NASA Technical Reports Server (NTRS) 20150010248: AgMIP Training in Multiple Crop Models and Tools

0.96 MB·English

by  NASA Technical Reports Server (NTRS)

Chapter 13

AgMIP ‘Training in
Multiple Crop Models and Tools

enh Heo’, Cuer Pole? Jo Tagrewe?, Gea Teogenhnoat,
ote Tooter, and Carolyn Mtr

*einbersin nf Forde, Gale, FT, USA
2 eben of Fora, Gedaceite FE USA

agri Pte Flagshg, CSIRO, Biba, Sista

iashngton Stine Unive, Prosser WA. DSA
‘agricola Protects Flohip, CIRO, Tam. sombe, Awl
ie Univer, New York, NB OSA

Introduction

‘The Agrieuttuxl Mode! Intermparison and Imgrosetient Project (AgMIP) bre
jhe got of wxing nti crop rac evaluate climate mpeets on ogricakra!
prnduclion ned food security in developed aa developing vouatie. Thete we
overl mtjr Kraitations Gat must be evervouné tn achieve this goa, inlaing the
ood to Hain AGMIP regional resatch team (RR) crop modelers to ove models
‘her that the ones Macy are cureny Faallan with, plus the need Wo harmonize
nd inerconyere Uae dispacule input le formets ed fur the varios aodctn. 160
tvtos were folloncd to addres those sbartoomings among AEMIF RKTS «0
fnabie thems to axe muffple model to valuate climate impacts on cop producti
hd food wecutity. We designed and coudncicd courses in which paricipant aned
on vodiferencseeai crop ods, wilh emphusts va the model least experience
Tnaeocond acGvty, the AgMLPTT greup created expres foriopuiting dats. on sil
tanageuent- weather anderops into AgMI hurmodized datas, and developed
tration tools Lor converting the harmunizod data ino files that ave rey for
tuliple erp model (hereafio termed red-modet) solos. Th. statexios for
‘Geathug and omedccing ins a-xuodol eearse and developing entry anc translation
tools re seven in thi caper.

ps
Participunls came to de mulcodel training couse with dale that they bad
Ssudy tested and sirutated with thet favored model; aa heratlve proceay teu
sony refered to 9 ode “cliraion”, Following lectures on the gene pin
les of eropyrvwth and sil-waier balance common to bub models, te pactisipena, =
used the T \wolsto commer the Giles nto the ateaatemndel, and worked withthe
xpecs of those modela to sep through a calibration pmcass withthe new inode)
‘his provided cach erap todeing tam with a second rinulavion of production
essocinted with he some Esmee Bld survey dats, ‘|
‘Thecnurse was leary valued hy ce paricipans, anit was umidepejestachine! |
‘aes allowed them to couple: Zhe srl znodelsnnlatione as pst ofthe inte.
grid ansessmtea that they were dog in tod gional sesarch teams (ne Pan 2,
Chapuess 1/12 in this value), The designation and use of tainers end Agha #
‘Ssourme portany was very vaosble, ax hey bemore and wed srl working
rou, the numberof which execeded the quaker of ustructos available, Parte
‘mote, tho coarse wes a guod testbed forthe IT tao, providing evaluation that ed >
‘improvements ip the conversion tuls tor crating model-caty Aes, ‘

“History of Crup Madsling Contses :
‘Dring ncrap modeling bes followed several uthways A common pathway iver ©
thet 30-at gents has boon one-on-one waning ding saul 7 pon-oclral
Programs, or dung tgs visits wit exp mosellag experts. A socnd pay
‘nu been struceaed using coumseain whlch mnaber of trainees come toa ocatog 7
‘und follow» five wo eight day course of leotures,hends-on traning, and exctolen,
{he tts of thoso types af one-week training cours was conducted in 1881 by the
Deparment of Theoretical Priduction Deolegy, Wageningen Agrictlral Univer
‘gg, the Netherlands. The sealor wos wos privileged t aiend that course, That
conse wos connected ts the 1982 bouk edited by Peaning de Voie tn vay Lear
1982),

