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Agricultural Modeling

Permanent Link: http://ncf.sobek.ufl.edu/NCFE004248/00001

Material Information

Title: Agricultural Modeling Predicting the effects of genetic coefficients on maize yield in waterlimiting environments
Physical Description: Book
Language: English
Creator: Farrell, Anne Amelia
Publisher: New College of Florida
Place of Publication: Sarasota, Fla.
Creation Date: 2010
Publication Date: 2010

Subjects

Subjects / Keywords: Agricultural Modeling
Maize
Corn
Agriculture
Drought
Aquacrop
DSSAT
Genetics
Coefficients
Genre: bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Limited water availability threatens agricultural efficiency, as crops require suffice water for maximum yields and productivity. As human populations grow, water will become more of a concern. Increased water demands require agriculture to compete with municipalities if agriculture is going to feed the masses. I reviewed two models that will soon aid scientists in determining plant modifications to produce marketable yields with available water. Therefore, an overview of drought tolerance in maize is discussed. Genetics and agronomy are two scientific fields that will aid the identification of specific traits or genetic coefficients to improve drought tolerance in crops. Scientists need improved options to predict effects of genetic traits on drought response. Two mathematical models, AquaCrop and CERES-Maize, are available to make rapid predictions and they illustrate physiological and ecological response. These models can serve as powerful tools to advance the science of crop yield improvements. Parameter changes in each model showed maize performance under water stress within 10% of the normal range. Yields were affected by changing the genetic coefficients within each model.. The impact of trait modification was evaluated within each program by comparing resulting yields. A 10% change in DSSAT CERES-Maize filling-rate coefficient resulted in the most yield increases. However, a 10% increase in Aquacrop rooting depth, resulted in the most yield increases. Therefore, CERES-Maize and AquaCrop models have potential uses in predicting and understanding genetic coefficients in maize.
Statement of Responsibility: by Anne Amelia Farrell
Thesis: Thesis (B.A.) -- New College of Florida, 2010
Electronic Access: RESTRICTED TO NCF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE
Bibliography: Includes bibliographical references.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Local: Faculty Sponsor: McCord, Jr., Elzie

Record Information

Source Institution: New College of Florida
Holding Location: New College of Florida
Rights Management: Applicable rights reserved.
Classification: local - S.T. 2010 F2
System ID: NCFE004248:00001

Permanent Link: http://ncf.sobek.ufl.edu/NCFE004248/00001

Material Information

Title: Agricultural Modeling Predicting the effects of genetic coefficients on maize yield in waterlimiting environments
Physical Description: Book
Language: English
Creator: Farrell, Anne Amelia
Publisher: New College of Florida
Place of Publication: Sarasota, Fla.
Creation Date: 2010
Publication Date: 2010

Subjects

Subjects / Keywords: Agricultural Modeling
Maize
Corn
Agriculture
Drought
Aquacrop
DSSAT
Genetics
Coefficients
Genre: bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Limited water availability threatens agricultural efficiency, as crops require suffice water for maximum yields and productivity. As human populations grow, water will become more of a concern. Increased water demands require agriculture to compete with municipalities if agriculture is going to feed the masses. I reviewed two models that will soon aid scientists in determining plant modifications to produce marketable yields with available water. Therefore, an overview of drought tolerance in maize is discussed. Genetics and agronomy are two scientific fields that will aid the identification of specific traits or genetic coefficients to improve drought tolerance in crops. Scientists need improved options to predict effects of genetic traits on drought response. Two mathematical models, AquaCrop and CERES-Maize, are available to make rapid predictions and they illustrate physiological and ecological response. These models can serve as powerful tools to advance the science of crop yield improvements. Parameter changes in each model showed maize performance under water stress within 10% of the normal range. Yields were affected by changing the genetic coefficients within each model.. The impact of trait modification was evaluated within each program by comparing resulting yields. A 10% change in DSSAT CERES-Maize filling-rate coefficient resulted in the most yield increases. However, a 10% increase in Aquacrop rooting depth, resulted in the most yield increases. Therefore, CERES-Maize and AquaCrop models have potential uses in predicting and understanding genetic coefficients in maize.
Statement of Responsibility: by Anne Amelia Farrell
Thesis: Thesis (B.A.) -- New College of Florida, 2010
Electronic Access: RESTRICTED TO NCF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE
Bibliography: Includes bibliographical references.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Local: Faculty Sponsor: McCord, Jr., Elzie

Record Information

Source Institution: New College of Florida
Holding Location: New College of Florida
Rights Management: Applicable rights reserved.
Classification: local - S.T. 2010 F2
System ID: NCFE004248:00001


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PAGE 1

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PAGE 18

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PAGE 27

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! VJ 6&/?)3&!2&)%=!21)(3!*,51%4!3.&!?,&')/&!58!?,&4):3)%=!#)&(4!1%4&,!;*3&,! /3,&//G! $@1*<,5? !.*/!%53!2&&%!*!?&,8&:3!?,&4):35,!85,!;* 3&,!1/&!&88):)&%:#!cNCEeD! E7&33!*%4!-5(L! cIJJ]e !,&')%4&4!1/!)%!3.&),!4)/:1//)5%!58!'54&(/!*%4!NCE! G!_&5,=&! "5Q!5%:&!/*)4G!*%4!i$((!'54&(/!*,&!;,5%=!213!/5'&!*,&!1/&81(jD!!0)'1(*3&4!NCE!2#! 5(4&,!'54&(/!*%4!3.&!'5,&!,&:&%3! $@1*<,5? !:*%!2&!)%*::1,*3&!1%4&,!:5%4)3)5%/!58! ;*3&,!/3,&//G!213!3.)/!45&/!%53!'&*%!3.&,&!.*/!%53! 2&&%!*%!)'?,57&'&%3!)%! '54&()%=D!! $@1*<,5? G!*/!;&((!*/!'5/3!&Q)/3)%=!'54&(/G!)/!*!4&7&(5?)%=!355(! cE7&33! *%4!-5(L!IJJ]e D!$/!:,5?!'54&(/!*,&!'5,&!:5%/)/3&%3(#!1/&4!85,! '*%*=&'&%3!*%4! ),,)=*3)5%! 4&:)/)5% !'*L)%= G!)3!)/!%&:&//*,#!3.*3!;&!:5%3)%1&!35!)'?,57&!3.&!*::1,*:#! 58!NCE!&/3)'*3 )5%/! cE7&33!*%4!-5(L!IJJ]e D!!>'?,57)%=!NCE!*::1,*:#!)%!'54&(/!;)((! :5,,&(*3&!;)3.!3.&!*2)()3#!58!3.&!/583;*,&!35!.*%4(&!&7*?5,*3)5%!*%4!3,*%/?),*3)5%!*/! /&?*,*3&!:5'?5%&%3/!58!&7*?53,*%/?),*3)5%D!<*%5?#G!,&/)41&!'*%*=&'&%3G!3)((*=&! ?,*:3):&/G!*%4!),,)=*3)5%!'&3.54/!=,&*3(#!)'?*:3! &7*?5,*3)5%!cEe!*%4!'1/3!2&! )%:5,?5,*3&4!;&((!)%35!*!'54&(D!0)'1(*3)%=!:,5?/!1%4&,!:5%4)3)5%/!3.*3!:*1/&!*! ,&41:3)5%!58!&7*?53,*%/?),*3)5%!;.)(&!13)()F)%=!/&?*,*3&!'&*/1,&/!58!&7*?5,*3)5%! *%4!3,*%/?),*3)5%G!;)((!*((5;!*%#!/)'1(*3)5%!,&/1(3/!,&(&7*%3!35!&7* ?5,*3)5%! ,&41:3)5%!&88&:3/!5%!NCE!35!2&!7&,)8)&4! cE7&33!*%4!-5(L!IJJ]e D <#,&=.#$&)0 % $@1*<,5? !.*/!1%4&,=5%&!)%3&%/&!:*()2,*3)5%!85,!%5% O ()')3)%=!:5%4)3)5%/G! ;*3&,!/3,&//G!*%4!=&5=,*?.):*(!:57&,*=&!)%!*,&*/!3.*3!3#?):*((#!=,5;!*!/?&:)8):!:,5?D!! >4&*((#G!)%)3)*(!:*()2,*3)5%!,&7&*(/!8 1%4*'&%3*(!?*,*'&3&,/!3.*3!:*%!*??(#!35!'*%#! 4)88&,&%3!:1(3)7*,/!58!*!/?&:)8):!:,5?D!!>%!,&*()3#G!*(3.51=.!'*%#!?*,*'&3&,/!.5(4!3,1&!

