THORNTHWAITE'S MOISTURE INDEX AS A MEASURE OF THE
INTENSITY TO WHICH HARVESTED CROPLAND IS DEVOTED
TO CORN UNDER NATURAL CLIMATIC CONDITIONS
by
ROBERT NEWELL HALL
A RESEARCH PAPER
submitted to
THE DEPARTMENT OF GEOGRAPHY
OREGON STATE UNIVERSITY
in partial fulfillment of
the requirements for the
degree of
MASTER OF SCIENCE
June 1968
TABLE OF CONTENTS
THEPROBLEM .................
Page
2
LITERATUREREVIEW ...............
2
THESTUDYAREA ................
4
ANALYSIS ...................
........
Analysis of Variance .............
Intensity of Harvested Croplanci Devoted to Corn .
Calculation of the Moistitre Index
.
B. ES U LT S ....................
CONCLUSIONS ..................
6
6
9
11
13
16
FOOTNOTES ..................
17
Bibliography ................
19
A PIENII)C ...................
LIST OF TABLES
Page
Table
1.
2.
3.
Percent of Total Harvested Acreage Devoted to Corn
(Total harvested acreage/acres of corn harvested) .
.
21
Extreme Dates of the Mean 32°F Growing Season and
Values of Thornthwaite's Moisture Index Summed
Through This Growing Season for Selected Stations in
the StudyArea .......... . .....
IntensityClasses ...............
30
35
LIST OF FIGURES
Page
Figure
1
Identification of Counties
2.
.
5
Derivation of Study Area Boundary ........
7
3. Method of determining boundary values of land use
intensity classes based on the percentage of
harvested cropland devoted to corn .........
4.
5.
Intensity of Harvested Cropland Devoted to Corn
.
9
10
Values of Thornthwait&s Moisture Index Summed
Through the Mean Growing Season .........
12
THORNTHWAITE'S MOISTURE INDEX AS A MEASURE OF THE
INTENSITY TO WHICH HARVESTED CROPLAND IS DEVOTED
TO CORN UNDER NATURAL CLIMATIC CONDITIONS
ABSTRACT: Moisture has long been identified as one of the major
limiting factors in the distribution of agricultural land use practices.
However, the importance of any environmental element can only be
determined by considering how it is affected by its relationship with
other elements of the environment. Thornthwaite's moisture index
attempts to measure the moisture conditions of an area as they are
controlled by other environmental conditions. Through analysis of
variance, this study seeks to determine whether Thornthwaite s
moisture index can be used as a measure of the intensity to which
harvested cropland is devoted to corn in the Corn Belt of the United
States.
The natural environment of a plant is a dynamic and eve rchanging complex of elements. All of these elements are in a state
of constant variation. The rates of change in intensity of each, the
time of their duration, and the extreme values reached by each all
have a direct effect on the survival and productivity of a plant.
Modern agriculture is concerned with using each parcel of land
to its productive optimum. This requires an nalysis of the several
components which combine to determine the quality of a given site
for agricultural production. The farmer then attempts to select the
crops and production processes which will result in the highest possible level of production from his land.
2
THE PROBLEM
If one assumes that there is some environmental variable (or
combination of variables) which is paramount in regulating the dis-
tribution of crops, the next step is to analyse those components of the
environmental complex which appear to exercise this overriding
control. This study attempts such an analysis. Its objective is to
determine whether the spatial variation of moisture, when measured
by Thornthwaites moisture index, coincides with that of the intensity
to which land is planted to corn in the Middle West.
LITERATURE REVIEW
Moisture is one of the major environmental factors which
determines the kind of crops that can be grown in an area. 2 It is
not only important as a reagent in photosynthesis, but is essential
for turgidity, maintenance of leaf form and several of the other
physiological movements of plants.
Its overall importance is well
reflected in the fact that water alone accounts for 85 to 90 percent
of the green weight of a plant.
There are several sources from which a plant may obtain its
water requirements. These include the many aspects of atmospheric
moisture such as precipitation, moisture held within the air (humid-
ity), dew and the like, and soil moisture. However, the extent to
which each of these is able to add to the moisture supply of a plant
3
depends on their relationship with other aspects of the environment
such as temperature, length of the growing season, latitude, drainage,
etc.
4
Perhaps one of the more notable attempts to combine several
of the more important environmental elements which affect the mois-
ture available for plant growth into one meaningful measure is that
by C. W. Thornthwaite. In 1955 Thornthwaite presented an index
which combined temperature, precipitation, latitude, potential
evapotranspiration, and total runoff into an index which reflects the
moisture conditions at a given station for the period through which
the variables are measured.
Although this new index was only a
slight modification of the one Thornthwaite presented in 1948,
6
the
latter was based on nearly five decades of research by various
authors.
Thornthwaite's moisture index is actually a combination of
two of his other climatic indices. It is derived by subtracting his
aridity index from his index of humidity. That is,
'h -
a
= 100 (
where: Im = moisture index
= index of humidity
'a = aridity index
D
PEPE
= moisture surplus (precipitation - actual evapotranspiration)
D
= moisture deficit (potential evapotranspiration actual evapotranspiration)
PE = potential evapotranspiration.
S
4
If one is interested in calculating only the moisture index, the
above formula may be reduced to I
100
(2
- 1)
8
Positive
values represent a moisture shortage. Although this new formulation of Thornthwaite's moisture index has been available for more
than a decade, it has not been used in any climatological studies and
has received only limited attention in climate classification.
Thornthwait&s moisture index may be calculated for any station
whose mean monthly temperature, latitude and monthly precipitation
(in millimeters) is known. This data allows one to select values from
several tables which are then introduced into nomograms for determining the actual and potential evapotranspiration of the station.
10
However, Thornthwaite Associates have published water balance data
for selected stations throughout the world. This study analyses the
1 60 stations within the study area for which this published data is
available. 11
THE STUDY AREA
The area selected for testing Thornthwaite's moisture index as
a measure of the intensity of land devoted to corn production is a
composite of two descriptions of that area identified as the major
corn producing region of the Middle West. It was delimited by using
the outermost boundary created by combining those definitions of the
Corn Belt by the Economic Research Service'2 and the Soil Conservation Service13 of the United States Department of Agriculture. (see
)t
-
L" \\/
/
/
-'
I
\I\I
I
4
-
I
-
_;-+----_J---_
%
/
I
I
I
¶-
-
--
---
-
:1
i---y
;:: ',':
Source US Bureau of Census
,
I--j
Fig.1.
Identification of Counties
Fig. 2). 14 Since counties, of which there are 648 in the area thus
delimited, were used as the basic areal data units, the final boundary
encloses entire county units and does not divide them as do both of
the above definitions.
AT\TAT VT
The following analysis consists of three parts. First, it was
necessary to determine the percent of harvested cropland devoted to
corn in each of the 648 counties so that intensity classes could be
formed. Next, Thornthwait&s moisture index was calculated for
each county for which the necessary climatic data was available.
Finally, each county with a moisture index was drawn from the three
intensity groups and the means of the moisture indices of each of
these groups compared through analysis of variance to determine
whether the moisture indices vary as does the intensity to which land
is devoted to corn within the study area.
Intensity of Harvested Cropland Devoted to Corn
In order to determine the percentage of harvested cropland
devoted to corn, data was obtained from the Preliminary Reports of
of the 1964 Census of Agriculture as to the total harvested acreage in
each county, the acreage of corn harvested for all purposes, and the
amount of harvested acreage that was under irrigation.
15
The per-
cent of harvested cropland devoted to corn was calculated by dividing
Sourcs: U.S.D.A.
MDARIIS
Fig.2.
Derivation of Study Area Boundary
the second figure by the first.
The irrigation data was used as a control to exclude counties
in which irrigation would compensate for deficit moisture conditions.
A value greater than 30 percent for the ratio of irrigated acreage
harvested to total acres harvested was considered sufficient to
exclude that county from further calculations. 16 Nine counties were
excluded in this manner. Table 1 lists the percentages for the
amount of harvested acreage devoted to corn for the remaining 639
counties.
The mean and standard deviation were then calculated for the
data on corn percentages. The mean being,
N
X
i=l
N
where:
mean
x = an individual percentage
N = total number of counties
j.
and, the standard deviation,
N
N
o-= Ex 2
i=1
where:
o
(Ex) 2
1/2
i=l
N
= standard deviation and x and N are as above.
Each county was then placed in one of three groups in the basis
of the intensity of harvested cropland devoted to corn production
(Fig. 4). Low intensity corn producing counties were defined as
those in which the ratio of corn to harvested acreage was less than
one standard deviation below the mean; medium intensity as those in
which this ratio was within one standard deviation about the mean;
and, high intensity as those where the ratio was greater than one
standard deviation above the mean. Figure 3 shows the method used
in determining these boundary values.
Low
High
Fig. 3. Method of determining boundary values of land use
intensity classes based on the percentage of harvested cropland
devoted to corn.
