Published October 14, 2016
Advances in Agricultural Systems Modeling
Transdisciplinary Research, Synthesis, and Applications
Volume 7
Lajpat R. Ahuja, Series Editor
Advances in Agricultural Systems Modeling
Transdisciplinary Research, Synthesis, and Applications
Volume 7
Lajpat R. Ahuja, Series Editor
Improving Modeling Tools to Assess
Climate Change Effects on Crop Response
Jerry L. Hatfield and David Fleisher, Editors
Book and Multimedia Publishing Committee
April Ulery, Chair
Elizabeth Guertal, ASA Editor-in-Chief
C. Wayne Smith, CSSA Editor-in-Chief
David Myrold, SSSA Editor-in-Chief
Lajpat Ahuja
Sangamesh Angadi
David Clay
David Fang
Girisha Ganjegunte
Zhongqi He
Srirama Krishna Reddy
Limei Liu
Shuyu Liu
Sally Logsdon
Trenton Roberts
Nooreldeen Shawqi Ali
Gurpal Toor
Director of Publications: Bill Cook
Managing Editor: Lisa Al-Amoodi
Copyright © 2016 by American Society of Agronomy, Inc.
Crop Science Society of America, Inc.
Soil Science Society of America, Inc.
All rights reserved. No part of this publication may be reproduced or transmitted without
permission from the publisher.
The views expressed in this publication represent those of the individual Editors and Authors.
These views do not necessarily reflect endorsement by the Publisher(s). In addition, trade
names are sometimes mentioned in this publication. No endorsement of these products by
the Publisher(s) is intended, nor is any criticism implied of similar products not mentioned.
American Society of Agronomy, Inc.
Crop Science Society of America, Inc.
Soil Science Society of America, Inc.
5585 Guilford Road, Madison, WI 53711-5801 USA
agronomy.org | soils.org | crops.org
dl.sciencesocieties.org
SocietyStore.org
ISBN: 978-0-89118-351-8 (print)
ISBN: 978-0-89118-352-5 (digital)
doi:10.2134/advagricsystmodel7
Library of Congress Control Number: 2016954887
Advances in Agricultural Systems Modeling
ISSN: 2163-2790 (online)
ISSN: 2163-2774 (print)
Cover design: Patricia Scullion
Printed in the United States of America.
Contents
Foreword
Introduction
Contributors
vii
ix
xiii
Testing Approaches and Components in Physiologically Based Crop Models
for Sensitivity to Climatic Factors
Kenneth J. Boote, James W. Jones, Matthijs Tollenaar, Kofikuma A. Dzotsi,
P.V. Vara Prasad, and Jon I. Lizaso Wheat Responses to a Wide Range of Temperatures: The Hot Serial
Cereal Experiment
B.A. Kimball, J.W. White, G.W. Wall, and M.J. Ottman
1
33
Rice Free-Air Carbon Dioxide Enrichment Studies to Improve Assessment
of Climate Change Effects on Rice Agriculture
Toshihiro Hasegawa, Hidemitsu Sakai, Takeshi Tokida, Yasuhiro Usui,
Mayumi Yoshimoto, Minehiko Fukuoka, Hirofumi Nakamura, Hiroyuki Shimono,
and Masumi Okada
Climate Change and Potato: Responses to Carbon Dioxide, Temperature,
and Drought
David H. Fleisher, Dennis J. Timlin, and V.R. Reddy
Farm Simulation Can Help Dairy Production Systems Adapt to Climate Change
C. Alan Rotz, R. Howard Skinner, Anne M.K. Stoner, and Katharine Hayhoe
45
69
91
Sentinel Site Data for Crop Model Improvement—Definition and Characterization
Kenneth J. Boote, Cheryl Porter, James W. Jones, Peter J. Thorburn, K.C. Kersebaum,
Gerrit Hoogenboom, J.W. White, and J.L. Hatfield
125
Evapotranspiration: Evolution of Methods to Increase Spatial and
Temporal Resolution
Jerry L. Hatfield, John H. Prueger, William P. Kustas, Martha C. Anderson,
and Joseph G. Alfieri
Variable Atmospheric, Canopy, and Soil Effects on Energy and Carbon Fluxes
over Crops
159
Jerry L. Hatfield and John H. Prueger
195
About the Series
217
v
Foreword
A
griculture is dynamic, and meeting the ever-increasing needs of a growing global population has required expanding application of science in
agriculture to overcome barriers to improving productivity. We have acquired
a tremendous storehouse of evidence-based knowledge about crop response to
site-specific conditions and management practices. The reality of climate change
promises to magnify the challenge of meeting future needs since crop performance and responses at any site on this planet are likely to differ from past
responses due to shifts in climate and weather patterns. Knowing how crops will
respond and by what degree is essential to agriculture’s ability to adapt to climate
change and have the greatest probability of continuing to meet societal needs.
