Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
h ps://doi.o g/10.5194/hess-29-4219-2025
© Au ho (s) 2025. This wo k is dis ibu ed unde
he C ea i e Commons A ibu ion 4.0 License.
Rele ance o eedbacks be ween wa e a ailabili y and c op sys ems
using a coupled hyd ological–c op g ow h model
Sneha Che u u1, Rens L. P. H. an Beek1, Michelle T. H. an Vlie 1, Je om P. M. Ae s2,3, and Ma c F. P. Bie kens1,4
1Depa men o Physical Geog aphy, U ech Uni e si y, U ech , he Ne he lands
2Wa e Resou ces Sec ion, Facul y o Ci il Enginee ing and Geosciences,
Del Uni e si y o Technology, Del , he Ne he lands
3Depa men o Hyd aulic Enginee ing, Facul y o Ci il Enginee ing and Geosciences,
Del Uni e si y o Technology, Del , he Ne he lands
4Uni Subsu ace & G oundwa e Sys ems, Del a es, U ech , he Ne he lands
Co espondence: Sneha Che u u (s.che[email p o ec ed])
Recei ed: 23 Feb ua y 2024 – Discussion s a ed: 12 Ma ch 2024
Re ised: 8 Ap il 2025 – Accep ed: 1 July 2025 – Published: 9 Sep embe 2025
Abs ac . Indi idual hyd ological and c op g ow h models
o en o e simpli y unde lying p ocesses, educing he ac-
cu acy o bo h simula ed hyd ology and c op g ow h dy-
namics. While c op models end o gene alize soil mois u e
p ocesses, mos hyd ological models commonly use con-
s an ege a ion pa ame e s and p esc ibed phenologies, ne-
glec ing he dynamic na u e o c op g ow h. Despi e some
s udies ha ha e coupled hyd ological and c op models,
a limi ed unde s anding exis s ega ding he eedbacks be-
ween hyd ology and c op g ow h. Ou objec i e is o quan-
i y he eedback be ween c op sys ems and hyd ology on
a ine-g ained spa io empo al le el. To his end, he PCR-
GLOBWB 2 hyd ological model was coupled wi h he
WOFOST c op g ow h model o quan i y bo h he one-
way and wo-way in e ac ions be ween hyd ology and c op
g ow h on a daily ime s ep and a 5 a cmin (∼10 km) esolu-
ion. Ou s udy spans he con iguous Uni ed S a es (CONUS)
egion and co e s he pe iod om 1979 o 2019, allowing
a comp ehensi e e alua ion o he eedback be ween hy-
d ology and c op g ow h dynamics. We compa e indi id-
ual (s and-alone) as well as one-way and wo-way coupled
WOFOST and PCR-GLOBWB 2 model uns and e alua e
he a e age c op yield and i s in e annual a iabili y o ain-
ed and i iga ed c ops as well as simula ed i iga ion wa e
wi hd awal o maize, whea , and soybean. Ou esul s e eal
dis inc pa e ns in he empo al and spa ial a ia ion o c op
yield depending on he included in e ac ions be ween hyd ol-
ogy and c op sys ems. E alua ing he model esul s agains
epo ed yield and wa e use da a demons a es he e icacy
o he coupled amewo k in eplica ing obse ed i iga ed
and ain ed c op yields. Ou esul s show ha wo-way cou-
pling, wi h i s dynamic eedback mechanisms, ou pe o ms
one-way coupling o ain ed c ops. This imp o ed pe o -
mance s ems om he eedback o WOFOST c op phenology
o he c op pa ame e s in he hyd ological model. Ou esul s
sugges ha when c op models a e combined wi h hyd olog-
ical models, a wo-way coupling is needed o cap u e he im-
pac o in e annual clima e a iabili y on ood p oduc ion.
1 In oduc ion
Global ends in popula ion and economic g ow h a e ex-
pec ed o inc ease he demand o wa e , ood, and ene gy,
h ea ening he sus ainable and equi able use o na u al e-
sou ces (Sophocleous, 2004; Tompkins and Adge , 2004).
Wa e as a esou ce plays a c ucial ole in c op g ow h, cool-
ing o he moelec ic plan s, hyd opowe gene a ion, and he
co e ing o domes ic and indus ial demand. Wa e , he e-
o e, is an essen ial esou ce a he co e o he Wa e -Ene gy-
Food-Ecosys em (WEFE) nexus. Cu en ly, 70 % o o al
global eshwa e wi hd awals a e accoun ed o by ag i-
cul u e, making i he la ges wa e use among all sec-
o s (Dubois, 2011). The Food and Ag icul u e O ganiza-
ion (FAO) o he Uni ed Na ions es ima ed ha he demand
o wa e and ood esou ces will likely inc ease by 50 % by
Published by Cope nicus Publica ions on behal o he Eu opean Geosciences Union.
4220 S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model
2050 compa ed o 2015 (IRENA, 2015; Co ona-López e al.,
2021). The inc easing demand o wa e and ood will likely
ha e nega i e impac s on he en i onmen and will inhibi
socio-economic de elopmen i a gap opens be ween g ow-
ing wa e demand and wa e a ailabili y.
The c i ical in e play be ween hyd ology and c op
g ow h becomes e iden du ing hyd oclima ic ex emes (e.g.,
d ough s, hea wa es), as ising demands coincide wi h po-
en ial declines in bo h wa e esou ces and ood p oduc ion
(c op yield) (Jackson e al., 2021). In add essing he com-
plexi ies associa ed wi h hese challenges, s udies by Jäge -
mey e al. (2017), u ilizing a dynamic ege a ion model
(LPJmL), e alua ed achie able i iga ed c op p oduc ion un-
de sus ainable wa e managemen . Thei indings e ealed
ha 41 % o global wa e use cu en ly comp omises en i-
onmen al low equi emen s c ucial o i e ecosys ems,
po en ially leading o losses in i iga ed c oplands. Concu -
en ly, esea ch by Vö ösma y e al. (2000) and Leclè e e
al. (2014) p ojec s he impac s o clima e change on global
ag icul u al sys ems, o eseeing an inc ease in i iga ed a -
eas in he u u e, unde sco ing he necessi y o signi ican
in es men s in i iga ion, ene gy, and wa e esou ce man-
agemen . These indings emphasize he u gen need o im-
p o ed modeling app oaches o assess he complex in e -
ac ion be ween wa e a ailabili y, clima e change, and c op
yields.
