Groundwater level response in US principal aquifers to ENSO, NAO, PDO, and AMO

14 Pages·2014·3.61 MB·English

JournalofHydrology519(2014)1939–1952
ContentslistsavailableatScienceDirect
Journal of Hydrology
journal homepage: www.elsevier.com/locate/jhydrol
Groundwater level response in U.S. principal aquifers to ENSO, NAO,
PDO, and AMO
Amber Jean M. Kussa, Jason J. Gurdakb,⇑
aUniversityofCalifornia,SantaCruz,DepartmentofEnvironmentalStudies,1156HighStreet,SantaCruz,CA95064,USA
bSanFranciscoStateUniversity,DepartmentofEarth&ClimateSciences,1600HollowayAve,SanFrancisco,CA94132,USA
a r t i c l e i n f o s u m m a r y
Articlehistory: Groundwaterwillplayanimportantroleinsociety’sadaptationtoclimatevariabilityandchange.There-
Received1March2014 fore, it is particularly important to understand teleconnections in groundwater with interannual to
Receivedinrevisedform26July2014 multidecadalclimatevariabilitybecauseofthetangibleandnear-termimplicationsforwater-resource
Accepted25September2014
management. Here we use singular spectrum analysis (SSA), wavelet coherence analysis, and lag
Availableonline5October2014
correlation to quantify the effects of the El Niño Southern Oscillation (ENSO) (2–7year cycle), North
ThismanuscriptwashandledbyPeterK.
Atlantic Oscillation (NAO) (3–6year cycle), Pacific Decadal Oscillation (PDO) (15–25year cycle), and
Kitanidis,Editor-in-Chief,withthe
assistanceofRoseannaM.Neupauer, Atlantic Multidecadal Oscillation (AMO) (50–70year cycle) on precipitation and groundwater levels
AssociateEditor acrosstheregionallyextensiveCentralValley,BasinandRange,andNorthAtlanticCoastalPlainprincipal
aquifers(PAs)oftheUnitedStates(U.S.).Resultsarecomparedtorecentfindingsfromasimilarclimate
Keywords: variabilitystudyoftheHighPlainsaquifertoprovidethefirstnational-scaleassessmentoftheeffectsof
Groundwater interannualtomultidecadalclimatevariabilityongroundwaterresourcesinU.S.PAs.Theresultsindicate
Climatevariability thatgroundwaterlevelsarepartiallycontrolledbyinterannualtomultidecadalclimatevariabilityand
ENSO arenotsolelyafunctionoftemporalpatternsinpumping.ENSOandPDOhaveagreatercontrolthan
NAO NAOandAMOonvariabilityingroundwaterlevelsacrosstheU.S.,particularlyinthewesternandcentral
PDO PAs. Findings and methods presented here expand the knowledge and usable toolbox of innovative
AMO
approaches that can be used by managers and scientists to improve groundwater resource planning
andoperationsunderfutureclimateuncertainty.
(cid:2)2014ElsevierB.V.Allrightsreserved.
1.Introduction levels and recharge are partially controlled by complex interac-
tions of low frequency (interannual to multidecadal) climate
Interannual to multidecadal climate variability partially variability (Dickinson et al., 2004; Hanson et al., 2004; Pool,
controlsprecipitationdistributioninspaceandtime,droughtfre- 2005; Fleming and Quilty, 2006; Gurdak et al., 2007; Anderson
quency and severity, snowmelt runoff, streamflow, and other andEmanuel,2008;Holmanetal.,2009,2011;Clarketal.,2011;
hydrologic processes that profoundly affect surface-water Figura et al., 2011; Perez-Valdivia and Sauchyn, 2011; Tremblay
resources (Ropelewski and Halpert, 1986; Cayan and Webb, et al., 2011; Venencio and Garcia, 2011; Perez-Valdivia et al.,
1992;DettingerandCayan,1994;Enfieldetal.,2001;Ghil,2002; 2012). Improved understanding of the long-term fluctuations in
Dettinger et al., 2000, 2002; McCabe et al., 2004; Labat, 2008, groundwater availability that is dominated by low frequency cli-
2010; Vicente-Serrano et al., 2011; Ionita et al., 2012). However, mate variability is essential for best informed management and
the effects of interannual to multidecadal climate variability on policydecisions,particularlywithin thecontextofthe increasing
recharge rates and mechanisms and other subsurface hydrologic use of groundwater for human consumption and irrigation
processesthataffectgroundwaterquantityandqualityarelargely (Wada et al., 2010) and the uncertainty of climate change and
unknowninmostaquifersoftheUnitedStates(U.S.)(Gurdaketal., related impacts on groundwater quantity and quality (Hanson
2009) and other regions of the world (Green et al., 2011; Treidel et al., 2006; Holman, 2006; Earman and Dettinger, 2011; Stoll
et al., 2012). High-frequency (synoptic to seasonal) climate vari- etal.,2011;Gurdaketal.,2012).
ability creates short-term hydrologic responses, but groundwater Thecomplexnatureofclimatevariabilityonalltemporalscales,
including interannual to multidecadal is a major obstacle in the
⇑ reliableidentificationofglobalchangecausedbyhumanactivities
Correspondingauthor.Tel.:[phone].
(Ghil, 2002). Recent discussions about adopting nonstationary
E-mailaddresses:[email protected](A.J.M.Kuss),[email protected](J.J.Gurdak).
http://dx.doi.org/10.1016/j.jhydrol.2014.09.069
0022-1694/(cid:2)2014ElsevierB.V.Allrightsreserved.
1940 A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952
models for water-resource risk assessment and planning is climate variability on groundwater resources in U.S. PAs, and
motivated by climate change and natural low-frequency climate advances current understanding needed for effective
variability(Millyetal.,2008).Thefourleadingatmospheric–ocean water-resourcemanagementandpolicydecisionsunderincreasing
circulationsystemsthataffectNorthAmericaninterannualtomul- climateuncertainty.
tidecadal climate variability are the El Niño Southern Oscillation
(ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscilla-
2.Background
tion (PDO), and Atlantic Multidecadal Oscillation (AMO) (Ghil,
2002;McCabeetal.,2004).Thetimingandphaserelationofthese
2.1.Climatevariability
quasiperiodicclimatecycleshaveteleconnectionswithhydrologic
variability across much of the U.S. (McCabe et al., 2004; Hanson
Climate variability is characterized in terms of anomalies,
andDettinger,2005;Gurdak,2008).
