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ENSO-Induced Drought Impacts on Groundwater Levels in the Lower Apalachicola-Chattahoochee-Flint River Basin By Subhasis Mitraa, Puneet Srivastavaa, Lynn.

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Presentation on theme: "ENSO-Induced Drought Impacts on Groundwater Levels in the Lower Apalachicola-Chattahoochee-Flint River Basin By Subhasis Mitraa, Puneet Srivastavaa, Lynn."— Presentation transcript:

1 ENSO-Induced Drought Impacts on Groundwater Levels in the Lower Apalachicola-Chattahoochee-Flint River Basin By Subhasis Mitraa, Puneet Srivastavaa, Lynn Torakb and Sarmistha Singha aBiosystems Engineering, Auburn University bGeorgia Water Science Center, USGS

2 Acknowledgement Part of the larger grant funded by the NOAA-SARP Program. Overarching goals are to (a) define groundwater levels as a drought indicator in support of NIDIS DEWS and (b) develop effective drought management policies for the ACF River Basin to help resolve tri-state (AL-GA-FL) water wars. Partners USGS Georgia Water Science Center (Lynn Torak) National Center for Atmospheric Research (David Yates and Kathy Miller) Albany State University, GA (Mark Masters)

3 Introduction Since 1980, the Southeast has experienced several severe droughts. Year 2000 Year 2007 Year 2011 Caused losses in agricultural productivity, prompted water-use restrictions, and intensified long-term water conflicts with neighboring states. Drought water shortages exacerbated by increased water demands in Atlanta area and irrigated agriculture in southwest Georgia. This led to the tri-state water conflict.

4 Tri-State Water War The ACF River Basin is at the center of the tri-state water crisis In the lower part of the basin, excessive water withdrawal for irrigation during drought threatens streamflows in Flint and Apalachicola River Basins. Major challenge is irrigation-related streamflow depletion during droughts.

5 Study Area in the Lower ACF River Basin
About 4632 mi2 of land area contributes surface water and groundwater to the Upper Floridan Aquifer (UFA). The climate of the lower ACF River Basin is humid subtropical with long summers and mild winters. Location of the study area, geohydrologic zones, and GW observation wells used in this study.

6 Irrigation in the Lower ACF
Middle and Lower Chattahoochee-Flint River basin Coastal Region Central-South Georgia Groundwater sites out number surface water sites 5 to 1. Lower ACF has about 500,000 irrigated acreage with approximately 4000 wells pumping water from the Upper Floridan Aquifer. 2 1 3

7 Irrigation in the Middle and Lower Chattahoochee-Flint River Basin
Can be hundreds of millions of gallons per day.

8 Ineffective Drought Management Policy
To reduce irrigation water demand and maintain streamflows during droughts, Georgia instituted the Flint River Drought Protection Act (FRDPA). However, the drought buy-back program was only used twice: in 2001 and Under 2012’s severe drought conditions, the state declined to implement the program, citing lack of funds. The program was costly and ineffective. There is a pressing need for alternate and mutually acceptable drought policy. In addition, there is a need for more effective drought indicators that can forecast the onset, persistence, and conclusion of all kinds of droughts.

9 Drought Indicators A number of drought indicators (precipitation, streamflow, etc.) are used in the Southeast to measure the onset, persistence and conclusion of droughts.

10 Groundwater Level as a Drought Indicator
Although indicators derived from precipitation, streamflows, and lake levels are extensively used for determining the onset, persistence, and conclusion of droughts, the use of groundwater levels has not been fully explored. Uses groundwater levels from a single well in the Upper Floridan Aquifer is currently used as a drought indicator.

11 Historic Range & 2011 Values
Location Daily Depth to Water Table Well A Well B Therefore, groundwater levels at different locations should be used as an indicator to develop a more complete picture of the severity, to develop strategies that can help Georgians manage through drought, and to determine recovery from drought.

12 Goals of the Study The overarching goals of the proposed project are to: Define groundwater levels as a drought indicator in support of the National Integrated Drought Information System (NIDIS) Drought Early Warning System (DEWS), and Develop effective drought management policies for the ACF River Basin to help resolve tri-state (AL-GA-FL) water wars.

13 Specific objectives Quantify the effect of climate variability induced droughts on groundwater levels under different overburden conditions. Quantify how pumping for irrigation exacerbates the effect of drought on groundwater levels and streamflows. Develop a procedure for forecasting groundwater levels. Analyze pros and cons of existing drought management policies and propose a set of policy alternatives that can be used to effectively manage drought in the basin.

14 El Niño Southern Oscillation (ENSO)
What Causes Droughts in Southeast USA? El Niño Southern Oscillation (ENSO) Cycle of above and below average sea-surface temperatures in the equatorial pacific of the coast of Peru. Three phases- El Niño (warm phase); La Niña (cold phase) and Neutral phase with 2-7 year periodicities. El Niño is expressed in decreased temperature and increased winter precipitation in the Southeastern USA. La Niña is expressed in increased temperature and decreased winter precipitation in the Southeastern USA.

