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A soil-climate index to predict corn yield
Agricultural Systems 18 (1985) 227-237
A Soil-Climate Index to Predict Corn Yield* K. R. O l s o n Department of Agronomy, University of Illinois, Urbana, Illinois, 61801, USA
& G. W. Olson Department of Agronomy, Cornell University, Ithaca, New York, 14853, USA SUMMARY Rainfall-soil storage (RAINSTOR) equations were developed and refined by fitting various combinations of RAINSTOR against measured corn yield. Separate equations are needed to reflect both water stress (droughty and ponding) conditions. The most limiting value (maximum stress) was used in the calculation of RAINSTOR index values. The RAINSTOR index is a good parameter for predicting corn yield on nearly level soils in the udic moisture regime of New York State. The initial correlation analyses showed a marginal relationship between rainfall and corn yield (r z = 0.13). After using the rainfall-soil storage equations, the RAINSTOR versus corn yield relationship dramatically improved (r2=0.80). The RAINSTOR equation was tested at two additional sites and the r2 was equal to 0"61 and 0.70, respectively.
INTRODUCTION The qualitative dependence of corn plant development upon weather is universally accepted. However, this dependency has been difficult to document satisfactorily, because of the complex plant, environment, management and soil interactions. * Contribution from the Department of Agronomy, New York State College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14853, USA. Agronomy Paper No. 1487. 227 Agricultural Systems 0308-521X/85/$03"30 © Elsevier Applied Science Publishers Ltd, England, 1985. Printed in Great Britain
228
K. R. Olson, G. W. Olson
The amount of available soil moisture in the crop-root zone has been considered a rational and direct parameter for evaluating the effect of weather on agricultural crops. Parks & Knetsch (1959), Gardner (1960), Denmead & Shaw (1962) and Baier & Robertson (1968) have shown that the loss of soil moisture is a joint function of the atmospheric energy which causes evaporation from the soil and plant transpiration surfaces, and the soil moisture available to supply this atmospheric demand. Shaw (1974) showed that excess spring moisture would substantially reduce yield. Morris (1972) made an extensive review of the literature concerning the physiochemical effects of wet conditions on soils and plants. He derived excess moisture, along with moisture stress indexes, by using a simulated model for rainfall infiltration, redistribution of water throughout the soil profile and moisture balance in the soil depending on atmospheric demand. De LaRosa et al. (1981) developed polynomial equations to predict the yield of wheat, corn and cotton in Spain using multiple regression analysis. The r 2 varied from 0.56 to 0.84. Soil properties utilized included clay content, depth to hydromorphic features, carbonate content, salinity, sodium saturation and cation exchange capacity. Studies have shown that silt and organic matter content of a soil layer have significant positive correlation with available water percentage (Bartelli & Peters, 1959). Other factors, however, should also be considered in estimating the soil moisture regime of a soil series. These include surface texture, root ramification zone, moisture conductivity and depth to free water. Associated land features, such as slope and shape of soil surfaces, affect the amount of rainfall, that effectively recharges the soil moisture supply (Hillel & Hornberger, 1979). The objective of this study is to develop a rainfall-water storage index (RAINSTOR) which can be used to predict annual corn yields for nearly level soils under both excessively dry and wet conditions. MATERIALS A N D METHODS
Experimental treatments The measured corn yield plots were located on Lima loam (fine-loamy, mixed, mesic Glossoboric Hapludalf), Niagara Variant silt loam (finesilty, mixed, mesic Aeric Hapludalf) and Raynham Variant silt loam
A soil-climate index to predict corn yield
229
(coarse-silty, mixed, calcareous, mesic Aeric Haplaquept) soils. The Niagara Variant and Raynham Variant soils were tile drained. The nearly level experimental sites were located at the Agronomy farm near Aurora, New York (Lima loam), Canton Agricultural and Technical College at Canton, New York (Niagara Variant), and at Miner Institute farm near Chazy, New York (Raynham Variant silt loam). Much of the corn yield data were collected by the Cornell Plant Breeding and Agronomy Departments as part of the commercial hybrid corn field trials or as part of corn rotation and maximum corn yield experiments. Moisture was measured and yields were adjusted to 15.5 ~o moisture for all hybrids. The mean averages for all hybrids were used as the yield values for each plot area location.