PAGE 38

! VK 85,!5%&!/?&:)&/G!53.&,!?*,*'&3&,/!,&@1),&!*4f1/3'&%3!)%!5,4&,!35!'54&(!*!%&;! :1(3)7*,D!!U*,*'&3&,/!3.*3!583&%!,&@1),&!:.*%= &!85,!%&;(#!'54&(&4!:1(3)7*,/!)%:(14&! :5&88):)&%3/!3.*3!4&/:,)2&!3.&!3)')%=!*%4!41,*3)5%!58!4&7&(5?'&%3*(!/3*=&/D!!! <1(3)7*,/!3.*3!*,&!2&)%=!)%3,541:&4!35!3.&!'54&(!/.51(4!2&!&7*(1*3&4!1/)%=!3.&! ?,&7)51/(#!:*()2,*3&4!?*,*'&3&,/!85,!3.&!=&%&,):!/?&:)&/! c03&4135!*%4!53.&,/!IJJ]e G! 1%3)(!3.&!'54&(!:*%!2&!8)33&4!35!3.&!:1(3)7*,g/!/?&:)8):!3,*)3/D >$#/+'%)2%?+4+,)@(+0$ $@1*<,5? !4&/:,)2&/!4&7&(5?'&%3!*/!4*#/!8,5'!/5;)%=D!!-.)/!)%:(14&/! &'&,=&%:&G!'*Q)'1'!:*%5?#!4&7&(5 ?'&%3G!8(5;&,)%=G!3.&!/3*,3!58!:*%5?#! /&%&/:&%:&G!'*Q)'1'!,553)%=!4&?3.G!*%4!'*31,)3#D!!C/&,/!:*%!*(/5!7)&;!3.&/&!4*#/! :5'?)(&4!)%35!+$d O ZY!/3*=&/G!;.):.!*,&!3.&!4*#/!35!)%)3)*(!/3*=&!c1?!35!KJb!=,51%4! :57&,eG!81((!:*%5?#!4&7&(5?'&%3G!')4/&*/5%!/3*=&!c8,5' !81((!:57&,!35!'*31,)3#eG!*%4! 3.&!(*3&!/&*/5%!/3*=&!c/3*,3!58!'*31,)3#!35!81((!/&%&/:&%:&eD !#$+.%'$.+'' % N*3&,!/3,&//!:5%3,) 213&/!851,!&88&:3/!35!3.&!'54&(D!> 3!:.*%=&/!3.&!,*3&!58!(&*8! =,5;3.G!*4f1/3/!/35'*3*(!:5%41:3*%:&G!*::&(&,*3&/!/&%&/:&%:&G!*%4!:.*%=&/!.*,7&/3! )%4):&/!cM>eD!$((!&88&:3/G!&Q:&?3!M>G!*,&!,&?,&/&%3&4!2#!3.&),!/3,&//!:5&88):)&%3/!c[/eG! ;.):.!)%4):*3&!3.&!,&(*3)7&!)%3&%/)3#!58!3.&!/3,&//5,D!M>! 45&/!%53!.*7&!*!,&(*3&4![/! 2&:*1/&!3.&!&88&:3/!58!/3,&//!5%!M>!*,&!4&?&%4&%3!5%!3.&![/!58!(&*8!=,5;3.!*%4! /35'*3*(!:5%41:3*%:&G!*/!;&((!*/!)%4),&:3(#!*//5:)*3&4!;)3.!3.&![/!85,!/&%&/:&%:&! c03&4135!*%4!53.&,/!IJJ] e D!![/! 7*(1&/!,*%=& !8,5'!K!c%5%&Q)/3&%3e!35!J!c'*Q)'1'eD!!

PAGE 39

! VI N*3&,!/3,&//!)/!,&?,&/&%3&4!2#![/!3.*3!)/!*!81%:3)5%!58!;*3&,!:5%3&%3!;)3.)%!3.&!,553! F5%&! c03&4135!*%4!53.&,/!IJJ]e D [/!3.,&/.5(4/!*,&!,&?,&/&%3&4! */!*!8,*:3)5%!c?e!58!353*(!*7*)(*2(&!/5)(!;*3&,! c-$NeD!!>%!5,4&,!35!'*)%3*)%!:*%5?#!=,5;3.G!3.&!8,*:3)5%!'1/3!2&!(&//!3.*%!5%&!c?!n! Ke!)%!5,4&,!35!L&&?!3.&!(5;&,!3.,&/.5(4!*257&!3.&!?&,'*%&%3!;)(3)%=!?5)%3!cUNUeG! 213!3 5!*88&:3!/35'*3*!*%4!/&%&/:&%:&D!.&!( 5;&,!3.,&/.5(4!)/!&Q*:3(#!*3!3.&!UNUG! ;.&,&!?oKD!!-.&!/.*?&!58![/!:1,7&G!:5%/&,7*3)7&(#!()%&*,!5,!:5%7&QG!)((1/3,*3&/!3.&! '*=%)314&!58!3.&!,&/1(3/!58!;*3&,!/3,&//! cW*&/!*%4!53.&,/!IJJ]e G!*%4!:*%!2&!/&& %!)%! +)=1,&!VD! I D!! -.&!/.*?&!58!3.&!:1,7&!*%4!4&=,&&!58!3.&!&88&:3!*,&!:*(:1(*3&4!1/)%=! E@1*3)5%!VD! I a 0 Ks = 1 # e D rel $ f shape # 1 e f shape # 1 1 IJ&)($,/*C;* B W)(.#*N(#.44*?&#:.; *L #.'* MXAQ*#.@#.4./(4*#.')($:.*-.@'.($,/;*Y.')($:.*-.@'.($,/*$4*(2.* 3#)%($,/*,3* 8)(.#*.T2)&4(.-*#.')($:.*(,*(2.*5)T$5&5*8)(.#*2,'-$/"*%)@)%$(7*,3*(2.*4,$';**H 42)@.* $4*(2.* 42)@.*3)%(,#* MY).4*)/-*,(2.#4*BOOPQ ; !!

