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Flood in Myanmar: Patterns and Insights
Flood in Myanmar: Patterns and Insights
Frequent and Intense Flooding: Myanmar deals with heavy and frequent floods, especially during the monsoon season from May to October.
River Systems at Play: The country has many large rivers, which make flooding more likely when the rains come pouring down.
Major Flood Events: One of the worst floods occurred in 2015, displacing thousands of people and causing massive destruction to crops, homes, and infrastructure.
Areas Most Affected: Regions like the Ayeyarwady Delta and cities such as Bago often bear the brunt of these floods.
Impact of Climate Change: In recent years, climate change has led to heavier rainfall, making floods even more common and difficult for local communities to manage.
Data Source
Data Source
The information on this page is sourced from:
Emergency Events Database (EM-DAT): Comprehensive data on flood events and impacts, available at www.emdat.be.
Explore Our Visualizations
Explore Our Visualizations
Discover our interactive dashboards designed to help you analyze floods in Myanmar. These tools allow you to explore data on flood occurrences, affected populations, disaster origins, and the most impacted regions over recent years.
Dashboard Features
Key Metrics:
Total Affected Population: Displays the number of people affected by floods.
Total Deaths: Highlights fatalities resulting from flood events.
Interactive Exploration:
Clickable Visualizations: Click on elements to drill down into specific data, such as region-specific impacts.
Dynamic Filters: Customize your view by selecting timeframes, flood types, and affected areas.
Year Selection: Easily change the year to view data from specific years and observe trends over time.
Geographical Mapping: Visualize the spread and intensity of floods across Myanmar.
Trends and Comparisons: Analyze trends in flood occurrences and impacts through line charts and bar graphs.
Our Tableau dashboards are user-friendly, empowering you to gain insights into the flood challenges in Myanmar effectively.
Visualization Dashboard: Explore detailed flood patterns across Myanmar, using filters to view specific events, timeframes, or impacts.
Association Rules Analysis
Association Rules Analysis
You can sort the rules by decreasing support or confidence.
Support means the proportion of transactions in the dataset that contain a specific rule. It indicates how frequently the rule applies in the dataset. A higher support value suggests that the rule is more relevant.
Confidence means the reliability of the inference made by the rule. It indicates the likelihood of the consequent occurring given that the antecedent is present. A higher confidence value signifies that the rule has a strong predictive power.
For example, the following rule can be interpreted as:
Rule: Origin=Seasonal rain, Disaster Subtype=Riverine flood → Total Affected=Severe impact
Interpretation: This rule suggests that when there is seasonal rain and the disaster subtype is classified as a riverine flood, there is a high likelihood that the total affected population will be categorized as having a severe impact. The support and confidence values associated with this rule would quantify how often this scenario occurs in the dataset and how reliable this prediction is based on historical data.
Association Rule Dashboard: Discover deeper patterns and relationships within the data, such as how flood origins link to severity, flood types, and affected regions.
Get Involved
Get Involved
Invite users to interact with both dashboards, explore different patterns, and gain a better understanding of Myanmar’s flood risks and potential areas of impact.
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