Urban waterlogging risk as an undervalued environmental challenge: An Integrated MCDA-GIS based modeling approach

Abstract

In the last few decades, rainfall-induced urban waterlogging has become a significant environmental barrier and acquired global prominence worldwide due to its frequent threat, which results in significant infrastructure damage and economic loss. This study aims to model and identify the waterlogging hazard, vulnerability, and risk zones in the unplanned city of Siliguri, ‘Gateway of North-east India’, with the help of an integrated Analytical hierarchy process (AHP) and GIS techniques. Due to the lack of a comprehensive database, a systematic waterlogging assessment in the Siliguri city has not yet been carried out. However, waterlogging is a seasonal phenomenon in the Siliguri city, especially during the monsoon seasons, when short-duration and high-intensity rainfall cause inundation in low-lying areas causing mayhem to the city. Therefore, in this present study, a primary field investigation was conducted to prepare waterlogging inventory map along with seventeen other parameters, including spatial and attribute data from the secondary sources to delineate waterlogging hazard, waterlogging vulnerability, and risk map. Further, the final risk map was integrated with the spatial distribution of the slums locations, revealing that a larger proportion of slum households are under high-risk zones. The results suggest that about 46% of the city is under high to very high waterlogging hazard zones, while 38% of the Siliguri is highly vulnerable to waterlogging. The final risk map reveals that around 35% of the study area is susceptible to threat of waterlogging, which is mostly concentrated in the central part of the city center. Besides, the consistency of the model was assessed by area under curve (AUC), which gives an accuracy of 0.782 or 78.2%. This study's overall strategy may be used for planning and mitigation efforts to reduce future waterlogging incidents all around the world.

Keywords

• Waterlogging
• Remote sensing and GIS
• Analytical hierarchy process
• Risk