A web dashboard and API that combines rainfall forecasts with city elevation and drainage data to predict street-level flooding up to three hours in advance.
Ministry of Earth Sciences (MoES) · National Centre for Medium Range Weather Forecasting (NCMRWF) · Software
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Decomposed from what the description asks for. Nothing added.
Rainfall Data Pipeline
A pipeline that ingests high-resolution rainfall nowcasts from Doppler Weather Radars.
Surface Terrain Model
A module that routes rainfall volume across a two-dimensional surface terrain model.
Drainage Graph Model
A graph-based model representing the stormwater drainage network to calculate hydraulic capacity.
GIS Dashboard
A dynamic web-based map showing real-time street-by-street flooding projections with water depth in centimeters.
Navigation API
An API utility that suggests flood-safe alternative routes for emergency services and commuters.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The jury will check if your system can couple rainfall nowcasts with digital elevation models and a drainage network graph, rather than relying on isolated weather models. They will test the 0 to 3 hour forward-looking window, the accuracy of street-level water depth estimations, and the functionality of the routing API.
A jury can still ask about these. Decide them deliberately rather than by accident.
Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.
Exact geographic coordinate data or GIS layers for a specific city's drainage network?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Access to live Doppler Weather Radar data feeds?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
The brief asks for rainfall data pipeline. How would you build that?
Decoded from SIH26085 itself — A pipeline that ingests high-resolution rainfall nowcasts from Doppler Weather Radars. The brief asks for it by name.
Each one is quoted from a gap in the brief, not a guess about your team.
Needs data you may not get
The prompt requires a graph-based mathematical model of a city's underground drainage network and high-resolution Digital Elevation Models, which are typically municipal assets not readily available to students.
What the organisers attached, and what the brief assumes you can get.
Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.
Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.
Who has this problem, what already exists, and what you would have to find out.
The brief asks for surface terrain model. How would you build that?
Decoded from SIH26085 itself — A module that routes rainfall volume across a two-dimensional surface terrain model. The brief asks for it by name.
The brief asks for drainage graph model. How would you build that?
Decoded from SIH26085 itself — A graph-based model representing the stormwater drainage network to calculate hydraulic capacity. The brief asks for it by name.
The brief asks for gis dashboard. How would you build that?
Decoded from SIH26085 itself — A dynamic web-based map showing real-time street-by-street flooding projections with water depth in centimeters. The brief asks for it by name.
The brief asks for navigation api. How would you build that?
Decoded from SIH26085 itself — An API utility that suggests flood-safe alternative routes for emergency services and commuters. The brief asks for it by name.
Where does your data come from — a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the jury will check if your system can couple rainfall nowcasts with digital elevation models and a drainage network graph, rather than relying on isolated weather models.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
Show me this working: they will test the 0 to 3 hour forward-looking window, the accuracy of street-level water depth estimations, and the functionality of the routing API.
This is the evaluator read for your problem statement, decoded from the brief's own wording.