15 El Niño Southern Oscillation (ENSO)
Major mode of climate variability in the Southeast United States. ENSO have been found to affect different components of the hydrologic cycle in the Southeast US (Vaishali et al., Lall et al.) Potentially can affect groundwater as well in the study area. Provides an opportunity to study ENSO effects on GW levels and its interaction with anthropogenic factors.

16 Upper Floridan Aquifer System (UFAS)
Overburden Groundwater levels in the UFA respond to seasonal climatic effects such as precipitation, droughts, stream stage and lake level changes. Fluctuations in groundwater levels in the UFA also depend on: Thickness and location specific hydraulic characteristics of the above lying upper semi-confining unit, Proximity to surface streams or lake system. Groundwater irrigation withdrawal for agricultural, industrial and municipal purposes.

17 Data Collection and Processing
Niño 3.4 Monthly Sea-Surface temperature (SST) data were collected from Climate Prediction Center-NOAA. Daily groundwater (GW) level data were collected from USGS-Georgia Water Science Center. Twenty-one long-term observation wells with 25 to 30 years of data were used. Groundwater level anomalies were calculated and sorted according to recharge (December-April) and non-recharge seasons (May-November). The software package for Wavelet analysis was used from the Matlab code developed by Aslak Grinsted ( wavelet-coherence).

18 Methodology Wavelet analysis was used to analyze teleconnection between Niño 3.4 and GW levels. Three wells under shallow (<50 ft), moderately deep (>50 ft) and deep overburden conditions (>100 ft) were used to study the fluctuations of groundwater levels with ENSO under different overburden conditions. Non-parametric Mann-Whitney tests were used to quantify the impacts of ENSO phases on the medians GW level anomalies in the ACF for recharge (December-April) and non-recharge seasons (May-November). Twenty-one long-term observation wells were used for this part. The year was specially analyzed to study the effects of strong La Niña events (prolonged droughts) on GW level anomalies. Recovery Periods were calculated. Two particular La Niña events, year and , representing short and prolonged La Niña (prolonged drought) were compared.

19 Methodology Wavelet Analysis
Wavelet analysis examines the relationship between two time series to determine the prevailing modes of variability and their variation over the time period. Used to quantify and visualize statistically significant changes in ENSO SST anomalies and GW level variance during the historical time period. Continuous Wavelet Transform The Continuous Wavelet Transform analyses localized recurrent oscillations in time series by transforming it into time and frequency space. Cross Wavelet Transform and Wavelet Coherence Transform Cross Wavelet Transform examines whether two time series in regions of time-frequency space share high common power and consistent phase relationship, which might suggest causalty. Wavelet Coherence Transform finds larger significant areas compared to Cross Wavelet Transform.

20 Methodology Recovery Period
Recovery period was calculated using 3 month running averages of GW level anomalies. Defined by the time required for GW level anomalies to remain above ft for at least 6 consecutive 3-month running averages after the end of the La Niña phase.

21 Results Continuous Wavelet Spectra
Time (year) Period (years) (a) (b) (d) (c) Continuous Wavelet Spectra SST Well under shallow and moderately deep overburden conditions showed regions of high power, though not statistically significant, in the 2-7 year ENSO periodicities. Shallow Moderately Deep Wells under deep overburden, did not exhibit any areas with high power. Deep

22 Results Cross-Wavelet Analysis and Wavelet Coherence Transform
(b) (e) (c) (f) Time (year) Period (years) Shallow The Cross-Wavelet Analysis and Wavelet Coherence Transform between SST and GW level anomalies shows high shared power in the areas that were seen to be sharing high power in the single wavelet spectra. Wells under shallow and moderately deep shared high and significant power in the 2-7 year periodicities and the significant areas within this periodicities are positively phase locked. These areas of shared power in Cross-Wavelet Analysis and Wavelet Coherence Transform suggests causalty. Moderately Deep Deep Well under deep overburden did not show any shared high and significant power in any period suggesting that groundwater levels under deep overburden conditions are not affected by ENSO.

23 Results Mann Whitney test results between ENSO phases and monthly groundwater level anomalies Well-ID El Niño (ft) La Niña (ft) Diff (ft) P (<0.05) 06F001 1.35 -3.96 5.30 0.00 10G313 0.72 -2.82 3.54 08G001 3.66 -5.50 9.16 08K001 5.74 -2.42 8.16 11K003 3.35 -1.52 4.87 12L030 2.33 -2.56 4.88 12L028 1.76 -3.19 4.96 13L049 2.89 -3.68 6.57 13M006 3.24 -1.62 4.86 07H002 3.79 -2.76 6.56 12L029 1.82 -2.24 4.07 11K015 0.36 -2.03 2.39 15L020 0.60 -1.95 2.56 0.41 Median 1.36 -2.02 Significant differences were found in GW level anomalies for all wells, except for deep well 15L020. The median of GW level anomalies during the El Niño and La Niña phases were above average (+ve) and below average (-ve), respectively.