To add ess hese challenges, biophysical p ocess-based
models ha e been widely used o s udy he in e ac ions be-
ween hyd ology and c op g ow h (Siad e al., 2019; Zhang e
al., 2021). These models p o ide aluable insigh s in o how
me eo ological e en s in luence wa e a ailabili y o c ops,
as well as how changes in c op g ow h and senescence a ec
hyd ological luxes such as e apo anspi a ion and oo wa-
e up ake. Howe e , exis ing s and-alone c op models and
hyd ological models o en simpli y hese p ocesses. Fo in-
s ance, c op models usually inco po a e a simpli ied soil-
wa e balance (Zhang e al., 2021) ha o e looks local hy-
d ological p ocesses and o en do no accoun o wa e use
o i iga ion and non-ag icul u al sec o s. Con e sely, mos
hyd ological models simpli y o neglec he e ec s o land
co e , phenology, and ege a ion changes on hyd ological
luxes and he s a e o a ailable wa e esou ces (Tsa ouchi e
al., 2014). These simpli ica ions a ise due o compu a ional
expediency, dispa i ies in p ocess scales be ween hyd ology
a he i e basin le el and c op yield a he ield le el, o
incomple e unde s anding o he o he domain by model de-
elope s o because o epis emological unce ain y (Siad e
al., 2019; McMillan e al., 2018; Sha iei e al., 2014). Rec-
ognizing he s eng hs o bo h c op models and hyd ologi-
cal models, a coupling allows o he explo a ion o dynamic
c op g ow h’s in luence on hyd ology and wa e use. Addi-
ionally, a model coupling allows he inco po a ion o spa-
io empo al a ia ions in hyd ological luxes, including wa e
use, in es ima es o c op yield. This unde s anding becomes
c ucial when assessed a he egional o global scale, whe e
local de ici s can ha e cascading consequences o bo h wa-
e and ood secu i y a he basin scale.
The a ionale o coupling hyd ological and c op g ow h
models is wo old. Fi s , coupling hese models allows o
he possibili y o assess he impac o limi ed i iga ion wa e
a ailabili y on c op yield. Second, i enables a de ailed anal-
ysis o how changes in c op ype and g ow h s ages in lu-
ence g oundwa e and su ace wa e a ailabili y, pa icula ly
h ough p ocesses such as e apo anspi a ion and oo wa-
e up ake. By combining a hyd ological model wi h a c op
g ow h model, his s udy aims o enhance ou unde s and-
ing o hyd ological and c op g ow h in e ac ions and hei
implica ions o ag icul u al p oduc i i y and wa e esou ce
managemen on he con inen al scale.
P e ious s udies ha e a emp ed o couple hyd ologi-
cal and c op models. No ewo hy e o s by D oppe s e
al. (2021) ha e success ully coupled hyd ological and c op
models, p ima ily ocusing on achie ing a ainable c op p o-
duc ion. Howe e , hese e o s we e conduc ed a hal -
deg ee (∼50 km) spa ial esolu ion and ocused on long- e m
a e age c op yield. They he e o e all sho in explo ing
he aspec s o ine-scale spa io empo al a iabili y in pa -
icula as a esul o in e annual clima e a iabili y. O he
ecen e o s o couple c op g ow h models and global hy-
d ological models (Jäge mey e al., 2017) p edominan ly
ocus on assessing yield unde di e en scena ios o adap-
a ion measu es. Howe e , limi ed wo k ocused on del ing
in o how wo-way in e ac ions and eedback mechanisms be-
ween c op g ow h and hyd ological sys ems ope a e.
In addi ion, in eg a ed assessmen models ha e been in-
s umen al in s udying he combined e ec s o clima e
change and socio-economic de elopmen s on c op yield and
wa e esou ces a a la ge scale. Typically, hese models op-
e a e on a mac o- egional le el (Eas e ling, 1997) and use
annual (o 5- o 10-yea ly) ime s eps, neglec ing he im-
pac s o in e - and in a-annual a iabili y and pa icula ly
sho - e m hyd oclima ic ex emes. Fu he mo e, in eg a ed
assessmen models o en adop an op imiza ion modeling ap-
p oach, making hem less sui able o s udying he e ec s o
hyd oclima ic ex emes (Ewe e al., 2015).
Ano he class o e o s o link wa e o c op p oduc ion
is wa e – ood nexus s udies, ha , howe e , end o concen-
a e on local linkages o p o ide quali a i e desc ip ions o
exis ing connec ions (Momblanch e al., 2019). Fo ins ance,
a ecen e iew o wa e – ood nexus s udies ocusing on he
con iguous Uni ed S a es (CONUS), shows ha such s ud-
ies ocus mainly on wa e secu i y indica o s (Vee il e al.,
2022) o clima e a iabili y impac s on c op yields (Huang
e al., 2021). Howe e , knowledge gaps pe sis , as wa e
and ood esou ces a e o en e alua ed sepa a ely (Co ona-
López e al., 2021), explo ing alloca ions h ough an op i-
miza ion model (Mo ada e al., 2018) ha lacks spa io em-
po al a iabili y conside a ions. No ably, he e is a lack o
e o o unde s and he in e ac ions be ween hyd ology and
c op g ow h. Fu he esea ch is needed o b idge hese gaps
Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025 h ps://doi.o g/10.5194/hess-29-4219-2025
S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model 4221
and enhance ou unde s anding o he dynamic and in e -
linked p ocesses shaping he wa e – ood nexus.
To add ess his knowledge gap, his s udy aims o quan i y
he wo-way in e ac ions be ween c op g ow h and hyd ol-
ogy, hypo hesizing ha coupling a c op g ow h model wi h
a hyd ological model will imp o e bo h c op yield and hy-
d ological p edic ions by inco po a ing dynamic eedbacks
be ween wa e a ailabili y and c op p ocesses. Speci ically,
we hypo hesize (1) ha a mo e ealis ic ep esen a ion o soil
mois u e dynamics and wa e a ailabili y will lead o be e
es ima es o wa e s ess and yield and (2) ha di ec ly in-
eg a ing c op g ow h in o ma ion in o hyd ological models
will enhance he accu acy o p edic ions ega ding i iga ion
needs and wa e esou ce alloca ion. To es hese hypo he-
ses, we compa e h ee modeling app oaches: a s and-alone
c op model, a one-way coupled model (whe e hyd ological
condi ions in luence c op g ow h bu no ice e sa), and a
wo-way coupled model (whe e in e ac ions be ween hyd ol-
ogy and c op g ow h a e ully ep esen ed). By e alua ing
hese di e en app oaches, we aim o de e mine whe he dy-
namic hyd ological–c op g ow h eedbacks imp o e he pe -
o mance o c op yield and i iga ion wa e use simula ions.
Al hough his s udy has a global scale in scope, we limi
his analysis o he con iguous Uni ed S a es (CONUS) e-
gion o keep he analysis ac able and because CONUS
has de ailed in o ma ion on yea ly c op p oduc ion and wa-
e use. CONUS is a majo p oduce and con ibu o o he
global p oduc ion o h ee p ima y c ops: maize, soybean,
and whea . These c ops we e selec ed due o hei subs an-
ial impac on he ag icul u al landscape and hei pi o al
ole in shaping global ood p oduc ion ends. The CONUS
se es as an ideal s udy a ea owing o i s ex ensi e a ail-
abili y o ele an da a, pa icula ly on ag icul u al s a is ics
and i iga ion wa e wi hd awals, which can p o ide a basis
o analysis and model e alua ion. Addi ionally, he CONUS
egion exhibi s di e se clima ic and geog aphic condi ions,
con ibu ing o a be e unde s anding o c op and wa e sys-
em dynamics and hei esponses o a ious en i onmen al
ac o s.
