Jakarta is considered to be one of the most vulnerable cities in the world to climate-related disasters, such as flooding, sea-level rise, and storm surge (Firman et al. 2011). Jakarta has experienced several flood disasters in the past, including in 1996, 2002, 2007, 2013, and 2020. These floods not only led to severe economic damages but also human casualties.
Several studies related to flood problems in Jakarta have been conducted. Moe et al. (2016) applied a rainfall-runoff and flood inundation model to the 2013 flood event and concluded that a shortage of capacity in the lower Ciliwung and other rivers accounted for 79.6% of the total flood inundation volume in Jakarta, with urbanization and land subsidence contributing to 20.4%. According to Bricker et al. (2014), the reduced capacity of the drainage system generated by trash-clogging flood gates is a factor that causes flooding. Budiyono et al. (2016) and Januriyadi et al. (2018) reported that climate change in the future would increase flood risk in Jakarta.
In these flood-prone situations, several countermeasures have been implemented in Jakarta to mitigate flood damages, such as dredging and diversion tunnels. However, flood risk in Jakarta is still high, and more than 60 people were killed in Jakarta during the most recent flood event that occurred in January 2020. A flood-forecasting system is required in Jakarta to ensure early evacuation and prevent traffic jam during flood disasters. Nevertheless, the development of a flood-forecasting system in Jakarta is a challenging task because of the rapid flooding of rivers and canals and the shortage of rainfall data attributed to uncertainty in predicting rainfall.
In this study, we analyzed whether satellite rainfall data can be used as an input for real-time flood forecasting in Jakarta because of the discontinuation of rainfall radars in 2013 owing to high maintenance costs. Various satellite rainfall products can be accessed and downloaded freely, and the data are provided in near real-time worldwide. We used global satellite mapping of precipitation (GSMaP) products as the satellite rainfall data in this study. GSMaP products have been evaluated and verified through comparison with observation data in several previous studies.
Based on a verification study of hourly GSMaP rainfall conducted by Setiawati and Miura (2016), GSMaP-MVK data can be used to replace rain gauge data, particularly for lowland areas in the Kyusyu region, Japan, if inconsistencies and errors are resolved. However, without bias correction, significant underestimation of the heavy rainfall events will be observed. Moreover, the current algorithm of the microwave radiometer of the GSMaP does not consider topographical effects (Setiawati and Miura 2016). Other researchers also reported underestimation via the GSMaP (Fu et al. 2011; Admojo et al. 2018; Pakoksung and Takagi 2016). Fu et al. (2011) evaluated the accuracy of the GSMaP using a gauge station in a basin in China and found that GSMaP products generally underestimated the precipitation amount. Additionally, GSMaP rainfall data are less accurate when used for mountainous regions than flat areas owing to the occurrence of topographical rainfall. Conversely, Tian et al. (2010) reported that satellite products (e.g., GSMaP) overestimate rainfall in the summer based on the estimations over the contiguous United States.
Hence, GSMaP rainfall products provide less accurate results compared to gauge-based rainfall networks or radar rainfall information systems. Nevertheless, GSMaP rainfall products are often used as an input for hydrological models in simulating flood events. Admojo et al. (2018) and Pakoksung and Takagi (2016) statistically evaluated satellite rainfall products, including the GSMaP, and applied hydrological simulations to a large river basin in Thailand using satellite data. They showed acceptable model results to simulate the observed discharge in a river basin. Additionally, the bias correction (Sayama et al. 2012) of satellite rainfall products and the ensemble flood simulation methods (Jiang et al. 2014) have been successfully used for flood simulations in large-scale basins. Sayama et al. (2012) applied a hydrological model with a bias-corrected GSMaP for flood inundation simulation in Pakistan to provide additional information for flood relief operations. The simulated flood inundation area reasonably matched well with the actual area even though the satellite rainfall products were used as the input for the simulation.
These literature reviews indicate that the accuracy of GSMaP data should be verified for several cities and regions before being used in practice. In several studies, hydrological models were applied with satellite rainfall data to large basins, where the flood travel time is relatively slow. However, GSMaP evaluation investigations of highly urbanized cities prone to rapid flooding in rivers and subjected to local convective rainfall owing to urban heat environment or humid tropical climate have not been conducted in detail.
The main objective of this study is to investigate a satellite-based rainfall product for the flood inundation modeling of a flood event in Jakarta, which is a mega Asian city located in a humid tropical region. Satellite-based rainfall can be used to reconstruct historical flood events. A problem faced by developing countries is the evaluation of historical flood events with insufficient survey and hydrological observation data. Thus, GSMaP data was also evaluated in this study as the input rainfall data to simulate the historical flood events in Jakarta, including the most recent large-flood event that occurred in January 2020.
Study Area
Jakarta is the capital of Indonesia and is located on the northwest coast of Java island. Jakarta is the largest metropolitan city in Indonesia, and its development is progressing rapidly.
The rainy season in Jakarta begins in November and ends in March, and the peak rainfall intensity often occurs in January and February. Thirteen main rivers flow through the region, with the Ciliwung River being the longest. The area selected for this study included Jakarta and the surrounding river basins, which cover a total of 1,346.6 km2 (Fig. 1). It should be emphasized that Jakarta is a highly urbanized area with complex urban systems of river channels and canals, buildings, and roads. Thus, the flood concentration time is relatively short (approximately 12–16 h), which creates problems regarding the use of warning systems, evacuation, and the prevention of traffic congestion.
Almost every year, Jakarta experiences flooding in January, February, or both owing to high rainfall with insufficient capacity flows in the drainage system. Details of the floods and damages are listed in Table 1. In Table 1 the damage cost and main damages were obtained from several sources such as web online news and several reports and the values of the rainfall, water level and flooded area were obtained from the observed data. In the 2013 flood event, the failure of an embankment on the west drainage canal at Laturharhari occurred, and city’s financial core, including the president palace, were inundated, which led to the death of 41 people. In 2020, at least 67 people were killed, and 60,000 were displaced in the worst flooding that has occurred in the area since 2007.