Calculation of the Moisture Index
Thornthwaite's moisture index was then calculated for the 160
counties for which the necessary evapotranspiration data was available. This entailed the summation of the moisture indices for those
months and portions of months contained within the mean 32°F
growing season for each station. 17 The formula for this calculation
is:
Source: U.S.D.A.
'S
Fig.4. Intensity of Harvested Cropland Devoted to Corn
11
b
I
m
= 100 E
1a
(P.21
PE
- 1)
moisture index
a
mean date of the last 32 F spring frost
= mean date of the first 32 fall frost
b
precipitation in millimeters
ppn
PE = potential evapotranspiration
where: I m
Table 2 lists the stations in each county used for this calcula-
tion, the extreme dates of the 32°F frost-free season, and the value
obtained for the moisture index when summed through this frost-free
season. Figure 5 shows the areal variation of the moisture indices
throughout the study area.
Analysis of Variance
The means of the moisture indices of each of the three intensity
groups were then compared for equality through analysis of variance.
This test tests the among-sample variance with the within-sample
variance by comparing their ratio with Fisher's F-distribution. 18
A small value (near one) for this ratio infers that the variance within
each sample is not significantly different enough from the variance
between samples for them to be considered as representing popula-
tions with different means. Conversely, if the ratio is significantly
greater than one, 19 it can be inferred that the samples were drawn
from populations with different means. The formula for the analysis
of variance test is:
\
,,
" Li1_
J
,4
I'
T'
r4
-U.
r4-
r1
b
JT.
L
J-
SI
i.
I
-
I
N0--
-.
I
-TI
-IS
- *O7
'
I41-
.---
-u
SO
-It
N
a
4.
-r-
j
-14
II
7W'-
"
-Ia
-SI
U Li
Fig. 5.
SI
74
.
I
r
,4 ____1
,,4Z?,--7t -
1
-
/
/
-_.
4
.
/
- I
_- -f
-'05
1
----t I
I?
50
I
/
/
I
-U
'
U/
,j_
-.------
-iso
-is
1il
_/i
Values of Thornthwaite's Moisture Index
Summed Through the Mean Growing Season
13
k
nE (-)
2
1
F
1=1
kn
2
Among-sample variance
Within-sample variance
1
1=1
k(n
-
1)
where: n = total number of observations in all samples
k = number of samples
x = an individual mois1ure index
the mean of the i sample
= the mean of all sample means
This ratio follows the SF-distribution with (k - 1) and k(n - 1) degrees
of freedom.
RESULTS
The 639 counties which were retained for analysis were found
to have a mean of 37. 58 percent of their harvested cropland devoted
to corn. The standard deviation of this data was 14.10 perceht.
This yielded the following boundaries for the intensity classes:
Low Intensity - 0.00% to 23. 485%
Medium Intensity - 23. 485% to 51. 687%
High Intensity - 51. 687% to 100. 0%
These boundaries resulted in 86 counties being classed as low
intensity, 457 as medium intensity and 96 as high intensity (Table 3).
With the exception of Ottawa County, Ohio, Milwaukee and
Eau Claire counties, Wisconsin and St. Francois County, Missouri,
the low intensity corn producing counties are located along the western
margin of the study area.
The majority of these are outside the
14
boundary of the Corn Belt as defined by the Soil Conservation
Service.
With the sole exception of Hughes County, Nebraska, the
medium intensity corn producing class is one contiguous unit which
surrounds those areas of high intensity production.
The high intensity class shows a definite concentration through-
out the central portion of the study area. One group follows the
Missouri River from the southeast corner of South Dakota to the
northwest corner of Missouri and extends into portions of Iowa and
Nebraska. The largest single unit occurs in eastern Iowa and northwestern Illinois. Smaller units are found in Indiana and Ohio.
An
apparent anomaly occurs in southeastern Illinois where a high
intensity county (Gallatin) falls along the boundary of the study area.
The nine counties which were excluded because of excessive
irrigation form a contiguous unit in Nebraska which is bifurcated by
the Platte River. The counties which comprise this group include
Merrick, Polk, York, Hamilton, Clay, Hall, Buffalo, Kearney and
Dawson.
The distribution of the intensity classes varies somewhat from
what one would consider the theoretical situation to be. Ideally, each
class (though it need not be a solid unit) should be entirely surrounded
by the next lowest class. This is the case (with the above noted
exception) for the high intensity counties, but, medium intensity
15
counties are found to lie along the boundary of the study area
throughout most of its northern, eastern and southern extent. One
would expect only low intensity counties adjoining the boundary line in
a theoretical distribution.
There appears to be little or no logic in the distribution of the
values obtained by the summation of Thornthwaite's moisture index
through the mean 32°F growing season. Highly negative values occur
along the western margin of the study area in portions of South
Dakota, Nebraska and Kansas in the areas of low intensity corn
production. But, these are compensated for by positive values in
eastern Kansas, Oklahoma and west-central Missouri. Large dif-
ferences in these values are also exhibited throughout the areas of
medium and high intensity production. The greatest variation occurs
in east-central Missouri where Lincoln County has an index of -103
and Warren County one of 26.
The analysis of variance test gave an F-value of 0. 1 65 with 2
and 477 degrees of freedom. The tabled value of Fisher's Fdistribution at 2 and 477 degrees of freedom is 1.00. Since the
computed value is less than the theoretical, it must be concluded
that there is no difference in the means of the moisture indices drawn
from each of the three groups based on the intensity of harvested
cropland devoted to corn.
16
CONCLUSIONS
In view of the value obtained through the test of analysis of
variance it must be concluded that Thornthwaite's moisture index,
when summed through the mean 32°F growing season, is not a good
measure of the intensity to which harvested cropland is devoted to
corn within the study area. This does not infer that this index is
totally useless for this purpose. Perhaps some other summation
(for the entire year or the 50°F growing season) would produce more
meaningful results. However, under the conditions listed in this
study, the index proves to be quite meaningless.
Also, it can not be assumed that moisture is not important in
determining the distribution of corn production under natural
climatic conditions. The fact that so much of the corn acreage in
the western portion of the study area was irrigated immediately discounts this theory.
20
Perhaps, as Billings has inferred, when considering the distribution of any plant, one must examine the myraid of environmental
conditions which impose influences upon that plant.
21
Thornthwait&s
moisture index considers only a very few of these variables, and then
only in terms as to how they affect the moisture available for plant
growth. However, the onerous task required to satisfy Billings'
approach far exceeds the limits of this paper.
17
FOOTNOTES
R. F. Daubenmire, Plants and Environment (New York:
John Wiley and Sons, 1959) p. 3.
1
2 Carroll P. Wilsie, Crop Adaptation and Distribution
(San Francisco: W.H. Freeman, 1962) p. 133.
3 P. J. Kramer, "The Role of Water in the Physiology of
Plants," Advances in Agronomy, Vol. 11 (1959) pp. 51-70.
4 W.D. Billings, "The Environmental Complex in Relation to
Plant Growth and Distribution," Quarterly Review of Biology, Vol.
27 (September, 1952) pp. 251-264.
5 C.W. Thornthwaite and 3. R. Mather, "The Water Balance,"
Drexell Institute Publications in Climatology, Vol. 8, No. 1 (1955).
6 C.W. Thornthwaite, "An Approach Toward a Rational
Classification of Climate," Geographical Review, Vol. 38 (January,
1948) pp. 75-81.
7 For a review of the moisture studies prior to the development of Thornthwaite's moisture index see, Thornthwaite, p. cit.,
footnote 6, pp. 73-75.
8 For the logic behind this reduction see, Douglas B. Carter
and John R. Mather, "Climatic Classification for Environmental
Biology," C. W. Thornthwaite Associates Publications in Climatology,
Vol. 19, No. 4 (1966) p. 323.
9
lid.
10 For a detailed description of the method used to determine
these values see, Thornthwaite and Mather, . cit., footnote 5.
11 C.W. Thornthwaite Associates, "Average Climatic Water
Balance Data of the Continents," Publications in Climatology, Vol.
17, No. 3, Part 7 (1964).
12 Economic Research Service, Map of Generalized Types of
Farming in the United States (Washington, D. C.: Government
Printing Office, 1965).
I]
14 Figure 1 is to be used with this and each of the following
maps for determining the names of the counties within the study area.
15 This data was placed on computer punchcards and all of the
calculations which follow were done on an IBM 350 computer.
1 6 In a preliminary study with Nebraska data it was found that
in counties where more than 30 percent of the harvested acreage was
irrigated a significantly greater amount of land was devoted to corn
than in those counties for which this ratio was less than 30 percent.
17 This follows the work of Kimball, Went and others (see
bibliography) who consider there to be a temperature period during
which other environmental elements exert their greatest influence
upon plants.
18 See, Jerome C.R. Li, Statistical Inference I(Ann Arbor:
Edwards Brothers, 1964) p. 184 for the theory behind this test.
19 Tables are available which give the critical values of the
F-distribution. For example see, Li, 2 .2.'.i
20 See, Nebraska Department of Agriculture and Inspection,
Nebraska Agricultural Statistics Annual Report 1964 (Lincoln: StateFederal Division of Agricultural Statistics, 1966).