Usiveesty of Flcids crop mndlees J. W. Youes, K, J. Boote, and G. Wilke
‘rs0n) conducted ther frst crop modeling course we the Univsisty af Florida in «2
1985, witha simiarexe-weck forms, Afr hat ntl ctr arger group al crop
modelers acociuted withthe Intemational Banchzoack Silex Network fie Agroiech,
ology Teasler OBSNAL) project proeecéed tocondvc sa tendayerep salting
‘uae at various ses in the US and around lhe world, beginning with Tyan is
1986 nd the itematioual Center for Reseach inthe Seal Avid Tropes (CRISAT)
1 1087, Coop modating ooarve with tho Decision Support System fee Agrotct
‘ology Transfer WSSAT) software heve vomtimzed since on a neatly annual oF
biamamal bosis (Hoogenbnam es al, 2010; Jones et al, 2003). The vnurse was
‘offered 20 rims ja the ISA since 1983, und intentional courses were tht
1b data that hey bad
lerative process coine
to the general prin
cles, he pariipasts
‘and worked with the
‘with the ner mode
ulaion of production

unld-projeclachiewo-
os as part of tite
ch teams (see Pare2,

uainess and AgMIP
sisted small working
>ev available, Futber-
tg evaluation that Ted
andy fies,

ooeson pathway over
‘uate or post-doctoral,
A second pathwny
vescometoaloeation
Sang, and exercises.
Tusted in 1981 by the
‘Axgculuzal Univer-
‘a hal cowmae. That
Vries md van Tar

Boule, wd G, WiDk-
versity of Florida in
Farge group af eng
stork for grote
cudayeropanoleling
‘ning With Talwan in
ITropios ICRISAT)
vestem for Agrotce-
‘ neatly sarual or
1), The course wa5
oarien were tang

Ate ogi i mp Mab nae 5

{ee toy foto SAT ening ctr se 1985

“Year aniog ue

ied me 3,199), 1998 199,194 1908, 1998, LY, 19EH,
ps, une "004, 2, 208 20,2040, 2011-2012, 201, 2014

savin 136

tase so 2010, 221,200

Sena (98,2018

Vio 198

Republi uf Sek HED 1290,1995

ineare erg

aes oo

emt 19% 1059

tage 19598

Tod 2,200, 2007, 20122014

chee nas

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‘Peal Rep of Cina "ais

Keay 2007

Membia aan

ayia 0

Sram me

piven) am

jn Taiwan, Indi, Senegal, Venevicle, Republic of South Attic, Hongery, Cade,
‘Togo, Ghana, Egypt, Tanzania, Aagonina, te People’s Republic of Chins, Ket,
Naauibia, Malayia, Hurbedos, Spon, ané Thailand (Table 1). The aumbec vf par~
Tetpants ranged irom 10 60 people, usally 20-20 ata tins. The book odind by
‘Taufl, Beogboos, and Thorztoa (1998) serves asthe textbook for the DSSAT
teup aodeting cours. Mar haa OVO sudents have been trxined over ths pecod,

