Introduction I think there i.\' a lI'odd marketjor maybe five cOlI/p"lers.
Thomas Wabon. pres;c!..:n! of IB M, 1943
The theoret ical foundati on for minfall- runoff modelling
"as built upon the c.'\ccplional scholarshi p o f Adhcmar
Jean Claude Ba rre de Sainl-Venant (1797- 1886),
lIenr: Philibert Gaspard Darcy (1 803- 1858), Edgar
Buckingham ( 1867- 1940), Karl von Termghi (1883­
1(63). Marion King Hubbert (1 903- 1989), Lorenzo
Adolph Richards ( 1904 19 93 ), Ho ward Pellma n ( 1909­
1984), Si r Michael James Lighlhill (1924- 1998). Ger:l td
Beresford Whitham (1927- ), amI John Lenno.'\ Monte ith
(lq29~). Obviously. an appreciation fo r the past is
c\')Cntial for eOicicntly mo ving forward inlo the futu re.
The Benchmark P{/per~' in Geology book series (e.g. Back
& Freen . 1983: Freeze & 133ck, 1983 ). the Critical
CQI/cep/s in Geography book series (e.g. Kirkby, 2004;
Slaymaker. 2004), and the IAI IS Benchmark Pa~rs ill
f/I'dr%g\' book series (i.e. Beven, 2006a; Gash &
Shuttlcwonh. 2007; Anderson, 2008) a rc al l exce llent
collections of important contributions.
This \olume of collected pape rs can be viewed as a
companion 10 an earlier volume in this same series
~'nti t lcd Sireamflo\\" Genera/ioll
Pl"Ocesses (Beven,
2006a). Beven's collection of bC1\ch nwrk papers focuse s
on field studies; he purposely excl udes modelling papers.
Ikrein, the emphasis is placed on hydrological·response
simulation. These simulation cOo rts arc related to the
d~,clopmcnt of an enhanced understandi ng of mi nfall­
mnoIT processes and the sometimes quixotic search fo r
process· based models that ,"'o illd prove 10 have
operational \alue.
Benchmark selection
What constitutes a benc hma rk paper? T he guidcli ncs for
thL~ benchmark series denote that thc selected papers
pro\ ide the foundations fo r hydrology in the 20th century
(Anderson, 2008). Comp.,red to hydro geology/ground­
I'oatcr (Back & Freeze. 1983; Freeze & Back, 1983 :
..... ndeTSOn, 2008 ), the bread th of material considered for
this \ol utne is rather narrow. Spcc itical1 y. the fOCus here
i~ process-Ix!sed simulation of surface/ncar-surface
h)drologka l response at the hillslopek utehmem sca le.
Ob\iou..,ly, bot h om understanding of streamnow
generation processes and the level or rigour associated
"jth rainfall runolf modell ing has evolved considerably
during the 20th .:entury. It is import:lIlt to note thai
operational hydrology was nOI considered in the selection
of papcn; lor this \ olume. The cut-ofT year sett led o n lo r
th l~ \01U111e is 1989 (i.e. 20+ years in prin t). Examples of
cut-oIT causal ities arc VandcrKwaak & Loague (200 1),
Ebcl et {II. (2007b), and Heppner & Loague (2008). In the
cnd. 30 papers (with a tolal of 35 d ifferent authors) were
selected. Interestingly, almost one third of the selec ted
papers were based 0 11 PhD research efforts. The 30
papers, identified in grou ps of 10 belo w, arc presented in
the order of the date of their publication. which to;. large
degree c hronieles the evolution or rainfall- runoff model­
li ng up until 1989.