To es he hypo heses coined abo e, he PCR-GLOBWB 2
hyd ological model (Su anudjaja e al., 2018) is coupled o
he WOFOST c op model (de Wi e al., 2019) a a daily
ime s ep and a a 5 a cmin (∼10 km) spa ial esolu ion ap-
plied o CONUS (Sec . 2.1). In examining he in e ac ion be-
ween hyd ology and c op g ow h, we conside bo h one-way
and wo-way in e ac ions. Fi s , a one-way coupling is es-
ablished o e alua e he e ec o he simula ed wa e a ail-
abili y o PCR-GLOBWB 2 o ain ed and i iga ed c op
g ow h in WOFOST (Sec . 2.1 and 2.3.1). In addi ion, a wo-
way coupling is es ablished in which, addi ional o passing
wa e a ailabili y om PCR-GLOBWB 2 o WOFOST, he
c op phenology o WOFOST in e ms o ac ual e apo an-
spi a ion, lea a ea index, and oo ing dep h is ed back in o
PCR-GLOBWB 2 (Sec . 2.1 and 2.3.2). The jus i ica ion o
his coupling app oach, along wi h echnical implemen a ion
de ails, is elabo a ed upon in Sec . 2.2.
Ou amewo k was es ed by compa ing indi idual
WOFOST and coupled one-way and wo-way model uns o
e alua e he impac o eedbacks on c op yield and i iga ion
wa e use (Sec . 2.4). The esul s o hese simula ions a e
compa ed wi h and e alua ed agains epo ed yield s a is-
ics and epo ed annual i iga ion wi hd awals o assess hei
alidi y (Sec s. 2.5 and 3). In he end, we elabo a e on he
unce ain ies, s eng hs, and usabili y o ou coupled model
amewo k o s udying he wa e – ood nexus unde global
change (Sec . 4).
2 Me hods
A newly coupled hyd ological–c op g ow h model ame-
wo k (Fig. 1) is de eloped o include he eedback be ween
c op g ow h and hyd ology. He e, we chose WOFOST as he
c op g ow h model because o i s de ailed c op phenology
and de elopmen and PCR-GLOBWB 2 as he hyd ological
model because o i s de ailed hyd ological p ocess simula-
ion and la ge-scale applicabili y. This amewo k includes
bo h a one-way and wo-way coupling be ween he PCR-
GLOBWB 2 global hyd ological and wa e esou ces model
(Su anudjaja e al., 2018) and he WOFOST c op g ow h
model (de Wi e al., 2019). The coupled amewo k was hen
used o quan i y he impac s o included eedbacks be ween
hyd ology and c op g ow h on a daily ime s ep and 5 a cmin
esolu ion o CONUS.
The ollowing (sub)sec ions p o ide a desc ip ion o he
PCR-GLOBWB 2 and WOFOST models and modules used
(Sec . 2.1), jus i ica ion o coupling (Sec . 2.2), he model
coupling se up (Sec . 2.3), model coupling simula ion expe -
imen s and pa ame iza ion (Sec . 2.3), and alida ion o c op
yield and o i iga ion wa e use (Sec . 2.4).
2.1 Model desc ip ions
2.1.1 PCR-GLOBWB 2
The PCRas e Global Wa e Balance (PCR-GLOBWB 2)
model (Su anudjaja e al., 2018), de eloped a U ech Uni-
e si y, is a global hyd ological and wa e esou ce model
ha ope a es on a la i ude–longi ude g id. This model sim-
ula es he e es ial hyd ological cycle wi h daily esolu-
ion, inco po a ing an h opogenic impac s like human-made
ese oi s, sec o al wa e demands, wi hd awals, consump-
i e use, and e u n lows. PCR-GLOBWB 2 is applied and
es ed ac oss local o global scales.
PCR-GLOBWB 2 u ilizes ime-explici schemes o all
dynamic p ocesses, unning on daily ime s eps o hyd ol-
ogy and wa e use and sub-daily s eps o hyd odynamic
i e ou ing. I simula es mois u e s o age in wo uppe soil
laye s and manages wa e exchange among he soil, a mo-
sphe e, and g oundwa e . A mosphe ic in e ac ions include
h ps://doi.o g/10.5194/hess-29-4219-2025 Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
4222 S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model
Figu e 1. The coupled model amewo k o he PCR-GLOBWB 2 hyd ological and wa e esou ce model and he WOFOST c op g ow h
model along wi h hei model s uc u es. The blue a ow ep esen s he one-way coupling om PCR-GLOBWB 2 o WOFOST and he
a iables ha a e exchanged; he g een a ow is added in case he ull wo-way coupling is conside ed. A he s a o he day, WOFOST
compu es e apo anspi a ion, lea a ea index, and oo ing dep h ha is used by PCR-GLOBWB 2 o compu e soil mois u e s a us. A he end
o he day, soil mois u e s o age in he uppe and lowe laye s om PCR-GLOBWB 2 is ed o WOFOST o compu e c op g ow h o he
nex day.
Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025 h ps://doi.o g/10.5194/hess-29-4219-2025
S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model 4223
p ecipi a ion, e apo a ion, anspi a ion, and snow p ocesses.
The model conside s sub-g id a iabili y in land use, soils,
and opog aphy, in luencing un-o , in e low, g oundwa e
echa ge, and capilla y ise. Run-o is ou ed h ough i e
ne wo ks using me hods anging om simple accumula ion
o kinema ic wa e ou ing, suppo ing loodplain inunda ion
and su ace wa e empe a u e simula ion.
The model includes a ese oi ope a ion scheme o o e
6000 human-made ese oi s om he GRanD da abase, in-
eg a ed acco ding o hei cons uc ion yea . Human wa e
use is comp ehensi ely modeled, es ima ing sec o al wa e
demands and con e ing hem in o wi hd awals om g ound-
wa e , su ace wa e , and desalina ion sou ces, while ac-
coun ing o esou ce a ailabili y and g oundwa e pumping
capaci y. Consump i e use and e u n lows a e calcula ed o
each sec o .
PCR-GLOBWB 2’s lexible s uc u e encompasses i e
main hyd ological modules: me eo ological o cing, land
su ace, g oundwa e , su ace wa e , i iga ion, and wa e
use. The me eo ological module uses g idded empe a u e
and p ecipi a ion da a. Re e ence po en ial e apo a ion is cal-
cula ed using Hamon’s me hod and employed in he land su -
ace module o de e mine c op-speci ic po en ial e apo a ion.
The g oundwa e and su ace wa e modules handle luxes
and s o es o g oundwa e and su ace wa e , espec i ely.
The i iga ion and wa e use module simula es wa e demand,
wi hd awals, consump ion, and e u n lows, sou cing wa-
e om su ace wa e ( i e s and ese oi s), g oundwa e
(bo h enewable and non- enewable), and desalina ed wa e ,
depending on a ailabili y. De ailed desc ip ions o each mod-
ule a e p o ided by Su anudjaja e al. (2018).
2.1.2 WOFOST
WOFOST (WO ld FOod STudies) is a c op simula ion model
de eloped a Wageningen “School o De Wi ”, in he Ne he -
lands, designed o quan i a i ely analyze he c op g ow h and
po en ial p oduc ion o annual ield c ops a he ield scale
(Supi e al., 1994). WOFOST employs a ixed ime s ep
o 1 d o simula e c op g ow h based on eco-physiological
p ocesses such as phenological de elopmen and g ow h (de
Wi e al., 2019). WOFOST has ound ex ensi e applica ion
in assessing he impac s o clima e change and managemen
s a egies on c op g ow h and yield a local o global scales
(D oppe s e al., 2021).
