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K I M B E R L Y L Y O N S , M A S T E R ’ S S T U D E N T
U N I V E R S I T Y O F S O U T H F L O R I D A S T .
P E T E R S B U R G
Evaluating the effects of precipitation
extremes on watershed hydrology under
current and projected future climate
conditions using SWAT
Introduction
 “Water, water everywhere,
but not a drop to drink.” -
The Rime of the Ancient Mariner, Samuel
Taylor Coleridge
Figure 1: Diagram of earth’s waters.
http://water.usgs.gov/edu/watercyclehi.html
Figure 2: Safelight view of Earth
Figure 3: Image of CA water crisis http://www.latinoreport.com/dam-our-
childrens-future-full-stadiums-ahead/
Introduction
 High demand for this
limited resource
 Demand will continue to
increase
Figure 4: Map of projected water scarcity. http://www.unep.org/dewa/vitalwater/article141.html
Figure 5: Diagram of the effects of population growth on water resources.
http://na.unep.net/geas/getuneppagewitharticleidscript.php?article_id=76
Introduction
 Managing current water resources and planning for future
generations is critical
Geoscience
Figure 6: Image of the ideology behind IWRM.
http://www.watercentre.org/news/integrated-water-management-2013-
the-way-of-the-future
Introduction
 Catchment Process: Precipitation
 Spatially and Temporally Variable
 High Intensity
 Infiltration Runoff  Discharge
Figure 7: Image of the framework for utilizing all precipitation
sources. http://wcel.org/integrated-stormwater-management
Figure 8 and 9: Images illustrating differences of precipitation
intensity and quantity on water supplies.
 Water Supply
 Quantity and Quality
 GW Recharge
 Capture/Storage
 Treatment
 Alternative
Management
Introduction
 Climate Change
 Frequency of high intensity precipitation has and will
continue to increase
 Global: Increase frequency of the upper 0.3% of daily precipitation
 US: 40% increases in the frequency >6in/day [5]
 Future Projected: The intensity of precipitation events will likely
increase on average [4]
Figure 10: Image of the frequency, distribution and magnitude of projected extreme events. https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch10s10-3-6-1.html
Introduction
 Therefore, planners and managers should
consider the effects of precipitation quantity
and intensity under current and future
climate projections
 Current climate surface water quantity
estimations could facilitate best management
practices (BMPs)
 Future climate surface water quantity projections
should result in more sustainable planning and
development
Extensive research on
watershed scale
hydrology using GIS ,
Historical Date and
Hydrologic Models
Far less research using
Future Projected
Climate Data and
Hydrologic Models
Introduction
Figure 11: Illustration of the steps required to
complete a climate impact
study.http://climate4im/impactportal/help/faq.jsp?q=scenarios
Figure 12: Illustration of the downscaling
processes that is required to for local watershed scale
hydrologic modeling.
Research Objectives
 This research utilizes the Soil and Water Assessment
Tool (SWAT) to evaluate the effects of precipitation
extremes on watershed hydrology in the Cobb Creek
Watershed, GA, USA under current and future
climate conditions projected by the Canadian Centre
for Climate Modeling and Analysis Coupled General
Circulation Model, CCCMA CGCM3.1, and the
Geophysical Fluids Dynamic Laboratory Coupled
Model, GFDL CM2.1.
