1. Research area Córrego Dantes in 2011 and 2015
ITT SYMPOSIUM, SEPTEMBER 22nd 2016
Alicia Bustillos Ardaya, PhD Candidate, Bolivia
Disaster Risk Reduction: governance and perception in dynamic environments
Study case in the State of Rio de Janeiro, Brazil
Research Questions
(Cummulative paper)
1. What is needed for a proper risk governance structure in an actual dynamic context?
How are elements presented in frameworks, related to dynamic environments?
What are the enablers and constrainers of the main elements in risk governance processes in dynamic environments?
How are this elements valued and applied?
2. What is the relation between perception and preventive actions for disaster risk reduction?
What are the main factors related to risk perception for dwellers?
How do those elements change with local and institutional influences?
How do those elements influence preventive actions in a dynamic context like Nova Friburgo municipality?
3. How are the interactions between decision makers?
What kind of interactions are given between decision makers? (frequency and given spaces)
What are the main differences and commonalities between people living in risk areas and people working for risk areas? .…
Case Study Region and Problem Statement
In 2011, a series of flash floods and landslides claimed the lives of more than 1,000 people in seven cities of the mountainous region located in the middle of the State of Rio de Janeiro. Over 100,000 people were left homeless and key infrastructure was destroyed, it was qualified as the worse weather related natural disaster in the history of Brazil (Freire et al., 2011; World Bank, 2012). Increases in the frequency and severity of flood and landslide events together with the increase of affected people, make risk prevention a top priority in Rio de Janeiro increasing the investment on risk governance issues. Bureaucracy and corruption, Overlapping And missing activities and hierarchical misuse of authority and power are some of the main problems in risk governance. Projected climate change that will exacerbate water scarcity (IPCC, 2007), added to the vulnerability of growing populations are creating several socio-environmental conflicts.
Research area Córrego Dantes in 2011 and 2015
Risk Governance Frameworks
Research Area
Methods
Possible Affected People (PAP)
Questionnaires (n=391)
Semi structured interviews to institution actors and PAP
Interviews (n=25)
PAP in different neighborhoods
Focus Groups (n=10)
Institutions and PAP
Workshop (n=1 (+1 in ))
Participatory observation
Official reports and archives
Others
Focus Groups and Workshops
Flood Risk Perception (6 influence factors)
Flood Risk Perception
Demographic Information
Years living in the area, gender, age, working sector
Max Coef =0,29
Geographical Location
Distance to urban center, river, streets, schools…
Max Coef = 0,0075
Previous Experience
Experienced floods, landslides, evacuation, contention
Max Coef = 0,52
Knowledge on Eco DRR
Reforestation as a measure, green areas importance, infraestructure
Max Coef = 0,10
Local Influence
Knowledge by own experience, family and friends information
Max Coef = 0,62
Institutional Influence
Inea system alert, knowledge on existing risk maps, capacity building
Questionnaires
Location of the Neighborhoods
Rural areas
Peri-urban areas
Total
Official INEA risk areas SF
Sao fidelis BM
Barracao dos Mendes CC
Caompo do Coelho CD
Corrego Dantes RG
Rio Grandina TN
Terra Nova
Number of questionnaires 21 49 45
124 48
104
391
Gender (female %)
71,43
42,86
40,00
45,97
62,50
32,69
44,76
Average age in years (%)
49,86
38,82
28,98
47,05
54,65
34,09
41,57
Years living in the area (%)
24,38
18,84
11,82
27,08
34,92
6,18
19,55
Access to media (0-4 items)
3,33
2,71
1,84
3,25
3,13
2,12
Formal work (%)
57,14
87,76
68,89
65,32
50,00
38,46
59,08
Retired (%)
9,52
6,12
15,56
14,52
11,54
15,09
Unemployed (%)
33,33
20,16
22,92
25,83
Affected by inundations (%)
95,24
79,59
57,50
83,06
72,92
34,62
65,47
Affected by landslides or droughts (%)
2,80
36,73
31,11
89,19
14,40
82,59
28,39
Further Steps
1. Relate specific characteristics of the neighborhoods (Corrego D., R. Grandina, T. Nova, C. Coelho, B. Mendez and S.Fidéis) with risk governance. 2. Find interaction possibilities between decision makers (dwellers in different neighborhoods and institutions). 3. Characterize differences and cohesions between public power and society. 4. Find enablers and constrainers in risk governance for the specific case of Rio de Janeiro. 5. Look for success and failure cases according to the different regions. 6. …
First supervisor: Prof. Dr. Mariele Evers, Department of Geography, Bonn University,
Supervisor: Prof. Dr. Lars Ribbe, Institute for technology in the Tropics and Subtropics, TH Köln