PAGE 40

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PAGE 41

! VX ET = # ( R n $ G ) + % a c p ( e s $ e a ) r a # + & ( 1 + r s r a ) IJ&)($,/*C;* C *1./5)/ 9 +,/(.$(2*.J&)($,/*3,#*#.3.#./%.*.:)@,(#)/4@$#)($,/ % A"+.(#,%$&(+%#0*%B.)5&0/%?+/.++ C ?#D' % W*3.&,!3.*%!1/)%=!*!3)' & !/:*(&!2*/&4!5%!/&*/5%/!5,!'5%3./G! $@1*<,5? 13)()F&/!*!3)'&/:*(&!58!4*)(#!/3&?/G!5,!=,5;)%=!4&=,&& O 4*#/!c_66eG!;.):.!)/!'5,&! :(5/&(#!:5,,&(*3&4!35!3.&!3)'&!/:*(&!58!:,5?!,&/?5%/&!35!;*3&,!4&8):)3! c03&4135!*%4! 53 .&,/!IJJ]e D!_,5;)%=!4&=,&& O 4*#/!!c_66e!*,&!*!'&*/1,&!58!.&*3!*::1'1(*3)5%!3.*3! )%8(1&%:&/!3.&!=,5;3.!*%4!4&7&(5?'&%3!3)')%=!58!3.&!:,5?D!!>%!3.)/!?*,3):1(*,!'54&(G! _66!)/!:*(:1(*3&4!1/)%=!3.&!B:B*/3&,!*%4!N)(.&('!'&3.54G!;)3.!*!'54)8):*3)5%!3.*3! *((5;/! 3.&!'54&(!35!)%:5,?5,*3&!4*'*=&!:*1/&4!2#!3&'?&,*31,&/!2&(5;!3.&! 4&/)=%*3&4!2*/&!3&'?&,*31,&! c03&4135!*%4!53.&,/!IJJ]e D >)&, % $@1*<,5? !:5%/)4&,/!/5)(!(*#&,/!58!7*,)*2(&!4&?3.!*%4!3&Q31,&/!2*/&4!5%!3.&! 3&Q31,*(!:(*//&/!)%!3.&!C06$!3,)*%=(&!c +)=1,&!VD! V eD!-.&!/5)(!:5'?5%&%3!'*L&/! ?,57)/)5%/!85,!8)&(4!:*?*:)3#!c1??&,!()')3!:*?*:)3#G! +< eG!3.&!?&,'*%&%3!;)(3)%=!?5)%3 !! c(5;&,!()')3!58!:*?*:)3#eG!*!4,*)%*=&!:5&88):)&%3!c $ eG!*%4!i.#4,*1():!:5%41:3)7)3#j! ;.&%!3.&!/5)(!)/!/*31,*3&4!c[ /*3 eD!!U&453,*%/8&,!81%:3)5%/!c81%:3)5%/!3.*3!?,&4):3!/5)(! ?,5?&,3)&/!8,5'!53.&,!*7*)(*2(&!5,!&*/)(#!'&*/1,&4!?,5?&,3)&/e!&/3)'*3&!3.&! .#4,*1 ():!:.*,*:3&,)/3):/!58!* !=)7&%!/5)(G!5,!3.&!'54&(!:*%!13)()F&!)%?13!7*(1&/D

PAGE 42

! VZ H$"&#.*C;* C *[NL!*N,$'4*(#$)/"'.*3#,5*4,$'4;&4-);",: -.&!'54&(!*??()&/!*!4*)(#!;*3&,!2*(*%:&!&@1*3)5%!3.*3!:5%/)4&,/!3.&! ?,5:&//&/!)%!;*3&, O ?(*%3!,&(*3 )5%/.)?/G!)%:(14)%=!)%8)(3,*3)5%G!,1%588G!4,*)%*=&G!,553! F5%&G!;*3&,!*7*)(*2)()3#G!&7*?5,*3)5%G!3,*%/?),*3)5%G!*%4!i:*?)((*,#!,)/&jD !!>%:5')%=! *%4!513=5)%=!;*3&,!8,5'!3.&!,553!F5%&!)/!3,*:L&4!*/!1?3*L&!*%4!)/!/)'1(*3&4!2#! :*(:1(*3)%=!*!,553!&Q3,*:3)5%!3&,' !0!c' V O V 4 O K e! c03&4135!*%4!53.&,/!IJJ]e D!! 0 Q !)/!3.&!'*Q)'1'!&Q3,*:3)5%!3&,'!*%4!)3!)/!1/&4!35!:*(:1(*3&!0!*3!*!/5)(!4&?3.! & !)%!3.& !&@1*3)5% 0 )! o![ / & Q!0 /G) IJ&)($,/*C;* D

PAGE 43

! VY ;.&,&![/ & )/!3.&!;*3&,!/3,&//!:5&88):)&%3!*3!*!?*,3):1(*,!4&?3.G!3#?):*((#![/ /35 !85,! /3,&//!3.* 3!)/!()')3)%=!/35'*3*(!5?&%)%=D !! -.&!&Q3,*:3)5%!,*3&!3.&%!*88&:3/! 3,*%/?),*3)5%!3.,51=. T = 1000( Ks i Sx i ) bottom top # !G! F! # ![/!Q!Q IJ&)($,/*C;* E W)3:.)&g/!*??,5*:.!)/!1/&4!35!:*(:1(*3&!/5)(!&7*?5,*3)5%G!213!5%(#!:5%/)4&,!3.&! &%&,=#!()')3&4!?.*/&!*%4!3.&!?.*/&!()')3&4!2#!3.&!3,*%/?5,3!58!;*3&,!35!3.&!/5)(! /1,8*:&D!! $@1*<,5? !13)()F&/!*!81%:3)5%!3.*3!4&?&%4/!5%!3.&!;*3& ,!:5%3&%3!58!3.&!3.)%! 35?!/5)(!(*#&,!;.):.!)'?,57&/!3.&!&/3)'*3)5%!58!&7*?5,*3)5%!1%4&,!*!;)4&!,*%=&!58! :5%4)3)5%/! c03&4135!*%4!53.&,/!IJJ]e D! 05)(!)/!:5'?5/&4!58!*!4&8*1(3!58!KI!:5'?*,3'&%3/!;)3.!*!4&?3.!58! FD!!-.&!/)F&! 58!3.&/&!:5'?*,3'&%3/!)/!*4f1/3&4!2#!3.&!/583;*,&!35!&%:5'?*//!3.&!&%3),&!,553! F5%&!*%4!)/!*4f1/3&4!&Q?5%&%3)*((#!;)3.!4&?3.!/)%:&!&7*?5,*3)5%!4#%*'):/!*3!3.&! /1,8*:&!,&@1),&/!'5,&!4&3*)(!3.*%!&7*?5,*3)5%!8,5'!25335'!(*#&,/D!!M#4,*1():! :.*,*:3 &,)/3):/!*,&!4&8)%&4!2#!3.&!*??,5?,)*3&!/?&:)8)&4!/5)(!.5,)F5%/D!!N*3&,! '57&'&%3!*%4!,553!1?3*L&!*,&!:*(:1(*3&4!2#!&@1*3)5%/!4&8)%&4!2#!3.&!4&?&%4&%3! 7*,)*2(&! G!13)()F)%=!*!4,*)%*=&!:5&88):)&%3! $ D!! $ !)/!4&,)7&4!8,5'![ /*3 !85,!45;%;*,4! ;*3&,!'57&'&%3! cW*&/!*%4!53.&,/!IJJ]e D! -.&!&@1*3)5%/!85,!/5)(!;*3&,!)%:(14&!4,*)%*=&G!/1,8*:&!,1%!588G!*%4!/5)(! &7*?5,*3)5%D!!-.&!&@1*3)5%/!*,&!()/3&4!2&(5; !)%! 85((5;)%=!3.,&&!&@1*3)5%/ D 05)(!;*3&,!)/!*88&:3&4!2#!3.&!&@1*3)5%!85,!4,*)%*=&G!/.5;%!)%! E@1*3)5%!VD! Y D

