Aga Khan Agency for Habitat

Place of Implementation

  • Maharashtra, Gujarat and Telangana
  • Year of Implementation


    About the initiative

    An innovative tool to facilitate evidence based participatory water governance has been developed by AKAH India. Its pilot scale deployment was conducted in areas that exhibited range of water crises. A WebGIS governance platform, mobile application and notifications-based advisory were developed integrating real-time primary data, remote sensed data and secondary data to generate robust decision support system.

    Key features

  • Mapping water resources for quality and quantity through data triangulation from secondary and primary sources.
  • Developing a social monitoring tool to ensure participatory, inclusive and transparent data generation and information dissemination.
  • Facilitating integrated planning through data analytics and creating dashboards for use by communities and decision makers.
  • Outcomes

  • 63 Villages with Community Mobilized For Primary Data Collection During Pilot Phase
  • 250 Settlement Reports Generated with Water Status Health Mapped Through Secondary Data
  • 47 District Reports Generated with Water Status Health Mapped Through Secondary Data
  • Training of Government officials for water mapping in Telangana and Maharashtra
  • Sustainability Measure

    The tool was developed by keeping agility as a focus at all levels. It facilitates collaborations and data integration from various sources. Innovative tools and methods deployed for automated data collection from borewells, semi-automated water quality testing modules and other API based tools where integrated in this platform seamlessly. This proved that the platform is capable of not only facilitating data integration across different levels but it can also support various participatory approaches to be undertaken across different levels of stakeholders. This tool is open source and available to the communities across the globe by facilitating the API-supported integration of data from contextual circumstances.