21
Billings,
.
cit.
APPENDIX
19
BIBLIOGRAPHY
1. W. D. Billings, "The Environmental Complex in Relation
to Plant Growth and Distribution," Quarterly Review of Biology,
Vol. 27 (September, 1952) pp. 251-264.
2. Douglas B. Carter and John R. Mather, "Climatic
Classification for Environmental Biology,' C.W. Thornthwaite
Associates Publications in Climatology, Vol. 19, No. 4 (1966).
3. R. F. Daubenmire, Plants and Environment (New York:
John Wiley and Sons, 1959).
Economic Research Service, Map of Generalized Types
of Farming in the United States (Washington, D. C.: Government
Printing Office, 1949).
4.
5. M.H. Kimball, "Plantclimates of California," California
Agriculture, Vol. 13 (May, 1959) pp. 7-12.
6. P. J. Kramer, "The Role of Water in the Physiology of
Plants," Advances in Agronomy, Vol. 11 (1959) pp. 51-70.
Jerome C.R. Li, Statistical Inference I(Ann Arbor:
Edwards Brothers, 1964).
7.
8. J. R. Mather, "The Climatic Water Balance," C.W.
Thornthwaite Associates Publications in Climatology, Vol. 14, No. 3
(1961).
9. Nebraska Department of Agriculture and Inspection,
Nebraska Agricultural Statistics Annual Report 1964 (Lincoln: StateFederal Division of Agricultural Statistics, 1966).
10. Soil Conservation Service, Land Resource Regions and
Major Land Resource Areas of the United States, Agricultural Handbook No. 296 (Washington, D.C.: Government Printing Office, 1965).
11. C. W. Thornthwaite, "The Climates of North America
According to a New Classification," Geographical Review, Vol. 21
(October, 1931) pp. 633-656.
20
"An Approach Toward A Rational Classification of Climate," Geographical Review, Vol. 38 (January, 1948)
pp. 75-81.
12.
13. ___________, "A Re-Examination of the Concept and
Measurement of Potential Evapotranspiration," Johns Hopkins
University Publications in Climatology, Vol. 7, No. 1 (1954)
pp. 200-210.
and J. R. Mather, "The Water Balance,"
Drexell Institute Publications in Climatology, Vol. 8, No. 1 (1955).
14.
15. C.W. Thornthwaite Associates, "Average Climatic Water
Balance Data of the Continents," Publications in Climatology,
Vol. 17, No. 3, Part 7 (1964).
16. U.S. Bureau of the Census, Map of County Boundaries as
of April 1, 1960 (Washington, D.C.: Government Printing Office,
1 960).
17. U.S. Bureau of the Census, 1964 Census of Agriculture
Preliminary Reports (Washington, D. C.: Government Printing
Office, 1966).
18. U. S. Weather Bureau, Climatography of the United States
No. 60 (Washington, D. C.: Government Printing Office, 1959).
19. F.W. Went, "The Response of Plants to Climate," Science,
Vol. 112 (October, 1950) pp. 489-494.
20. Carroll P. Wilsie, Crop Adaption and Distribution
(San Francisco: W.H. Freeman, 1962).
21
Table 1.-Percent of Total Harvested Acreage Devoted
to Corn (Total harvested acreage/acres
of corn harvested)
State
County
-- -
- -
Percent
r-
IlTUnois.
ADAMS
ALEXA
BOND
BOONE
BROWN
BUREA
CALHO
CARRO
CASS
CHAMP
CHRIS
CLARK
CLAY
CLINT
COLES
COOK
CRAWF
CUrvIBE
DE KA
DE WI
DOUGL
DU PA
EDGAR
EDWAR
EFFIN
FAYET
FORD
FRANK
FULTO
GALLA
GREEN
GRUND
HAM IL
HANCO
HARDI
HENDE
HENRY
IROQU
JACKS
State
County
Percent
-'-r----
44.1264Q5
29.446198
35.839569
53.454575
41.458344
62.592407
51.913940
55.859314
43.579849
46.623032
42.324921
38.520157
24.814682
36.330032
47.559921
35.422729
33.371674
38.602325
60.234360
48.998322
49.155609
46.782272
47.607727
44.320938
35.881958
32.217316
48.305069
28.476624
56.0267C3
60.313721
49.041992
51.472351
29.200607
47.477036
34.079468
59.402100
60.880112
47.370209
39.793365
Illinois (cont.)
JASPE 29.616501
JEFFE 27.103012
JERSE 44.187378
JO DA 42.789536
JOHNS37.295135
KANE
KANKA
KENDA
KNOX
LAKE
LAWRE
LA SA
LEE
LIVIN
LOGAN
MACON
MACOU
MADIS
MARIO
MARSH
MASON
MASSA
MC 00
MC LE
MENAR
MERCE
MQNRO
MONTG
MORGA
MOULT
OGLE
53.133820
4q.154221
59.588272
59.537659
31.626587
42.810684
57.143646
54.374893
51.579666
47.895721
45.215683
42.798391
30.420944
26.827866
55.595367
42.846603
36.568069
56.020294
55.370438
46.731461
65.650284
39.692810
41.104385
44.629684
44.849258
56.030869
PEORI 51.395386
PERRY 30. 444489
PIATT 44.834671
PIKE 50.308701
POPE 33.296600
PULAS 28.C53879
PUTNA 58.274L39
RANDO 37.099386
22
Table 1. cont.
$tate
County
Percent
Illinois (corit.)
RICHL 31.417786
ROCK 61.4O5807
S.ALIN 41.09'254
SANGA
SCHUY
SC0TT
SHELB
STARK
ST. C
STEPH
TAZEW
UNION
VERMI
WABAS
45.705750
45.082977
44.780991
43.783997
60.881699
31.180695
48.346451
54.983902
41.131149
43.938568
44.219101
W.ARRE 65.716248
WASHI
WAYNE
WHITE
WHITE
25.715256
29.816605
43.717133
62.216324
WILL
46.333527
WILLI 35.197876
WP'JE 53.444595
.W0ODF 60.422943
Indiana
ADAMS
ALLEN
8ARTH
BLACK
BOONE
BROWN
CARRO
CASS
CLARK
CLAY
CLINT
DAVIE
DEARB
DECAl
OE KA
DELAW
ELKHA
34.168228
34.106613
45.682892
34.400330
47.636459
47.304001
55.196030
51.811539
30.955765
40.219025
51.427261
44.815140
28.457581
46.669861
32.587555
40.499084
44.370270
State
County
Percent
Indiana (cont.)
FAYET 50. 5093 69
FLOYD 26 441895
F 0 IJ NT
44.096893
FRANK 47. 971573
FULTO 45.680069
GIBSO 50 . 321930
GRANT 40.433472
GREEN 43.417709
HAM IL
42. 877365
H A N CO
40.726196
HEN DR 44. 942917
HENRY 42.753860
HOW AR 47. 43 8034
HiJNTI 36. 06 9443
JACKS 38.976044
J ASPE 52 812347
J AY
30.485275
JEFFE 28.679672
JENNI 31. 1602 63
JOHNS 43 786987
KNOX 49.169235
K OS CI 47.294495
LAKE 47.189056
LA PD 43.971954
MAD IS 41 129074
MARIO 36.327194
MARSH 45.732422
MIAMI 46.939972
MONTG 51. 315765
MO R GA
NEWID
NOBLE
OWEN
PARKE
PIKE
PORTE
45. 704514
52.620514
42.794952
32.273071
48.706131
43.534027
44.030563
POS EY 49 546432
PULAS 45 192642
PUTNA 49. 08 1863
RANDO 38.213196
RI PL E 29.584824
RUSH 51.249954
23
Table 1
State
.
cont.
County
Percent
Indiana (cont.)
24.342682
45.554825
37.009644
47.927094
43.569839
40.216339
33.141342
47.197952
44.784195
55.372803
46.420746
49.383209
44.335922
44.021698
41.548325
36.157257
37.105515
47.607330
36.365585
WHiTE 48.760284
WHJTL 39.403366
Iowa
44.853607
44.755341
40.750214
33.285843
AUDUB54.161331
BENTO
BLACK
BOONE
BREME
BUCHA
BUENA
BUTLE
CALH0
CARRO
CASS
CEDAR
CERRO
CHERO
County
Percent
Iowa (cont.,)
SCOTT
SHELB
SPENC
STARK
ST. J
STUEB
SULL!
TIPPE
TIPTO
UNION
VANDE
VERMI
VIGO
WABAS
WARRE
WARRI
WASH!
WAYNE
WELLS
ADA1R
ADAMS
ALLAM
APPAN
State
54.986404
53.340622
49.655029
49.854324
1.785217
50.154358
54.644223
44.645642
52.973663
53.634872
57.372620
54.892181
52.632370
CHICK
CLARK
CLAY
CLAYT
CLINT
CRAWF
DALLA
DAVIS
DECAT
DELAW
DES M
DICK!
