+    min_size, max_size = 4, 15
+    normalized_sizes = (
+        (df_glacier_regions['glacier_area'] - df_glacier_regions['glacier_area'].min()) /
+        (df_glacier_regions['glacier_area'].max() - df_glacier_regions['glacier_area'].min())
+    )
+    bubble_sizes = normalized_sizes * (max_size - min_size) + min_size
+
+    fig = go.Figure()
+    fig.add_trace(go.Scattergeo(
+        lat=df_glacier_regions['latitude'],
+        lon=df_glacier_regions['longitude'],
+        mode='markers',
+        marker=dict(
+            size=bubble_sizes,
+            color=df_glacier_regions['simulated_discharge'],
+            colorscale='Viridis',
+            cmin=df_glacier_regions['simulated_discharge'].min(),
+            cmax=df_glacier_regions['simulated_discharge'].max(),
+            showscale=True,
+            colorbar=dict(title="Discharge (m³/s)", thickness=15, len=0.5),
+            line=dict(width=0.4, color='DarkSlateGrey')
+        ),
+        text=df_glacier_regions.apply(lambda row: (
+            f"Region: {row['region']}<br>Year: {row['end_dates']}<br>Glacier Area: {row['glacier_area']:.2f} km²<Br>Discharge: {row['simulated_discharge']:.2f} m³/s"
+        ), axis=1),
+        hoverinfo='text',
+        customdata=df_glacier_regions[['region']]
+    ))
+
+    fig.update_geos(
+        projection_type="orthographic",
+        showland=True,
+        landcolor="rgb(230, 230, 230)",
+        showocean=True,
+        oceancolor="rgb(180, 210, 255)",
+        showcountries=True,
+        countrycolor="rgb(150, 150, 150)",
+        center=dict(lat=20, lon=0),
+        resolution=50,
+    )
+
+    fig.update_layout(
+        title="🌍 3D Globe - Glacier Melt and Water Resources",
+        margin=dict(l=0, r=0, t=40, b=0),
+        dragmode='pan',
+        geo=dict(
+            projection_rotation=dict(lon=0, lat=0),
+            projection_scale=0.9,
+            lataxis=dict(range=[-90, 90]),
+            lonaxis=dict(range=[-180, 180]),
+        ),
+        font=dict(family="Arial", size=13, color="#2C3E50"),
+    )
+
+    return fig
+
+# Callback to update the region detail chart when a bubble is clicked
+@app.callback(
+    Output('region-detail-chart', 'figure'),
+    [Input('world-map-visualization', 'clickData')]
+)
+def update_region_chart(clickData):
+    if not clickData:
+        return go.Figure(layout=dict(title="Select a region to see details", font=dict(size=14)))
+
+    selected_region = clickData['points'][0]['customdata'][0]
+    region_data = df_glacier_regions[df_glacier_regions['region'] == selected_region].sort_values(by='end_dates')
+
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(
+        x=region_data['end_dates'],
+        y=region_data['combined_gt'],
+        mode='lines+markers',
+        name='Glacier Mass Change (Gt)',
+        line=dict(color='blue')
+    ))
+    fig.add_trace(go.Scatter(
+        x=region_data['end_dates'],
+        y=region_data['simulated_discharge'],
+        mode='lines+markers',
+        name='Simulated River Discharge (m³/s)',
+        line=dict(color='green')
+    ))
+
+    fig.update_layout(
+        title=f"Glacier Mass vs Water Discharge - {selected_region.replace('_', ' ').title()}",
+        xaxis_title="Year",
+        yaxis_title="Value",
+        legend=dict(x=0.02, y=0.98),
+        margin=dict(l=30, r=20, t=40, b=40),
+        font=dict(family="Arial", size=12)
+    )
+
+    return fig
+
+if __name__ == '__main__':
+    app.run_server(debug=True, port=8060)
+

