1. Institute of Water Research1
An Integrative Decision Support System for
Managing Water Resources Under Increased
Climate Variability
USDA AFRI and NIWQP Project Directors Meeting
10/13/2016
Washington D.C.
Glenn O’Neil
Institute of Water Research
Michigan State University

2. Institute of Water Research
Collaborators
2
Jon Bartholic
James Duncan
Jeremiah Asher
Lois Wolfson
Jason Piwarski
Phanikumar Mantha
Qiu Han
Stephen Gasteyer
Jennifer Lai
$

3. Institute of Water Research
Context
Southwest Michigan is one of the most agriculturally
productive areas within the Great Lakes basin.
It is also one the most heavily irrigated; therefore, the
sustainability of its water resources will be of critical
importance in meeting future food demand.
3

4. Institute of Water Research
Project Objectives
• Hydrologic model development in SW MI
• Potential impacts of future climate
• Engagement of local stakeholders
• Development of an online decision support
system (DSS)
4

5. Institute of Water Research
Study Area
5
Kalamazoo River
Watershed
Prairie View River
Watershed
MI
OH
IN
Lake
Michigan
Lake
Huron
Lake
Erie
Flint
Detroit
Toledo
Lansing
Grand
Rapids
Ft. Wayne
Gary
Kalamazoo
Battle Creek

6. Institute of Water Research
Hydrologic Models
1. Soil and Water Assessment Tool (SWAT)
- watershed-based
- daily time-step
- broadly-utilized
2. Process-based Adaptive Watershed Simulator
(PAWS)
- grid-cell based
- daily time-step
- detailed representation of sub-surface hydrology
6

7. Institute of Water Research
Model Development
Inputs
Land cover/rotations (CDL)
Soils (SSURGO)
Daily weather (NCDC)
Topography (USGS)
Streams (NHD)
Water use (State of Michigan)
Outputs
Streamflow
Groundwater recharge
Evapotranspiration (ET)
Soil moisture
Water table depth (PAWS only)
7

8. Institute of Water Research
Model Calibration and Validation
Models were primarily evaluated against observed
streamflow in USGS gages
8
SWAT

9. Institute of Water Research
Model Calibration and Validation
Models were primarily evaluated against observed
streamflow in USGS gages
9
PAWS

10. Institute of Water Research
Model Calibration and Validation
… but also against
ET
10

11. Institute of Water Research
Model Calibration and Validation
… but also against
Depth to the
water table
(PAWS Only) →
Crop yields
Irrigation rates
11

12. Institute of Water Research
Future Climate Projections
Models were run forward to 2100 with future
climate data from Hayhoe et al. (2013).
4 scenarios
- 2 climate models (from CMIP 3)
1. UK Meteorological Office Hadley Centre (HadCM3)
2. National Center for Atmospheric Research, USA (CCSM3)
- 2 CO2 emission scenarios (from IPCC)
1. B1 – best case (549 ppm by 2100)
2. A1Fi – worst case (970 ppm by 2100)
12

13. Institute of Water Research
Future Climate Projections
13
700
750
800
850
900
950
1000
1050
1100
1150
1200
mm
decades
Average Annual Precipitation
CCSM3-A1Fi
CCSM3-B1
HadCM3-A1Fi
HadCM3-B1

14. Institute of Water Research
Future Climate Projections
14
4
6
8
10
12
14
16
18
DegreesC
decades
Average Annual Temperature
CCSM3-A1Fi
CCSM3-B1
HadCM3-A1Fi
HadCM3-B1

15. Institute of Water Research
Future Hydrology
15
150
200
250
300
350
400
450
500
550
600
650
2020-2029 2030-2039 2040-2049 2050-2059 2060-2069 2070-2079 2080-2089 2090-2099
mm/yr
decades
PRW - Groundwater Recharge
PAWS Baseline
PAWS CCSM-A1Fi
PAWS CCSM-B1
PAWS HadCM3-A1Fi
PAWS HadCM3-B1
SWAT Baseline
SWAT CCSM-A1FI NO WGN MOD
SWAT CCSM-B1 NO WGN MOD
SWAT HadCM3-A1Fi NO WGN MOD
SWAT HadCM3-B1 NO WGN MOD

16. Institute of Water Research
Future Hydrology
16
450
500
550
600
650
700
750
2020-2029 2030-2039 2040-2049 2050-2059 2060-2069 2070-2079 2080-2089 2090-2099
mm/yr
decades
PRW - Evapotranspiration
PAWS Baseline
PAWS CCSM-A1Fi
PAWS CCSM-B1
PAWS HadCM3-A1Fi
PAWS HadCM3-B1
SWAT Baseline
SWAT CCSM3-A1Fi NO WGN MOD
SWAT CCSM3-B1 NO WGN MOD
SWAT HadCM3-A1Fi NO WGN MOD
SWAT HadCM3-B1 NO WGN MOD

