why know 4-drr conference final 19 5

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Why KNOW4DRR? Necessity and usefulness of knowledge on DRR. CEPREDENAC, México, April 2015, P. Pigeon. Knowledge limitaLons. André, C (2013), PhD ContestaLon of knowledge on DRR La Faute sur Mer 2007 RPP, and local opposiLon to DRR policy. Which knowledge for whom?

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Why  KNOW-­‐4-­‐DRR?  

Necessity  and  usefulness  of  knowledge  on  DRR.  CEPREDENAC,  México,  April  2015,  P.  Pigeon.  

Knowledge  limitaLons.  André,  C  (2013),  PhD  

ContestaLon  of  knowledge  on  DRR  

La  Faute  sur  Mer  2007  RPP,  and  local  opposiLon  to  DRR  policy.  Which  knowledge  for  whom?  

Structure  

1.  The  context  :  the  more  we  know,  the  more  we  lose….  2.  DRR  policies  necessary,  yet  limited.  3.  IdenLfying  limitaLons  :  a  quesLon  of  informaLon  and  knowledge  for  assessing  DRR…  4.  But  not  only  a  quesLon  of  informaLon  and  knowledge  as  such….  THE  challenges….  

1.  The more we know, the more we lose? Assessments on disaster frequencies and losses look paradoxical (White et al. 2001): « the more we know, the more we lose…. »

Papers on resilience in peer-review journals. (Kuhlicke, 2011)

A. The more we know

B. The more we lose???

Yet, C….

How to reduce losses even more?

People killed and economic losses, Colombia, GAR 2015.

Poorly  prevenLon  oriented   More  prevenLon  oriented  

DRR  policies  more  prevenLon  oriented…yet  sLll  with  peak  losses  (as  with  Xynthia  related  disasters…).  Where  do  we  find  the  most  disaster  prone  areas?    

2.  DRR  policies  necessary,  yet  limited.….  

Chautagne  RPP,  2004  

La  Faute-­‐sur-­‐Mer  RPP,  2007  

5 WCDRR  3  -­‐  Sendai  -­‐  17  March  2015  -­‐  Side  event  on  Risk  Data  Sharing  Platforms  

3. Identifying DRR policies limitations : a question of information and knowledge for assessing DRR. ONRN « develops national risk assessment »

•  Provided   by   ONRN   iniLal  

partners   (now   amounLng  

to  100)  

•  Limited  to:  

ü  Flood  hazard,  

ü  Exposed  assets,  ü  Loss  records,  ü  Progress   of   one   DRR  

procedure  (PPRNI)  

at   munic ipal i ty   gr id ,  

naLonwide  (metropolitan)  

 

Downloadable indicators and data (www.onrn.fr) eg. Map  of  cumulated  flood  losses    per  municipality  (from  1995  to  2010)  

NaLonal  and  regional  observatories  draw  a`enLon  on  the  need  to  focus  on  the  municipal  scale  

From  2  to  5  M  Euros  

From  5  to  276  M  Euros  

6 WCDRR  3  -­‐  Sendai  -­‐  17  March  2015  -­‐  Side  event  on  Risk  Data  Sharing  Platforms  

ONRN « refines risk management planning » at regional and municipal scales.

Screenshots of interactive maps from www.onrn.fr allowing to compare exposure/loss records and evolution of public prevention policy

Yet  :  sLll  local  opposiLons  to  naLonal  DRR  policies…  Need  to  address  local  scales  more  in  details  and  to  share  knowledges  with  local  stakeholders.    

Over  5  million  euros  losses   Approved  (enforced)  PPR  

Cumulated insured losses due to floods period 1995 – 2010, at municipality grid

Status of public preventive actions, as of end 2013: municipal flood risk prevention plans (PPRI)

4.  Iden?fying  limita?ons  :  not  a  ques?on  of  informa?on  and  even  not  of  knowledge  only….  

Percentage  of  insured  goods  damaged    during  the  Rhone  river  2003  floods  in  Arles.  

Domenichini,  J.  2008.  PhD,  p.  70.  

Losses  intensiLes  

Level  of  water  

AND  level  of  water  does  not  explain  losses  experienced  only,  according  to  experience  returns  and  insurance  data  (plurifactoriality…..).    How  to  share  that?  

Yet,  we  find  building  prescripLon  discrepancies…  

Insights  

•  How  to  reduce  more  informaLon  fragmentaLon  on  DRR  between  insLtuLons  and  stakeholders?    

•  How  prevenLng  more  disasters  with  local  stakeholders?  

•  “Increasing  the  quality  and  coverage  of  data  is  seen  as  central  to  operaLonalising  DRR  policies,  but  success  does  not,  however,  hinge  simply  on  the  provision  of  more  accurate  and  comprehensive  data”    

(White,  I  et  alii,  2011,  p.  14).