About the potential of novel, alternative rain sensors, such as microwave links (MWL) used for telecommunication, crowd sensing, or cheap ubiquitous sensors.

1. Eawag: Swiss Federal Institute of Aquatic Science and Technology
New information sources for rain fields
− cheap sensors
− (ab)use of existing infrastructure
− community sensing
June 17, 2014
Jörg Rieckermann, Andreas Scheidegger
Water Horizon Conference 2014, Berlin

2. Density of rain gauges
weather stations listed by the World Meteorological Organisation

3. World Water Development Report 4. World Water Assessment Program (WWAP), March 2012.
Water scarcity

4. For urban run-off modeling rainfall information in
very high-resolution is required
https://flic.kr/p/wYJxB, Guillaume Bertocchi
?

5. New sources of
information
We need:

6. New sources of information
1. Cheap and dirty
2. (Ab)use of existing infrastructure
3. Community sensing

7. Cheap and dirty sensors
http://www.bbc.com/news/science-environment-27222282, Delft University
Rabiei et al. (2013)
www.instructables.com/id/Make-an-
acoustic-rain-gauge-
disdrometer/?lang=es
Building automation
sensors
http://imomohub.org/?id=1-1027-1093-1098

8. Cheap and dirty sensors
Example Airquality
100m x 100m resolution
Hasenfratz,etal(2014)
Measure roof runoff?

9. Cheap and dirty sensors
Paradigm shift I:
Sensors do not have to be precise

10. New sources of information
1. Cheap and dirty
2. (Ab)use of existing infrastructure
3. Community sensing

11. Use of existing infrastructure in a new way
Microwave links – backbone of mobile networks

12. Microwave links as rain sensor
Receivedsignallevel[dBm]
Rainfall[mm/hr]
rain intensity
Attenuation
of signal
Use of existing infrastructure in a new way

13. Donnerstag, 25. Juni 2009 13
Meteoswiss A-Netz vs. ORANGE Network
Use of existing infrastructure in a new way

14. Zurich, CH
Use of existing infrastructure in a new way
ORANGE network in urban area

15. Prag, CZ
Use of existing infrastructure in a new way
Microwave network in urban areas

16. Comparing rain gauges to radar and MWLs (point estimates)
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Microwave links case study Adliswil
Rain gauges [mm/h] Rain gauges [mm/h]
Radar[mm/h]
MWL[mm/h]

17. No. 1
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Comparing rain gauges to radar and MWLs (point estimates)
Microwave links case study Adliswil
Rain gauges [mm/h] Rain gauges [mm/h]
Radar[mm/h]
MWL[mm/h]

18. LCF = 0.99LCF = 2.3
LCF = linear correction factor
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Comparing rain gauges to radar and MWLs (point estimates)
Microwave links case study Adliswil
Rain gauges [mm/h] Rain gauges [mm/h]
Radar[mm/h]
MWL[mm/h]

19. http://worldplantage.blogspot.ch/2010/02/african-farmers-and-web.html
WorldBank,WirelessIntelligenceandITU

20. Microwave links – work and collaboration of Eawag
CZECH TECHNICAL
UNIVERSITY IN PRAGUE
Deutschland:
Harald Kunstmann
(KIT Karlsruhe)
Africa / Central Asia:

21. Use of existing infrastructure in a new way
Paradigm shift II:
Use existing infrastructure for
new purposes

22. New sources of information
1. Cheap and dirty
2. (Ab)use of existing infrastructure
3. Community sensing

23. Community sensing I
Oxford Flood Network http://oxfloodnet.co.uk/
“Making a citizen-built flood
detection network in Oxford,
based on river levels,
groundwater and local
knowledge.”
Ben Ward

24. Community sensing I
Oxford Flood Network http://oxfloodnet.co.uk/

25. Community sensing II
British Met office http://wow.metoffice.gov.uk/

26. Community sensing III
www.openstreetmap.org

27. COBWEB Citizen OBservatory WEB
TU Dresden
“The Citizen OBservatory WEB project seeks to […] enabling the
fusion of citizen-sourced data with reference data […].”

28. Use of existing infrastructure in a new way
Paradigm shift III:
Trust non-experts

29. Making use of all
information

30. Many ways to measure rain
Rasmussen et al.
(2008)
www.unidata.com.au/
www.ott.com
Building
automation
sensor
Microwave Links
Rabiei et al. (2013)

31. Sensor properties
• What does it measure?
• point/areal measurement?
• What kind of information is provided?
• Continuous, binary signal, …
• How reliable is this information?
• Noise, biases, …

32. 1D-example
time
Rainintensity

33. Continuous Assimilation of Integrating Rain Sensors
CAIRS is under development
Feedback is highly welcome!
https://github.com/scheidan/CAIRS.jl
Interested in collaborating?
 andreas.scheidegger@eawag.ch
CAIRS
Aims:
• Generality: every signal is correctly
considered
• Flexibility: moving sensors,
irregular time intervals, …
• Fast: near real time assimilation
• “Good” code: stable, reusable, user friendly

34. Microwave Links + Pluviometers
2013-06-09 21:38:00 2013-06-09 21:38:00
x-coordinate [m] x-coordinate [m]
y-coordinate[m]
y-coordinate[m]
Rain intensities Uncertainty of rain intensities

35. Microwave Links + Radar + Pluviometers
2013-06-09 21:38:00 2013-06-09 21:38:00
x-coordinate [m] x-coordinate [m]
y-coordinate[m]
y-coordinate[m]
Rain intensities Uncertainty of rain intensities

36. Measure roof run-off?
maps.google.com

37. Signals in arbitrary time resolution
Time resolution of predicted
rain maps:
10 seconds
Measurement intervals:
MWLs: 174 – 276 seconds
Gauges: 60 seconds
time

38. Arbitrary prediction points
Compute higher
resolution for critical
areas

39. Making use of all information: Assimilation
Paradigm shift IV:
Not “A or B” but “A and B”

40. Conclusions

41. Why now?
• Telecommunication: the internet is
everywhere
• Low energy demand: micro controller and
with very low consumption available  energy
harvesting seems possible
• Computer power: Assimilation of a variety of
different signals is demanding (MCMC)
• Social media: everybody is always online
What changed in the last 10 years?
http://www.ines.zhaw.ch/
4G-AbdeckungderTelekom

42. Interdisciplinarity
“Sensors”
Data
transmission
Model
Energy
Data
assimilation
User
Computer science
Social science
Electrical engineering
Meteorology
Hydrology
Statistics

43. Paradigm shifts
I. Sensors don’t have to be precise
II. Use existing infrastructure for new purposes
III. Trust non-experts
IV.Not “A or B” but “A and B”