The WOFOST c op model comp ises ou modules: me-
eo ological, c op, as onomical, and soil (Fig. 1). The
WOFOST modules simula e a ange o p ocesses, includ-
ing phenological de elopmen , CO2assimila ion, lea de-
elopmen , ligh in e cep ion, anspi a ion, espi a ion, oo
g ow h, assimila ed pa i ioning o he a ious o gans, and
he o ma ion o d y ma e . The model’s ou pu includes sim-
ula ed c op biomass o al, c op yield, and a iables such as
lea a ea and c op wa e use.
Tempe a u e e ec s on c op de elopmen wi hin
WOFOST a e modeled using empe a u e sums, which
accumula e daily empe a u es abo e a speci ied h eshold.
These sums in luence ge mina ion and phenological s ages,
he eby a ec ing CO2assimila ion. Addi ionally, he model
accoun s o he di ec and indi ec e ec s o subop imal
day ime empe a u es on c op g ow h and de elopmen ,
which a e c i ical o o e all plan pe o mance. Daily
pho osyn hesis in he c op g ow h model is simula ed by
conside ing abso bed adia ion and wa e s ess. A e ac-
coun ing o he assimila es used in main enance espi a ion,
he emaining esou ces a e alloca ed among he plan ’s
lea es, s ems, oo s, and s o age o gans. A key in e nal
d i e o his p ocess is he lea a ea index (LAI), which
esul s om lea a ea dynamics go e ned by pho osyn hesis,
biomass alloca ion, lea age, and de elopmen al s age. LAI,
in u n, in luences he daily a es o pho osyn hesis.
WOFOST has been inely uned o accoun o di e se cli-
ma e and soil condi ions, pa icula ly o commonly s udied
c ops such as maize, soybean, and whea , he eby educing
he need o u he ecalib a ion. This p e- uning ensu es
ha simula ions eliably cap u e he g ow h and yield e-
sponses o hese c ops unde a ying en i onmen al condi-
ions. Fo mo e de ailed in o ma ion on he ine uning o
c op a iables, see de Wi and Boogaa d (2021).
WOFOST employs a classic wa e balance app oach de-
signed o eely d aining soils whe e g oundwa e is oo
deep o a ec soil mois u e con en in he oo ing zone. This
app oach di ides he soil p o ile in o wo compa men s: he
oo ed zone and he lowe zone ex ending om he ac ual
oo ing dep h o he maximum oo ing dep h. The subsoil be-
low his maximum oo ing dep h is no conside ed. As oo s
ex end deepe owa ds he maximum oo ing dep h, he lowe
zone g adually me ges wi h he oo ed zone. This app oach
is sui able o egional applica ions wi h limi ed soil p op-
e y in o ma ion. Soil mois u e in he oo zone se es as a
p ima y link be ween he WOFOST model and he unde ly-
ing soil module. Fo a de ailed desc ip ion o he WOFOST
c op g ow h model, we e e o de Wi and Boogaa d (2021)
and Supi e al. (1994).
2.2 Jus i ica ion o model coupling
The in eg a ion o he hyd ological model PCR-GLOBWB 2
(Su anudjaja e al., 2018) wi h he c op g ow h model
WOFOST (Supi e al., 1994) is c ucial o accu a ely sim-
ula ing he complex in e ac ions be ween wa e a ailabil-
i y and c op de elopmen . The hyd ological model PCR-
GLOBWB 2 is designed o simula e hyd ological p ocesses
such as i e discha ge, g oundwa e low, and wa e s o age
dynamics. I p o ides de ailed ep esen a ion and insigh s
in o he s a e and dynamics o wa e esou ces o e la ge
spa ial scales and long empo al scales. On he o he hand,
he c op g ow h model WOFOST is ocused on simula ing
c op phenology, including he s ages o c op de elopmen ,
h ps://doi.o g/10.5194/hess-29-4219-2025 Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
4224 S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model
g ow h, and yield o ma ion unde a ying en i onmen al
condi ions.
Despi e he s eng hs o each model, hey indi idually
ha e limi a ions ha can a ec he accu acy o simula ions.
PCR-GLOBWB 2 elies on s a ic ege a ion pa ame e s,
such as ixed lea a ea index (LAI) and oo dep h, which can
limi i s abili y o e lec he dynamic na u e o c op g ow h.
On he o he hand, WOFOST o e s a de ailed and dynamic
ep esen a ion o c op phenology and de elopmen , adjus ing
pa ame e s like LAI and oo dep h based on ac ual g ow h
s ages. Howe e , WOFOST employs a simpli ied wa e bal-
ance model, which may no adequa ely cap u e complex hy-
d ological in e ac ions.
To add ess hese limi a ions, i is impo an o combine he
s eng hs o bo h models o enhance hyd ological and c op
modeling pe o mance. By in eg a ing WOFOST’s de ailed
c op g ow h simula ion capabili ies wi h he obus hyd o-
logical p ocess simula ions o PCR-GLOBWB 2, we can be -
e unde s and and ep esen he soil–plan –a mosphe e in e -
ac ions. The e o e, his s udy in eg a es PCR-GLOBWB 2
and WOFOST by passing soil mois u e da a om PCR-
GLOBWB 2 o WOFOST and eeding ege a i e luxes om
WOFOST back in o PCR-GLOBWB 2 on a daily basis. Ad-
di ionally, o unde s and he in ica e dynamics be ween hy-
d ology and c op model, PCR-GLOBWB 2 is coupled o
WOFOST in one-way and wo-way in e ac ions.
In e alua ing a ious coupling me hods o in eg a ing
hyd ological and c op models, we iden i ied se e al ap-
p oaches, including one whe e he hyd ological model di-
ec ly p o ides de ailed i iga ion schedules and pe cola ion
a es o he c op model. While his me hod o e s highly de-
ailed hyd ological inpu s, i o en leads o inconsis encies
due o he sepa a e handling o soil mois u e dynamics be-
ween he models, esul ing in e o s in soil mois u e man-
agemen and wa e balance. Commonly used coupling p o-
cedu es, such as hose desc ibed by Li e al. (2014) and
Tsa ouchi e al. (2014), calcula e po en ial e apo anspi a-
ion and ege a ion wa e up ake wi hin he hyd ological
model, which is hen passed o he c op model o simula e
c op g ow h. The c op model hen calcula es s a e a iables
like lea a ea index, oo dep h, and canopy heigh , which
a e subsequen ly ed back in o he hyd ological model. How-
e e , hese me hods can in oduce sys em e o s, pa icula ly
in he anspi a ion module, i he e is a disc epancy be ween
e apo anspi a ion calcula ed by he c op and hyd ological
model, as highligh ed by Wang e al. (2012). Ou chosen
coupling me hod, whe e soil mois u e is calcula ed by PCR-
GLOBWB 2 and passed o WOFOST and ege a i e dynam-
ics and e apo anspi a ion luxes a e hen ed back in o PCR-
GLOBWB 2, o e s a balanced app oach ha ensu es con-
sis ency and he necessa y complexi y and e iciency in he
simula ions.
