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ARTICLE
International Journal of Water Sciences

Assessment of Spring Chinook Salmon
Habitat Suitability in the San Joaqui...
The  river  is  crucial  for  the  propagation  and  survivability  
of   Chinook   salmon   and   other   aquatic   speci...
37.4

FFB
Reach 5

37.3

J2
Alt1/2/3
Alt1

Reach 4B2

Eastside Bypass

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N

Alt2/3

J1

EBM
Mariposa Bypass

Latitude,
...
Station  Description  

Station  ID  

Station  Location,  
NAD83  
36.9949,  -­‐‑120.501  
37.1114,  -­‐‑120.591  

Reach...
 
Element  #  
Node  #  

Alternative  1  
2483  
9568  

Alternative  2  
1841  
7056  

Reaches  included  
(Figures  1 ...
hydrodynamic   conditions   affecting   salmon   migration   in  
the   SJR.   The   discharge   data   were   used   for ...
Upstream condition: Discharge at SDP

Discharge (cfs)

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(a)

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SJR Discharge at SWA

Discharge (cfs)

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observed
modeling

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...
quantified   using   the   habitat   Suitability   Index   (SI)   [27].  
Figures   6a   and   6b   were   developed   by ...
The   representative   values   of   velocity   and   depth   for   each  
element  were  the  values  at  its  centre,  w...
Eastside Bypass
SWA

Eastside Bypass
4B1
1.00
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SWA

...
downstream   WSE,   it   is   necessary   to   identify   any   cross-­‐‑
correlations.   The   normalized   cross-­‐‑corr...
NNC (Velocity)

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Alternative 1
Alternative 2
Alternative 3