Mulvany (1851 , Paper I ). the only selected paper
no t from the 20lh centu ry. presents the rat ional method
for estimat ing peak now, wh ich is cons idered by most to
be the first rainfall to m no O'model. Ross (1921. Paper 2)
demonstrates a t ime/conto ur approach fo r estimating
ru noff production for d ilferent areas and times, enabling
the generation of a hydrograph. Richards (193 1. Pa per 3)
deve loped the nonl inear partial-di lferential equation
( Richards equation) for the movement of water in the
unsaturated ncar surface. Shennan (1932, Paper 4)
introduced the unit· graph (unil· hydrograph) method as a
linear (given effective r.li nfal1 and stann runofl) rainfall­
m noff model. Mock us ( 1949, Pape r 5 ) provides the
empi rical basis fo r what wou ld become the SCS-CN (Soil
Conservat ion Service - eurve nu mber) approach,
essentiall y estimati ng e ffec tivc r.linfa ll. Doogc ( 1959,
Puper 6) is a lucid exp lanation o f the general theory for
the unit hydrogr.lph. Lins ley & Crawford (1960. Pa per 7)
describes the early computer·based approach that became
known as the Stanford Watershed Model. Ilendcn;on &
Wooding (1964, Paper 8) simu lated both O\erland now
and groundwater now w ith kinematic wave theory. Ragan
(1966. I'a per 9) used the method of characteristics to
simulate channel now (with lateral inflows), compa ring
the simulated results wit h measu rements fro m nume
experiments. Woolhiscr & Liggctt ( 196 7, PU ller 10 )
numerically so lvc non· d imensional fo nns of the s ha llow.
w;l\er equations for overland now, comparing the
complete solutions with kine matic wave solutions.
Freeze & lIarlan (1969. Pa per U ) provide the
blueprint o f a physicall y-based digitally simulated,
hyd rologic-response model. Freeze (1971, l'Il I)Cr 12)
reports a finite-diOcrcnce development of Richards
equat ion lor a transien t 3-D variably·saturated subsurface
now model, a major component in the Frceze & Harlan
( 1969 , IJape!" II ) bluepri nt. Smith & Woolhiser ( 1971,
I'ape r 13) report the development of'l Horton overland
now mode l based Ilpon the I· D (vert ical ) Richards
equation and the. kinematic wave simplification for I-D
non-unifonn unstead y now . Freeze (1 9 72a, I'llper 14:
1972 b. IJ:1per 15) reports the de velopmellt of the first
physics-based hydrologieal.response mode l, by coupling
a 1-0 £mdually-varied, unsteady channel now model "ith
his 3- D variably-salUr.:ncd subsurface flow model (Freeze.
1971, Paper 12 ). ful lil ling the blueprint proposed in
Freeze & Harlan ( 1969. Paper II ). In this pair of papers
Freeze investigated the role that subsurface now plays in
generating surface ru noff either as bascflow to the
channel or from upstream source areas. Engman &
Rogowski (1 974, )la per' 16) report the development of a
Horton-type partial-area model based on Philip 's
infihration equat ion and kinematic wave algorithms fo r
both overland and chan nel flows. Stephenson & Freeze
( 1974, Paper 17) report the applicat ion of Freeze's
hydrologic-response model (Freeze, 197 1. l)a per 12;
1972a, Pa per 14; 1972b, Paper 15) fo r the upper Sheep
Creek study basin located \\ ithin the Reynolds Creek
Experi mental Watershed in southwest Idaho, USA. Wood
(1976, Puper 18) investigated parameter uncertain ty with
a deterministic hydrologic-response mode l by considering
infi ltration us a stochastic vllfiab lc. Ileven ( 1977,
Paper 19) reports thc de\'elopment of a 2- D (vert ical
s lic(.') trans ien t variably-suturatcd subsurface fl ow model.
employi ng the Ga lcrkin fi nite-clement method. Smith &
Parlangc (1 978. Pilpel' 20) int roduce a t\... o-p.1.ramctcr
infiltrat ion equation thut is an analytica l so lw ion for
Richards' equation with:. rainfa ll boundary cond ition.
Be ven & Kirkby (1979. 1':ll'cr 21 ) report the
development ofn topogmphic index in the minfa ll- Illiloff
model Ih..t is known as TOPMODEL. Freeze (1980.
(':1 per 22 ) reports the results from concept-development
si mulati ons conducled with .. stochastic-conceptllal
rainfall- runofT model thill employs the Smith & Pa rlan ge
(1 978. Paper 20) inli lt rut ion equati on. Moorc 8:. Clarke
( 1981. "a per 23) use a statistical popula tion of' stores
ra ther than a si ng le store in an updated distribut ion­
fu nction approac h to mi nfal1- n mo lT modell ing. l3even
(1982, Pa per 24) uses kinematic appro:l;imat ions to
simulate subsurface storm flow fo r saturated and un­
saturated condit ions. Smi th & (-Iebbcrl (1983 , 1':II)er 25)
report on the development of a detcnninistic-conceptual
rai11I;11I runoff modcl. whose operating algorit hms arc
b..sed on analytical sol ut ions including the Smi th &
Pm·l an ge ( 1978. "({pl'r 20) in fi ltration equation. for "what
if' concept-deve lopment sim ulations. Lougue & Freeze
( 1985 Paper 26) eVilluate Illodd pcrfomlance for a S('t of
three underlying event-based rainfall- runolT model1i ng
techniques using data fro m three experimenta l catch­
ments. Abbott el al. (1986a. Paper 21) describe the
motiva tion and unique intcmational/ intcragcncy history
beh ind th\.o devc lopmcnt of the distributed. process-based
SH E model. Siv:q)alan el al. (1987, ":lper 28) employ
TOPMODEL to investigutc ckments of hydrological
similurit), for stann mnolT production. Sill ley el al.