“The Dutch czop modelers condacid rill wsiing courses ona ego hss,
cepesitly during he Dutch gosermacat-fanded project, Sutation aud Systems
‘Analytis for sive Producllon (SARP) in Asia during the mia-1980s to the mid
Tox (lon Berge, 1893). Ia that projet, the Center for Agrobiolugcal Revearch
sand Wegeaiagen Apscaltura Unversity inked with re Itzmational Bice Research
Tnstate and 16 nakwnal opticutral resarch ceater im Asia, to conduct systems
dnalysn and sivollion modeling metiy on dct, by axing the SUUCROS model
(Penning de Vis eta, 1989), Tniing onanee were conducted ot Wageningen
fod at immcoatonal sles, following the tempts of the Penning do Vries und va
[eas (1982) book, along ith taialag n wse of SLCROS and use of the Continuous
Systeus Modeling Progen (CSMD? language,
(Otksr models and modcting romps sueh as the Agsiullural Production Syne
‘Simuletor (APSIM; Keating et af, 2003), EPIC: (Feaurude of eh 2006; Willisny,
sal, 1989), aad Crop (Stickle ef af, 22} old somcthal sherttinchowag
‘rsining sessions for ope to ten poople al time, generally at Usir research sn,
“Phe CeopSyatgronp use web-bated tang apmoaches, APSIM conduct two-day
‘ening session evra tines por yer n Anstalis, mol om operon poe 2
of the model sofeware. Many Austaloninisonatonslagricltual recess proces,
Josie five day APSIM wots n-countr for 15-20 personas regurd, The |
contes eo talored for the eplus Ce, Ate and Aa in which he pret ins 2
‘ers operas, and usually consist of hres days of hunds-0a esiviten with sence ©
‘theory and wodetsunding of tie dynamics ofthe process petucing the riualatiog ©
‘sul followed by tn days of amal-groupsctitis ining simtlations to explore 2
Jucal iesars and strengthen slnulstion skills. bal-day of ieuetisn om sil sama.
ing ieee condaetedOthor APSTM intomatona ining atts ade
peripsory vp modeling ning dal urge! esearch od
$n tho are of APSLMGor adling value to u-ferm research and extension foeuthngon 2
‘timate change sdaptaion and cp production. The fistiniematioaal APSTMuonne ©
‘sod in 1997 at he ICRISAT couter ax part of a joint project enttlod “Collabo.
‘ation on Azsicolaral Resource Modeling and Applications in Semi- Ari Tropes

Approaches Followed in Crop Miodsting Comrses

“The approaches in the DSSAT and Duteh-SARP orep mock! training courte foe
‘ovied a templar thal included some lectures interpre d with handovon une of he
softwae und model Inlerfuos, slong with exencses. The lectures covered prince
Pk of erp phonology crop eatbon (dry matt) buluncs, cup sot wate bilance,
Soil-plan.N helance, model calibration, model sensitivity atalyses, et. ‘The band
‘om talaing with the software included excicses lo demonstrate dta ears, proper
creation of wor, soils, ad managermcut Ole, mel calibration, mode st~
Jatin, and data analyses, Trainees were encouraged to come vith thee own deca
and to devsiop a special topic or exercise With ei data. I they did not have dae,
sSludents wore given topes in which they wete to rvale model waly ies o.com,
dura mut-yoae simulations of vaions ueatments or otop sequcuces. Remit were
(hen analyzed te evloste how various eatments afleted crop yields, imigaton
‘equlrements, sewonal evapotranspvaion, wil C dynamios, filer N response
[Nleashing, economic eburas, and optnal exavomie decisions, et

be Datch govenuneat-funded SARP project, panicclaly in ite later phuses
discovered Ut stained flow-through was very important, Project uganizers
‘atlished wu! fondod a program for old-riented aciutisls ftom Asia far one
ent of fermul maining at involved abot half-time on field dete coleeion snd
balt-time om erop modeling (ton Rerye, 1983), The African Netwnrk for Sel iatogy
Ag gi i ny sno m

‘wal Frodustion Systems and Ferny (AIN) Project (Bationa ofa, 2072) established iar program
leecat, 2006; Wilms Jr Afica i bis wald-yeartnned pooact Aficun slendete peiped i a0
otha shone iastinte Jourodocunry crop modeling workthop, Fllawed y Held Gx colcstion ca a opie
Jat hee research ten iat utd be urbe analyze By crop del sltins, followed by workshop
PsIbteondacts tw day ‘ith hemes and heir dats, and ber athinl woke to preseo eek il els
¥ ow operational sapects thet coded yp #2 written papers being pabliaheil in a book (Butione ef a, 2012).
tollurul research projects ‘A similar approach is followed by Auswalisn projects that make use of the APSIM_
‘Sons asrequired. These stems naodcling a ua uals 0

whieh the project mem 'APSIM wockshops are conducted in Austealian projects in which sicanlation iy
1 ects with iene sequted wan asl tox for compomeais of he poet (Resting, 2003). Most
‘reducing the sinmuleuisn | ‘expericaces are pahtished in project reports by the penjectsponsars (e.g, Australian
|g simnladions to explore ‘Center for facernationsl Agricoltral Research, Austrulian Agoncy for Ltemnational
instveGun on sol stm- Cevelopmeat, ICRISAX, and Rockefele Fonntatia).