The selec ed coupling app oach also add esses speci ic
challenges associa ed wi h he models. PCR-GLOBWB 2 al-
lows o lexible land co e classi ica ion and pa ame iza-
ion, which is essen ial o accu a ely ep esen ing di e se
c op ypes and hei in e ac ions wi h wa e esou ces. Fo
his s udy, we de ined 12 land co e ypes ( all na u al, sho
na u al, pas u e, i iga ed maize, i iga ed soybean, i iga ed
whea , non-paddy i iga ed c ops (i iga ed o he c ops),
paddy i iga ed c op, ain ed maize, ain ed soybean, ain ed
whea , and ain ed o he s). WOFOST’s ole in his coupling
is o pass he luxes o i iga ed and ain ed maize, soybean,
and whea o PCR-GLOBWB 2, ensu ing a de ailed simula-
ion o c op wa e use.
One o he key conside a ions in his coupling is accu a ely
calcula ing he soil-wa e balance. Gi en i s mo e ad anced
soil mois u e accoun ing scheme, PCR-GLOBWB 2 handles
his aspec , as WOFOST’s simple single-laye leaky bucke
app oach could in oduce complexi ies i soil mois u e da a
we e passed om WOFOST o he mul i-laye ed soil model
o PCR-GLOBWB 2. The e o e, he coupling app oach we
selec ed minimizes po en ial disc epancies while maximiz-
ing he s eng hs o each model.
I is impo an o acknowledge ha indi idual models
come wi h inhe en unce ain ies, ela ed o model s uc u e,
pa ame e s, and da a. When coupling hese models, he le el
o unce ain y compounds u he (Kanda e al., 2018). Ad-
di ionally, he na u e o coupling i sel can in oduce ano he
laye o unce ain y. Acco ding o An le e al. (2001), cou-
pling models leads o u he concep ualiza ion and compu-
a ional p oblems, ele a ing unce ain y le els. The e o e, an
e icien coupling is essen ial o minimize hese isks. The e
a e h ee p ima y me hods o coupling models (Ve eecken e
al., 2016): ligh /loose coupling, ex e nal/ amewo k coupling
using a cen al couple , and ull coupling.
In ligh o loose coupling, he ou pu o one model se es
as he inpu o he o he , which can lead o a s aigh o wa d
bu limi ed in e ac ion. F amewo k coupling uses a cen al
couple o communica ion be ween models wi hou equi -
ing code modi ica ion, o e ing a balance be ween in eg a ion
and lexibili y. Full coupling in ol es bo h models sha ing
he same bounda y condi ions, d i e s, and a iables, which
equi es signi ican code modi ica ion.
2.2.1 Implemen a ion o he (BMI) amewo k
coupling
Gi en he complexi y o in eg a ing he PCR-GLOBWB 2
and WOFOST models and he need o e icien simula ions,
we op ed o amewo k coupling. This app oach was cho-
sen because WOFOST and PCR-GLOBWB 2 a e w i en in
di e en p og amming languages (C and PCRas e -Py hon,
espec i ely). F amewo k coupling allows o seamless in-
e ac ion be ween he models a each ime s ep, acili a ing
dynamic exchanges while limi ing I/O- ela ed compu a ion
imes. We employed he Basic Model In e ace (BMI) o
his pu pose (Hu on e al., 2020; Peckham e al., 2013). The
decision o use BMI o e al e na i e echniques was d i en
by i s non-in e e ing na u e, ensu ing no code en anglemen
Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025 h ps://doi.o g/10.5194/hess-29-4219-2025
S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model 4225
and acili a ing seamless connec ion be ween he wo mod-
els. BMI unc ions ac as a b idge, enabling di ec a iable
exchange be ween WOFOST and PCR-GLOBWB 2 wi h-
ou modi ying hei sou ce code. This non-in asi e app oach
ensu es a lexible and obus coupling amewo k, allowing
con inuous model de elopmen wi hou in e up ions. In e-
g a ing BMI unc ions in o bo h models p o ides a se o
unc ions o e ie ing o al e ing model a iables, he eby
enhancing adap abili y and e iciency.
An addi ional w appe was equi ed o ansla e he model-
speci ic BMI unc ions in o Py hon-compa ible in o ma ion
o es ablish a Py hon-based coupling amewo k. The Ba-
belize w appe (CSDMS, 2024) was u ilized o his pu -
pose wi h he WOFOST BMI. Con e sely, no supplemen-
a y w appe is needed in he PCR-GLOBWB 2 BMI, as he
model is inhe en ly Py hon-compa ible due o i s p og am-
ming language.
The Babelize w appe acili a es he in eg a ion o he
WOFOST model by u ilizing an inpu ile ha p o ides es-
sen ial de ails, including he model lib a y, en y poin , pack-
ages, and au ho in o ma ion. This inpu ile guides he con-
s uc ion o he necessa y dependencies o gene a e Py hon
bindings. Once hese Py hon bindings a e c ea ed, Babelize
ensu es he success ul in eg a ion o he WOFOST BMI in o
Py hon by e i ying ha he bindings a e co ec ly buil and
loaded.
2.2.2 Wo k low o PCR-GLOBWB 2–WOFOST model
amewo k
In he PCR-GLOBWB 2–WOFOST coupling amewo k, he
wo k low a e implemen ing BMI unc ions emains consis-
en o bo h one-way and wo-way coupling, up un il he
ini ializa ion o he hyd ological and c op models (Fig. 2).
Be o e ini ia ing he Py hon session, i is c ucial o ac-
i a e he BMI w ap en i onmen , which includes all nec-
essa y lib a ies o bo h hyd ological and c op models. A -
e his se up, he PCR-GLOBWB 2 and WOFOST models,
along wi h hei con igu a ion iles ha de ine he coupling
se ings, a e loaded in o he Py hon session. BMIw ap eads
he con igu a ion ile, ini ializing he model-speci ic con ig-
u a ion se ings be o e es ablishing bo h models as a coupled
en i y.
Once he coupled models a e ini ialized, a loop is ini ia ed,
commencing a he s a ime and concluding a he end ime.
Du ing each i e a ion o his loop, a iables a e exchanged
be ween he models based on he one-way o wo-way cou-
pling con igu a ion. This i e a i e p ocess ensu es a con in-
uous and seamless low o in o ma ion be ween he PCR-
GLOBWB 2 hyd ological model and he WOFOST c op
model h oughou he simula ion pe iod.
2.3 Model coupling se up
The de eloped PCR-GLOBWB 2–WOFOST coupled model
amewo k in eg a es hyd ological and c op models h ough
bo h one-way and wo-way couplings, as illus a ed in Figs. 1
and 3. This model coupling aims o assess he in ica e in e -
ac ions be ween hyd ology and c op g ow h unde di e en
ag icul u al condi ions, speci ically i iga ed and ain ed se -
ings. The one-way coupling examines he impac o wa e
a ailabili y on c op g ow h, while he wo-way coupling in-
co po a es he exchange o soil mois u e s a us and hyd o-
logical pa ame e s and luxes based on c op s a us.