( 1989b. Paller 29) employ II physics-bascd model to
investigule the likelhood that equivaknt homogeneous
hil1slopes can cO-ect ivcl y capture the hydrologic-response
dynamics from heterogeneous hillslopcs. Beven (1989 .
Paper 30) prO\ ides a lucid critique of physical1y-bilscd
hydrologic-response model s that ( fi tt ingly) dovetail s \\ ith
the 1989 cu t-otT dale for thi s volume.
0
2
The representation of process in papers I. 2, 4, 5, 6.
7 and 23, while well considt:rcd, is empi rica l, generally
preventi ng meaningful concept-development simuilitions
designed to understand how systems work at the
hillslopelcatchmcnt scale. Model s based on both the
rationlll method t Mu lvany, 185 1. Pa per 1) and the unit
hydrograph method (Shennan (1 932, Pa per 4; Dooge.
1959, Paper 6) are still widely used (albeit with in a
calibrated range) today (see Brutsaert, 2005). The usc of
transfer functions has in fact experienced something of a
renaissance in Ihe last decade or so (e.g. Wei ler el a/.,
2003). Arguably, Richards ( 193 1. PlI per 3) and Smit h &
Parlange (1 978, Paper 20) arc soil-physics contri bu tions:
however, both efforts were li nchpins in the development
of various hydrologic-response tnodels . The phvsically­
based models di scussed in the papcrs selected f or this
vo lume. while oncn li mited by the computer resources
that were available at the time, fllcil itated stunni ng
advances in our ubili ry to understand distributed
hydrological responses withi n hillslopelcatehment stak
systems. Computer resources an.' no longer the govcrnor
holding back heurist ic hyd ro logic-response simulation .
Today the missing link is a luck o f data with wh ich to
cfTec ti vely excite and evaluate a new generation or
phys ics-based models. If one wcre to expect a physica lly­
based, di stributed hydrol ogic-response model to work
wi thout error, then one wi ll be disappointed. However. it
is often morc prod uctive to rejcct a hypothesis, fro m a
conccpt-deve lopment perspect ive, tha n it is to accept 11
givcn hypothesis. I believe it was Albert Einstein who
stated: "No amOlll1t of eXp€I'imeIllGtio n can el'er pl'OI'e II/e
rig ht: a single experiment call pro lie me wrong" .
Streamflow generation processes
It is well known that there are three disti nct forms by
which lateral innows enter a channe l reach wi thin a
catchment (sec Dunne, 1978: Freeze, 1980, Paper 22 :
Woolhiser, 1982): (i) groundwater d ischarge, (ii) su bsurf­
ace stormflow . and (iii) overland flow. Groundwater
disdmrgc provides the sustaining baseflo w component to
a strearn hydrogruph between storm periods. The fl ashy
response of streamflow to individua l minfal1 events can
IX' ascribed to either subsurface stormnow or overland
!low. At most locat ions the pri mary sou rce ofrupid lateral
innows is overland fl ow. Overland flow can only be
generated on a hillslope alier surf<lce pond ing has
occurred. It has been recogn ized for some time that
surL1.cc snturat ion can occur by two quite distinct
mechan isms: I-lorton overland flow and Dunne overland
!low. For the Horton mechanism, the min fall intens ity
mllst exceed the saturated conductivi ty of the su rface soil
for a period of time long enough for l>ond ing to occur.
For the Dunne mechan ism. thc duration of ra infall. at an
intensi ty less than the satu rated hydrau lic conducti vity.
muSt exceed the period of' time Ilcc(.'ssary for an init iil ily
shallow saturated zone to rise 10 the surface. Obvious I)'.
