New technology for nowcasting and management of emergency in a city centre

1. Monitoring and Early
Management of Emergences:
New Instruments
Daniele Caviglia, DITEN - University of Genoa
Domenico Sguerso, DICCA - University of Genoa
Bianca Federici, DICCA - University of Genoa
Andrea Caridi, Darts Engineering
Tiziano Cosso, Gter
LOGO IMPRESA/ENTE

2. Objectives
1. Support the decision maker in the monitoring
meteorological phenomena and evaluation of alerts:
of
– GNSS technology, based on a precise satellite positioning, able to
assess the content of water vapor present in the atmosphere;
– A system consisting of a widely distributed set of sensors to
estimate and locate rainfall in real time, able to define space-time,
high-resolution maps of the precipitation phenomena on a local
scale;
2. Offer a tool to the Civil Protection for a timely intervention on
the transport system in an emergency.

3. GNSS – Concept
GNSS positioning is affected by different physical effects,
one of these coming from low atmospheric layers
that delay the signals.
The study of such signal noise allows to obtain information on the
precipitable water content in atmosphere
Nowaday, meteorological predictive models integrates different
technologies: radar
→ very precise but short-term
satellite images → less precise but longer-term

4. GNSS – PWV

5. GNSS – Genoa 2001 flood (1/3)

6. GNSS – Genoa 2001 flood (2/3)

7. GNSS – Genoa 2001 flood (3/3)

8. Smart Rainfall System
Estimation and localization of rainfall in real-time
•
Technological innovation:
–
–
•
Main purpose:
–
•
Allow a timely evaluation of the onset of weather-hydrological alarm conditions due to intense
rainfall
Recipients:
–
•
Exploiting the propagation model of microwave signals to estimate the amount and distribution of
rainfall at river basin level
Deployment of a distributed system of measurement and localization of precipitation in realtime
Entities responsible for forecasting, monitoring and surveillance of the weather-hydrological risk for
civil protection
Results:
–
–
Reduction in the time required by the management and dissemination of alarms in the territory
Timely information for a controlled evacuation

9. Smart Rainfall System
Estimation and localization of rainfall in real-time
•
Functionalities:
–
–
•
Implemented with:
–
–
•
Sensors distributed in the areas to be monitored for the measurement of the precipitation
Central system for data integration, and the spatiotemporal identification of the event
Uses a TLC infrastructure available on the territory:
–
–
–
•
Real-time measurement of rainfall rate (in mm/h) for each acquisition sensor
Construction of a map of the space-time distribution of rainfall
Parabolic antennas for the reception of satellite DVB
Commercial satellite constellations
Internet access (3G, ADSL, FTTH)
Only requires the installation of the sensor downstream of the dish:
–
–
–
Condominium or private antennas
Based on components widely available on the market
Without any interference with the satellite TV service

10. Smart Rainfall System
Sensor Prototype
•
Implementation of the electromagnetic model:
–
•
Design and construction of a prototype of the electronic sensor:
–
–
–
•
Measure of the degradation of the satellite signal due to rain
Real time calculation of rainfall rate (in mm/h ) according to the algorithm
Communication with the central system
Simplified realization of the SW of the central system:
–
•
Algorithm for estimating precipitation according to interference with the satellite signal (dB of attenuation)
Application for collecting and displaying data
Technological innovation:
–
Exploiting the propagation model of microwave signals to estimate the amount and distribution of rainfall at river basin
level

11. Smart Rainfall System
Rain Estimation Approach
The output of the antenna (and consequently of
the sensor) is related to the rain rate R by the
following relationship:
•
𝑣 𝑡 = 𝑣0 𝑒 −𝑏𝑅
𝑡 𝑎𝑙
0° isotherm
𝑣0 is the baseline
𝑎 is a parameter depending on location of the RX antenna
𝑏 is a parameter depending on wave polarization
𝑙 is the part of the path connecting
𝜃
ℎ 𝑎𝑛𝑡
The path to the zero isotherm can be
computed from the knowledge of the
geographical positions of RX antenna
and satellite, i.e.:
•
𝑙=
•
Earth projection
ℎ0 −ℎ 𝑎𝑛𝑡
sin 𝜃
Finally the rain rate below the path to the
zero isotherm is obtained as:
𝑅 𝑡 =
𝑎
1
ln
𝑏𝑙
𝑣0
𝑣 𝑡
ℎ0
Earth path
where
rain rate is
estimated

12. Smart Rainfall System
Experimentation and Validation
20
•
Experimentation:
-15
10
-20
-25
Prototype validation:
–
•
Collecting sets of measures in the UNIGE
laboratories in various weather conditions
15
5
–
•
Signal Level (dBm) -10
Observed Rain (mm/30 min)
Through the comparison between the
measurements of the Smart Rainfall
System and those of a reference rain
gauge, under different atmospheric
conditions
Conclusions:
–
–
–
The Smart Rainfall System, operating in
real time, anticipates up to 30 mins the
results of the rain gauge
The measurements of the two instruments
are strongly correlated
The Smart Rainfall System even detects
light rain (tenths of mm/h)
0
4:00
5:00
6:00
7:00
8:00
9:00
-30
10:00 11:00 12:00
Morning of 3-Sep-2012
The peak of the rain gauge measure (red line) is of 9.6 mm/30 mins
5.0E-01
14
Observed Rain (mm/30 min)
12
10
4.0E-01
3.0E-01
8
6
2.0E-01
4
1.0E-01
2
0
4:00
5:00
6:00
7:00
8:00
0.0E+00
9:00 10:00 11:00 12:00
The integral of the estimation from the SRS is consistent with what
observed with the rain gauge

13. Smart Rainfall System
New Input for Models
•
Map of Precipitation:
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Geolocation of GNSS antennas using off-the-shelf instrumentation
Integration and correlation of real-time data from peripheral sensors
High-resolution (at the level of the river basin) maps of precipitation
 New input for the models needed to estimate risks for the environment
•
Traditional instruments, already used:
–
–
•
Measure and transmit the integral of the rain fallen in a temporal interval
Evaluate the precipitation on few locations (rain gauges), or over large areas (RADAR)
SRS:
–
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Allows the operator to take emergency decisions in less time than at present
Patentability of the Smart Rainfall System

14. Emergency Management
• Cartographic tools:
• Aerial image
• Technical cartography
• Openstreetmap
• Flood risk map:
• Decide the priority areas
• Different degrees of hazard
• Hazard in relation to the river discharge

15. Geo-web Service
Near real time data coming from different sensors and sources
Radar meteo
Idrometer
Meteo Model
DATA - ASSIMILATION
GPS
SRS

16. Mobility Use Case
The operator can choose an area to close
Geowebservice calculates in RT the roads to close
It is sent a message to some sensors
collocated at the beginning of each roads

17. The Main Functionality
VIRTUAL GATE
Timely interventions in case of emergency!

18. Conclusions
Proposal for a real time system:
A. Deploy a SRS sensor network on a pilot area:
 To monitor the rainfall distribution in real time;
B. Obtain the real time observed data from GNSS network
 To estimate the Precipitable Water Vapour pattern;
 Enter the results in the decision flow, which may draw a
new innovative tool for timely management of potentially
flood-prone areas.

19. Thank You
daniele.caviglia@unige.it
domenico.sguerso@unige.it
bianca.federici@unige.it
andrea.caridi@darts.it
tiziano.cosso@gter.it

20. LOGO IMPRESA/ENTE