This document summarizes a research project on sustaining agriculture through adaptive management of the Ogallala Aquifer under climate change. The project has over 40 researchers from 8 institutions studying the Ogallala Aquifer region. The Nebraska team includes the director of the Nebraska Water Center and researchers studying irrigation, soils, crops, and economics. The project's objectives are to integrate models to evaluate scenarios, identify efficient irrigation technologies and practices, analyze policies to encourage adoption, and effectively communicate results. Studies include evaluating deficit irrigation, sensor technologies, variable rate fertigation, and engaging producers. Over 50 papers have been published and many extension efforts have reached thousands regarding sustainable water management.

1. Research/Extension
Project
NebraskaWaterCenterRetreat
Kearney,NE
March4,2019
DaranR.Rudnick,Ph.D.
AssistantProfessor:IrrigationSpecialist
DepartmentofBiologicalSystemsEngineering
WestCentralResearchandExtension Center
UniversityofNebraska-Lincoln
Phone:(308)696-6709,Email:daran.rudnick@unl.edu

2. Acknowledgement
Project Title:
• Sustaining agriculture through adaptive management to preserve the Ogallala
aquifer under a changing climate
Project Sponsorship:
• National Institute of Food and Agriculture, U.S. Department of Agriculture (USDA-NIFA)
under award numbers 2016-68007-25066.
• Daugherty Water for Food Global Institute graduate student support.

3. Project Overview
• Amount: $10 Million
• Duration: 2016-2020
• Researchers: > 40
• Institutions
• Colorado State University
• Kansas State University
• Oklahoma State University
• Texas A&M University
• West Texas A&M University
• University of Nebraska-Lincoln
• New Mexico State University
• Texas Tech University
• USDA-ARS
Source: Amy Kremen

4. Nebraska Team
• Chittaranjan Ray – Director of NE Water Center
• Karina Schoengold – Ag Economist
• Daran Rudnick – Irrigation Specialist
• Tim Shaver – Soil Nutrient Specialist
• Erin Hacker – NE Water Center Post-Doc
• Vaishali Sharda – NE Water Center Post-Doc
• Himmy Lo – PhD Graduate Student/ Post Doc

5. Primary Objectives:
1. Integrate Hydrologic, crop, soil, and climate models and databases to
provide baseline data for evaluating management and policy scenarios.
2. Develop and identify the best irrigation technologies, cropping system
management practices, and decision support tools to improve water use
efficiency.
3. Analyze current social, policy, and economic frameworks in the Ogallala
aquifer region (OAR) and identify incentives and policies to increase the
adoption of adaptive strategies.
4. Enable the adoption of tools and recommended strategies for improved
water use through highly integrated and effective communication among
the project team and technology transfer with stakeholders.

6. Sub-Objectives:
1.1 – Compile & develop hydrologic models & databases for the OAR
1.2 – Calibration & validation of DSSAT
1.3 – Identify environmental factors driving variability in crop yields using historical climate datasets
1.4 – Quantify climate change scenario impacts on crop, soil, & water management
2.1 – Develop/identify new precision irrigation technologies that improve WUE & have potential for adoption
2.2 – Develop user friendly irrigation scheduling tools
2.3 – Quantify water-production functions & best management practices under limited irrigation
2.4 – Quantify the impact of soil management practices on ecosystem resilience
3.1 – Develop a local agricultural decision model to predict water use decisions amongst agricultural producers
3.2 – Integrate hydrologic groundwater models with the local economic agricultural decision models
3.3 – Predict regional income & employment impacts of the economy under different policy & climate scenarios
3.4 – Identify the social values & beliefs driving on-farm decisions about natural resource use & adaptive management
4.1 – Facilitate integration of models for the adoption of sustainable management strategies for the OAR
4.2 – Interpret research results & promote appropriate adoption of irrigation technologies, cropping system
management practices, & decision support tools to improve water use efficiency
4.3 – Summarize & communicate results of analyses of social, policy, & economic frameworks & interpret incentives &
policies to increase the adoption of adaptive strategies
4.4. – Integrate extension/technology transfer to increase impact, efficiency, & audience acceptance

7. Integrated model calibration, validation & implementation:
Initial tests complete for test area region of Finney Co, KS;
Team is testing crop/economic scenarios in 5 study area across the Ogallala region.
Field research underway spans dryland to fully irrigated systems:
Each area of our work is being conducted across a minimum of three states,
enabling us to draw broader conclusions about their potential.
Ogallala-wide survey of irrigators: analysis & sharing of initial findings
Farmers say: conserving groundwater is important (drought resilience + value of
water for future generations & communities). However: they aren’t sure how
they can conserve more water than they already do.
This past project year, the Ogallala Water CAP team presented at and/or
helped organize well over 150 events directly reaching at least 5000 people
across the Ogallala region, the U.S. and internationally.