Methodology: Research Area
 Cobb Creek
 Southeastern Georgia
 Headwaters of the Altahmaha
 Oconee and Ocmulgee
 HUC 10 Sub-basin
 892 km2
 Land use
 Forested: 50.7 %
 Row crops: 21.7%
 Wooded wetlands: 10.1%
 Pasture: 6.1%
 Soils
 Loam and Alluvium
 Elevation
 Minimum: 19m
 Maximum: 103m
 Impairments
 USEPA 305(b) and 303(d) lists
 Fecal Coliform
 Dissolved oxygen
Figure 13: Real-estate
photos showing land
uses in Cobb Creek
http://www.ghland.com/listing
/toombs-county-ga
Figure 14; The Cobb
Creek Watershed
Methodology:
SWAT Model
 USDA Model
 Two tiered
desegregation
scheme
 Semi distributed
 Continuous time
step
 Physical/ Physics
based
Figure 15: Conceptual Framework of SWAT Model
Figure 16:SWAT Model Calibration and Validation
Results
Methodology: Precipitation Inputs
 Current
 2010-2014
 NOAA Climatic Database
 Site/ Point Data
 Future
 2060- 2064
 Models
 CCCMA CGCM3.1
 GFDL CM2.1
 A1B Scenario
 Grid to Site Data
 Reduce natural variably 5yrs was used to represent each
time interval [5]
 High intensity: Top 10% of daily watershed precipitation
events
Figure 17: IPCC emissions
scenarios [4}
Results: The Big Picture
Results: The Big Picture
Results: The Top 10%
 Discharge Increases
 Total Flow
 CCMA: 38%
 GFDL: 47%
 Max Flows
 CCMA: 26%
 GFDL: 20%
 Precipitation
 Current: 8.6mm/day-
99.6mm/day
 CCMA: 12.1mm/day-
92.5mm/day
 GFDL: 11.6mm/day-
86.8mm/day
Results: The Top 10%
 Changes in
Temporal
Distribution
Conclusion
 The amount of watershed discharge from the top
10% of daily precipitation event could increase by
nearly 50% in the next 50 years
 Max flows increasing by almost 30%
 Consecutive high flow days and temperature could have also
had a large influence on flow magnitude
 Decrease in summer high flows could be detrimental
to agriculture and aquatic habits
 Slight shifts in the timing of seasonal rain could be indicative
of future large scale seasonal shifts
 Obvious differences in climate model projections
 Grain of salt
 Objective eye
References
1. Brady, N. C. & Weil, R. R. (2008) Nature and Properties of Soil. Pearson.
2. Fu et al. 2000. The relationships between landuse and soil conditions in the hilly area of the Loess Plateay in northern Shaanxi,
China. Catena. 39: 69-78.
3. Dourte, D. R., Fraisse, C., & Bartels, W. (2015). Exploring changes in rainfall intensity and seasonal variability in the southeastern
U.S.: Stakeholder engagement, observations, and adaptation. Climate Risk Management, 7, 11-19
4. IPCC. (2013). Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report
of the Intergovernmental Panel on Climate Change. Stocker, T.F., D. Qin, G.-K. Plattner, M.
5. Maraun, D., Widmann, M., Gutiérrez, J., Kotlarski, S., Chandler, R., Hertig, E., & Wilcke, R. (2015). VALUE: A framework to
validate downscaling approaches for climate change studies. Earth's Future, 3(1), 1.
6. Mukundan, R., Pradhanang, S., Schneiderman, E., Pierson, D., Anandhi, A., Zion, M., & Steenhuis, T. (2013). Suspended sediment
source areas and future climate impact on soil erosion and sediment yield in a New York City water supply watershed, USA.
Geomorphology, 183, 110-119.
7. PRISM Climate Group. (2012). Oregon State University. Data retrieved from http://www.prism.oregonstate.edu
8. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex & P.M. Midgley (eds.) Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA, 1535 pp.
9. Teutschbein, C., Wetterhall, F., & Seibert, J. (2011). Evaluation of different downscaling techniques for hydrological climate-
change impact studies at the catchment scale. Climate Dynamics, 37(9), 2087-2105.
10. USDA-NRCS. (2000). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss
Equation (RUSLE). Agricultural Handbook. 703. USDA: National Resource Conservation Service.
11. USDA-NRCS. (2002). National Hydrography Dataset. USDA: National Resources Conservation Service. Data retrieved from
https://gdg.sc.egov.usda.gov.
12. USDA-NRCS. 2006a. National Elevation database. National Resources Conservation Service. Data retrieved from
https://gdg.sc.egov.usda.gov.
13. USDA-NRCS. 2006b. Soil Survey Geographic (SSURGO) database. National Resources Conservation Service. Data retrieved from
https://gdg.sc.egov.usda.gov.
14. USDA-NRCS. 2014. National Landuse and Land Cover database. USDA: National Resource Conservation Service. Data retrieved
from https://gdg.sc.egov.usda.gov.