Soil sample analyses The particle size distribution of the less than 2mm fraction was determined using the pipet method and sand sieving (Dower & Olson, 1980). Bulk density was measured using Saran coated undisturbed clods at 33 k Pa (Olson, 1979). Two different methods were used for determining soil moisture. The 33 kPa values were determined for Saran coated clods. The 1.5 MPa moisture data were obtained for sieved (less than 2 mm) samples. Water retention difference (WRD) was the weight in grams of water retained in one cubic centimeter of whole soil between 33 kPa and 1.5 MPa tension (Soil Survey Staff, 1972).
RESULTS A N D DISCUSSION Consistent differences in corn yields can be attributed to differences in the rainfall conditions for the geographical area and the water storage capacity of the soil. A preliminary examination of the corn yields and rainfall data for the Aurora plot area (Table 1) suggests that yields under identical management were depressed under both droughty (years 1964 and 1965) and very wet (year 1974) conditions. The correlation analyses showed an r z of 0" 13 between rainfall and corn yield. The resulting linear equation had an intercept of 5.1 and a coefficient of 0.05. The rainfall period used in the equation was from May 1st to August 31st. The rainfall data for September and October were eliminated because heavy rains in those
K. R. Olson, G. W. Olson
230
TABLE 1 C o r n Yields, Rainfall a n d R A I N S T O R D a t a at the A u r o r a Plot A r e a ( L i m a Soil)
Year
Corn yieM (Mg/ha)
Rainfall (cm)
RA I NSTO R (cm)
1962 1963 1964 1965
8'03 7.15 3'58 3.76
25.76 24.79 15-04 16.30
- 10.16 - 6.20 - 38-20 - 25.91
1966 1974 1975 1977 1978 1979 1980
6"84 5"39 8"28 7.40 7.65 7-21 6"96
25"93 58"67 44.30 28.70 33-27 33'53 32.26
- 2.54 - 15.49 + 3.15 - 12.45 - 7.87 - 7.62 - 8.89
1981
8"03
36"07
- 5-08
months did not significantly depress or increase yields. In New York State the months of September and October are not normally droughty. The first step in calculating the water storage capacity of a soil was to determine the rooting depth. If no root-restricting layers were present, a maximum rooting depth of 1 m was used for corn. Restrictive barriers considered included bedrock (lithic or paralithic), fragipans and dense basal till. Horizons with less than 10~o silt and clay can be rootrestricting. However, they were not excluded due to the very low water storage contribution and potential lateral textural changes within the soil horizons. Gleyed horizons were not considered root restrictive if they were within l m of the surface, since a tile drainage system was a management requirement and did lower the water table. The available water (water retention difference) in a soil was assumed to be the water held in tension by the soil between the field capacity (33kPa) and the wilting point (1.5 MPa). Water retention difference values include corrections for rock fragments. The amount of water stored in a soil depends on the amount held per unit volume of soil and the depth of soil from which plants can extract their water. The pore sizes which can actually retain water (that plants can utilize) are primarily between 0.5#m and 50#m in diameter (Olsom 1985). Both the rainfall and water storage capacity of a soil need to be combined in equations in order to improve the correlation with crop
A soil-climate index to predict corn yield
231
yield. In addition, both droughty and ~ponding conditions must be considered. The following equations were developed to fit the rainfall, storage, and crop yield data.
Rainfall-soil storage equations 1.
Drought Equation (Water Stress) ( F I * R ) + S - (F2*E) = O
2.