css/styles.css

+:root {
+  --background-color: #f4f4f9;
+  --text-color: #34495e;
+  --button-bg: #34495e;
+  --button-text: #fff;
+  --box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
+  --border-radius: 12px;
+}
+
+.dark-mode {
+  --background-color: #2c3e50;
+  --text-color: #ecf0f1;
+  --button-bg: #e74c3c;
+  --button-text: #fff;
+  --box-shadow: 0 4px 8px rgba(0, 0, 0, 0.4);
+}
+
+body {
+  font-family: Arial, sans-serif;
+  background-color: var(--background-color);
+  color: var(--text-color);
+  margin: 0;
+  padding: 10px;
+  height: 100vh;
+  display: flex;
+  flex-direction: column;
+}
+
+h1 {
+  font-size: 30px;
+  font-weight: bold;
+  margin-bottom: 20px;
+  text-align: center;
+}
+
+#controls {
+  display: flex;
+  justify-content: center;
+  align-items: center;
+  gap: 15px;
+  padding: 10px;
+  margin-bottom: 15px;
+  background-color: var(--background-color);
+  border-radius: var(--border-radius);
+  box-shadow: var(--box-shadow);
+}
+
+.dark-mode #controls {
+  background-color: #34495e !important;
+  box-shadow: 0 4px 8px rgba(0, 0, 0, 0.4) !important;
+}
+
+.dark-mode #controls button, 
+.dark-mode #controls select, 
+.dark-mode #controls input,
+.dark-mode #controls label {
+  color: #ecf0f1 !important;
+  background-color: rgba(255, 255, 255, 0.1) !important;
+  border: 1px solid rgba(255, 255, 255, 0.2) !important;
+}
+
+.year-control {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+}
+
+#year-input {
+  width: 70px;
+  padding: 5px;
+  border-radius: 6px;
+  text-align: center;
+  border: 1px solid #ccc;
+}
+
+#year-slider {
+  width: 200px;
+}
+
+button, select, input[type="number"], input[type="range"] {
+  padding: 6px 12px;
+  border-radius: 8px;
+  border: 1px solid #ccc;
+  cursor: pointer;
+  transition: all 0.2s ease;
+}
+
+button:hover, select:hover, input:hover {
+  box-shadow: 0 0 8px rgba(0, 0, 0, 0.3);
+}
+
+#container {
+  display: flex;
+  justify-content: space-between;
+  gap: 20px;
+  flex-grow: 1;
+}
+
+#map-container {
+  flex: 1;
+  max-width: 70%;
+  height: 80vh;
+  position: relative; 
+  border-radius: var(--border-radius);
+  box-shadow: var(--box-shadow);
+}
+
+#map {
+  width: 100%;
+  height: 100%;
+  border-radius: var(--border-radius);
+  position: relative;
+  z-index: 1; 
+}
+
+#chart-container {
+  flex: 1;
+  max-width: 28%;
+  height: 80vh;
+  display: flex;
+  flex-direction: column;
+  gap: 20px;
+}
+
+#region-chart {
+  width: 100%;
+  height: 100%;
+  border-radius: var(--border-radius);
+  box-shadow: var(--box-shadow);
+}
+
+/* Legend Styles */
+#legend {
+  position: absolute;
+  top: 10px;
+  right: 10px;
+  background-color: rgba(255, 255, 255, 0.9);
+  padding: 10px;
+  border-radius: 8px;
+  box-shadow: var(--box-shadow);
+  font-weight: bold;
+  width: 200px;
+  z-index: 1002; 
+}
+
+#legend .legend-title {
+  text-align: center;
+  font-size: 14px;
+  margin-bottom: 8px;
+}
+
+#legend .legend-item {
+  display: flex;
+  align-items: center;
+  margin-bottom: 5px;
+}
+
+#legend .color-box {
+  width: 20px;
+  height: 20px;
+  margin-right: 8px;
+  border-radius: 4px;
+  border: 1px solid #ccc;
+}
\ No newline at end of file

