JalLoop AutoReserve: Building a Smarter Approach to Rainwater Management
A project built for Environmental Hacks 2026 | Heat and Water Track
Series: Building Sustainable Solutions with AWS (1 article)
- 1JalLoop AutoReserve: Building a Smarter Approach to Rainwater Management This article
Software Engineer
Introduction
Water scarcity and rainwater overflow may seem like opposite problems, but buildings often experience both. During dry periods, households and institutions struggle to maintain sufficient water supplies. During heavy rainfall, storage tanks may already be full, causing potentially useful rainwater to overflow.
We built JalLoop AutoReserve, a forecast-aware water management platform designed to help buildings make better decisions about water storage, rainwater collection, and reserves for dry days.
Our goal was to explore how weather forecasts and simple water-balance calculations could support more informed water management.
The Problem We Wanted to Solve
Many buildings depend on rooftop water collection and storage tanks, but deciding how much water to store before rainfall can be difficult.
Keeping a tank full may leave insufficient space for incoming rainwater. Emptying too much water before a storm may create shortages if the expected rainfall does not arrive or demand increases.
These decisions matter to residential buildings, apartments, colleges, and commercial facilities, especially in areas that experience seasonal rainfall and water shortages.
We wanted to build a tool that connects rainfall forecasts with a building's actual storage requirements instead of treating rainwater collection and water conservation as separate problems.
Our Solution: JalLoop AutoReserve
JalLoop AutoReserve brings key water-management parameters into a single dashboard. Users can provide details such as rooftop catchment area, runoff coefficient, tank capacity, current water level, daily water demand, and expected rainfall.
The application uses these inputs to estimate:
- Potential rainwater runoff from the rooftop.
- Available tank capacity before rainfall.
- A possible pre-storm drawdown while maintaining a water reserve.
- Expected rainwater capture and potential overflow.
- How long the stored water could support daily demand.
The platform also presents advisory recommendations to help users compare water-storage decisions. These recommendations are estimates rather than automatic control instructions.
How the Technology Works
We developed the application using a React-based frontend and a FastAPI backend. The frontend presents the water parameters and calculation results, while the backend handles the water-balance logic and calculation history.
We integrated Open-Meteo to retrieve weather forecast data without requiring a conventional API key. The application combines the available forecast information with user-provided building parameters to estimate potential water-management outcomes.
We also created a simulated sensor telemetry interface to demonstrate how building water-level information could be represented in a future connected system. The current prototype does not connect to physical sensors, pumps, or automated valves.
Our technology stack includes:
- Frontend: React, Vite, and Tailwind CSS
- Backend: Python and FastAPI
- Local data storage: SQLite
- Weather forecasts: Open-Meteo
- AWS development tool: AWS Serverless Application Model (SAM) CLI
How We Used AWS
AWS was an important part of our exploration of a serverless deployment architecture.
We used the AWS SAM CLI locally to validate and build our serverless application template. We ran
sam validate to check the template and sam build to prepare the application build. Both commands completed successfully.Our SAM template defines a planned architecture involving AWS Lambda, Amazon API Gateway, and Amazon DynamoDB. This architecture provides a starting point for a future cloud deployment.
However, these AWS cloud services have not yet been deployed. Our current live prototype is hosted on Render and uses FastAPI and SQLite. We chose to distinguish between the AWS tooling we actually used and the cloud architecture we intend to implement, rather than claiming a deployment that has not happened.
Challenges and What We Learned
One of our main challenges was balancing two competing goals: making enough space to capture incoming rainfall while retaining enough water for future demand.
We addressed this by combining rainfall estimates, tank headroom, and reserve requirements into a single calculation workflow. We also worked on integrating weather data with the application and ensuring that the frontend and backend communicated correctly.
Deploying the prototype introduced additional practical challenges, including resolving a missing weather-service module and verifying that the production frontend could build successfully.
These issues reinforced an important lesson: a project is not complete simply because it works locally. The deployed application, its dependencies, and its documentation must also be checked.
We also learned to distinguish simulated telemetry from real sensor measurements and calculated savings from verified environmental impact.
Environmental Impact and Future Scope
JalLoop AutoReserve is intended to help users understand their available storage capacity, plan for rainfall, and reduce avoidable rainwater overflow while protecting essential water reserves.
Future improvements could include integrating real water-level sensors, connecting to building-management systems, deploying the backend on AWS Lambda and API Gateway, and storing operational data in DynamoDB. Further testing with real rainfall, tank-level, and water-demand measurements would be necessary to evaluate the accuracy and practical benefits of the system.
The current project is a decision-support prototype, not an autonomous water-control system. Its estimates can support planning, but actual outcomes depend on local weather, roof conditions, storage infrastructure, and water consumption.
Conclusion
JalLoop AutoReserve explores a practical question: how can buildings prepare for incoming rainfall without compromising their water supply during dry periods?
By combining weather forecasts, water-storage calculations, and an accessible dashboard, we developed a prototype that helps users examine this trade-off more systematically.
Environmental problems often require solutions that connect several everyday decisions. For us, this project was an opportunity to explore how software and cloud-oriented architecture could contribute to more informed water management.
Project links
- Live demo: https://jalloop-autoreserve-1.onrender.com/
- GitHub repository: https://github.com/bharat7-cyber/jalloop-autoreserve
- Demo video: https://youtu.be/DlkSj4_FBBs
Series: Building Sustainable Solutions with AWS (1 article)
- 1JalLoop AutoReserve: Building a Smarter Approach to Rainwater Management This article
Enjoyed reading this content? Let the author know!
Your likes, comments, shares, and saves help creators reach more builders.
Loading recommendations
Loading article