Hazards product
SAROVARAसरोवरLive data

Know which glacial lakes above India's valleys are growing, and when to look closer.

Sarovara watches 38 glacial lakes in Sikkim, Arunachal Pradesh, Uttarakhand, Himachal Pradesh, Ladakh, Nepal and Tibet. It measures each lake's water in recent Sentinel-2 images against published inventories, checks earthquakes, heavy rain and warm spells at the lake, and lists the towns downstream with approximate flood-wave times. It is advisory and says so on every page.

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Problem

On the night of 3 to 4 October 2023, about 14.7 million m³ of frozen moraine collapsed into South Lhonak lake in North Sikkim. Roughly 50 million m³ of water left the lake, and the flood did damage along 385 km of the Teesta (Eos; Sattar et al., Science, 2025). The front reached Chungthang, 62 km downstream, about 2 hours 17 minutes after the collapse.

In 2026, a suspected outburst from a lake in Tibet sent a flood down Nepal's Bhote Koshi and Trishuli on 26 August, and a flash flood without heavy rain hit the Budhi Gandaki on 11 October; both rivers reach Bihar as the Gandak. Sikkim now lists 40 high-hazard glacial lakes, 16 of them at the highest risk (PTI, 4 Sep 2026). Many of these lakes sit above 4,500 m, freeze for half the year, and are seen mainly from orbit.

What it does
  • Measures open water at each lake in the latest clear Sentinel-2 scene, with a stated uncertainty, and shows the image with the detected shoreline.
  • Judges growth from the cleanest evidence: the same season in 2019 to 2021 measured the same way, then the inventory trend, and flags any scene a person should look at instead of hiding it.
  • Checks three triggers at every lake: earthquakes of magnitude 4 and above within 100 km in 30 days, heavy rain against IMD's categories, and warm spells that melt snow and ice.
  • Combines them with each lake's documented hazard into a watch level (normal, watch or warning), labelled as a heuristic, and orders the board by a monitoring priority.
  • For 20 lakes, lists towns downstream with river distance and an approximate flood-wave time, calibrated on the 2023 Teesta flood.
Imja Tsho, Solukhumbu, Nepal, from Copernicus Sentinel-2 L2A via Microsoft Planetary Computer.
How it works

A Python pipeline reads two glacial lake inventories from Zenodo and keeps the watchlist lakes. For each lake it asks the Planetary Computer for recent Sentinel-2 scenes, reads a pixel window around the lake, and finds water with the normalised difference water index (green against near-infrared) at a threshold chosen for that scene. Scenes with cloud, missing data or ice over the lake are rejected; doubtful ones are flagged. USGS earthquakes and Open-Meteo forecasts at the lake's elevation give the triggers. Everything is written as small JSON files with the time each source was read, and the console reads only those files.

Sarovara data flow Glacial lake inventories give the outlines and area history. Sentinel-2 scenes give the current water area and same-season comparison. USGS earthquakes and Open-Meteo weather give triggers. Growth, hazard tier and triggers combine into the watch level and priority, shown with downstream towns on the board and lake pages. Lake inventoriesGLO and HMA, Zenodo Sentinel-2 L2APlanetary Computer USGS, Open-Meteoquakes, rain, warmth Area recordtrend since 2016 Water nowNDWI, flags, images Triggersheuristic scores Watch levelgrowth, tier, triggers Board and lake pagessource and time on each Downstream townscurated, approximate
Full method, formulas, thresholds and limits: methods (console sign-in) or the methods note.
Data
SourceWhatLicenceStatus
Glacial Lake Observatory inventoryAnnual lake outlines for Nepal and transboundary catchments, 2017 to 2024, with area uncertaintyCC BY 4.0Versioned release
High Mountain Asia lake inventoryLake outlines for 2016-17 and 2022-24 (median composites)CC BY 4.0Versioned release
Sentinel-2 L2A via Planetary ComputerScenes from the last 90 days and the same season in 2019 to 2021, pixel windows at 10 mCopernicus data, free and openLive
USGS earthquake catalogueMagnitude 4 and above in the region, last 30 daysPublic domainLive
Open-Meteo forecastHourly temperature, precipitation and freezing level at each lake's elevationCC BY 4.0Live
OpenStreetMapLake names and the positions of downstream townsODbL 1.0Curated by hand
ICIMOD (2020), Sikkim (2026), published studies and reportsDocumented hazards and recorded outbursts, each linked where it is usedCitedCurated by hand

For

State disaster management authorities and district administrations decide which lakes need a field visit, a sensor or a drill, and when. CWC and IMD liaison officers get an independent second look at lakes between their own surveys. Programme teams for glacial lake risk reduction track which lakes are changing. Valley communities and their volunteers learn how much time the towns below a lake might have.

Safeguards
  • Advisory only, on every page: Sarovara flags conditions; warnings come from CWC, NDMA, IMD, the state and district authorities, and in Nepal from DHM and NDRRMA.
  • Every number carries its source and the time it was read. Doubtful measurements are shown with a flag, never hidden or silently corrected.
  • Lakes in the Tibet Autonomous Region are shown only as natural hazards to the valleys below, in neutral language.
  • Downstream lists name towns and villages only. Sarovara does not list dams, bridges or other infrastructure, or their vulnerabilities.
  • No data about people: lakes, weather, earthquakes and places only.
Limits
  • Sarovara does not detect or forecast outbursts. Collapses, ice avalanches and slow moraine failure leave little in earthquake or weather feeds, so a lake can be at normal on the day it fails.
  • From October many lakes freeze, and monsoon cloud hides them in summer; the latest area can be up to 90 days old or fall back to the inventory.
  • Thin grey ice and very turbid water can be missed as water; large cases are flagged for review.
  • Model weather over steep terrain carries large errors; the rain thresholds are IMD station categories applied to model values.
  • Flood-wave times come from two wave speeds and straight-line distances, not a hydraulic model. Use them for awareness and drills, never for evacuation timing.
Call

Pilot: one state's glacial lakes through a melt season, weekly runs, with your field team's observations fed back to tune the flags and thresholds. contact@trinetra.in