17. Institute of Water Research
Model Differences
Why the difference?
– Improvement in plant water use efficiency at
elevated CO2 concentration
(Pritchard, Rogers, Prior, & Peterson, 1999; Saxe, Ellsworth, & Heath, 1998;
Wand, Midgley, Jones, & Curtis, 1999; Andrew D. B. Leakey et al., 2009)
– Less ET = more recharge
– SWAT documentation cites a doubling of CO2 from 330
ppm to 660 ppm leads to a 40% reduction in leaf
conductance (Morrison 1987)
17

18. Institute of Water Research
Model Differences
Why the difference?
18
Year
CO2 Concentrations (ppm)
A1FI B1
2010 389 388
2020 417 412
2030 455 437
2040 504 463
2050 567 488
2060 638 509
2070 716 525
2080 799 537
2090 885 545
2100 970 549
Source: IPCC

19. Institute of Water Research
Static CO2
19
500
550
600
650
700
750
800
850
2010-2019 2020-2029 2030-2039 2040-2049 2050-2059 2060-2069 2070-2079 2080-2089 2090-2099
mm/yr
decades
PRW - Evapotranspiration
SWAT CCSM3-A1Fi
SWAT CCSM3-B1
SWAT HadCM3-A1Fi
SWAT HadCM3-B1

20. Institute of Water Research
Static CO2
20
0
100
200
300
400
500
600
2010-2019 2020-2029 2030-2039 2040-2049 2050-2059 2060-2069 2070-2079 2080-2089 2090-2099
mm/yr
decades
PRW - Groundwater Recharge
SWAT CCSM3-A1Fi
SWAT CCSM3-B1
SWAT HadCM3-A1Fi
SWAT HadCM3-B1

21. Institute of Water Research
Stakeholder Engagement
– Interviews
• conservation organization staff
• municipal and elected officials
• county farm bureau
• farmers
• planners
• crop advisors
• utility operators
21

22. Institute of Water Research
Stakeholder Engagement
– Different views of farmers toward water and
water management than among many at the
modeling and policy level
– Local knowledge must be better utilized by
modelers
– Farmers have less freedom to conserve because
of dominance of corporate contracting in farming
22

23. Institute of Water Research
Stakeholder Engagement
– Interviews also provided feedback on the design
of the DSS
– Conflicting model results make buy-in difficult
– “They can’t predict the weather on Thursday, why
should I believe projections for 2080?”
23

24. Institute of Water Research
Online DSS
24

25. Institute of Water Research
Online DSS
25

26. Institute of Water Research
Online DSS
26

27. Institute of Water Research
Takeaways
– High uncertainty between hydrologic and climate
models
– We have to acknowledge and effectively
communicate this uncertainty to stakeholders
27

28. Institute of Water Research
Outputs
– Paper in review on SWAT outputs
– Paper in progress on SWAT-PAWS differences
– 3 papers from interviews with stakeholders
• Gasteyer, S., J. Lai. Convening Irrigators: Large Quantity Water Use Regulation in Michigan.
Regulations and Governance.
• Gasteyer, S. Irrigating Lakeland: Sociotechnical Imaginaries and Groundwater Management in
Michigan. Social Studies of Science
• Lai, J. and S. Gasteyer. The battle over creeks: water translations in Southwest Michigan.
Rural Sociology
– On-line DSS (on hold)
– Supported 3 graduate students
28

29. Institute of Water Research
References
Hayhoe, K., Stoner, A., Yang, X., Crow, C., Swaminathan, R., Scott-Fleming, I., … Swain, S. (2013). Development and
Dissemination of a High-Resolution National Climate Change Dataset (Final Report for the United States Geological
Survey No. G10AC00582) (p. 497). USGS.
Leakey, A. D. B., Ainsworth, E. A., Bernacchi, C. J., Rogers, A., Long, S. P., & Ort, D. R. (2009). Elevated CO2 effects on plant
carbon, nitrogen, and water relations: six important lessons from FACE. Journal of Experimental Botany, 60(10), 2859–
2876. http://doi.org/10.1093/jxb/erp096
Morrison, J. I. . (1987). Intercellular CO2 concentration and stomatal response to CO2. In E.Seiger, G.D Farquhar and I.R.
Cowan (ed.) Stomatal Function (pp. 229–251). Stanford University Press.
Pritchard, S. G., Rogers, H. H., Prior, S. A., & Peterson, C. M. (1999). Elevated CO2 and plant structure: a review. Global
Change Biology, 5(7), 807–837. http://doi.org/10.1046/j.1365-2486.1999.00268.x
Saxe, H., Ellsworth, D. S., & Heath, J. (1998). Tree and forest functioning in an enriched CO2 atmosphere. New Phytologist,
139(3), 395–436. http://doi.org/10.1046/j.1469-8137.1998.00221.x
Wand, S. J. E., Midgley, G. F., Jones, M. H., & Curtis, P. S. (1999). Responses of wild C4 and C3 grass (Poaceae) species to
elevated atmospheric CO2 concentration: a meta-analytic test of current theories and perceptions. Global Change
Biology, 5(6), 723–741. http://doi.org/10.1046/j.1365-2486.1999.00265.x
29