which are defined as the difference between the current climate
In this paper we quantify the teleconnections between ENSO,
conditionsandthemeanstate,whichisrepresentativeof‘‘normal’’
NAO, PDO, and AMO and the groundwater resources of principal
conditions that are computed over many years (Hurrell et al.,
aquifers (PAs) along a west–east transect of the U.S. based on
2003).Naturalclimatevariabilityoccursonmanydifferentspatio-
observed anomalies in the Pacific and Atlantic Oceans. PAs are
temporalscalesandiscreatedduetointerplaybetweenmultiple
regionallyextensiveaquifersand aquifersystemsofnationalsig-
variables including (but not limited to) sea-level pressure (SLP)
nificancebecauseoftheirhighproductivityoruseandarecritically
anomalies,pressureheightvariations,fluctuationsinwindspeeds,
important sources of potable water (USGS, 2003). The primary
variationsintheEarth’sorbit,andvolcaniceruptions(Ghil,2002).
objectivesofthispaperaretocharacterizenonstationarypatterns
Climateindicesaregenerallycreatedusingavarietyofanomalies
inclimatevariabilityandlagcorrelationstospatiotemporaltrends
atdifferentlocations,suchaschangesinthemeandistributionof
inlong-termrecordsofprecipitation(55–89years)andgroundwa-
SLPattwolocations,thedeviationfrommeansea-surfacetemper-
ter levels (41–93years) (Table 1) of the Central Valley aquifer
atures (SSTs) at multiple locations, variations in oceanic wind
(52,000km2),BasinandRangeaquifersystem(700,000km2),and
strength, or a combination of multiple variables (Ghil, 2002;
North Atlantic Coastal Plain aquifer system (130,000km2)
Hurrelletal.,2003).
(Fig. 1). Some results from these aquifers are compared to major
findingsfromarecentandsimilarclimatevariabilitystudyofthe
High Plains aquifer (450,000km2) (Gurdak et al., 2007) that is 2.1.1.ElNiñoSouthernOscillation(ENSO)
locatedinthecentralU.S.(Fig.1).Thispaperisthefirsttoprovide TheENSOisa2–7yearquasiperiodicphenomenonthatresults
national-scaletrendsontheeffectsofinterannualtomultidecadal fromlarge-scaleinteractionsbetweenthetropicalandsubtropical
portionsofthePacificandtheIndianOceanbasins,whichresultsin
variations in pressure, temperature, and precipitation patterns
Table1 throughout the U.S. and other regions of the world (Ropelewski
Hydrologictime-seriessiteinformation.
and Halpert, 1986; Diaz and Markgraf, 1992; Hanson et al.,
StudyID AgencysiteID Periodofrecord Years N 2006). We use the Multivariate ENSO Index (MEI) (Wolter and
CVP1 47292 1951–2009 58 696 Timlin,2011)tomeasurethetemporalextentandthephasedesig-
CVGW1 401059122102801 1937–2004 67 128 nationofENSO(Fig.2a).Thepositive(negative)MEIisrelatedto
CVP2 45385 1920–2009 89 1068 thepositive(negative)ENSOphase.TheMEIisbasedonmultiple
CVGW2 391028121312501 1947–2003 56 114 variables of the Comprehensive Ocean-Atmospheric Data Set
CVP3 49200 1926–2009 83 996 (COADS), and represents a weighted average of SLP, zonal and
CVGW3 382458121455801 1951–2004 53 104 meridional winds, SST, air temperature, and total cloudiness
CVP4 45032 1927–2009 82 984 (WolterandTimlin,2011).
CVGW4 380238121091301 1962–2004 42 354 DuringthepositiveENSO(ElNiño)phase,theequatorialPacific
CVP5 41244 1940–2009 69 828 experiences abnormally low SLP in the east and increased SLP in
CVGW5 352228119295201 1937–2004 93 128 the west, allowing for the warm waters of the western Pacific to
BRP1 266779 1950–2009 59 708 migrate eastward, thus creating a shift in the jet stream
BRGW1 393737119514801 1966–2007 41 138 (Ropelewski and Halpert, 1986). A U.S. coast-to-coast continuity
BRP2 264950 1931–2009 78 936 of increased precipitation (especially in the winter months of
BRGW2 393310114475001 1948–2006 58 438 December–February) from North Carolina to California has been
BRP3 426135 1941–2009 68 816 observed during the positive ENSO phase, with stronger correla-
BRGW3 393143111523301 1935–2007 72 1951 tions in the southwest and central U.S. (Ropelewski and Halpert,
BRP4 262243 1950–2009 59 708 1986;KiladisandDiaz,1989;KurtzmanandScanlon,2007).Dur-
BRGW4 361843115161001 1943–2007 64 1847 ing a negative (La Niña) phase, SLPs increase and SSTs decrease
BRP5 264436 1951–2009 58 696 in the eastern equatorial Pacific, creating opposing temperature
BRGW5 360528115094201 1965–2007 42 1923 and precipitation patterns across the U.S (Ropelewski and
NAP1 307633 1938–2009 71 852 Halpert, 1986; Kiladis and Diaz, 1989; Diaz and Markgraf, 1992).
NAGW1 405308072553101 1945–2006 61 2119 Additionally, winter precipitation is generally above-normal in
NAP2 307134 1931–2009 78 936 the Pacific Northwest and below-normal in the Southwestern
NAGW2 405743072425701 1954–2007 53 544 U.S.duringthenegativeENSOphase,whiletheoppositeconditions
NAP3 283181 1948–2009 61 732 aregenerallyobservedduringthepositiveENSOphase(Kiladisand
NAGW3 402553074271701 1944–2005 61 649 Diaz,1989).Thisdipolesignatureinthewinterprecipitationofthe
NAP4 72730 1948–2009 61 732 western U.S. is influenced by the phasing of the Pacific Decadal
NAGW4 391949075410701 1957–2004 47 564 Oscillation(PDO)(BrownandComrie,2004).
NAP5 188000 1954–2009 55 660
NAGW5 382329075263701 1967–2010 43 683
2.1.2.TheNorthAtlanticOscillation(NAO)
CV, Central Valley; BR, Basin and Range; NA, North Atlantic Coastal Plain; P, The NAO is a north–south dipole of pressure anomalies, with
precipitationsite;GW,groundwaterlevelsite;N,numberofdatapoints. one anomaly centered over Greenland and the other anomaly
A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952 1941
Fig.1. MapshowingthelocationoftheCentralValley,BasinandRange,andNorthAtlanticCoastalPlainaquifersystems; andthefiveco-locatedprecipitationand
groundwaterlevelsitesineachaquifer(Table1).FindingsfromarecentclimatevariabilitystudyoftheHighPlainsaquifer(Gurdaketal.,2007)isusedheretocompletethe
east–westgradientofPrincipalAquifers(PAs)acrosstheUnitedStates.ThefindingsandsiteinformationfortheHighPlainssites1–6isdetailedbyGurdaketal.(2007).