PAGE 44

! VT IJ&)($,/*C;* F MY).4*)/-*,(2.#4*BOOPQ 01,8*:&!,1% O 588!)/!'54&(&4!2#!C06$!'&3.54!13)()F)%=!:1,7&!%1'2&,/!3.*3!*,&! *4f1/3&4!85,!*%3&:&4 &%3!'5)/31,&!:(*//&/D!!05)(!&7*?5,*3)5%!:5%/)/3/!58!3;5!/3*=&/D!! -.&!8),/3!)/!*%!&%&,=#!()')3)%=!/3*=&D!!-.&!:1'1(*3)7&!&7*?5,*3)5%!41,)%=!3.)/!/3*=&G! ,&8&,,&4!35!*/!WENG!)/!:*(:1(*3&4!2#! E@1* 3)5%!VD! T !8 5,!3.&!/1,8*:&!(*#&,!5%(#G IJ&) ($,/*C;* \ ;.&,&! *),!4,# !)/!/5)(!;*3&,!:5%3&%3!;.&%!3.&!*),!)/!4,#P!*%4!k &G/1,8 !)/!3.&!3.):L%&//!58! 3.&!&7*?5,*3)%=!/1,8*:&!(*#&,! cW*&/!*%4!53.&,/!IJJ]e D -.&!/&:5%4!)/!*!8*(()%=!,*3&!/3*=&G!*/!;*3&,!2&:5'&/!' 5,&!4)88):1(3!35! 3,*%/?5,3!8,5'!(5;&,!/5)(!(*#&,/D!!B1(:.)%=!?,*:3):&/!*88&:3! 3.)/!&@1*3)5%G!213!85,! 1%'1(:.&4!/5)(!3.&!85((5;)%=!&@1*3)5%!VDY!.5(4/D ;.&,&![ :G;&3! )/!3.&!&7*?5,*3)5%!:5&88):)&%3!85,!/*31,*3&4!*%4!1%/.*4&4!/5)(D!! -.&!4&8*1(3!7*(1&!)/!KDKJ! cW*&/!*%4!53.&,/!IJJ]e D![,!)/!&7*?5,*3)5%!,&41:3)5%! :5&88):)&%3G!&@1*(!35!K!41,)%=!3.&!8),/3!/3*=&!58!&7*?5,*3)5%D!N.&%!/3*=&!>!&%4/G![,! *4f1/3/!35 !2&:5'&!(&//!3.*%!5%&!*/!;*3&,!(&*7&/!3.&!35?!(*#&,!58!/5)(!ck &G35? eD!!0)%:&! !!"#$%&'(')*#+',&(-.#/#0'.,)1#2324#566,1#7#/#"338 !"#$%&'()*+!,-+ .!"./"!'&$,+0%$.1-/%1* Details are given for algorithms and calculation procedures used by AquaCrop to model the concepts presented by Steduto et al. (2009). Some emphasis is placed on the soil water balance, because a number of the equations for crop and biomass development and for nal yield are presented by Steduto et al. (2009). To accurately describe the retention, movement, and uptake of water in the soil pro le throughout the growing season, AquaCrop divides the soil pro le into small fractions. e soil pro le is divided into soil compartments (12 by default) with thickness z (0.10 m by default). However, AquaCrop will adjust the size of the compartments to cover the entire root zone. For deep root zones, z is not constant but increases exponentially with depth, so that in ltration, evaporation (E), and transpiration (Tr) from the top soil layers can be described with su # cient detail. e hydraulic characteristics of each compartment are that of the soil horizon to which it belongs. e soil water movement and root water uptake are simulated by a set of equations in terms of the dependent variable, using a dimensionless drainage coe # cient ( # ) as derived from K sat (Raes et al., 2006) for downward water movement in the pro le. -2345367 Drainage occurs when of a compartment is above FC. The amount of water that drains out of compartment i at time step t, is described by an exponential drainage function that takes into account the water content ( i ) and the drainage characteristic of the soil layer (Raes, 1982; Raes et al., 1988, 2006): FC satFC satFC 1 ( ) t 1 i i e e !! !! "! = #!! ! [3] where !" i / t is the decrease during t (m 3 m 3 d 1 ). When # is close to one, a thoroughly wetted soil will drain in 1 or 2 d to FC. Low values of # result in the slow drainage of the soil profile. To simulate internal drainage in a profile composed of various compartments, not necessarily equally wet and may belong to soil layers with different # values, the calculation procedure considers the drainage ability ( !" i / t) of the different compartments. The assumption made is that the total drainage of the compartments above will pass through the compartment below that has a drainage ability greater than or equal to that of the compartment above. By comparing drainage abilities and not water contents, the calculation procedure is independent of the soil layer, to which successive compartments may belong. If a compartment is reached with drainage ability smaller than the one above, the excess is stored in that compartment, thereby increasing its water content and its drainage ability. The drainage function used in AquaCrop mimics very well the infiltration and internal drainage observed in the field (Garcia Cardenas, 2003; Raes et al., 2006; Descheemaeker, 2006; Geerts et al., 2008). *8293:7+%85;$99+35<+&5 +=>23>4?5 Surface run-o $ is simulated by the curve number method (USDA, 1964; Rallison, 1980; Steenhuis et al., 1995). e speci ed Curve Number (CN II ) is adjusted for the simulated wetness of the top soil layer. Relationships derived from Smedema and Rycro % (1983), presenting corresponding CN values for antecedent moisture class (AMC) I (dry), II, and III (wet), are used. A soil depth of 0.3 m is considered by default when calculating the AMC. For simplicity, irrigation is assumed to be fully controlled; hence, the runo $ subroutine (for rainfall) is bypassed for irrigation water in ltration and tailwater is assumed to be zero. If surface runo $ from the eld is important when irrigating, the above assumption requires that irrigation be speci ed as a net application amount. e maximum amount that can in ltrate the soil, either as rainfall or irrigation, is however limited by K sat of the topsoil layer. A % er in ltrating into the soil, the water is stored in successive compartments from the top downward, governed by the limit imposed by the drainage ability ( !" i / t) of the di $ erent compartments. *?4=+1@3A?23>4?5 Evaporation from soil takes place in two stages (Philip, 1957; Ritchie, 1972): an energy limiting stage (Stage I) and a falling rate stage (Stage II), when water transport to the surface from layers below is limiting. In AquaCrop, the cumulative Stage I evaporation (REW) is estimated as: REW = 1000 & ( FC air dry ) & Z e, surf [4] where air dry is soil water content (m 3 m 3 ) when air dry, and Z e,surf the thickness (m) of the evaporating surface layer. By assuming air dry to be half of PWP and 40 mm for Z e,surf an agreement was found between REW and the cumulative evaporation for the energy limiting stage (Stage I evaporation), that is, the U value of Ritchie (1972). As long as readily evaporable water remains in the surface layer, E is in the energy limiting stage, and the rate is the maximum rate (E x ). When all the REW is gone from the surface layer, E switches to the falling rate stage (Stage II) and water ( ows from the soil layer below (Z e,top ) to the surface layer. For bare soil, evaporation is described by the following equation, for both stages: E = Kr & E x = Kr & Kc e, wet & ET o [5] where Kc e, wet is the evaporation coe # cient for fully wet and unshaded soil surface with a default value of 1.10 (Allen et al., 1998), and Kr ( ) 1) is the dimensionless evaporation reduction coe # cient, and is 1 during Stage I evaporation. As Stage I ends and Stage II begins, Kr decreases below 1 as water is depleted from Z e,top (Fig. 4). To account for the sharp decline in hydraulic conductivity with decreasing soil water content, an exponential equation is used to relate Kr to relative water content of the soil layer (W rel ): rel fW f exp 1 0 Kr = 1 exp 1 K K $ %% [6] !!"#$%&'(')*#+',&(-.#/#0'.,)1#2324#566,1#7#/#"338 !"#$%&'()*+!,-+ .!"./"!'&$,+0%$.1-/%1* Details are given for algorithms and calculation procedures used by AquaCrop to model the concepts presented by Steduto et al. (2009). Some emphasis is placed on the soil water balance, because a number of the equations for crop and biomass development and for nal yield are presented by Steduto et al. (2009). To accurately describe the retention, movement, and uptake of water in the soil pro le throughout the growing season, AquaCrop divides the soil pro le into small fractions. e soil pro le is divided into soil compartments (12 by default) with thickness z (0.10 m by default). However, AquaCrop will adjust the size of the compartments to cover the entire root zone. For deep root zones, z is not constant but increases exponentially with depth, so that in ltration, evaporation (E), and transpiration (Tr) from the top soil layers can be described with su # cient detail. e hydraulic characteristics of each compartment are that of the soil horizon to which it belongs. e soil water movement and root water uptake are simulated by a set of equations in terms of the dependent variable, using a dimensionless drainage coe # cient ( # ) as derived from K sat (Raes et al., 2006) for downward water movement in the pro le. -2345367 Drainage occurs when of a compartment is above FC. The amount of water that drains out of compartment i at time step t, is described by an exponential drainage function that takes into account the water content ( i ) and the drainage characteristic of the soil layer (Raes, 1982; Raes et al., 1988, 2006): FC satFC satFC 1 ( ) t 1 i i e e !! !! "! = #!! ! [3] where !" i / t is the decrease during t (m 3 m 3 d 1 ). When # is close to one, a thoroughly wetted soil will drain in 1 or 2 d to FC. Low values of # result in the slow drainage of the soil profile. To simulate internal drainage in a profile composed of various compartments, not necessarily equally wet and may belong to soil layers with different # values, the calculation procedure considers the drainage ability ( !" i / t) of the different compartments. The assumption made is that the total drainage of the compartments above will pass through the compartment below that has a drainage ability greater than or equal to that of the compartment