Inuoductlon
Rainfall-Runoff Modelling
the implicalion ~ of scale arc cmcia l in charactcrizi ng the
lpatial and temporal variability of ncar-surfa ce soil­
hydraulic properties <lntl the related hydrological
response. Some in-depth literature exists for the problems
of scale in hydrology (e.g. Klemd, 1983: Blosch l &
Si,apalan. 1995; Doog~, 1997: Beven, 2006c: Loague &
Corwin, 2007).
There have been many out sta nding hydrologists and
hydrological investigations over the years. However. it
I,a~ the process-based focus (i.e. measurc and model) of
Roben Elmer Horton ( 1875- 1945) that substantially
innuenccd hydrology. The best look into Horton's impact
on hydrology is provided by Be\ cn (2004a,b,c.d: 2006a).
One of the best catchment-scale measure and model
(field) experiments was the eITort led by Bill Dietrich for
the Coos Bay site located in the Oregon Coast Range.
LSA. The exhaustive Coos Bay data sets include thrcc
sprinkling experiments and sevcn years of natural events.
The Coos Bay eITort is well documcntcd in the literature
(e.g. Anderson el (1/.. 1997a.b. 2002; Montgomcry et al.,
1997. 2002, 2009: Torres et oJ.. 1998: Anderson &
Dietrich. ~OOI : Montgomery & Dictrich, 2002; Ebel &
Loague, 2006. 2008: Ebcl el al.. 2oo7a,b, 2008, 2009a).
Tht: ~omments of Ki rkby (2004), related to the Coos Bay
stud). arc certainly food fo r Ihought: " As compllling
pO\\'er becomes cheaper alld field work mor e eXpel/Si Fe.
Ihere is a rrend (limy from jield work alld lowards more
comp/ere dependence 011 simlllmion. 11 is rherefore worth
inc/tiding ill Ihis series of papers all crirical COllcepts a
rt'C(!1/I example of an illlellsil'e!y inSlrumented field sile.
If/WI il slloll'.\· is (h(lf (he real world is always more
complex {lnd smprising than aliI' simll/atiolls, and liIal
Iltere {Ire .f/ill severe limitations 01/ 0/11' physical
a.lsllmplio/ls and our model/ing polell/iul. Perhaps this
remind:; liS of Free:es conclusions (1978) all hills/ope
hrdrologl'. 111m we 1I'01lld I/(!. I·er be able 10 lIIodel Ihe
romplexily ofrea/ world hills/ope hydrology. alld IIUll lhe
din!rge1/ce.~ belween model (md realilY 1I'0/lid always
rvmai/l Sllbstallfial. " (p. 16).
The cssenl ial hillslope hydrology li terature. which is
prerequisite for any budding rainfall mnon' modeller. can
Ix gleaned from Freclc (1974), Kirkby ( 1978) and Beven
Rainfall-runoff models and modelling
output variables. as well as the system parameters and
residual error, can be either stochastic or deterministic. A
model is stochastic if any of the variables are described
by n probability distribution, or deterministic if all Ihe
variables arc (viewed ns) free from random variations.
Models arc conceptual if their fun ctional fonn is derived
from considenllion of phys ical prc)(:csses. and empirical if
nol. Clarke (1973) categorizes mnthemalical models as
stochastic-conceptual. stochastic-empirical. deterministic­
conceptual. or determin istic-empirical.
In the last half-century there have been hundreds (if
not thousands) of hydrologic-response models. each with
their own attributes and shortcomings. deve loped by
researchers, students, and consultants. coveri ng the enli re
spectmm of Clarke's classification (1973). Beven (2000a)
wrote ,," is nolV r;I'!/fally impossible fol' lilly one person
{a be aware of aI/ 'he models Ihal are reponed ill fhe
literalllre. lei a/one know sOlllefhil1g of the IIis forical
framewOI'k of Ihe djfferellf iniliatives:' (p.ix-x). It is
important to recognize that not all o f these models were
created equally. The relat ively si mple empirical models,
whose system parameters cannot (usua lly) be measured in
the field. perfonn successfully only within a calibra ted
range. Many conceptual models have been developed
around a single process (c.g. the l'lorton mechnnism).
Table I provides an abbreviated summary of the evolution
of detenninistie-conceptunl hydro logic-response models.
