An Integrative Decision Support System for Managing Water Resources under Increased Climate Variability

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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Models were primarily evaluated against observed streamflow in USGS gages

PAWS


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… but also against

ET


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… 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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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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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

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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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– 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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– 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)

An Integrative Decision Support System for Managing Water Resources under Increased Climate Variability

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