Ponding Equation (Water Stress) (F2*E) - ( E l * R ) = P
Where: D = d r o u g h t index (cm); E = e v a p o t r a n s p i r a t i o n from a pan (cm); F1 = run-off or run-in coefficient; F2 = canopy evaporation coefficient; P = ponding index; R = rainfall (cm) from May I st to August 31 st and S = total available water-holding capacity (cm). The values of D and P can be positive or negative. The maximum water stress situation (lowest number) was the value chosen. I f D is greater than, or equal to, P, then choose P. If D is less than P, then select D. The soil profile was assumed to be saturated on May 1st, a c o m m o n situation in New York State. The run-in coefficient (F1) was assumed to be 1.0 for a well-drained soil on nearly level slope (0 to 2 ~ ) . The F1 coefficient is for soils with slopes less than, or equal to 2 ~o. Adjustments were made for poorly-drained laterally recharging (run-in) sites (F1 = 1-3). The evapotranspiration coefficient (F2) was calculated to be (0.76) for the period from May 1st to August 31 st due to the lower than measured pan evapotranspiration effects attributed to a lower plant canopy in May and June. This F2 value (0.76) provided the best fit of the experimental data. The rainfall-soil storage equations were developed and refined by statistically testing various combinations of storage and corn yield data for the nearly level Aurora plot area (Lima soil). Included in Table 1 are the corn yield, rainfall and R A I N S T O R data for the plot area. The total evapotranspiration from May 1st to August 31st was 46cm, after an adjustment for an early canopy effect. The final R A I N S T O R versus corn yield data (Fig. 1) had an intercept of 8.14, a coefficient of 0.13 and an r 2
K. R. Olson, G. W. Olson
232
r 2 - .80 Y-8.14÷O.13X I
-40
I
-30
~2
I
-20
I
-10
(
I
0
10
RAINSTOR (cm)
Fig. 1. R A I N S T O R effects on c o r n yields at A u r o r a plot area.
equal to 0.80. Obviously, R A I N S T O R was a much better prediction parameter than rainfall (r 2 = 0" 13) for the corn yields at the A u r o r a plot area. Two independent sites were then selected to test the R A I N S T O R variable as a predictor of corn yields. The first test site selected was the nearly-level Canton plot area with Niagara Variant soil. A total of 19 years of corn yield and climate data were available for the site. The soil was sampled and tested. The rooting depth was determined to be 95 cm and the water storage capacity, 16 cm. Table 2 contains the corn yields, rainfall and R A I N S T O R data for the Canton plot area. The initial correlation analyses showed an r 2 of 0.03 between rainfall and corn yield. After using the rainfall-soil storage equations to calculate R A I N S T O R values, the R A I N S T O R versus corn yield relationship had an r 2 of 0.70 (Fig. 2). The second test site selected was the nearly-level Miner plot area with R a y n h a m Variant soil. Corn yields and climate data were available for nine years. The soil was characterized and the rooting depth was determined to be 100 cm and the water storage capacity was calculated to be 23cm. The plot area was in a depression with a significant lateral recharge. A 30~o increase in effective rainfall was projected to be
TABLE 2 C o r n Yields, Rainfall a n d R A I N S T O R D a t a at the C a n t o n Plot Area ( N i a g a r a Variant Soil)
Year
Corn yield ('M,g/ha)
Rainfall (cm)
RAINSTOR (cm)
1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1974 1975 1976 1977 1978 -1979 1980 1981
6.23 6-60 4.84 4.97 6.04 8.36 6.98 7.86 7.29 5.85 4.34 3.90 6-10 6.10 7-11 5.91 4.91 5.47 6.35
29.89 34-90 36.37 25.25 32.02 31.12 29-31 38.71 34.62 34.01 50.77 39.09 22.71 48.64 32-36 31-75 29.21 27,68 35,56
+0.18 + 5-18 - 9.19 - 4.47 - 0.25 + 9.02 + 5.49 + 7-01 + 4.90 + 4.29 - 5-05 - 6-63 - 7.01 - 2.92 + 2.64 + 0.23 - 1-91 - 1.96 + 3.23
•10 8
r 2 =
•
0, 2
.70
Y=6.03+0,19X I -10
I -5
I 5
0 RAINSTOR
I 10
(cm)
Fig. 2. R A I N S T O R effects o n c o r n yields at C a n t o n plot area.