Early on , researchers assumed that physica lly-based
distrihuled models. testcd with cxh:lUst ive plot-scale data
sets. could be employed (Il lbei l \\ ith much more
infonnat ion needed) to simulate hydro logic II response at
IlI rger scales. This assumption I\ as grounded in the fac t
that plots make up hillslopes . hillslopes make up
calchments, and catchments make up watcrsheds. The
fact is, howcver. that in regard to fully-coupled
surface/near-surface hydrologic-response simulation, no
existing catchment-scale data set has allowed (with high
levels of confidence in both space and time) for a
complele characlerization of Ihe boundary-value problcm
or a rigorous evaluation of model performance . The
advant.;lges. lim itations, and nuances o f rainfllll- runoIT
modelling are well described by Eagleson (1 969).
Woolhiser (1973, 1996), Beven (1985, 1989, 1993 .
2000a.b. 2oo2a.b). Abbon ( 1992), Singh & Woolhiser
(2002). Loague & VanderKw;w k (2004). Loague e r a/.
(2006) and Kampf & Burges (2007) .
C'larke (1973) general i'les n mmhemll tica! rai nfall- runoff
model by:
Cain and Abel
(2006a).
q, = f(p,
I'
P, .~ , .. ·:q,
I'
il, 2· .. ·: a l · a c.... )+.;,
Il hel\" PI arc the input variables, q, are the oUlplil
lariablcs. and a~ are the systcm parameters, ';, is the
residual error. and f is the functio nal f0n11 of the modt,1.
Lneoded in this relalionsh ip is a fund amenta l distincliOIl
between model elements (i.e. \a riablcs eh'lIlgc wit h time,
parameters remain constaTlt). The functi ona l form of the
relalionship can be conceptll:ll or empirical: Ihe input and
Why model? The answer (to many) is relatively simple;
process-based simu lmion is necessary as: (i) there is no
way to measure cveryth ing wilhout digging everything up
(which in and o f itself is problematic): and (ii) most oOen
waiting to see what wi ll IliIppell (verSlis estimating what
might happen) is not good enough, especially in the fast
paced decision-management arenu. Table 2 sho\\ s exam­
ples of coupled surface w;lIcr/groundwaler simulation
lnuoduction
3
Introdu ction Table I Characteristics of selected hyd rologic-response models (after Loague ef (11., 2005). Primary reference
Subsurface
Freeze(1971. I':lper 12, 1972a. Paper 14, 1972b.l)ape r I S)
Smith & Woolhiser(1971, Pa per 13)
Beven (1977. Pa per 19)
Akan & Yen (198Ia,b)
AbboU etal. (1986a. l)aper27 : 1986b)
Beven el al. (1987)
Sinley el al. (19893, 1989b. Paper 29)
Govindaraju & Kavvas (1991 )
Yeh elal. (1998)
VanderKwaak (1999)
Morita & Yen (2000. 2002)
Paniconi el aJ. (2003)
Panday & Huyakom (2004)
Therrien el 01. (2005)
Qu & OutTy (2007)
Kollel & Max well (2008) He et al. (2008) 30. UlS. R
ID. U.R
20. UlS . R
2 0. U/S . R
10 . U. R: 20, S, G
2D. UlS. R
30. U/S. R
Surface
O verland
Channel
11).0
S
10 . 0
2 0, D
10 , K
I D.K
ID.D
10. 0
10 . 0
W.K
10. E
IO.E
S
S
S
S
S
S
S
S
F
10. K
"'
20 . UlS. R
10. 0
10.0
31). U/S. R
20, 1)
20 , 1)
10.0
3D. U/S, R
3D. UlS, R
3D, UIS. R
3 ~. U/S. R
3D. UIS. R
20, U/S. A
30. U/S. R
30. U/S. R
Coupling
20. 1
10. 0
20,0
20, D
20 . D
20. K
20 . 0
20. 1)
20. 1
10,0
S
S
F
F
F
F
10,0
20.0
20. 0
20. K
20. ])
F
NOh:. the method of 501IIIion is nUlllcricalllnlcss otherwise idclllir.ed. I D. 2D. 3D (dimensions); U (unsallIfaled); S (salllralcd); UIS (unsatunuedlsmuTUled); A (analytical SOIUlioll): E (empirical solutioll): R (Richards equmion); G (g.round\\!lICr equlltion); D (diffusion W8\ e): I (non-inertia W3\e); K (kinematic 11'11\ e): S (sequential); F (first-ordcr).