data/glacier_data.json

+[
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2000.0,
+        "end_date": 2001.0,
+        "glacier_area": 1282.75515,
+        "glacier_mass_change": -1.5256898932375544,
+        "simulated_discharge": 441.54079982858934,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2001.0,
+        "end_date": 2002.0,
+        "glacier_area": 1275.82805,
+        "glacier_mass_change": -0.7523721686565512,
+        "simulated_discharge": 283.5918221724801,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2002.0,
+        "end_date": 2003.0,
+        "glacier_area": 1268.90095,
+        "glacier_mass_change": 0.3736522375370595,
+        "simulated_discharge": 53.60303732926075,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2003.0,
+        "end_date": 2004.0,
+        "glacier_area": 1261.97385,
+        "glacier_mass_change": 0.3913096299000091,
+        "simulated_discharge": 49.996541599046154,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2004.0,
+        "end_date": 2005.0,
+        "glacier_area": 1255.04675,
+        "glacier_mass_change": 0.6360925487896292,
+        "simulated_discharge": 0.0,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2005.0,
+        "end_date": 2006.0,
+        "glacier_area": 1248.11965,
+        "glacier_mass_change": 0.2166234935187321,
+        "simulated_discharge": 85.67592120600898,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2006.0,
+        "end_date": 2007.0,
+        "glacier_area": 1241.19255,
+        "glacier_mass_change": -1.0808310207835916,
+        "simulated_discharge": 350.6790467976166,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2007.0,
+        "end_date": 2008.0,
+        "glacier_area": 1234.26545,
+        "glacier_mass_change": -1.5967452192637428,
+        "simulated_discharge": 456.05374288694077,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2008.0,
+        "end_date": 2009.0,
+        "glacier_area": 1227.33835,
+        "glacier_mass_change": -0.5404262217384886,
+        "simulated_discharge": 240.3021825199011,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2009.0,
+        "end_date": 2010.0,
+        "glacier_area": 1220.41125,
+        "glacier_mass_change": -0.4336528707431656,
+        "simulated_discharge": 218.49388679026964,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2010.0,
+        "end_date": 2011.0,
+        "glacier_area": 1213.48415,
+        "glacier_mass_change": -0.8591613718604939,
+        "simulated_discharge": 305.40335569178774,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2011.0,
+        "end_date": 2012.0,
+        "glacier_area": 1206.55705,
+        "glacier_mass_change": -0.7173569958488278,
+        "simulated_discharge": 276.4400259939708,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2012.0,
+        "end_date": 2013.0,
+        "glacier_area": 1199.62995,
+        "glacier_mass_change": -1.8119059633143595,
+        "simulated_discharge": 500.0,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2013.0,
+        "end_date": 2014.0,
+        "glacier_area": 1192.70285,
+        "glacier_mass_change": -0.2524468555698191,
+        "simulated_discharge": 181.48283178403014,
+        "latitude": 42.0,
+        "longitude": 45.0
+    },
+    {
+        "region": "12_caucasus_middle_east",
+        "start_date": 2014.0,
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+]
\ No newline at end of file

