GEO Intelligence - Brasil. Gestão de Riscos de Desastres com Grupos Interdisciplinares de Monitoramento e Alerta

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1 GEO Intelligence - Brasil Gestão de Riscos de Desastres com Grupos Interdisciplinares de Monitoramento e Alerta Prof. Dr. Eduardo Mario Mendiondo CEMADEN - MCTI Centro Nacional de Monitoramento e Alerta de Desastres Naturais Ministerio de Ciência, Tecnologia e Inovação

2 Early Warning Systems for Flood Risk Management at Local Scales: Regarding Vulnerability, Impacts and Adaptation Strategies Motivation topics and main messages Forecast skills for extremes at challenging biomes NationalStrategy for DisasterRiskManagement FloodUncertaintyawarenessand management Rainfall-forecastvsradar-basedforecast Friendly flood forecasting at local scale Participatory flood forecasting a step forward

3 Forecast skills for extremes at challenging biomes Uncertainty of flood forecasts Special focus in semi-arid regions (intermitency), or in urban regions (disturbed systems, or ungauged basins (i.e. Amazon) Amazonas River at Obidos Station m3/s m3/s Source: Clarke, Mendiondo&Brusa(2000) J Tomasella (pers. comm.)

4 Municipalityof Óbidos-PA (onjune 30, 2014) O nível do rio Negro em Manaus-AM ficou abaixo da máxima histórica (29,97 m) ocorrida em 29/05/2012: a cota máxima registrada foi de 29,47 m no dia 30/06/2014. Segundo a ANA, é a 5a maior cheia já registrada desde o ano Cota (cm ) jan fev mar abr mai jun jul ago set out nov Mínimos históricos Transbordamento Máximos históricos dez O rio Amazonas em Óbidos atingiu níveis próximos aos máximos absolutos registrados (ANA): A cotamáxima registrada foi 8,40 m no dia 30/05/ affectedfamilies, living atfloodplains, 150 familieswereremovedsour ce: CENAD, 30/06/2014). FloodriskareasatleftmarginofAmazon River, atobidosmunicipality-pa (source: CPRM, 2012).

5 Vulnerability and impacts related to hydrohazards in Brazil Evolution of Natural Disasters in Brazil Anhembi, São Paulo Occupation of floodplains Occupation of the slopes E Macedo - IPT

6 DebrisFlow s Distribution of natural disasters in Brazil Source: BrazilianMinistryof Planning, 2014 Floods, flashfloods&flo odings Mudflows& Landslides

7 AdaptationMechanismsthroughtheNationalStrategy for DisasterRisk Management CEMADEN INMET, INPE, DECEA/MD & STATE CENTRES Hydrometeorologyinformati on MI, MCide IBGE DisasterRisk& VulnerabilityAnalyses CPRM GeologicalVulnerabil itymapping ANA Hydrological information COMMUNITY Local feedback CENAD Alert&Logistics MonitoringandEar lywarning MS, GSI, MT, Army Force CIVIL DEFENSE UNIVERSITIES & RESEARCH INSTITUTES Knowledgetransfer, methodsandhypothesis-testing, appliedresearchdatabaseson natural disasters (vulnerability, exposure, hazards, risks) Multidisciplinary Team: Geologists Geographers Engineers Hydrologists Meteorologists Biologists Social scientists IT professionals Started in December, h, 365-day a yearmonitoring Early warning reports on landslides, mudslides, floods, floodings, flashfloods and severe drought impacts 753 municipalities monitored Contingency& Response Plans

8 CEMADEN HISTORICAL OVERVIEW and24-h MONITORING Aug Fullyoperational: 753municipalitiesmonitored Mar Fullyoperational: 593municipalitiesmonitored Feb Fully operational: 286 municipalities monitored May 2012 Fully operational: 153 municipalities monitored Dec Fully operational: 56 municipalities monitored Legal framework: PresidentialDecreetNº 7.513, 1st July Established CEMADEN and defines its role andmission

9 Research lines in CEMADEN Hydrology Flood risks mapping Determination of rainfall thresholds for the occurrence of the flashfloods Hydrologic forecasts using distributed hydrological models Probabilistic forecasts using hydrological models Meteorology Improved estimation of rainfall (QPE) based on radar information Improvements in the parameterization of mesoscaleatmospheric models Application of agro-meteorological models to detect crop failure in the brazilian semiarid

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11 Bacia do rio Itajaí-Açu Precipitação acumulada no período de 26 a 30de junho de 2014 (09:00h de Brasília) nas Estações do CEMADEN 96h

12 HydrologicalEarlywarning system: conceptual design Ensemble weather forecasts Lead times greater than 24 hs Porbability Forecasts Atenção Hydrological models Observação Early Warning Very High Real-line Rainfall and hydrological data, radar. Lead times up to 6 hs High Moderate Stand by Courtesy: Dr. J. Tomasella

