Estimation of river flood damages in Jakarta, Indonesia

Abstract

Flooding is a serious problem in Jakarta, and detailed estimation of flood damage is necessary to design optimal flood management strategies. This study aims to estimate flood damage in a densely populated area in Jakarta by means of a survey, to develop the relationship between flood characteristics and flood damage, and to compare the damage estimates from the survey with the damage estimates obtained by a flood damage model for Jakarta, i.e. the damage scanner model. We collected data on economic losses of the January 2013 flood in a survey of flood-affected households and business units in Pesanggrahan River. The actual flood damage in the survey area is US$ 0.5 million for the residential sector and US$ 0.7 million for the business sector. The flood damage for a similar event in the same area based on the damage scanner model is estimated to be US$ 1.3 million for the residential sector and US$ 9.2 million for the business sector. The flood damage estimates obtained by the survey approach are lower compared to the damage scanner approach due to different ways in obtaining flood damage data and in defining the maximum flood damage per object, the different spatial levels of analysis, and uncertainties in constructing the flood damage curves that were applied in the damage scanner model.

The cost of floods in developing countries’ megacities: a hedonic price analysis of the Jakarta housing market, Indonesia

“…They also found the annual expected damage due to river flooding in Jakarta is approximately US$ 321 million per year, and obtained new estimates of economic exposure values for different land use classes (industry and warehouse, commercial and business, planned house, and density urban). In the same vein, the study undertaken by Wijayanti et al (2017) measured flood damage in Jakarta but distinguished between residential and business sectors, with reported values of US$ 1.3 million and US$ 9.2 million in 2013, respectively. Wahab and Tiong (2017) proposed a multi-variate residential flood loss estimation model to estimate direct tangible loss to buildings and contents for the residential sector after the 2013 January floods.…”

Transformative Flood Risk Reduction in Jakarta: Between Urgent Needs and Contested Measures

“…In 2007, at least 56 died in one of the worst floods in the city's history, in which over 340,000 people had to be evacuated and more than 74,000 houses were flooded (IFRC 2007). The economic damage of that flood alone, which inundated around 60 percent of the city with flooding depths of up to four meters (IRFC 2007), were estimated at around USD 560 million (Wijayanti et al 2017). Yet, the 2007 flood was by no means a one-off event.…”

Using rapid damage observations from social media for Bayesian updating of hurricane vulnerability functions: A case study of Hurricane Dorian

“…Observations, such as those from surveys (Wijayanti et al, 2017), can improve the accuracy of damage estimates (Douglas, 2007). However, affected areas are often difficult to access following a disaster (Bono and Gutiérrez, 2011), and human resources are often limited (Koshimura et al, 2009).…”