Primary: IIT Delhi Drainage Master Plan (2018)
Gosain, A. K., Khosa, R., Chahar, B. R., Kaushal, D. R., & Dhanya, C. T. “Drainage Master Plan for NCT of Delhi — Final Report,” IIT Delhi for I&FC Department, GNCTD, July 2018. SWMM + SWAT simulation of 3 major basins (Najafgarh, Barapullah, Trans-Yamuna), 5 intervention scenarios, junction-flooding volume/duration analysis. Design parameters: Manning’s n (Table 4.1-3), Horton infiltration (Table 4.3-1/2/3), IDF curves (Ch 4.4, Safdarjung & Palam).
Pluvial Mechanism: SWMM Conveyance Model
Drain capacity proxy (capacity_c) calibrated against IIT Delhi SWMM conduit-flow analysis. The ratio C/(R×T) maps to junction overflow volume under design storm. Najafgarh basin: 3,854 junctions flooded under 2-year storm (Scenario 1); reduced to 2,794 after cross-section correction (Scenario 2). Horton soil saturation (f∞=0.635 mm/hr, Group D loam) applied as multi-event capacity reduction factor.
Fluvial Mechanism: CWC Yamuna Thresholds
Central Water Commission, “Delhi Floods 2023 Case Study,” August 2024. Peak stage 208.66m at Old Railway Bridge (Jul 13), peak discharge 3,60,000 cusecs at Hathnikund (Jul 11). CWC warning level 204.5m, danger level 205.33m. Validated against INDOFLOODS gauge INDOFLOODS-gauge-164 (IIT Delhi HydroSense Lab, 2025, DOI: 10.5281/zenodo.14584654).
Compound Mechanism: Drain Backflow
Interaction model grounded in IIT Delhi DMP Executive Summary: outfalls into Yamuna are final storm water disposal points; when river submerges outfalls, drain reversal occurs. DDMA documented 18 major drains experiencing reverse flow during Yamuna spate. Multiplicative interaction ensures compound score only activates when BOTH rain AND river are elevated AND ward is low-lying.
Basin Delineation & Catchment Validation
Delhi: 3 major basins delineated using SWAT (IIT Delhi Ch 1.2). Najafgarh (largest, ~2/3 Delhi area, 123 natural drains), Barapullah (44 drains), Trans-Yamuna (34 drains, former floodplain). Total: 201 natural drains + 3,311 km engineered storm drains. Catchment attributes cross-validated via INDOFLOODS (IIT Delhi HydroSense Lab, DOI: 10.5281/zenodo.14584654).
Intervention Mapping
IIT Delhi DMP 5 scenarios map to interventions: (1) Base condition, (2) Cross-section correction → desilting; (3) Water body rejuvenation → detention basins; (4) Parks as recharge → permeable surfaces; (5) Storage/LID → rain gardens + permeable pavement. Nangloi case study: LID reduced J_3144 flood volume from 172,880 to 3,460 ×10³ litres (Table 3.3-8).
Three-mechanism model grounded in IIT Delhi DMP 2018 (SWMM/SWAT), CWC 2023 case study, and INDOFLOODS database. In production, direct PWD drain gauge integration would replace proxy capacity values.