Fig.2. (a)ThemonthlyMultivariateElNiñoSouthernOscillation(ENSO)index(WolterandTimlin,2011),(b)Hurrellstation-basedannualNorthAtlanticOscillation(NAO)
index(Hurrell,1995),(c)monthlyPacificDecadalOscillation(PDO)index(Mantuaetal.,1997),andthe(d)KaplanSST,unsmoothedAtlanticMultidecadalOscillation(AMO)
index(Enfieldetal.,2001).
spanningthecentrallatitudesoftheAtlanticbetween35(cid:3)and40(cid:3) 2.1.3.ThePacificDecadalOscillation(PDO)
N (Hurrell, 1995). The positive phase NAO is characterized by Decadal to interdecadal variability in atmospheric circulation,
below normal geopotential heights and pressures in the North specificallythewintertimeAleutianLowpressuresystemandSSTs
Atlantic and above normal heights and pressures over eastern from 20(cid:3) N poleward, is often associated with the PDO (Mantua
U.S.andwesternEurope,andviceversaduringthenegativephase et al., 1997). The PDO is indexed with monthly northern Pacific
NAO (Hurrell, 1995). The NAO index (Fig. 2b) is the difference SST residuals (the difference from the observed anomalies and
betweennormalizedmeanwinter(December–March)SLPanoma- themonthlymeanglobalaverageSSTanomaly)(Fig.2c)(Mantua
liesbetweenLisbon,PortugalandStykkisholmur,Iceland(Hurrell, andHare,2002).FluctuationsinthePDOindexoverthe20thcen-
1995). The NAO has a dominant quasiperiodic oscillation of turyweremostenergeticintwogeneralperiodicities–onefrom
3–6years with a less significant 8–10year mode (Hurrell et al., 15 to 25years and the other from 50 to 70years (Mantua and
2003). During the positive NAO, enhanced westerly flow across Hare,2002).Inthispaper,weevaluateonlythe15-to25-yearperi-
the Atlantic moves warm moist air over Europe and the eastern odicityofthePDO.
U.S., creating an increase in winter storms (Hurrell, 1995; The climate anomalies connected to the PDO are somewhat
Ottersen et al., 2001; Hurrell et al., 2003). While the majority of similar to the ENSO with comparable shifts in the jet stream
thepositiveprecipitationsignalsareseeninEurope,weakerposi- (MantuaandHare,2002).ThepositivephasesofthePDOareasso-
tive correlations are observed in the eastern U.S. (Hurrell et al., ciated with warm dry periods in the Pacific Northwest and cool
2003). wet periods in the southwestern U.S. (Mantua and Hare, 2002).
1942 A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952
RegimeshiftsinthePDOalsoaffectthephaseandtheoccurrence uppermost aquifer in the North Atlantic Coastal Plain aquifer
oftheENSO(BrownandComrie,2004;Gutzleretal.,2002).During system (Trapp, 1992). Average annual temperature is 11(cid:3)(cid:3)C and
thenegative(positive)PDO,thereisagreateroccurrenceofnega- average annual precipitation is 1044mm (Polsky et al., 2000).
tive(positive)ENSOevents(Gutzleretal.,2002). The North Atlantic Coastal Plain aquifer system is ranked 13th
among the PAs in terms of total withdrawals (Maupin and
2.1.4.TheAtlanticMultidecadalOscillation(AMO) Barber,2005).
TheAMOisanatmospheric–oceanphenomenonwithaperiod-
icityof50–70yearsthatarisesfromvariationsinSSTsintheAtlan-
3.Methods
tic Ocean associated with variations in the strength of the
thermohaline circulation (Kerr, 2000; Enfield et al., 2001). The
The time series evaluated here include the previously men-
AMO is indexed with a ten-year running mean of Atlantic SSTs
tioned MEI, NAO, PDO, and AMO indices, groundwater levels
from0to70(cid:3)N,withapeakvariationof0.4(cid:3)Cdeterminingaphase
(1933–2009)frommonitoringwellsintheU.S.GeologicalSurvey
shift (Fig. 2d) (Enfield et al., 2001). The AMO is associated with
(USGS)NationalWaterInformationSystem(NWIS)(USGS,2012),
variations in air temperature and precipitation regimes across
and precipitation data (1920–2009) from NOAA (2012) meteoro-
the U.S., with a positive (negative) phase producing decreased
logicalstations(Table1).Atotalof5monitoringwellsineachPA
(increased)rainfall(Enfieldetal.,2001;McCabeetal.,2004).The
were selected based on the length and completeness of the
AMO may also modulate the strength and occurrence of NAO
water-levelrecordsandtorepresentarangeofhydrogeologiccon-
(PeingsandMagnusdottir,2014)andENSOcycles,creatingaweak-
ditionsintheuppermostandunconfinedaquiferunits.Inorderto
ened (strengthened) El Niño during the positive (negative) AMO
assessinterannualtointerdecadalclimatevariability,weselected
phase (McCabe et al., 2004). Coupled influences of the PDO and
wells that had at least 40years of water-level records (Table 1).
theAMOmayalsoproduceextensivespatialandtemporalfluctu-
Although our site selection criteria required at least annual
ations,withcoincidentpositiveAMOandnegativePDOincreasing
water-level values with no multi-year gaps in the records, the
theoccurrenceofdroughtsintheU.S.(McCabeetal.,2004).
majority of the wells have at least quarterly water-level data
(Table 1). One long-term (>40years) meteorological station was
2.2.Sitedescription
required to be co-located within 24km of each monitoring well.
The 5 co-located meteorological stations and monitoring wells
TheCentralValley,BasinandRange,andNorthAtlanticCoastal
wereselectedtocharacterizethegeneralspatialpatternsineach
Plainaquifersystemsarelocatedalongawest–easttransectofthe
PA and not meant to be an exhaustive representation of the
contiguousU.S.(Fig.1).Theaquifersaregenerallyunconfinedand
heterogeneityineachPA.Theco-locatedwellsandmeteorological
consistofunconsolidatedsand,gravel,andsilt,andrepresentsome
stationsareidentifiedbytheaquifername(CV,CentralValley;BR,
ofthemostimportantgroundwaterresourcesintheU.S.foragri-
Basin and Range; and NA, North Atlantic Coastal Plain), location
culture, industry, and domestic uses (Maupin and Barber, 2005).
(labeled1–5fromnorthtosouth)(Fig.1),andsitetype(P,precip-
McMahon et al. (2006, 2007) and Gurdak et al. (2007) provide a
itation; and GW, groundwater) (Table 1). Because long-term
detaileddescriptionoftheHighPlainsaquifer(Fig.1).
groundwater pumping records are not publically available, we
TheCentralValleyaquiferlocatedinCalifornia(Fig.1)isasin-
use a simulated groundwater-pumping time series (1962–2003)
gle,heterogeneousaquifersystemthatisgenerallyunconfinedin
from the Central Valley aquifer that was developed by Faunt
the upper hundred meters and confined at depth by overlapping
etal.(2009)toquantifytheeffectsofinterannualtomultidecadal
discontinuous clay beds, primarily in the southern portion
climate variability on groundwater pumping. Simulated ground-
(PlanertandWilliams,1995;Fauntetal.,2009).ClimateisMedi-
water-pumping time series are not publically available for the
terranean and Steppe, with hot summers and mild winters
otherPAsinthisstudy.
