The evolution of an extreme positive Indian Ocean Dipole (pIOD) that took place in the tropical Indian Ocean during the late boreal summer to early winter of 2019 is examined in terms of coupled ocean–atmosphere dynamics. The patterns of anomalous sea-surface temperature (SST) revealed a typical pIOD characteristic: cooling (warming) in the southeastern (western) tropical Indian Ocean. Based on the Dipole Mode Index (DMI), the evolution of the event started in mid-July and gradually strengthened with an abrupt weakening in early September before coming to its peak in late October/early November. It quickly weakened in November, and then it terminated in mid-December. During the peak phase of the event, the SST anomaly in the southeastern (western) tropical Indian Ocean reached about −2 °C (+1 °C). The pattern of anomalous SST was followed by an anomalous pattern in precipitation, in which deficit precipitation was observed over the eastern Indian Ocean, particularly over the Indonesia region. Earlier study has shown that dry conditions associated with the pIOD event created a favorable condition for a forest-peat fire in southern Sumatra. The number of fire hotspots has increased significantly during the peak phase of the 2019 pIOD event. In addition, anomalously strong upwelling forced by strong southeasterly wind anomalies along the southern coast of Java and Sumatra had induced a surface chlorophyll-a (Chl-a) bloom in this region. High surface Chl-a concentration was collocated with the negative SST anomalies observed off the southwest Sumatra coast and south Java.

Forest fire, classified as a natural hazard or human-induced hazard, has negative impacts on humans. These negative impacts are including economic loss, health problems, transportation disruption and land degradation or even biodiversity loss. During 2015, forest fire had occurred at the Merang-Kepahyang peat forest that has a total area of about 69.837,00 ha. In order to set a rehabilitation plan for recovering the impact of forest fire, information on the total burnscar area and severity level is required. In this study, the total burnscar area and severity level is evaluated using a calculation on the Normalized Burning Ratio (NBR) Index. The calculation is based on the Near Infra Red (NIR) and Short Wave Infra Red (SWIR) of the satellite imageries from LANDSAT. The images of pre-and post-fire are used to evaluate the severity level, which is defined as a difference in NBR Index of pre- and post-fire. It is found that about 42.906,00 ha of the total area of Merang-Kepahyang peat area have been fired in 2015. These burned area are classified into four categories, i.e., unburned, low, extreme and moderate extreme. By overlying the spatial map of burning level with other thematic maps, it is expected that strategy for rehabilitation plan can be well developed.

Peatlands play a critical role in global and regional climate regulation by functioning as long-term carbon sinks, regulating hydrology, and modulating land–atmosphere energy exchange. Intact peat ecosystems store large amounts of organic carbon and stabilize local climate through high water retention and evapotranspiration, whereas peatland degradation disrupts these functions and can transform peatlands into significant sources of greenhouse gas emissions and climate extremes such as drought and fire. Indonesia contains approximately 13.6–40.5 Gt of carbon, around 40% of which is stored on the island of Sumatra. However, tropical peatlands in this region are highly vulnerable to climate anomalies and land-use change. This study investigates the impacts of major climate anomalies—specifically El Niño and positive Indian Ocean Dipole (pIOD) events in 1997/1998, 2015/2016, and 2019—on peatland cover change across South Sumatra, Jambi, Riau, and the Riau Islands. Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager/Thermal Infrared Sensor imagery were analyzed using a Random Forest machine learning classification approach. Climate anomaly periods were identified using El Niño-Southern Oscillation (ENSO) and IOD indices from the National Oceanic and Atmospheric Administration. To enhance classification accuracy and detect vegetation and hydrological stress, spectral indices including the Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI) were integrated. The results show classification accuracies of 89–92%, with kappa values of 0.85–0.90. The 2015/2016 El Niño caused the most severe peatland degradation (>51%), followed by the 1997/1998 El Niño (23–38%), while impacts from the 2019 pIOD were comparatively limited. These findings emphasize the importance of peatlands in climate regulation and highlight the need for climate-informed monitoring and management strategies to mitigate peatland degradation and associated climate risks.

The Seasional Trends of Dissolved Oxygen and pH in Sugihan River, South Sumatra, Indonesia