above. By comparing drainage abilities and not water contents, the calculation procedure is independent of the soil layer, to which successive compartments may belong. If a compartment is reached with drainage ability smaller than the one above, the excess is stored in that compartment, thereby increasing its water content and its drainage ability. The drainage function used in AquaCrop mimics very well the infiltration and internal drainage observed in the field (Garcia Cardenas, 2003; Raes et al., 2006; Descheemaeker, 2006; Geerts et al., 2008). *8293:7+%85;$99+35<+&5 +=>23>4?5 Surface run-o $ is simulated by the curve number method (USDA, 1964; Rallison, 1980; Steenhuis et al., 1995). e speci ed Curve Number (CN II ) is adjusted for the simulated wetness of the top soil layer. Relationships derived from Smedema and Rycro % (1983), presenting corresponding CN values for antecedent moisture class (AMC) I (dry), II, and III (wet), are used. A soil depth of 0.3 m is considered by default when calculating the AMC. For simplicity, irrigation is assumed to be fully controlled; hence, the runo $ subroutine (for rainfall) is bypassed for irrigation water in ltration and tailwater is assumed to be zero. If surface runo $ from the eld is important when irrigating, the above assumption requires that irrigation be speci ed as a net application amount. e maximum amount that can in ltrate the soil, either as rainfall or irrigation, is however limited by K sat of the topsoil layer. A % er in ltrating into the soil, the water is stored in successive compartments from the top downward, governed by the limit imposed by the drainage ability ( !" i / t) of the di $ erent compartments. *?4=+1@3A?23>4?5 Evaporation from soil takes place in two stages (Philip, 1957; Ritchie, 1972): an energy limiting stage (Stage I) and a falling rate stage (Stage II), when water transport to the surface from layers below is limiting. In AquaCrop, the cumulative Stage I evaporation (REW) is estimated as: REW = 1000 & ( FC air dry ) & Z e, surf [4] where air dry is soil water content (m 3 m 3 ) when air dry, and Z e,surf the thickness (m) of the evaporating surface layer. By assuming air dry to be half of PWP and 40 mm for Z e,surf an agreement was found between REW and the cumulative evaporation for the energy limiting stage (Stage I evaporation), that is, the U value of Ritchie (1972). As long as readily evaporable water remains in the surface layer, E is in the energy limiting stage, and the rate is the maximum rate (E x ). When all the REW is gone from the surface layer, E switches to the falling rate stage (Stage II) and water ( ows from the soil layer below (Z e,top ) to the surface layer. For bare soil, evaporation is described by the following equation, for both stages: E = Kr & E x = Kr & Kc e, wet & ET o [5] where Kc e, wet is the evaporation coe # cient for fully wet and unshaded soil surface with a default value of 1.10 (Allen et al., 1998), and Kr ( ) 1) is the dimensionless evaporation reduction coe # cient, and is 1 during Stage I evaporation. As Stage I ends and Stage II begins, Kr decreases below 1 as water is depleted from Z e,top (Fig. 4). To account for the sharp decline in hydraulic conductivity with decreasing soil water content, an exponential equation is used to relate Kr to relative water content of the soil layer (W rel ): rel fW f exp 1 0 Kr = 1 exp 1 K K $ %% [6] !!"#$%&'(')*#+',&(-.#/#0'.,)1#2324#566,1#7#/#"338 !"#$%&'()*+!,-+ .!"./"!'&$,+0%$.1-/%1* Details are given for algorithms and calculation procedures used by AquaCrop to model the concepts presented by Steduto et al. (2009). Some emphasis is placed on the soil water balance, because a number of the equations for crop and biomass development and for nal yield are presented by Steduto et al. (2009). To accurately describe the retention, movement, and uptake of water in the soil pro le throughout the growing season, AquaCrop divides the soil pro le into small fractions. e soil pro le is divided into soil compartments (12 by default) with thickness z (0.10 m by default). However, AquaCrop will adjust the size of the compartments to cover the entire root zone. For deep root zones, z is not constant but increases exponentially with depth, so that in ltration, evaporation (E), and transpiration (Tr) from the top soil layers can be described with su # cient detail. e hydraulic characteristics of each compartment are that of the soil horizon to which it belongs. e soil water movement and root water uptake are simulated by a set of equations in terms of the dependent variable, using a dimensionless drainage coe # cient ( # ) as derived from K sat (Raes et al., 2006) for downward water movement in the pro le. -2345367 Drainage occurs when of a compartment is above FC. The amount of water that drains out of compartment i at time step t, is described by an exponential drainage function that takes into account the water content ( i ) and the drainage characteristic of the soil layer (Raes, 1982; Raes et al., 1988, 2006): FC satFC satFC 1 ( ) t 1 i i e e !! !! "! = #!! ! [3] where !" i / t is the decrease during t (m 3 m 3 d 1 ). When # is close to one, a thoroughly wetted soil will drain in 1 or 2 d to FC. Low values of # result in the slow drainage of the soil profile. To simulate internal drainage in a profile composed of various compartments, not necessarily equally wet and may belong to soil layers with different # values, the calculation procedure considers the drainage ability ( !" i / t) of the different compartments. The assumption made is that the total drainage of the compartments above will pass through the compartment below that has a drainage ability greater than or equal to that of the compartment above. By comparing drainage abilities and not water contents, the calculation procedure is independent of the soil layer, to which successive compartments may belong. If a compartment is reached with drainage ability smaller than the one above, the excess is stored in that compartment, thereby increasing its water content and its drainage ability. The drainage function used in AquaCrop mimics very well the infiltration and internal drainage observed in the field (Garcia Cardenas, 2003; Raes et al., 2006; Descheemaeker, 2006; Geerts et al., 2008). *8293:7+%85;$99+35<+&5 +=>23>4?5 Surface run-o $ is simulated by the curve number method (USDA, 1964; Rallison, 1980; Steenhuis et al., 1995). e speci ed Curve Number (CN II ) is adjusted for the simulated wetness of the top soil layer. Relationships derived from Smedema and Rycro % (1983), presenting corresponding CN values for antecedent moisture class (AMC) I (dry), II, and III (wet), are used. A soil depth of 0.3 m is considered by default when calculating the AMC. For simplicity, irrigation is assumed to be fully controlled; hence, the runo $ subroutine (for rainfall) is bypassed for irrigation water in ltration and tailwater is assumed to be zero. If surface runo $ from the eld is important when irrigating, the above assumption requires that irrigation be speci ed as a net application amount. e maximum amount that can in ltrate the soil, either as rainfall or irrigation, is however limited by K sat of the topsoil layer. A % er in ltrating into the soil, the water is stored in successive compartments from the top downward, governed by the limit imposed by the drainage ability ( !" i / t) of the di $ erent compartments. *?4=+1@3A?23>4?5 Evaporation from soil takes place in two stages (Philip, 1957; Ritchie, 1972): an energy limiting stage (Stage I) and a falling rate stage (Stage II), when water transport to the surface from layers below is limiting. In AquaCrop, the cumulative Stage I evaporation (REW) is estimated as: REW = 1000 & ( FC air dry ) & Z e, surf [4] where air dry is soil water content (m 3 m 3 ) when air dry, and Z e,surf the thickness (m) of the evaporating surface layer. By assuming air dry to be half of PWP and 40 mm for Z e,surf an agreement was found between REW and the cumulative evaporation for the energy limiting stage (Stage I evaporation), that is, the U value of Ritchie (1972). As long as readily evaporable water remains in the surface layer, E is in the energy limiting stage, and the rate is the maximum rate (E x ). When all the REW is gone from the surface layer, E switches to the falling rate stage (Stage II) and water ( ows from the soil layer below (Z e,top ) to the surface layer. For bare soil, evaporation is described by the following equation, for both stages: E = Kr & E x = Kr & Kc e, wet & ET o [5] where Kc e, wet is the evaporation coe # cient for fully wet and unshaded soil surface with a default value of 1.10 (Allen et al., 1998), and Kr ( ) 1) is the dimensionless evaporation reduction coe # cient, and is 1 during Stage I evaporation. As Stage I ends and Stage II begins, Kr decreases below 1 as water is depleted from Z e,top (Fig. 4). To account for the sharp decline in hydraulic conductivity with decreasing soil water content, an exponential equation is used to relate Kr to relative water content of the soil layer (W rel ): rel fW f exp 1 0 Kr = 1 exp 1 K K $ %% [6] IJ&)($,/*C;* ]