(Bertoldietal.,1991).Approximately85%oftheannualprecipita-
tion occurs from November to April, with a steady decrease in
overallprecipitationfromthenorth(average584mm)tothesouth 3.1.Pre-processing
(average152mm)(Bertoldietal.,1991).Pumpingtosupportirri-
gation has affected groundwater levels, with major declines in Time series analysis has been used to assess long-term varia-
muchoftheaquifer(MaupinandBarber,2005). tions in hydrologic variables (Enfield et al., 2001; Hanson et al.,
The Basin and Range aquifer system, located primarily in Ari- 2004,2006;McCabeetal.,2004;Gurdaketal.,2007).Usingdata
zona, California, Nevada, New Mexico, and Utah, includes about pre-processingmethodsoutlinedbyHansonetal.(2004),weinter-
120alluvium-filledbasinsinterspersedbetweenmountainranges polated each time series with a monthly spline to integrate any
(Fig. 1) (Planert and Williams, 1995). The basins are generally irregular sampled records, and then converted these data into
unconsolidatedtomoderatelyconsolidated, welltopoorlysorted cumulative departures seriesfrom the period of recordusing the
bedsofgravel,sand,silt,andclaydepositedonalluvialfans,flood monthly mean. Next, the residuals of the monthly cumulative
plains,andPleistocenelakes(PlanertandWilliams,1995).Thecli- departureseries wereobtained by subtracting a regression-fitted
mate is arid, with average annual precipitation ranging from low-order(cubic)polynomial.Theoverallshapeofthelow-order
approximately 102 to 203mm in the basins and 406–508mm in polynomial represents temporal trends (or responses) in the
the mountain ranges (Sheppard et al., 2002). Hot summers and hydrologic time series to larger climatic cycles or periods of
largeevapotranspirationrates,particularlyinloweraltitudes,limit anthropogenic effects (Hanson et al., 2004). Finally, the residuals
rechargetoanestimated5%ofprecipitation(PlanertandWilliams, arenormalizedbythehistoricmeantofacilitatestatisticalcompar-
1995).TheBasinandRangeaquifersystemisranked4thamongthe isonsbetweenvariousdatatypesandarereferredtoasnormalized
PAsintermsoftotalwithdrawals,andapproximately81%ofwith- departures (unitless). The primary goal of the data-processing
drawalssupportirrigatedagriculture(MaupinandBarber,2005). stepsistoremoverednoisepriortousingsingularspectrumanal-
The North Atlantic Coastal Plain aquifer system, located in ysis (SSA) to identify temporal structure in the time series that
Delaware, Maryland, New Jersey, New York, North Carolina, and have a statistically significant difference from red noise. The
Virginiaconsistsofsixregionalunconfinedandconfinedaquifers data-processing steps also remove much of the long-term,
(TrappandHorn,1997).Thisstudyfocusedonwellsinthesurficial multidecadalanthropogenicsignalsinthegroundwater-leveltime
aquiferthatconsistsofunconsolidatedsandandgravelandisthe series,suchaslong-termland-usechangeandtheimplementation
A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952 1943
ofimprovedirrigationtechnology,andannualanthropogenicsig- variations in both amplitude and frequencythat can be analyzed
nals, such as crop rotation and other irrigated-agricultural prac- using wavelet transforms (Torrence and Compo, 1998; Grinsted
tices (Hanson et al., 2004; Gurdak et al., 2007). Following the et al., 2004; Labat et al., 2000; Labat, 2005, 2008; Holman et al.,
pre-processingsteps,thetimeserieswereprocessedusingSSAto 2011).Theuseofwaveletcoherencecanprovideimportantinsight
extracttemporalstructuresfromthenoisydataandusingwavelet inhowthestrengthofgroundwaterteleconnectionsvariesthrough
analysis to characterize periodicity as a function of time, as time (Holman et al., 2011). We applied wavelet analyses on the
describedindetailnext. compositeRCsfromtheclimateindices,precipitation,andground-
water level time series using a MATLAB script developed by
3.2.Singularspectrumanalysis(SSA) Grinstedetal.(2004)andoutlinedinHolmanetal.(2011).Tocal-
culatecoherencebetweentwoseries,thewaveletpowerspectrum
UsingthemethodsoutlinedbyHansonetal.(2004)andGurdak ofeachtimeserieswasused(TorrenceandCompo,1998).Impor-
et al. (2007), we applied the SSA–MTM toolkit (Dettinger et al., tantfeaturesofthewaveletpowerspectrumareidentifiedassig-
1995; Ghil et al., 2002) for time series frequency analyses using nificantatthe5%level,whichindicatesa95%confidencelevelof
SSA, which is a modified form of principal component analysis coherence between the two series, identifying the relation
(PCA) in the vector space of delay coordinates for a time series. between climatic and hydrologic variables (Torrence and Compo,
SSA incorporates a data-adaptive method to analyze short-noisy 1998; Newman et al., 2003; Grinsted et al., 2004; Holman et al.,
series and extract the dominant frequencies of a time series 2011).
(Vautardetal.,1992).SSAhasbeenwidelyappliedtogeophysical Weusethecontinuouswavelettransform(CWT)thatislocal-
datasetsofvariouslengthsandtoidentifyquasi-periodicoscilla- izedintime(Dt)andfrequency(Dx)toidentifytheperiodicities
tions, for example ENSO and other interannual to multidecadal and phases of cycles within a single time series (Grinsted et al.,
coupledoceanic–atmosphericphenomenon(Vautardetal.,1992). 2004;Holmanetal., 2011). Forthe best balanceoftime and fre-
WeusedSSAtodecomposethedetrendedandnormalizedhydro- quency, the Morlet wavelet is used (Torrence and Compo, 1998;
logic time series into temporal principal components (PCs) that Grinsted et al., 2004). The CWT establishes the power spectrum
representtheprojectionoftheoriginaltimeseriesontoempirical ofeachprecipitation,groundwaterlevel,andclimateindexbefore
orthogonal functions (EOFs) (Vautard et al., 1992; Ghil et al., the cross-correlation of the series is performed (Grinsted et al.,
2002).Thephaseinformationofthetimeseries,oscillatorymodes, 2004).