0.8
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500...
Figure   11   shows   the   correlations   represented   by   the  
different   lag   times   between   WAHSIs   (Figures ...
[8]   Quinn   TP   (2005)   The   Behaviour   and   Ecology   of  
Pacific   Salmon   and   Trout.   University   of   Was...
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  1. 1. ARTICLE International Journal of Water Sciences Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model Regular Paper Lubo Liu1,* and Joaquin Ramirez1 1 Department of Civil and Geomatics Engineering, Lyles College of Engineering, California State University Fresno, Fresno, US * Corresponding author E-mail: llubo@csufresno.edu Received 9 Sep 2013; Accepted 22 Nov 2013 DOI: 10.5772/57437 © 2013 Liu and Ramirez; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract   The   San   Joaquin   River   Restoration   Program   (SJRRP)  provides  adult  Chinook  salmon  with  a  passage   to   upstream   spawning   beds   and   a   safe   route   for   juveniles   returning   to   the   Delta.   A   two-­‐‑   dimensional   depth-­‐‑averaged   hydrodynamic   model   based   on   the   RMA10   scheme   was   developed   to   simulate   the   hydraulic   properties   (current   velocities,   depth,   water   surface   elevation)   of   three   proposed   alternative   migration   pathways   to   explore   flow   patterns   and   offer   useful   insights   into   the   effects   of   hydrodynamic   alterations   of   the   channel,   a   critical   capability   for   determining   the   best   passage   for   migration.   The   finite   element   model   reasonably   described   the   hydrodynamic   conditions  and  calculated  a  Suitability  Index  (SI)  for  the   habitat   for   spring-­‐‑run   Chinook   salmon, with   a   Nash-­‐‑ Sutcliffe  Coefficient  (NSC)  of  0.75  for  discharge and  0.56   for   water   surface   elevation   (WSE)   respectively.   The   alternatives  analysed  were  found  to  be  characterized  by   similar   SI   distributions   under   the   same   boundary   conditions.   Alternatives   2   and   3   had   higher   overall   Weighted   Area   Habitat   Suitability   Index   (WAHSI)   values   and   would   thus   be   expected   to   provide   better   environments   for   salmon   migration   than   Alternative   1.   Normalized   cross-­‐‑   correlation   calculations   revealed   fair   correlations   between   the   WAHSI   values   and   upstream   discharge   or   downstream   water   surface   elevation.   The   hydrodynamic   model   may   also   provide   a   reference   for   similar   suitability   studies   of   salmon   habitat   in   other   inland  rivers.       www.intechopen.com Int. j. Spring Chinook Vol. 2, 5:2013 Lubo Liu and Joaquin Ramirez: Assessment of water sci., 2013,Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model Keywords   Hydrodynamic   Model,   Habitat   Suitability,   Salmon  Migration,  Correlation   1.  Introduction     As  the  second  longest  river  in  California,  the  San  Joaquin   River   (SJR)   is   a   vital   natural   resource   for   numerous   residents   and   industries.   It   provides   an   array   of   utilities   within   the   Central   Valley   and   is   home   to   some   of   California’s   most   productive   agricultural   areas   [1].   Headwaters   for   the   river   originate   in   the   high   Sierra   Nevada,   mainly   from   snowmelt   and   runoff   [2].   Eventually  the  SJR  conjoins  with  the  Sacramento  River  to   form   the   largest   river   delta   on   the   west   coast   of   North   America  [3].     1
  2. 2. The  river  is  crucial  for  the  propagation  and  survivability   of   Chinook   salmon   and   other   aquatic   species   and   wildlife,   but   over   the   years   it   has   experienced   considerable   hydrologic   disconnection  along   its   reaches   due   to   extensive   water   diversion.   Indigenous   salmon   populations  have  suffered  as  a  result  and  their  numbers   have   decreased   significantly   due   to   insufficient   flows   and   anthropogenic   activities   [4].   In   order   to   restore   salmon   and   other   fish   populations   to   a   point   of   self-­‐‑ sustainment,  the  San  Joaquin  River  Restoration  Program   (SJRRP)   was   established   in   2006   to   maintain   a   continuous   flow   from   the   Friant   Dam   to   its   confluence   with   the   Merced   River.   Due   to   practical   limitations,   routing  the  flow  along  several  alternative  pathways  has   been  considered  [5].  A  critical  task  for  the  SJRRP,  the  so-­‐‑ called   “Reach   4B   Project”,   was   to   modify   and   improve   the   channel   capacity   of   Reach   4B   (which   is   separated   into   4B1   and   4B2,   shown   in   Figure   1)   of   the   SJR.   Multiple  scenarios  for  the  restoration  of  the  river  and  for   modifications   of   existing   SJR   channels   were   designed   and   studied   to   ensure   fish   passage   and   adequate   flow   throughout  the  study  area  [6].     Natural   Chinook   salmon   runs   along   the   SJR   (above   the   Merced   River   Confluence)   originally   occurred   in   fall,   spring  and  in  late  autumn  for  some  species.  However,  all   runs  had  ceased  by  the  late  1940s  due  to  water  diversion   [7].   In   a   natural   river   system,  salmonids   have   evolved   to   exploit   natural   flow   patterns   in   streams   so   that   migrations   can   take   place   when   water   characteristics   are   ideal   [8].   However,   anthropogenic   activities   alter   natural   settings   and   offset   the   timing   of   advantageous   river   conditions   and   hence   salmonid   migration   [9].  As   part   of   the  effort  to  restore  the  river’s  natural  conditions,  a  great   deal  of  research  has  been  devoted  to  the  study  of  habitat   and  flow  relationships  in  recent  years  [9-­‐‑11].  In  relation  to   California’s   waterways,   researchers   have   mainly   focused   on   the   delta   region   with   only   limited   investigations   conducted  for  the  SJR,  especially  for  the  middle  section  of   the   river   [12].   When   salmon   return   to   their   spawning   grounds,   they   must   complete   their   migration   within   a   certain   amount   of   time   and   with   adequate   reserves   of   energy   in   order   to   complete   their   life   cycle   [13].   Hydrodynamic   conditions   affecting   salmon   passage   include  the  water  velocity,  depth  and  water  quality,  all  of   which  are  important  factors  for  their  migration.  Sustained   water   velocity   and   water   depth   provide   opportune   passage  conditions  for  the  successful  upstream  migration   of   adult   salmon   [14,   15].   An   in-­‐‑depth   hydrodynamic   investigation   is   therefore   essential   to   support   efforts   to   better   delineate   the   impact   of   flow   characteristics   on   salmon  migration  and  habitat  conditions.       