PAGE 45

! V^ .#4,*1():!:5%41:3)7)3#!,*?)4(#!4&:()%&/!;.&%!;*3&,!)/!,&'57&4!8,5'!3.&!/5)(G![,!)/! ,&(*3&4!&Q?5%&%3)*((#!35!3.&!,&(*3)7&!;*3&,!:5%3&%3!58!3.&!/5)(!(*#&,!cN ,&( e!2#! &@1*3)5%a IJ&)($,/*C;* P MY).4*)/-*,(2.#4*BOOPQ -.&!,*3&!58!/3*=&!5%&!)/!*88&:3&4!;.&%!*!81((!:*%5?#!8)%)/.&/!4&7&(5?)%=D!!-.)/!,*3&!)/! :.*%=&4!2#!E Q !o!cK O <3!)/!)'?5,3*%3!35!:5%/)4&,!3.*3!%13,)&%3!/3,&//!*88&:3/! <_23>4?5 Surface run-o $ is simulated by the curve number method (USDA, 1964; Rallison, 1980; Steenhuis et al., 1995). e speci ed Curve Number (CN II ) is adjusted for the simulated wetness of the top soil layer. Relationships derived from Smedema and Rycro % (1983), presenting corresponding CN values for antecedent moisture class (AMC) I (dry), II, and III (wet), are used. A soil depth of 0.3 m is considered by default when calculating the AMC. For simplicity, irrigation is assumed to be fully controlled; hence, the runo $ subroutine (for rainfall) is bypassed for irrigation water in ltration and tailwater is assumed to be zero. If surface runo $ from the eld is important when irrigating, the above assumption requires that irrigation be speci ed as a net application amount. e maximum amount that can in ltrate the soil, either as rainfall or irrigation, is however limited by K sat of the topsoil layer. A % er in ltrating into the soil, the water is stored in successive compartments from the top downward, governed by the limit imposed by the drainage ability ( !" i / t) of the di $ erent compartments. *?4=+1@3A?23>4?5 Evaporation from soil takes place in two stages (Philip, 1957; Ritchie, 1972): an energy limiting stage (Stage I) and a falling rate stage (Stage II), when water transport to the surface from layers below is limiting. In AquaCrop, the cumulative Stage I evaporation (REW) is estimated as: REW = 1000 & ( FC air dry ) & Z e, surf [4] where air dry is soil water content (m 3 m 3 ) when air dry, and Z e,surf the thickness (m) of the evaporating surface layer. By assuming air dry to be half of PWP and 40 mm for Z e,surf an agreement was found between REW and the cumulative evaporation for the energy limiting stage (Stage I evaporation), that is, the U value of Ritchie (1972). As long as readily evaporable water remains in the surface layer, E is in the energy limiting stage, and the rate is the maximum rate (E x ). When all the REW is gone from the surface layer, E switches to the falling rate stage (Stage II) and water ( ows from the soil layer below (Z e,top ) to the surface layer. For bare soil, evaporation is described by the following equation, for both stages: E = Kr & E x = Kr & Kc e, wet & ET o [5] where Kc e, wet is the evaporation coe # cient for fully wet and unshaded soil surface with a default value of 1.10 (Allen et al., 1998), and Kr ( ) 1) is the dimensionless evaporation reduction coe # cient, and is 1 during Stage I evaporation. As Stage I ends and Stage II begins, Kr decreases below 1 as water is depleted from Z e,top (Fig. 4). To account for the sharp decline in hydraulic conductivity with decreasing soil water content, an exponential equation is used to relate Kr to relative water content of the soil layer (W rel ): rel fW f exp 1 0 Kr = 1 exp 1 K K $ %% [6]

