Upstream  Satellite-­‐derived  Flow  Signals  for  River  Discharge  Predic;on  

Tom  Hopson1  F.  A.  Hirpa2;  T.  De  Groeve3;  G.  R.  

Brakenridge4;  M.  Gebremichael2;  P.  J.  Restrepo5  

1  

2Uconn;  3Joint  Res  Counc;  4U.  of  CO;  5Office  Hydro  Devel  

Outline  I.  Monitoring  river  flows  using  Satellite-­‐based  

Passive-­‐Microwave  data    II.  Case  study:  Bangladesh’s  vulnerability  to  

flooding  a)  Es;ma;ng  flood  wave  celerity  b)  River  discharge  es;ma;on  “nowcas;ng”  c)  Discharge  forecas;ng  

III.  Future  Work    

Data and data services to be discussed are available at the Flood Observatory http://floodobservatory.colorado.edu/

-­‐-­‐  Advanced  Microwave  Scanning  Radiometer  -­‐  Earth  Observing  System  (AMSR-­‐E)  &  NASA  TRMM  (Future:  Global    Precipita;on  Measurement  System)    -­‐ -­‐  U;lizing  36-­‐37Ghz  (unaffected  by  cloud)  -­‐ -­‐  pixel  size  ~20km  -­‐ -­‐  ~2day  complete  global  coverage  (night-­‐;me  brightness  temperatures)  -­‐ -­‐  data  range:  1997  to  present  

Objec&ve  Monitoring  of  River  Stage  and  Flow:  Satellite-­‐based  Passive  Microwave  Radiometer  

Other  Approaches:  satellite  al;meter-­‐derived  water  level  (and  discharge  derived  through  ra;ng  curve):  e.g.  Birkee,  1998;  Alsdorf  et  al.  2000;  Jung  et  al.  2010,  Papa  et  al.  2010,  Alsdorf  et  al.  2011,  Biancamaria  et  al.  2011    

One  day  of  data  collec;on  (high  la;tudes  revisited  most  frequently)  

=>  On  average,  global  coverage  1-­‐2  days  

       MODIS  sequence  of  2006  Winter  Flooding          2/24/2006  C/M:  1.004                          3/15/2006  C/M:  1.029                    3/22/2006  C/M:    1.095  

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Example:  Wabash  River,  Indiana,  USA  

Black  square  shows  measurement  pixel.  White  square  is  calibra;on  pixel.  

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Brakenridge,  et  al,  1998,  2005,  2007  

GDACS,  JRC    Gridded  Approach  

De  Groeve,  et  al,  2009,  2010  

=>  Use  “M/C”  ra;o    

s =MC=Tb,measurementTb,calibration

Hardinge  Bridge  gauge  (Ganges)  

Gauging  data  reference:  Hopson  2005;  Hopson  and  Webster  2010  

Bahadurabad  gauge  (Brahmaputra)  

Ganges  

Brahmaputra  

CorrelaUon  vs.  lag  Ume  and  distance  between  Gage  Q  &  satellite  signals  

Ganges   Brahmaputra  

Es;ma;ng  the  kinema;c  wave  celerity  

Assump;ons  (large):  hydraulic  parameters  homogenous;  rainfall  predominantly  upper-­‐catchment;  wave  speed  varia;on  with  depth  lower-­‐order;  dynamic  wave  effects  lower-­‐order  (confirmed  through  ra;ng  curve  analysis  –  not  shown),  etc.    Independent  analysis:  Kleitz-­‐Seddon  Law  for  kinema;c  wave  celerity  c:    W  channel  top-­‐width,  Q  discharge,  y  the  river  stage.  Brahmaputra  at  Bahadurabad:  4m/s  <  c  <  8m/s;  Ganges  at  Hardinge  Bridge:  2m/s  <  c  <  6m/s.    

c = 1W

dQdy

Genera;on  of  Nowcasts  and  Forecasts  

Regressor  and  model  selec;on  procedure:    i)  Correlate  all  variables  with  gauged  observa;ons  

ii)  Sort  in  decreasing  level  

iii)  Select  using  step-­‐wise  forward-­‐selec;on  using  K-­‐fold  cross-­‐valida;on  and  RMSE  cost  func;on  

iv)  Repeat  ii)  –  iii)  for  all  lead-­‐;mes  

Discharge  es;ma;on  “Nowcas;ng”  

Ganges  2003   Brahmaputra  2007  

1-­‐,  5-­‐,  15-­‐day  Forecasts  

Skill  Scores  

Nash-­‐Sutcliffe  efficiency  (frac;on  of  variance  explained):    -­‐-­‐  80%  (1-­‐day)  to  55%  (15-­‐day)  

   explained  

Now,  generate  a  forecast  including  “persistence”:      -­‐-­‐  satellite  informa;on  improves  forecasts  by  10-­‐20%  at  all  lead-­‐;mes  

SS =Aforc − ArefAperf − Aref

Future  Work  Blend  with  ECMWF-­‐derived  forecasts  

(Hopson  and  Webster  2010;  Opera&onal  in  2003)    

2007  Brahmaputra  Ensemble  Forecasts  and  Danger  Level  Probabili;es  

7-10 day Ensemble Forecasts 7-10 day Danger Levels

7  day   8  day  

9  day   10  day  

7  day   8  day  

9  day   10  day  

Summary  

§   Satellite-­‐based  passive  microwave  imagery  useful  tool  for  monitoring  river  condi;ons  for  limited-­‐gauged  basins    §   Useful  for  es;ma;ng:  

-­‐-­‐  flood  wave  celerity  -­‐-­‐  discharge  es;mates  (nowcasts)  including  filling  in  missing  data  

§   Combined  with  other  methodologies,  a  poten;ally  useful  tool  for  flood  forecas;ng  of  large  river  basins  

 

   Further  ques;ons:  hopson@ucar.edu