2.3.1 One-way coupling
In he one-way coupling, in o ma ion on soil mois u e s a-
us is passed om PCR-GLOBWB 2 o WOFOST (Fig. 3b).
He e, PCR-GLOBWB 2 simula es soil mois u e con en o
e e y day, and he soil wa e s o age is simula ed sepa a ely
o each land co e ype. Consequen ly, WOFOST ecei es
he soil mois u e con en om PCR-GLOBWB 2 as inpu ,
wi h gene ally highe alues o soil mois u e o i iga ed
c ops han o nea by ain ed c ops. WOFOST hen simu-
la es he c op yield based on he simula ed soil mois u e con-
en and he same me eo ological inpu s as PCR-GLOBWB 2
uses.
The combined model amewo k cap u es he impac o
hyd oclima ic condi ions by assessing wa e s ess and hea
s ess. Wa e s ess, in luenced by soil mois u e le els de-
i ed om PCR-GLOBWB 2, a ec s a ious p ocesses in
WOFOST such as a educ ion in he lea a ea, a dec ease in
he assimila ion o biomass (g ow h), changes in he pa i-
ioning o biomass, and an inc ease in a ious plan o gans
o senescence (aging p ocesses). Ele a ed empe a u es ha e
a ying e ec s ac oss di e en s ages o c op de elopmen .
They can accele a e c op g ow h by p omo ing as e accu-
mula ion o g owing deg ee days, which a e essen ial o
de e mining c op ma u i y. Howe e , p olonged exposu e o
high empe a u es can also induce hea s ess, ad e sely im-
pac ing c op heal h and po en ially sho ening he o e all du-
a ion o he c op’s g ow h cycle. Insu icien wa e a ailabil-
i y ha limi s he e apo anspi a ion also educes he amoun
o assimila ion and he co esponding yield.
2.3.2 Two-way coupling
–In addi ion o one-way coupling, he wo-way cou-
pling app oach in ol es i e a ing da a exchange be-
ween WOFOST and PCR-GLOBWB 2 wice pe day.
WOFOST calcula es he ege a ion s a es (such as
lea a ea index (LAI), biomass, and oo dep h) and
luxes (e.g., e apo anspi a ion) o i iga ed and ain ed
maize, soybean, and whea c ops, while o he ege a-
ion and non- ege a ion luxes o o he c ops a e simu-
la ed wi hin PCR-GLOBWB 2. To be mo e speci ic, o
h ps://doi.o g/10.5194/hess-29-4219-2025 Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
4226 S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model
Figu e 2. Schema iza ion o he wo k low o he coupled PCR-GLOBWB 2–WOFOST model amewo k.
he ac ion o land co e ha is di e en om maize,
whea , and soybean, he ege a ion s a es and luxes a e
calcula ed wi hin he PCR-GLOBWB 2. Fo hese land
co e ypes, ege a ion phenology in he o m o c op
ac o s is app oxima ed by a yea ly clima ology. In he
wo-way coupling, da a a e exchanged be ween PCR-
GLOBWB 2 and WOFOST as ollows (Fig. 3c): a he
s a o he day, PCR-GLOBWB 2 passes he p e ious
day’s soil mois u e o he WOFOST, assuming no oo
de elopmen has occu ed o e nigh . WOFOST hen
compu es he po en ial e apo anspi a ion based on he
me eo ological a iables a he cu en ime s ep and he
pe inen ege a ion s a es om he p e ious ime s ep
(lea a ea index (LAI), oo ing dep h, and c op heigh ).
I also calcula es he ac ual ba e soil e apo a ion, ac-
ual anspi a ion (ac ual e apo anspi a ion), po en ial
e apo a ion, and open wa e e apo a ion.
–The calcula ed luxes a e passed o PCR-GLOBWB 2,
oge he wi h he oo dep h. The oo dep h is used o
pa i ion he ac ual anspi a ion om he single oo
zone o WOFOST o e he wo soil laye s o PCR-
GLOBWB 2, dependen on he oo con en . Fo bo h
i iga ed and ain ed c ops, he ac ual e apo anspi a-
ion om WOFOST is o ced o PCR-GLOBWB 2 and
used o upda e he soil mois u e con en o he wo soil
laye s in PCR-GLOBWB 2 o he cu en daily ime
s ep.
–In he case o i iga ed c ops, he s ages o ege a ed de-
elopmen a e used o compu e he amoun o i iga ion
in PCR-GLOBWB 2. Po en ial e apo a ion is used o
calcula e he i iga ion wa e demand o paddy c ops
(no conside ed he e), whe eas he i iga ion wa e e-
qui emen o non-paddy c ops is compu ed based on
he soil mois u e s a us acco ding o he FAO guidelines
(Allen e al., 1998). The i iga ion wa e equi emen is
wi hd awn om he a ailable wa e esou ces in PCR-
GLOBWB 2, and he a ailable i iga ion wa e supply
is applied o he c ops in addi ion o any na u al p ecip-
i a ion.
–A he end o he day, he esul ing soil mois u e om
he wo soil laye s om PCR-GLOBWB 2 is agg ega ed
o p o ide a o al o he oo zone o each c op, which
is hen passed back o WOFOST.
–Using he upda ed soil mois u e om PCR-
GLOBWB 2, WOFOST compu es he ac ual an-
spi a ion and upda es c op g ow h and he c op s a us.
The new luxes and c op pa ame e s a e hen passed o
PCR-GLOBWB 2 again on he nex day (Figs. 1 and
3c).
In his wo-way coupling, he c op phenology om
WOFOST de e mines e apo anspi a ion and hus he soil
hyd ology o PCR-GLOBWB 2, pa icula ly du ing d y
spells. Compa ed o he p ede ined phenology o PCR-
GLOBWB 2, he LAI, oo ing dep h, and e apo anspi a-
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S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model 4227
Figu e 3. Schema ic iew o he coupled model amewo k: panel (a) shows he calcula ed phenology om WOFOST and PCR-GLOBWB 2
o e ime along wi h he associa ed luxes. Panel (b) displays a de ailed ep esen a ion o he one-way coupling app oach, whe e soil mois u e
is ans e ed om PCR-GLOBWB 2 o WOFOST, and panel (c) illus a es he wo-way coupling app oach, whe e a iables a e exchanged
in bo h di ec ions be ween PCR-GLOBWB 2 and WOFOST.
ion as simula ed by WOFOST will lag du ing d y spells and
less wa e may be los om PCR-GLOBWB 2. Howe e , he
hinne oo ing dep h will also lead o an ea lie d ying ou o
he soil and educed capilla y ise. This subsequen ly leads o
educed soil mois u e (compa ed o PCR-GLOBWB 2 s and-
alone), which in u n eeds back o a educed simula ed yield
in WOFOST, in pa icula o ain ed c ops. Fo i iga ed
c ops, he ex a wa e supplied will la gely o se hese eed-
backs and esul in nea -op imum g ow h.
