A maize soil moisture and temperature stress model is described which was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions in the major maize-producing areas of the world. The model also identifies optimum climatic conditions and planting/harvest problems associated with poor tractability

Ravet, F. W.

Taylor, T. W.

English

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Early Warning and Crop
Condition Assessment
EW-U1-04119
JSC-17399
A Joint Program for
Agriculture and
Resources Inventory
Surveys Through
Aerospace
Remote Sensing
April 1981
A METEOROLOGICALLY DRIVEN MAIZE STRESS INDICATOR MODEL
T. W. Taylor
U.S. Department of Agriculture
Science and Education Administration-Agricultural Research
F. W. R4vet
National Aeronautics and Space Administration
Johnson Space Center
Houston, TX 77058
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Lyi don B. Johnson Space Center
Houston. Texas 77058
L^___ ­­­-
1, Report No, 2, Government Accession No. 3. Reci pient's Catalog No,
JSC-17399; EW-U1-0411
e. Title and Subtitle	 AgR ISTARS S. Report Date
A Meteorologically Driven Maize Stress Indicator Model April	 1()8l
6. Performing Organization
7, Authar(s)
T.'4. Taylor - USDA/SEA-AR 8. Performing Organization Report No
F.W. Ravet - NASA
10. Work Unit No..,
9, hdorming Organization Name and Address
Science and Education Administration-Agricultural Research
11, Contract or Grant No.Early Warning and Crop Condition Assessment REsearch Unit
1050 Bay Area Blvd.
Houston, Texas	 77058 13. Type of Report and Period Covered
Technical Memorandum12. Sponsoring Agency Name and Addreu
AgRISTARS Program at Johnson Space Wenter Sponsoring Ager+cy Code'4	 sHouston, TX
	
