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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.
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.