Crop models and the data to run them are essential for reliable prediction of
crop response, to guide on-farm practices, and to develop policy adjustments. The
interactive nature of crop growth factors and their intense spatial and temporal
variability make models critical for meeting this challenge. This book provides
guidance to modelers as well as to those conducting research with the potential
to generate data sets useful in the improvement, validation, and application of
those models.
The Tri-Societies—American Society of Agronomy, Soil Science Society
of America, and Crop Science Society of America—believe that the improved
synthesis of existing knowledge of how climate impacts crop growth and development is urgently needed. This book represents a significant contribution in
meeting that need.
Harold van Es, 2016 President, Soil Science Society of America
Paul Fixen, 2016 President, American Society of Agronomy
Michael A. Grusak, 2016 President, Crop Science Society of America
vii
Introduction
C
limate change has a multitude of dimensions and impacts in space and time.
It is often assumed that climate change projections of a 2°C temperature
increase or a 10% change in precipitation apply uniformly across the globe. How-
ever, the recent analysis of climate change in the US National Climate Assessment
(Walsh et al., 2014) reveals that changes in temperature and precipitation have not
been uniform across the United States, nor will the projected changes occur uniformly. This same holds true for the world assessment relative to agriculture (Porter
et al., 2014). There is an increasing concern for food security relative to the changing climate. Hatfield et al. (2014) pointed out that climate change will place more of
a stress on both plant and animal production systems in the future, and this level
of stress may increase to the point that adaptation strategies may not be sufficient
to preserve the production potential required to supply the food demands for an
increasing population. Production of food and livestock are not the only systems
affected. We can expect major impacts on weeds, diseases, and insects, leading the
potential for more pest pressures and an increased effect on the quality of our natural resources. These concerns have prompted a whole new focus on how we can
assess what the impact will be of climate change on crop response. To address this
topic, we convened a symposium at the 2014 ASA, CSSA, and SSSA international
meeting on the current state of knowledge on how we could improve our models
to assess climate change effects on crop response. We thank the participants in this
symposium for their outstanding contributions to the success of this effort and the
ensuing dialog about the status of climate impacts on agriculture.
There have been previous reports on the impact of climate change on crops,
rangeland, and pasture (Hatfield et al., 2011; Izaurralde et al., 2011). These reports
highlight the need for expanded understanding of the impact of climate change
on agricultural systems through the use of improved experiments to quantify the
interactions of temperature, water, and nutrients with the backdrop of a changing CO2 concentration in the atmosphere and the use of crop simulation models
to extend these results into potential climate scenarios for our future world. The
latter component is the focus of the Agricultural Model Intercomparison and
Improvement Project (AgMIP), as outlined by Rosenzweig et al. (2013).
This volume focuses on considerations that need to be undertaken in crop
models to help to improve model performance and account for the changes in
the climate and crop physiological and productivity responses. These chap-
ix
x
ters blend experimental data with evaluation of crop models using some of the
innovative experiments conducted. Boote et al. (2016a) demonstrated that testing of crop models requires approaches to continally evaluate models using the
best available data. They described the methods needed to compare response
to different factors and to evaluate the process level components within the
model. These chapters show this approach in their evaluation of different crop
and livestock models.
Kimball et al. (2016) used a hot serial cereal experiment to evaluate the effect
of different planting dates on wheat in Arizona to quantify the effect of different
temperature regimes on all aspects of wheat growth. Hasegawa et al. (2016) used
the Free-Air Carbon Dioxide Enrichment (FACE) studies on rice to evaluate the
interactions of a changing CO2 concentration with temperature during the growing season. Most crop models have been confined to grain crops, but as part of
the AgMIP effort, an emphasis has been placed on different crops. The synthesis by Fleisher et al. (2016) regarding the use of experimental CO2, temperature,
and drought responses used to improve and evaluate geospatial potato modeling
applications serves as an example of this emphasis. Simulation of agricultural
systems is not limited to crops and trees, and Rotz et al. (2016) focused on the
development, testing, and application of a model for dairy production systems.
