The Mahir Tech
GIS Water Resources & Hydrology Production Deployed

River Flow Prediction from Historical Data on Google Earth Engine

A Google Earth Engine model that predicts river flow from historical climate and catchment data, for a basin with thin gauge coverage.

CLIENT SECTOR

Water Resources Stakeholder

DELIVERY ARCHITECT

M. A Zia

DELIVERY STATUS

100% Complete & Active

IP & CODE OWNERSHIP

Full Client Handover

THE OPERATIONAL BOTTLENECK & CHALLENGE

The client needed to anticipate river flow for planning, but the basin had sparse and inconsistent gauge records. Decisions about water availability were being made on short, patchy history, and there was no practical way to install and wait on new instrumentation.

THE CUSTOM ARCHITECTURE & SOLUTION

We rebuilt the picture from satellite and reanalysis archives on Google Earth Engine. The catchment was delineated from elevation data, then decades of precipitation, temperature and snow-cover records were extracted over it and aligned with the gauge discharge that did exist. A regression model trained on that relationship produces flow predictions, and because the whole thing runs on Earth Engine, it re-runs against fresh data without any local processing burden.

Quantifiable Business Outcomes

Measurable Results & Return on Investment

Flow prediction made possible despite sparse gauge records
Decades of climate and catchment history brought into the model
Runs entirely on Earth Engine, no local processing infrastructure needed
Re-runnable as new seasons of data become available
Technology Stack Applied
Google Earth Engine JavaScript API CHIRPS MODIS Python Regression Modelling
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