77058
15, Supplementary Notes
16. Abstract
A maize soil moisture and temperature stress model described herein was developed to
serve as a meteorological data filter to alert commodity analysts to potential stress
conditions in the major maize-producing areas of the world. 	 The model also identifies
optimum climatic conditions and planting/harvest problems associated with poor tract -
ability.
17. Key Words (Suggssted by Authorls)) 18, Distribution Statement
Maize
Corn
Stress
Model
19. Security Omit, (of this report)
Unclassified
20. Security Classif. lov this page)
Unclassified
21. No, of Pages 22,	 Price'
'For We by the National Technical Information Service, Springfield, Virginia 22161
J$C Form 14241)tev Nev 75)	 NASa — 1sc
A METEOROLOGICALLY DRIVEN MAIZE STRESS INDICATOR MODEL
PRINCIPAL INVESTIGATORS
T. W. Taylor and F.W. Ravet
APPROVED BY
Gl.ennis O. Boatwright, Manag
Early Warning/Crop Condition Assessment Project
AgRISTARS Program
E4rth. Observation Division
Space and Life. Science Directorate
NATIONAL AERONAUTICS AND SPACE ADMINISTRATION
LYND014 B. JOHNSON SPACE CENTER
Houston, Texas
April 1981
x
TECHNICAL MEMORANDUM
NO.
A METEOROLOGICALLY DRIVEN MAIZE STRESS IVDICATOR MODEL
EARLY WARNING/CROP CONDITION ASSESSMENT
UNITED STATES DEPARTMENT OF AGRICULTURE
HOUSTON TEXAS
UNITED STATES DEPARTMENT OF AGRICULTURE
AGRISTARS-EARLY WARNING/CROP CONDITION ASSESSMENT
A METEOROLOGICALLY DRIVEN MAIZE
STRESS INDICATOR MODEL 	 FIRST ISSUE
1. REASON FOR ISSUANCE
Document the development of a model. capable of giving an early indi-
cation of actual or potential plant stress due to moisture and temp-
erature.	 'k
2. COVERAGE
The mo,isture/temperature values which both stress and optimize the
vigor of maize by specific growth stages are reviewed. A description
of the model. structure and stress parameters are set forth. Model,
output and preliminary results are discussed.
3. PREPARED BY
Terry W. Taylor	 Date
<olf j
T.W. Ravet	 Date
a
1
W
METEOROGICALLX DRIVEN MAIZE STRESS INDICATOR MODEL
PART 1.0 INTRODUCTION
1,1 PURPOSE
The purpose of this section is to document a corn hazard model that
detects plant stresia due to moisture deficiency and adverse temper-
atures. A brief synopsis of the climatic stress thresholds for corn
(maize) at different growth stages is also given.
1.2 SITUATION
USDA policy is to provide American farmers and commodity analysts
with the most timely information concerning world and national.
agricultural, activities. Early Warning/Crop Condition Assessment,
located in Houston, Texas is one of eight projects of the AgRISTARS
program. AgRISTARS is the program for Agriculture and Resources
Inventory Surveys Through Aerospace Remote Sensing and is a cooper-
ative effort of 5 Fe0aral agencies. These agencies are; Department
of Agriculture (USDA); National, Aeronautics and Space Administration
(NASA); Department of the interior (USDI); and the Agency of Inter-
national Development (USAID).
Early warning of changes affecting production and quality of com-
modities and renewable resources is the number one priority area of
the Secretary's Initiatives. The overall. objective of the EW/CCA
Project is to provide a capability for the USDA to respond in a
timely manner to factors which affect the quality and production of
economically important crops. The response will involve identifying
the occurrence of environmental and agronomic factors which infl.u-
ence crop condition and determine the severity of the area affected.
This research activity will be directed toward teeniques which will
augment and strengthen the operational Crop Condition Assessment
Division (CCAD) of the Foreign Agricultural Serivice (FAS) and pro-
vide new analysis tools to domestic users in USDA.
The CCAD operations plan calls for assessment based on a convergence
of•evidence from all sources. In 1981, this consists of the tradi-
tional sources plus increased use of agrometeorological models that
can be used to infer crop conditions and initial subjective opera-
tional use of remote sensing techniques.
A corn indicator stress model was developed to alert a crop analyst
of a potential problem area. The model, utilizes meteorological data
because it is generally available much sooner thail Landsat data, and
provides daily data versus the eighteen day interval data from
Landsat. This model eliminates the necessity of spending time and
resources to concentrate on areas which the model indicates have
high probability that stress is occurring or is likely to occuro
After a potential stress area has been identified, an analyst can
assess the condition using meteorological, Landsat, and ancillary
data. This model is not intended as a stand-alone system, but
rather, an indicator to a crop analyst to initiate an investigation
of the area.
The CCAD mission of alert analysis requires a quick response system
and will sacrifice exact quantative results to meet their response
requirement. A subjective estimate, if timely, which provides
information in general terms such as better or worse than last year
and an approximate pgrcentage is very useful in assessing an alert
situation. As research provides better tools, it is believed that
these subjective estimates can be quantitatively accurate,
3
PART 2.0 STRESS FUNCTIONS
2.1 MAJOR VARIABLES
.
The degree of stress is dependent on three variables - phenological
growth stage, available soil moisture and temperature.
2.2 The Hanway Growth Stage (HGS) system (Hanway, 1963) was used in the
model as defined below:
HGS	 PHENOLOGICAL STATE
0.0
	
Emergence
1.0	 4 Leaves
2.0	 8 Leaves
3.0	 12 Leaves
4.0	 16 Leaves
5.0	 Silk-tassel
6.0
	