and noise are reconstructed by using linear combinations of the AftertheCWT,weusedthecrosswavelettransform(XWT)to
PCs and EOFs to create the reconstructed components (RCs). No identify the cross wavelet power of two time series against the
informationislostduringthereconstructionprocessbecausethe background power spectra for each of the series (Torrence and
sumoftheindividualRCsequalstheoriginaltimeseries.Thevar- Compo, 1998; Grinsted et al., 2004). Because errors are present
iabilityinmosthydrologictimeseriescanbeadequatelydescribed atthebeginningandendofthefinitewaveletpowerspectrum,a
intermsofthefirst10RCs(withdecreasingvariancefromoneto coneofinfluence(COI)isusedtoidentifytheregionofthewavelet
ten)(Hansonetal.,2004). spectrumwheretheseedgeeffectsneedtobeexcluded(Torrence
WeappliedSSAtoidentifythefirst10RCsthatrepresentstatis- andCompo,1998;Grinstedetal.,2004).
tically significant oscillatory modes within each of the individual While the XWT identifies areas of high common power, the
climate index, precipitation, groundwater level, and simulated waveletcoherence(WTC)measuresthecross-correlationbetween
pumping time series. The reader is referred to Kuss (2011) for twoseriesasafunctionoffrequencyasaquantitybetween0and1
the SSA results of all 10 RCs for each time series. We used the andidentifiesspectralcoherenceofthetwoseriesevenifthereisa
Chi-Squared significance test (Allen and Smith, 1996) on each of low common power when each series is localized in time–fre-
thefirst10RCstoidentifythosestatisticallysignificantoscillations quencyspace(TorrenceandCompo,1998).Althoughthespectral
(Ha)againstared-noisenullhypothesis(H0).TheSSA–MTMtoolkit coherenceofthetwoseriesishighlighted,thetemporalcoherence
userguideprovidesdetailsaboutthetheoryandapplicationofChi- isdiminishedascomparedtotheXWT(Labat,2005;Grinstedetal.,
Squaredsignificancetest(Dettingeretal.,1995;Ghiletal.,2002). 2004).InordertotestthesignificanceoftheWTC,1000randomly
Foreachindividualtimeseries,wegroupandsumonlythestatis- constructedsyntheticseriesarecreatedusingMonteCarlometh-
tically significant RCs according to the following period ranges: ods(Grinstedetal.,2004).
2–7year(ENSO-like),3–6years(NAO-like),15–25years(PDO-like), The three methodological steps of CWT, XWT, and WTC help
and>25years(>PDO).PDOfluctuationsoverthe20thcenturywere establish the coherence in the temporal viability of the climate
most energetic in two general periodicities – one from 15 to indices,precipitation,andgroundwaterlevels.Althoughthethree
25years and the other from 50 to 70years (Mantua and Hare, steps were necessarily followed, we present only the results and
2002). Here we evaluate only the 15- to 25-year periodicity of discussionontheWTC,whichprovidesthemostrobustoutcomes
the PDO. Because the periodicity of the AMO is indistinguishable ofinteresttothereader(Holmanetal.,2011).Kuss(2011)presents
from the lower frequencymode (50–70years) of PDO variability, detailedresultsanddiscussionfromtheCWTandXWT.
we use thenaming convention proposedby Hansonet al. (2004)
and we refer to all periods of climate variability greater than 3.4.Lagcorrelations
25years as greater than PDO (>PDO). By summing RCs based on
similar period ranges, we create composite RCs that represents Correlation coefficients measure the strength of association
the statistically significant oscillatory modes within each of the betweentwovariables(HelselandHirsch,2002)andwhenasys-
raw hydrologic time series that are consistent with ENSO, NAO, temhasadelayedresponsetosomeforcingoracommondelayed
PDO, or >PDO periodicity (Hanson et al., 2004; Gurdak et al., responsetoanadditionalvariable.Tocalculatethelagcorrelations
2007). The statistically significant composite RCs are used in all andtheirstatisticalsignificance,weusedtheUSGSHydrologicand
subsequentwaveletandlagcorrelationsanalyses. Climatic Analysis Toolkit (HydroClimATe), which is a computer
programtoassessrelationsbetweenvariableclimaticandhydro-
3.3.Waveletanalysis logictime-seriesdata(Dickinsonetal.,2014).Usingaprioriexpec-
tations from regional hydroclimatology documented in the
WeusewaveletanalysistocomplementtheSSAbecausemany literature, we report the strongest and statistically significant
hydrologic time series are nonstationary and have temporal (95% confidence interval) lag correlation coefficients (unitless)
1944 A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952
and corresponding phase lags (year) betweenthe climate indices consistentwithfindingsfromGurdaketal.(2007)thatgroundwa-
andcompositeRCsfromtheprecipitationtimeseriesandbetween ter levels can be substantially influenced by PDO variability. No
thecompositeRCsfromtheco-locatedprecipitationandground- SSA modes of variability with periodicities consistent with NAO
water level time series. As explained by Dickinson et al. (2014), or >PDO were identified in precipitation or groundwater levels
thephaselagsbetweenmanycomplexphysicalprocessesaregen- sitesintheCentralValley(Fig.3a).
erallyundetermined,butthelagcorrelationanalysisisvaluablein GroundwaterlevelsintheCentralValleyaquiferareaffectedby
providinginsightintothesystemwithoutusingadynamic,numer- withdrawals for irrigation (Faunt et al., 2009). We evaluated the
icalmodel. responseingroundwaterpumpingtoclimatevariabilityandtofur-
ther explore the hypothesis that groundwater levels are partially
4.Resultsanddiscussion controlled by climate variability and are not solely a function of
temporal patterns in pumping. The results of SSA indicate that
4.1.HydroclimaticteleconnectionswithENSO,NAO,PDO,and>PDO no statistically significant RCs are present within the simulated
pumpingtimeseries(Fauntetal.,2009),whichindicatesthatthe
TheresultsoftheSSAindicatethatallthehydrologictimeseries simulatedpumpingisnotsubstantiallycontrolledbyclimatevar-
contain variations that are partially consistent with ENSO, NAO, iability.Amorerobustanalysisonadditionalgroundwaterpump-
PDO,and>PDO.Theprecipitationandgroundwaterleveltimeser- ing time series is needed to more definitively evaluate pumping
ies in the Central Valley have two dominant modes of variability responsestointerannualtomultidecadalclimatevariability.How-
consistent with PDO and ENSO (Fig. 3a). The amount of variance ever, it iswell documentedthat agriculturalland-use patternsin
attributed to the PDO-like cycle ranged from 26.4% to 83.0% and theCentralValleyaredynamicandmayvarygraduallyorabruptly
was consistently larger in the precipitation (range 38.6–83.0%, intimebecauseofthecumulativeeffectofurbanizationanddevel-
average of 68.7%) than the co-located groundwater levels (range opment, free-market trends and changing crops types, resource
26.4–53.1%, average 34.5%) (Fig. 3a). The second largest amount limitations, particularly water, and climate variability (Faunt
of variance in precipitation and groundwater levels (range etal., 2009). These complexand changing land-use patternspar-
7.3–20.5%, average 13.3%) was attributed to the ENSO-like cycles tiallycontrolagriculturalgroundwaterdemandwithinthecontext
(Fig. 3a). These findings indicate the importance of lower- ofindividualfarmingpracticesandcropselection.TheSSAfindings
frequency PDO forcings with lesser controls by ENSO and are supportthesecomplexitiesandindicatethatthe2-to7-and15-to
Fig.3. Thepercentvariance(%)andperiod(years)ofthecombinedreconstructedcomponents(RC)fortheprecipitationandgroundwaterleveltimeseriesareshownforthe
(a)CentralValleyaquifer,(b)BasinandRangeaquifersystem,and(c)NorthAtlanticCoastalPlainsaquifersystem.GWdenotesgroundwatersiteandPdenotesprecipitation
site.
