High Plains aquifer Acknowledgements Interannual to ...

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Interannual Interannual to to Multidecadal Multidecadal Climate Climate High Plains aquifer High Plains aquifer Interannual Interannual to to Multidecadal Multidecadal Climate Climate Variability Effects on Sustainable Variability Effects on Sustainable Groundwater for Agriculture Groundwater for Agriculture Groundwater for Agriculture Groundwater for Agriculture Jason Jason Gurdak Gurdak, PhD , PhD Assistant Professor Assistant Professor Department of Geosciences Department of Geosciences Department of Geosciences Department of Geosciences San Francisco State University San Francisco State University Acknowledgements Acknowledgements Bret Bruce, USGS, Denver, CO Bret Bruce, USGS, Denver, CO Brian Clark, USGS, Little Rock, AR Brian Clark, USGS, Little Rock, AR Kevin Kevin Dennehy Dennehy, USGS, CO , USGS, CO Randy Hanson, USGS, San Diego, CA Randy Hanson, USGS, San Diego, CA Pete McMahon, USGS, Denver, CO Pete McMahon, USGS, Denver, CO Rheannon Rheannon Scheiderer Scheiderer, USGS, Little Rock, AR , USGS, Little Rock, AR USGS, National Water Quality Assessment (NAWQA) Program USGS, National Water Quality Assessment (NAWQA) Program USGS, Groundwater Resources Program, Office of Groundwater USGS, Groundwater Resources Program, Office of Groundwater UNESCO UNESCO – Groundwater Resource Assessment under the Groundwater Resource Assessment under the Pressures of Humanity and Climate change (GRAPHIC) Pressures of Humanity and Climate change (GRAPHIC) Pressures of Humanity and Climate change (GRAPHIC) Pressures of Humanity and Climate change (GRAPHIC) Natural Climate Natural Climate Forcings Forcings El Ni El Niñ /S th O ill ti (ENSO) /S th O ill ti (ENSO) 2 6 l El Ni El Niño/Southern Oscillation (ENSO): o/Southern Oscillation (ENSO): 26 6 year cycle year cycle NOAA, 2010 Winter anomalies and atmospheric circulations Winter anomalies and atmospheric circulations NOAA, NOAA, 2008 2008 Natural Climate Natural Climate Forcings Forcings Pacific Decadal Oscillation (PDO Pacific Decadal Oscillation (PDO): ): 10 10–25 25 & & 50 5070 70 year periodicities year periodicities Mantua (2010) Atlantic Atlantic Multidecadal Multidecadal Oscillation (AMO Oscillation (AMO): ): 40 40–80 80 year periodicities year periodicities NOAA (2010) Modified from McCabe et al., 2004 Natural Climate Natural Climate Forcings Forcings 1930s “Dust Bowl” 1950s drought Motivation: Motivation: Coupling between global climate cycles Coupling between global climate cycles and and hydrogeologic hydrogeologic processes is poorly understood. processes is poorly understood. Effects of ENSO, PDO, AMO on Groundwater Resources? Effects of ENSO, PDO, AMO on Groundwater Resources? Recharge? Nitrate Fate & Transport? Recharge? Nitrate Fate & Transport? High Plains High Plains “Ogallala” “Ogallala” aquifer aquifer Mississippi Mississippi Embayment Embayment aquifer aquifer Embayment Embayment Regional aquifer Regional aquifer study (MERAS) study (MERAS) Denver Denver Memphis Memphis

Transcript of High Plains aquifer Acknowledgements Interannual to ...

Page 1: High Plains aquifer Acknowledgements Interannual to ...

InterannualInterannual toto MultidecadalMultidecadal ClimateClimate

High Plains aquiferHigh Plains aquifer

InterannualInterannual to to MultidecadalMultidecadal Climate Climate Variability Effects on Sustainable Variability Effects on Sustainable

Groundwater for AgricultureGroundwater for AgricultureGroundwater for AgricultureGroundwater for Agriculture

Jason Jason GurdakGurdak, PhD, PhDAssistant ProfessorAssistant Professor

Department of GeosciencesDepartment of GeosciencesDepartment of GeosciencesDepartment of GeosciencesSan Francisco State UniversitySan Francisco State University

AcknowledgementsAcknowledgements

Bret Bruce, USGS, Denver, COBret Bruce, USGS, Denver, COBrian Clark, USGS, Little Rock, ARBrian Clark, USGS, Little Rock, AR, , ,, , ,