data/gtn_report.json

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+    {
+        "station_name":"URENGOY",
+        "station_no":2997120,
+        "station_id":1073406,
+        "station_latitude":65.97,
+        "station_longitude":78.35,
+        "station_status":"Active",
+        "river_name":"PUR",
+        "station_elevation":6.0,
+        "CATCHMENT_SIZE":"80400,00 km\u00b2",
+        "NAT_STA_ID":"11571",
+        "GRDCCOUNTRY":"RU - RUSSIAN FEDERATION"
+    },
+    {
+        "station_name":"USINA ALTAMIRA",
+        "station_no":3652039,
+        "station_id":1068538,
+        "station_latitude":-11.73472,
+        "station_longitude":-37.80333,
+        "station_status":"Active",
+        "river_name":"RIO ITAPICURU",
+        "station_elevation":17.0,
+        "CATCHMENT_SIZE":"35150,00 km\u00b2",
+        "NAT_STA_ID":"50595000",
+        "GRDCCOUNTRY":"BR - BRAZIL"
+    },
+    {
+        "station_name":"USK",
+        "station_no":4245250,
+        "station_id":1068072,
+        "station_latitude":54.630554,
+        "station_longitude":-128.43195,
+        "station_status":"Active",
+        "river_name":"SKEENA RIVER",
+        "station_elevation":100.0,
+        "CATCHMENT_SIZE":"42200,00 km\u00b2",
+        "NAT_STA_ID":"08EF001",
+        "GRDCCOUNTRY":"CA - CANADA"
+    },
+    {
+        "station_name":"UST'-PINEGA",
+        "station_no":6970250,
+        "station_id":1067225,
+        "station_latitude":64.13,
+        "station_longitude":41.92,
+        "station_status":"Active",
+        "river_name":"SEVERNAYA DVINA",
+        "station_elevation":2.0,
+        "CATCHMENT_SIZE":"348000,00 km\u00b2",
+        "NAT_STA_ID":"70801",
+        "GRDCCOUNTRY":"RU - RUSSIAN FEDERATION"
+    },
+    {
+        "station_name":"VARGOENS KRV",
+        "station_no":6233315,
+        "station_id":1066477,
+        "station_latitude":58.3551,
+        "station_longitude":12.3749,
+        "station_status":"Active",
+        "river_name":"GOTA ALV",
+        "station_elevation":44.0,
+        "CATCHMENT_SIZE":"46882,71 km\u00b2",
+        "NAT_STA_ID":"1954",
+        "GRDCCOUNTRY":"SE - SWEDEN"
+    },
+    {
+        "station_name":"VARZUGA",
+        "station_no":6971600,
+        "station_id":1067783,
+        "station_latitude":66.4,
+        "station_longitude":36.58,
+        "station_status":"Active",
+        "river_name":"VARZUGA",
+        "station_elevation":9.0,
+        "CATCHMENT_SIZE":"7940,00 km\u00b2",
+        "NAT_STA_ID":"71186",
+        "GRDCCOUNTRY":"RU - RUSSIAN FEDERATION"
+    },
+    {
+        "station_name":"VERKHNE-TULOMSKIY GES",
+        "station_no":6971130,
+        "station_id":1066124,
+        "station_latitude":68.6,
+        "station_longitude":31.75,
+        "station_status":"Active",
+        "river_name":"TULOMA",
+        "station_elevation":-999.0,
+        "CATCHMENT_SIZE":"17500,00 km\u00b2",
+        "NAT_STA_ID":"71060",
+        "GRDCCOUNTRY":"RU - RUSSIAN FEDERATION"
+    },
+    {
+        "station_name":"VERNOR",
+        "station_no":5101503,
+        "station_id":1074240,
+        "station_latitude":-27.4675,
+        "station_longitude":152.599,
+        "station_status":"Closed",
+        "river_name":"BRISBANE RIVER",
+        "station_elevation":21.83,
+        "CATCHMENT_SIZE":"10056,00 km\u00b2",
+        "NAT_STA_ID":"143001B",
+        "GRDCCOUNTRY":"AU - AUSTRALIA"
+    },
+    {
+        "station_name":"VICKSBURG, MS",
+        "station_no":4127800,
+        "station_id":1068162,
+        "station_latitude":32.315,
+        "station_longitude":-90.9058,
+        "station_status":"Active",
+        "river_name":"MISSISSIPPI RIVER",
+        "station_elevation":14.09,
+        "CATCHMENT_SIZE":"2964255,00 km\u00b2",
+        "NAT_STA_ID":"07289000",
+        "GRDCCOUNTRY":"US - UNITED STATES"