A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952 1945
25-year cycles within the groundwater levels are responses to vadosezonetothewatertable.ThetemporallagsbetweenENSO
ENSOandPDO.Theresultsofthestatisticallysignificantlagcorre- coherenceintheprecipitationandENSOcoherenceintheground-
lations, presented below, further support these teleconnections waterlevelsarefurtherquantifiedinSection4.3.Atsites1and5,a
withgroundwaterlevels. 5%significantcoherenceinthe3-to7-yearperiodicityisobserved
TheSSAresultsfromtheBasinandRangeaquifersystemindi- and an approximate 5-year temporal lag in the groundwater
cate multiple modes of variability (Fig. 3b). The PDO-like cycle coherence behind the precipitation coherence to ENSO (Fig. 4a).
was consistently observed as the leading mode of variability in Additionally, moderate to strong coherence is observed at most
allthesites exceptfortwo(BRP2and BRGW2)andcontributed sites(withtheexceptionofGW3andP4),howevertheresultsdo
about 20–77.2% of the variability in all Basin and Range sites notshowa5%significantcoherence.Moderatetostrongcoherence
(Fig.3b).AtBRP2andBRGW2,the>PDOcontributedtothegreat- atthe9-to24-yearperiodisalsoapparentintheWTCofthepre-
est amount of site variability (66.1% and 47.3%, respectively). cipitationandgroundwaterlevelsatallCentralValleysites(with
Althoughthelengthofthetimeseriescanbea limitingfactorin theexceptionofGW2,GW3,andP5)(Fig.4b),whichisconsistent
identifyinglow-frequencycycles,BRP2andBRGW2havemoder- withtheperiodicityofthePDO.Theextentofthe5%significancein
aterecordlengths(1931–2009and1948–2006,respectively)and precipitationthatisconsistentwithPDOvariesacrosstheCentral
manysiteshaveconsiderablylongerrecords.Therefore,thelength Valley, with no 5% significance found at sites P1, P5, GW2, GW3,
oftherecorddoesnotappeartobeacontrollingfactorinobserving andGW4.Thenorthernlocations(sites1and2)havemoretempo-
the low frequency >PDO cycle at BR P2 and GW2. The ENSO-like rally discrete 5% significance that spans the 1970s to 2000s and
cycle is also observed in all of the Basin and Range sites except centers on the 1980s (Fig. 4b), which was a period of persistent
forBRGW2,andcontributes5.8–27.1%ofthevarianceintheBasin positive phase PDO (Fig. 2c) associated with cool wet conditions
and Range sites (Fig. 3b). Excluding the BR GW2, the ENSO-like inthesouthwesternU.S.Sites3and4locatedneartheSanFran-
cyclecontributestoanaverageof13.5%inthevarianceofthepre- cisco Bay and Delta have 5% significance that spans the 1930s to
cipitationandgroundwatersites(Fig.3b). present day (Fig. 4b). For sites 1–3, the 5% significance level in
Thereisanapparentshiftinthedominantcyclepresentinthe groundwater levels that is consistent with PDO tends to be less
hydrologictimeseriesoftheNorthAtlanticCoastalPlainascom- apparent,shorterinduration,andoftentemporallylaggedbehind
pared to the Central Valley and Basin and Range aquifer systems the 5% significance level in the co-located precipitation sites
(Fig.3c).The>PDOcycleisobservedatthreeoftheprecipitation (Fig.4b).TheWTCforNAOand>PDOwerenotpresentedbecause
sitesintheNorthAtlanticCoastalPlain(NAP2,NAP3,andNAP4), the Central Valley precipitation and groundwater levels do not
andcontributestothegreatestamountofvarianceineachrecord havestatisticallysignificantRCswithperiodicitiesconsistentwith
with63%,70.7%,and65.5%,respectively(Fig.3c).SimilartoBasin NAOor>PDO.
and Range sites with >PDO-like variations, the record lengths at Results of the WTC from the Basin and Range aquifer system
sites NAP2, NAP3, and NAP4 are not the longest in this study. (Fig.5)havemanysimilaritiestotheWTCfromtheCentralValley
The North Atlantic Coastal Plain sites have PDO-like cycles that aquifer.AllsitesintheBasinandRangehavemoderatetostrong
contributeabout20–77.7%ofthevariability(Fig.3c).A2-to7-year (0.5–1) coherence with ENSO in the 3- to 7-year period range
signalcontributes4.1–51.2%(NAP3andNAGW2,respectively)of (Fig.5a)andPDOinthe8-to24-yearperiodrange(Fig.5b).How-
thevarianceattheNorthAtlanticCoastalPlainsites,andmaybe ever, unlike the Central Valley, site 2 in the Basin and Rangehas
attributedtotheENSOortheNAO(Fig.3c).TheENSO2-to7-year coherencewith>PDOintheprecipitationandgroundwaterlevels
periodicityislongerthantheNAO3-to6-yearperiodicity,butthe (Fig. 5c). The coherence between precipitation and groundwater
NAO also has an observed 8- to 10-year periodicity (Kiladis and levelsandPDOhastwogeneralpatternssomewhatsimilartothose
Diaz,1989;Hurrelletal.,2003).Previousstudieshavealsoshown fromtheCentralValley.Thereisstrongcoherenceatlonger(16–
coherent ENSO effects in the Mid-Atlantic regions of the U.S. 25year)periodicitiesfromaboutthe1940sand1950stopresent
(RopelewskiandHalpert,1986).Weusethewaveletanalysisand insitesP2andGW4,whilesitesP1,P3,GW3,andP5havestrong
thelag correlationstoidentifytherelativeinfluenceoftheENSO coherence at shorter (8–14years) periodicities (Fig. 2c). Strong
and (or) NAO on the 2- to 7-year cycle in the precipitation and coherenceconsistentwith>PDOwaspresentatsiteP2,particularly
groundwaterlevelsintheNorthAtlanticCoastalPlain,asdescribed fromthe1940sto1960s(Fig.5c),whichisconsistentwiththelast
below. fullpositivephaseofAMO(Fig.2d).However,thecoherenceofthe
>PDOsignalisobserved outsidethecone ofinfluence.The phase
4.2.Coherencebetweenclimateindices,precipitation,and arrowsintheprecipitationandgroundwaterlevelWTCpointsto
groundwaterlevels the left (out-of-phase), which is consistent with drought across
muchoftheU.S.andespeciallythesouthwesternU.S.thatassoci-
The wavelet transforms support the SSA findings and indicate atedwiththepositiveAMOphase(McCabeetal.,2004).