Acknowledgements
 USF
Environmental
Science and Policy
Program
 Dr. Barnali Dixon
and the Geospatial
Analytics Lab
 My loving family
and dear friends
Lyons_AAG_16

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Lyons_AAG_16

  • 1. K I M B E R L Y L Y O N S , M A S T E R ’ S S T U D E N T U N I V E R S I T Y O F S O U T H F L O R I D A S T . P E T E R S B U R G Evaluating the effects of precipitation extremes on watershed hydrology under current and projected future climate conditions using SWAT
  • 2. Introduction  “Water, water everywhere, but not a drop to drink.” - The Rime of the Ancient Mariner, Samuel Taylor Coleridge Figure 1: Diagram of earth’s waters. http://water.usgs.gov/edu/watercyclehi.html Figure 2: Safelight view of Earth Figure 3: Image of CA water crisis http://www.latinoreport.com/dam-our- childrens-future-full-stadiums-ahead/
  • 3. Introduction  High demand for this limited resource  Demand will continue to increase Figure 4: Map of projected water scarcity. http://www.unep.org/dewa/vitalwater/article141.html Figure 5: Diagram of the effects of population growth on water resources. http://na.unep.net/geas/getuneppagewitharticleidscript.php?article_id=76
  • 4. Introduction  Managing current water resources and planning for future generations is critical Geoscience Figure 6: Image of the ideology behind IWRM. http://www.watercentre.org/news/integrated-water-management-2013- the-way-of-the-future
  • 5. Introduction  Catchment Process: Precipitation  Spatially and Temporally Variable  High Intensity  Infiltration Runoff  Discharge Figure 7: Image of the framework for utilizing all precipitation sources. http://wcel.org/integrated-stormwater-management Figure 8 and 9: Images illustrating differences of precipitation intensity and quantity on water supplies.  Water Supply  Quantity and Quality  GW Recharge  Capture/Storage  Treatment  Alternative Management
  • 6. Introduction  Climate Change  Frequency of high intensity precipitation has and will continue to increase  Global: Increase frequency of the upper 0.3% of daily precipitation  US: 40% increases in the frequency >6in/day [5]  Future Projected: The intensity of precipitation events will likely increase on average [4] Figure 10: Image of the frequency, distribution and magnitude of projected extreme events. https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch10s10-3-6-1.html
  • 7. Introduction  Therefore, planners and managers should consider the effects of precipitation quantity and intensity under current and future climate projections  Current climate surface water quantity estimations could facilitate best management practices (BMPs)  Future climate surface water quantity projections should result in more sustainable planning and development Extensive research on watershed scale hydrology using GIS , Historical Date and Hydrologic Models Far less research using Future Projected Climate Data and Hydrologic Models
  • 8. Introduction Figure 11: Illustration of the steps required to complete a climate impact study.http://climate4im/impactportal/help/faq.jsp?q=scenarios Figure 12: Illustration of the downscaling processes that is required to for local watershed scale hydrologic modeling.
  • 9. Research Objectives  This research utilizes the Soil and Water Assessment Tool (SWAT) to evaluate the effects of precipitation extremes on watershed hydrology in the Cobb Creek Watershed, GA, USA under current and future climate conditions projected by the Canadian Centre for Climate Modeling and Analysis Coupled General Circulation Model, CCCMA CGCM3.1, and the Geophysical Fluids Dynamic Laboratory Coupled Model, GFDL CM2.1.