+    },
+    {
+        "station_name":"VINCES-DCP",
+        "station_no":3844450,
+        "station_id":1068372,
+        "station_latitude":-1.549167,
+        "station_longitude":-79.750556,
+        "station_status":"Active",
+        "river_name":"RIO VINCES",
+        "station_elevation":41.0,
+        "CATCHMENT_SIZE":"4400,00 km\u00b2",
+        "NAT_STA_ID":"H348",
+        "GRDCCOUNTRY":"EC - ECUADOR"
+    },
+    {
+        "station_name":"VIOOLSDRIF (27811003)",
+        "station_no":1159100,
+        "station_id":1067539,
+        "station_latitude":-28.75798997,
+        "station_longitude":17.72159144,
+        "station_status":"Active",
+        "river_name":"ORANGE RIVER",
+        "station_elevation":152.0,
+        "CATCHMENT_SIZE":"866486,00 km\u00b2",
+        "NAT_STA_ID":"D8H003",
+        "GRDCCOUNTRY":"ZA - SOUTH AFRICA"
+    },
+    {
+        "station_name":"VOLGOGRAD POWER PLANT",
+        "station_no":6977100,
+        "station_id":1067161,
+        "station_latitude":48.804722,
+        "station_longitude":44.585833,
+        "station_status":"Active",
+        "river_name":"VOLGA",
+        "station_elevation":null,
+        "CATCHMENT_SIZE":"1360000,00 km\u00b2",
+        "NAT_STA_ID":null,
+        "GRDCCOUNTRY":"RU - RUSSIAN FEDERATION"
+    },
+    {
+        "station_name":"VORONTSOVO",
+        "station_no":2903981,
+        "station_id":1071852,
+        "station_latitude":69.58,
+        "station_longitude":147.35,
+        "station_status":"Closed",
+        "river_name":"INDIGIRKA",
+        "station_elevation":4.0,
+        "CATCHMENT_SIZE":"305000,00 km\u00b2",
+        "NAT_STA_ID":"03871",
+        "GRDCCOUNTRY":"RU - RUSSIAN FEDERATION"
+    },
+    {
+        "station_name":"WALKERS BEND",
+        "station_no":5109151,
+        "station_id":1073749,
+        "station_latitude":-18.1617,
+        "station_longitude":140.858,
+        "station_status":"Active",
+        "river_name":"FLINDERS RIVER",
+        "station_elevation":2.097,
+        "CATCHMENT_SIZE":"106300,00 km\u00b2",
+        "NAT_STA_ID":"915003A",
+        "GRDCCOUNTRY":"AU - AUSTRALIA"
+    },
+    {
+        "station_name":"WALLA",
+        "station_no":5101470,
+        "station_id":1073745,
+        "station_latitude":-25.1362,
+        "station_longitude":151.982,
+        "station_status":"Active",
+        "river_name":"BURNETT RIVER",
+        "station_elevation":16.427,
+        "CATCHMENT_SIZE":"32455,00 km\u00b2",
+        "NAT_STA_ID":"136001B",
+        "GRDCCOUNTRY":"AU - AUSTRALIA"
+    },
+    {
+        "station_name":"WHARTON, TEX.",
+        "station_no":4150450,
+        "station_id":1069475,
+        "station_latitude":29.3091,
+        "station_longitude":-96.1038,
+        "station_status":"Active",
+        "river_name":"COLORADO RIVER",
+        "station_elevation":15.98,
+        "CATCHMENT_SIZE":"108788,00 km\u00b2",
+        "NAT_STA_ID":"08162000",
+        "GRDCCOUNTRY":"US - UNITED STATES"
+    },
+    {
+        "station_name":"WILLARE",
+        "station_no":5607025,
+        "station_id":1074209,
+        "station_latitude":-17.7362,
+        "station_longitude":123.646,
+        "station_status":"Active",
+        "river_name":"FITZROY RIVER",
+        "station_elevation":19.0,
+        "CATCHMENT_SIZE":"91902,00 km\u00b2",
+        "NAT_STA_ID":"802008",
+        "GRDCCOUNTRY":"AU - AUSTRALIA"
+    },
+    {
+        "station_name":"WUZHOU 3",
+        "station_no":2186800,
+        "station_id":1073307,
+        "station_latitude":23.48,
+        "station_longitude":111.3,
+        "station_status":"Active",
+        "river_name":"XI JIANG",
+        "station_elevation":null,
+        "CATCHMENT_SIZE":"329705,00 km\u00b2",
+        "NAT_STA_ID":"81016",
+        "GRDCCOUNTRY":"CN - CHINA"
+    }
+]
\ No newline at end of file