DLJBUQ
EMMET
FAYET
FLOYD
FRANK
FREMO
GREEN
GUND
GUTHR
HAMIL
HANCO
HARDI
HARRI
HENRY
HOWAR
HUMBO
IDA
IOWA
J.CKS
JASPE
iEFF
JOHNS
JONES
KEOKU
KOSSU
LEE
FLINN
LOUIS
LUCAS
51.85c619
36.908691
50.617920
45.976547
59.110886
47.544647
49.739914
36.027649
35.599701
51.943939
54.204803
51.621231
45.593796
50.365158
48.298523
53.209549
46.959610
58.361526
50.807205
55.505600
46.540482
52.681305
51.827301
54.638397
54.520981
55.219315
43.798691
50.854919
53.085419
53.043259
47.902100
54.349350
42.969528
53.817413
55.671616
50.611801
49.231125
50.162827
54.510498
55.842957
35.853668
24
Table 1. cont.
State
County
Percent
0 BRI
OSCEO
PAGE
PALO
PLYMO
POCAH
POLK
POTTA
POWES
RINGG
SAC
SCOTT
SHELB
SIOUX
STORY
TAMA
TAYLO
UNION
VANBU
WAPEL
WARRE
WASH!
WAYNE
WEBST
WINNE
WINNE
WOODB
WORTH
WPIGH
County
Percent
Kansas
Iowa (cont,,)
LYON
MADIS
MAHAS
MARIO
MARSH
MILLS
MITCH
MONON
MONRO
MONTG
MUSCA
State
54.131943
44.769058
51.875656
48.979507
55.581955
57.342163
52.552704
54.132797
36.874313
53.462189
53.666016
49.863068
51.451920
51.412659
49.597305
53.273209
57.793106
51.143250
56.010223
497447
36.180405
50.636261
72.637604
54.149536
57.92C578
53.538818
51.762863
39.385864
43.372086
37.022583
42.313980
44.966309
54.392273
33.707809
45.445938
51.894882
45.416992
54.018524
49.668777
50.701370
ALLEN 24.509445
ANDER 20.106689
ATCHI 28.391663
BOURB 22.438461
BRflWN 39.267624
CHERO 12.717592
CLAY
10.465258
CLOUD 8.446890
COFFE 14.398109
CRAWE 19.091949
4.361275
DECAl
DONIP 43.590439
DOUGL 25.346420
FRANK 19.684921
GREEN 9.251362
JACKS 19.997086
JEFFE 29.063431
JEWEL 6.498343
JOHNS 23.679489
LABEl 12.117612
LEAVE 29.171005
LINN 25.060822
LYON
15.180498
MARSH12.683898
MIAMI 25.103790
MONTG 13.843816
NEMAH 31.254623
NEOSH 21.787964
NORTO
3.221268
0SAGE15.65C964
PH1LL
3.261211
POTTA 14.302557
RAWLI
2.277858
REPUB 18.046219
RILEY 11.773020
SHAWN 23.820404
SMITH 4.387011
WABAU 10.085570
WASHI
8.953291
WILSO 17.871536
WOODS 11.105716
WYAND 25.160217
25
Table 1. cont.
State
County
Percent
North Dakota
State
County Percert
Minnesota (cont.)
RICHL 16.661087
S4RGE 12.443334
LTNCO
LYON
MARTI
MC LE
MEEKE
MOWER
MURRA
NOBLE
OLMST
OTTER
PIPES
POPE
Michigan
ALLEG
BARRY
BERRI
BRANC
CALHO
CASS
HILLS
JACKS
KALAM
LENAW
MONRO
ST. J
VAN B
WASHT
WAYNE
36.694427
33.743958
23.326233
45.911469
41.033142
2.623871
43.048874
38.141464
40.118210
40.861679
30.747635
41.430191
33.113922
37.04C344
24.402679
RAMSE 28. 811584
REOWO 46.566101
RENVI 42.264481
RICE 39.912186
ROCK
54.447098
SCOTT 40.844528
SIBLE 40.798859
STEAR 34.996140
STEEL 42.390732
STEVE 39.059189
Minnesota
BIGST
BLUE
BROWN
CARVE
32.105087
SWI FT 39.32 1289
44. 754761
TODD
TRAVE
WABAS
WASEC
WASHI
WATON
WILKI
WINON
WRIGH
YELLO
44. 32 0740
43.488861
CIPP 43.030212
COT TO
OAK UT
DOD GE
48.512985
35.514206
36.485535
DOUGL 28. 479370
F AR 18
45.097260
F ILL M
41. 217316
FREEB 45.7363 13
GOb OH 32 253860
GRANT 25.156906
HENNE 36.154388
HOUST 37. 345062
JACKS 51 633865
K AN D I
42.162735
51.345825
53.487366
40.108246
38.710175
39.643524
49.45g595
49.539948
39.453476
22.828461
49.437302
33.492722
41. 0 28809
LAC Q 39.40 1260
LE SU 39 647614
32.673767
19.784317
33.541031
46.163635
34.084015
50.983871
10.633242
35.661713
40.940323
45.718704
Missouri
ADAIR 27.23C194
ANDRE 34.308517
ATCHI 66. 299942
AUDRA 31.319946
BARTO 19.838425
BATES 27.752670
2 G
Table 1. corit.
State
County
Percent
Missouri (cont.)
State
Percent
Missouri (cont..)
MONRO
MONTG
MORGA
NODAW
OSAGE
PERRY
PETIT
PIKE
PLATT
PUTNA
RALLS
RANDO
BENTO 26.460892
BOLL I 29.295151
BOONE 29.846909
TBUCHA 30.298294
CALLA 31.437943
CAPE 35.974976
CARRO 36.992371
CASS 33.863068
CEDAR 20.622696
CHADW 29.279953
CHART 35.410080
CLARK 41.775742
CLAY 40.057983
CLiNT 34.104782
COLE 30.149307
CUOPE 41.156326
DADE 20.634613
DAV1E 28.265076
DE KA 29.963135
FRANK 35.512253
GASCO 32.800293
GENTR 28.412827
GRUND 32.662704
RAY
SALIN
SCHUY
SCOTL
SHELB
ST. C
ST. C
SI. F
ST. L
STE.
SULLI
VERNO
WARRE
WORTH
HARRI 29.00 5249
HENRY 20.908722
HOLT 55.253815
HOW AR 44.896042
JACKS 38.965881
J ASP E
20. 200256
J EFFE
2. 275894
28.497314
29.058289
44.156738
16.571518
38.161575
42;398285
27.368469
30.C84244
27.290421
34.825653
JOHNS
KNOX
LAFAY
LAWRE
LEWIS
LINCL
LTNN
LIVIN
MACON
MARIO
County
MERCE 2'.l524l
MONIT 35.629349
29.713516
34.689438
30.363770
39.916489
33.589294
39.274612
35.908722
40.582565
33.829834
25.091293
28.781052
30.357346
42.223267
47.485626
27.479935
33.912598
32.148422
37.229996
19.317642
21.550064
29.376862
40.412949
24.811646
21.972900
36.632492
26.550476
Nebraska
ADAMS
ANTEL
BOONE
BOYD
BUFFA
18.784485
48.324524
35.857620
24.674728
36.666397
BURT 55.025497
BUTLE 36.545227
CASS 3ó.681564
CEDAR 4.124619
CLAY
COLFA
CDMIN
CUSTE
18.368942
44.059036
55.361938
30.597839
27
Table 1. cont.
State
County
Percent
Nebraska (cont.)
DAWS0 41.962540
DIXON 55.873749
0000E 47.290680
DOUGL 64.803970
F1LLM 21.073853
FRANK 20.128769
FRONT 12.277770
FURNA 14.927279
GAGE
18.147949
CREEL 33.596100
GOSPE 22.145599
HALL
54.555649
HAMIL 39.919556
HARLA 13.982814
HAYES 23.819885
HITCH 14.088613
HOLT
11.361634
HOWAR 33.987793
JEFFE 12.194276
JOHNS 30.513458
KEARN 32.676865
KEVA
6.365078
KNOX 37.964462
LANCA 13.412309
LINCO 17.834473
MADIS 46.708618
MERRI 54.219818'
NANCE 29.569031
NEMAH 44.756958
NUCKO 15.822714
UTOE 39.742722
PAWNE 24.429886
PIERC 49.937164
PLAIT 34.431549
POLK
32.473633
RED W 15.827256
RICHA 47.752213
ROCK
1.580793
SALIN 19.306824
SARPY 60.624817
SAUND 43.254333
SEWAR 27.874313
State
County
Percent
Nebraska (cont.,)
SHERM 23.001373
ST.ANT 53.271408
THAYE 13.106930
THURS 51.925980
VALLE 33.114075
WASHI 50.638763
WAYNE 51.371826
WEBST 12.897921
WHEEL
.390455
YORK
39.344193
Ohio
ALLEN
AUGLA
BROWN
BUTLE
CHAMP
CLARK
CLERM
CLINT
35.699753
35.842300
27.821976
48.002472
43.203369
44.233582
27.716187
49.729279
CRAWF36.877C'75
DARKE
DEFIA
DELAW
ERIE
FAIRF
FAYET
FRANK
FULTO
GREEN
HAMIL
HANCO
HARDI
HENRY
HIGHL
HOCKI
HURON
KNOX
LOGAN
LICKI
LUCAS
MADIS
41.496216
25.121078
35.676605
31.164688
40.051300
42.007935
36.087738
45.642303
51.454285
50.282883
37.031845
36.384933
34.770538
38.719376
32.695374
29.394730
35.817978
34.851517
34.086029
26.723602
41.725555
Table 1.