Table 2 Selected coup led surface watcr/groundwa ter simulation efforts \\ ithin the last decade (after Ebc l el al.• 2009b).
Focus
References
Agricultural sustainability
Atmosphere-subsurface waler and energy nuxes
Cumulative watershed elTcets
Dam removal
Ground\\ aler recharge
Groundwiltcr- Iake intcmction
Island-scale erosion
New- old water
Pore· water pressure development and slope instability
Schoups el al. (2005)
Maw.. ell el al. (2007)
Carr (2006) I-Ieppner & Loaguc (2008) Lemieux el (II. (2008). Smerdon el (If. (2008) Smcrdon el (II. (2007) Ran et al. (2009) VandcrKwaak (1999), Jones el (II. (2006) Ebcl el 01. (2007b, 2008. 2009a), Mirtls el aJ. (2007). BeVille -
el 0/. (2009) McLaren et (II. (2000). Sixio el al. (2002) Radionue I ide comam i nat ionl\'u Inerabi Iity
RunofT generation
VanderKwaak & Loague (2001). Morita & Yen (2002), Loague el 01. (2005). Kolle! & Ma:\well (2006). Heppner el al. (2007). Ebel et al. (2007b. 2008. 2009a). Jones el (II. (2008). Li el 01. (2008). Mirus et al. (2009) Heppner (!I al. (2006. 2007). Ran er al. (2007)
VanderKwaak (\999), Ebcl el 01. (2007b). Sud icky el (II. (2008) Weng el af. (2003). Gunduz & Aral (2005). Peymrd el al. (2008) Langevin el al. (2005 ) Se diment transport
Solute transpon
Stream- aquifer exchange
Wetland-estuaryexchange
eITon s w ithin the last decade. illustrati ng the importa nce
of process~ba sed simulation.
Of course not evcryone is enamoured with computers.
nor belie\ es that simulation is good for hydrology. Ph ilip
(1992). in discussing hydro logy and the real world, wrotc:
"Olthe making oJmodels Ihere is 110 end The ("ompollelll
paris Ina)' be well-foullded ill lIalll m/ sciellce. iliaI' be
cnu/e simp/{ficatioll. or may be I/O more Iha1/ (J black box
\fMcil has ,akell ' lie modeller's jallcy. Equ{//~I '. Ihe
prescripliolls jor jitTing the (:OIl1jJrmellls logelher IJUI}' or
4
may 1101 be weI/-based Beyond Ihe question oj Ihe
l'oJidiZ)' oj l ite mode/:~ //Iachinery. there are also difficull
questiolls oj lite qtlalily hOlh of Ihe parameteri=alioll oj
l ite compOl1elllS of the model (llld o/the dala inpllts. A
dislllrhing del'elopmellf iJ Ihat complller modelling 11m
largely supplanted labo/'{l folY experimel1lalioll alld field
obsen'aliOI/ (IS Ihe resean ll (lelil'il)" oj bOlh lil/der­
graduoles and graduate studellls .... II i.~ sad fO see Ihe
young going d01\'1/ Ihis track. They canllOI be blamed. Fo,­
Ihem to develop ollrenl'ise delllai/(/.<; a menial and moral
introduction
Rainfall- Runoff Modelli ng
IfIIe[.!rily we call1lot expect il1 YO llng per.l·ons gil'en open
~/al"er 10 play around lI'ilh glamlJrOIlS space-age IOYS. ·'
IP·.205 ).
And. Klcmcs (1997) commented "For hydrology (/$
a science. 'he jlll'(ISiOI1 of /1/alnemlllic(l1 modelling \\'(/$
I/()/Iling short of a disas ler. It has re/arded ralher Ihal1
v.dmIlC(!ll the dewJopmell1 of hydmlogy becllltse, with
I"i:ry /1'11' exceptions. it focI/sed all efforls on polishing Ihe
lIIatll('I1Wlicallll1d comp"t(llional aspecfs of methOds (jlld
tech"iques. leaving the lIIuJerslalldillg of Ihe substance l1l
rhe 193()s lerel. where it had bcclI brought by Ille oid
gllurd of professionals like lIa::ell, Shermall, I/OrtOll.
Theis. 10 Illlme lIfell'." (pA3).
In Ihe face of lhcsc commenlS by Phi lip and Klemd.