All models require data, and Boote et al. (2016b) described the data structure
for model testing and evaluation using the concept of sentinel site data and the
use of platinum, gold, and silver quality definitions for data sets. The description
as to what is involved at each quality grade will help crop modelers and experimentalists understand what is contained in each data set and how it may be
most appropriately used in model evaluation and improvement. The goal of this
classification is to guide the development of data sets that may be used in more
robust evaluation of crop models and to identify the key elements needed in data
sets. One of the key components in assessing the impact of climate change is the
water and CO2 exchanges by a crop canopy. Hatfield and Prueger (2016) and Hatfield et al. (2016) offer two approaches to understand the variation of energy and
carbon fluxes from corn and soybean canopies under field conditions and then
an effort on the evolution of our understanding of measurement techniques for
evapotranspiration. There is a major effort underway to evaluate the ability of
crop models to estimate the yearly and growing season evapotranspiration from
crops, and this chapter provides insights into how we have evaluated and quantified the evapotranspiration process using a variety of methods.
All of the chapters in this volume provide a unique perspective on crop
modeling and experimental approaches to obtain high quality data. These efforts
will continue to expand as we gather more information on the effect of changes
xi
in climate on agriculture. The insights provided in these chapters continue
to advance science and showcase how we can improve our ability to measure
different responses but also incorporate that knowledge into crop models that
can detail the impacts of our changing climate. The chapters assembled in this
volume Improving Modeling Tools to Assess Climate Change Effects on Crop Response
offer these insights from multiple perspectives in the agricultural system. We are
indebted to these authors who have graciously shared their knowledge with us in
the preparation of this volume, and we thank them for their efforts.
Jerry L. Hatfield and David Fleisher, Editors
References
Boote, K.J., J.W. Jones, M. Tollenaar, K.A. Dzotsi, P.V. Vara Prasad, and J.I. Lizaso. 2016a. Testing
approaches and components in physiologically based crop models for sensitivity to climatic
factors. In: J.L. Hatfield and D. Fleisher, editors, Improving modeling tools to assess climate
change effects on crop response. Advances in Agricultural Systems Modeling 7. ASA, CSSA,
SSSA, Madison, WI. p. 1–32, 10.2134/advagricsystmodel7.2014.0019.5.
Boote, K.J., C. Porter, J.W. Jones, P.J. Thorburn, K.C. Kersebaum, G. Hoogenboom, J.W. White, and
J.L. Hatfield. 2016b. Sentinel site data for crop model improvement—Definition and characterization. In: J.L. Hatfield and D. Fleisher, editors, Improving modeling tools to assess climate
change effects on crop response. Advances in Agricultural Systems Modeling 7. ASA, CSSA,
SSSA, Madison, WI. p. 125–158, 10.2134/advagricsystmodel7.2014.0019
Fleisher, D.H., D.J. Timlin, and V.R. Reddy. 2016. Climate change and potato: Responses to carbon
dioxide, temperature, and drought. In: J.L. Hatfield and D. Fleisher, editors, Improving modeling
tools to assess climate change effects on crop response. Advances in Agricultural Systems Modeling 7. ASA, CSSA, SSSA, Madison, WI. p. 69–90, 10.2134/advagricsystmodel7.2014.0018.5
Hasegawa, T., H. Sakai, T. Tokida, Y. Usui, M. Yoshimoto, M. Fukuoka, H. Nakamura, H. Shimono,
and M. Okada. 2016. Rice Free-Air Carbon Dioxide Enrichment studies to improve assessment of climate change effects on rice agriculture. In: J.L. Hatfield and D. Fleisher, editors,
Improving modeling tools to assess climate change effects on crop response. Advances
in Agricultural Systems Modeling 7. ASA, CSSA, SSSA, Madison, WI. p. 45–68, 10.2134/
advagricsystmodel7.2014.0015
Hatfield, J.L., K.J. Boote, B.A. Kimball, L.H. Ziska, R.C. Izaurralde, D. Ort, A.M. Thomson, and D.W.
Wolfe. 2011. Climate Impacts on Agriculture: Implications for Crop Production. Agron. J.
103:351–370. doi:10.2134/agronj2010.0303
Hatfield, J.L., and J.H. Prueger. 2016. Variable atmospheric, canopy, and soil effects on energy and
carbon fluxes over crops. In: J.L. Hatfield and D. Fleisher, editors, Improving modeling tools to
assess climate change effects on crop response. Advances in Agricultural Systems Modeling 7.
