Climate responsive design for road surface drainage systems: a case study for city of Bengaluru

ABSTRACT

This study proposes a Geographic Information System (GIS) based algorithmic design of surface road drainage systems. The algorithm identifies a mechanistic workflow based on the rational method to estimate runoff. The approach leverages satellite imagery to delineate contributing watersheds and predict the land-use class for design roads. Rainfall intensity is determined from high temporal resolution climate corrected Intensity-Duration-Frequency curves derived from cascade modelling and non-stationarity analysis based on Global Climate Models. The proposed algorithm predicts the cross-sectional area of drains considering climate change-induced rainfall correction factor of 1.14 derived from a multi ensemble of 9 RCMs with RCP4.5 scenario. The algorithm is applied to 27 roads in Bengaluru City to check the adequacy of drains. Results show an average increase of 15.7% in rainfall intensity for a five-year return, reflecting a 13.3% average increase in the cross-sectional area of roadside drains.

KEYWORDS:

• Road surface drainage
• rainfall disaggregation
• catchment area
• non-stationary IDF
• climate change

Disclosure statement

No potential conflict of interest was reported by the author(s).

Abbreviations

CMIP	=	Coupled Model Intercomparison Project
GCM	=	Global Climate Model
DEM	=	Digital Elevation Mode
RFB	=	Ratio of Future precipitation to baseline precipitation
SRTM	=	Shuttle Radar Topography Mission
CCCR	=	Centre for Climate Change Research
IMD	=	Indian Meteorological Department
IDF	=	Intensity Duration Frequency

Data availability statement

Datasets related to this article can be found at https://github.com/amanbagrecha/surface-drainage, hosted on GitHub.