Ihere is not a beller example (p~ SI or presenl) o f a Horton
I)pe measure and mode l exercise Ihan Ihe eOort by Ebel
1'1 al. (.2007a.b). From a concept-development perspcc­
ti\~. the greatest utility or physically-based distributed
~imulation is identirying (and refining) the next grea t
field cxpcrim!.'ntlmeasurement. Obviously, relative to
ton~ t ructi\e concept-development simulation, it is better
10 be \\rong for the right reason thun right ror the wrong
camp. It is important to distinguish between appropriate
and inappropriate mode l applications. Sacrificing the
hydrology (e .g. reduc ing the dimension, ignoring the
unsaturated zone, a nd/or assuming a steady-state
response) to raci litate an application can ( in the cxtreme)
prod uce nonsensical results.
Ir there IS another bcnchmark volume on rainfall­
runorr modelling in the ruture . I full y expcct tha t Ihe
papers will rocus in large pan on uncertai nty. The next
paper that t would have ~ddcd to thi s volume (a lbeit
stretching the cul-oO' dale) is l3even & Bill ley ( 1992).
which int roduced the G LUE (Genemli.lcd Li kelihood
Uncerta inty Estimation) mcthodology to quantify thc
uncertainty of model predictions. The GLUE hypothesis
is tha t there are several rcaliLations that equa lly-well
represent
an
observed
hydrological
response.
Equifi nality, in the context of dctenn inistic-conceptual
simulation. refers to more than olle parameter set
providing all cqually good re presentation of overall
hydrologica l response (see Beven. 2006b). Ebcl &
Loague (2006) discuss cquifinali ty rrom the pers pectivc
or integrated \'erSIiS distributed responses.
reason.
Dunne (1983) called for a closer cooperation
bct\\l'Cll scienlisb work ing on fi eld studies and those
interested in modclling. Heed ing that call. between the
('ain ~ and Abels of hydrology. it is c ritica l that proccss­
hascd models be teSled rigorollsly (see Seibert &
McDonncl1. .2002; Fenicia el (I/., 2008). The vnrious calls
ror detailed long-duration field moni toring programmes at
selected experimental catchments (e.g. Dunne. 1983 ,
1998: Entekhabi el lIl.. 1999), in the spi rit o f the
lnt!.'mational Il ydrological Decade. must be answered.
For example. MlrlilC!.' soil -water cont ent data, whether
acquired \ ia ad\ anced technology or by the squish lest,
are needed to criticall y e valua te the rcsponse of eve n [he
simplest hydrologica l sys.tem. It is also important to
l\."'Cogni/(· und ack no\1 ledge thaI there are sti ll no
C5labtished model perronnance standards ror dirrerent
:lpplications (sec Seibert. 2001 : Wagener. 2003: Vache el
al., .2004. 2006: Criss & WmSlon, 2008).
Back to the future
lI}drologic-responst: simu lation is a wel l established tool
lor ~urrac \.." \I ater/groundwater conl3mination. geotech­
nical engineering. and cli mate change problems.
U)Jrolog.ic-re~pon sc simu lat ion w ill (perhaps) be even
more u!>erul for applications in the emerging di ~ci p 1i ncs
of h)'droecology (Newman el lIl. . 2006), hydrogco­
morphology ( Paola ell/I.• 2006). and hydro pedology (Lin
clal.. .2(06). [t is important to remember. however. th:lt
h>drology is not just a plug-u nd-play resource ror these
other disciplines. In gcnera l. the re are two dirrerent kinds
or rolks in the modelling game, modellers ~nd model
USI.'fS. The papers selccted for th is volume (al beit
illustrating many appliclltions) lire from the modellers'
Acknowledgements
My appreciation ror the e vol ut ion or ideas in hydrology
(and soil physics) has benefitted rrom time spent w ith A I
Freeze, Ste....e Burges. Dick G reen. Gary Sposito. 13 i11
Dietrich and Irwi n Rc mson. I am graterul to Joel
VanderK waak. Adrianne Carr, Chris I·h:ppner. Qihua
Ran, Brian Ebel a nd Ben M i ru ~ (aka "T he Fellowship or
the Infi ltrat ion Rings") ror rescu ing me rrom the regional­
scale non-point sou rce groundwater vu lnerability
behe moth . T he cncouragement and support or Kei th
Beven, Jerr McDon nell, Steve LeDuc , and Cate Ga rdne r
on th is project arc great ly appreciated .
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Introduction