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UNIVERSITÀ DEGLI STUDI DELLA BASILICATA
DICEM – salvatore.manfreda@unibas.it
Surface Hydrology and Flood Plains
Prof. Salv...
Flood	
  Exposure	
  at	
  the	
  Global	
  Scale	
  
Flood	
  Monitoring	
  
Are	
  Natural	
  Hazard	
  increasing?	
  
Number	
  of	
  Reported	
  Events	
  
Flood	
  Mapping	
  
Flood	
  Mapping:	
  LimitaCons	
  
Geomorphic	
  Approaches	
  
Geomorphic	
  Approaches	
  
Digital	
  ElevaCon	
  Models	
  
•  The	
  increasing	
  availability	
  of	
  digital	
  terrain	
  models	
  has	
  
gi...
Advantages	
  In	
  the	
  Use	
  of	
  UAVs	
  
•  Ability	
  to	
  monitor	
  the	
  river	
  morphology	
  over	
  a	
 ...
Basin	
  morphology	
  contains	
  an	
  extraordinary	
  amount	
  of	
  informaCon.	
  
	
  
	
  
Digital	
  Eleva+on	
 ...
Basin	
  Morphology	
  (Small	
  Scale)	
  
Lidar	
  DEM	
  with	
  2m	
  resoluCon	
  
Generally	
  in	
  hydrology	
  mo...
Downslope	
  Index	
  
	
  
Mod.	
  Topographic	
  Index	
  
ln[hl/H]	
  
[hr-­‐H]/tan(αd)	
  
	
  
ln[hr/H]	
  
	
  
[hr-...
15	
  
APPLICATION:	
  BRADANO	
  RIVER	
  	
  (ITALY)	
  	
  
(A)  Flood	
  map	
  derived	
  by	
  using	
  a	
  1-­‐D	
...
Measuring	
  soil	
  moisture	
  based	
  on	
  
surface	
  measurements	
  
InfiltraCon	
  	
   Soil	
  Water	
  Losses	
  
 Soil	
  Moisture	
  AnalyCcal	
  RelaConship	
  
(SMAR)	
  
(Manfreda	
  et	
  al.,	
  HESS	
  2014)	
  
SMAR	
  applicaCon	
  in	
  NIGER	
  
SMAR	
  applicaCon	
  in	
  NIGER	
  
Comparison	
  between	
  the	
  relaCve	
  saturaCon	
  at	
  5	
  cm	
  (s1)	
  and...
 
	
  
	
  
	
  
	
  
	
  
	
  
….Thanks	
  	
  
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Lecture by Prof. Salvatore Manfreda

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Potential Use of UAVs for Detection of Flood Prone Areas and Soil Moisture

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Lecture by Prof. Salvatore Manfreda

  1. 1. UNIVERSITÀ DEGLI STUDI DELLA BASILICATA DICEM – salvatore.manfreda@unibas.it Surface Hydrology and Flood Plains Prof. Salvatore MANFREDA APPLIED COURSE ON UAVs FOR ENVIRONMENTAL MONITORING University of Basilicata, Matera – 27-31 Luglio 2015
  2. 2. Flood  Exposure  at  the  Global  Scale  
  3. 3. Flood  Monitoring  
  4. 4. Are  Natural  Hazard  increasing?  
  5. 5. Number  of  Reported  Events  
  6. 6. Flood  Mapping  
  7. 7. Flood  Mapping:  LimitaCons  
  8. 8. Geomorphic  Approaches  
  9. 9. Geomorphic  Approaches  
  10. 10. Digital  ElevaCon  Models   •  The  increasing  availability  of  digital  terrain  models  has   given  a  strong  impulse  to  the  development  of  so  called   distributed  and  DEM-­‐based  models.   •  Digital  terrain  model  obtained  through  interferometric   data  gathered  by  the  space  shuIle  campaign  by  NASA   with  a  cellsize  of  90m.  (CGIAR-­‐CSI:   hIp://srtm.csi.cgiar.org/)   •  ASTER  GDEM  30m  available  from  June  2009  (hIp:// asterweb.jpl.nasa.gov/gdem.asp  )   •  AddiConal  informaCon  at  high  resoluCon  may  be   obtained  by  the  use  of  UAVs.    
  11. 11. Advantages  In  the  Use  of  UAVs   •  Ability  to  monitor  the  river  morphology  over  a   relaCvely  large  area  up  to  0.5km2;   •  Possibility  to  monitor  flood  extent  and  flow  velocity  at   the  surface;   •   Possibility  to  update  flood  risk  a]er  rapid  changes  of   the  river  morphology  (e.g.  in  riverbanks);   •  Possibility  to  monitor  the  temporary  deposits  of   floaCng  materials  and  flood  damages  over  an  area.  
  12. 12. Basin  morphology  contains  an  extraordinary  amount  of  informaCon.       Digital  Eleva+on  Models  (DEMs)  based  approaches     for  the  idenCficaCon  of  flood-­‐prone  areas  over  large  regions  or  for  a   preliminary  iden+fica+on  in  non-­‐studied  areas.       Basin  Morphology  (Large  Scale)   12  
  13. 13. Basin  Morphology  (Small  Scale)   Lidar  DEM  with  2m  resoluCon   Generally  in  hydrology  most  of  the  problems   related  to  flood  risk  are  related  to  small  basins   or  flat  region.  In  these  case,  we  need     •  Detailed  descripCon  of  the   DEM;   •  Need  to  monitor  changes  in   river  morphology;   •  Small  scale  surveys  may  help   in  understanding  erosional/ deposiConal  processes.  
  14. 14. Downslope  Index     Mod.  Topographic  Index   ln[hl/H]   [hr-­‐H]/tan(αd)     ln[hr/H]     [hr-­‐H]/D   Linear  binary  classifiers   Contribu+ng  area  [km2]   Slope  [-­‐]   Eleva+on  difference   to  the  nearest  channel  [m]   Curvature  [-­‐]   Distance  to  the  nearest   channel  [m]   DEM-­‐derived  morphologic  descriptors  of  the  Bradano  River  basin  (Basilicata,  Italy).   Single  features   Composite  indices  
  15. 15. 15   APPLICATION:  BRADANO  RIVER    (ITALY)     (A)  Flood  map  derived  by  using  a  1-­‐D  approach  over  the  enCre  basin  of  Bradano.     (B)  Flood  map  derived  by  using  a  2-­‐D  approach  at  the  outlet  of  Bradano  River  basin.   (A)   (B)   En+re  basin   Outlet  
  16. 16. Measuring  soil  moisture  based  on   surface  measurements   InfiltraCon     Soil  Water  Losses  
  17. 17.  Soil  Moisture  AnalyCcal  RelaConship   (SMAR)   (Manfreda  et  al.,  HESS  2014)  
  18. 18. SMAR  applicaCon  in  NIGER  
  19. 19. SMAR  applicaCon  in  NIGER   Comparison  between  the  relaCve  saturaCon  at  5  cm  (s1)  and  the  averaged  value  over   100,  130,  and  135  cm  depth,  and  the  filtered  value  (s2SMAR  –  black  line)  obtained  with   SMAR  for  two  sites  located  atWankama  (A)  and  Tondikiboro  (B),  respecCvely  
  20. 20.               ….Thanks    

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