2.4 Model coupling simula ion expe imen s and
pa ame iza ion
Hyd ological simula ions we e conduc ed wi h a daily ime
s ep a a 5 a cmin g id esolu ion, whe e o each g id cell
WOFOST was used o simula e c op g ow h o i iga ed
and ain ed maize, soybean, and whea . To assess he im-
pac o hyd ology on c op g ow h and unde s and he in e -
ac ions be ween hyd ology and c op g ow h, h ee se s o
simula ions we e ca ied ou o bo h i iga ed and ain ed
c ops: (a) s and-alone simula ions using he WOFOST c op
model solely, (b) one-way coupled, and (c) wo-way cou-
pled PCR-GLOBWB 2–WOFOST simula ions. No e ha o
he s and-alone simula ions wi h WOFOST unde i iga ion
he po en ial c op yield is simula ed, which is po en ial yield
wi hou wa e (and nu ien ) s ess excep o empe a u e e -
ec s. When coupled o PCR-GLOBWB 2, wa e s ess can
occu e en o i iga ed c ops in case he e is no enough wa-
e a ailable (in PCR-GLOBWB 2) o ully sa is y he c op
wa e demand. Fo ain ed c ops, g ow h is in luenced by
a ailable soil mois u e o all simula ions and is hus sen-
si i e o wa e s ess and empe a u e. G een wa e om na -
u al ain all is he p ima y wa e supply in ain ed analysis,
while i iga ed c ops ge wa e om bo h g een and blue wa-
e ( om su ace wa e and enewable g oundwa e ) and non-
enewable g oundwa e , leading o g oundwa e deple ion.
Daily ime s ep simula ions co e ed he pe iod om 1979
and 2019, using wea he a iables (minimum and maximum
ai empe a u e, sho wa e adia ion, p ecipi a ion, apo
p essu e, wind speed, and humidi y) om he W5E5 o c-
ing da a (Lange e al., 2021) as inpu o PCR-GLOBWB 2
h ps://doi.o g/10.5194/hess-29-4219-2025 Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
4234 S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model
Figu e 6. Mean i iga ed c op yields o maize, soybean, and whea wi hin CONUS as ob ained om s and-alone, one-way and wo-way
coupled simula ions and di e ences be ween one-way and wo-way coupled simula ions o 1979–2019. Legend in pe cen age o alues
shown on he yaxes.
Figu e 7. Mean ain ed c op yields o maize, soybean, and whea wi hin CONUS as ob ained om s and-alone, one-way and wo-way
coupled simula ions and di e ences be ween one-way and wo-way coupled simula ion o 1979–2019. Legend in pe cen age o alues
shown on he yaxes.
Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025 h ps://doi.o g/10.5194/hess-29-4219-2025
S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model 4235
Figu e 8. Coe icien o a ia ion (CV) o e 1979–2019 o i iga ed c op yields o maize, soybean, and whea wi hin CONUS as ob ained
unde s and-alone, one-way, and wo-way coupling and he di e ence be ween one-way and wo-way coupling.
Figu e 9. Coe icien o a ia ion (CV) o e 1979–2019 o ain ed c op yields o maize, soybean, and whea wi hin CONUS as ob ained
unde s and-alone, one-way, and wo-way coupling and he di e ence be ween one-way and wo-way coupling.
4 Discussion and conclusion
In his s udy, we de eloped a coupled hyd ological–c op
g ow h model amewo k o in es iga e he in ica e eed-
backs be ween wa e a ailabili y and c op g ow h wi hin
he CONUS egion ocusing on maize, soybean, and whea .
This discussion del es in o he implica ions o he indings,
emphasizing hei signi icance and add essing bo h me hod-
ological conside a ions and inhe en unce ain ies.
We hypo hesized ha a mo e ealis ic ep esen a ion o
soil mois u e dynamics and wa e a ailabili y will lead o
be e es ima es o wa e s ess and yield ou comes. Valida-
h ps://doi.o g/10.5194/hess-29-4219-2025 Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
4236 S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model
Figu e 10. Spa ial a ia ion o one-way and wo-way i iga ion
wa e wi hd awal compa ed wi h USGS- epo ed wa e wi hd awal
da a pe s a e o all c ops ac oss he CONUS egion wi h a loga-
i hmic scale.
Figu e 11. Tempo al a ia ion o one-way and wo-way i iga ion
wa e wi hd awal compa ed wi h USGS wa e wi hd awal da a o
5-yea in e als ac oss he CONUS egion wi h a loga i hmic scale.
ion agains epo ed yields howe e did no show a no able
imp o emen compa ed o he s and-alone WOFOST, bo h
o ain ed and o i iga ed ag icul u e. Thus, i he ocus
is on yield only, coupling wi h a hyd ological model such
as PCR-GLOBWB 2 seems no needed. Howe e , al hough
no picked up by he alida ion exe cise, he coupling s ill al-
lows he inclusion o he impac o limi ed i iga ion wa e
a ailabili y as well as he impac o c op de elopmen on he
hyd ological sys em. Ou s udy also shows ha i he ocus is
on hese impac s, i is necessa y o use a wo-way coupling o
make su e ha c op de elopmen s eed back on e apo a ion
and soil mois u e.
Ano he hypo hesis we es ed is whe he in eg a ing eal-
ime c op g ow h in o ma ion in o hyd ological models
will enhance he accu acy o p edic ions ega ding i iga-
ion needs and wa e esou ce alloca ion. Al hough i can
be expec ed ha eeding back c op in o ma ion o PCR-
GLOBWB 2 in he wo-way coupling would imp o e es i-
ma es o i iga ion wa e wi hd awal, his could no be sub-
s an ia ed by compa ison wi h epo ed wa e wi hd awal
s a is ics. One possible explana ion is he use o cons an c op
a ea da a ac oss all yea s, which in oduces unce ain ies and
limi s he model’s esponsi eness o ac ual land-use dynam-
ics.
The spa io empo al analysis o hyd ological impac s on
c op g ow h con i ms he esul s shown om he compa i-
son wi h epo ed alues. No ably, o ain ed c ops, he es-
ima ed yield is mos ly highe o one-way coupled simu-
la ions compa ed o wo-way and s and-alone simula ions.
Also, he in e -annual a ia ion o yield, ha is, he sensi-
i i y o d ie and we e yea s, is no ably highe o he wo-
way coupled and s and-alone simula ions han he one-way
coupled simula ions. This sugges s ha o a co ec sensi i -
i y o d ough , a wo-way coupling ha includes he eedback
o c op s a us o he hyd ological sys em is needed.