Modelling  methods  have  been  very  effective  tools  for  this   type  of  riverine  study  and  several  hydrodynamic  models   have   been   constructed   for   the   SJR.   However,   most   have   2 Int. j. water sci., 2013, Vol. 2, 5:2013 been   one-­‐‑dimensional   [12,   16],   providing   a   large-­‐‑scale   overview   of   the   river   network.   Considering   the   complexity   and   heterogeneous   properties   of   the   SJR,   a   two-­‐‑dimensional   model   is   more   suitable   for   describing   detailed   local   conditions   such   as   those   critical   for   the   progress  of  salmon  migration  [17-­‐‑20].     The   goal   of   the   SJRRP’s   Reach   4B   was   to   provide   a   passage   for   adult   Chinook   salmon   to   spawning   beds   further   upstream   and   a   safe   route   for   juveniles   to   the   delta   [5].   To   this   end,   the   objective   of   this   research   was   therefore   to   model   the   stream   conditions,   including   current  velocity,  depth  and  water  surface  elevation  (WSE),   for   each   of   the   three   alternatives   proposed   in   Project   4B   under   the   same   hydrologic/hydraulic   boundary   conditions.   A   two-­‐‑dimensional   depth-­‐‑averaged   model   incorporating   disconnected   portions   of   the   SJR   was   developed   based   on   the   RAM10   scheme   and   used   to   simulate  these  local  river  characteristics  and  conditions  to   further   explore   the   correlations   between   river   flow   and   salmon   migration   under   the   different   alternatives   proposed.   The   model   facilitates   the   development   of   a   better   understanding   of   the  effects   of  different   boundary   conditions,   both   upstream   and   downstream,   on   salmon   habitat   suitability,   survival   and   migration   conditions.   Model  simulations  allow  the  exploration  of  flow  patterns   and   enable   users   to   compare   alternative   scenarios.   Modelling   results   also   provides   insights   into   the   hydrodynamic   behaviour   that   would   result   from   proposed  river  alterations  and  support  the  prediction  and   analysis   of   the   consequent   impact   on   the   conditions   for   Chinook  salmon  runs.   2.  Description  of  study  area   The  study  area  lies  within  the  Middle  San  Joaquin-­‐‑Lower   Chowchilla   watershed   and   extends   approximately   57.6   river   miles   (92.2   km)   from   monitoring   stations   SJR   near   Dos  Palos  (SDP)  to  SJR  at  the  Fremont  Ford  Bridge  (FFB)   near   California   Highway   140.   The   SJR   is   divided   into   different   river   segments   in   this   area,   designated   Reaches   4A,  4B1,  4B2  and  5,  Eastside  Bypass  and  Mariposa  Bypass   (see  Figure  1).  Initially,  the  channel  of  pathway  of  the  SJR   consisted   of   Reaches   4A,   4B1,   4B2   and   5.   Descriptions   of   each  river  reach  are  listed  in  Table  1.  The  original  Eastside   Bypass   and   Mariposa   Bypass   were   utilized   as   flood   control   channels.   However,   the   Eastside   Bypass   now   conveys  all  water  from  upstream  as  a  portion  of  the  river   and  Reach  4B1  is  hydraulically  disconnected.  The  portion   of   the   Eastside   Bypass   within   our   scope   of   study   begins   directly  downstream  of  Reach  4A  near  SWA  and  extends   to  Reach  5  of  the  SJR.  Mariposa  Bypass  is  another  channel   designed  to  convey  flood  flow  and  connects  the  Eastside   Bypass   to   Reach   4B2.   Under  normal   flow   conditions,   the   river  flows  from  Reach  4A  to  the  Eastside  Bypass  and  re-­‐‑ enters  the  SJR  at  Reach  5.   www.intechopen.com
  3. 3. 37.4 FFB Reach 5 37.3 J2 Alt1/2/3 Alt1 Reach 4B2 Eastside Bypass 37.2 N Alt2/3 J1 EBM Mariposa Bypass Latitude, o Alt3 Alt1/3 Alt2 Reach 4B1 SWA 37.1 Alt1/2/3 Reach 4A San Joaquin River 37.0 SDP 5 miles North 36.9 121.0 120.8 120.6 Longitude, o 120.4 W Figure  1.  Geographic  map  showing  the  reaches  in  the  modelling  domain  of  the  San  Joaquin  River  (SJR)  (Alt  –  Alternative,  1  mile  =  1.6   km).  Monitoring  stations  (SDP,  SWA,  EBM  and  FFB)  are  described  in  Table  2.     Reach/bypass   Reach  4A   Length   (miles)   13.5   Flow  capacity   (cfs)   4500   Connections   SDP**  –  SWA** Usage   Current Status F   River  flow   Runoff,  receiving  water  from   Reach  4B1   21.3   Unknown   SWA  –  J1* NF   agricultural  practices  and  rain  events   Occasional  flood  water  received  from   Reach  4B2   11.4   10000   J1  –  J2     the  Eastside  Bypass  and  backflow   F from  Reach  5   River  flow  received  from  the  Eastside   Reach  5   17.5   26000   J2  –  FFB**   Bypass,  Reach  4B2  and  agricultural   F return  flows   Eastside  Bypass   21.8   15700  (average)   SWA–EBM**–J2   Flood  control  and  SJR  flow   F   Mariposa Flood  flow,  transporting  water  from   3.4   8000   EBM–J1     F Bypass   the  Eastside  Bypass  to  the  SJR   F:  Functional;  NF:  Not  Functional;   *:  J1  and  J2  -­‐‑   Junction  points;   **:  SDP  -­‐‑   SJR  near  Dos  Palos,  EBM  -­‐‑   Eastside  Bypass   below  Mariposa  Bypass,  SWA  -­‐‑  SJR  near  Washington  Rd,  FFB  -­‐‑  SJR  near  Washington  Rd.   Table  1.  Reaches  and  bypasses  in  the  middle  of  the  San  Joaquin  River  (SJR)   (1  mile  =  1.6  km;  1  cfs  =  0.028  cms)   www.intechopen.com Lubo Liu and Joaquin Ramirez: Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model 3
  4. 4. Station  Description   Station  ID   Station  Location,   NAD83   36.9949,  -­‐‑120.501   37.1114,  -­‐‑120.591   Reach/confluence   Agency SJR  near  Dos  Palos   SDP   4A   SJR  near  Washington  Rd   SWA   4A   Eastside   Bypass   below   Mariposa   EBM   Eastside  Bypass   37.2060,  -­‐‑120.697   Bypass   SJR  at  Fremont  Ford  Bridge   FFB   Reach  5   37.3099,  -­‐‑120.931   *:  CADWR  -­‐‑  California  Department  of  Water  Resources,  USGS  -­‐‑  U.  S.  Geological  Survey   CADWR* CADWR   CADWR   USGS* Table  2.  Monitoring  stations  in  the  study  river  reaches     The   data   used   for   the   model   development   and   calibration,   including   bathymetry,   channel   flow   rate   and   WSE,   were   obtained   from   the   U.S.   Geological   Survey   (USGS),   the   U.S.   Bureau   of   Reclamation   (USBR)   and   the   California   Department   of   Water   Resources   (CADWR).     Bathymetry  data  were  collected  during  2010  and  2011  by   USBR   using   GPS   and   the   Acoustic   Doppler   Current   Profiler   (ADCP)   at   a   spatial   interval   of   20   feet.   Flowrate   and   river   stage   data   were   collected   for   the   year   of   2011   (from  January  1st  to  September  30th)  by  the  four  CADWR   and  USGS  in-­‐‑situ  river  gauge  stations  located  in  the  study   area  at  15  minute  intervals.  Station  descriptions  are  listed   in   Table   2.   