PAGE 46

! V] $@1*<,5? g/!7*,)*2(&!5?3)5%/!85,!;*3& ,!'*%*=&'&%3!)%:(14&!,*)%8&4!:,5?/G! *%4!/:.&41(&4!),,)=*3)5%!/1:.!*/!4,)?G!/?,)%L(&,G!5,!/1,8*:&!),,)=*3)5%! c03&4135!*%4! 53.&,/!IJJ]e D!>,,)=*3)5%!)%?13/!13)()F&!*??():*3)5%!3)'&!*%4!4&?3.D!! $@1*<,5? ?,541:&/!) ,,)=*3)5%!/:.&41(&/!1/)%=!3.&!/*'&!/583;*,&!*/!W0>0A!:*%!2&!'5,&!:5'?():*3&4!3.*%!:*(:1(*3)%=!2)5'*//D!-.&!.*,7&/3*2(&!?5,3)5%!58! 2)5'*//!)/!4&3&,')%&4!*/!"!Q!M>! c03&4135!*%4!53.&,/!IJJ]e D!<,5?!:5'?5%&%3/! ,&?,&/&%3!?.&%5(5=#G !85()*=&G!:*%5?#G!,553)%=!4&?3.G!2)5'*//!?,541:3)5%!*%4! .*,7&/3*2(&!#)&(4D!! N*3&,!?,541:3)7)3#!cNUe!)/!)'?5,3*%3!85,!2)5'*//!*::1'1(*3)5%!2&:*1/&!3.&! =,5;3.!&%=)%&!58! $@1*<,5? !)/!85:1/&4!5%!;*3&,!*7*)(*2)()3#! cW*&/!*%4!53.&,/!IJJ]e D! N*3& ,!?,541:3)7)3#!)/!:5%/&,7*3)7&!1%4&,!;*3&,!/3,&//!/5!)3!)/!,&(*3)7&(#!:5%/)/3&%3! 57&,!3)'&!*%4!:5%4)3)5%/G!213!3.&!&7*?5,*3)7&!4&'*%4!58!3.&!*3'5/?.&,&!%&&4/!35! 2&!%5,'*()F&4!)%!5,4&,!35!=&%&,*()F&!NU!*%4!L&&?!3.)/!:5%/&,7*3)7&!2&.*7)5,D!! $@1*<,5? !.*/!%5,' *()F&4!NU!*%4!3.)/!*:3/!*/!*!:5%/3*%3!?*,*'&3&,!85,!*!/?&:)8):! :,5?!*/!(5%=!*/!)3!)/!%53!()')3&4!2#!%13,)&%3/!c*(3.51=.!NU!.*/!5%(#!/.5;%!*!/'*((! /&%/)3)7)3#!35!8&,3)()3#!4&8):)3/e! c03&4135!*%4!53.&,/!IJJ]e D!! -.&!'54&(!45&/!588&,! :*3&=5,)&/!58!%13,)&%3!4&8):)&%:)&/!35!:.*%=&!3.&!NU!)%!3.&/&!3#?&/!58!/:&%*,)5/D!!

PAGE 47

! XJ 95,'*()F*3)5%!58!NU!)/!85:1/&4!*,51%4!EJ !*%4!
PAGE 48

! XK ;.&,&!<8!3,*%/?),*3)5%!)/!2&)%=!*88&:3&4!2#!*!;*3&,!/.5,3*=&!)%!3.&!,553!F5%&G! 3.&,&2#!,&41:)%=!/35'*3*(!5?&%)%=!3.&%! Tr = Ks sto T x IJ&)($,/*C;* AB <#0)@D % $@1*<,5? !)/!1%)@1&!)%!3.*3!:*%5?#!:57&,!c<
PAGE 49

! XI &Q?*%/)5%G!*%=(&G!*%4!4)/3,)213)5%!)%35!5%&!81%:3)5%D!! $@1*<,5? !*((5;/!1/&,/!35!&%3&,! 7*(1&/!58!:*%5? #!:57&,!*/!'&*/1,&4!5,!&/3)'*3&4!2#!*&,)*(!?.535/!5,!7)/1*(! '&*/1,&'&%3/! c03&4135!*%4!53.&,/!IJJ]e D % <*%5?#!:57&,!*88&:3/!3,*%/?),*3)5%P!3.&,&85,&G!*88&:3/!2)5'*//!?,541:&4! 3.,51=.!NU! c03&4135!*%4!53.&,/!IJJ]e D ** <*%5?#!:57&,!&@1*3)5%/!,&@1),&!?(*%3! 4&%/)3#G!3.&!:*%5?#!:57&,!*3!]Jb!&'&,=&%:&G!'*Q)'1'!:*%5?#!:57&,!c<< Q e!85,!3.&! ?*,3):1(*,!?(*%3!4&%/)3#!1%4&,!?,)'&!:5%4)3)5%/G!*!:*%5?#!=,5;3.!:5&88):)&%3!c<_
PAGE 50