Blister Kernel
7.0	 Lough
8.0
	
Begin Dent
9.0	 Full Dent
10.0	 Physiological Maturity
During each stage optimum and stress condicitions exist. Most of
these conditions are directly related to meteorological factors.
Stress was defined in this model version as those factors considered
to most affect the maize growth cycle and for which input data are
presently available to CCAD. Problem and optimal conditions that
form the model logic are presented by growth stage in Table 1.
.
4
TABLE 1
.
GROWTH STAGE DAMAGING CONDITION OPTIMUM CONDITION
-1 - 0.1 Tavg < 9C Tavg > 20C
AWC surface < 18%, > 90% AWC survace > 50%, < 75%
0101 - 1.0 Tmax > 38C Tmax < 32
Tmin < OC Tmin > 15C
AWC surface < 40X, > 95% AWL surface > 50%, < 80%
1.01 - 2.5 Tmax > 38C Tmax < 32C
Tmin < 2C Tmin > 15C
AWC < 40%, > y 5% AWC > 50% 6 < 80%
2.51 - 4.75 Tmax > 38C Tmax <	 32C
Tmin < 3C Tmin > 15C
AWC < 40%, > 95% AWC > 55X 9
 < 80%
4.76 - 6.5 Tmax > 33C Tvax <	 30rC
Tmin < 5C Tmin > 15C
AWC < 45% t > 95% AWC > 55X 0
 > 80%
6.51 - 8.0 Tmax > 38C Tmax < 32C
Tmin < OC Tmin > 15C
AWC < 40%, > 957.. AWC > 50X, < 80%
8.01 - 10.00 Tmax > 41C Tmax < 38C
Tmin < OC Tmin > 15C
AWC < 30X 0
 > 95% AWC > 40X, < 90%
2.3 STRESS CONDITIONS BY GROWTH STAGS
A. Growth Stage - 1.0-0.0. Climatic planting requires at least
1^vailable water i the surface layer with 65% being
optimum. Corn germination is affected by both moisture and
temperature. Mean daily temperatures of less than 9 0C will
inhibit maize germination. Optimum conditions occur with
daily mean temperature2 greater than the 20C and available
water capacities (AW()^ in the 50-75% range. Alerts are
also issued at the stage for insufficient pre-season stored
moisture. The bulk of corn is produced by dryland farming
and notmal precipitation is often insufficient. The amount
of necessary stored soil moisture is location dependent.
Tractability problems occur at plant and harvest when more
than 5= of precipitation falls or when soil moisture values
exceed 80% AWC.
B. Growth Stage - 00.0-1 .0. During the period from emergence
untilthe collar of the fourth leaf is visible damaging
conditions occur when temperatures drop below freezing of
rise above 38C. The minimum moisture requirement is 40% AWC
with values above 95% capacity also deterimental to sus-
tained photosynthesis. Optimal conditions range from 15-32C
with 50-80% AWC.
C. Growth Stage - 1.01-2.5. During the 4-8 leaf interval,
damaging and optimal thresholds are identical to the
emergence-4 leave period with the exception of cold tol-
erance; the minimum temperature is 2C.
D. Growth Stage - 2.51-4.75. From 8 leaf to effective cover,
the plant is stressed by AWC values less than 40% or greater
than 95%. Cold tolerance continues to decrease with temper-
ature less than 3C being harmful. Optimum conditions are
defined as being between 55-80% AWC and 15-32C.
Available-water-holding-capacity (AWHC) can be defined in laymans terms
as the amount of water that a soil will hold that is available to the
plant. The technical definition states the AWHC as the difference
between the vpper and lower limits of the moist soil-water state or the
difference between the field capacity and the permanent wilting percen -
tage and is usually expressed on a volume basis when the bulk density
is known. The concept of AWHC can apply to a horizon, layer or pedon.
This can be expressed in terms of centimeters of water per specified
depth of soil, as the two horizontal dimensions of the water and soil
volumes are the same. Thus, the units of AWHC applied to characterize
polypedons, or soil series are commonly expressed as centimeters (or
inches) of available water per unit thickness (cm or inches) of soil,
by horizon, or to the depth of rooting.
5
C. Growth Stage - 4.76-6.5. Maize is moat sensitive to stress
during the pollination period. huaaian scientists have
stated that even 2-3 hours exposuze Lo excessive temper-
atures at Bilking will significantly reduce yield. Thres-
hold for moisture are set at 45 and 95% AWC; temperature
stress is defined at 5C and 33C. Optimal conditions ,,4ry
from 55-80% AWC and 15-30C.
F. Growth Stage - 6.51 .8.0. Stress values are relaxed somewhat
after the pollinationn period. Adverop temperatures in the
dough period are those below freezing and greater than 38C.
Moisture requirements range from 40-95% AWC. Temperatures
between 15-32C with 50-80% AWC are optimal.
C, Growth Stage - 8.01-10.0. The dry-down from full dent to
physl toica maturity is Lhe final period checked in the
model. The plant is vary hardy and environmental impact on
final yield is reduced. Stress conditions ocevr outside the
0-41C temperature range with AWC values less than 25% or
greter than 95% signaling alerts. Optimal situations are
expanded to 15-38C and 44-90% AWC. Freezing temperatures
are most damaging to yield. Tractability alerts are gen-
erated from gresuvh stage 9.0 to maturity.
6
PART 3.0 MAIZE STR45S INDICATOR MODEL
3.1 STRESS MODEL COMPONENTS
The stress model. has 3 central. components - a hazard model, a crop
calendar model and a soil water budget modal. Thaw models collec-
tively require daily meteorological data - maximum and minimum
temperature and precipitation. The phonology-based hazard routine
contains the stress definitions and thresholds. The crop calendar
is a fixed
-increment degree-day model developed by EW/CCA that
requires an actual or estimated planting date. Degree-day summa-
tions are variety specific. A two-layer soil moisture model. as
implemented by Ravet and Hickman (1979) is employed to track the
amount of plant-available soil water (Appendix 1) .
3.2 DEGREE-DAY CALCULATION
Temperature is a regulator of maize growth and development. Most
efforts to predict the timetable of maize development have used a
heat-unit approach; the most common is the degree-day. The Shown
method (1975) of determining degree days is based on the physiol.og-
ical response of plants to temperature and is determined as follows:
DD n (Xmax + Ymin) /2
where Ymax - (Ym$x - 10oC*[3.33-0.084*(Tmax - 10 oC) and Ymino
1.8*(Tmin - 4.44 C) . When Tmex is less than or equal. to 10 C the
value of Xmax is zero and Tmax values greater 0 than 32C are equal. to
32C. When Tmi.n is less than or equal to 4.44 C the value of Ymin is
zero
The values of the accumulated degree-days for the most common Soviet
Union and Kansas/Oklahoma (in parenthesis) varieties are: 110 (146)
to emergence, 420 (540) to HGS 1.0, 800 (990) to 2.5, 1380 (1665) to
4.75 0 2085 (2770) to 8.0 and 2580 (3320) to 10.0.
3.3 MODEL PARAMETERS AND OUTPUTS
The model, identifies three environmental conditions - optimum,
adequate and hazardous. Hazardous conditions include:
(a) Insufficient pre-season stored soil. moisture
(b) Planting/harvest delay (tractability problems)
(c) Poor germination
(d) Poor emergence
(e) Adverse growing season soil moisture and temperature
(excessive/deficient, phonology-based)
(f) Optimal soil moisture and temperature conditions
The stress indicator model: determines the possibility of maize
stress based on temperature and moisture conditions (see Table 1).
The stress and optimal growth conditions- are recorded for each
growth stage as well as the time the plant remained in these stages.
7
From this information the analyst can judge the degree of damage or
stress occurring ut a growth stage and then determine the overall
effect on crop development. The model does not predict events nor
does it attempt to assess the impact of stress, it provides informa-
tion that indicates conditions occurring within a predescribed
geographic area around the data :source. The output from the model
is a record of each day that a stress optimal. condition has occu*ed,
the reason for the condition and the crop growth stage. At the
completion of processing data for a given meteorological station,
the data are summarized giving the total days for development, and 	 w
the number of optimum and hazardous growth days.
f
8
PART 4.0 CONCLUSIONS
4.1 SUMMARY
A maize soil moisture and temperature stress model was developed by
the Early Warning and Crop Condition Assessment co[nponent of 	 k
AgRISTARS to support the Crop Condition Assessment Division of the.
	