(cont.,)
State
County
Ohio (cont..)
MAR10
MERCE
MIAMI
MONTG
MORRO
OTTAW
PAULD
PERRY
PICKA
PREBL
PUTNA
RICHL
Percent
SANDU
SENEC
SHELB
UNTON
VAN W
WARRE
WILLI
WOOD
WYAND
40.415421
35.983002
44.104706
45.477402
30.594055
15.885091
27.115781
28.880753
45.164261
54.641663
31.C57693
28.581741
43.644836
31.224640
33.372070
34.297592
36.567734
32.490936.
42.077072
33.602539
33.414108
37.324127
CRAIG
HUGHE
MAYES
MC IN
MUSKO
NUWAT
OKFUS
OKMUL
OTTAW
ROGER
TULSA
WAGON
WASHI
4.604335
6.637018
5.227081
5.100485
3.924349
6.845325
5.464095
6.135866
5.446508
4.312735
5.123413
4.638718
4.499737
R0SS
State
County Percent
South Dakota (corit..)
BON H
BROOK
BUFFA
CHARL
CLARK
CLAY
CODIN
DAVIS
DAY
DEVEE
DOUGL
GRANT
GREGO
HAMLI
HANSO
HUTCH
JERAU
KINGS
LAKE
LINCO
MARSH
MC CO
MINER
MINNE
MOODY
ROBER
SANBO
TURNE
UNION
YANKT
Oklahoma
South Dakota
AUROR 32.576721
BEADL 27.383820
44.959518
44.659363
15.738695
33.261292
23.835144
53.166595
16.397232
40.658401
11.826658
28.420670
42.783188
26.299362
27.042328
31.845932
44.471344
47.254288
24.744202
38.35200's
50.952667
54.817932
18.820663
50.160614
36.260574
56.257294
53.580368
21.081818
34.024002
51.415451
50.680542
50.746185
Wisconsin
BUFFA 28.476959
CRAWF 25.521072
DUNN
28.001144
EAU C 21.942474
GRANT 36.442963
GREEN 35.498047
IOWA 33.012161
JACKS 26.664856
KENOS 35.506592
29
Table 1
State
.
cont.
County
Percent
Wiscon1n (contj
LA CR 33.533905
LAF.AY 40.891464
MILWA
MONRO
PEPIN
PIERC
RAC1N
RICHL
19.591919
25.489929
27.869873
30.972412
33.919235
26.159607
SAUK
32.821259
TREMP 26.448181
VERNO 23.765457
30
Table 2. - Extreme Dates of the Mean 32°F Growing Season and Values of Thornthwait&s
Moisture Index Summed Through This Growing Season for Selected Stations
in the Study Area
City
County
Mean Date of
Last Spring
Frost
Illinois
Cairo
Carlinville
Chicago
Alexander
Macoupin
Cook
Dixon
Effingham
Effingham
Greenville
Bond
Harrisburg
La Salle
Lincoln
Monmouth
Saline
La Salle
Logan
Warren
Mount Carroll
Mt. Vernon
Carroll
Paris
Peoria
Pontiac
Roc]cford
Rushville
Springfield
Urdana
Indiana
Brookville
Evansville
Fort Wayne
Indianapolis
Lafayette
Sacamonia
South Bend
Terra Haute
Vincennes
Wabash
Winamac
Iowa
Algona
Ames
Belle Plaine
Burlington
Clarinda
Davenport
Denison
Des Moines
Lee
Jefferson
Edgar
Peoria
Livingston
Ogle
Schuyler
Sangamon
Champaign
Franklin
Vanderburgh
Allen
Marion
Tippecanoe
Jay
St. Joseph
Vigo
Knox
Wabash
Pulaski
Kossuth
Boone
Benton
Des Moines
Page
Scott
Crawford
Polk
Mean Date of
First Fall
Moisture
Index
Frost
April 29
April 22
April 19
May 3
April 22
April 18
April 16
May 1
April 29
April 25
May 7
April 15
April 29
April 22
April 24
May 6
April 19
April 8
April 23
November 1
October 17
October 28
October 6
October 15
October 25
October 19
October 9
October 15
October 16
October 3
October 19
October 18
October 16
October 18
October 6
October 20
October 30
October 21
May 5
April 2
April 24
April 17
April 27
May 8
May 3
April 11
April 14
May 4
May 4
October 6
November 4
October 20
October 27
October 12
October 7
October 16
October 28
October 23
October 11
October 12
-110
April 15
May 1
May 3
April 20
April 30
April 12
May 5
April 20
October 19
October 9
October 5
October 16
October 10
October 24
October 4
October 19
-6
-165
-39
-41
-66
-76
-18
-40
-116
-72
-78
-71
-47
-79
-69
-109
-73
-42
-22
-35
39
-61
-24
-47
-75
-76
-38
-15
-47
-77
-30
-21
-28
-20
-17
-61
-53
31
Table 2. cont.
City
County
Mean Date of
Last Spring
Frost
Mean Date of
First Fall
Moisture
Index
Frost
Iowa (cont.)
Dubuque
Fairfield
Greenfield
Guthrie Center
Inwood
Iowa Falls
Le Mans
Logan
Mason City
Mount Ayr
Oskaloosa
Pocahontas
Post Ville
Rockwell City
Sioux City
Spencer
Washington
Waterloo
April 19
April 29
April 29
May 3
May 10
May 4
May 7
May 1
May 8
April 30
April 28
May 7
May 6
May 5
April 28
May 9
May 4
April 26
October 19
October 10
October 10
October 6
September 28
October 2
October 2
October 9
October 3
October 13
October 11
October 4
October 4
October 9
October 12
October 3
October 4
October 9
Phillips
Shawnee
April 15
April 10
April 16
April 19
April 22
April 14
April 9
April 23
May 8
April 17
April 26
April 9
October 23
October 25
October 24
October 22
October 17
October 26
October 26
October 16
October 2
October 23
October 15
October 26
Washtenaw
Wayne
Berrien
Hillsdale
Kalamazoo
May 2
April 25
May 4
May 11
May 9
October 17
October 23
October 22
October 4
October 9
-80
-97
Freeborn
Bigstone
May 3
May 17
May 13
October 6
September 23
September 25
-24
-112
-107
Dubuque
Jefferson
Adair
Guthrie
Lyon
Hardin
Plymouth
Harrison
Cerro Gordo
Ringgold
Mahaska
Pocahontas
Clayton
Calhoun
Woodbury
Clay
Washington
Black Hawk
18
-29
-16
-26
-79
-32
-69
-40
-40
17
56
-38
-10
-41
-144
-59
-56
-27
Kansas
Burlington
Chanute
Concordia
Emporia
Horton
Independence
lola
Manhattan
Oberlin
Ottawa
Phillipsburg
Topeka
Coffey
Neosho
Cloud
Lyon
Brown
Montgomery
Allen
Riley
Decator
FrankLin
23
27
-152
-19
-14
-1
73
-64
-237
28
-183
-26
Michigan
Ann Arbor
Detroit
Eau Claire
Hilisdale
Kalamazoo
Minnesota
Albert Lea
Beardsley
Fergus Falls
Otter Tail
-33
-93
-72
32
Table 2. cont.