8. ~55 published peer-reviewed journal articles
~17 other reports and fact sheets.
Many more coming: (incl. JAWRA, Ag. Water Mgmt, Irrig Science issues)
• Magazines and other reports intended for a non-academic audience are
reaching 1000s through print & digital distribution.
• Social media reach: >900 followers.

9. My Role
Sub-Objectives:
• 2.1, 2.3, 4.2, and 4.4
Studies/Projects
• Deficit irrigation review
• Sensor technology
assessment
• Variable rate fertigation
• Grower input management
evaluation
• Producer engagement
WCREC Irrigation Research Team (2018)

10. Deficit Irrigation Review
Nebraska:
• Clay Center: Irmak (2015a,b) & Rudnick et al. (2016)
• North Platte: Payero et al. (2008, 2009) & van Donk et al. (2012)
• Scottsbluff: Spurgeon and Yonts (2013)
Colorado:
• Akron: Benjamin et al. (2015) & Schneekloth et al. (2012)
• Yuma: Al-Kaisi and Yin (2003)
Kansas:
• Colby: Lamm et al. (1995, 2014)
• Tribune: Schlegel et al. (2012)
• Garden City: Klocke et al. (2011) & Kisekka et al. (2015, 2016)
Texas:
• Etter: Hao et al. (2015a,b)
• Lubbock: TAWC (2017)
• Bushland: Baumhardt et al. (2013), Musick and Dusek (1980),
Howell et al. (1995), & Schneider and Howell (1998)
Rudnick et al. (2019)

11. In-Field Sensor Evaluation
Sensors:
• AquaSpy
• AquaCheck
• John Deere Field Connect
• Hortau
• Decagon 5TE, EC5, MPS-2, MPS-6
• Stevens Hydraprobe
• Acclima TDR315
• Campbell Scientific CS616 & CS655
• CPN Neutron Gauge
• Irrometer Watermark, Tensiometer
Year: 2016 - 2017
Location: North Platte, NE
Crop Type: Soybean
Loam Soil  little salinity

12. In-Field Sensor
Performance
• All Sensors tended to
over-estimate
θv (m3 m-3) Combined Depths
Sensor MD SDD RMSD
TDR315 0.047 0.019 0.050
CS655 0.056 0.055 0.078
HydraProbe2 0.095 0.036 0.102
5TE 0.036 0.015 0.039
EC5 0.048 0.026 0.054
CS616 0.149 0.051 0.157
Field Connect* 0.079 0.027 0.083
AquaCheck* 0.162 0.017 0.163
Singh et al. (2018)

13. Variable Rate Fertigation
• Chemical injection rate (i) remains
constant, while irrigation intensity
and/or duration are adjusted.
• Prescription tool was developed in
Python to convert a map of chemical
dosages into a VRI map to achieve
variable fertilizer.
Lo et al., 2019 (In-Press)

14. Water & Nitrogen Efficiencies
Terms:
• Irrigation Efficiency (IE)
• Irrigation Water Use Efficiency (IWUE)
• Crop Water Use Efficiency (CWUE)
• Evapotranspiration Water Use Efficiency (ETWUE)
• Recovery Efficiency (RE)
• Internal Efficiency (IE)
• Physiological Efficiency (PE)
• Agronomic Efficiency (AE)
• Relative Water Input Efficiency (RWIE)
• Relative Nitrogen Input Efficiency (RNIE)
• Relative Water × Nitrogen Input Efficiency (RWNIE)
• Water Intensification Performance Index (WIPI)
• Nitrogen Intensification Performance Index (NIPI)
• Water × Nitrogen Intensification Performance
Index (WNIPI)
IE
CWUE
ETWUE IWUE
RE NE
PE
RWIE
AE
RNIE RWNIE
WIPI NIPI WNIPI
Lo et al. (2019)

15. Input Recommendations
Temporal EvaluationSeasonal Evaluation

16. AdvancingTechandAccelerating
Adoptionvia Grower,Industry,&
UniversityTestbedPlatform

17. Thank You!
The mention of trade names or commercial products in and during this
presentation does not constitute an endorsement or recommendation for
use by the University of Nebraska-Lincoln or the author.