ASA, CSSA, SSSA, Madison, WI. p. 195–216. doi:10.2134/advagricsystmodel7.2014.0018
Hatfield, J.L., J.H. Prueger, W.P. Kustas, M.C. Anderson, and J.G. Alfieri. 2016. Evapotranspiration:
Evolution of methods to increase spatial and temporal resolution. In: J.L. Hatfield and D. Fleisher,
editors, Improving modeling tools to assess climate change effects on crop response. Advances
in Agricultural Systems Modeling 7. ASA, CSSA, SSSA, Madison, WI. p. 159–194. doi:10.2134/
advagricsystmodel7.2015.00176
Hatfield, J., G. Takle, R. Grotjahn, P. Holden, R.C. Izaurralde, T. Mader, E. Marshall, and D. Liverman. 2014. Agriculture. In: J.M. Melillo, T.C. Richmond, and G.W. Yohe, editors, Climate change
impacts in the United States: The third national climate assessment. U.S. Global Change
Research Program. p. 150–174. doi:10.7930/J02Z13FR
Izaurralde, R.C., A.M. Thomson, J.A. Morgan, P.A. Fay, H.W. Polley, and J.L. Hatfield. 2011. Climate
Impacts on Agriculture: Implications for Forage and Rangeland Production. Agron. J. 103:371–
380. doi:10.2134/agronj2010.0304
xii
Kimball, B.A., J.W. White, G.W. Wall, and M.J. Ottman. 2016. Wheat responses to a wide range
of temperatures: The hot serial cereal experiment. In: J.L. Hatfield and D. Fleisher, editors, Improving modeling tools to assess climate change effects on crop response. Advances
in Agricultural Systems Modeling 7. ASA, CSSA, SSSA, Madison, WI. p. 33–44. doi:10.2134/
advagricsystmodel7.2014.0014
Porter, J.R., L. Xie, A.J. Challinor, K. Cochrane, and S.M. Howden. M.M., Iqbal, D.B. Lobell, and M.I.
Travasso. 2014. Food security and food production systems. In: C.B. Fieldet al., editors, Climate
Change 2014: Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change. Cambridge Univ. Press, Cambridge, UK. p. 485–533.
Rosenzweig, C., J.W. Jones, J.L. Hatfield, A.C. Ruane, K.J. Boote, P. Thorburn, J.M. Antle, G.C. Nelson, C. Porter, S. Janssen, S. Asseng, B. Basso, F. Ewert, D. Wallach, G. Baigorria, and J.M. Winter.
2013. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols
and pilot studies. Agric. For. Meteorol. 170:166–182. doi:10.1016/j.agrformet.2012.09.011
Rotz, C.A., R.H. Skinner, A.M.K. Stoner, and K. Hayhoe. 2016. Farm simulation can help dairy
production systems adapt to climate change. In: J.L. Hatfield and D. Fleisher, editors,
Improving modeling tools to assess climate change effects on crop response. Advances
in Agricultural Systems Modeling 7. ASA, CSSA, SSSA, Madison, WI. p. 91–124. doi:10.2134/
advagricsystmodel7.2014.0021
Walsh, J., D. Wuebbles, K. Hayhoe, J. Kossin, K. Kunkel, G. Stephens, P. Thorne, R. Vose, M. Wehner,
J. Willis, D. Anderson, S. Doney, R. Feely, P. Hennon, V. Kharin, T. Knutson, F. Landerer, T. Lenton,
J. Kennedy, and R. Somerville. 2014. Our Changing Climate. In: J.M. Melillo, T.C. Richmond, and
G.W. Yohe, editors, Climate change impacts in the United States: The Third National Climate
Assessment, U.S. Global Change Research Program. p. 19–67. doi:10.7930/J0KW5CXT
Contributors
Alfieri, J.G.
Hydrology and Remote Sensing Laboratory, 10300 Baltimore Ave., Beltsville,
MD ([email protected])
Anderson, M.C.
Hydrology and Remote Sensing Laboratory, 10300 Baltimore Ave., Beltsville,
MD ([email protected])
Boote, K.J.
University of Florida, Agronomy Dep., 3105 McCarty Hall, Gainesville, FL
32611-0500 ([email protected])
Dzotsi, K.A.
The Climate Corporation, 4 City Place Dr., Suite 100, St. Louis, Missouri 63141
([email protected])
Fleisher, D.H.
USDA-ARS Northeast Area/BARC, Bldg. 001, Rm. 342, BARC-West, 10300
Baltimore Ave., Beltsville, MD 20705 ([email protected])
Fukuoka, M.
National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba,
Ibaraki, 305-8604, Japan ([email protected])
Hasegawa, T.
