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Item Water Level Monitoring and Mapping Seasonal Changes in the Reservoir Body Using Altimetry Data: A Case Study of Shivsagar/Koyna Reservoir(Springer Science and Business Media Deutschland GmbH, 2025) Nalluri, A.; Ramesh, H.Water is essential to human existence, and current research emphasizes the need to monitor freshwater bodies. A considerable segment of India is presently struggling with a condition of water stress. Monitoring of rivers, reservoirs and lakes is always a booming question in a field of research where it comes to a question of minimal cost and time. Gauging stations are disappearing because of the high maintenance cost of Indian Reservoirs. The use of satellite data can help to aid in minimizing all these parameters with effective results. Monitoring of smaller reservoirs is highly unlikely to occur. Satellite altimetry has been successful in monitoring inland water bodies for the past three decades. The current study emphasizes using SARAL/Altika, one of India’s high-frequency satellites in the field of altimetry, to monitor water levels (WL) of Koyna Reservoir, which is located over the Koyna River in the state of Maharashtra, India. The seasonal water spread of the reservoir is mapped with the use of Landsat-8 imaging satellite, 30 m resolution, which has a particular band to monitor water. BRAT (Broad view radar altimetry toolbox) is used for processing SARAL. Bias correction is observed while calculating water level from altimetry which is mainly caused due to geography of the reservoir. The normalized differential water index (NDWI) is employed to derive the water spread area of the reservoir. A capacity survey of the reservoir is quantified, and a loss of reservoir storage over the years is calculated using a mathematical approach. SARAL/Altika and Landsat-8 data’s which are freely available and downloaded and processed from April 2013 to May 2016. SARAL/Altika derived WL has validated against the field WL. The coefficient of determination, R2 is 0.9 for all the years, and the root-mean-square error (RMSE) is found to be less than 0.3. Additionally, altimetry studies can be employed for deriving bathymetry information, monitoring river systems, reservoir operations and various other applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.