Megan Konar's Talk on Water and Food

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Megan gave a fascinating talk showcasing her work on network analysis of virtual water trade. We discussed water and food security in the context of population growth, economic development and climate change.

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Megan Konar's Talk on Water and Food

  1. 1.  Network  Analysis  of  Virtual  Water  Trade   Megan  Konar       Civil  &  Environmental  Engineering   Princeton  University    
  2. 2. Global  DistribuKon  of  Water  on  Earth   From  space,  Earth   is  a  “Blue  Planet”  
  3. 3. Global  DistribuKon  of  Water  on  Earth   SURFACE   WATER   0.34%   UNDERGROUND   30%   FRESH  WATER   3%   FROZEN   70%   OCEANS  97%   Water  available  for   plant  use  is  less  than   0.34%  of  all  fresh  water  
  4. 4. Water  for  Food  Water  and  food  security  are  inextricably  linked.    Water  and  food  systems  face  increasing  pressures  from  global  populaKon  growth,  economic  development,  and  climate  change.    How   are   water   and   food   systems   linked   through  internaKonal  trade?  
  5. 5. Sources  of  Water  The  vast  majority  (80%)  of  irrigaKon  (i.e.  “blue”)  water  resources  goes  to  agriculture.    Most  food  (60-­‐70%)  is  actually  rainfed,  or  produced  using  “green”  water  resources.   Green  Water  Blue  Water  
  6. 6. ProducKon  Chain   0.16 0.47 Cotton seed oil 1.07 1.00 Cotton seed oil, refinedCo`on   Cotton seed Hulling/ extraction 0.51 0.33 Cotton seed cake 0.63 0.18 0.10 0.20 Cotton linters HarvestingCotton plant Seed-cotton Ginning 0.05 0.35 0.10 Garnetted stock 0.82 1.00 Cotton, not Carding/ Cotton lint 1.00 carded or combed Spinning 0.95 Cotton, carded or 0.99 combed (yarn) Knitting/ weaving 0.95 0.05 0.99 0.10 Grey fabric Yarn waste Wet processing 1.00 1.00 Fabric Legend Finishing 0 .35 Product fraction 1.00 1.00 0 .82 Value fraction Final textile Hoekstra,  2009  
  7. 7. Hoekstra,  2009  
  8. 8. Crop  Water  Use  Varies   In  Both  Space  and  Time   Virtual  Water  Content  [-­‐]             Hanasaki,  2010  H08  Global  Hydrologic  Model    ½₀  x  ½₀  SpaKal  ResoluKon    
  9. 9. Water,  Food,  and  Trade  The   water   embodied   in   the   internaKonal   food   trade   is  referred  to  as  “virtual  water  trade”.      Virtual   water   trade   is   driven   by   underlying   economic  system  and  climaKc  factors.  
  10. 10. Water,  Food,  and  Trade  The   water   embodied   in   the   internaKonal   food   trade   is  referred  to  as  “virtual  water  trade”.      Virtual   water   trade   is   driven   by   underlying   economic  system  and  climaKc  factors.    This  complex  system  can  be  represented  as  a  network.   NODES:   Countries   parKcipaKng   in  internaKonal  food  trade.     LINKS:   Weighted   by   water       volumes,  directed  by  trade.    
  11. 11. What  is  a  network?   …Quick  Intro  
  12. 12. Unweighted  &  Undirected   Weighted  &  Undirected   Node   Link   Unweighted  &  Directed        Weighted  &  Directed   4   4   1   1   8   2   2   6   3  
  13. 13. Network  ProperKes   Undirected Directed Degree k out = 0 k in = 1 k =2 Strength 4 1 s out = 3 2 s in = 10 6 s =7
  14. 14. Network  ProperKes   Unweighted Weighted Nearest Neighbor Clustering
  15. 15. Virtual  Water  Trade  Network  
  16. 16. Regional  Networks        Crops  and  Livestock                          Crops                                                Livestock                                                              All  Water            Green  Water                                                        Blue    Water                                    
  17. 17. Regional  Networks        Crops  and  Livestock                          Crops                                                Livestock                                                              All  Water            Green  Water                                                        Blue    Water                                    
  18. 18. Regional  Networks        Crops  and  Livestock                          Crops                                                Livestock                                                              All  Water           EnKre  network  is      Green   driven  by  the  trade    Water   of  rain-­‐fed  crops                                                        Blue    Water                                    
  19. 19. Network  ProperKes  Node  Degree                             k out = 0 k in = 1 ExponenKal  export  degree   distribuKon   Node  Strength                       Data   4 1 Fit   s out = 3 2 s in = 10 6 Stretched-­‐exponenKal   strength  distribuKon  
  20. 20. Power  Law  RelaKonship  Volume  of  virtual  water  traded  vs.  number  of  trade  partners  follows  a  power  law  relaKonship   Data   Fit  This  relaKonship  is  parKcularly  strong  for  food  import,  indicaKng  that  the  more  import  trade  partners  a  country  has,  the  much  more  virtual  water  it  imports.  
  21. 21. Evidence  of  Rich  Club  Nearest-­‐Neighbor  Degree          Clustering  Coefficient     Unweighted   Unweighted   Weighted   Weighted   Weights  break  down  disassortaKve  structure  
  22. 22. Network  Dynamics  Over  Time  1986   2007   %  Change  from  1986   Green  Water   Blue  Water  Volume  of  virtual  water  embodied  in  trade  has  more  than  doubled  from  1986-­‐2007,  parKcularly  for  green  water.   Dalin  et  al,  2012;  Konar  et  al,  In  Review  
  23. 23. Global  Water  Savings  from  Trade   Savings  =  238  km3  yr-­‐1   Equivalent  to  9%  of  global     agricultural  water  use   Dalin  et  al,  2012  
  24. 24. Blue  and  Green  Networks  Save  Water   .   Pos.    Links  [%]   .   Blue  Water   Green  Water  Global  Water  Savings  [m3]      <VWC  Gap>   Crop  Trade  [%]   What  is  driving  this  increased  water  saving  over  Kme?  
  25. 25. IntensificaKon  of  Trade  on     Water-­‐Efficient  Links   .   .   Blue  Water   Green  Water  
  26. 26.  Thank  You       QuesKons?    

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