Monitoring and analyzing natural disasters in Brazil
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1 Monitoring and analyzing natural disasters in Brazil Jose A. Marengo CEMADEN (Thanks to Osvaldo Moraes, Regina Alvala, Mario Mendiondo, Carlos de Angelis) Finding solutions for urban resilience to nature s challenges Brazilian Finnish Workshop Sao Paulo, SP November, 28 and
2 Natural disasters related to climate ( ) Sub-título 24pt Corpo 18pt FONTE: CRED-UNISDR 2015
3 Catalyst for Recent Disaster Risk Reduction Policies in Brazil Source: IBGE, 2010 Natural disaster of January 2011 in the mountains west of Rio: over 900 fatalities, 350 missing and thousands left homeless. A catalyst for DRR policies focused on prevention Creation of CEMADEN Urban Growth: change from rural to urban population Over 5 million people, mostly poor and vulnerable, living in areas of high disaster risk in Brazilian cities 3
4 Towards an interdisciplinary perspective Understanding: what different type of data need to be collected? How to engage citizens? Forecasting: How to include emerging data in forecasting models and systems? Alerting: how to issue warnings in face of uncertainties? How to communicate risks? 4
5 Natural Disasters and Population Governance & Policies for: Disaster Risk Reduction and Adaptation* Urban Water Management Climate Change, Agriculture and Water Planning and Scenarios Water State-of-the-Art in São Paulo State Urban Planning International Research Cooperation Source: IBGE, 2010 *Source: Brazilian Atlas of Natural Disasters
6 Natural Disasters in Brazil: over 95% of disasters are climate related Forest fires, Floods, Drought, Mass movements Droughts, Floods, Flash Floods Wildfires, Floods, Erosions Flash Floods, Wind Storms, Hails, Landslides Wildfires, Flash Floods, Floods, Droughts, Landslides, Debris Flows 6
7 Main Research Areas in Natural Disasters Natural Disasters Natural Disasters Modeling Hydrology Geology Meteorology Agrometeorology Forest Fires
8 Post-2011 Sendai DRR Policy in Brazil: A Paradigm Shift National Plan for Risk Management and Response to Disasters $ 8 billion over 4 years Relief and recovery Prevention Building structural resilience (slope, stabilization, drainage and flood control) Response Strengthening early warning networks (e.g., 4 thousand automated raingauges, 9 weather radars, 300 riverflow sensors, data integrations, modeling, hazard prediction, etc.) Monitoring and warning Mapping and understanding risk High resolution mapping of risk areas for 1000 municipalities
9 Fully Integrated System of DRR Disaster Risk Governance
10 ...Towards a National Strategy for Disaster Risk Management CEMADEN INMET, INPE, DECEA/MD & STATE CENTRES Hydrometeorology information MI, MCid e IBGE Disaster Risk & Vulnerability Analyses CPRM Geological Vulnerability Mapping ANA Hydrological information COMMUNITY Local feedback CENAD Alert & Logistics Monitoring and Early Warning MS, GSI, MT, Army Force CIVIL DEFENSE UNIVERSITIES & RESEARCH INSTITUTES Knowledge transfer, methods and hypothesis-testing, applied research databases on natural disasters (vulnerability, exposure, hazards, risks) Multidisciplinary Team: Geologists Geographers Engineers Hydrologists Meteorologists IT professionals Social scientists Contingency & Response Plans
11 Science, Technology and Innovation for a more resilient Society Operation (monitoring & alerts) Information Technology and Data Sharing Support IT infrastructure according to ISSO and Brazilian Law of Information Transparency Observational Sensor Network Multidisciplinarity Promotion of management mechanisms to integrate research, development to operational alert systems Mission: Promote advanced topics of Science, Technology and Innovation for disaster risk prevention through applied interdisciplinary research, using participatory public policies towards a more resilient society to disaster risks * Budget Growing observational sensor network, fully operational and online Planning Strategic planning according to international and national frameworks Applied Research & Development Innovation Innovation leadership for disaster risk reduction Capacity building and training towards innovation and leaps of knowledge Infrastructure & Engineering
12 CEMADEN Observational Sensor Network + 9 Radars Online Rainfall Stations + 286* Online Streamflow Stations All information and database are open & available for research & development through officially signing MoUs 10* Robotic Stations + 900* Motion Sensors + 135* Soil Moisture Stations Online Agrometeo. Platforms Online Stations Soil Moisture and Precipitation
