Incorporating socio-economic effects and uncertain rainfall in flood mitigation decision using MCDA

Abstract

The decision making process in flood mitigation typically involves a number of factors reflecting flood severity, flood vulnerability and the cost of the mitigation measures, which implies that the decision framework needs to combine both social-economic parameters and flood extent prediction analysis. A socio-economic vulnerability index (SEVI) is developed here to represent social-economic factors and its use demonstrated within a multi-criteria decision analysis (MCDA) for assessing flood levee options for a central basin of Jakarta, Indonesia. The variables defining the SEVI are selected based on available national social-economic data reported for Indonesia with overlapping information removed using Pearson's correlation analysis. Two different methods are used to further scale the SEVI which is developed along administrative boundaries into a Net SEVI which is dependent on the predicted flood hazard as resulting from the levee plan options while capturing uncertainty in the rainfall forecasting. The MCDA technique adopted uses criteria of Net SEVI, annual expected loss, graduality and levee construction cost for analyzing six different levee plans and with uncertainty in the rainfall incorporated. The Net SEVI thus specifically reflects the social-economic impact on the flood-affected population, and this approach thereby provides a higher degree of granularity in the flood mitigation decision process. The MCDA decision framework developed is general in that the Net SEVI can be applied for consideration of other flood mitigation strategies. Here, it is shown that the inclusion of the Net SEVI criteria changes the best choice levee plan decision to a higher protection level for the basin considered.

Effect of climate change and urbanisation on flood protection decision‐making

“…MCDA is widely used across disciplines and particularly in the field of water resources planning and management covering water policy evaluation, strategic planning and infrastructure selection (Abrishamchi, Ebrahimian, Tajrishi, & Mariño, 2005; Cabrera & Lee, 2020; Porthin, Rosqvist, Perrels, & Molarius, 2013; Raju & Vasan, 2007; Young, Younos, Dymond, Kibler, & Lee, 2010). The flood protection decision framework adapted here was first developed by Daksiya et al (2015) and improved in Daksiya, Su, et al (2017) to account for socio‐economic factors. Criteria of AEL and G as key measures of flood severity, Net SEVI as a measure of socio‐economic vulnerability and further reflecting population distribution and economic productivity, and levee upgrading cost C were used in the MCDA as described in Section 2.2.…”

“…The Jakarta flood model was first developed by Lo and Chen (2013) and used in recent studies for flood risk assessment under current conditions (Daksiya et al, 2015; Daksiya, Su, et al, 2017). The model uses the Hydrologic Engineering Centre (HEC)‐Hydrologic Modelling System (HMS) version 4.2 and River Analysis System (RAS) version 4.1 for hydrologic and hydraulic modelling of two major rivers, Ciliwung and Cengkareng (Figure 1).…”

“…Loss curves as shown in Figure 2 were generated for the daily rainfall for the range of 100–350 mm/day. The developed flood model was calibrated with the recorded water level from DPU for the earlier February 2007 and February 2002 flood events with percentage difference in peak flow of ≤5.4% and ≤7.1% for the two events as measured at Katulampa, Depok and Manggarai stage stations (see Figure 1; Daksiya, Su, et al, 2017). There are extensive studies on hydrology and hydraulic model uncertainties and its impact on flood inundation mapping (Ahmadisharaf, Kalyanapu, & Bates, 2018; Annis, Nardi, Volpi, & Fiori, 2020; Apel, Merz, & Thieken, 2008; Bates, Pappenberger, & Romanowicz, 2014; Dimitriadis et al, 2016; Rafiei Emam, Kappas, Fassnacht, & Linh, 2018).…”

A review of structural approach to flood management in coastal megacities of developing nations: current research and future directions

“…This study was useful in highlighting the best solution in terms of investment value to risk level reduction. Similarly, Daksiya et al (2017) carried out a comparative evaluation of six different flood levee construction plans for a central basin of Jakarta using a MultiCriteria Decision Analysis (MCDA) technique that takes into consideration flood extent estimates, cost of flood mitigation measures, and the social-economic impact of flooding on people. Findings from Yin et al (2015) and Xian et al (2018) suggest that in-depth decision making regarding priority-based selection of flood protection measures can be influenced by other factors, including flood return periods, institutional aspects of governance, topography, societal exposure, and experience with past extreme events.…”

Decision making on flood mitigation incorporating uncertainty, socio-economic factors and a changing future

“…This approach treats the levee protection level as a continuously varying design variable to be optimized, rather than as the selection of a best plan amongst a fixed number of alternatives. (Daksiya et al, 2017a) (Daksiya et al, 2017b) software packages available, the freely available HEC-HMS which has the ability to simulate the land-use changes and design-rainfall precipitation in flood peak flows in used in the Jakarta Flood Model of Chapter 3.…”