Multi-temporal remote sensing data is instrumental in mapping and analyzing post-earthquake land cover changes (Aydöner and Maktav 2009; Balamurugan and Aravind 2015; Fichera et al. 2012; Gong et al. 2012; Iwasaki et al. 2020; Jelének et al. 2018). Multi-sensor satellite imageries such as Landsat and Sentinel-2 data, are commonly used to monitor land cover changes effectively. This study examined land cover changes in the river systems impacted by the 2015 Ranau earthquake using Landsat and Sentinel-2 data. We used OBIA to classify the land cover before and after the earthquake because of its superior performance over the conventional pixel-based classification approach. The Kappa accuracies were 0.90, 0.92, and 0.89 for the 2014, 2015, and 2020 land cover classifications, respectively. The accuracy levels were comparable to other object-based classification studies (Phua et al. 2021; Ye et al. 2018).
There were more than 120 aftershocks with a magnitude above two during the three months after the mainshock on June 5, 2015 (Tongkul 2016). The aftershocks are confined to a narrow zone, and the aftershocks' depth gradually increases up to 30 km in the northwest direction. These earthquake-induced shocks cause massive landslides, especially in hillsides, mountain areas, and riverbanks within a water catchment (Xue et al. 2013). Removal of natural vegetation cover during mass movement is one of the critical factors that could significantly impact the geomorphology and hydrological functioning of a water catchment. Direct runoff increases when impermeable surfaces replace vegetation. It also leads to increased soil erosion and sediment transport that accumulate at the base of steep hillslopes, thus increasing the likelihood of debris flow occurring in due time (Simon et al. 2015). Among the five rivers, it was reported that the earthquake most impacted the Penataran River. It was noted that several hundred hectares of vegetation disappeared along with soil and rocks due to the landslides (Tongkul 2016). Our land cover change analyses revealed that vegetation decreased in all rivers, except for the Wariu River, during the immediate impact period. The vegetation cover of the Penataran River decreased the most among the five rivers. Deforestation in the Penataran River was 1.76 and 2.35 times higher than in the Kilambun and Kadamaian rivers, respectively. Generally, earthquake-induced landslides trigger severe erosion in the hills and mountains, leading to soil degradation. Soil erosion and landslides are expected to increase in the following years after the earthquake due to the absence of vegetation that affords rainfall interception and soil-binding processes. This high erosion rate may accelerate topsoil loss and further prevent revegetation (Roslee et al. 2018), thus entering a positive feedback mechanism until equilibrium is achieved. However, increased vegetation cover was observed predominantly in Kadamaian and Panataran rivers in the five-year impact period. The vegetation cover increase in the Kadamaian River was 4.13 times that of the Penataran River.
Besides erosion, deposition is a critical factor affecting the accumulation of sediment layers in river channels over time. These disturbances have a clear correlation with debris flow in a water catchment. Debris flow occurs when soil and rock materials are loosened, and water is saturated. When this occurs in steep mountainous areas, gravity can mobilize soil and rocks rapidly downhill (Edgar et al. 2018). Deposition in river channels downstream occurs when streamflow slows down, causing sediment and debris to accumulate along the rivers as river bars (Roslee and Norhisham 2018). These sediments can vary in composition, ranging from fine-grained materials such as sand and silt to larger rocks and boulders (Roslee and Sharir 2019).
The object-based classifications captured the formation of river bars in the study area. Based on the land cover time series, single "forced bars" were the primary bar type observed in the study area. Point bars, which form inside a river bend, and central bars, which form in more comprehensive sections, are examples of forced bars. As a mixture of loose materials forms the river bars, the river channels in the study area have been experiencing changes over time. Through object-based image analysis, we found that the changes in river bars in the Kadamaian and Penataran rivers were the highest among the five rivers. The river bar areas increased on both rivers in the one-year change period. The river bar increased more than 2.5 times to 92.79 ha in 2015 for the Kadamaian River. The Penataran River had no river bar before the earthquake, but new river bar areas of 54.36 ha were formed a year later. The river bar area in the Kadamaian River further increased to 112.23 ha in 2020. In contrast, the Penataran River experienced a decrease in river bar area to 33.3 ha in the five-year change period.
Although the Penataran River is five times smaller than that of the Kadamaian River, the river bar cover rate of the Penataran River after the earthquake is higher than that of the Kadamaian River. The river bar cover in the Panataran River was 20.59%, compared to only 6.83% for the Kadamaian River in 2015. In 2020, the river bar cover was 12.61% and 8.28% for Penataran and Kadamaian rivers, respectively. Considering that the Penataran River is an order lower than the Kadamaian River, the governing influence of stream order associated with a steeper gradient and smaller catchment size could have overridden other factors such as land cover, soil, and lithology (Clarke and Walsh 2006; Grieve et al. 2018; Shaw and Cooper 2008). It is only natural to expect that sediments in the Penataran river (upstream) are eventually transported to Kadamaian river (downstream) considering that the upstream reaches have steeper gradients which facilitates debris movement by the effect of gravity (Nainar et al., 2018; Pike and Scatena, 2010).
Further analysis by breaking up the Kadamaian River into two sections: Kadamaian Upper (before the Penataran confluence) and Kadamaian Lower (after the Penataran confluence) revealed that the loss in river bar areas in the Penataran and Kadamaian Upper rivers corresponds to a gain in the Kadamaian Lower River. This may reflect the dynamic nature of these river systems and imply that bedload mobilization was still active up to five years post-earthquake (2015–2020). Besides material mobilization within the channel, it is also possible that other deposition mechanisms, namely material mobilization from the catchment side slope to the river channel, may have contributed to the changes in the river bars (Chappell et al. 2004). This can only be ascertained with further geochemical or geophysical investigation in the future (Sugumaran et al. 2023). At present, our aim is not to balance the sediment budget but to demonstrate the extent of bedload mobilization following an earthquake.
Based on the land cover changes in the immediate and five-year impact periods, it is evident that the earthquake most impacted the Penataran River and Kadamaian River. The formation of river bars was one of the most important causes of river channel changes in the study area. Thus, detailed land cover transitions to and from river bars in the two most affected rivers were analyzed based on the land cover time series. The earthquake caused a significant increase in river bars in the Kadamaian River. Of the 78.39 ha of new river bars in 2015, 34.67% were river water areas before the earthquake. For the Panataran River, almost 20% of the newly deposited river bars (54.36 ha) were river water areas before the earthquake. The transition from river water to river bar continued to occur during the five-year change period. The new river bar areas that originated from river water areas between 2015 and 2020 were 71.12% and 81.36% for the Kadamaian River and Panataran River, respectively. These findings indicate the reduction of river channel area, thus altering water flow patterns in the earthquake-affected rivers. The sediment accumulation in river bars also leads to raised riverbeds. This eventually causes a reduction in channel capacity and an alteration in water flow patterns, increasing the risk of flooding, especially during heavy rainfall (Bohorques and Moral-Erencia 2017; Mahmood et al. 2002).