Kevin Kevin DennehyDennehy, USGS, CO, USGS, CORandy Hanson, USGS, San Diego, CARandy Hanson, USGS, San Diego, CA

Pete McMahon, USGS, Denver, COPete McMahon, USGS, Denver, CORheannonRheannon ScheidererScheiderer, USGS, Little Rock, AR, USGS, Little Rock, AR

USGS, National Water Quality Assessment (NAWQA) ProgramUSGS, National Water Quality Assessment (NAWQA) ProgramUSGS, Groundwater Resources Program, Office of GroundwaterUSGS, Groundwater Resources Program, Office of Groundwater

UNESCO UNESCO –– Groundwater Resource Assessment under the Groundwater Resource Assessment under the Pressures of Humanity and Climate change (GRAPHIC)Pressures of Humanity and Climate change (GRAPHIC)Pressures of Humanity and Climate change (GRAPHIC) Pressures of Humanity and Climate change (GRAPHIC)

Natural Climate Natural Climate ForcingsForcingsEl NiEl Niññ /S th O ill ti (ENSO)/S th O ill ti (ENSO) 22 66 llEl NiEl Niñño/Southern Oscillation (ENSO): o/Southern Oscillation (ENSO): 22––6 6 year cycleyear cycle

NOAA, 2010

Winter anomalies and atmospheric circulations Winter anomalies and atmospheric circulations

NOAA, NOAA, 20082008

Natural Climate Natural Climate ForcingsForcingsPacific Decadal Oscillation (PDOPacific Decadal Oscillation (PDO): ): 1010––25 25 & & 5050––70 70 year periodicitiesyear periodicities(( )) y py p

Mantua (2010)

Atlantic Atlantic MultidecadalMultidecadal Oscillation (AMOOscillation (AMO): ): 4040––80 80 year periodicitiesyear periodicities

NOAA (2010)

Modified from McCabe et al., 2004Natural Climate Natural Climate ForcingsForcings

•1930s •“Dust Bowl”

•1950s •drought

Motivation: Motivation: Coupling between global climate cycles Coupling between global climate cycles and and hydrogeologichydrogeologic processes is poorly understood. processes is poorly understood.

Effects of ENSO, PDO, AMO on Groundwater Resources?Effects of ENSO, PDO, AMO on Groundwater Resources?Recharge? Nitrate Fate & Transport?Recharge? Nitrate Fate & Transport?g pg p

High Plains High Plains “Ogallala” “Ogallala” aquiferaquifer

Mississippi Mississippi EmbaymentEmbaymentaquiferaquifer Embayment Embayment Regional aquifer Regional aquifer study (MERAS)study (MERAS)DenverDenver

MemphisMemphis

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MotivationMotivationEstimated Withdrawals from Principal Aquifers in the U.S.Estimated Withdrawals from Principal Aquifers in the U.S.

M i d B b (M i d B b (200200 ) USGS Ci l) USGS Ci l 12 912 9Maupin and Barber (Maupin and Barber (20052005): USGS Circular ): USGS Circular 1279 1279

Maupin and Barber, 2005

MotivationMotivationEstimated Withdrawals from Principal Aquifers in the U.S.Estimated Withdrawals from Principal Aquifers in the U.S.

Maupin and Barber (Maupin and Barber (20052005): USGS Circular): USGS Circular 12791279Maupin and Barber (Maupin and Barber (20052005): USGS Circular ): USGS Circular 1279 1279

USGS NAWQA Study Design:USGS NAWQA Study Design:Source, Transport, and ReceptorSource, Transport, and Receptor

•10 year groundwater-quality study

A l d 180 h i l•Analyzed 180 chemical compounds and physical properties from:

300 d i ( i ) ll- 300 domestic (private) wells,- 70 public-supply wells,- 50 irrigation wells, and - 160 shallow monitoring wells.