! XV -.)/!&@1*3)5%!:5%/)4&,/!7*,)*2(&!?(*%3!4&%/)3)&/D!!-.)/!) /!5%(#!1/&4!*83&,! /&&4()%=/!2&:5'&!*1353,5?.):D!!"&85,&!/&&4()%=/!2&=)%!35!)%4&?&%4&%3(#! ?.535/#%3.&/)F&G!3.&!=,5;3.!)/!5%(#!*88&:3&4!2#!3.&!*7*)(*2)()3#!58!3.&!/&&4!/3*,:.! ,&/&,7&D!!<< J !)/!3.&!:*%5?#!:57&,!*3!]Jb!/&&4()%=!&'&,=&%:&G!*!4&:)/)5%!3.*3! :5%/)4 &,&4!3.&!.&3&,5=&%&)3#!58!=&,')%*3)5%D!!<*%5?#!/)F&!?&,!/&&4()%=!:51(4!2&! 21)(3!)%35!3.&!'54&(!85,!'*f5,!:,5?/G!/5!3.*3!<< J !:*%!2&!:*(:1(*3&4!1/)%=!*!1/&, O /?&:)8)&4!?(*%3!4&%/)3#! c03&4135!*%4!53.&,/!IJJ]e D!!-. )/!:5%/3*%3!,&(*3)7&!=,5;3.! :.*%=&/!;.&%!:*%5?#!:57&,!2&:5'&/!4&%/&!&%51=.!35!2&=)%!/.*4)%=!%&)=.25,)%=! ?(*%3/D!!-.&!,&(*3)5%/.)?!2&3;&&%!:*%5?#!:57&,!*%4!?(*%3!=,5;3.!:&*/&/!2&)%=! ?,5?5,3)5%*(G!*%4!*,&!,&(*3&4!2#!&Q?5%&%3)*(!4&:*#! c03&4135!*%4!53.&,/!IJJ]e G! /.5;%!)%! E@1*3)5%!VD! KX D <
PAGE 51

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PAGE 56

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c$%*?*(()!*%4!53.&,/!IJJZe D! !-;5!=&%&3):!:5&88):)&%3/! 4&3&,')%&!3.&!3)')%=!*%4!41 ,*3)5%!58!*%3.&/)/!*%4!'*31,)3# !;.):.! *,& !2*/&4!5%! =,5;)%=!4&=,&&!4*#!,&@1),&'&%3/D!!-;5!53.&,!:5&88):)&%3/!*88&:3&4!#)&(4!3.,51=.!3.&! &88&:3! 58!/5)(!; *3&,!*%4!,553)%=!?,58)(&/! c`*%=!*%4!53.&,/!IJJ^e D! -*2(&!XD! K 2&(5;! 4&/:,)2&/!3.&!/)Q!=&%&3):/!:5&88):)&%3/! 3.*3!'.*D;* A *^./.($%*%,.33$%$./(4*3,#*+)$6.*$/* LNN!=*?.#.4 9 +)$6.* M_,/.4*BOOCQ UK!*88&:3/!3.&!7&=&3*3)7&!?.*/&!2&85,&!3.&!?(*%3/!2&:5'&!*1353,5?.):D!!UI!)/! 3.&!'&*/1,&'&%3!58!3.&!?(*%3!/&%/)3)7)3#!35!4*#!(&%=3.D!!UK!*%4!UI!)%3&,*:3!35! *88&:3! 3)'&!,&@1),&4!2&85,&!*%3.&/)/D!>8!53.&,!3,*)3/!* ,&!1%:.*%=&4G !*%3.&/)/!*%4!'*31,)3#! (maize,wheat,sorghum,millet,barley,andrice)as wellaspotato( Hoogenboometal.,1999;Ritchie etal.,1998;Singhetal.,1998 ),andweare con v ertingothers.Onecouldaddadditionalcrops byadheringtothemodularstructureandpro v idingtheinterface v ariablesdefinedin Table2 .Here, wesummarizehowcropgrowthiscomputedfor threecrops(maize,wheat,andbarley). TheCERES-Maize,WheatandBarleymodels weremodifiedforintegrationintothemodular DSSAT / CSM.FortheseCERESmodels,the plantlifecycleisdi v idedintose v eralphases, whicharesimilaramongthecrops( Table5 ). Rateofde v elopmentisgo v ernedbythermal time,orgrowingdegree-days(GDD),whichis computedbasedonthedailymaximumand minimumtemperatures.TheGDDrequiredto progressfromonegrowthstagetoanotherare eitherdefinedasauserinput( Table6 ),orare computedinternallybasedonuserinputsand assumptionsaboutdurationofintermediate stages.Culti v ar-specificinputsforallDSSAT / CSMCERESmodelsarepresentedinabsolute termsforconsistency,acon v entionchangefrom thatfollowedpre v iouslyforwheatandbarleyfor whichrelati v e v alueswereused.Thenumberof GDDoccurringonacalendardayisafunctionof atriangularortrapezoidalfunctiondefinedbya basetemperature,oneortwooptimumtemperatures,andamaximumtemperatureabo v ewhich de v elopmentdoesnotoccur.Daylengthmayaffect thetotalnumberoflea v esformedbyalteringthe durationofthefloralinductionphase,andthus, floralinitiation.Daylengthsensiti v ityisaculti v arspecificuserinput.Currently,onlytemperature and,insomecases,daylength,dri v etheaccumulationofGDD;droughtandnutrientstresses currentlyha v enoeffect.Duringthe v egetati v e phase,emergenceofnewlea v esisusedtolimitleaf areade v elopmentuntilafteraspecies-dependent numberoflea v esha v eappeared.Thereafter, v egetati v ebranchingcanoccur,andleafarea de v elopmentdependsonthea v ailabilityofassimilatesandspecificleafarea.Leafareaexpansionis modifiedbydailytemperatureGDD,andwater andnitrogenstress. Dailyplantgrowthiscomputedbycon v erting dailyinterceptedphotosyntheticallyacti v eradiationintoplantdrymatterusingacrop-specific radiationuseefficiencyparameter.LightinterceptioniscomputedasafunctionofLAI,plant population,androwspacing.Theamountofnew drymattera v ailableforgrowtheachdaymayalso bemodifiedbythemostlimitingofwateror Table5 GrowthstagessimulatedbytheDSSATCERES-maize,wheat andbarleymodels MaizeWheatBarley GerminationGerminationGermination EmergenceEmergenceEmergence Endofju v enile FloralinductionTerminalspikeletMaximumprimordia EndeargrowthEndeargrowth 75%Silking BeginninggrainfillBeginninggrainfillBeginninggrainfill MaturityMaturityMaturity Har v estHar v estHar v est Table6 GeneticcoefcientsfortheDSSATCERES-Maize,Wheatand Barleymodels (A)Maize P1Degreedays(base8 8 C)fromemergencetoendof ju v enilephase P2Photoperiodsensiti v itycoefficient(0 / 1.0) P5Degreedays(base8 8 C)fromsilkingtophysiological maturity G2Potentialkernelnumber G5Potentialkernelgrowthratemg/(kerneld) PHINTDegreedaysrequiredforaleaftiptoemerge (phyllochroninter v al)( 8 Cd) (B)Wheatandbarley P1DPhotoperiodsensiti v itycoefficient(%reduction/h nearthreshold) P1VVernalizationsensiti v itycoefficient(%/dofunfulfilled v ernalization) P5Thermaltimefromtheonsetoflinearfilltomaturity ( 8 Cd) G1Kernelnumberperunitstem / spikeweightat anthesis( # /g) G2Potentialkernelgrowthrate(mg/(kerneld)) G3Tillerdeathcoefficient.Standardstem / spikeweight whenelongationceases(g) PHINTThermaltimebetweentheappearanceofleaftips ( 8 Cd) J.W.Jonesetal./Europ.J.Agronomy18(2003)235 / 265 249

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