The   year   2011   was   selected   for   model   calibration  because  adequate  interim  flows  were  released   from   upstream   and   the   data   for   this   period   are   quality-­‐‑ assured  by  reporting  agencies.  The  geographic  boundary   of  the  SJR  was  determined  using  coordinates  from  Google   Earth   based   on   the   WGS84   global   reference   system.   The   data   collected   from   multiple   government   agencies   were   converted   and   georeferenced   using   the   same   coordinate   system  and  reference  datum,  namely  the  North  American   Vertical   Datum   NAVD   88   and   California   State   Plane,   Zone  3,  North  American  horizontal  Datum  NAD  83.       3.  Hydrodynamic  model   A   vertically-­‐‑integrated   hydrodynamic   model   was   developed  using  the  finite  element  scheme  RMA10  [21]  to   describe   the   flow   velocity,   water   depth   and   WSE.   The   governing   equations   in   the   x and y   directions   are   as   follows:   ∂h ∂h ∂h ∂U ∂V +U +V + h( + ) = 0            (1) ∂t ∂x ∂y ∂x ∂y h = −gh ( ∂U ∂U ∂U + hU + hV − fVh = ∂t ∂x ∂y ∂ ∂U ∂ ∂U (ε xxh )+ (ε xyh ) ρ ∂x ∂x ∂y ∂y 1 2 2 2 ∂a ∂h Ugn (U + V ) )− + + ζ W 2 cosψ 1/3 ∂x ∂x h (2) 4 Int. j. water sci., 2013, Vol. 2, 5:2013 h = −gh ( ∂V ∂V ∂V + hU + hV + fUh = ∂t ∂x ∂y ∂ ∂V ∂ ∂V (ε yxh )+ (ε yyh ) ∂x ∂y ∂y ρ ∂x 1 2 2 2 ∂a ∂h Vgn (U + V ) + + ζ W 2 sinψ )− h 1/3 ∂y ∂y (3) U , V   are   the   depth-­‐‑averaged   velocities   in   the   x, y directions;   h   is   the   water   depth   and   a   is   the   bottom   surface   elevation;   g   is   the   acceleration   due   to   gravity;   W  is  the  wind  velocity;  ψ  is  the  wind  direction;   ζ  is  an  empirical  wind  coefficient;  and   f  is  the  Coriolis   parameter.   n   denotes   the   Manning’s   roughness   Where coefficient   and   ε   is   the   depth-­‐‑averaged   eddy   viscosity.   Horizontal  mixing  was  described  using  the  Smagorinsky   eddy  parameterization:   ∂U ε S = 2 Am = αA ∂x 2 ∂V + ∂y 2 1 ∂U ∂V ) + ( + 2 ∂y ∂x (4) ε S   is   the   eddy   viscosity;   α   is   a   constant   in   the   range   0.01-­‐‑0.5   ( α = 0.05 was   used   for   this   study)   and   where A   is   the   area   of   the   current   element.   The   horizontal   turbulent  mixing  of  momentum  was  typically  ignored  in   some  previous  hydrodynamic  models  of  the  SJR  [22,  23].   Our   results   suggest   that   the   model   is   insensitive   to   the   eddy   viscosity   within   a   range   from   0   to   10   m2/s,   so   a   constant   value   of   1.0   m2/s   was   used   for   the   minimum   eddy  viscosity.  Values  in  the  different  regions  were  varied   depending  on  the  element  size  and  the  velocity  gradients   according   to   Equation   4.   Wind   stress   and   Coriolis   force,   both  of  which  typically  play  a  critical  role  in  large  water   bodies   such   as   oceans   or   lakes,   were   neglected   in   this   model  of  a  small-­‐‑scale  river  section.   For   the   initial   conditions   for   the   model,   it   was   assumed   that   the   river   was   at   rest   at   the   start   and   it   took   a   considerable  time  (ten  days  in  this  case)  for  the  model  to   www.intechopen.com
  5. 5.   Element  #   Node  #   Alternative  1   2483   9568   Alternative  2   1841   7056   Reaches  included   (Figures  1  and  2)   Reach  4A     Eastside  Bypass   Reach  5     Reach  4A     Reaches  4B1  and  4B2   Reach  5     Alternative  3   2134   8209   Reach  4A   Eastside  Bypass   Mariposa  Bypass     Reach  4B2   Reach  5     Table  3.  Finite  Element  Model  (FEM)  information   Salmon  Species   Spring  Salmon   Autumn  Salmon   Cruising  Velocity1* 0  –  3.41  (ft/s)   0  –  1.04  (m/s)   0  –  3.41  (ft/s)   0  –  1.04  (m/s)   Swimming  Speed   Sustained  Velocity2*   3.41  –  10.79  (ft/s)   1.04  –  3.29  (m/s)   3.41  –  10.79  (ft/s)   1.04  –  3.29  (m/s)   Minimum  Depth     Darting  Velocity3* 10.79  –  22.41  (ft/s)   3.29  –  6.83  (m/s)   10.79  –  22.41  (ft/s)   3.29  –  6.83  (m/s)   0.80  (ft)   0.24  (m)   0.80  (ft)   0.24  (m)   : Cruising speed  is  the  speed  at  which  a  fish  can  swim  for  an  extended  period  of  time,  usually  hours.   : Sustained  is  a  speed  that  can  be  maintained  for  minutes.   3*: Darting represents  a  single  effort  or  burst  which  is  not  maintainable.   1* 2* Table  4.  Salmon  swimming  capabilities  (velocity,  depth)  reported  in  the  literature  [9,  13,  15]   reach   the   actual   initial   conditions.   The   boundary   conditions   for   the   hydrodynamic   simulation   included   a   no   leakage   condition   across   the   surface   and   the   bottom,   no  wind  stress  and  zero  pressure  at  the  free  water  surface,   a   drag   stress   condition   at   the   bottom   of   the   river,   a   discharge  condition  at  the  upstream  and  a  WSE  condition   at  the  downstream.     injuries  and  compromise  their  migration  [24].  In  addition,   when  fish  are  not  fully  submerged  they  partially  lose  the   ability   to   generate   thrust   [25].   In   Thompson’s   model,   it   was  assumed  that  a  safe  passage  depth  of  greater  than  0.8   ft  must  be  maintained  over  25%  of  the  stream  width  and   must  remain  continuous  for  10%  of  the  cross  section  [14].   5.  Results  and  discussion   In   order   to   accurately   delineate   the   complex   physical   boundaries   of   the   SJR,   a   finite-­‐‑element   mesh   was   used   (see  Table  3)  for  this  model.  The  sizes  of  the  non-­‐‑uniform   elements  were  between  1  and  100  feet  (Figure  2d).     4.  Hydrodynamic  considerations  for  salmon  migration   To   address   the   hydrodynamic   impact   on   salmon   in   a   river,   Bell   [15]   divided   the   swimming   capabilities   of   salmon   into   three   speed   categories   (Table   4).   Fish   normally   travel   at   a   cruising   speed   for   several   hours   during   migration,   at   a   sustainable   speed   over   a   few   minutes   for   navigation   through   difficult   areas   and   at   a   darting   speed   for   feeding   or   escape   [15].   Based   on   this   behaviour,   velocity   can   be   manipulated   for   use   as   either   an   artificial   barrier   or   as   a   means   to   attract   fish.   Ideally,   cruising   speed   can   be   considered   attractive,   while   sustained   speed   can   become   a   barrier   over   an   extended   distance   and   darting   speed   an   immediate   barrier   if   the   transition   is   rapid   [15].   The   ranges   of   velocity   values   of   these   three   categories   are   listed   in   Table   4.   A   suitable   minimum   depth   of   0.8   ft   (0.244m)   has   also   been   recommended   for   the   passage   of   adult   spring   Chinook   salmon   (Table   4)   [14].   