University of Birjand Water Harvesting Research 2476-6976 9 1 2026 03 01 Water Extent Monitoring Using Sentinel-2 (Case Study: Latyan Dam Reservoir) 28 39 3921 10.22077/jwhr.2026.10498.1191 EN Amirhossein Maeli Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran. Amirali Alavi Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran. 0009-0007-1300-806X Ehsan Vasheghani Farahani Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran. 0000-0002-0228-8314 Mahmoud Mashal Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran. Armin Nasrollahi Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran. Journal Article 2025 11 16 Monitoring the surface area of reservoirs is crucial for effective water resource management, particularly in arid and semi-arid regions where water availability fluctuates significantly. This study utilizes Sentinel-2 imagery to assess water extent variations in the Latyan Dam reservoir in Iran from 2016 to 2024. By applying three well-established water indices—NDWI, MNDWI, & AWEIsh—water surface areas were delineated. Sentinel-2 Level-2A images, preprocessed using the Sen2Cor algorithm, were analyzed in SNAP software, ensuring high accuracy in atmospheric correction and reflectance values. The derived water area was validated using index intersection and union approaches to refine detection accuracy. The reservoir’s surface area showed a clear declining trend, decreasing from 3.3 km² in 2016 (wettest year) to 1.1 km² in 2023 (driest year), corresponding to a shrinkage of about 2.2 km². Throughout 2016–2024, the uncertainty band between the union and intersection of NDWI, MNDWI, and AWEIsh remained relatively narrow, fluctuating between approximately 0.2 and 0.4 km², with slightly lower values in drier years. Applying Otsu thresholding substantially increased the number of uncertain water pixels compared to the fixed global threshold (index ≥ 0), from 3446 to 8250 pixels in 2016 and from 1718 to 7191 pixels in 2023, indicating that the global threshold provides more stable and conservative water detection for long‑term monitoring. This approach provides an efficient, replicable methodology for large-scale water monitoring, supporting sustainable water resource management and policy decisions. https://jwhr.birjand.ac.ir/article_3921_66cc7c95a0f92f31d3c78d94b8bf28c7.pdf