siting tives nla

Ureseutchos pruicient ——_engopa fur Mtuld-model Couroe Taught by AMP Scteatits
dextenviontonsingen

‘national APSIMcouns. © tbe AgMTP project as u stroag focus on muti-roudel simnlations wo evaluste
ject entitled “Colo. | spats of ciate aconarios ut agricultural production, similar the use of mule
dt Semi Atid Teogice” tiple global climate models fur prodicdon of forure climate (Rosenases et al,

12013). The concept of ruld-mode] vs in thal Ine ensemble of several models may
ti eheter prodiciot than any given single mode, 28 sleady leaenvd by the AgMIP
rhea sans (Assen ot at, 2013), che AgNIP onze tearm Basso etal, 2014,

traning courte foe The AGMIP tie tans, and AgMIProgcoane uwlers Asa ret project sig
ith handaon we ot [gM prtcolsvoqie ho aplication of a as ce crop mune, Thin al a
setores covered printi- bbe achieved by hringing together scientists with expertise iu different models t0
‘psi snte alee, Ghalyee daira from herein of iatro. However fn ray elon eres
slyses, ete. Tachands- ‘in developlag cours, there are fer scientists proticicat in <top modeling and
ate dae entry, oper [RET may have seieatsa proficien! wih unt one ntode, “hs, there i 2 necd to
‘atom, mode sim ‘courage thet crap deters era tus ore tha ae erp modal el
ve with heron dae Tpcellarate wi bert ruta ative.

fy dnote da, Sousa, pudipering sions in he region tows fended by abs UK
del ready fas 1 cone Degartwont of Foroign Intemational Development (DFID) wished w use avis
uae. Rasils ore pe ciop ml (DSSAT apd AISI t mia) to szelst ils elaive
‘otup yields, erigation ‘fumn survey data colleoted by sucio-camomists as 4 way (0 evaluate climate impact
‘eros Srespensa ‘ofan fom vasa in provatin, sad sbsequeny to coma iaaret
Tl ‘production-somorti¢ assensment. Therelore, AgMIP leaders develuped training
Ay in fs ber pass, ura for i eon paige x which lode aogier
7m Project organizers ‘coophusived. Ia the AgMTP Handbook protacel (ace Part t, Appeadix 1 in this vol:
Tetiom Asia for oe. iuand Rezenzwoig dh, 2014 of the DFO regina iteteted we
4 dato clecton ant Inept veges se the ible eof vray ag shad

‘Work or SoilBiology ‘dnote change rato (2, te yield under 30-yeut fim climale divided by yield
der er oar inal or sth fn), The whe # pid by
ohn frm rarey sek npr en neal wort te ead
sam he farsa fect nace an echanlogied wgtens nk
‘ae offra gea flim era ple Yr seeeg eae
Olu te pln et nat vhag on cp vce

thereon fra el ous tet pepe want ak ay
crop dsl techn sel hey sure te Parla oe nce
sein om er mol ake sea apps wer al pcos ean
sumagomen and ulin, The eepusdelers cantante cs ecto
‘oa madal to the next, because the conzepex are often similar even if dhe cncfficicars *
and model structure may be differem. Althomgh Ibe crop modcts sun the: soltware
interes omy elieramng ten! wotsing ropa tobusepariveren eee,
lel woscof weer is tad managezet data Likewan ce porary
yeidnetsveers atesimlerineanpupuednlediPesot anise meson
sift rpc nd ext eatrarsos sinlnal ets ohare re

lyn sad all noise ocala dh
<rmeat i ingrve ber sian of tops eld content Loca eg=
hw kat moc smulte nape fo be ea avsonenn ects
‘ich stimulus for considering how \o further innprove moda! processes themuctys,
Diieendy parantrnd relly yie derent esi ene np
Sata cpg wy Ms hgpom ia petal eanng epee ee
ks who mw be able ase and nee one ah of che oe
nation (or Thnitations) a8 10 how models simalate agricultural systems, and why 7
‘they sometimes “fail”, «