Although   salmon   have   been   observed  travelling  at  depths  less  than  those  indicated  in   Table   4,   at   depths   of   less   than   0.8   feet   fish   may   suffer   www.intechopen.com The   model   simulated   hydrodynamic   flow   characteristics   under  the  three  alternative  water  pathways  for  the  spring   Chinook  salmon  run.  The  two-­‐‑dimensional  finite  meshes   for  the  three  alternatives  are  shown  in  Figure  2.  Figure  2a   shows   the   Alternative   1   which   has   flow   from   Reach   4A   through   the   Eastside   Bypass   (passing   through   stations   SWA   and   EBM)   to   Reach   5   and   the   RMA10   model   for   Alternative   1   does   not   include   any   finite-­‐‑element   mesh   for  Reaches  4B1  and  4B2.  Alternative  2  (Fig.  2b)  has  flow   from   Reach   4A   through   the   original   course   of   the   SJR   (Reaches   4B1   and   4B2)   to   Reach   5   and   the   model   for   Alternative  2  does  not  include  any  mesh  for  the  Eastside   Bypass.   Figure   2c   includes   all   sections   of   the   study   domain.   The   currently   preferred   option   (Alternative   3)   consists   of   conveying   a   small   amount   of   flow   through   reach  4B1,  with  the  remaining  restoration  flow  continuing   down  the  Eastside  Bypass,  transferring  into  the  Mariposa   Bypass   and   re-­‐‑entering   the   SJR   in   Reach   4B2   [26].   Therefore,   the   major   fish   route   in   Alternative   3   follows   Reach   4A,   Eastside   Bypass,   Mariposa   Bypass,   Reach   4B2   and  Reach  5.  Figure  2d  shows  an  enlarged  portion  of  the   two-­‐‑dimensional  mesh  in  the  area  around  station  SWA.     The   model   was   calibrated   using   the   2011   data   set   and   deemed   applicable   for   modelling   the   investigation   of   Lubo Liu and Joaquin Ramirez: Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model 5
  6. 6. hydrodynamic   conditions   affecting   salmon   migration   in   the   SJR.   The   discharge   data   were   used   for   the   upstream   boundary   condition   at   station   SDP   and   the   WSE   data   were   used   for   the   downstream   boundary   condition   at   station   FFB.   These   data   sets   were   recorded   at   15-­‐‑minute   intervals   between   January   1st   and   September   1st   2011,   by   CADWR   and   USGS.   Figure   3   shows   these   boundary   conditions.  In  the  convergence  test,  0.1%  and  0.05%  were   set   as   the   convergence   criteria   for   current   velocities   and   WSE  respectively,  for  each  iteration  within  the  same  time   (a) level.   The   data   indicate   that   little   flow   (less  than   100   cfs)   occurred  upstream  at  SDP  in  early  spring  until  late  March   2011   (before   the   80th   day   of   the   simulation   period).   In   2011,   the   most   abundant   flow   occurred   from   late   spring   to   late   summer,   the   period   when   the   adult   Chinook   salmon  in  the  spring  run  enter  the  freshwater  to  spawn  in   the   autumn.   The   model   simulated   the   discharge   and   the   WSE  in  this  period  utilizing  a  time  step  (15  minutes)  that   was   the   same   as   the   data   collection   interval   for   calibration.     (b) FFB FFB Eastside Bypass EBM EBM SJR SWA SWA SJR SDP (c) SDP (d) FFB Eastside Bypass 4B2 EBM Eastside Bypass 4B1 4B1 SWA SWA SJR SDP Figure   2.   Finite   element   meshes   of   three   flow   pathways:   (a)   Alternative   1;   (b)   Alternative   2;   (c)   Alternative   3;   and   (d)   Enlarged   2-­‐‑ dimensional  finite  element  meshes  in  the  SJR  near  Washington  Rd  (SWA)  region.   6 Int. j. water sci., 2013, Vol. 2, 5:2013 www.intechopen.com
  7. 7. Upstream condition: Discharge at SDP Discharge (cfs) 5000 (a) 4000 3000 2000 1000 0 0 20 40 60 80 100 120 140 160 180 200 160 180 200 Downstream condition: WSE at FFB WSE (ft) 80 (b) 70 60 50 0 20 40 60 80 100 120 Julian days, 2011 140 Figure   3.   Boundary   conditions:   (a)   Upstream   condition:   Discharge   at   the   SJR   near   Dos   Palos   (SDP);   and   (b)   Downstream   condition:   Water  Surface  Elevation  (WSE)  at  the  SJR  at  Fremont  Ford  Bridge  (FFB).  (1ft  =  0.3048  m,  1  cfs  =  0.0283  cms)   Data  Stations   SWA  (Discharge)   Table  5.   RMSE  and   SWA  (WSE)   EBM  (WSE)   0.47   0.017   0.014   SDP  (WSE)   0.064   0.75   Minimum RMSE NSC 0.56   0.42   0.34   NSC results   The   Manning   roughness   coefficient   of   the   channel   was   manually   adjusted   to   calibrate   the   model   using   the   method   of   minimum   normalized   Root   Mean   Squared   Error  (RMSE),  which  is  defined  as  follows:     RMSE = 1 N N t =1 i i ( X m − X o )2    (5)   Xo i i X m   and   X o   are   the   modelled   and   observed   discharge/WSE   at   time   ti   while   N   is   the   number   of   where observations.   X o is   the   average   of   the   observed   values.   By   varying   the   values   of   the   roughness   coefficient   in   Equations   2   and   3,   we   obtained   the   optimum   value   of   0.035,  which  resulted  in  the  minimum RMSE . In   addition,   to   quantitatively   describe   the   accuracy   of   model   output,   the   Nash-­‐‑Sutcliffe   Coefficient   (NSC)   was   calculated  as  follows,   N NSC = 1 − i =1 N i =1 www.intechopen.com i i ( X o −X m ) 2 i ( X o −X o ) 2                    (6)   where, NSC   is   the   Nash-­‐‑Sutcliffe   model   efficiency   Coefficient.   The   error   results   including   the   minimum   RMSE   and   the   corresponding   NSC are   reported   in   Table  5.   Figure   4   compares   the   observed   data   for   the   discharge   (Figure   4a)   and   WSE   (Figure   4b)   at   SWA   with   the   modelling   results.   Figures   5a   and   5b   compare   observed   WSE  at  SDP  and  at  EBM,  respectively,  with  the  modelling   results.   The   results   obtained   from   the   hydrodynamic   model   were   generally   found   to   be   consistent   with   the   observed  data  and  found  to  reasonably  describe  both  the   WSE   and   the   discharge   at   the   observing   stations.   While   the   WSE   values   (Figures   4b,   5a   and   5b)   were   simulated   fairly   accurately,   simulating   the   discharge   was   relatively   challenging   due   to   the   lack   of   discharge   data   for   several   minor   tributaries   along   the   river   in   the   study   area.   The   water   surface   elevation   abruptly   dropped   from   93   ft   (28.35   m)   to   57   ft   (17.37   m)   and   then   rose   up   to   117   ft   (35.66   m)   between   days   22   and   35   at   Station   EBM   in   Figure   5;   these   results   appear   to   represent   equipment   malfunction   or   error.   The   water   surface   elevation   (WSE)   fluctuation  of  more  than  50  ft  (15.24  m)  during  these  days   was  not  reflected  by  the  nearest  functional  gauge  stations   (see   Figure   4b   for   upstream   at   SWA   and   Figure   3b   for   downstream  at  FFB).   Lubo Liu and Joaquin Ramirez: Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model 7
