Optimizing SAR Flood Extent Mapping in Central Chile: The Critical Role of Image Timing

Abstract. This study critically quantifies the temporal uncertainty inherent in flood extent estimation using Sentinel-1 SAR data in the high-relief, flash-flood-prone river systems of Central Chile, following the extreme events of 2023. We applied the iterative Jaccard optimization framework to five sites in the Maule and Mataquito watersheds, identifying the Difference Image Index (DII) as the most robust flood indicator. Our key finding is that the estimation of maximum flood extent is fundamentally limited by the timing of the SAR acquisition. River gauge analysis confirmed a flash-flood regime with an extremely rapid recession rate (river height dropping ∼ 50 % within four days of the peak). This rapid drainage means that a delay of 24–48 hours results in a severe underestimation of the true flood footprint. While the DII performed best, overall Jaccard scores remained low (≤ 0.6). We conclude that the method's accuracy is primarily constrained by physical limitations- namely, the rapid recession rate and complex topography- rather than the calibration technique itself. Relying solely on the Sentinel 1 revisit cycle is insufficient for operational mapping in such dynamic environments, and we recommend integrating SAR monitoring with hydraulic modeling or high-frequency aerial surveys to accurately interpolate the maximum flood extent.