significantcoherencebetweenENSO,NAO,PDO,and>PDOinmany ResultsoftheWTCfromtheNorthAtlanticCoastalPlainaquifer
of the precipitation and groundwater levels. The WTC from the system(Fig.6)indicatemoderatetostrong(0.5–1)coherencewith
Central Valley aquifer (Fig. 4), Basin and Range aquifer system ENSOinthe3-to7-yearperiodrange(Fig.6a)(withtheexception
(Fig. 5), and North Atlantic Coastal Plain aquifer system (Fig. 6) ofGW1andP2),NAOinthe3-to7-yearperiodrange(Fig.6b),PDO
arediscussednext. in the8- to24-year periodrange(Fig. 6c) (withthe exceptionof
AllsitesintheCentralValleyhavemoderatetostrong(0.5–1) GW2), and with >PDO (Fig. 6d). The North Atlantic Coastal Plain
coherencewithENSOintheWTCatthe3-to7-yearperiodrange sitesgenerallyhaveagreaterinfluenceofclimateoscillationsfrom
(Fig.4a).AtCVP1,coherenceatthe5%significancelevelfrom3-to the Atlantic Ocean than from the Pacific Ocean; including coher-
7-yearsintheWTCispredominantlyfromtheearly-1970stothe ence with NAO at all 5 sites and with >PDO at 3 sites (Fig. 6b
mid- to late-1980s, which is consistent with the strong 1976– and d). Each of the North Atlantic Coastal Plain sites has strong
1977 negative ENSO event and the 1982–1983 extreme positive coherenceandinsomecases(notablyatsitesP3andGW5)5%sig-
ENSOevent(Fig.2a).AtCVGW1,coherenceatthe5%significance nificance level from 2 to 7years, which is consistent with ENSO
levelfrom3to7yearsintheWTCisfromthelate-1970stolate- and NAO. WTCs were not computed with the NAO in the Basin
1980s, which is approximately 4- to 5-years lagged behind the and Range or the Central Valley due to the low probability of
5%significancelevelintheP1WTC(Fig.4a)duetothelagbetween influences from the NAO in the western U.S. (Hurrell et al.,
thearrivalofprecipitationandthetraveltimeofwaterthroughthe 2003).WhereastheCentralValleyandBasinandRangesiteshad
1946 A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952
Fig.4. Waveletcoherence(WTC)betweenprecipitationandgroundwaterlevelsattheCentralValleyaquifersites1–5andthe(a)ElNiñoSouthernOscillation(ENSO)and(b)
PacificDecadalOscillation(PDO).Notethatspectralpowerisdimensionless,thethickblacklinesarethe5%significancelevel,andthelessintensecolorsindicatetheconeof
influence(COI).Thephaseangle(shownwithblackarrows)identifiesthephaserelationbetweentwoseries,witharight-pointingarrowindicatinganin-phaserelationanda
left-pointingarrowindicatingananti-phaserelation,andarrowspointingupordownshowthatonetimeseriesisleadingtheotherby90(cid:3)(Grinstedetal.,2004;Holman
etal.,2011).(Forinterpretationofthereferencestocolorinthisfigurelegend,thereaderisreferredtothewebversionofthisarticle.)
5%significancecoherencewithENSOcenteredonthe1980s,most AtlanticCoastalPlainWTCgenerallyareright-pointingindicating
oftheNorthAtlanticCoastalPlainshaveweaktomoderatecoher- anin-phaserelationbetweenthe>PDOcycleandtheprecipitation
enceduringthe1980s(Fig.6a).MostoftheNorthAtlanticCoastal (Fig.6d),whichisconsistentwiththelessfrequentdroughtasso-
Plain sites have 5% significance coherence with NAO that is cen- ciated with the positive phase AMO along the eastern coast of
teredonthemid-tolate-1980s(Fig.6b),whichisconsistentwith theU.S.(McCabeetal.,2004).
the shift from the 1940s to 1970s negative phase to a positive
phase in the 1980s with the greatest NAO index values in 1983, 4.3.Lagcorrelationsbetweenclimateindices,precipitation,and
1989, and 1990 (Fig. 2b) (Hurrell and Van Loon, 1997). These groundwaterLevels
WTC findings indicate relatively less ENSO and relatively more
NAO influence on the precipitation, groundwater levels, and Results indicate that nearly all of the composite RCs from the
recharge to aquifers along the North Atlantic Coast as compared precipitation time series from the selected PAs are statistically
tothoseaquifersinthewesternU.S.Moderatetostrongcoherence correlated(95%confidenceinterval)withtheMEI,NAO,PDO,and
(0.5–0.8) with >PDO is more apparent in the precipitation (sites AMO indices. These findings are consistent with the well estab-
2–4)than groundwater levels of theNorth AtlanticCoastal Plain, lished hydroclimatology literature presented in the background
particularly from the 1940s to 1970s (Fig. 6d). Unlike the >PDO that U.S. precipitation spatiotemporal patterns have complex
coherence in the Basin and Range, the phase angle in the North teleconnectionstointerannualandmultidecadalclimatevariability.
A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952 1947
Fig.5. Waveletcoherence(WTC)betweenprecipitationandgroundwaterlevelsattheBasinandRangeaquifersystemsites1–5andthe(a)ElNiñoSouthernOscillation
(ENSO),(b)PacificDecadalOscillation(PDO),and(c)AtlanticMultidecadalOscillation(AMO).Notethatspectralpowerisdimensionless,thethickblacklinesarethe5%
significancelevel,andthelessintensecolorsindicatetheconeofinfluence(COI).Thephaseangle(shownwithblackarrows)identifiesthephaserelationbetweentwoseries,
witharight-pointingarrowindicatinganin-phaserelationandaleft-pointingarrowindicatingananti-phaserelation,andarrowspointingupordownshowthatonetime
seriesisleadingtheotherby90(cid:3)(Grinstedetal.,2004;Holmanetal.,2011).(Forinterpretationofthereferencestocolorinthisfigurelegend,thereaderisreferredtotheweb
versionofthisarticle.)