National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba,
Ibaraki, Japan, 305-8604 ([email protected])
Hatfield, J.L.
USDA-ARS, National Laboratory for Agriculture and the Environment, 1015 N.
University Blvd., Ames, IA 50011 ([email protected])
Hayhoe, K.
Climate Science Center, 72 Holden Hall, Texas Tech Univ., Lubbock, TX 794091015 ([email protected])
Hoogenboom, G.
AgWeatherNet Program, Washington State University, Prosser, WA 99350
([email protected])
Jones, J.W.
Agricultural and Biological Engineering Dep., Univ. of Florida, 289 Frazier
Rogers Hall, Gainesville, FL 32611-0570 ([email protected])
Kersebaum, K.C.
Inst. of Landscape Systems Analysis, Muencheberg, Germany (ckersebaum@
zalf.de)
Kimball, B.A.
USDA-ARS, US Arid-Land Agricultural Research Center, 21881 North Cardon
Lane, Maricopa, AZ 85238 ([email protected])
Kustas, W.P.
Hydrology and Remote Sensing Laboratory, 10300 Baltimore Ave., Beltsville,
MD ([email protected])
Lizaso, J.I.
Dep. Producción Vegetal, Univ. Politécnica of Madrid, Calle Senda del Rey 13,
28040 Madrid, Spain ([email protected])
Nakamura, H.
Taiyo Keiki Co. Ltd., 1-12-3, Nakajujo, Kita-ku, Tokyo 114-0032, Japan
([email protected])
Okada, M.
Iwate University, 3-18-8 Ueda, Morioka, Iwate 020-8550, Japan (mok@
iwate-u.ac.jp)
Ottman, M.J.
University of Arizona, Plant Sciences Dep., Forbes 303, 1140 E. South Campus
Drive, Tucson, AZ 85721 ([email protected]).
Porter, C.
Agric. and Biol. Eng. Dep., University of Florida, Gainesville, FL 32611
([email protected])
Prasad, P.V.
Sustainable Intensification Innovation Lab, Kansas State Univ., 108 Waters Hall,
1603 Old Claflin Place, Manhattan, KS 66506 ([email protected])
Prueger, J.H.
USDA-ARS, National Laboratory for Agriculture and the Environment, 1015 N.
University Blvd., Ames, IA 50011 ([email protected])
Reddy, V.R.
USDA-ARS Northeast Area/BARC, Bldg. 001, Rm. 342, BARC-West, 10300
Baltimore Ave., Beltsville, MD 20705 ([email protected])
xiii
xiv
Rotz, C.A.
USDA-ARS, 3702 Curtin Rd., Univ. Park, PA 16802-3702 ([email protected])
Sakai, H.
National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba,
Ibaraki, Japan, 305-8604 ([email protected])
Shimono, H.
Iwate University, 3-18-8 Ueda, Morioka, Iwate 020-8550, Japan (shimn@
iwate-u.ac.jp)
Skinner, R.H.
USDA-ARS, 3702 Curtin Rd., Univ. Park, PA 16802-3702 (howard.skinner@ars.
usda.gov)
Stoner, A.M.K.
Climate Science Center, 72 Holden Hall, Texas Tech Univ., Lubbock, TX 794091015 ([email protected])
Thorburn, P.J.
CSIRO Agriculture Flagship, 306 Carmody Rd., St. Lucia, QLD 4067, Australia
Timlin, D.J.
USDA-ARS Northeast Area/BARC, Bldg. 001, Rm. 342, BARC-West, 10300
Baltimore Ave., Beltsville, MD 20705 ([email protected])
Tokida, T.
National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba,
Ibaraki, Japan, 305-8604 ([email protected])
Tollenaar, M.
808 Pinehurst Dr., Chapel Hill, NC 27517 ([email protected])
Usui, Y.
National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba,
Ibaraki, Japan, 305-8604 ([email protected])
Wall, G.W.
USDA-ARS, US Arid-Land Agricultural Research Center, 21881 North Cardon
Lane, Maricopa, AZ 85238 ([email protected])
White, J.W.
USDA-ARS, US Arid-Land Agricultural Research Center, 21881 North Cardon
Lane, Maricopa, AZ 85238 ([email protected])
White, J.W.
USDA-ARS Arid Land Agric. Res. Center, Maricopa, AZ 85138 (Jeffrey.White@
ars.usda.gov)
Yoshimoto, M.
National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba,
Ibaraki, 305-8604, Japan ([email protected])