data/region_to_country_mapping.csv

+

data_analysis.py

+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+# Load the glacier data (assumed to be preloaded)
+region_data = pd.read_csv('glacier_data/1_alaska.csv')  # Example file, adjust as necessary
+
+# Load the GTN dataset
+gtn_data = pd.read_excel('GTN Report.xlsx')  # Example for GTN data
+
+# Set the plot style
+sns.set(style="whitegrid")
+
+# Create a figure with 3 subplots
+fig, axes = plt.subplots(3, 1, figsize=(10, 18))
+fig.suptitle('Glacier and River Discharge Visualization Prototype', fontsize=16)
+
+# 1. Time-based Change (Glacier Mass Change Over Time)
+axes[0].plot(region_data['end_dates'], region_data['combined_gt'], marker='o', color='b', label='Mass Change (Gt)')
+axes[0].set_title('Glacier Mass Change Over Time', fontsize=14)
+axes[0].set_xlabel('Year')
+axes[0].set_ylabel('Mass Change (Gt)')
+axes[0].legend()
+
+# 2. Size-based Relationship (Glacier Area vs. Glacier Mass Change)
+axes[1].scatter(region_data['glacier_area'], region_data['combined_gt'], c=region_data['end_dates'], cmap='viridis')
+axes[1].set_title('Glacier Area vs. Mass Change', fontsize=14)
+axes[1].set_xlabel('Glacier Area (km²)')
+axes[1].set_ylabel('Mass Change (Gt)')
+cbar = fig.colorbar(plt.cm.ScalarMappable(cmap='viridis'), ax=axes[1])
+cbar.set_label('Year')
+
+# 3. Scatter Plot: Glacier Mass Change vs. Catchment Size (Matching regions and years)
+# Filter data for matching years and regions (for Alaska in this case)
+region_name = 'alaska'
+catchment_data = gtn_data[gtn_data['river_name'].str.contains(region_name, case=False, na=False)]  # Adjust for region
+
+# Merge datasets based on year (assuming region_data and catchment_data are aligned)
+merged_data = pd.merge(region_data, catchment_data, left_on='end_dates', right_on='station_elevation', how='inner')
+
+# Ensure both datasets have matching rows
+if not merged_data.empty:
+    axes[2].scatter(merged_data['CATCHMENT_SIZE'], merged_data['combined_gt'], color='r', alpha=0.5)
+    axes[2].set_title('Glacier Mass Change vs. Catchment Size', fontsize=14)
+    axes[2].set_xlabel('Catchment Size (km²)')
+    axes[2].set_ylabel('Mass Change (Gt)')
+else:
+    axes[2].text(0.5, 0.5, 'No matching data for selected region', ha='center', va='center', fontsize=12, color='red')
+
+plt.tight_layout(rect=[0, 0, 1, 0.97])
+plt.show()

data_preprocessing.py

+import zipfile
+import pandas as pd
+import json
+import os
+
+# Paths
+zip_path = "Glacier.zip"
+xlsx_path = "GTN Report.xlsx"
+extract_dir = "glacier_data"
+output_dir = "data"
+
+# Create data directory if it doesn't exist
+os.makedirs(output_dir, exist_ok=True)
+
+# Process glacier data
+glacier_data = []
+region_coordinates = {
+    '1_alaska': (64.2008, -149.4937), '2_western_canada_us': (52.9399, -106.4509),
+    '3_arctic_canada_north': (75.0, -100.0), '4_arctic_canada_south': (65.0, -100.0),
+    '5_greenland_periphery': (72.0, -40.0), '6_iceland': (64.9631, -19.0208),
+    '7_svalbard': (78.0, 16.0), '8_scandinavia': (60.0, 15.0),
+    '9_russian_arctic': (70.0, 100.0), '10_north_asia': (60.0, 90.0),
+    '11_central_europe': (47.0, 10.0), '12_caucasus_middle_east': (42.0, 45.0),
+    '13_central_asia': (43.0, 75.0), '14_south_asia_west': (35.0, 70.0),
+    '15_south_asia_east': (27.0, 85.0), '16_low_latitudes': (0.0, -60.0),
+    '17_southern_andes': (-40.0, -70.0), '18_new_zealand': (-41.2865, 174.7762),
+    '19_antarctic_and_subantarctic': (-75.0, 0.0)
+}
+
+for file in os.listdir(extract_dir):
+    if file.endswith('.csv') and file != '0_global.csv':
+        region = file.replace('.csv', '')
+        df = pd.read_csv(os.path.join(extract_dir, file))
+        lat, lon = region_coordinates.get(region, (0, 0))
+        for _, row in df.iterrows():
+            glacier_data.append({
+                "region": region,
+                "start_date": row['start_dates'],
+                "end_date": row['end_dates'],
+                "glacier_area": row['glacier_area'],
+                "glacier_mass_change": row['combined_gt'],
+                "simulated_discharge": 500 * (1 - ((row['combined_gt'] - df['combined_gt'].min()) / (df['combined_gt'].max() - df['combined_gt'].min()))),
+                "latitude": lat,
+                "longitude": lon
+            })
+
+# Save glacier data to JSON
+with open(os.path.join(output_dir, 'glacier_data.json'), 'w') as f:
+    json.dump(glacier_data, f, indent=4)
+
+# Convert GTN Report to JSON
+df_gtn = pd.read_excel(xlsx_path)
+df_gtn.to_json(os.path.join(output_dir, 'gtn_report.json'), orient='records', indent=4)
+
+print("✅ Data successfully converted and saved in 'data/' directory.")

