an integrative decision support system for managing water resources under increased climate...
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Institute of Water Research
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An Integrative Decision Support System for Managing Water Resources Under Increased
Climate Variability
USDA AFRI and NIWQP Project Directors Meeting10/13/2016
Washington D.C.
Glenn O’NeilInstitute of Water Research
Michigan State University
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Collaborators
Jon BartholicJames DuncanJeremiah AsherLois WolfsonJason Piwarski
Phanikumar ManthaQiu Han
Stephen GasteyerJennifer Lai
$
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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.
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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)
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Study Area
Kalamazoo RiverWatershed
Prairie View RiverWatershed
MI
OHIN
LakeMichigan
LakeHuron
LakeErie
Flint
Detroit
Toledo
Lansing
GrandRapids
Ft. Wayne
Gary
KalamazooBattle Creek
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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
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Model Development
Inputs
Land cover/rotations (CDL)Soils (SSURGO)Daily weather (NCDC)Topography (USGS)Streams (NHD)Water use (State of Michigan)
Outputs
StreamflowGroundwater rechargeEvapotranspiration (ET)Soil moistureWater table depth (PAWS only)
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Model Calibration and Validation
Models were primarily evaluated against observed streamflow in USGS gages
SWAT
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Model Calibration and Validation
Models were primarily evaluated against observed streamflow in USGS gages
PAWS
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Model Calibration and Validation
… but also against
ET
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Model Calibration and Validation
… but also against
Depth to thewater table(PAWS Only) →
Crop yields
Irrigation rates
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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)
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Future Climate Projections
2010-2019
2020-2029
2030-2039
2040-2049
2050-2059
2060-2069
2070-2079
2080-2089
2090-2099
700
750
800
850
900
950
1000
1050
1100
1150
1200
Average Annual Precipitation
CCSM3-A1FiCCSM3-B1HadCM3-A1FiHadCM3-B1
decades
mm
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Future Climate Projections
2010-2019
2020-2029
2030-2039
2040-2049
2050-2059
2060-2069
2070-2079
2080-2089
2090-2099
4
6
8
10
12
14
16
18
Average Annual Temperature
CCSM3-A1FiCCSM3-B1HadCM3-A1FiHadCM3-B1
decades
Degr
ees C
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Future Hydrology
2020-2029
2030-2039
2040-2049
2050-2059
2060-2069
2070-2079
2080-2089
2090-2099
150
200
250
300
350
400
450
500
550
600
650
PRW - Groundwater Recharge
PAWS BaselinePAWS CCSM-A1FiPAWS CCSM-B1PAWS HadCM3-A1FiPAWS HadCM3-B1SWAT BaselineSWAT CCSM-A1FI NO WGN MODSWAT CCSM-B1 NO WGN MODSWAT HadCM3-A1Fi NO WGN MODSWAT HadCM3-B1 NO WGN MOD
decades
mm
/yr
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Future Hydrology
2020-2029
2030-2039
2040-2049
2050-2059
2060-2069
2070-2079
2080-2089
2090-2099
450
500
550
600
650
700
750
PRW - Evapotranspiration
PAWS BaselinePAWS CCSM-A1FiPAWS CCSM-B1PAWS HadCM3-A1FiPAWS HadCM3-B1SWAT BaselineSWAT CCSM3-A1Fi NO WGN MODSWAT CCSM3-B1 NO WGN MODSWAT HadCM3-A1Fi NO WGN MODSWAT HadCM3-B1 NO WGN MOD
decades
mm
/yr
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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)
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Model Differences
Why the difference?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
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Static CO2
2010-2019 2020-2029 2030-2039 2040-2049 2050-2059 2060-2069 2070-2079 2080-2089 2090-2099500
550
600
650
700
750
800
850
PRW - Evapotranspiration
SWAT CCSM3-A1FiSWAT CCSM3-B1SWAT HadCM3-A1FiSWAT HadCM3-B1
decades
mm
/yr
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Static CO2
2010-2019 2020-2029 2030-2039 2040-2049 2050-2059 2060-2069 2070-2079 2080-2089 2090-20990
100
200
300
400
500
600
PRW - Groundwater Recharge
SWAT CCSM3-A1FiSWAT CCSM3-B1SWAT HadCM3-A1FiSWAT HadCM3-B1
decades
mm
/yr
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Stakeholder Engagement
– Interviews• conservation organization staff• municipal and elected officials• county farm bureau• farmers• planners• crop advisors• utility operators
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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
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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?”
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Online DSS
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Online DSS
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Online DSS
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Takeaways
– High uncertainty between hydrologic and climate models
– We have to acknowledge and effectively communicate this uncertainty to stakeholders
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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
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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
(Pritchard, Rogers, Prior, & Peterson, 1999; Saxe, Ellsworth, & Heath, 1998; Wand, Midgley, Jones, & Curtis, 1999; Andrew D. B. Leakey et al., 2009)