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New technology for nowcasting and management of emergency in a city centre
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LOGO IMPRESA/ENTE
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
Objectives
1. Support the decision maker in the monitoring of meteorological phenomena and evaluation of alerts:
– 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.
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
GNSS – PWV
GNSS – Genoa 2001 flood (1/3)
GNSS – Genoa 2001 flood (2/3)
GNSS – Genoa 2001 flood (3/3)
Smart Rainfall System
Estimation and localization of rainfall in real-time
• Technological innovation: – 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 real-time
• Main purpose: – Allow a timely evaluation of the onset of weather-hydrological alarm conditions due to intense
rainfall
• Recipients: – 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
Smart Rainfall System
Estimation and localization of rainfall in real-time
• Functionalities: – Real-time measurement of rainfall rate (in mm/h) for each acquisition sensor
– Construction of a map of the space-time distribution of rainfall
• 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: – 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
Smart Rainfall System
Sensor Prototype
• Implementation of the electromagnetic model: – Algorithm for estimating precipitation according to interference with the satellite signal (dB of attenuation)
• 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: – 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
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 = 𝑣0𝑒−𝑏𝑅 𝑡 𝑎𝑙
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
The path to the zero isotherm can be
computed from the knowledge of the
geographical positions of RX antenna
and satellite, i.e.:
• 𝑙 =ℎ0−ℎ𝑎𝑛𝑡
sin 𝜃
Finally the rain rate below the path to the
zero isotherm is obtained as:
• 𝑅 𝑡 = 1
𝑏𝑙ln
𝑣0
𝑣 𝑡
𝑎
ℎ𝑎𝑛𝑡
ℎ0 𝜃
0° isotherm
Earth projection
Earth path
where
rain rate is
estimated
Smart Rainfall System
Experimentation and Validation
• Experimentation:
– Collecting sets of measures in the UNIGE laboratories in various weather conditions
• Prototype validation: – 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)
The integral of the estimation from the SRS is consistent with what
observed with the rain gauge
Morning of 3-Sep-2012
The peak of the rain gauge measure (red line) is of 9.6 mm/30 mins
-30
-25
-20
-15
-10
0
5
10
15
20
4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00
Observed Rain (mm/30 min) Signal Level (dBm)
0.0E+00
1.0E-01
2.0E-01
3.0E-01
4.0E-01
5.0E-01
0
2
4
6
8
10
12
14
4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00
Observed Rain (mm/30 min)
Smart Rainfall System
New Input for Models
• Map of Precipitation: – 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: – Allows the operator to take emergency decisions in less time than at present
– Patentability of the Smart Rainfall System
• 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
Emergency Management
Near real time data coming from different sensors and sources
DATA - ASSIMILATION
Radar meteo Idrometer Meteo Model SRS GPS
Geo-web Service
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
Mobility Use Case
The Main Functionality
VIRTUAL GATE
Timely interventions in case of emergency!
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.
Thank You
LOGO IMPRESA/ENTE
