Precision Hydrology: The Science Behind the Data
Our methodology bridges satellite observation with ground-level validation to model the Ganga basin with unprecedented accuracy. We don't just collect data; we interrogate the river system.
The GangaAnalytics Stack
From satellite capture to actionable policy briefs, our pipeline is engineered for scientific rigor. We visualize the flow of data across our infrastructure.
Satellite Data
Optical & SAR
Ingestion
Atmospheric Correction
Processing
ML Algorithms
Validation
Ground Truthing
Insight
Policy Briefs
Core Methodologies
Our analysis rests on three distinct, interoperable pillars.
1. Multispectral Remote Sensing
We process Sentinel-2 and Landsat imagery to track water turbidity, surface temperature, and vegetation health across the basin. This macro-view allows us to identify pollution plumes and sediment shifts at a resolution of 10 meters per pixel.
- NDVI & NDWI indexing
- Thermal anomaly detection
- 8-year historical archive
2. Ground Validation Network
Satellite data is calibrated against physical sensor arrays deployed at key river stations. We maintain a network of automated loggers measuring pH, dissolved oxygen, and flow velocity, providing the "ground truth" that refines our models.
Real-time Stream Data
3. Predictive River Dynamics
Fusing satellite and ground data, we simulate hydrological scenarios. This allows us to forecast flood risks, drought impacts, and pollutant dispersion pathways under variable climate conditions, giving stakeholders a window into the future.
"The Varanasi model accurately predicted the 2024 pre-monsoon sediment peak within 4% variance."
Regional Calibration: The Varanasi Hydrological Model
Generic global models fail in the intricate topography of the Upper Ganga. Our proprietary calibration adjusts for local sediment load, monsoon intensity variances, and the unique interaction between tributaries and the main channel near Varanasi.
Local Terrain Mapping
High-resolution DEMs of riverbanks.
Monsoon Correlation
Adjusting for 50-year rain patterns.
Data Integrity & Validation Protocols
Trust in data begins with transparency in validation. We employ a rigorous three-stage verification process to ensure that every data point is defensible and reproducible.
Automated Outlier Detection
Algorithmic flagging of sensor drift and atmospheric noise.
Cross-Source Verification
Comparing satellite returns against physical lab samples.
Peer Review Integration
Methodology available for academic scrutiny and citation.
Open Source Technology
We build on the shoulders of giants. Our stack leverages open-source scientific computing libraries to ensure reproducibility and lower barriers to entry for local agencies.
Python
Data Science
QGIS
Geospatial
TensorFlow
Prediction
Docker
Deployment
Partner with Us
Whether you require a custom basin analysis, ground validation support, or access to our historical archive, our Varanasi-based team is ready to assist.