Using AHP-PROMOTHEE for Selection of Best Low-Impact Development Designs for Urban Flood Mitigation

Abstract

In this study, in addition to studying the effects of several LID schemes on urban ood control, the Analytic Hierarchy Process-Preference Ranking Organization Method for Enrichment Evaluation (AHP-PROMETHEE) combination method has been used to select the best design. This paper investigates the drainage system in Golestan town of Semnan under a 5-year return period. The LID methods have been selected based on the region's conditions and available facilities. Then Rain Barrel (RB), Permeable Pavement (PP), and In ltration Trench (IT) were considered as LID methods. Seven scenarios with the names RB, PP, IT, IT-PP, IT-RB, PP-RB, and IT-PP-RB have been considered to provide the best LID usage combination. Four analytical ranking criteria were selected for the ranking procedure, including implementation cost, hydraulic performance, environmental impact during implementation, and ease of implementation. Then the weight of these criteria was obtained using Analytic Hierarchy Process (AHP). Finally, after determining the weight criteria, the LID designs were ranked using the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method. The results of hydraulic studies indicate the effectiveness of the PP-RB scenario with an average reduction of 90% of peak discharge and an average reduction of 80% of total ood volume. Also, the weakest performance is related to the IT scenario, with an average decrease of 60% of peak ow and 47% of total ow volume. AHP-PROMETHEE analysis showed that the simultaneous use of RB and IT with a coverage percentage of 5% and a cost of $ 57,710 reduced the total volume by 51.54% and the peak discharge by 48.8% compared to the results of the current system. According to AHP-PROMETHEE, IT-RB-5 is the best project proposed among the 70 projects studied. This study showed that the AHP-PROMETHEE method could be used as a practical method to choose from several LID schemes for ood control.

Balancing Flood Control and Economic Development in Flood Detention Areas of the Yangtze River Basin

“…For example, the flood risk of the Shenzhen metro system was effectively evaluated by researchers using AHP and TFN-AHP, further validating their findings with actual inundation data and showcasing the strengths of the AHP method in risk assessment [23]. Other researchers have used AHP (the preference ranking organization method for enrichment evaluation) to choose the optimal Low Impact Development (LID) design for urban flood prevention, eventually deriving the most practical solution [24]. However, due to the reliance of the AHP on expert scoring, which introduces a degree of subjectivity, we integrated the Entropy Weight Method (EW) to minimize this subjective bias [25,26].…”

A Review of Flood Mitigation Literature: A Case Study of Sidoarjo Regency, Indonesia

“…Additionally, the study discusses the future prospects and challenges for improving forecasting accuracy and reliability, highlighting the importance of incorporating climate change projections, improving data availability, and enhancing stakeholder engagement in the development of forecasting systems. Dadrasajirlou et al (2023) examined the pressing problem of urban flooding and emphasises the importance of implementing low-impact development (LID) strategies. By framing the issue within the context of sustainable urban planning, the authors effectively convey the urgency and relevance of their research.…”

Comparison of hydrological modeling, Artificial Neural Networks and multi-criteria decision making approaches for determining Flood Source Areas

“…Floods are almost the most prevalent (47%) of all climate-related disasters in the last two decades, affecting 2.3 billion people and causing the third biggest amount of economic damage (662 billion USD) according to the CRED and UNISDR analysis (CrED, 2015). Among natural calamities, floods are more hazardous than landslides, earthquakes, and volcanoes (Bolt et al, 2013).…”

“…MCDM methods aim to find the best or optimal solution among a set of alternatives by considering multiple criteria, which can be quantitative or qualitative in nature (Belton & Stewart, 2002). Some commonly used MCDM methods in hydrology include Analytic Hierarchy Process (AHP) (Wijesinghe et al, 2023), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Hwang et al, 1981;Mahmoodi et al, 2023;Mitra & Das, 2023), and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) (Brans et al, 2005;Dadrasajirlou et al, 2023). Multi-criteria decision methods provide a structured approach to consider multiple criteria and objectives in decision-making (Saaty, 1980).…”