Using Satellite Observations to Support Water Management in South India
Bibliographic record
Abstract
Small reservoir tank structures across South India form part of a complex ancient traditional water distribution system that has historically supplied irrigation to cropped fields during the dry-season. Despite their historical significance and the critical need for water storage in an agrarian dominated country with unpredictable rainfall, thousands of tanks have fallen into a state of disrepair. Our current understanding of these systems lacks knowledge about the functional state of these water systems. To understand tank functionality, spatially explicit and temporally dynamic frequent high-resolution surface water (SW) estimates developed in a synoptic and detailed way are needed. Building from an existing surface water monitoring approach (Vanthof and Kelly, 2019), we assess basin-scale dynamics of tank water storage state by segmenting water in multi-date and multi-sensor satellite images (Landsat-8, Sentinel-1, Sentinel-2, PlanetScope) for several years. These SW observations are converted to volumes using empirical rating curves developed for the region from Vanthof and Kelly (2019). Annually tanks were categorized by ‘tanks with water’ or ‘tanks without water’. For the ‘tanks with water’ category, an analysis was performed annually to identify spatial and temporal patterns in two indicators: temporal period of water storage and the rate of storage loss. Results show that hundreds of tanks are not able to store water despite precipitation inputs to the system. For tanks with water, further analysis reveals great variability among tanks for both indicators. As shown, this decade of Earth observation offers exciting opportunities to apply data-driven approaches to complement more traditional physically-based hydrological understanding and the ability to elucidate the role of reservoir filling strategies. Vanthof, V., & Kelly, R. (2019). Water storage estimation in ungauged small reservoirs with the TanDEM-X DEM and multi-source satellite observations. Remote Sens. of Environ., 235, 111437.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".