Ou s udies adds o p e ious wo k by D oppe s e
al. (2021), which in es iga ed wo ldwide wa e cons ain s
and sus ainable i iga ion by coupling he Va iable In il a-
ion Capaci y (VIC) hyd ological model wi h WOFOST, and
Zhang e al. (2021), who ocused on e ining he coupled
VIC hyd ological model wi h a c op g ow h model EPIC
by inco po a ing he e apo anspi a ion module a a egional
scale. In compa ison, ou esea ch ex ends he analysis o a
ine spa ial scale and places a s onge emphasis on he com-
p ehensi e in eg a ion o eedback loops be ween hyd ology
and c op g ow h. Pa icula ly, we demons a e he impo -
ance o wo-way coupling in cap u ing ealis ic yield ou -
comes, which is pa icula ly e iden o ain ed c ops. This
is mainly because he wo-way coupled sys em add esses
he in luence o c op s a us on e apo anspi a ion and oo -
ing dep h, he eby impac ing soil mois u e con en , which in
u n eed backs on c op g ow h. The wo-way coupling ap-
p oach p o ides a mo e ealis ic depic ion o wa e a ailabil-
i y o c ops, which esul s in la ge in e -annual a iabili y
and lowe mean c op yields when in e -annual clima e a i-
abili y is signi ican . Including his wo-way in e ac ion is
pa icula ly impo an unde d ie condi ions (see Sec . 3.2)
o i he coupled amewo k is used o assess educed su -
ace wa e a ailabili y unde clima e change o he impac o
en i onmen al cons ain s on g oundwa e and su ace wa e
use.
While he esul s o his s udy o e aluable insigh s in o
he coupled hyd ological–c op g ow h model amewo k, i
is essen ial o ecognize and add ess he unce ain ies as-
socia ed wi h he s uc u e and pa ame iza ion, as well as
inhe en limi a ions in he esea ch. A signi ican limi a ion
is ha he s udy does no accoun o po en ial ad ance-
Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025 h ps://doi.o g/10.5194/hess-29-4219-2025
S. Che u u e al.: Feedbacks be ween wa e a ailabili y and c op sys ems using a coupled model 4237
men s in ag icul u al echnology and e ol ing a ming p ac-
ices, which could impac c op yields. This becomes e iden
when compa ing yield es ima es wi h obse a ions o e ime
(Sec . 3.1; Fig. 4).
Fu he mo e, unce ain ies linked o inpu da ase s (Po -
wollik e al., 2017; Roux e al., 2014) such as c op calen-
da s, cul i a s, and land-use changes in oduce po en ial lim-
i a ions and implica ions o he s udy esul s. Accu a e ep-
esen a ions o c op g ow h dynamics hinge on accu a e c op
calenda de ini ions (Wang e al., 2022), encompassing plan -
ing, ma u a ion, and ha es ing pe iods. Va ia ions in hese
imelines due o clima e change o e ol ing ag icul u al p ac-
ices po en ially in oduce unce ain ies in yield p edic ions.
Addi ionally, he assump ion o s a ic cul i a s neglec s po-
en ial shi s in ag icul u al p ac ices o he in oduc ion o
new a ie ies, in luencing c op g ow h esponses o en i on-
men al s esso s o e ime. Land-use changes u he con-
ibu e o unce ain ies (P es ele e al., 2016; Eckha d e al.,
2003; Dendoncke e al., 2008) as dynamic shi s in ag icul-
u al p ac ices al e wa e demand, e apo anspi a ion pa -
e ns, and o e all hyd ological dynamics. Igno ing hese po-
en ial shi s limi s he model’s abili y o cap u e he complex
in e ac ions be ween wa e and c op sys ems, and his should
be conside ed in u u e de elopmen s eps.
Hence, u u e wo k should also conside ep esen ing he
dynamic na u e o c op a eas, including bo h i iga ed and
ain ed c op ha es a eas, as well as he o al c op a ea.
The assump ion o cons an a eas, as made in p io s ud-
ies (Mülle e al., 2017; Ai and Hanasaki, 2023; Jäge mey
e al., 2021), was based on da a a ailabili y cons ain s bu
acknowledging he po en ial a iabili y in hese ac o s o e
ime. Add essing his aspec is c ucial o enhancing he ac-
cu acy o yield calcula ions and, consequen ly, ad ancing
he o e all unde s anding o hyd ological–c op g ow h in-
e ac ions. The in eg a ion o such a iabili y in o modeling
amewo ks is essen ial no only o imp o ing he accu acy
o assessmen s bu also o con ibu ing o an enhanced un-
de s anding o he b oade wa e – ood nexus.
In conclusion, he de elopmen and applica ion o he wo-
way coupled hyd ological–c op g ow h model amewo k
p esen ed in his s udy ep esen a signi ican ad ancemen
in ou abili y o unde s and he cascading mechanisms and
eedbacks be ween wa e and c op sys ems. Al hough i does
no show an imp o emen o yield es ima es pe se, he cou-
pling amewo k enhances ou unde s anding o he in e play
be ween hyd ology and c op g ow h. Also, h ough he sec-
o al wa e use modules o PCR-GLOBWB 2, i con ains he
necessa y componen s o e alua e la ge-scale wa e use man-
agemen s a egies and simula e he la ge-scale impac s o
in o med decision-making unde change, pa icula ly when
dealing wi h hyd oclima ic ex emes.
Code and da a a ailabili y. The de eloped coupled PCR-
GLOBWB 2-WOFOST model amewo k is a ailable a
h ps://doi.o g/10.5281/zenodo.10681452 (Che u u, 2024).
The da ase s used in he coupled model amewo k a e a ailable
a h ps://opendap.4 u.nl/ h edds/ca alog/da a2/pc globwb/ e sion_
2019_11_be a/pc globwb2_inpu /ca alog.h ml (las access: 30
Augus 2025).
Supplemen . The supplemen ela ed o his a icle is a ailable on-
line a h ps://doi.o g/10.5194/hess-29-4219-2025-supplemen .
Au ho con ibu ions. SC designed he s udy and pe o med he
analyses, alida ion, and isualiza ion o he esul s unde he su-
pe ision o LPH B, MTH V, and MFPB. SC de eloped he cou-
pled amewo k in close collabo a ion wi h LPH B. JA con ibu ed
o he concep ualiza ion o so wa e. SC w o e he o iginal d a
manusc ip , and all co-au ho s e iewed and edi ed he manusc ip .
Compe ing in e es s. The con ac au ho has decla ed ha none o
he au ho s has any compe ing in e es s.
Disclaime . Publishe ’s no e: Cope nicus Publica ions emains
neu al wi h ega d o ju isdic ional claims made in he ex , pub-
lished maps, ins i u ional a ilia ions, o any o he geog aphical ep-
esen a ion in his pape . While Cope nicus Publica ions makes e -
e y e o o include app op ia e place names, he inal esponsibili y
lies wi h he au ho s.
Acknowledgemen s. The au ho s acknowledge B am D oppe s
(U ech Uni e si y) and Iwan Supi (Wageningen Uni e si y) o
hei aluable ad ice on he WOFOST c op model.
Financial suppo . This esea ch has been unded by he Eu opean
Union Ho izon p og am GoNexus p ojec (g an ag eemen num-
be 101003722). Michelle T. H. an Vlie was inancially suppo ed
by he Ne he lands Scien i ic O ganisa ion (NWO) by a VIDI g an
(VI.Vidi.193.019) and he Eu opean Resea ch Council (ERC) un-
de he Eu opean Union’s Ho izon Eu ope Resea ch and Inno a ion
p og am (g an ag eemen 101039426 B-WEX).
Re iew s a emen . This pape was edi ed by Sh addhanand Shukla
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h ps://doi.o g/10.5194/hess-29-4219-2025 Hyd ol. Ea h Sys . Sci., 29, 4219–4239, 2025
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