GROUP 4(JM, Carlos, Pieter, Esther, Taigbenu & Yasmina )

• Which technologies are being developed – or are they already used in water productivity and management?

• Best practices and lessons learned?

• Real challenge: how to choose the right technology and how to get it into use?

Which technologies are being developed – or are they already used in water productivity and management?

• Define target audience in order to bridge the gap and make these technologies useful – develop different layers of intervention

• Define target areas:

- Thematic areas (adaptation to climate change, food security, productive use for sustainable agriculture)

- SDGs and address the specific 7 issues:– Safe drinking water– Sanitation and hygiene – Water quality– Water-related ecosystems– IWRM– Water efficiency – Y

- Rain gauges used to measure rainfall (using technology from one field and using it for another (loudspeaker to mic)

- Making groundwater visible with gauge floater: information symmetrical

- Wide variety of technologies from extremely advance (GIS) to very simple (mics)

- Open access data and real information: - To have impact on the data influenced by all levels - Knowledge means power which will effect decision makers

Which technologies are being developed – or are they already used in water productivity and management?

Best practices and lessons learned?• Best practices: - Technologies owned by end users with the right skills to operate and maintain

the technologies without reliance on external bodies

- Translating knowledge into operational skills

• Lessons learned: - Collaboration and partnerships – being in touch with those with the know-how

- Mobile usage: used and reported by head of household or end user? How reliable is the data?

- Cultural impact on technology can be significant

Real challenge: how to choose the right technology and how to get it into use?

• WHO is choosing this technology?

• Integrate indigenous knowledge into the data gathered (two-way data gathering)

• Disillusionment to end user when system fails – need to have ownership at end user level

• Quality assurance • Forecasting – thresholds