‘Aiport eas rhe ARP lr oreo nse
toch te ero mods low oa he vey devepe tol ne is Ro
hater in is volume) fr dameny a consoles aes ocelot
ee reais eum oldie DSSAT ex ASTM peice Rrtuseiegeny
sminogencat in te rndels base on the in es aba od eno
sxomplicd te oes of hare tbe ented ned sree eh egphen
‘nthe ApMP-sarvoniel fran and hing unaiablcuoite Neceantees
far hoth reel rth eso, te IT ols were asorag faa at eee Oe
isso teasing cout Aphis mad ole nl tat arco
th se of mu del pera by easing teat nse song rot
oct tatu ne nlsration wth te stall Secope dese te
‘ho Fal | Charney

‘Planning and Prepurstlons for the Multimode Training Course

Potential participants wore surveyed (ole of thet prior experionce im emp mock
‘ing with ice curren useu mndel aad te designate which mevlel they ranted 10
‘is mulipicd by he
tof wiers and ose
logic adepaton.The
useepessting re
00 crop peaicton
ats want oar abo
ipa ae iatererte
5 i ponenses cp
(sic experiences fem
veal coef
alls und he sear
sieprncplesare dims
vise crop growth
Texea variable naming
‘us observed wakes.
nai wd devel
‘tous. Laaming abe
crviroament provides
processes themselves
sts fete same gat
gexperiense for mad.
of shih yc} ator
vl stems, aud why

‘was lo introdnge and
loots (ee also Pat 1,
Idemntive wood ave
lwolsSordefining erp
this wootd aot have
‘eee wid tempts
"te los ready to ran
2eus fora leant moe
ool thal emuinage
ve among roadele, 7
2persthenselies (98

erence in exup mod
nodal they wanted to

ght Tahn bie Case nem ie co

Jeam ue cboat. At tnportant requirement war thal participants have rior exper-
cae wilh atleast one yp akedel, a this course wus act.designed tobe u begimer"
‘Prive 1 dhe taining cous, an email was sont to pericipants roqacating thet
they: (1) eonne with thei own portable lulup cornater, (2) identity und some
vith sentie! aie experimental Gta following AgMIP sentinel sle date staddards
(Gerebaum etal, 2014)ehalbnd aminimom anouutand quality of weasuremcotsoF
‘roplile-cycle phenology, nal biomass, ral yields, modest growth analyses long
‘wih se-spocfic weal, ils and crep masnageatent inputs in der smal
crep owt, forwhich toy wore ald romning their entrent meta for which
thoy would caltbotecullvar enefviens with anew model; (9) come with te Ear
survey yleld data (es well 88 anrociuled menagesnent and sols data), which they
‘pould enter during the courses and (8) cou With 30 yeas of historical “baseline”
‘peather daa forthe fm survey region, including wealhes forthe acoal fra survey
yer.
"The 30-year aurontbuseline wealbe dan see tobe ified by their otimate
scicnrn, colleagnes to prodnoe a given define climate scenario hy using the della
Insthed. Duiog the coure they followe-op sth exop slnlations of the fade
‘dua farm sles in order to calcules the climate change atios to provide to ie
economist callbortior, by Sullewing rouxols ofthe AgMIP Tianabooe (sos Fut 1,
‘Appendix 1 inthis valume and Rosemreweig et ut, 2044),

Tasteuctors and Teato-the-Tiainers

‘an poeta goal of AgMTP i capacity -ildiag and development of wegionl crop
‘modeling capability, toiuclads Ga ditting individuals wih the potential o bocome
nure inscuctors dnd texiner of ofher crop modes, Prior t> te caut-meset
training euurse, he instructors J, Boots, C. H, Pore, J. Hargreaves, and