234
K. R. Olson, G. W. Olson TABLE 3
Corn Yields, Rainfall and RAINSTOR Data for the Miner Plot Area (Raynham Variant Soil) Year
Corn yield (Mg/ha)
Rainfall" (cm)
1973 1974 1975 1976 1977 1978 1979 1980 1981
2.00 3.64 9.79 9.16 8-66 8.28 6.77 6.84 6.77
51.1 34.8 21.1 42.4 27.7 24.9 25-7 21.8 45.5
RAINSTOR (cm) + + + + + + -
22.52 4"65 3.02 10.46 9-65 9,42 8.97 4.01 13.28
"Value increased by 30 ~o to reflect lateral recharge. a p p r o p r i a t e . This was d o n e b y increasing the coefficient in 0.05 i n c r e m e n t s until the m a x i m u m r 2 c o r r e l a t i o n b e t w e e n rainfall a n d c o r n yield o c c u r r e d . T h e r 2 w a s e q u a l to 0.31 with a 30 ~ increase in effective rainfall ( T a b l e 3). A f t e r using the r a i n f a l l - s o i l s t o r a g e e q u a t i o n s to calculate R A I N S T O R values, the R A I N S T O R versus c o r n yield r e l a t i o n s h i p h a d an r 2 o f 0.61 (Fig. 3). 12-
u.i 7.
/
8-
r 2 = .61
Y= 6 . 7 7 + 0 . 1 7 X
! -20
I -10
0
RAINSTOR
Fig. 3.
I 10
i 20
(cm)
RAINSTOR effects on corn yields at Miner plot area.
A soil-climate index to predict corn yield
235
The calculated R A I N S T O R values did prove to be a much better indicator of corn yields than rainfall for the initial and both test plots. The r 2 values were improved from the 0.03 to 0.31 range for rainfall to between 0-61 and 0.80 for R A I N S T O R . The equations were developed for one soil and location but tested at two distant sites located in New York State. Monthly rainfall data for the May 1st to August 31st period did provide a reliable data base for predicting corn yields in the humid climate of New York State. One would expect that daily, rather than monthly, rainfall and R A I N S T O R data might be better, but an initial check at the Aurora plot area did not significantly improve the r 2 value from the 0-80 for monthly data (was 0.83). In addition, daily weather summaries are more difficult to obtain and utilize. They may also require a computer to analyze up to 20 years of daily weather data for each site and they are not readily available in all parts of the world.
CONCLUSIONS The depth to which roots of corn plants can ramify is quite important. In New York State many soils have root-restricting barriers, including bedrock, fragipans and dense basal till. The total water storage capacity (available water) of a soil can be significantly reduced when rootrestricting layers are present. Soil porosity, bulk density, 33 kPa moisture and 1-5 MPa moisture tests were run to determine rooting depth, rooting volume and the total a m o u n t of water stored in pores (50 #m to 5 #m in diameter). Both droughty and ponding conditions were considered.The most limiting value (maximum stress) was used in the calculations. When the water storage capacity of the soil is combined with the rainfall and evapotranspiration data, this variable (RAINSTOR) becomes a good parameter for predicting yearly corn yields in the udic moisture regime of New York State. After using the rainfall-soil storage (RAINSTOR) equations the R A I N S T O R versus corn yield relationship had an,r 2 = 0.80 for the Aurora plot area. The R A I N S T O R parameter was tested at two additional sites with 18 and 9 years of corn yield and climate data. The r 2 was 0.70 and 0.61, respectively, suggesting the R A I N S T O R parameter was quite useful for predicting yearly corn yields for nearly level soils in New York State.
236
K. R. Olson, G. W. Olson ACKNOWLEDGEMENTS
The authors wish to acknowledge Drs R. F. Lucey, W. D. Pardee and R. B. Musgrave for permitting the use of their corn yield data. Dr B. A. Pack provided the climatic data for the plot areas. Dr G. W. Fick helped in the development of rainfall-soil storage equations.