Ofthe21precipitationtimeseriesanalyzedfromthefourPAs,20 Fisher and Healy, 2008; Faunt et al., 2009). Results of these
havecompositeRCslagcorrelatedwiththeMEI(coefficientsrange statisticalanalysesprovideinsightintothephysicalprocessesthat
from0.12to0.60),5havecompositeRCslagcorrelatedwithNAO influence hydroclimatic variability in groundwater levels. Future
index(coefficientsrangefrom0.13to0.27),19havecompositeRCs modeling studies are needed to explore how the lag times of
lag correlated with PDO index (coefficients range from 0.14 to climate signal at co-location precipitation and groundwater level
0.83), and 8 have composite RCs lag correlated with AMO index sitesrespondtolocalvadosezonematerials(Gurdaketal.,2007),
(coefficientsrangefrom(cid:2)0.27to(cid:2)0.72).OnlythecompositeRCs includingtheverticaldistributionofsandcontentorlayersofclay
in precipitation that were significantly correlated to the climate andthehydrogeologicpropertiesofthesaturatedaquifer,includ-
indices were used in the lag correlation analysis between the inglocaltransmissivityandstorativity(Dickinsonetal.,2004).
co-locatedprecipitationandgroundwaterlevels(Fig.7). Moderatetostrongstatisticallysignificantlagcorrelationscoef-
ManyCentralValleyandBasinandRangeco-locatedprecipita- ficients between co-located precipitation and groundwater levels
tion and groundwater levels had moderate to strong statistically composite RCs that have periodicities consistent with PDO were
significant (95% confidence interval) lag correlations (coefficients identified in the Central Valley and Basin and Range (Fig. 7a and
rangefrom0.5to0.9)withcompositeRCsofsimilarperiodicities b).Interestingly,therangeofphaselags(11–27years)ofRCswith
asENSOandPDOcycles(Fig.7aandb).However,onlyBasinand periodicities similar to PDO are generally larger than phase lags
Range site 2 had statistically significant lag correlations between (3–14years)ofRCswithperiodicitiessimilartoENSOintheCentral
precipitationandgroundwaterlevelswithperiodicitiessimilarto Valley (Fig. 7a) and Basin and Range (Fig. 7b). These statistical
>PDO (Fig. 7b). In the Central Valley, the average lag correlation resultsprovideinsightsintothephysicalprocessesthatgroundwa-
coefficient between precipitation and groundwater levels consis- ter levels in the western U.S. may have a relatively faster hydro-
tent with ENSO periodicity was 0.5 with an average phase lag of logic response to ENSO as compared to PDO. The statistically
11years(Fig.7a).Wesuggestthattheaveragephaselagisconcep- significant phase lags between the co-located precipitation and
tuallyequivalenttotheaveragetraveltimeofwaterinthevadose groundwaterlevelsintheNorthAtlanticCoastalPlainrangedfrom
zone between the arrival of precipitation at land surface and the 3 to 16years (Fig. 7c) and are generally much smaller than the
responseinthegroundwaterlevels,andthe11-yearaveragephase corresponding phase lags for ENSO or PDO in the Central Valley
lag is reasonable given previously reported recharge rate of or Basin and Range aquifers. These statistical results point to
86–530mmyr(cid:2)1 in the Central Valley (Phillips et al., 2007; importantdifferencesinhydrologicresponsetoENSOandPDOin
1948 A.J.M.Kuss,J.J.Gurdak/JournalofHydrology519(2014)1939–1952
Fig.6. Waveletcoherence(WTC)betweenprecipitationandgroundwaterlevelsattheNorthAtlanticCoastalPlainaquifersystemsites1–5andthe(a)ElNiñoSouthern
Oscillation(ENSO),(b)NorthAtlanticOscillation(NAO),(c)PacificDecadalOscillation(PDO),and(d)AtlanticMultidecadalOscillation(AMO).Notethatspectralpoweris
dimensionless,thethickblacklinesarethe5%significancelevel,andthelessintensecolorsindicatetheconeofinfluence(COI).Thephaseangle(shownwithblackarrows)
identifiesthephaserelationbetweentwoseries,witharight-pointingarrowindicatinganin-phaserelationandaleft-pointingarrowindicatingananti-phaserelation,and
arrowspointingupordownshowthatonetimeseriesisleadingtheotherby90(cid:3)(Grinstedetal.,2004;Holmanetal.,2011).(Forinterpretationofthereferencestocolorin
thisfigurelegend,thereaderisreferredtothewebversionofthisarticle.)
the western groundwater levels as compared to the responses in
the eastern water levels. These differences may be a function of
the relatively smaller recharge fluxes in the western aquifers as
compared to recharge fluxes in the eastern aquifers (McMahon
et al., 2011), which may help regulate the propagation of the
climate variability signals from land surface in the infiltrating
watertothewatertableintherechargeflux.Additionalnumerical
modeling is needed to further explore the controlling physical
processes for the observed spatial and temporal differences in
the phase lags of the climate variability signals in the co-located
precipitationandgroundwaterlevels.
4.4.Nationaltrends
Thisstudyprovidesevidenceofimportantregionalandnational
patternswithrespecttotheENSO,NAO,PDO,and>PDOtelecon-
nections and groundwater level variability across the U.S. In
general, climate oscillations associated with the Pacific Ocean
(ENSOandPDO)(Fig.8aandc)haveagreatercontrolthanAtlantic
Oceanoscillations(NAOandAMO)(Fig.8bandd)onhydroclimatic
variabilityinPAsacrosstheU.S.
AlthoughENSOwasnotthedominantmodeofvariabilityinthe
groundwaterlevels(onaverage13.3%,13.5%,and26.7%intheCen-
tral Valley, the Basin and Range, and the North Atlantic Coastal
Plain,respectively(Fig.3)),ENSOisastatisticallysignificantmode
ofvariabilitythatwasobservedatallbut1ofthe42(precipitation
and groundwater level) sites, including those in the High Plains
(Fig. 8a). Interestingly, there are no statistical differences
Fig.7. Summaryoflagcorrelationcoefficients(unitless)andphaselags(years)for (a=0.05,Tukey–Kramertest(Tukey,1977))inthestrengthoflag
RCs that are significantly (95% confidence interval) correlated with ENSO, NAO,
correlations between ENSO and hydroclimatic variability in the
PDO,and>PDOfromco-locatedprecipitationandgroundwaterlevelsiteinthe(a)
PAs(Fig.8a).Althoughnotstatisticallysignificant,themedianlag
CentralValleyaquifer,(b)BasinandRangeaquifersystem,and(d)NorthAtlantic
CoastalPlainaquifersystem.Sitesarenumber1–5andcorrespondtoTable1. correlations coefficients are slightly stronger in the PAs in the