ongeabooun) and P. Thutbora cngaged AgMIP exadntion tnx process of cane
dss solectin, with seleciews demansraing good érup modeling sil, oud leas
‘rahip, and good teaching and renting pototil, vith appropriicregioaal and
TFeudet repesentaton (live developing vouumies and lve swomien), "The selctees
avluded D. S. MacCunhy (Ghana), D. ML Kadiyelu adi. D. #itondyi (Nie),
IN. Suboch (lin), G, Baigueia (US), P Masitati (nababwi, B, ‘Singh {Indah
ima A, Wajid (Pakistan), Daziag the ruining course, these individuals wok an active
fue lo sneator und sie thee eallgagucy om geticulsr mouels andlor cop exper:
Se at eacy had. Tho instructors provided additional guidance aud aGvice tm hese
evigosted individuals, wih the expectation thac bey weal ruta to theit region
‘or emiveesty and help ober cv atodeleria dlr eueet team university, oF

gion.
Fi non wut-acsriagewe mise hs ingests tale CRIA, $
‘ria Rah ii 7

(Conducting she Course and the Course Syllabi

‘he ooume was conducted two Iosation esng the same cuit and ove
lon: During March 18 22,2013 atotel Ausaparae, Kathmaaada, Nepel(abontten
‘denis tended), und during March 25-29, 2013 tthe 'CRISAT cent. Anko
‘rade din (abom 40 studemisauende, se Part 2, Appondix in is votome or
‘e TCRISAT Workshop report, To the exten posse rane in-iuing ated
och events, Thin alld for cle nterationwod adanccaeat of thes oon cope
bilan th ft miler evene — end provided immediate oppastunity ty le
‘aie sills a enews in the ascond, Igor event, The photo (Tig. (shown the int
ation ofthe second couse, held a the Learning Sysiems Uail st TCRISA. Come
scivites fe the AGMIP Meltple Crop Madel Training Program are dcecibed in
(he ayllbs (Annex | at the ead of this hope). tn aden, patcipans wee
Provide Witt Gide for Regional Imagraced Ausetsment: Handbook of Red
ads and Provedies, Version 4.0, specifically Appendix 2, Crp Moret Stratton
Jor tntegrated Asscounents: User's Gd, wailale inthe AgMIP Handbook (soe
Past 3, Appendix 1 in this volume and Resenzweig et al, 2J14). The later cow
fain the AgMIP protoots for using the FF tls for easing Cam survey yield
lata in template les, cveting ube dau ovceay fs 1o prose anseaptony tor
‘formation melas from sorry tuauageracat and sol, an condeting the ett
‘mod! unultons ts produce ests topes ut the economist fot fmt
Diophysiew and socio-cconmie assent
psec ital RSA

© curiculs aud overa)
sand, Nepal (about en
RISA cence, Andhra
iin Jin his volume for
snein-raining amended
tent of tele own capa
= opportuni to vilize
Fig: Datovethe inte
‘ites CRISAT. Course
vgcam ate Uesribed Lo
joo, paicipan's were
‘8: Handbook of Meth-
‘op Modet Simulations
AgMIP Handbook (2
2014). "The lller com
ing farm survey viol
vide assvargions Zoe
A onneacting the crap
nts for ae tages

At Ting ap Cop Moat ec, a

‘Dusing the fest day of the corse, we introduosd Un falegeated asienereat
geal, and then gave aD everview of DSSAT und APSIM stop models, speci
aly how phenologieal develope, crow and yisld soil—water dynamics, ant
eactccoelisints are formula in each model Prlacplo of genetic coaticicat
Znittion wore intodiced, Initials, al pordeipanls were together in the sam
{oom Jeaming abou Poth mode, Late {nthe aternoun of the frst day. purtiolpanis
Jjtalled their newly chosen odes, and lesmed the procedures for inputiag uw
up. Sol, meageinont und weachsr dite for the purpose of extimasing genetic
coelisents fren he sootinel ste experiment dat,

‘On day 2of the cours, alley one plenary Ietute on sls and top management
saepects, we separated ina two paralcl seasions, wih one, group learning DSSAT
“andthe odie arsiag APSIML Dusing the res. of thin da. stents worked with
Ice new ctop mde), ad spured soll, Weather, asinegement, und crop observu-
tion data which they used to eainate the model-spesfic genetic coefticent for
their eabivar fom thsi seatine ste experiment deta. Ax necessary, suul-group
tnodelaperiic hotues wert conducted te addreee model-spectfic issues rested up
_eetic coeffiient calibration,

‘Oa day 3.thoctudenis completed thei calibration of genetic ovefients forthcir
no erop mode], erste visuals, and prescatcd thei oss por team a plenary
fasion near mid-day. Aller esch prefegtation, we discuseed what bul beta dons
tu gave roveramendations for improveaet.