City
County
Mean Date of
Last Spring
Frost
Minnesota (cont)
Hutchinson
Long Praire
Minne apolis -
Mean Date of
First Fall
Moisture
Index
Frost
McLeod
Todd
May 13
May 16
September 29
September 23
-135
St. Paul
Hennepin
Red Wing
Rochester
Goodhue
April 30
May 2
May 15
May 9
May 8
May 8
May 7
May 7
October 13
October 11
September 29
September 29
October 6
September 29
October 6
October 4
-91
-31
-51
-72
-139
-93
-41
-43
April 12
April 26
April 19
April 9
April 24
April 11
April 16
April 13
April 5
April 21
April 13
April 19
April 22
April 8
April 2
April 13
April 12
April 16
October 24
October 11
October 15
October 24
October 11
October 23
October 16
October 20
October 31
October 19
October 24
October 17
October 13
October 28
November 8
October 22
October 25
October 21
May 5
May 11
May 1
May 8
May 10
April 25
May 5
April 26
May 9
April 29
April 29
October 3
September 26
October 8
September 30
October 1
October 15
October 7
October 9
October 2
October 6
September 30
St. Cloud
Tracey
Wilimar
Winnebago
Worthington
Olmstead
Stearns
Lyon
Kandiyohi
Faribault
Nobles
-97
Missouri
Appleton City
Bethany
Chillicothe
Columbia
Elsberry
Hannibal
Jackson
Jefferson City
Kansas City
Kirksville
La Mar
Macon
Maryville
St. Joseph
St. Louis
Sedalia
Warrensburg
Warrenton
Nebraska
Alma
Broken Bow
Columbus
Curtis
Ewing
Fairbury
Fairmont
Falls City
Gothenburg
Grand Island
Greeley
St. Clair
Harrison
Livingston
Boone
Lincoln
Marion
Cape Girardeau
Cole
Jackson
Adair
Barton
Macon
Novaway
Buchanan
St. Louis
Pettis
Johnson
Warren
Harlan
Custer
Platte
Frontier
Holt
Jefferson
Fillmore
Richardson
Dawson
Hall
Greeley
54
6
95
21
-103
-34
-1
-22
-31
46
89
6
80
-13
26
16
-14
26
-173
-210
-89
-174
-141
-68
-121
-32
-185
-141
-137
33
Table 2. cont.
City
County
Mean Date of
Last Spring
Frost
Nebraska (cont)
Hartington
Kearney
Lincoln
Mc Cook
Nebraska City
Norfolk
North Platte
Omaha
Osceola
Red Cloud
Tecumseh
Waithill
Mean Date of
First Fall
Moisture
Index
Frost
May 3
May 1
April 20
May 3
April 26
May 4
April 30
April 14
May 1
May 1
April 25
May 5
October 7
October 6
October 17
October 6
October 13
October 3
October 7
October 20
October 7
October 4
October 7
October 4
-191
-127
-110
-207
April 25
April 15
April 17
April 19
May 7
-99
-65
-101
-79
-82
-90
Fayette
May 9
April 17
May 1
April 24
May 4
April 28
October 15
October 25
October 30
October 25
October 5
October 11
October 6
October 30
October 12
October 25
October 7
October 12
Muskogee
Okemah
Okmulgee
Tulsa
Ottawa
Muskogee
Olduskee
Okmulgee
Tulsa
April 4
March 31
March 30
April 1
March 31
October 27
November 1
November 15
October 30
November 2
-7
South Dakota
Academy
Armour
Charles Mix
Douglas
May 11
May 8
May 13
May 11
May 8
May 5
May 4
May 7
May 5
September 26
September 30
September 27
September 25
September 28
October 2
September 30
September 30
October 1
-165
-156
-148
-140
-182
-212
-207
-162
-136
Cedar
Buffalo
Lancaster
Red Willow
Otoe
Madison
Lincoln
Douglas
Polk
Webster
Johnson
Thurston
-38
-152
-252
-84
-94
-145
-52
-50
Ohio
Chillicothe
Cincinnati
Columbus
Dayton
Lancaster
Lima
Mansfield
Sandusky
Sidney
Toledo
Upper Sandusky
Washington C.H.
Oklahoma
Miami
Brookings
De Smet
Cannvalley
Gregory
Huron
Milbank
Mitchell
Ross
Hamilton
Franklin
Montgomery
Fairfield
Allen
Richland
Erie
Shelby
Lucas
Wyandot
Brookings
Kingsbury
Buffalo
Gregory
Beadle
Grant
Davison
May3
-20
-76
-69
-107
-74
-113
104
36
13
7
Table 2. cOnt.
City
County
Mean Date of
Last Spring
Frost
South Dakota (cont)
Sioux Falls
Tyndall
Watertown
Webster
Wentworth
Wisconsin
Blair
Minnehaha
Bon Homme
Codington
Day
Lake
Darlington
Eau Claire
Trempealeau
Lafayette
Eau Claire
La Crosse
La Crosse
Milwaukee
Virogiia
Milwaukee
Vernon
Mean Date of
First Fall
Moisture
Index
Frost
May 5
May 3
May 17
May 18
May 14
October 3
October 3
September 27
September 23
September 29
-116
-122
-128
-100
-99
May 19
May 12
May 5
May 1
April 20
May 6
September 24
September 29
October 4
October 8
October 25
October 5
-52
-15
12
-43
-44
13
35
Table 3.- Intensity Classes
State County
Low Intenslty
Percent Cropland
Moisture
Planted to Coma
inclexb
TO 23.485 PERCENT
20.107
NDER
22.4.38
BOURB
12.718
CHERO
10.465
CLAY
8.447
KS CLOUD
14.398
KS COFFE
19.092
KS CRAWF
4.361
KS DECAT
19.685
KS FRANK
9.251
KS GREEN
19.997
KS JACKS
6.498
KS JEWEL
12.118
KS LABET
15.180
KS LYON
12.684
KS MRSH
13.844
KS. MONTG
21.788
KS NEOSH
3.221
KS NORTO
J5.65l
KS OSAGE
0.0
KS
KS
KS
KS
KS
KS
KS
KS
KS
KS
KS
KS
KS
KS
MG
MN
MN
MN
MS
MS
MS
MS
MS
0
0
0
0
.
PHILL
POTTA
RAWLI
REPUB
RILEY
SMITH
WABAU
WASHI
WILSO
WOODS
BERRI
OTTER
TRAVE
WILKI
BARTO
CEDAR
DADE
HENRY
JASPE
MS LAWRE
MS ST. C
MS ST. F
-152
23
-237
0
0
0
-1.
0
-1
27
0
0
-183
3.261
14.303
2.278
0
0
-64
11.773
4.387
10.086
8.953
17.872
- ....
0
0
....11.1c6.---.-
23.326
22.828
19.784
10.633
19.838
20.623
20.635
2O.909
20.200
16.572
19.313
21.550
--0
-33
0
------- ........
0
0
0
-14
-103
26
0
36
Table 3. cont.
State County
Percent Cropland Moisture
Indexb
Planted to Coma
Low Intensitj (cont.)
MS VERNO
NB ADAMS
NB FILLM
NB FRANK
NB FRONT
NB FURNA
NB GAGE
NB GOSPE
NB HARLA
NB HITCH
NB HOLT
NB JEFFE
NB KEVA
NB LANCA
NB LINCO
NB NUCKO
NB RED W
NB ROCK
NB SAL IN
NB THAVE
NB WEBST
NB WHEEL
ND RICHL
-:ND SARGE
OH OTTAW
0K CRAIG
OK HUGHE
OK MAYES
OK MC IN
UKMUSK0
OK NOWAT
UKFUS
OKMUL
OTTAW
ROGER
TULSA
WAGON
WASHI
BUFFA
SD CODIN
OK
OK
0K
OK
0K
OK
OK
SD
SD DAY
21.973
lS.784
21.074
0
0
-174
20.f29-12.278
14.927
18.143
[37
13.983
0
11.362
-68
0
0
0
12194
6.365
13.412
17.834
15.823
15.827
1.581
19.307
13.107
12.898
9.390
16.661
-110
0
0
o
0
0
-90
12.443 -----..015.885
0
6.637
5.227
5.100
0
0
54413
6.845
6.136
_5.447
4.313
5.123
4.639
15.739
16.397
11.827
0
104
0
0
-182
-]o
37
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Moisture
Indexb
Low Intensity (cant.)
SD MARSH
SD ROBER
WS EAU C
WS MILWt
Medium ifl!tV
18.821
21.082
0
21 .°42
12
19.592
-41t
23.48510 51.Ô87PERCENT
IL
IL
ADAMS
ALEXA
BOND
1L
BROWN
IL
IL
CASS
IL CHAMP
IL CHRIS
IL
IL
IL
IL
IL
IL
IL
CLARK
CLAY
CLINT
COLES
COOK
CRAWF
CUMBE
IL
DE WI
IL
IL
1L
IL
IL
DOUGL
IL
IL
FAYET
IL
IL
FRANK
GREEN
DU PA
EDGAR
EDWAR
EFF IN
FORD
IL GRUND
IL HAM IL
IL HANCO
IL HARDI
IL
1L
IL
IL
IL
IROQU
JACKS
JASPE
JEFFE
JERSE
44.126
29.446
35.840
41.458
43.580
46.623
42.325
38.520
24.815
36.330
47.560
35.423
33.372
38.602
48.998
49.156
46.782
47.608
44.321
35.882
32.217
48.305
28.477
51.472
2920F
47.477
0
;-165
-18
---O
0
0
0
0
-41
0
0
0
0
-76
0
0
0
0
0
0
34 079O
47.370
39.793
29.617
27.I03
44.187
0
0
47
0
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Moisture
Indexb
Medium Intensity (cont.,)
IL
JO DA
IL JOHNS
IL KANKA
42.790
37.295
0
0
0
0
0
49.I. 54
IL LAKE
IL LAWRE
IL LIVIN
31.627
1L LOGAN
IL MACON
IL MACOU
51.580
-109
47.89&
72
IL MADIS
1L
MARIO
IL MASON
MASSA
IL MENAR
1L
42.81l
45.216
42.788
30.421
26.828
42.847
IL RANDO
IL RICHL
1L
41.094
MONRO
IL MONTG
IL MORGA
IL
iL
MOULT.