glacier_data/0_global.csv

+start_dates,end_dates,glacier_area,region,combined_gt,combined_gt_errors,combined_mwe,combined_mwe_errors
+2000.0,2001.0,704082.6956499998,global,-78.04414729402814,111.56095088251794,-0.1111786793375206,0.1583621138501352
+2001.0,2002.0,701805.4987500003,global,-215.16931097001844,95.3001011576375,-0.3075164866023069,0.1350498121659405
+2002.0,2003.0,699528.3018500003,global,-128.46636738674923,91.14634450070768,-0.1841997326262217,0.1289299604899674
+2003.0,2004.0,697251.1049500001,global,-192.6724697716301,72.79887688516011,-0.2771630264606625,0.1028951725208123
+2004.0,2005.0,694973.9080500001,global,-229.2369109878561,73.022158218317,-0.3308421919121849,0.1028436503023272
+2005.0,2006.0,692696.71115,global,-315.0371756633185,74.19065798809451,-0.4561666396999292,0.1044578602427483
+2006.0,2007.0,690419.51425,global,-279.8898739792978,72.77317030930298,-0.4066108567264724,0.1025138185768302
+2007.0,2008.0,688142.31735,global,-323.16570882967466,71.78509732133082,-0.4710335566158922,0.1010360421851532
+2008.0,2009.0,685865.12045,global,-178.6324817323364,71.86184704387401,-0.2612321087124307,0.1011209402057232
+2009.0,2010.0,683587.9235500002,global,-231.2381243724868,71.29354455724742,-0.3392890923913098,0.1001020384598227
+2010.0,2011.0,681310.7266500002,global,-231.1966727048064,72.2582027545506,-0.3403621001158775,0.101352981542154
+2011.0,2012.0,679033.5297499998,global,-365.9472468839626,68.11267549573648,-0.540545313270877,0.0950926143458494
+2012.0,2013.0,676756.3328500001,global,-188.0208512243996,67.35045471659744,-0.2786624991943321,0.0941254547446842
+2013.0,2014.0,674479.1359500001,global,-304.73798136525033,66.47051377096227,-0.4531718327704068,0.0925856747213776
+2014.0,2015.0,672201.9390499997,global,-149.889416279315,65.94044282966604,-0.2236536803279121,0.0920570437100916
+2015.0,2016.0,669924.74215,global,-284.97423508815865,66.77259130583126,-0.4266624477275931,0.0932270670335857
+2016.0,2017.0,667647.5452499996,global,-340.6076946742656,68.35959222730513,-0.5116960211749099,0.0952916518024702
+2017.0,2018.0,665370.3483500001,global,-217.68675972042345,66.39070274109359,-0.3281507593734814,0.0924077513562398
+2018.0,2019.0,663093.1514499999,global,-243.81282612823085,66.54077158950466,-0.3687965484035694,0.0924649491234518
+2019.0,2020.0,660815.9545499999,global,-412.9645781490086,69.99144862252744,-0.6268117422048606,0.0969733224466875
+2020.0,2021.0,658538.75765,global,-405.0394156368366,76.20680182507151,-0.6169085501621713,0.1065416966938755
+2021.0,2022.0,656261.5607500002,global,-217.7163545547422,81.6846283807594,-0.3327506622695744,0.1151000186974428
+2022.0,2023.0,653984.3638500002,global,-460.2989143829609,100.8285184125692,-0.7059556646949124,0.138700930079604
+2023.0,2024.0,651707.1669499998,global,-548.025110248126,120.16099017378784,-0.8434372990227316,0.1662574332317422