REFERENCES Baier, W. & Robertson, G. W. (1968). The performance of soil moisture estimates as compared with the direct use of climatological data for estimating crop yields. Agr. Meteorol., 5, 17-31. Bartelli, L. J. & Peters, D. B. (1959). Integrating soil moisture characteristics with classification of some Illinois soils. SoilSci. Soc. Am. Proc., 23, 149.-51. De LaRosa, D. F., Cardona, F. & Almorza, J. (1981). Crop yield predictions based on properties of soils in Sellilla, Spain. Geoderma, 25, 267 74. Denmead, O. T. & Shaw, R. H. (1962). Availability of soil water to plants as affected by soil moisture content and meteorological conditions. Agron. J., 45, 385-90. Dower, M. M. & Olson, K. R. (1980). Revised pipet method oJparticle size analysis. Agron. Mimeo 80-17, Dept. of Agronomy, Cornell Univ., Ithaca NY. 7pp. Gardner, W. R. (1980), Dynamic aspects of water availability to plants. Soil Sci., 89, 63-73. Hillel, D. & Hornberger, G. M. (1979). Physical model of the hydrology of sloping heterogeneous fields. Soil Sci. Soc. Am. J., 43, 434-9. Morris, R. A. (1972). Simulation-model-derived weather indexes Jbr regressing Iowa corn yields on soil management and climatic Jactors. Unpublished. PhD dissertation. Library, Iowa State Univ., Ames. 312 pp. Olson, K. R. (1979). Saran coated method jbr determining bulk densities, soil moisture values and coelfi'cient of linear extensibility. Agron. Mimeo 79 5, Dept. of Agron., Cornell Univ., Ithaca NY. 6pp. Olson, K. R. (1983). Soils and climate effects on yieldsJbr assessment evaluations. Unpublished PhD Thesis, Dept. of Agron., 'Cornell Univ., Ithaca NY. 324 pp. Olson, K. R. (1985). Characterization of pore size distributions within soils by mercury intrusion and water release methods. Soil Sci., 139, 400-4. Parks, W. L. and Knetsch, J. L. (1959). Corn yields as influenced by nitrogen level and drought intensity. Agron. J., 51, 363~,. Shaw, R. H. (1974). A weighted moisture stress index for corn in Iowa State. J. Res., 49, 101-14. Soil Survey Staff (1972). Soil survey laboratory methods and procedures ./'or
A soil-climate index to predict corn yield
237
collecting soil samples. Soil Survey Investigations Report No. 1. Soil Conservation Service, US Dept. of Agric., Gov't. Printing Office, Washington DC. 50 pp. Thompson, L. M. (1963). Weather and technology in the production of corn and soybeans. CAED Report 17. The Center for Agricultural and Economic Development, Iowa State Univ., Iowa. 46 pp.
A Soil-Climate Index to Predict Corn Yield* K. R. O l s o n Department of Agronomy, University of Illinois, Urbana, Illinois, 61801, USA
& G. W. Olson Department of Agronomy, Cornell University, Ithaca, New York, 14853, USA SUMMARY Rainfall-soil storage (RAINSTOR) equations were developed and refined by fitting various combinations of RAINSTOR against measured corn yield. Separate equations are needed to reflect both water stress (droughty and ponding) conditions. The most limiting value (maximum stress) was used in the calculation of RAINSTOR index values. The RAINSTOR index is a good parameter for predicting corn yield on nearly level soils in the udic moisture regime of New York State. The initial correlation analyses showed a marginal relationship between rainfall and corn yield (r z = 0.13). After using the rainfall-soil storage equations, the RAINSTOR versus corn yield relationship dramatically improved (r2=0.80). The RAINSTOR equation was tested at two additional sites and the r2 was equal to 0"61 and 0.70, respectively.
