1. 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?

2. 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

3. -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?

4. 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

5. 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