PEORI
IL PERRY
IL PIATT
IL PIKE
POPE
IL PULAS
1L
SALIN
IL SANGA
1L
IL
1L
1L
1L
SCHUY
SCOTT
SHELB
ST. C
STEPH
IL UNION
IL VERM I
IL WABAS
1L WtSHI
IL WAYNE
IL WHITE
IL WILL
IL WILLI
0
0
0
0
0
0
0
36 .568
46.731
39.693
41.104
44.630
44.849
51.395
30.444
44.835
50.309
33.297
28.054
37.089
31.418
IL
0
45.706
45.083
44.781
43.784
31.181
48.346
41.131
43.939
44.219
25.7l5
29.817
43.717
46.334
35.198
0
0
0
0
0
0
-22
-42
0
0
- ...............
0
0
0
0
0
0
0
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Medium Tntenjj
IN
IN
IN
TN
IN
IN.
IN
1N
IN
1N
IN
IN
IN
IN
IN
TN
IN
IN
IN
IN
IN
IN
IN
IN
(contj
ADAMS
ALLEN
BARTH
BLACK
BOONE
BROWN
CLARK
CLAY
CLINT
DAVIE
DEARB
DECAT
DE KA
DELAW
ELKHA
FAYET
FLOYD
FOUNT
FRANK
FULTO
GIBSO
GRANT
GREEN
HAMI[
HANCO
HENDR
HENRY
IN
IN
IN
IN HOW AR
IN HUNTI
IN
Moisture
Indexb
JACKS
IN JAY
IN JEFFE
IN JENNI
IN JOHNS
IN KNOX
IN KOSCI
IN LAKE
1N LA PU
IN MADIS
IN MARIO
IN MARSH
34.168
34.l07
45.683
34.400
47.636
47.304
30.956
40;219
51.427
44.815
28.458
46.670
32.583
40.499
44.370
50.509
26.442
44.097
0
-61
0
0
0
0
0
0
0
0
0
0
0
0
0
47.72
-110
45.680
50.322
40.433
43.418
42.877
40.726
44.943
42.754
47.438
36.069
38.976
30.485
28.680
31.160
43.787
49.169
47.294
47.189
0
0
97
41.129
36.327
45.732
0
0
0
0
0
00
0
-75
0
0
-15
0
4
0
-24
0
LI1
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Moisture
Indexb
Medium fln!tT (cont.)
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
1N
MIAMI
MONTG
MORGA
NOBLE
OWEN
PARKE
PIKE
PORTE
POSEY
PULAS
PUTNA
RANDO
RIPLE
RUSH
SCOTT
SHELB
SPENC
STARK
ST. J
STUEB
SULLT
TIPPE
TIPTO
VANDE
VERMI
VIGO
WABAS
WARRE
WARRI
WASHI
IN
IN
IN
IN WAYNE-
IN WELLS
IN WHITE
IN
IA
IA
IA
IA
IA
iA
IA
WHITL
ADAIR
ADAMS
ALLAM
APPAN
BOONE
BREME
BUENA
46.940
51.316
0
0
42.795
32.273
48.706
43.534
44.031
49.546
45.193
48.082
38.213
29.585
51.250
24.343
45.555
37.0i0
47.927
43.570
40.216
33.141
47.198
44.784
46.421
49.383
44.336
44.022
41.548
36.157
37.106
47.607
36.366
48.760
39.403
0
45.705O
44.755
40.750
33.286
49.655
49.854
50.154
0.
0
-77
0
00
0
0
0
-47
0
39
-38
0
0
0
0
0
0
0
0
0
41
Table 3
.
(cont,)
State County
Percent Cropland
Planted to Coma
Moisture
Indexb
Medium Intensity (cont.)
IA
IA
IA
IA
IA
IA
IA
IA
IA
TA
IA
IA
IA
1A
IA
14
IA
IA
IA
IA
IA
l.A
IA
IA
IA
CALHO
CLARK
CLAY
CLAYT
CRAWF
DALLA
DAVIS
DECAT
DICKI
DUBUQ
EMMET
FAYET
FRANK
GREEN
GUTHR
HOWAR
HUMBO
JACKS
JEFFE
KEOKU
KOSSU
LEE
LUCAS
MADIS
MARIO
1AMONRO
IA 0 BRI
IA OSCEO
l.A
PAGE
14 PALO
lA POLK
IA POWES
IA
RINGG
IA
IA
IA
IA
SAC
TAYLO
UNION
VANBU
WAPEL
WARRE
IA WAYNE
IA WEBST
IA
IA
44.846
36.909
50.618
45.977
47.545
49.740
36.028
51.621
-4l
0
-59
-10
-61
0
0
0
l8
50.365
48.299
46.960
50.807
46.540
43.799
50.855
47.902
42.970
50.612
49.231
35.854
44.769
48.980
36.874
49.863
51.452
51.413
49.597
51.143
49.867
36.180
0
0
0
-26
0
0
-29
0
-6
0
0
0
--0
-20
-38
17
50.6
360
39.386
0
43.372
37.023
44.966
33.703
45.446
0
0
0
42
Table 3. cont.
-
State County
----
.-
---
-- -
Percent Cropland
Planted to Corna
Moisture
Indexb
Medium Intensitl (cont.)
IA
IA
IA
KS
WINNE
WORTH
WRIGH
ALLEN
KS ATCHI
KS BROWN
KS DONIP
KS DOUGL
KS JEFFE
KS JOHNS
KS LEAVE
KS LINN
KS MIAMI
KS NEMAH
KS SHAWN
KS WYAND
MG
MG
MG
MG
MG
MG
ALLEG
BARRY
BRANC
CALHO
CASS
HILLS
MGJACKS
45.417
49.669
50.701
24.509
:28.302
39.268
43.590
25.346
29.063
23.679
29.171
25.061
25.104
31.255
23.820
25.160
36.694
33.744
73
0
-14
0
0
0
0
O
0
0
0
0
0
45.-911
41.033
42.624
43.049
38.141
40.118
40.862
30.748
41.430
33.114
37.040
24.403
32.105
44.755
MG
MG
MG
MG
MG
MG
MG
MN
MN
MN
KALAM
LENAW
MONRO
ST. J
VAN B
WASHT
WAYNE
BIGST
BLUE
BROWN
MN
MN
MN
MN
MN
CARVE
43.489
CHIPP
COTTO
DAKOT
DODGE
43030
MN DOUGL
MN FARIB
MN FILLM
0
0
48.513
35.514
36.486
28.479
45.097
41.217
0
-93
o
- --------
-72
0
0
-97
0
0
0
0
0
-41.
43
Table 3. cont.
State County
Medium Intensi
(ont.)
MN FREEB
MN G000H
MN GRANT
MN HENNE
MN HOUST
MN JACKS
MN KANDI
MN LAG Q
MN LE SU
MN LINGO
MN LYON
'MN MC LE
MN MEEKE
MN MOWER
MN MURRA
MN NOBLE
MN OLMST
'MN PIPES
MN POPE
MN RAMSE
MN REDWO
MN RENVI
MN RICE
'MN SCOTT
MN SIBLE
MN STEAR
MN STEEL
MN STEVE
MN SWIFT
MN TODD
MN WABAS
MN
MN
MN
MN
OH
OH
MN
MN
MS
MS
WASEC
WASHI
WATON
WINON
LO GAN
LICK I
WRIGH
YELLO
ADAIR
ANDRE
Percent Cropland
Planted to Coma
45.735
32.254
25.157
36.154
37.345
51.634
41.029
39.401
39.648
42.163
51.346
38.710
39.644
49.460
49.54O
39.453
49.437
33.493
28.812
46.566
42.264
39.912
40.845
40.799
34.996
42.391
39.059
39.321
33.541
4&.164
34.084
50.984
35.662
Molsturp
'nclex3
-24
-31
0
--91
0
0'
-93
0
0
0
-139
0
0
-51
0
0
0
0
0
72
0
0
0
0
0
0
0
34. 8 52
34.086
40.940
45.719
0
27.2 30
0
0
34.309
0
Table 3 .
cont.
State County
Percent Cropland
Planted to Coma
Medium
Moisture
Indexb
(cont.)
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
AUDRA
BATES
BENTO
BOLLI
BOONE
BUCHA
CALLA
CAPE
CARRO
CASS
CHADW
CHAR 1
CLARK
CLAY
MS CL INI
MS COLE
MS COOPE
MS DAVIE
MS DE KA
MS FRANK
MS GASCO
MS GENTR
MS GRUND
MS HARRI
MS HOWAR
MS JACKS
MS JEFFE
MS JOHNS
MS KNOX
MS LAFAY
MS LEWIS
MS LINCL
MS LINN
MS LIVIN
MS MACON
MS MARIO
MS MERCE
MS MONIT
MS MONRO
MS MONTG
MS MORGA
31.320
27.753
26.461
29.295
29.847
30.293
31.433
35.975
36.992
33.863
29.280
35.410
0
0
2I
-13
-i
0
0
0.
