What do climate projections say about future droughts in Alabama and the Apalachicola ...

140 Pages·2015·2.75 MB·English

What do climate projections say about future droughts in Alabama and
the Apalachicola-Chattahoochee-Flint River Basin?
by
Nischal Mishra
A thesis submitted to the Graduate Faculty of
Auburn University
in partial fulfillment of the
requirements for the Degree of
Master of Science
Auburn, Alabama
August 1, 2015
Keywords: drought, drought indices, climate change, groundwater, Standardized
Precipitation Index, Standardized Precipitation Evapotranspiration Index
Copyright 2015 by Nischal Mishra
Approved by
Puneet Srivastava, Chair, Butler-Cunningham Eminent Scholar and Professor of
Biosystems Engineering
Latif Kalin, Professor, School of Forestry and Wildlife Sciences
Ming-Kuo Lee, Robert B. Cook Professor, Department of Geosciences
Abstract
Droughts, often considered the costliest natural disaster, are triggered by severe
shortage of water, mainly in the form of precipitation. The Southeast US has been
affectedbyfrequentseveredroughtsinrecentyearsandthiscallsforamorepragmatic
approach to better manage its consequences. The primary objective of this study was
to analyze how droughts in Alabama and ACF River Basin will change in future as a
result of projected climate change. Commonly used drought indices were computed
to quantify the change in droughts.
Historical and future droughts were quantified by the means of Standardized
Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index
(SPEI) and the change in frequency, severity and spatial extent of future droughts
were studied using Severity-Area-Frequency (SAF) curves. Precipitation and tem-
perature data, regionally downscaled for the Southeast US for high emission scenario
(A2), from three General Circulation Models, Hadley Centre Coupled Model Version
3 (HadCM3), Geophysical Fluid Dynamics Laboratory (GFDL) Model and Commu-
nityClimateSystemModel(CCSM),fromtheThirdCoupledModelInter-comparison
Project (CMIP3) archive were used for this study. Data from 1969 to 1999 were used
for historical simulation and that from 2039 to 2069 were used for future projections.
The study showed that droughts similar to ones in the past would be observed
frequently in future as well. In Alabama, SPI from GFDL and HadCM3 models
indicated increasing frequency of droughts with more severity and increased spatial
extent in the future. SPI from CCSM model indicated decreased severity of droughts
in the future spread over similar area as in the past. This model indicated decreased
occurrences of severe and extreme droughts but increased occurrences of moderate
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droughts. Similar conclusions were drawn about droughts in the ACF River Basin as
well from the respective models and indices.
SPI was also correlated with groundwater levels in the Lower ACF River Basin
to determine if it could be used to monitor groundwater conditions in the region.
The index, when calculated at timescales between 9 and 12 months, showed strong
correlation with groundwater levels in many groundwater wells in the region. The
results suggested that it can be used as a tool to monitor groundwater conditions and
hydrologic droughts in the Lower ACF River Basin.
The results of this research can be used by policymakers to plan ahead of time
for better preparation of drought years. If droughts can be projected well ahead of
time, their consequences can be tackled more appropriately. The results will also help
us understand expected changes in droughts in the Southeast US and would help us
prepare better to mitigate the economic, social and environmental effects of droughts.
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Acknowledgments
This thesis would not have been possible without the constant love, support
and encouragement from many people throughout my academic endeavors at Auburn
University.
I would never have reached this stage in life without the incessant love, support
and encouragement of my parents. They stood by me in every decision I’ve made
in my life and directed me in the right direction whenever I seemed to wander away
from my chosen path. They instilled in me the confidence to attain the goals I set.
I owe them my immortal gratefulness and can never thank them enough for all that
they have done for me. I would also like to thank my grandparents for their love and
encouragement and providing me the inspiration do something meaningful in my life.
I am beyond grateful to my academic advisor, Dr. Puneet Srivastava for con-
sistently guiding me throughout my graduate studies. I want to extend my sincere
thanks to him for his persistent support, academically as well as morally, and in
pushing me forward to conquer greater heights. I also express my gratitude for him
being patient with my work and my shortcomings.
I would also like to gratefully acknowledge my thesis advisory committee Dr.
Latif Kalin and Dr. Ming-Kuo Lee for their invaluable help, guidance and feedback
during the course of my research. I would like to thank Dr. Lydia Stefanova for
providingthedataandnecessaryinformationaboutthedatasets. Also, specialthanks
to Dr. T. Prabhakar Clement for encouraging me to think critically and analytically
while performing any research step.
My heartfelt thanks to all my friends who stood by me through all my frenzies
and forever encouraged me to move a step further and make a difference. My special
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thanks to Nafiul Islam, Dr. Golbahar Mirhosseini, Sarmistha Singh, Dr. Subhasis
Mitra, Aurelie Poncet, Oluwafemi Oyedeji, Thomas Loxley, Ryan McGehee, and Uj-
jain Pradhan for consistently reviewing my research works, suggesting improvements
and guiding me forward.