  • 10. Methodology: Research Area  Cobb Creek  Southeastern Georgia  Headwaters of the Altahmaha  Oconee and Ocmulgee  HUC 10 Sub-basin  892 km2  Land use  Forested: 50.7 %  Row crops: 21.7%  Wooded wetlands: 10.1%  Pasture: 6.1%  Soils  Loam and Alluvium  Elevation  Minimum: 19m  Maximum: 103m  Impairments  USEPA 305(b) and 303(d) lists  Fecal Coliform  Dissolved oxygen Figure 13: Real-estate photos showing land uses in Cobb Creek http://www.ghland.com/listing /toombs-county-ga Figure 14; The Cobb Creek Watershed
  • 11. Methodology: SWAT Model  USDA Model  Two tiered desegregation scheme  Semi distributed  Continuous time step  Physical/ Physics based Figure 15: Conceptual Framework of SWAT Model Figure 16:SWAT Model Calibration and Validation Results
  • 12. Methodology: Precipitation Inputs  Current  2010-2014  NOAA Climatic Database  Site/ Point Data  Future  2060- 2064  Models  CCCMA CGCM3.1  GFDL CM2.1  A1B Scenario  Grid to Site Data  Reduce natural variably 5yrs was used to represent each time interval [5]  High intensity: Top 10% of daily watershed precipitation events Figure 17: IPCC emissions scenarios [4}
  • 13. Results: The Big Picture
  • 14. Results: The Big Picture
  • 15. Results: The Top 10%  Discharge Increases  Total Flow  CCMA: 38%  GFDL: 47%  Max Flows  CCMA: 26%  GFDL: 20%  Precipitation  Current: 8.6mm/day- 99.6mm/day  CCMA: 12.1mm/day- 92.5mm/day  GFDL: 11.6mm/day- 86.8mm/day
  • 16. Results: The Top 10%  Changes in Temporal Distribution
  • 17. Conclusion  The amount of watershed discharge from the top 10% of daily precipitation event could increase by nearly 50% in the next 50 years  Max flows increasing by almost 30%  Consecutive high flow days and temperature could have also had a large influence on flow magnitude  Decrease in summer high flows could be detrimental to agriculture and aquatic habits  Slight shifts in the timing of seasonal rain could be indicative of future large scale seasonal shifts  Obvious differences in climate model projections  Grain of salt  Objective eye
  • 18. References 1. Brady, N. C. & Weil, R. R. (2008) Nature and Properties of Soil. Pearson. 2. Fu et al. 2000. The relationships between landuse and soil conditions in the hilly area of the Loess Plateay in northern Shaanxi, China. Catena. 39: 69-78. 3. Dourte, D. R., Fraisse, C., & Bartels, W. (2015). Exploring changes in rainfall intensity and seasonal variability in the southeastern U.S.: Stakeholder engagement, observations, and adaptation. Climate Risk Management, 7, 11-19 4. IPCC. (2013). Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker, T.F., D. Qin, G.-K. Plattner, M. 5. Maraun, D., Widmann, M., Gutiérrez, J., Kotlarski, S., Chandler, R., Hertig, E., & Wilcke, R. (2015). VALUE: A framework to validate downscaling approaches for climate change studies. Earth's Future, 3(1), 1. 6. Mukundan, R., Pradhanang, S., Schneiderman, E., Pierson, D., Anandhi, A., Zion, M., & Steenhuis, T. (2013). Suspended sediment source areas and future climate impact on soil erosion and sediment yield in a New York City water supply watershed, USA. Geomorphology, 183, 110-119. 7. PRISM Climate Group. (2012). Oregon State University. Data retrieved from http://www.prism.oregonstate.edu 8. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex & P.M. Midgley (eds.) Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp. 9. Teutschbein, C., Wetterhall, F., & Seibert, J. (2011). Evaluation of different downscaling techniques for hydrological climate- change impact studies at the catchment scale. Climate Dynamics, 37(9), 2087-2105. 10. USDA-NRCS. (2000). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agricultural Handbook. 703. USDA: National Resource Conservation Service. 11. USDA-NRCS. (2002). National Hydrography Dataset. USDA: National Resources Conservation Service. Data retrieved from https://gdg.sc.egov.usda.gov. 12. USDA-NRCS. 2006a. National Elevation database. National Resources Conservation Service. Data retrieved from https://gdg.sc.egov.usda.gov. 13. USDA-NRCS. 2006b. Soil Survey Geographic (SSURGO) database. National Resources Conservation Service. Data retrieved from https://gdg.sc.egov.usda.gov. 14. USDA-NRCS. 2014. National Landuse and Land Cover database. USDA: National Resource Conservation Service. Data retrieved from https://gdg.sc.egov.usda.gov.
  • 19. Acknowledgements  USF Environmental Science and Policy Program  Dr. Barnali Dixon and the Geospatial Analytics Lab  My loving family and dear friends