24 Recharge (December-April) Non – Recharge (May–November)
Results Recharge (December-April) Well-ID El Niño (ft) La Niña (ft) diff (ft) p-value 06F001 5.40 -5.77 11.17 0.00 10G313 1.91 -3.37 5.29 08G001 7.31 -7.93 15.23 08K001 4.54 -2.21 6.75 11K003 4.61 -3.23 7.84 12L030 3.64 -2.77 6.42 12L028 4.02 -4.06 8.08 13L049 6.31 -4.42 10.73 13M006 3.35 -1.51 4.86 07H002 3.78 -2.47 6.25 12L029 3.14 -2.87 6.01 11K015 3.34 -3.21 6.54 15L020 0.7 -3.91 0.16 Median 3.13 -2.83 6.13 Non – Recharge (May–November) Well-ID El Niño (ft) La Niña (ft) diff (ft) p-value 06F001 0.10 -3.38 3.48 0.00 10G313 -0.30 -2.40 2.10 08G001 2.18 -4.35 6.53 08K001 6.27 -3.30 9.56 11K003 2.06 -0.86 2.92 0.04 12L030 1.47 -2.45 3.92 12L028 0.51 -3.17 3.68 0.01 13L049 1.17 -2.82 3.99 13M006 2.93 -1.73 4.66 07H002 3.81 -4.16 7.97 12L029 1.02 -1.78 2.81 11K015 -0.41 -1.26 0.86 0.92 15L020 0.53 1.28 -0.75 0.75 Median 0.58 -1.68 2.32

25 Results Comparison of monthly averaged GW anomalies for severe ( ) and average La Niña phase during recharge and non-recharge seasons. Well_Id Recharge Non Recharge Minimum La Niña Year 06F001 -5.20 -4.49 -2.86 -4.24 -10.44 10G313 -2.90 -6.70 -2.15 -6.38 -9.60 08G001 -5.83 -8.83 -3.68 -7.90 -14.31 08K001 -3.58 -3.02 -3.48 -6.19 -15.26 11K003 -3.21 -8.47 -1.26 -7.37 -13.66 12L030 -2.28 -3.79 -1.65 -3.83 -6.71 12L028 -3.56 -6.21 -2.09 -4.73 -10.13 13L049 -3.57 -6.13 -2.12 -5.38 -8.50 13M006 -1.93 -2.06 -3.01 -3.93 -17.43 07H002 -2.56 -3.19 -1.77 -2.18a 12L029 -3.70 -3.76 -4.96 11K015 -3.78 -9.07 -1.03 -7.15 -14.38 10K005 -0.51 -0.32 -0.49 -5.48 Mean -2.81 -4.42 -1.78 -4.29 Average GW level anomalies were approximately twice lower during than average La Niña phase in both the recharge and the non-recharge seasons. Minimum GW level anomalies for year were almost 3 times lower than average La Niña phase values with GW level anomalies going below 10 ft at 8 well locations and below 5 ft at 20 at well locations. Wells 08G001, 08K001 and 13M006 groundwater levels fell to approximately below 15 ft during , which demonstrates the effect of severe and prolonged La Niña can have on groundwater levels.

26 Results Comparison of recovery periods (months) for prolonged (2001) and short (1989) La Niña phase. Well-ID Year 2001 Year 1989 06F001 18 1 10G313 24 8 08G001 08K001 11K003 25 2 13L012 12L030 26 12L028 6 13L049 13M006 12L029 11K015 10K005 Mean 22 Year representing severe La Niña phase shows significantly higher recovery times than the year The average recovery time for year was 22 months as compared to 2 months for Important information regarding drought indicators as other drought indicators might show that drought is over and this might not be true for GW indicator wells.

27 Conclusions Wavelet Analysis showed that wells under shallow and moderately deep overburden conditions exhibit ENSO signals while wells under deep overburden conditions does not exhibit such a relationship. Mann Whitney test results validates the above relationship. GW level anomalies tended to be above average during El Niño phase and below average during La Niña events. ENSO signals are stronger during recharge season than non-recharge. Severe La Niña events can severely affect groundwater resources and their recovery periods thereby threatening sustainability.

28 Future Work Objective 2 Quantify how pumping for irrigation exacerbates the effect of La Niña on groundwater levels. Methodology Separate the effects of rainfall and irrigation. Use MODFE model to simulate different irrigation scenarios and identify critical areas. How irrigation affects leakage and stream-aquifer interactions. MODFE Model USGS MODular Finite-Element model (developed by Cooley and Torak) Two Dimensional Groundwater flow model. The model uses boundary and initial conditions to simulate groundwater levels and other aspects of groundwater flow.

29 Uses finite element mesh to simulate groundwater levels at the node points.

30 Future Work Develop procedure for forecasting groundwater levels using ENSO forecasts. Prediction Results from first objective indicates a potential for possible groundwater level prediction with respect to ENSO phases. Predictions can be used to notify agricultural users of possible restrictions on agricultural water withdrawal. Ensure sustainable use of groundwater resources in the study area.

31 Thank you! Subhasis Mitra Dr. Puneet Srivastava

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