A 1985–2023 time series dataset of absolute reservoir storage in Mainland Southeast Asia (MSEA-Res)

Abstract. The recent surge in reservoir construction has increased global surface water storage, with Mainland Southeast Asia (MSEA) being a significant hotspot. Such infrastructural evolution demands updates in water management strategies and hydrological models. However, information on actual reservoir storage is hard to acquire, especially for transboundary river basins. To date, no high spatio-temporal dataset on absolute storage time series is available for reservoirs in MSEA. To address this gap, we present (1) a comprehensive, open-access database of absolute storage time series (sub-monthly) for 185 reservoirs (larger than 0.1 km³) in MSEA spanning the period 1985–2023, and (2) an analysis of the reservoir storage dynamics. The MSEA-Res database includes static (Area-Elevation-Storage curves, water frequency, reservoir extent) and dynamic (area, water level, and absolute storage time series) components for each reservoir. The 185 reservoirs collectively store around 175 km³ (140 km³ – 210 km³) of water, covering an aggregated area of 8,700 km² (6,500 km² – 10,000 km²). We show that the combined average reservoir storage has increased from 70 km³ to 160 km³ (+130 %) from 2008 to 2017, primarily contributed by dams in the Irrawaddy, Red, Upper Mekong, and Lower Mekong basins. Our in-situ validation provides a good match between estimated storage and in-situ observations, with 60 % of the validation sites (12 out of 20) showing an R² > 0.65 and an average nRMSE < 15 %. The indirect validation (based on altimetry-converted storage) shows even better results, with an R² > 0.7 and an average nRMSE < 12 % for 70 % (14 out of 20) of the reservoirs. Furthermore, the analysis of the 2019–2020 drought event reveals that nearly 30–40 % of the MSEA region experienced more than five months of drought, with the most significant impact on reservoirs in Cambodia and Thailand. As a result, storage departures ranged up to -40 % in some reservoirs, highlighting significant impacts on water availability. Overall, this analysis demonstrates the potential of the inferred storage time series for assessing real-life water-related problems in Mainland Southeast Asia, with the possibility of applications in other parts of the world. The MSEA-Res database and associated Python code are publicly available on Zenodo at https://doi.org/10.5281/zenodo.12787699 (Mahto et al., 2024).