glacier_data/10_north_asia.csv

+start_dates,end_dates,glacier_area,region,combined_gt,combined_gt_errors,combined_mwe,combined_mwe_errors
+2000.0,2001.0,2487.7225,north_asia,-0.9197019532932548,1.0265275291265996,-0.3708087865014635,0.4267978293382843
+2001.0,2002.0,2477.3595,north_asia,-1.5411560324271425,0.5757372429047373,-0.6239681453842844,0.2374580820623789
+2002.0,2003.0,2466.9965,north_asia,-2.008519104670919,0.5971520843045376,-0.8166054524398674,0.2449868095663878
+2003.0,2004.0,2456.6335,north_asia,-1.3367036448471714,0.5605964144603081,-0.5457573636092294,0.2316484965833838
+2004.0,2005.0,2446.2705,north_asia,-0.6073020718796399,0.5800062732919948,-0.2490033135176266,0.2410596415169421
+2005.0,2006.0,2435.9075,north_asia,-0.4421699496148141,0.543997009186656,-0.1820678539590347,0.2262170617791567
+2006.0,2007.0,2425.5445,north_asia,-1.4369095884292484,0.5547031793605927,-0.5941895884796716,0.2289152797255827
+2007.0,2008.0,2415.1815,north_asia,-1.5576011706781698,0.555112921025605,-0.6468615442700755,0.2287454249490515
+2008.0,2009.0,2404.8185,north_asia,-1.7288465569663265,0.5495905128318924,-0.7210725895012671,0.2258850833242974
+2009.0,2010.0,2394.4555,north_asia,0.4721992168201645,0.5558080553432801,0.1977986548721905,0.2311109134930584
+2010.0,2011.0,2384.0925,north_asia,-1.278298719425217,0.549382943810827,-0.5377916984722222,0.2270930475136839
+2011.0,2012.0,2373.7295,north_asia,-2.1266620946428576,0.5504841757070587,-0.8986117746265077,0.2247891996692553
+2012.0,2013.0,2363.3665,north_asia,-2.082237426114749,0.5503336578162555,-0.8836982900957205,0.2249054279600158
+2013.0,2014.0,2353.0035,north_asia,-0.9064403927766193,0.5632256664521381,-0.3863861215956616,0.2336466676687554
+2014.0,2015.0,2342.6405,north_asia,-0.7676348462089759,0.5665440381989155,-0.3286653160182816,0.2352461601417673
+2015.0,2016.0,2332.2775,north_asia,-1.9092539350345972,0.578671943989981,-0.8210853690566785,0.2375356175403869
+2016.0,2017.0,2321.9145,north_asia,-1.0968359067228153,0.5699045112972384,-0.4738056959762406,0.2360857122049479
+2017.0,2018.0,2311.5515,north_asia,-2.229459832807573,0.5802175682894745,-0.9673884998110736,0.2369800852580313
+2018.0,2019.0,2301.1885,north_asia,-1.4296283286683342,0.5770101437116635,-0.6231258843095254,0.2382938770019798
+2019.0,2020.0,2290.8255,north_asia,-0.8149763258916679,0.551439985831076,-0.356827096488514,0.2288743209514384
+2020.0,2021.0,2280.4625,north_asia,-1.0545339240245566,0.6479196117270417,-0.4638125139790883,0.2687609048907057
+2021.0,2022.0,2270.0995,north_asia,-1.2541491015757211,0.6493331246844912,-0.5541267553189984,0.2689804421564722
+2022.0,2023.0,2259.7365,north_asia,-2.084194149188092,1.143432150387618,-0.9250926140395432,0.4739003462856356
+2023.0,2024.0,2249.3735,north_asia,-2.383431710308152,1.1452951255418866,-1.0627863806836724,0.4740687462418848

glacier_data/11_central_europe.csv

+start_dates,end_dates,glacier_area,region,combined_gt,combined_gt_errors,combined_mwe,combined_mwe_errors
+2000.0,2001.0,2140.639,central_europe,-0.5934003711822097,0.6009122609745883,-0.2780412432778796,0.2877558756683069
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glacier_data/12_caucasus_middle_east.csv

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glacier_data/13_central_asia.csv

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glacier_data/14_south_asia_west.csv

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glacier_data/15_south_asia_east.csv

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glacier_data/16_low_latitudes.csv

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