INTRODUCTION The qualitative dependence of corn plant development upon weather is universally accepted. However, this dependency has been difficult to document satisfactorily, because of the complex plant, environment, management and soil interactions. * Contribution from the Department of Agronomy, New York State College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14853, USA. Agronomy Paper No. 1487. 227 Agricultural Systems 0308-521X/85/$03"30 © Elsevier Applied Science Publishers Ltd, England, 1985. Printed in Great Britain
228
K. R. Olson, G. W. Olson
The amount of available soil moisture in the crop-root zone has been considered a rational and direct parameter for evaluating the effect of weather on agricultural crops. Parks & Knetsch (1959), Gardner (1960), Denmead & Shaw (1962) and Baier & Robertson (1968) have shown that the loss of soil moisture is a joint function of the atmospheric energy which causes evaporation from the soil and plant transpiration surfaces, and the soil moisture available to supply this atmospheric demand. Shaw (1974) showed that excess spring moisture would substantially reduce yield. Morris (1972) made an extensive review of the literature concerning the physiochemical effects of wet conditions on soils and plants. He derived excess moisture, along with moisture stress indexes, by using a simulated model for rainfall infiltration, redistribution of water throughout the soil profile and moisture balance in the soil depending on atmospheric demand. De LaRosa et al. (1981) developed polynomial equations to predict the yield of wheat, corn and cotton in Spain using multiple regression analysis. The r 2 varied from 0.56 to 0.84. Soil properties utilized included clay content, depth to hydromorphic features, carbonate content, salinity, sodium saturation and cation exchange capacity. Studies have shown that silt and organic matter content of a soil layer have significant positive correlation with available water percentage (Bartelli & Peters, 1959). Other factors, however, should also be considered in estimating the soil moisture regime of a soil series. These include surface texture, root ramification zone, moisture conductivity and depth to free water. Associated land features, such as slope and shape of soil surfaces, affect the amount of rainfall, that effectively recharges the soil moisture supply (Hillel & Hornberger, 1979). The objective of this study is to develop a rainfall-water storage index (RAINSTOR) which can be used to predict annual corn yields for nearly level soils under both excessively dry and wet conditions. MATERIALS A N D METHODS
Experimental treatments The measured corn yield plots were located on Lima loam (fine-loamy, mixed, mesic Glossoboric Hapludalf), Niagara Variant silt loam (finesilty, mixed, mesic Aeric Hapludalf) and Raynham Variant silt loam
A soil-climate index to predict corn yield
229
(coarse-silty, mixed, calcareous, mesic Aeric Haplaquept) soils. The Niagara Variant and Raynham Variant soils were tile drained. The nearly level experimental sites were located at the Agronomy farm near Aurora, New York (Lima loam), Canton Agricultural and Technical College at Canton, New York (Niagara Variant), and at Miner Institute farm near Chazy, New York (Raynham Variant silt loam). Much of the corn yield data were collected by the Cornell Plant Breeding and Agronomy Departments as part of the commercial hybrid corn field trials or as part of corn rotation and maximum corn yield experiments. Moisture was measured and yields were adjusted to 15.5 ~o moisture for all hybrids. The mean averages for all hybrids were used as the yield values for each plot area location.
Soil sample analyses The particle size distribution of the less than 2mm fraction was determined using the pipet method and sand sieving (Dower & Olson, 1980). Bulk density was measured using Saran coated undisturbed clods at 33 k Pa (Olson, 1979). Two different methods were used for determining soil moisture. The 33 kPa values were determined for Saran coated clods. The 1.5 MPa moisture data were obtained for sieved (less than 2 mm) samples. Water retention difference (WRD) was the weight in grams of water retained in one cubic centimeter of whole soil between 33 kPa and 1.5 MPa tension (Soil Survey Staff, 1972).