USGS NAWQA Study Design:USGS NAWQA Study Design:Source, Transport, and ReceptorSource, Transport, and Receptor

focus of talkof talk

Gurdak et al., 2009

VadoseVadose Zone Research NetworkZone Research Network

Monitoring Monitoring wellwell

Recharge Rates (Recharge Rates (33H and H and ClCl––))Controlled by land use and climateControlled by land use and climate

22 8 8

yy

22..8 8 in/yrin/yr

44..4 4 in/yrin/yr

00..008 008 in/yrin/yr

00..7 7 in/yrin/yr

McMahon et al., McMahon et al., 20062006, WRR , WRR

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Conversion of Rangeland to Irrigated Cropland Conversion of Rangeland to Irrigated Cropland Affects Water QualityAffects Water QualityAffects Water QualityAffects Water Quality

Gurdak et al., Gurdak et al., 2009 2009

Conversion of Rangeland to Irrigated Cropland Conversion of Rangeland to Irrigated Cropland Aff W Q liAff W Q liAffects Water QualityAffects Water Quality

Gurdak et al., Gurdak et al., 2009 2009

Episodic Recharge EventEpisodic Recharge Event200420042004 2004 –– second wettest year on recordsecond wettest year on record

(snow in November and January)(snow in November and January)

IrrigatedIrrigated IrrigatedIrrigated

ff

Irrigated Irrigated IrrigatedIrrigatedField Rangeland Field RangelandField Rangeland Field Rangeland

beforebefore

afterafter

Gurdak et alGurdak et al 20072007 VadoseVadose Zone JournalZone JournalGurdak et al., Gurdak et al., 20072007, , VadoseVadose Zone Journal Zone Journal

Episodic Chemical Mobilization EventEpisodic Chemical Mobilization Event2000 20052000 20052000 2005 2000 2005

Gurdak et al., Gurdak et al., 20072007, , VadoseVadose Zone Journal Zone Journal

Hydrologic Time SeriesHydrologic Time Series

•• GW Levels GW Levels ((1930 1930 –– present)present)•• Precipitation Precipitation ((1888 1888 –– present)present)pp (( p )p )•• GW Pumping GW Pumping ((1978 1978 –– present) present) •• Stream FlowStream Flow ((1924 1924 –– present)present)•• Stream QualityStream Quality ((19381938 –– present)present)•• Stream QualityStream Quality ((1938 1938 –– present)present)•• GW QualityGW Quality ((1937 1937 –– present)present)•• Tree RingTree Ring ((1476 1476 –– present)present)

•• ENSO index (ENSO index (WolterWolter and and TimlinTimlin))•• PDO index (Mantua and Hare)PDO index (Mantua and Hare)( )( )•• AMO index (Enfield et al.)AMO index (Enfield et al.)

GurdakGurdak et al.,et al., 20072007,, VadoseVadose Zone JournalZone JournalGurdakGurdak et al., et al., 20072007, , VadoseVadose Zone Journal Zone Journal

Singular Spectrum Analysis (SSA)Singular Spectrum Analysis (SSA)Singular Spectrum Analysis (SSA) Singular Spectrum Analysis (SSA)

Transform from time domain to frequency domainTransform from time domain to frequency domain

Relatively Wet

Transform from time domain to frequency domain.Transform from time domain to frequency domain.

Relatively Wet

Relatively Dry

Modified from Hanson et al., Modified from Hanson et al., 20042004

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Results: Singular Spectrum AnalysisResults: Singular Spectrum Analysis High Plains Aquifer: Variance in GW LevelsHigh Plains Aquifer: Variance in GW Levels

ENSOENSO PDOPDO AMOAMO

Estimate Recharge using Spectral AnalysesEstimate Recharge using Spectral AnalysesHydrologicHydrologic Time Series (HTS) MethodTime Series (HTS) MethodHydrologicHydrologic--Time Series (HTS) MethodTime Series (HTS) Method

LagLag--Correlation Coefficients = Correlation Coefficients = 00..65 65 to to 00..9898

t = phase lag

t = transit time

water tablewater table

GurdakGurdak et al., et al., 20072007, , VadoseVadose Zone Journal Zone Journal

PDO Affects Recharge Rates & MechanismPDO Affects Recharge Rates & Mechanism

yr-1

) (m

m y

Focused Rechargeduring +PDO

char

ge

during +PDO

recharge flux

Rec

Diffuse Recharge

recharge flux

north central south water tablewater table

McMahon et al., McMahon et al., 20062006, Water Resources Research , Water Resources Research Gurdak et al., Gurdak et al., 20072007, , 20082008, , VadoseVadose Zone JournalZone Journal

MERASMERASHydrologic TimeHydrologic Time Series NetworkSeries NetworkHydrologic TimeHydrologic Time--Series NetworkSeries Network

•• GW LevelsGW Levels ((1935 1935 –– present)present)(( p )p )•• Stream Flow Stream Flow ((1905 1905 –– present)present)•• Tree Ring Tree Ring ((1004 1004 –– present)present)•• ClimateClimate ((18631863 present)present)•• Climate Climate ((1863 1863 –– present)present)

(US Historical Climate Network)(US Historical Climate Network)

•• ENSO index (ENSO index (WolterWolter and and TimlinTimlin))(( ))•• PDO index (Mantua and Hare)PDO index (Mantua and Hare)•• AMO index (Enfield et al.)AMO index (Enfield et al.)