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Table of Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvi
List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xviii
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Thesis Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Review of Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1 The Hydrologic Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 Droughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.3 Kinds of Droughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.1 Meteorological Droughts . . . . . . . . . . . . . . . . . . . . . 8
2.3.2 Agricultural Droughts . . . . . . . . . . . . . . . . . . . . . . 8
2.3.3 Hydrological Droughts . . . . . . . . . . . . . . . . . . . . . . 8
2.3.4 Socioeconomic Droughts . . . . . . . . . . . . . . . . . . . . . 9
2.4 Effects of Droughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.5 Droughts in the Southeast USA . . . . . . . . . . . . . . . . . . . . . 10
2.6 Drought Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.6.1 Palmer’s Drought Severity Index (PDSI) . . . . . . . . . . . . 12
2.6.2 Self-calibrating Palmer’s Drought Severity Index (sc-PDSI) . . 13
2.6.3 Standardized Precipitation Index (SPI) . . . . . . . . . . . . . 14
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2.6.4 Standardized Precipitation Evapotranspiration Index (SPEI) . 15
2.7 Climate Change and Droughts . . . . . . . . . . . . . . . . . . . . . . 16
2.8 Climate Change Scenarios . . . . . . . . . . . . . . . . . . . . . . . . 17
2.9 General Circulation Models . . . . . . . . . . . . . . . . . . . . . . . 18
2.9.1 Community Climate System Model . . . . . . . . . . . . . . . 19
2.9.2 Geophysical Fluid Dynamics Laboratory Model . . . . . . . . 19
2.9.3 Hadley Center Coupled Model Version 3 . . . . . . . . . . . . 19
2.10 Regional Downscaling . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.11 Potential Evapotranspiration (PET) . . . . . . . . . . . . . . . . . . . 20
2.12 Severity-Area-Frequency (SAF) Curves . . . . . . . . . . . . . . . . . 21
2.13 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3 Projectedfuturechangesinfrequency,severityandspatialextentofdroughts
in Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.3 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.4 Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.5 Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.5.1 Standardized Precipitation Index (SPI) . . . . . . . . . . . . . 30
3.5.2 Standardized Precipitation Evapotranspiration Index (SPI) . . 30
3.5.3 Potential Evapotranspiration . . . . . . . . . . . . . . . . . . . 31
3.5.4 Severity-Area-Frequency (SAF) Curves . . . . . . . . . . . . . 31
3.5.5 Timescale of Indices . . . . . . . . . . . . . . . . . . . . . . . 32
3.6 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.6.1 SPI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.6.2 SPEI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.7 Summary and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 45
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4 Howwouldfrequency,severityandspatialextentoffuturedroughtschange
in the Apalachicola-Chattahoochee-Flint River Basin? . . . . . . . . . . . 47
4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.3 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.4 Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.5 Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.5.1 Standardized Precipitation Index (SPI) . . . . . . . . . . . . . 54
4.5.2 Standardized Precipitation Evapotranspiration Index (SPI) . . 55
4.5.3 Potential Evapotranspiration . . . . . . . . . . . . . . . . . . . 55
4.5.4 Severity-Area-Frequency (SAF) Curves . . . . . . . . . . . . . 56
4.5.5 Timescale of Indices . . . . . . . . . . . . . . . . . . . . . . . 57
4.6 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.6.1 SPI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.6.2 SPEI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.7 Summary and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 69
5 Applicability of Standardized Precipitation Index for monitoring ground-
water conditions in the lower ACF River Basin . . . . . . . . . . . . . . 71
5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
5.3 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
5.4 Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
5.5 Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.5.1 Standardized Precipitation Index . . . . . . . . . . . . . . . . 76
5.5.2 Pearson’s Correlation . . . . . . . . . . . . . . . . . . . . . . . 77
5.6 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 77
5.7 Summary and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 92
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6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
6.1 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . 93
6.1.1 Objective 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
6.1.2 Objective 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
6.1.3 Objective 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
7 Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
A Standardized Precipitation Index . . . . . . . . . . . . . . . . . . . . . . 111
A.1 Stepwise procedure to calculate the SPI . . . . . . . . . . . . . . . . . 111
B Standardized Precipitation Evapotranspiration Index . . . . . . . . . . . 113
B.1 Stepwise procedure to calculate the SPEI . . . . . . . . . . . . . . . . 113
C Potential Evapotranspiration . . . . . . . . . . . . . . . . . . . . . . . . 115
C.1 Thornthwaite Method to compute PET . . . . . . . . . . . . . . . . . 115
D Probability Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
D.1 Gamma Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
D.1.1 Probability Density Function . . . . . . . . . . . . . . . . . . 116
D.1.2 Cumulative Distribution Function . . . . . . . . . . . . . . . . 117
D.2 Three Parameter Log-logistic Distribution . . . . . . . . . . . . . . . 118
D.2.1 Probability Density Function . . . . . . . . . . . . . . . . . . 118
D.2.2 Cumulative Distribution Function . . . . . . . . . . . . . . . . 119
D.3 Extreme Value Type-I Distribution . . . . . . . . . . . . . . . . . . . 119
D.3.1 Probability Density Function . . . . . . . . . . . . . . . . . . 119
D.3.2 Cumulative Distribution Function . . . . . . . . . . . . . . . . 120
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List of Figures
2.1 Pathways through which water circles the earth. . . . . . . . . . . . . . . 6
2.2 Surface warming projections according to different emission scenarios. . . 18
3.1 The average annual rainfall in Alabama. . . . . . . . . . . . . . . . . . . 27
3.2 The average annual temperature in Alabama. . . . . . . . . . . . . . . . 28
3.3 TotalnumberofdifferentkindofdroughtincidencesaccordingtoSPIfrom
CCSM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.4 SAF curves for droughts with different recurrence intervals during histor-
ical and future periods (SPI from CCSM). . . . . . . . . . . . . . . . . . 35
3.5 TotalnumberofdifferentkindofdroughtincidencesaccordingtoSPIfrom
GFDL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.6 SAF curves for droughts with different recurrence intervals during histor-
ical and future periods (SPI from GFDL). . . . . . . . . . . . . . . . . . 37
3.7 TotalnumberofdifferentkindofdroughtincidencesaccordingtoSPIfrom
HadCM3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.8 SAF curves for droughts with different recurrence intervals during histor-
ical and future periods (SPI from HadCM3). . . . . . . . . . . . . . . . . 39
3.9 Total number of different kind of drought incidences according to SPEI
from CCSM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
x