How Well Can the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Irrigation Canals?

Abstract The capability of the Surface Water and Ocean Topography (SWOT) satellite for observing irrigation canals has remained relatively unexplored. Here, we assess SWOT observability of irrigation canal networks across 22 Asian countries using a new confidence level (CL) metric. Validation against in situ gauge observations showed that higher CL corresponds to significantly lower water‐level retrieval error. Of approximately 795,110 km of canals analyzed, 37.5% (297,799 km) show high confidence, 46.9% (373,035 km) moderate confidence, and 15.6% (124,276 km) low confidence of observability. Observability is highest in the Indus Basin, Indo‐Gangetic Plain, Bangladesh delta, North China Plain, and parts of Myanmar, the Philippines, Nepal, and the Mekong delta, and lowest across parts of Central Asia. Our analysis indicates SWOT can meaningfully support irrigation canal water monitoring across much of Asia's most intensively irrigated regions and around the world.

Authors

Institutions

Publication Details

Journal
Geophysical Research Letters
Published
2026-09-30
DOI
https://doi.org/10.1029/2026gl124090
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

How Well Can the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Irrigation Canals?

Sanchit Minocha, Tamlin M. Pavelsky, Shahzaib Khan, Sarath Suresh et al.
Geophysical Research Letters
Flood Risk Assessment and Management
article

How Well Can the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Irrigation Canals?

Sanchit Minocha, Tamlin M. Pavelsky, Shahzaib Khan, Sarath Suresh, Faisal Hossain, Mridul Sharma
article en

Abstract

Abstract The capability of the Surface Water and Ocean Topography (SWOT) satellite for observing irrigation canals has remained relatively unexplored. Here, we assess SWOT observability of irrigation canal networks across 22 Asian countries using a new confidence level (CL) metric. Validation against in situ gauge observations showed that higher CL corresponds to significantly lower water‐level retrieval error. Of approximately 795,110 km of canals analyzed, 37.5% (297,799 km) show high confidence, 46.9% (373,035 km) moderate confidence, and 15.6% (124,276 km) low confidence of observability. Observability is highest in the Indus Basin, Indo‐Gangetic Plain, Bangladesh delta, North China Plain, and parts of Myanmar, the Philippines, Nepal, and the Mekong delta, and lowest across parts of Central Asia. Our analysis indicates SWOT can meaningfully support irrigation canal water monitoring across much of Asia's most intensively irrigated regions and around the world.

Geophysical Research LettersVol. 53(19)
University of North Carolina at Chapel Hill (US), University of Washington (US)
Life below water
Openalex Percentile: Top 15%
Flood Risk Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.