Peatland fires in Southeast Asia are strongly influenced by hydrological conditions, yet most studies rely on low-temporal-resolution data, limiting the capture of rapid hydrological dynamics. This study analyzes high-frequency hydrological dynamics in relation to fire occurrence in protected peatlands of Central Sumatra. Real-time monitoring using 12 IoT sensors recorded groundwater level (GWL), soil moisture (SM), and soil temperature (ST). Results show substantial spatial variation, with GWL (−144.30 to 9.00 cm), SM (14.52% to 94.82%), and ST (23.01 to 33.93 °C). Linear mixed-effects models (LMMs) and first-order autoregressive (AR (1)) temporal correlation showed significant associations of GWL with SM (β = 0.460, p < 0.001) and ST (β = −0.516, p < 0.001). GWL decreased by 13.73 cm (−0.54 cm day−1) during the pre-fire period and by a further 6.34 cm (−0.47 cm day−1) during the fire period (27 August 2024–9 September 2024), when the descriptive mean GWL reached −89.43 cm. Post-fire, GWL increased by 41.99 cm (0.82 cm day−1), while SM increased and ST decreased, coinciding with reduced hotspot activity. The fire period was identified using SIPONGI hotspots and SIPP fire records and suppression. These findings show temporal associations between hydrological dynamics and fire occurrence, supporting high-frequency IoT monitoring of peatland hydrology.
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Wulandari et al. (2026) studied this question.
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