The foundation of the KADA Groundwater Observatory relies on a robust multi-source data collection framework. We integrate real-time telemetry from piezometers, satellite-based remote sensing data, and historical records from state agencies.

• Real-time Telemetry: High-frequency water level monitoring from automated digital water level recorders (DWLRs).
• Remote Sensing: GRACE satellite data for large-scale storage anomalies and Sentinel-1 SAR for surface deformation correlations.
• Field Surveys: Periodic manual measurements to validate automated readings and check for sensor drift.

We utilize numeric groundwater flow models to simulate aquifer behavior under various stress scenarios. These models help in calculating the water budget, estimating recharge rates, and predicting future trends.

Surface and subsurface hydrology are analyzed to understand the interaction between rainfall, runoff, and groundwater recharge. We employ GIS-based spatial analysis to delineate watersheds and identify potential recharge zones.

Key analytical outputs include:

• Runoff Coefficient Mapping: Based on land use/land cover (LULC) and soil characteristics.
• Drainage Density Analysis: To assess the surface permeability and potential for infiltration.

Rigorous QA/QC protocols are applied to all incoming data. Outlier detection algorithms identify potential sensor errors, which are then flagged for manual review. Cross-validation with nearby stations ensures spatial consistency.