  8. 8. SJR Discharge at SWA Discharge (cfs) 4000 (a) observed modeling 2000 0 0 20 40 60 80 100 120 140 160 180 200 140 160 180 200 SJR WSE at SWA WSE (ft) 120 observed modeling 110 100 90 0 20 40 60 80 100 120 Julian days, 2011 Figure  4.  Comparison  of  observed  and  modelling  results  of:  (a)  San  Joaquin  River  (SJR)  discharge  at  the  SJR  near  Washington  Rd  (SWA);   and  (b)  SJR  Water  Surface  Elevation  (WSE)  at  SWA.  (1ft  =  0.3048  m,  1  cfs  =  0.0283  cms)   SJR WSE at SDP WSE (ft) 130 120 110 100 observed modeling (a) 90 120 130 140 150 160 170 180 190 200 SJR WSE at EBM WSE (ft) 120 100 80 60 observed modeling (b) 0 20 40 60 80 100 120 140 160 180 200 Julian days, 2011 Figure  5.  Comparison  of  observed  and  modelling  results  for:  (a)  San  Joaquin  River  (SJR)  Water  Surface  Elevation  (WSE)  at  the  SJR  near   Dos  Palos  (SDP);  and  (b)  SJR  WSE  at  Eastside  Bypass  below  Mariposa  Bypass  (EBM).  (1ft  =  0.3048  m)   The  output  from  the  validated  and  calibrated  model  was   used   to   assess   the   habitat   suitability   of   the   river   channel   for   the   spring   Chinook   salmon   run.   Historically,   there   were   four   distinct   salmon   runs   in   the   Sacramento-­‐‑San   Joaquin  River  system,  designated  according  to  the  season   in  which  the  majority  of  the  run  entered  the  freshwater  as   adults   [27].   The   spring-­‐‑run   Chinook   salmon   entered   the   water   system   from   late   March   through   September,   with   adults  staying  in  cool  water  habitats  through  the  summer   8 Int. j. water sci., 2013, Vol. 2, 5:2013 and   then   spawning   in   the   autumn   from   mid-­‐‑August   through   early   October.   For   this   run,   therefore,   the   hydrodynamic   scenario   in   the   summer   season   is   especially   critical   for   the   salmon   migrating   from   the   ocean   to   upstream   spawning   grounds.   In   this   research,   the   hydrodynamic   model   simulated   water   depth   and   velocity   between   late   March   and   late   June   (between   day   90  and  day  181  of  the  simulation  period)  of  2011  and  the   corresponding   habitat   suitability   for   salmon   was   www.intechopen.com
  9. 9. quantified   using   the   habitat   Suitability   Index   (SI)   [27].   Figures   6a   and   6b   were   developed   by   the   California   Department   of   Fish   and   Wildlife   (CADFW)   [28,   29]   and   show   the   standard   habitat   SI   for   Chinook   salmon   for   velocity   (Velocity   SI)   and   depth   (Depth   SI),   respectively.   The  range  of  the  dimensionless  SI  at  any  location  in  a  river   is   between   1   and   0,   representing   the   best   and   the   worst   habitat   quality,   respectively.   To   align   with   the   standard   convention  in  the  literature,  metric  units  were  used  for  the   SI   calculations,   so   velocities   between   12.2   cm/s   and   21.3   cm/s  and  depths  between  30.5  cm  and  61  cm  constitute  the   best   ranges   for   Chinook   salmon   (Figure   6).   The   best   velocities   in   this   method   all   support   cruising   velocity,   which  is  consistent  with  the  literature  (Table  4).  Figures  6a   and   6b   show   that   the   best   velocity   ranges   of   velocity   and   depth  are  12  –  22  cm/s  and  35  –  60  cm,  respectively.     1.2 (a) 1.0 SI 0.8 0.6 0.4 0.2 0.0 0 10 20 30 40 50 60 70 80 90 100 Velocity (cm/s) 1.2 (b) 1.0 SI 0.8 0.6 0.4 0.2 0.0 0 20 40 60 80 100 120 140 160 180 200 Depth (cm) Velocity WAHSI Figure  6.  Suitability  Index  (SI)  curves  for  Chinook  salmon:  (a)  Velocity;  and  (b)  Depth  suitability  (By  California  Department  of  Fish  and Wildlife  (CADFW)  [28]).       1.0 0.8 0.6 (a) Alternative 1 Alternative 2 Alternavite 3 0.4 0.2 0.0 80 100 120 140 160 180 Depth WAHSI 1.0 0.8 0.6 (b) Alternative 1 Alternative 2 Alternavite 3 0.4 0.2 0.0 80 Overall WAHSI 200 100 120 140 160 180 2.0 1.6 1.2 200 (c) Alternative 1 Alternative 2 Alternavite 3 0.8 0.4 0.0 80 100 120 140 160 180 200 Julian days, 2011 Figure  7.  Model  Weighted  Area  Habitat  Suitability  Index  (WAHSI)  for  three  alternatives  for:  (a)  Velocity  suitability;  (b)  Depth  suitability;   and  (c)  Overall  suitability.   www.intechopen.com Lubo Liu and Joaquin Ramirez: Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model 9
  10. 10. The   representative   values   of   velocity   and   depth   for   each   element  were  the  values  at  its  centre,  which  were  calculated   by  interpolating  the  values  at  all  nodes  of  the  element  to  the   centre  using  Inverse  Distance  Weighted  method  (IDW).  The   calculated  velocity  and  depth  for  each  element  were  used  for   determining   its   SIs   at   different   times   using   Figures   6a   and   6b.   The   values   of   velocity   SI,   depth   SI   and   the   overall   SI   (velocity   SI   +depth   SI)   for   the   entire   domain   under   investigation  can  be  calculated  using  the  following  weighted   average  habitat  suitability  index  ( WAHSI ), M WAHSI j = i =1 ( SI i , j ⋅ ∆Ai ) M i =1   ∆Ai                    (7)   j   =1   for   velocity,   2   for   depth   and   3   for   the   combined   WAHSI   for   velocity   and   depth;   M   is   the   where total  number  of  wetted  finite  elements;  and   A  is  the  area   of  element.   Figures   7a,   7b   and   7c   show   the   time   variation   of   WAHSI   values  derived  from  the  velocity  SI,  depth  SI  and  the  overall   SI,  respectively,  for  all  three  of  the  proposed  alternatives.  In   the  late  spring  (day  90)  and  early  summer  (day  181),  neither   velocity  (with  WAHSI   around   0.3)   nor  depth   (with   WAHSI   around   0.1)   was   deemed   suitable   for   salmon   migration.   Under   the   conditions   obtaining   in   the   summer   of   2011,   the   SIs  of  all  the  proposed  alternatives  increased  from  Day  90  to   Day   145,   then   maintained   these   peak   values   for   about   30   days.   After   this   point,   the   hydrodynamic   conditions   for   salmon   fluctuate   and   deteriorate,   so   the   period   between   mid-­‐‑May   and   mid-­‐‑June   of   that   year   would   have   been   the   best   period   for   Chinook   salmon   migration.   Generally,   the   impact  of  velocity  is  more  stable  than  that  of  depth.  Among   the   three   proposed   alternatives,   the   WAHSI   values   of   Alternatives  2  and  3  were  generally  equal  to  or  higher  than   those   of   Alternative   1,   which   incorporates   the   Eastside   Bypass.   The   similar   shapes   of   the   depth   (Figure   7b)   and   overall  (Figure  7c)  WAHSIs  indicate  that  the  overall  WAHSI   in   this   case   is   controlled   by   water   depth,   which   was   thus   more   critical   for   aquatic   life   than   the   velocity   under   the   insufficient   discharge   conditions   experienced   during   the   modelling  period.   