1. 1 Water scheme monitoring using mobile-to-Web technologies in Senegal World Water Forum Istanbul 16-22 March 2009 Session 2.1.1

2. 2 A quick overview of rural water schemes (RWS) in Senegal Operating data –Persons served4 396 980 –Villages connected5 100 –Public standposts >10.800 –Private connections66 881 –Cumulated output: 120 000 m 3 /day (estim.) –Mean availability rate: 95% (2007) 1200 RWS

3. 3 Challenge: the need for reliable operating data on 1200 rural schemes What for ? –Regulation of water service management –Management of ground water resources –Follow-up of O&M by private operators Strategic stakes for sector governance –Continuity of safe water delivery to 4,4 million people in rural areas –Transparency, accountability and efficiency of water service over 1200 RWS

4. 4 Issues to address in developing a countrywide monitoring system Weakness of present monitoring activities –Limited to a small number of sites (projects) –Lack of feedback to water user assoc. (ASUFOR) –Not really sustainable after projects closure Logistical constraints –Geographical dispersion of the 1200 RWS Effective participation from stakeholders –Endorsement required from the ASUFOR –Deal with variable capacities of ASUFOR staff

5. 5 Conceptual ideas for a basic monitoring system on RWS Goal: a monitoring system that can be deployed over a large number of RWS and accessed by multi-users Concept –A limited set of data (i) relevant for monitoring needs and (ii) that can be collected on-the-spot –A reliable, simple and sustainable data handling and management system –A continuous feedback to each ASUFOR

6. 6 A favorable context: the high use of mobile telephony in rural areas High penetration growth in rural population  70% of RWS locations covered by networks Existing mobile-based services in agriculture

7. 7 Designing a basic performance monitoring using 3 monthly data 1.Reading of bulk water production meter(s) 2. 2.Balance of current and savings accounts 3. 3.Nb. of days of down- time in the current month

8. 8 Data sent by SMS Today: by typing 2 sms on an ordinary mobile phone Soon: with a user- friendly, dedicated “water” mobile phone cpt 4740000#4763800 Balance of accounts eau 98540# Index of water meter

9. 9 Data received on a mobile-to-web platform and transferred to a website for processing and analysis DATA SENDING DATA PROCESSING DATA ANALYSIS AND FEEDBACk

10. 10 Data processing and Performance monitoring outputs 5 indicators calculated from data –Mean daily outputm 3 /day –Actual / Authorized daily output ratio % –Self-financing capacityFCFA –Self-financing capacity per m3FCFA/m 3 –Service availability rate% Evaluation of indicators against –Reference values –Analysis of historical trends

11. 11 Indicative table of reference values INDICATOR REFERENCE VALUE AVERAGE DAILY OUTPUT > 120 m 3 /day 70 to 120 m 3 /day < 70 m 3 /day ACTUAL / AUTHORIZED A.D.O. < 70%70 to 90%> 90% SELF FINANCING CAPACITY > 10 MFCFA 5 to 10 MFCFA < 5 MFCFA SERVICE AVAILABILITY RATE > 95%90 to 95%< 90%

12. 12 Output #1: Monthly summary report Risk notification (Reference values) Risk anticipation (Historical trends) Feedback and advice

13. 13 Output #2: Water extractions chart

14. 14 Output #3: Management chart Sites with low financing capacity vs daily output Sites with medium to high financing capacity vs daily output TO BE CHECKED 1st

15. 15 Implementation of the service Public private partnership PEPAM-MANOBI –Development by MANOBI with PEPAM guidance –Service delivery by MANOBI to ASUFORs through a subscription system –Data shared with PEPAM for regulation needs Steps –Pilot phase in 2008 with 60 ASUFORs –Progressive deployment starting 2009 Support of the Water and Sanitation Program

16. 16 Thank you