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High need for precision agriculture today has been associated with the completeness of the data available. The application of smart technology becomes the main alternative for fulfilling incomplete data and predicting future data. This paper presents the results of a research that aims to monitor and to predict water availability for determining conservation strategy on water availability using time series data from satellite rainfall, spanning from 2007 to 2022. We employed the innovative use of remote sensing technology, global rainfall measurement (GPM) and Climate Hazards Group InfraRed Rainfall with Station data (CHIRPS), to assess and correct satellite-derived rainfall estimates against ground-based observations. Conducted in the Serang watershed of Mount Merbabu’s volcanic landscape, the research employs a quantitative descriptive approach. We used coupled climate models MIROC6 and MRI-ESM2-0 in the CMIP-6 Framework for rainfall projections 2023–2030, then continued with the F.J. Mock model simulations for water availability projection. Our findings reveal a significant impact of climate change on water availability over the decade, with the most extreme conditions observed in 2029 and 2030, where the increasing of water availability reaching 10 m3 /s. The results showed that CHIRPS performed well in describing rainfall data. The novelty of this research highlighting the potential of: firstly, the use of satellite rainfall data for this specific region has not been extensively studied before; secondly, the discovered impacts of climate change to the water availability are particularly noteworthy, and thus contributing to the sustainability of agricultural practices in response to climate change. A limitation of this study is the short investigation period of just one decade, which does not fully capture the long-term impacts of climate change. Future research is recommended to utilize satellite data over extended periods to better represent extreme climate events and derive drought and wetness patterns over durations exceeding one decade. [ABSTRACT FROM AUTHOR]