c
Foreign Agriculture Service. The model is essentially a data filter
that alerts a commodity analyst to corn producing areas that are
under a potential stress condition due to adverse climatic condi-
tions. The model also identifies areas of optimum climatic condi-
tions and planting/harvest problems associated with poor tract-'
ability. The model has been teited over sites in the United States
and Soviet Union under a wide range of climatic conditions with
favorable results.
To assess the impact of alerts= generated by the model requires the
analytical skills of a commodity analyst well versed in agronomy and
remote sensing. Future improvements in the model are expected to
focus on phenology and spectral inputs.	 .
9
nLITERATURE CITED
Brown, D.M. 1975• Heat Units for Corn in Southern Ontario, No. 75-007
Ministry of Agriculture and Food, Ontario, Canada.
Hanway, J.J. 1971. How a Corn Plant Develops. Agron, J. 55;487-492.
Ravet, F.W. and J.R. Hickman. 1979. A Meteorologically Driven Wheat
Stress Indicator Model. USDA-FAS Technical Memorandum #8, Houston,
Texas.
10
TWO-LAYER SOIL MOISTURE MODEL
The two-layer soil moisture model in use by CCAD and EW/CCA is similar
to the Palmer two-layer model (Palmer, 1965). In the models, the amount of
water withdrawn by both direct evaporation from the soil surface and trans-
piration L y plants is determined by atmospheric demand and soil water
availability.
Both models assumed that the first inch of available water is held in 	
.
the layer. The actual thickness of each layer is variable depending on
soil type, rooting depth and layers permeability.
The original Palmer model assumed that moisture was removed from the
surface layer at a rate equal to potential evapotranspiration calculated by
the Thornthwaite method (1948) and that moisture was removed from the lower
layer at a fraction of the potP rial rate. It was assumed that moisture
could not be removed from the lower layer until the surface layer was com-
pletely dry. These assumptions do not adequately represent the true layer
condition.
The various stress indicator models being developed (Ravet and
Hickman, 1979) required more accurate representation of the soil moisture
condition, particularly in the surface layer. The two-layer model was
modified to allow a more gradual and realistic depletion of the surface
layer and also allows moisture to be depleted from the lower layer before
the surface is completely dry.
SOIL MOISTURE EQUATION
Top Layer	 =	 Contains 1 inch of plant available water.
Lower Layer	 =	 Normally contains between 5 and 10 inches of
available water.
Ls	S's - (PET-P) Df
Lu	(PET-P-L.) S'u : Lu < Sou
AWE
D f	Surface moisture extraction function.
D f	1 if P	 PET
D f	(S's	 .75)
	
