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GROUNDWATER POTENTIAL ASSESSMENT - Coggle Diagram
GROUNDWATER POTENTIAL ASSESSMENT
CONTROLLING FACTORS
Geology
Slope
Land use
Soil type
Drainage density
Lineament density
Altitude
Rainfall
GIS – Geographic Information Systems
Spatial analysis
Thematic layers
Data integration
Layer weighting
Groundwater potential maps
REMOTE SENSING
Satellite images
DEM
Landsat
Lineament extraction
Surface information
Difficult-to-access areas
MACHINE LEARNING
Random Forest (RF)
Logistic Regression (LR)
Boosted Regression Tree (BRT)
Support Vector Machine (SVM)
Hybrid/ensemble models
APPLICATIONS IN COLOMBIA
Well-site selection
Groundwater recharge assessment
Sustainable groundwater extraction
Groundwater quality protection
Aquifer management
Bogotá River Basin
Sabana de Bogotá
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ADVANTAGES
Faster spatial analysis
Integration of multiple data sources
Large-area assessment
Improved prediction
Supports well-site selection
Supports sustainable groundwater management
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LIMITATIONS
Results depend on input-data quality.
GIS does not generate hydrogeological data by itself.
Remote sensing mainly provides surface information.
Dense clouds and vegetation can limit satellite observations.
High-resolution satellite data can be expensive.
Machine Learning requires sufficient data for training and validation.
Field data are necessary for validation.