Eastside Bypass Eastside Bypass 4B1 SWA SWA 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 Eastside Bypass Eastside Bypass SWA (d) Depth SI for Alternative 1 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 (c) Velocity SI for Alternative 3 (b) Velocity SI for Alternative 2 (a) Velocity SI for Alternative 1 SWA 0.20 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 4B1 SWA (e) Depth SI for Alternative 2 0.20 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 SWA 0.20 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 (f) Depth SI for Alternative 3 Figure  8.  Spatial  distribution  of  Suitability  Index  (SI)  in  the  region  at  the  SJR  near  Washington  Rd  (SWA)  at  day  130  for:  (a)  Velocity  SI for   Alternative   1;   (b)   Velocity   SI   for   Alternative   2;   (c)   Velocity   SI   for   Alternative   3;   (d)   Depth   SI   for   Alternative   1;   (e)   Depth   SI   for   Alternative  2;  and  (f)  Depth  SI  for  Alternative  3.         10 Int. j. water sci., 2013, Vol. 2, 5:2013 www.intechopen.com
  11. 11. Eastside Bypass SWA Eastside Bypass 4B1 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 SWA 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 Eastside Bypass Eastside Bypass SWA (d) Depth SI for Alternative 1 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 (c) Velocity SI for Alternative 3 (b) Velocity SI for Alternative 2 (a) Velocity SI for Alternative 1 SWA 0.20 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 4B1 0.20 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 SWA (e) Depth SI for Alternative 2 SWA 0.20 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 (f) Depth SI for Alternative 3 Figure  9.  Spatial  distribution  of  Suitability  Index  (SI)  in  the  region  at  the  SJR  near  Washington  Rd  (SWA)  at  day  170  for:  (a)  Velocity  SI for   Alternative   1;   (b)   Velocity   SI   for   Alternative   2;   (c)   Velocity   SI   for   Alternative   3;   (d)   Depth   SI   for   Alternative   1;   (e)   Depth   SI   for   Alternative  2;  and  (f)  Depth  SI  for  Alternative  3.         Since  the  SWA  confluence  region  (Figure  2)  is  common  to   all   three   alternative   flow   paths,   it   was   used   to   compare   the  spatial  distributions  of  the  SIs  at  specific  times.  Figure   8   (a   through   f)   shows   the   distribution   of   SI   in   the   SWA   confluence  region  on  Day  130,  when  SI  started  to  rise,  for   velocity  SI  (Figures  8a,  8c  and  8e  for  Alternatives  1,  2  and   3  respectively)  and  for  depth  SI  (Figures  8b,  8d  and  8f  for   Alternatives   1,   2   and   3   respectively).   Figure   9   shows   the   corresponding   distributions   on   day   170,   when   the   SIs   started  to  fall  near  the  end  of  the  most  suitable  period.  All   SIs   generally   increased   over   the   period   from   Day   130   to   Day   170.   Figure   10   shows   the   corresponding   velocity   vectors  and  depth  distributions  at  day  130.  Figures  8  and   9  show  the  significant  improvement  of  the  SIs  for  all  three   alternatives  during  the  period.  The  areas  with  higher  SIs   increased   in   both   velocity   SIs   and   depth   SIs.   Most   locations   in   the   river   reach   on   day   170   have   higher   velocity  SIs  (greater  than  0.6)  than  those  on  day  130.  The   improvement  of  the  depth  SI  was  not  as  significant  as  that   of  the  velocity  SI.  Figures  8  and  9  show  an  improvement   of   0.12   -­‐‑   0.2   for   depth   SI   and   0.2   –   0.4   for   velocity   SI   in   many   regions   during   this   period.   These   observations   were  consistent  with  Figure  7.                   www.intechopen.com Lubo Liu and Joaquin Ramirez: Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model Interestingly,   there   is   some   similarity   between   the   time   variation   trend   for   the   boundary   conditions   (Figure   3)   and   that   of   the   WAHSIs   (Figure   7)   during   the   salmon   migration   period   between   Day   90   and   Day   180,   with   an   expected   lag   time.   For   example,   the   peak   values   of   the   discharge  at  SDP  and  the  WSE  at  FFB  occurred  at  around   Day   100   and   Day   87,   respectively.   To   better   understand   how   the   boundary   conditions   impact   salmon   migration   and   thus   predict   the   suitability   for   salmon   migration   (WAHSI)   based   on   the   upstream   incoming   flow   or   11
  12. 12. downstream   WSE,   it   is   necessary   to   identify   any   cross-­‐‑ correlations.   The   normalized   cross-­‐‑correlation   between   discharge  or  WSE  and  WAHSI  was  defined  as  follows  [30]:   N −k NCC = meanwhile   w(i ) and u (i )  are  the  WAHSI  and  discharge   or   WSE   at   the  time   step,   respectively;   i is   the  number   of   model  data  points;  and   n  is  the  number  of  lag  time  steps   u (n + k ) w(n) n =1 N i =1 [w(i)]2 ⋅ N i =1 where NCC   is   the   normalized   cross-­‐‑correlation   function   and   has   a   value   between   -­‐‑1   and   1,   with   0   being   completely   unrelated   and   1   or   -­‐‑1   highly   correlated;   [u (i)]2   (8)   between  two  correlated  parameters.   Eastside Bypass Eastside Bypass 4B1 SWA 5.00 m 4.50 m 4.00 m 3.50 m 3.00 m 2.50 m 2.00 m 1.50 m 1.00 m 0.50 m SWA SWA 5.00 m 4.00 m 3.50 m 3.00 m 2.50 m 2.00 m 1.50 m 1.00 m 0.50 m 5.00 m 4.50 m 4.00 m 3.50 m 3.00 m 2.50 m 2.00 m 1.50 m 1.00 m 0.50 m (b) Depth for Alternative 2 (a) Depth for Alternative 1 (c) Depth for Alternative 3 Eastside Bypass Eastside Bypass 4B1 SWA SWA SWA 100 cm/s (d) Velocity vector for Alternative 1 100 cm/s 100 cm/s (f) Velocity vector for Alternative 3 (e) Velocity vector for Alternative 2 Figure  10.  Spatial  distribution  of  depth  and  velocity  vector  in  the  region  at  the  SJR  near  Washington  Rd  (SWA)  at  day  130  for:  (a)  Depth   for  Alternative   1;   (b)   Depth   for  Alternative   2;   (c)   Depth   for  Alternative   3;   (d)   Velocity   vector   for  Alternative   1;   (e)   Velocity   vector   for   Alternative  2;  and  (f)  Velocity  vector  for  Alternative  3.         Parameter   Upstream  Discharge  (SDP)   Velocity Depth Overall Downstream  WSE  (FFB)   Velocity Depth Overall NCC 0.834   0.895   0.855   0.926   0.765   0.895   Lag  Time  (days)   -­‐‑50.7   -­‐‑47.6   -­‐‑47.8(53)   0.0   0.0   0.0   Table  6.  Maximum  and  corresponding  lag  time  for  three  alternatives   12 Int. j. water sci., 2013, Vol. 2, 5:2013 www.intechopen.com