1 de aflernoon of day 3, the ARMIP IT tools — sarvey data template, da
cexetlay Hes, ni Quad (Oke deaktep aplication for doa naaslaion) — Gor enter
ng farm survey dite were iatzodoood and explained (oe alvo Part 1, Chaptce
{a this wilame}. The parcipeats then began to enter thei farm survey pled md
‘management infrintion ino Une AgMIP lenpate mreadsheets,

‘Onda tse sas apenary locereonile gone Ag MIPiategretodassessmet
for malyzing farm prodimotion as wel aemetbodsforanulyzing feu sorvey data and
mulled production, We diacusted proper use of AgMIP wols to complete ats
ff field survey uta us well as czestion of Dota Overlay for Bfultismodel Txport
(OME) lic fe iepu of rising iatiabizatvo ant mamagement information. Wie
sexist he partojpenls In vse of the AgMIP tool to conven Led survey as ino
sondel-eeady flo. We advised on the cdo verify thet inputs (aadagement, sil,
{nial eondiions, and culver and salsted fm getting the crop andes ro ran st
thie da

‘Wo anid in analyzing simul sess and in vonppting the mean and ple
ting dhe onmalative probsbiity of esevedance for the observed farm survey yickts
ated yields on the wane graph. Figure 2 Dhustrates the probability

and ote!

of excevdance of u given yield lel fx frmar sary yields, compared with the
fields slated by DSSA und APSIM for peanut Delis near Niorn, Seoeyal in
Plvatiy ot ercmense

g

Yeon
ig. 2 Probably of exes sen il lama fume srr el, DRA na

eins, so APIS ros ea ei a is, Snel 207 Gono CIV
‘san in Par 2, Chaya 2 a Yl).

2007 (eounesy of AgMIP's Wesiem Affi eam, CTWARA; sce ssw Pat 2, Chaps
‘er inthis volume). The fener survey fads wenerlybave gretce yield variation,
powibly because dines frou peat, disease, and weed problems i Laer fis
smeun thatthe medels da not simula, a5 Vell aa inulcient yatlation of sole §
(naerfproductivty) ansigned to the mode] simulations. We discuss the need a
‘value the simulated and observed diatrdbuions and (understand te causes for *
sone! flee to prediot evunlely the msn ut well as he high or low tal ofthe 2
‘umulative probability of exveedance, [some cates, these were caused by shale 2
‘ror in seling ap of thc models und cae were resalved, invome casa, iii
condition assumptions relat ogo water und aa organic carton pools had majoe
fica oa ln distribtions busine. ag
Alipough the econcustsadroquested ato exueral hias adjustments ic mae *
(hocause they only needed te value of climate change rio (R) lo be predisted (0 5
‘raneform the obsrvsd yield in cach fam), ero Wore often serious bis-nfuenciag
pt issues rlativo wo initial sit water initial sol mineral NY, soll xganic C poo
and resides assumyctions that wort mud (borause auch inforinaon was mises
fom the firm wovvey dfs). Consistent rales fo biuadjwsting correcions wets *
‘suggested > taille reais pie levels aud datbations fnr the tex thal
‘Would be heloved by skehoWers. At the name (ime stadenls ers caus thal
ontetions necded to be Timed ro broxs classes of prddlems for anuldgle ams,
and in no case Were adjanments allowed tu be mad on “Turo-by-Gern” bans
sin absenee of data. ‘The reason for this euulion was that wt least oa group had
presfously miero-aliested inpats for every single ficld (without te evideuce
‘nut variation) to ensety mimic the chseeve yield fo each una every macy tld