PostPost--SSASSAClimateClimate Cycle Extrapolation:Cycle Extrapolation: 20082008 20382038ClimateClimate--Cycle Extrapolation: Cycle Extrapolation: 2008 2008 –– 2038 2038

Autoregressive (AR) model: Autoregressive (AR) model: 2 2 example precipitation sites example precipitation sites

Variance / PeriodicityVariance / Periodicity

7373% / PDO, AMO% / PDO, AMO

9898% / ENSO, PDO, AMO% / ENSO, PDO, AMO

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20082008 –– 201020102008 2008 –– 2010 2010

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

20122012 –– 201420142012 2012 –– 2014 2014

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

20162016 –– 201820182016 2016 –– 2018 2018

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

20202020 –– 202220222020 2020 –– 2022 2022

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

20242024 –– 202620262024 2024 –– 2026 2026

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

20282028 –– 203020302028 2028 –– 2030 2030

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

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20322032 –– 203420342032 2032 –– 2034 2034

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

20362036 –– 203820382036 2036 –– 2038 2038

MonthlyMonthly Deviation fromDeviation fromMonthly Monthly Precipitation (cm) Precipitation (cm)

Deviation fromDeviation fromLongLong--Term Average (%) Term Average (%)

USGS Groundwater Resources ProgramUSGS Groundwater Resources Program

Motivation: Availability of GW in the MERAS?Motivation: Availability of GW in the MERAS?

Mississippi River ValleyMississippi River Valley

USGS Groundwater Resources ProgramUSGS Groundwater Resources ProgramClark et al., In Review, USGS Professional PaperClark et al., In Review, USGS Professional Paper

Mississippi River ValleyMississippi River Valleyalluvial aquiferalluvial aquifer

MODFLOW-2005 Model

13 13 layers.layers.++5050,,000 000 calibration wells.calibration wells.66,,000 000 mile of streams.mile of streams.

Plunging syncline, axis parallel to river.Plunging syncline, axis parallel to river.5 5 aquifers and aquifers and 4 4 confining units.confining units.

SimulatedSimulatedWaterWater--LevelLevelWaterWater--Level Level

Change Change

2038 2038 -- 20072007

2626% loss of % loss of 2007 2007 storage.storage.

< < 130 130 yr life expectancy. yr life expectancy.

Modified from:Modified from:

y p yy p y

Modified from: Modified from: Clark et al., In Review, Clark et al., In Review, USGS Professional PaperUSGS Professional Paper

Conclusions: Understanding GW SustainabilityConclusions: Understanding GW SustainabilityQuantifying spatiotemporal patterns of climate variability and Quantifying spatiotemporal patterns of climate variability and y g p p p yy g p p p y

effects on groundwater will be crucial to improve our effects on groundwater will be crucial to improve our understanding of resource sustainability. understanding of resource sustainability.

•• ENSO and PDO important controls on recharge, GW levels, ENSO and PDO important controls on recharge, GW levels, storage, and contaminant transport.storage, and contaminant transport.

•• Conceptual models of GW systems must consider climate Conceptual models of GW systems must consider climate forcingsforcings on these timescales. on these timescales.

P t ti l di t bilit ltiP t ti l di t bilit lti /d d ti l/d d ti l•• Potential predictability over multiPotential predictability over multi--year/decade timescales.year/decade timescales.

•• Preferred periods for artificial recharge, agricultural Preferred periods for artificial recharge, agricultural ti d th b tti d th b t t t t it t t ipractices, and other bestpractices, and other best--management strategies.management strategies.

•• Discriminate human impacts from natural variability Discriminate human impacts from natural variability ( t l h li t h ill ff t li t l )( t l h li t h ill ff t li t l )(not clear how climate change will affect climate cycles).(not clear how climate change will affect climate cycles).

QuestionsQuestionsJason GurdakJason Gurdak

email: [email protected] site: http://online.sfsu.edu/~jgurdak/

Geosciences Department, San Francisco State University

High Plains High Plains “Ogallala”“Ogallala”“Ogallala” “Ogallala” aquiferaquifer Mississippi Mississippi

EmbaymentEmbaymentRegionalRegionalRegional Regional aquiferaquifer