To tackle this challenge, we developed a user-friendly crowdsourcing web application that estimates the quality class of the water using well-established water quality standards and displays the results on a map. A user can use our app to filter the water classes and see which areas demand immediate action. The data that we are currently using are collected from web repositories but can also be imported from sensors or entered manually by any user, including both organizations and local people.

This project is solving the Clean Water Mapping challenge.


Our project aims to improve the mapping of information regarding the water quality of our planet. Water quality mapping is a topic of critical importance, as it can reduce the current access limitations to drinking water in rural areas of the developing world and can also help scientists identify areas that demand immediate attention due to low water quality. Furthermore, by improving water quality mapping, space engineers will be able to develop and implement innovative ways to make clean water available and will gain a better understanding of community water needs. Moreover, learning more about drinking water on Earth could potentially inform future space explorers on techniques to use during long-duration spaceflights. Last but not least, water quality mapping will increase citizens' awareness about global water issues and increase people's participation in actions that aim to improve earth's water quality.

We decided to solve this challenge by creating a user-friendly crowdsourcing web application to display the water quality classes on a map and enable both technical and non-technical people to enter water quality data easily. The data are used to estimate the water quality classes automatically, using a smart algorithm. Further work may include available soil, weather, climate and population density data for the improvement of our application and the development of early warning systems for regions that are under water stress.

Project Information

License: MIT license (MIT)

Source Code/Project URL:


Web App -
Screenshot -


  • Eleni Proxenou
  • Stefanos Chrs