Job Detail
Completed
Done!
Location Info
Location Name
Sriwulan
Coordinates
-6.943039, 110.493386
Description
Pondok Raden Patah 2, Sriwulan, Demak, Jawa Tengah, Jawa, 50117, Indonesia
Analysis Period
Start Date
01 January 2021
End Date
31 December 2021
Duration
365 days
📊 ANALYSIS SUMMARY
Structured SummaryJob Info
Data Statistics
Rainfall
Retention Pond Volume
System Reliability
Analysis Results
Output Components
Input Components
River Morphology
Soil Storage Condition
Water Balance
Data Quality
Available Files:
Management Recommendations (1)
Build flood early warning system and increase drainage capacity in high-risk zones.
WATER DISTRIBUTION & PRIORITY
WATER SOURCES
COST & BENEFIT
WATER QUALITY
RIVER & ENVIRONMENT CONDITION
📊 SYSTEM CONDITIONS SUMMARY
🌊 Flood Risk & Water Ponding Analysis
What is TWI? Topographic Wetness Index (TWI) is an index that measures how easily water accumulates in a location based on topography/terrain. The higher the TWI value, the greater the likelihood that the area will be flooded or waterlogged during rain.
Your Location Risk Status
🚨 Detected Flood Prone Areas
Our Machine Learning system found 3 zones zones potentially prone to flooding during heavy rain.
📍 Flood Zone Location Details
🌳 Green Open Space (RTH) Recommendations
To reduce flood risk, the Machine Learning system recommends creating 0 Recommended Locations such as parks, urban forests, or water absorption areas.
🚰 Drainage System Recommendations
To control water flow and prevent ponding, the system recommends building 4 drainage channels at strategic locations.
📍 Drainage Location Details
🔧 Technical Specifications
✨ Expected Benefits
🔧 Maintenance Requirements
- High TWI (24.9) indicates severe water accumulation
- Multiple flood zones (3) require comprehensive drainage
- Flat terrain (1.4°) requires artificial drainage
- Strategic placement for optimal flood mitigation
🔧 Technical Specifications
✨ Expected Benefits
🔧 Maintenance Requirements
- High TWI (24.9) indicates severe water accumulation
- Multiple flood zones (3) require comprehensive drainage
- Flat terrain (1.4°) requires artificial drainage
- Strategic placement for optimal flood mitigation
🔧 Technical Specifications
✨ Expected Benefits
🔧 Maintenance Requirements
- High TWI (24.9) indicates severe water accumulation
- Multiple flood zones (3) require comprehensive drainage
- Flat terrain (1.4°) requires artificial drainage
- Strategic placement for optimal flood mitigation
🔧 Technical Specifications
✨ Expected Benefits
🔧 Maintenance Requirements
- High TWI (24.9) indicates severe water accumulation
- Multiple flood zones (3) require comprehensive drainage
- Flat terrain (1.4°) requires artificial drainage
- Strategic placement for optimal flood mitigation
⚡ Required Actions
Implement drainage systems and green spaces to reduce flood risk.
-
1.
Main Priority: Immediately review and give special attention to 3 detected high risk zones
-
2.
Drainage Construction: build 4 high priority drainage channels to channel rainwater
-
5.
Regular Monitoring: Conduct routine monitoring during rainy season for early anticipation
-
6.
Coordination: Involve Public Works Department and community in solution implementation
📅 30-Day Rainfall Forecast
Rainfall Forecast
Retention Pond
Reliability
High rainfall predicted. Watch for flood potential and ensure drainage system is functioning well.
📋 Management Suggestions
1. Retention pond volume is critical (<20%). Reduce water distribution immediately and activate backup sources.
2. System reliability is good (>85%). Maintain regular maintenance schedule.
🔧 Improvement Suggestions
Soil Conservation
Medium PriorityProblem: Low soil moisture (8.63 mm)
- Build infiltration wells
- Rainwater harvesting system
- Apply mulching to retain moisture
Retention Pond Capacity
High PriorityProblem: Retention pond volume is critical (5.68 mm)
- Evaluate storage capacity and expansion potential
- Optimize water distribution schedule
- Implement water demand management
- Identify alternative water sources
Flood Mitigation
High PriorityProblem: High flood risk (47.4%)
- Increase drainage system capacity
- Build flood detention ponds
- Optimize spillway operations
- Flood early warning system
🌊 Interactive River Network Map NEW
River network visualization with interactive layers
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Analysis Location
Sriwulan
Map Layers
4 Data Sources
Buffer Area
10 km radius
📊 Data Sources
- HydroSHEDS - Flow Accumulation
- JRC Global Surface Water
- SRTM DEM - Elevation
- OpenStreetMap - Basemap
🗺️ Map Features
- River network visualization
- Water occurrence overlay
- Topography (DEM)
- Interactive layer control
Tip: Use the layer control in the top-right corner of the map to toggle layers on/off. Zoom in for more detail. Click the marker for analysis location info.
Generated Files
Total 21 file
RIVANA_Peta_Aliran_Sungai.html
RIVANA Main Dashboard
Main dashboard showing hydrological analysis results using Machine Learning
RIVANA Complete Dashboard
Complete dashboard with predictions, risk analysis, and recommendations
RIVANA_TWI_Dashboard.png
Water Balance Dashboard
Water balance visualization: input vs output, hydrological components
Morphometry Summary
Watershed morphometric parameters: area, shape, slope, drainage
Morphology & Ecology Dashboard
River geomorphological condition and aquatic ecosystem health
ML vs Traditional Comparison
Accuracy comparison between Machine Learning model and traditional methods
Complete Simulation Results
Complete time series data: rainfall, temperature, ET, discharge, reservoir level, supply-demand
Monthly Water Balance
Monthly summary: precipitation, evapotranspiration, infiltration, runoff, storage
30-Day Forecast Data
30-day rainfall and reservoir level forecast from ML model
GEE_Raw_Data.csv
RIVANA_WaterBalance_Indices.csv
RIVANA_Hasil_Simulasi.csv
Complete Model Validation
Model validation metrics: NSE, R², PBIAS, RMSE for all parameters
RIVANA_Baseline_Comparison.json
RIVANA_TWI_Analysis.json
Water Balance Validation
Water balance validation with maximum 5% error tolerance
RIVANA_Model_Validation_Report.json
GEE_Data_Metadata.json
RIVANA_Metadata_Peta.json
Timeline
Created
10 Mar 2026, 15:44
Submitted
10 Mar 2026, 15:44
Processing Started
10 Mar 2026, 15:45
Finished
10 Mar 2026, 15:48