0
0
40.053
34.105
30.149
-22
41 .1 56
28.265
29.963
35.512
-32.800
28.413
32.66329.005
44.896
38.966
29.275
28.497
29.058
44.157
38.16?
42.398
27.363
30.084
27.290
34.825
---.
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
95
-34
0
0
26..TI59
35.629
29.714
34.689
30.364
0
0
80
45
Table 3. cont.
S tate County
Percent Cropland
Planted to Coma
Mo sture
Indexb
Medium Intensity (cont.)
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
MS
NODAW
OSAGE
PERRY
PETTI
PIKE
PLATT
PUTNA
RALLS
RANDO
RAY
SALIN
MSSCHUY
MS
MS
MS
MS
MS
SCOTL
SHELB
ST. C
ST. L
STE.
SULLI
MS WARRE
MS WORTH
MS
NB ANTEL
NB BOONE
NB BOYD
NB BUTLE
NB
CASS
39.916
33.589
39.275
_35.909
40.583
33.830
25.091
28.781
30.357
42.223
47.486
27.480
33.913
32.143
37.230
29.377
40.413
24.812
36.632
26.553
48.325
35.858
24.675
36.545
36.682
0
16
0
0
0
0
0
0
0
0
0
0
26
0
0
0
-191
0
NBCEDAR
NB COLFA
NB CUSTE
NB DODGE
NB GREEL
NB HAYES
NB HOWAR
NB JOHNS
NB KNOX
NB MADIS
NB NANCE
NB NEMAH
NB OTOE
NB PAWNE
NB PIERC
NB PLAIT
44.059
-210
30.598 --------0
47.2°1
-121
33.596i4
23.820
-141.
33.98
30.513
37.964
46.709
29.569
44.757
39.743
24.430
49.937
34.432
0
-252
0
0
-38
0
-89
-207
46
Table 3.
cont1
State County
Percent Cropland
Planted to Corna
Moisture
Indexb
Medium Intensity (cont.)
NB RICHA
NB SAUND
NB SEWAR
NB SHERM
NBVALLE
NB WASHI
NB WAYNE
OH
OH
OH
OH
OH
OH
OH
ALLEN
AUGLA
BROWN
BUTLF
CHAMP
CLARK
CLERM
OH CL TNT
OH CRAWF
OH DARKE
OH DEFIA
OH DELAW
OH ERIE
OH FATRF
OH FAYET
0H FRANK
OH FULTO
OHGREEN
OH
OH
OH
OH
OH
HAM IL
HANCO
HARDI
HENRY
HIGHL
0H HOCKI
OH
OH
OH
OH
OH
OH
OH
HURON
KNOX
LUCAS
MADI S
MARIO
MERCE
MIAMI
OHMONTG
OH MORRO
OH PAULO
47.752
43.254
27.874
28.001
0
0
0
51.372
35.700
35.842
27.822
48.002
43.203
44.234
27.716
49.729
36.877
41.496
25.121
-0
31.165
-113
33.1140
50.639
-145
0
0
0
0
0
0
0
-76
35677
4005U
42.008
36.088
45.642
51.454
50.283
37.032
36.385
34771
38.719
32.695
29.395
35.818
26.724
41.726
40.415
35.983
44.105
45.477
30.594
27.176
0
-O
-65
0
-
0
e
0
-107
0
0
0
0
47
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Medium
Moisture
Indexb
(cont.)
OH PERRY
OH PICK.A
OH PUTNA
0H RICHL
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
SD
SD
SD
SD
SD
SD
SD
ROSS
SANDU
SENEC
SHELB
UNION
VAN W
28.881
45.164
31.058
28.582
43.645
31.225
33.372
34.293
36.56.3
33.603
WOOD
33.414
BEADL
BUN H
BROOK
CHARL
CLARK
DAVIS
SD DEVEE
SD DOUGL
SD GRANT
SD GREGO
-SD HAMLI
SD H.ANSO
0
-99
0
-69
0
32.491
42.077
WARRE
WiLL I
WYAND
AUROR
0
0
32.577
27.384
44.960
44.659
33.261
23. 835
0
0
0
0
-207
-122
148
-165
0
40.658
28.421
42.783
26.299
27.042
31.846
44.471
-136
24.744
38.352
50.953
50.161
36.261
0
0
-156
-162
-212
0
SD HUTCH
SD JERAU
KINGS
LAKE
SD
SD
SD
SD
SD
SD
SD
MC CO
MINER
SANBO
TURNE
UNION
SD YANKT
WS BUFFA
WS
WS
WS
CRAWF
DUNN
GRANT
-gg
0
0
34C24O
51.415
0
50.681
0
50.746
28.477
25.521
28.001
36.443
0
.--.. ......
0
0'
0
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Nedlluj
Moisture
Indexb
Intensity (cont..)
WS GREEN
WS iOWA
WS JACKS
WS .KENOS
WS
WS
WS
WS
LA CR
LAFAY
MONRO
PEPIN
WSPTERC
WS
WS
WS
WS
WS
High Intensity
RACIN
RICHL
SAUK
TREMP
VERNO
35.498
33.012
26.665
35.507
0
0
40.891
25.490
27.870
30.972
33.919
-15
32.821
26.448
23.765
0
0
33.534-43
0
0
13
51.68710 100.0 PERCENT
BOONE
BUREA
IL CALHO
IL CARRO
IL DE KA
IL FULTO
IL GALLA
1L HENDE
IL HENRY
IL KANE
IL KENOA
53.455
62.592
51.914
55.259
60.234
ILKNOX
IL
1L
IL
1L
IL
IL
IL
1L
IL
1L
IL
LA SA
LEE
MARSH
MC 00
MC LE
MERCE
OGLE
PUTNA
ROCK
0
0
0
60.314
0
0
0
60.880
0
59.5 88
0
59.538
57.144
-116
55.595
0
56. 027
594C20
656500
582740
55.370
0
56.031
-73
61.406
0
54.984
65.716
-78
1LSTARK
IL
IL
TAZEW
WARRE
0
49
Table 3. cont.
State County
Percent Cropland
Planted to Corn8-
I ntens I t
Moisture
Indexb
(c ont.)
WHITE
WINNE
IL WOODF
IN CARRO
IN CASS
IN JASPE
IN NEWTO
IN UNION
IL
IL
IA .AUDUB
IA BENTO
IA BLACK
IA
IA
BUCHA
BUTLE
IA
IA
LA
LA
IA
IA
IA
IA
IA
IA
IA
IA
IA
CRR0
IA
IA
IA
IA
IA
1A
IA
IA
IA
1A
IA
CASS
CEDAR
CERRO.
CHERU
CHICK
CLINT
DELAW
DES N
FLOYD
FREMO
GRUND
HAMIL
HANCO
HARDI
HARRI
HENRY
IDA
IOWA
JASPE
JOHNS
JONES
LINN
LOUIS
1A LYON
IA M4HAS
IA MARSH
1A MILLS
62.216
0
C
60.42.3
0
55.196
51.812
0
52.621
55.373
54.161
0
0
54.86
53.341
51.785
54.844
52.974
53.635
57.373
54.892
52.632
51.860
59.U1
51.944
54.2C5
53.210
58.362
55.506
52.681
51.827
54.638
54.521
-27
0
0
-40
0
0
o
0
-28
0
0
0
-32
-40
55.2190
53.085
0
53043
5434g
-0--
53.817
55.672
54.510
55.843
0
0
0
o
0
55.582
57.342
0
0
54.13279
51.876
56
50
Table 3. cont.
State County
Percent Cropland
Planted to Coma
Hig
Intensity (cont.)
IA
IA
IA
IA
TA
IA
IA
IA
IA
IA
IA
IA
IA
IA
IA
MITCH
MONON
MONTG
MUSCA
PLYMO
POCAH
POTTA
SCOTT
SHELB
SIOUX
STORY
TAMA
WASHI
WINNE
WOODB
MN MARTI
MN ROCK
MS ATCHI
MS HOLT
NB BURT
NB CUMIN
NB DIXON
NB DOUGL
NB SARPY
NB STANT
NB THURS
OI1 PREBL
SD LAY
SD LINCO
SD MINNE
SD MOODY
a
b
Moisture
Indexb
52.553
54.133
53.462
53.666
0
0
57.793
56.O10
72.638
54.15O
57.921
53.539
51.763
0
0
-17
0
0
54392
51.895
54.019
53.487
54.447
66.300
55.254
55.025
55.362
55.874
64.804
60.625
53.?71
51.926
54.642
53.167
54.818
56.257
53.580
Acres of Corn Harvested
Total Acres Harvested'
Summed through the mean 32°F growing season
0
0
0
89
-31
0
-185
-84
0
-50
0
0
--0
-116