A scenario planning approach for propositioning rescue centers for urban waterlog disasters

Highlights

• A system specification for urban waterlog disasters is developed.

• A two-stage stochastic programming model is formulated.

• The economic cost and loss, and environmental and casualty risks are considered.

• The urban waterlog disasters in Pudong District of Shanghai, China is examined.

Abstract

An urban waterlog disaster can produce severe results, such as residents’ property loss, environmental damages and pollution, and even casualties. This paper presents a system specification for urban waterlog disasters according to the analysis of urban waterlog disaster risks. Then, a two-stage stochastic mixed-integer programming model is formulated. The model minimizes the total logistics cost, and risk-induced penalties. Moreover, a deterministic counterpart of the stochastic model is proposed to study the expected value of perfect information. The multi-attribute utility theory is used to build assessment functions that assess the utility of the rescue system and the degree contributed to disaster relief for each rescue center. Finally, a real example of rescue logistics is examined for the urban waterlog disasters in Pudong District of Shanghai, China. Using the proposed model, two main results can be obtained. First, the expected value of perfect information experiment reveals that an additional ¥45,005 logistics cost and an additional ¥2417 risk-induced penalties can be incurred due to the presence of uncertainty. Second, as the weight of risk-induced penalty increases from 0.1 to 0.9, the logistics cost is increased by 41.21%, which thus contributes to a decrease of risk-induced penalty by 97.44%. Some managerial implications are discussed based on the numerical studies.

Introduction

Urban waterlog disaster (UWD) is caused by a rainfall that the drainage system of the city fails to drain off the water produced by the rainfall. UWD is one of the most frequent disasters over the developing countries due to its poor drainage system of the city. The statistics carried out by the Ministry of Housing and Urban-Rural Development in China based on a survey of 350 cities, revealed that China is a victim of UWDs. From 2008 to 2010, 62% Chinese cities have suffered from UWDs, and 137 of them have been affected for three times or more, such as Beijing, Shanghai, Chongqing, Nanjing, Hangzhou, Changsha, Hefei, Xi’an and Nanning. Among the cities affected by waterlog, in 76.4% of them, the deepest water depths are over 50 cm, and 90% of them over 15 cm (the height of the most vehicular exhaust pipes). About 79.8% of them suffered UWDs for more than 30 min and even 59 cities have suffered UWDs that lasted over 12 h.

On July 21st, 2012, a worst UWD ever happened in Beijing, which brought by a torrential rain. The rain led to the tragedy of nearly ten billion economic losses, 1.9 million people affected, 37 casualties, and 7 people missing (http://bj.bendibao.com/news/2012723/81560.shtm, assessed 2013-10-08). Shanghai is one of the cities in the world that are most vulnerable to serious flooding (http://www.bbc.co.uk/news/science-environment-19318973, accessed 2013-10-07). Shanghai is located in the coastal area under East Asian Monsoon, and the oceanic climate brought an average annual precipitation of about 1100 mm. UWD also became a concern to Shanghai. On September 20th, 2008, the rainfall in Pudong District from 14:15 to 15:15 reached 108 mm, which exceeded the standard of once-for-one-hundred-year torrential rain (101 mm/h). It ended up with one death, 14 injuries, more than 20 waterlog roads and 60 flooded homes (Yin, Bao, & Yin, 2011). UWD is a serious problem because of the unique climate and topographic situation of Shanghai.

Wang (2012) analyzed the reasons of waterlog at Nanning (in China) in water system balance; Liu and He (2012) investigated the reasons of UWD in Peking (in China) from 2004 to 2011. Based on Wang, 2012, Liu and He, 2012, the reasons for UWD of Chinese cities are summarized below: the size of impermeable surface is larger than before; Rain Island Effect: rainfall in urban areas is heavier and larger than suburban areas; the river drainage capability is insufficient; the infrastructure of drainage system is poor; the capacity of drainage pumping stations is insufficient. The drainage systems cannot be improved in a short term. Therefore, emergency logistic planning plays an important role in UWD management.

UWD is different from most natural disasters. Natural disasters such as typhoon, earthquake or hurricane are difficult to be predicted and usually cause numerous casualties. Therefore, relief actions mainly aim at saving people’s lives. The water depths and flow velocities of UWDs are lower than floods. UWDs also impose great influences on society because it happens frequently. In rural area, UWD may lead to cropping yield reduction, because the majority of the crop cannot growth well when its roots are inundated by water for a long period of time. In urban areas, UWDs may interrupt traffic seriously, and inundates property, then result in economic loss. Especially, when the depth of water is more than 60 cm, the UWD will bring a major losses to in-door properties. Therefore, the purpose of UWD relief is mainly to minimize the economic loss.

To reduce impacts on society, local governments must create a series of programmed relief decision-making methods for UWDs, and reserve enough rescue equipment, resources and rescue teams at rescue centers in advance. Once a UWD occurs, a rescue operation according to the programmed decision-making methods is launched into the schedule without serious delays.

Fig. 1 presents a system specification for this work. First, the main purposes of our works is propositioning rescue centers and allocating pumps to UWD-affected sites. Second, according to degrees of the disaster severity, a scenario planning approach is employed to reveal the uncertainty of the model. Then, logistic costs and risk-induced penalty are examined to formulate objective function. Finally, implications of the expected value of perfect information, sensitivity of solutions is analyzed, and the utility functions are devised to assess the rescue ability of the network of rescue centers.

This work contributes to the related literature in the following aspects. First, The previous researches on UWD were primarily limited to risk assessment, vulnerability analysis (Yin et al., 2011) and dangerousness analysis (Jing, Yin, Yin, Wang, & Wen, 2010), whereas this work focuses on the emergency logistics issues for UWD relief. Second, the logistics operational cost for facility location is mostly considered in literature, whereas the penalties induced by property loss and environmental damages, transport accidents and casualties in UWD relief are considered. Third, the studies in literature assess the solutions of disaster relief mainly by logistical cost (Lin, Batta, Rogerson, Blatt, & Flanigan, 2011) or transportation time (Yi & Özdamar, 2007), whereas this work uses multi-attribute utility functions to assess the rescue ability of each solution and the contribution degree of each rescue center.

In the remainder of the paper, Section 2 reviews studies related to emergency logistics considering uncertainty, risk quantification and assessment of planning. In Section 3, a deterministic model for UWD is formulated. And then based on the deterministic model, the uncertainties in rainfall intensity and scope are incorporated. A two-stage stochastic mixed-integer programming model is formulated. In Section 4, the details of input data acquisition, and parameters estimation are given. Section 5 describes the numerical studies, including the experiments and their numerical results. In addition, findings observed from these numerical results are summarized. Managerial implications, and suggestions for future research, are summarized in Section 6.