13 Courtesy: Dr. J. Tomasella

14 Rainfall-forecastvsradar-basedforecast Blinding forecast (without radar inputs) ETA is based upon 40 x 40 Km grid (South America wide) MODELO X ETA: 06/02/ /01/ /11/2005 Precipitação [mm] [mm] :00 20:00 17:00 17:00 21:00 18:00 18:00 19:00 19:00 22:0020:00 20:0021:00 23:0021:00 22:00

15 Rainfall-forecastvsradar-basedforecast Forecasted precipitation compared with observed precipitation

16 Scalingtechniques Pros and cons of hydrometeorological forecasts * Storm with a high forecast predictability Figura C.1. Evento 3 (15/02/2006). (a) Imagem de refletividade do radar de Bauru no CAPPI de 3,5 km; (b) Imagem do satélite GOES no canal infravermelho termal. *Source: Gonçalves (2009)

17 Precipitation forecasts related to time-autocorrelation capacity but autocorrelation of inputs, outputs or composite (cross-correlation) approach? Storm with a high forecast predictability *Fuente: Gonçalves (2009) Autocorrelograma temporal para refletividades de radar en CAPPIs de 1,5 km (CAPPI 1,5) y 3,5 km (CAPPI 3,5), VIL, tope de ecos, e intensidad de precipitacion registrada en la estacion PCD01 (PCD01). Evento 3 (15/02/2006).

18 Direct (ground-gauged) precipitation Vs indirect (radar-based) precipitation Figura D.2. Intensidade de chuva (i) obtida pela estação PCD01 (PCD01) e a partir da conversão da refletividade de radar, para os CAPPIs de 1,5 km (CAPPI 1,5) e 3,5 km (CAPPI 3,5). Evento 1 (19/01/2006).

19 Friendly flood forecasting for communities 13:47 13:47 13:47 13:47 Inundação Muito Alta - Desastre 23º 23º 23º 23º Inundação Alta - Risco Inundação Média - Ameaça/Vulnerabilidade Ação Sem Baixa Inundação - Perigo : Baixo Perigo Source: Mendiondo (2003), Ribeiro & Mendiondo (2007)

20 Friendly flood forecasting for communities Community perception of flood risk management in urban catchments of Sao Carlos City, SP, Brazil (web-mapping / Participatory webgis) flo o days from Giuntoli & Mendiondo (2008)

21 PROJETO PLUVIÔMETROS SEMIAUTOMATICOS Participatory flood forecasting a step forward

22 LOCAL ACTION: RAINGAUGE AT LOCAL COMMUNITIES MainGoal: Promotionofpreparednessanddisasterrisk management perceptionat local scale, empowering local communitiesandmakingcapacitybuildingto cope withrisks. How? More than 1100 semiautomaticraingaugestobeoperatedby local community. Who? Officialpartnershipbetween SEDEC/MI and CEMADEN/MCTI.

23 PLUVIÔMETROS INSTALADOS NAS REGIÕES SUL E SUDESTE Petrópolis, Rio de Janeiro Campos do Jordão, São Paulo São Paulo, São Paulo Fonte: Cemaden Teresópolis, Rio de Janeiro Mauá, São Paulo Joinville, Santa Catarina Fonte: Cemaden Fonte: Cemaden Fonte: Cemaden Fonte: Cemaden Fonte: Cemaden

24 Participatory monitoring: Flood Citizen Observatory

25 Sistema de Monitoramento Experimental WSN (Wireless Sensor Network) e Sistema de Previsão Antecipada de Enchentes Urbanas Sinalizacao nos locais de monitoramento experimental Figura 2 Bacia de estudo e pontos de monitoramento.

26 Source: Fava, M. C., G. S. Santana, D. A. Bressiani, A. Rosa, F. Horita, V. C. Souza, E. M. Mendiondo(2014) Integration of Information Technology Systems for Flood Forecasting With Hybrid Data Sources, In: Int. Conf. Flood Mgmt, Sao Paulo, Acquacon/ABRH, Proceedings Paper - PAP Prevenção e Monitoramento do Risco de Inundações em Bacias Urbanas Adaptado para escoamento em canais Sinalizacao nos locais de monitoramento experimental Adaptado para escoamento em sarjetas

27 Source: Fava, M. C., G. S. Santana, D. A. Bressiani, A. Rosa, F. Horita, V. C. Souza, E. M. Mendiondo (2014) Integration of Information Technology Systems for Flood Forecasting With Hybrid Data Sources, In: Int. Conf. Flood Mgmt, Sao Paulo, Acquacon/ABRH, Proceedings Paper - PAP Sistema de monitoramento fluviométrico em tempo real com sinalização para prevenção de riscos de inundações urbanas USP-1, Sao Carlos Sensor de pressao Rede WSN (online) Régua para observador voluntário (VGI) Sinalizador para Alerta e Preven;cao (Defesa Civil e Bombeiros) FINEP/MAPLU: Parceria UFAL-EESC/USP Executado: 95%

28 Waiting for the Next Flood ManyThanks! Eduardo Mario Mendiondo