.1 < Df < 1.
D f	= .1 if Df <.1 and Df = 1. : Df>1.
R	 s	 Excess P after both layers are filled.
PET -	 PET'(d) (Thornthwaite, 481
If	 T less than 0°C
PET' - 0
If 0°C < T < 26°C
PET' - 1.6 (lOT I)a
If T > 260C
PET' - Sin (T - 9.5) -.76
a	 -	 6.75 x 10-7 13 -7.71 x 10-5 12 + .017921 + .49239
i
'	 12	 1.514
I	 (T/5)
i-1
d	 -0.767 tan(.410117Cz.,s(..0172264(JDAY-172)))
DEFINITION OF TERMS
L s = Moisture loss from surface
S's Available water in surface layer at start
PET Potential evapotranspiration
P Daily precipitation
Lu Loss from lower layer
so = Available moisture stored in lower layer
AWC c Conbined	 available water capawity;	 i.e.,	 MAX(S' s + S'u)
R = Runoff
D f = Surface moisture extraction function
PET' Unadjusted potential evapotranspiration
d Day length adjustment for PET
T Average daily temp degree C
I Annual heat index
JDAY W Julian date
a = Coefficient
REFERENCES
Hill, J. D. 1974. The Use of a Two-Layer Model to Estimate Soil Moisture
Conditions in Kentucky. Monthly Weather Review. Oct:726-730.
Palmer, W. C. 1965. Meteorological Drought. U.S. Weather Bureau Research
Paper 45. 45 pp.
i{
Ravet, F. W., and J. R. Hickman. 1979. A Meteorologically Driven Wheat
Stress Indicator Model. USDA-FAS Technical Memorandum #8. Houston,
Texas.
Thornthwaite, C. W. 1948. An Approach Toward a Rational Classification of
•	 Climate. Geograph. Rev. 38:55-94.	 j
a
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