  13. 13. NNC (Velocity) 1 Alternative 1 Alternative 2 Alternative 3 0.8 0.6 0.4 0.2 (a) 0 −2500 −2000 −1500 −1000 −500 0 500 1000 1500 2000 2500 NNC (Depth) 1 Alternative 1 Alternative 2 Alternative 3 0.8 0.6 0.4 0.2 (b) 0 −2500 −2000 −1500 −1000 −500 0 500 1000 1500 2000 2500 NNC (Overall) 1 Alternative 1 Alternative 2 Alternative 3 0.8 0.6 0.4 0.2 (c) 0 −2500 −2000 −1500 −1000 −500 0 500 1000 1500 2000 2500 Lag time (Hours) Figure   11.   Correlations   between   upstream   discharge   and   Model   Weighted   Area   Habitat   Suitability   Index   (WAHSI)   for   the   three   alternatives  for:  (a)  Velocity  WAHSI;  (b)  Depth  WAHSI;  and  (c)  Overall  WAHSI   NNC (Velocity) 1 Alternative 1 Alternative 2 Alternative 3 0.8 0.6 0.4 0.2 (a) 0 −2500 −2000 −1500 −1000 −500 0 500 1000 1500 2000 2500 NNC (Depth) 1 Alternative 1 Alternative 2 Alternative 3 0.8 0.6 0.4 0.2 (b) 0 −2500 −2000 −1500 −1000 −500 0 500 1000 1500 2000 2500 NNC (Overall) 1 Alternative 1 Alternative 2 Alternative 3 0.8 0.6 0.4 0.2 (c) 0 −2500 −2000 −1500 −1000 −500 0 500 1000 1500 2000 2500 Lag time (Hours) Figure  12.  Correlations  between  downstream  Water  Surface  Elevation  (WSE)  and  Weighted  Area  Habitat  Suitability  Index  (WAHSI)  of   three  alternatives  for:  (a)  Velocity  WAHSI;  (b)  Depth  WAHSI;  and  (c)  Overall  WAHSI.     www.intechopen.com Lubo Liu and Joaquin Ramirez: Assessment of Spring Chinook Salmon Habitat Suitability in the San Joaquin River Using a 2-D Depth-Averaged Model 13
  14. 14. Figure   11   shows   the   correlations   represented   by   the   different   lag   times   between   WAHSIs   (Figures   11a,   11b,   11c   for   velocity,   depth   and   the   overall   WAHSI,   respectively)   and   the   discharge   boundary   condition   (incoming   flow).   The   figures   demonstrate   fairly   similar   correlations  for  each  of  the  three  alternatives.  The  values   for  the  best  correlations  and  their  corresponding  lag  times   are   listed   in   Table   6.  All   the   best   values   are   greater   than   0.8,   indicating   reasonably   good   correlations   between   the   upstream   flow   condition   at   SDP   and   the   salmon   habitat   suitability  expressed  by  the  WAHSI  values.  However,  the   best  correlations  occur  at  a  time  lag  of  about  50  days  (1200   hours)   between   these   two   parameters.   For   example,   the   salmon   habitat   suitability   based   on   velocity   considerations  (represented  by  the  velocity  WAHSI)  fully   responds   to   upstream   discharges   in   about   50   days.   The   second   peak   values   (all   less   than   0.5)   occurring   near   a   zero  time  lag  represent  only  the  local  best  values  and  are   not  optimized  correlations  on  a  global  scale.     Figure   12   shows   the   correlations   represented   by   the   NCC   between   the   WAHSI   and   the   downstream   WSE   values  at  FFB  for  different  lag  times.  The  velocity  WAHSI   (Figure   12a)   correlates   better   with   downstream   WSE,   exhibiting   a   higher     value   (0.926)   than   either   the   depth   WAHSI   (=   0.765,   Figure   12b)   or   the   overall   WAHSI   (=   0.895,  Figure  12c).  All  the  best  correlations  are  observed  at   a   zero   lag   time   for   each   of   the   three   alternatives.   This   indicates   almost   synchronized   responses   between   the   downstream  WSE  and  the  WAHSI  values.       6.  Conclusions   The  two-­‐‑dimensional  hydrodynamic  model  using  a  finite   element   scheme   developed   in   this   study   reasonably   described   the   hydrodynamic   conditions   in   the   middle   reaches   of   the   San   Joaquin   River   (SJR).   It   can   be   used   to   calculate   the   habitat   suitability   in   terms   of   Suitability   Index   (SI)   for   the   spring   Chinook   salmon   run   within   the   investigation   domain   of   the   SJR.   Three   proposed   alternatives   for   the   San   Joaquin   River   Restoration   Program   (SJRRP)   were   compared   based   on   both   their   hydrodynamic   and   SI   aspects.   All   three   alternatives   showed  similar  SI  distributions  under  the  same  boundary   conditions.  Alternatives   2   and   3   produced   higher   overall   Weighted  Area  Habitat  Suitability  Index  (WAHSI)  values   than  Alternative  1,  indicating  that  these  alternatives  could   lead  to  a  better  environment  for  salmon  migration.  There   exist  fair  correlations  between  the  WAHSI  values  and  the   boundary  conditions.  The  lag  time  that  produced  the  best   correlation   between   salmon   habitat   suitability   and   upstream   discharge   was   around   50   days   based   on   the   cross-­‐‑correlation   calculations.   The   WAHSI   and   the   downstream   Water   Surface   Elevation   (WSE)   values   change   synchronically.   This   study   demonstrates   that   the   boundary   conditions   may   help   predict   habitat   suitability   14 Int. j. water sci., 2013, Vol. 2, 5:2013 for  salmon  by  using  the  hydrodynamic  model  for  the  SJR.   The   modelling   method,   together   with   the   correlation   results  reported  here,  may  provide  a  reference  for  similar   suitability  studies  of  salmon  habitat  in  other  inland  rivers.     7.  Acknowledgements     The  observed  data,  including  the  discharge,  water  surface   elevation   and   bathymetry   data,   used   in   this   paper   for   model   validation   and   calibration   were   provided   by   the   California   Department   of   Water   Resources,   the   U.S.   Geological   Survey   (USGS)   and   the   U.S.   Bureau   of   Reclamation   (USBR),   respectively.   Special   thanks   go   to   our   colleague,   Dr   John   Suen   of   the   Department   of   Earth   and   Environmental   Sciences   of   California   State   University,   Fresno,   whose   help   in   reviewing   the   manuscript  and  the  many  stimulating  exchanges  we  have   enjoyed   during   the   course   of   this   project   have   greatly   improved  the  outcome.   8.  References   [1]   California   Water   Plan   Update   2009  Integrated   Water   Management   (2009)   San   Joaquin   River   Hydrological   Region  Vol.  3  Available:       http://www.waterplan.water.ca.gov/.   Accessed   2013   April  10.   [2]   Gronberg   JM,   Dubrovsky   NM,   Kratzer   CR,   Domagalski   JL,   Brown   LR,   Burow   KR   (1998)   Environmental   Setting   of   the   San   Joaquin-­‐‑Tulare   Basins,   California.   U.S.   Geological   Survey   Water-­‐‑ Resources  Investigations  Report  97-­‐‑4205,  45  p.   [3]   Herbold   B,   Moyle   PB   (1989)   The   Ecology   of   the   Sacramento-­‐‑San   Joaquin   Delta:   A   Community   Profile.   Report   prepared   for   the   U.S.   Department   of   the   Interior,   Fish   and   Wildlife   Service.   Biological   Report  85(7.22).  107  p.   [4]   Yoshiyama   R,   Fisher   F,   Moyle   P   (1998)   Historical   Abundance   and   Decline   of   Chinook   Salmon   in   the   Central  Valley  Region  of  California.  North  American   Journal  of  Fisheries  Management,  18(3):  487-­‐‑521   [5]   California  Department  of  Water  Resources  (2013)  San   Joaquin   River   Restoration   Program   Overview.   Available:   http://www.water.ca.gov/rivers/sanjoaquin/program/.   Accessed  2013  Mar  15.   [6]   San   Joaquin   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