Exploring the role of new technologies in quantifying precipitation levels and urban flooding
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1 Exploring the role of new technologies in quantifying precipitation levels and urban flooding Jörg Rieckermann Urban Water Management Eawag, Swiss Federal Institute of Aquatic Science and Technology
2 Motivation «The Geysir of Hamburg» Hamburgwasser
3 Urban flooding «The Geysir of Hamburg»
4
5
6 Hazard potential Exploring the role of new technologies Rainfall monitoring Flood risk assessment in urban areas Vulnerability potential
7 Precipitation monitoring Problem Rainfall is highly variable in space and time Existing monitoring networks only provide limited data
8 benmeadows.com Precipitation monitoring various possibilities Rain gauge Ground rainfall Point measurement
9 COMET program benmeadows.com, COMET program Precipitation monitoring various possibilities Rain gauges Ground rainfall Point measurement Weather radar and satellite Spatial information Volume measurement Limited resolution
10 Satellite GPM (Global Precipitation Monitoring) Follow-up of TRMM Start deg inclination 5x5 km2 3 hourly data NASA, JAXA, CNES, ISRO, NOAA, EUMETSAT
11 Satellite GPM (Global Precipitation Monitoring) Follow-up of TRMM Start deg inclination 5x5 km2 3 hourly data NASA, JAXA, CNES, ISRO, NOAA, EUMETSAT Core observatory Precipitation radar (DPR) Passive radiometers Improvements Dual frequency precip. radar light rain, snow and hail
12 Jensen (2011) Installation and application of a country-wide nework of LAWR X-Band radars in El Salvador Local Area Weather Radar (LAWR) Ship radar Specs X-band, S-band km 5 min resolution Cheap, low data quality
13 Jensen (2011) Installation and application of a country-wide nework of LAWR X-Band radars in El Salvador Local Area Weather Radar (LAWR) Ship radar Specs X-band, S-band km 5 min resolution Cheap, low data quality Local operators Urban drainage operators Research
14 Nielsen (2011) GLUE based uncertainty estimation of urban drainage modeling using weather radar precipitation estimates Local Area Weather Radar (LAWR) Ship radar Specs X-band, S-band km 5 min resolution Cheap, low data quality Local operators Urban drainage operators Research
15 Nielsen (2011) GLUE based uncertainty estimation of urban drainage modeling using weather radar precipitation estimates Local Area Weather Radar (LAWR) Ship radar Specs X-band, S-band km 5 min resolution Cheap, low data quality Local operators Urban drainage operators Research
16 Local Area Weather Radar (LAWR) Ship radar Specs X-band, S-band km 5 min resolution Cheap, low data quality Local operators Urban drainage operators Research El Salvador NWS 3 LAWRs, 6 months, $0.45 Mio Jensen (2011)
17 Local Area Weather Radar (LAWR) Ship radar
18 COMET program benmeadows.com, COMET program Precipitation monitoring various possibilities Rain gauge Ground rainfall Point measurement Weather radar and satellite Spatial information Volume measurement Limited resolution
19 ott.com, thiesclima.com benmeadows.com, COMET program Precipitation monitoring various possibilities Rain gauge Ground rainfall Point measurement Weather radar and satellite Spatial information Volume measurement Limited resolution Disdrometer Rain, snow, Point measurement
20 benmeadows.com, COMET program Precipitation monitoring various possibilities Rain gauge Ground rainfall Point measurement Weather radar and satellite Spatial information Volume measurement Limited resolution Disdrometer
21 Microwave links from telecommunication networks Use existing infrastructure for precipitation monitoring!
22 Microwave links from telecommunication networks Use existing infrastructure for precipitation monitoring!
23 Electromagnetic wave propagation Raindrops attenuate the transmitted signal from microwave links (MWL) Rain drop
24 Electromagnetic wave propagation Raindrops attenuate the transmitted signal from microwave links (MWL) Rain drop Hydrometeor scattering and adsorption: Empirical model: A a A b R 0 Q t D N D dd R k
25 Case study Zurich Collaboration with ORANGE and Zurich sewer operator (ERZ)
26 Case study Zurich Data Pre-processing 1. Baseline separation 2. Calculation of rain rate from differential attenuation
27 ce [mm] cer [-] Results (1) Accuracy, comparing MWL to Rain gauge over time Absolute error Relative error Jan Mai Jul Sep Nov Jan Mai Jul Sep Nov Jan
28 Rainfall MWL [mm] R fitted [mm] Results (2) Accuracy, comparing MWL to Rain gauge and Radar gauge radar R measured [mm] Rainfall measured [mm]
29 Microwave links from telecommunication networks Spatial distribution, Meteoswiss A-Netz vs. ORANGE Network Donnerstag, 25. Juni
30 Microwave links from telecommunication networks Spatial distribution, Israel Zinevich et al. (2008) Estimation of rainfall fields using commercial microwave communication networks of variable density Donnerstag, 25. Juni
31 Microwave links from telecommunication networks Discussion PRO Existing infrastructure Spatial distribution of MWL, dense network in urban areas Near-surface precipitation To do Wet antenna attenuation Comprehensive uncertainty assessment Detection of snow, sleet, hail CON Telecom operators: General data availability (no business case) Antenna manufacturers: hardware, data logging Long-term historical data, mobile internet Donnerstag, 25. Juni
32 Hazard potential Exploring the role of new technologies Rainfall monitoring Flood risk assessment in urban areas Vulnerability potential
33 Flood risk assessment Example, state-of-the-art
34 Flood risk assessment Requirements Numerical simulation model Complex: Hydrodynamic, 1D/2D Schmid, T. et al. (2009)
35 Flood risk assessment Requirements Numerical simulation model Complex: Hydrodynamic, 1D/2D (too) Simple: GIS Schmid, T. et al. (2009) Hamburgwasser
36 Flood risk assessment Requirements Numerical simulation model Complex: Hydrodynamic, 1D/2D (too) Simple: GIS Digital elevation model LIDAR (laserscanning, ~cm) SAR (radar, ~dm) TanDEM-X (~2m rel)
37 MOEKAH AG, Henggart, 1997 Flood risk assessment Requirements Numerical simulation model Complex: Hydrodynamic, 1D/2D (too) Simple: GIS Digital elevation model LIDAR (laserscanning, ~cm) SAR (radar, ~dm) TanDEM-X (~2m rel) Urban drainage system «Black hole» No remote sensing technology Discharge data for model calibration
38 Urban flooding «The Geysir of Hamburg»
39 Discussion/Conclusions Exploring the role of new technologies Precipitation monitoring in SEE Automated weather stations are mandatory MWL could complement observations Existing infrastructure, spatial distribution, Satellite and LAWR not recommended (for urban hydrology) Flood risk assessment in urban areas Simulation models are available Good terrain data are mandatory (Digital) Information on urban drainage network insufficient Climate change? «Stationarity is dead!»
40 Discussion/Conclusions Exploring the role of new technologies Precipitation monitoring in SEE Automated weather stations are mandatory MWL could complement observations Existing infrastructure, spatial distribution, Satellite and LAWR not recommended (for urban hydrology) Flood risk assessment in urban areas Simulation models are available Good terrain data are mandatory (Digital) Information on urban drainage network insufficient Climate change? Milly et al. Stationarity Is Dead: Whither Water Management?, Science 1 February 2008: Vol. 319 no pp DOI: /science «Stationarity is dead!»
41 Thank you! Hamburgwasser
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