13 Rede Observacional Ambiental do CEMADEN
14 Community raingauge" pilot project LOCAL ACTION: RAIN GAUGE AT LOCAL COMMUNITIES: A CITIZEN S NETWORK FOR EARLY WARNING >1000 raingauges installed in communities exposed to high disaster risk Enhancing risk perception and education for sustainability
15 Weekly and monthly technical reports on Disaster Risk Reduction in the Brazilian territory
16 Observational network and number of alerts in Sao Paulo
17 Observational network and number of alerts in Sao Paulo Petrópolis, Rio de Janeiro São Paulo, São Paulo Campos do Jordão, São Paulo Teresópolis, Rio de Janeiro Fonte: Cemaden Joinville, Santa Catarina Fonte: Cemaden Mauá, São Paulo Fonte: Cemaden Fonte: Cemaden Fonte: Cemaden Fonte: Cemaden
18 Building the risk scenarios 18
19 Issuing an Early Warning 19
20 Vazão (m³/s) Flood awareness using nowcasting and multi-source nowcasting (SHORT TERM FORECASTING): Modelagem Hidrológica Operacional com dados de radar meteorológico. Bacia Urbana de Nova Friburgo RJ (160 km²). Resolução espacial de 250 m x 250 m (mod. hidro. MHD-INPE) 1 km x 1km (radar met. Pico do Couto) Estação Conselheiro Paulino -INEA Science, Technology and Innovation for a more Society 16:00 17:00 18:00 19:00 20:00 Tempo (h) 21:00 22:00 ALERTA 0017 Cemaden PERIGO MHD - INPE
21 Early Warning Systems for Disaster Risk Reduction of Hydrologic Extremes on Vulnerable Communities Opportunities for Applied Research of SKILLED EARLY WARNINGS with MODELLING and COMMUNITY FEEDBACKS Traditional approach : Operational agent makes own alerts and assimilation Alert warning strongly based on recorded data, with few modelling Research not fully applied at operation crisis room Alert evaluation with methodological limits Vulnerability features not fully integrated into alerts Spatial scale limited to priority municipalities Interdisciplinary approach: Automatic alert/assimilation supervised by operators Alert warning based on both records and multisource, intensive nowcasting modelling Interdisciplinary research fully applied at operation room Alert evaluation replicable with local feedback (decentralization) Vulnerability features integrated at alert warning and evaluation Spatial scale extended to multi-risk - prone areas
22 Drought Risk Reduction in NE Brazil CEMADEN s Monitoring Network of Agrometeorological Risks in NE Brazil PCDAgro: ONLINE (GPRS) air temp., air humidity, precipitation, wind direction and velocity, solar radiation, net radiation flux, 4 soil depth: temp. & moisture PC D A qua : O N L I N E ( G PR S) precipitation & 2-level depth of soil moisture Courtesy: Dr M. Zeri & A. P. Cunha - CEMADEN
23 Making emergency policies for disaster mitigation in NE Brazil Financial benefits for people affected by the drought; Financial support for well drilling; Distribution of water for population; Etc; 23
24 Monitoring of drought Impacts by CEMADEN-Montlhy Bulletin
25 Sao Francisco River basin: Weekly monitoring and early warning for risks of flow running to hydropower stations
26 Sistema Cantareira: Weekly monitoring and early warning for water supply system under drought risk Precipitação (mm) Vazão diária (m 3 /s) /14/2015 P ETA 15x15 km P Observada Vazão Afluente e Precipitação Diárias para o Sistema Cantareira 14/julho/ /julho/2015 P Média P Eta15 (MHD) Q Membro 1 Q Membro 2 Q Membro 3 Q Membro 4 Q Membro 5 Q Membro 6 Q ETA 15x15 km Q Média Q Observada 7/15/2015 7/16/2015 7/17/2015 Eta15 (MHD) 7/18/2015 7/19/2015 7/20/2015 7/21/2015 7/22/2015 7/23/2015 7/24/2015 7/25/2015 7/26/2015 7/27/2015 7/28/2015 7/29/2015 Natural river flow (m 3 /s) abr/15 Q sim (since Apr., 2016) Q sim.(since Jan.,2016) Q sim. (since Oct.,2015) Q sim (since Jul.,2015) Q. sim. (since Apr., 2015) Pmensal/Pmédia Mensal Q obs mai/15 jun/15 jul/15 ago/15 set/15 out/15 nov/15 dez/15 jan/16 fev/16 mar/16 abr/16 mai/16 0% 100% 200% 300% 400% 500% 600% Observed Precipita on (rela ve to monthly average, %)
27 Sistema Cantareira: Weekley monitoring and early warning for water supply system under drought risk 27
28 Brazil Federal Disaster Risk Reduction Framework International cooperation in support of a post 2015 framework for disaster risk Governing Disaster Risk - Overcoming Challenges Public Investment in Disaster Risk Reduction Reducing Disaster Risk in Urban Settings Mobilizing Women s Leadership in Disaster Risk Reduction Risk sensitive Investments Public Private Partnerships Inclusive Disaster Risk Management Risk Identification and Assessment
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