Picture this: Indraprastha Complex, the commercial area around one of the busiest and upscale roads-the Drive-in Road near Himalaya Mall-was flooded after heavy rainfall in Ahmedabad on July 23. Nearly 40 shops in the complex remained flooded for days. This was not the case for over two decades, the owners who suffered losses running into crores said.
For city officials, it creates a difficult operational challenge, the Ahmedabad civic body authorities stated, adding that during heavy rain, teams must simultaneously respond to complaints, deploy field staff, manage pumping and drainage operations, protect critical routes, coordinate public communication and prepare for the next spell of rainfall.
Looking at the available information, which is often fragmented across maps, rain gauges, field teams, citizen messages and separate departmental records, the Indian Institute of Technology Gandhinagar’s (IITG) ‘Rain2Resilience’ platform for Ahmedabad Municipal Corporation (AMC) seeks to bring these pieces together.
IIT Gandhinagar is developing the end-to-end urban flood monitoring and decision-support system with support from its Research Park incubation system.
However, the purpose is not to create another static flood map, but to help city teams understand emerging flood risk and test response options before committing time and public resources.
“As Ahmedabad city has increasingly become prone to flooding in the last few years, as various parts of the city get submerged for days due to heavy and sudden rainfall events, we hope this will effectively address this problem. This is a technology-based system that collects rainfall forecasts, areas prone to waterlogging, drainage network and weather information at one place, helping the administration to provide timely warnings and take appropriate decisions,” said Ahmedabad Municipal Commissioner Banchhanidhi Pani.
The platform, launched July 31, will combine rainfall observations, rainfall nowcasting and forecast products, drainage and geospatial layers, satellite information, field evidence and relevant water conditions outside the municipal boundary. This matters because urban flooding can be compound in nature: intense local rainfall may interact with drainage constraints, backwater effects and connected water systems beyond the city itself.
The idea is already visible in an experimental flood-reporting portal developed by the team.
“If a school route repeatedly floods, the important question is not only where water has accumulated. The city should be able to test what might reduce the depth, duration or disruption: a drainage improvement, pumping plan, storage option or another targeted intervention. That is the shift from mapping flood impacts to testing solutions,” said Prof Udit Bhatia, Assistant Professor in Civil Engineering and Computer Science and Engineering at IIT Gandhinagar.
From a citizen report to city-scale intelligence
During the recent trial, residents were able to upload a photograph of waterlogging along with the location, approximate flood depth, time and a brief description. For AMC, this creates a new kind of local evidence. A resident’s report is no longer only a complaint to be resolved; it can become a verified observation and citizen partnership that helps identify emerging hotspots, validate flood-model outputs and guide field response.
“When such reports are combined with rainfall, drainage, terrain, satellite and forecast information, the system can distinguish between an isolated incident and a recurring or rapidly worsening flood-risk location,” explains Prof Udit Bhatia.
GPU-scaled models and a scenario lab
At the centre of the system is FloodAstra-GPU, an in-house graphics processing unit-scaled flood modelling engine. The high-performance computing capability is intended to allow city-scale flood scenarios to be processed quickly enough to support operational planning, rather than only post-monsoon analysis. It also gives the project local scientific control over the model: it can be inspected, adapted and improved for Ahmedabad’s own terrain, drainage network, rainfall patterns and field evidence.
The team has already demonstrated the idea through FloodAstra-GPU work in Gurugram, where the system brings together rainfall, drainage, terrain, citizen reports, GIS layers and operational scenarios. The same approach is now proposed for Ahmedabad through Rain2Resilience, with an emphasis on municipal workflows, compound flooding and locally relevant response planning.
“Urban flooding is a long-term and difficult urban challenge. It evolves quickly during a storm, but its drivers build up over time as rainfall patterns, drainage conditions and urban form change. Municipal teams already have too much on their plate during a major rain event. Scientific solutions are needed to translate rainfall, drainage, field observations and citizen reports into practical decision support,” Prof Udit Bhatia from IIT Gandhinagar told The Indian Express.
A key feature of the proposed platform is the ‘Scenario Lab’. It would allow teams to examine potential interventions such as improving a drainage connection, deploying temporary pumping, creating local storage, protecting a critical route or identifying recharge opportunities. “The objective is not to replace engineering surveys or detailed design. Rather, it is to identify where field verification and detailed investment should be prioritised,” he adds.
The team states that the long-term aim is a living flood-intelligence system that learns from every monsoon. As rainfall records, field surveys, municipal data, satellite products, sensors and citizen reports accumulate, the system can improve its understanding of Ahmedabad’s evolving hotspots. For residents, the intended benefit is claimed to be direct, quicker recognition of flooding, better-informed municipal response, and a clearer path from an on-ground report to city-level action.
IIT Gandhinagar’s Rain2Resilience platform aims to help Ahmedabad tackle urban flooding by combining weather forecasts, citizen reports, drainage data and real-time flood modelling (File photo). 
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