RESULTS A N D DISCUSSION Consistent differences in corn yields can be attributed to differences in the rainfall conditions for the geographical area and the water storage capacity of the soil. A preliminary examination of the corn yields and rainfall data for the Aurora plot area (Table 1) suggests that yields under identical management were depressed under both droughty (years 1964 and 1965) and very wet (year 1974) conditions. The correlation analyses showed an r z of 0" 13 between rainfall and corn yield. The resulting linear equation had an intercept of 5.1 and a coefficient of 0.05. The rainfall period used in the equation was from May 1st to August 31st. The rainfall data for September and October were eliminated because heavy rains in those
K. R. Olson, G. W. Olson
230
TABLE 1 C o r n Yields, Rainfall a n d R A I N S T O R D a t a at the A u r o r a Plot A r e a ( L i m a Soil)
Year
Corn yieM (Mg/ha)
Rainfall (cm)
RA I NSTO R (cm)
1962 1963 1964 1965
8'03 7.15 3'58 3.76
25.76 24.79 15-04 16.30
- 10.16 - 6.20 - 38-20 - 25.91
1966 1974 1975 1977 1978 1979 1980
6"84 5"39 8"28 7.40 7.65 7-21 6"96
25"93 58"67 44.30 28.70 33-27 33'53 32.26
- 2.54 - 15.49 + 3.15 - 12.45 - 7.87 - 7.62 - 8.89
1981
8"03
36"07
- 5-08
months did not significantly depress or increase yields. In New York State the months of September and October are not normally droughty. The first step in calculating the water storage capacity of a soil was to determine the rooting depth. If no root-restricting layers were present, a maximum rooting depth of 1 m was used for corn. Restrictive barriers considered included bedrock (lithic or paralithic), fragipans and dense basal till. Horizons with less than 10~o silt and clay can be rootrestricting. However, they were not excluded due to the very low water storage contribution and potential lateral textural changes within the soil horizons. Gleyed horizons were not considered root restrictive if they were within l m of the surface, since a tile drainage system was a management requirement and did lower the water table. The available water (water retention difference) in a soil was assumed to be the water held in tension by the soil between the field capacity (33kPa) and the wilting point (1.5 MPa). Water retention difference values include corrections for rock fragments. The amount of water stored in a soil depends on the amount held per unit volume of soil and the depth of soil from which plants can extract their water. The pore sizes which can actually retain water (that plants can utilize) are primarily between 0.5#m and 50#m in diameter (Olsom 1985). Both the rainfall and water storage capacity of a soil need to be combined in equations in order to improve the correlation with crop
A soil-climate index to predict corn yield
231
yield. In addition, both droughty and ~ponding conditions must be considered. The following equations were developed to fit the rainfall, storage, and crop yield data.
Rainfall-soil storage equations 1.
Drought Equation (Water Stress) ( F I * R ) + S - (F2*E) = O
2.
Ponding Equation (Water Stress) (F2*E) - ( E l * R ) = P
Where: D = d r o u g h t index (cm); E = e v a p o t r a n s p i r a t i o n from a pan (cm); F1 = run-off or run-in coefficient; F2 = canopy evaporation coefficient; P = ponding index; R = rainfall (cm) from May I st to August 31 st and S = total available water-holding capacity (cm). The values of D and P can be positive or negative. The maximum water stress situation (lowest number) was the value chosen. I f D is greater than, or equal to, P, then choose P. If D is less than P, then select D. The soil profile was assumed to be saturated on May 1st, a c o m m o n situation in New York State. The run-in coefficient (F1) was assumed to be 1.0 for a well-drained soil on nearly level slope (0 to 2 ~ ) . The F1 coefficient is for soils with slopes less than, or equal to 2 ~o. Adjustments were made for poorly-drained laterally recharging (run-in) sites (F1 = 1-3). The evapotranspiration coefficient (F2) was calculated to be (0.76) for the period from May 1st to August 31 st due to the lower than measured pan evapotranspiration effects attributed to a lower plant canopy in May and June. This F2 value (0.76) provided the best fit of the experimental data. The rainfall-soil storage equations were developed and refined by statistically testing various combinations of storage and corn yield data for the nearly level Aurora plot area (Lima soil). Included in Table 1 are the corn yield, rainfall and R A I N S T O R data for the plot area. The total evapotranspiration from May 1st to August 31st was 46cm, after an adjustment for an early canopy effect. The final R A I N S T O R versus corn yield data (Fig. 1) had an intercept of 8.14, a coefficient of 0.13 and an r 2
K. R. Olson, G. W. Olson
232
r 2 - .80 Y-8.14÷O.13X I
-40
I
-30
~2
I
-20
I
-10
(
I
0
10
RAINSTOR (cm)
Fig. 1. R A I N S T O R effects on c o r n yields at A u r o r a plot area.
equal to 0.80. Obviously, R A I N S T O R was a much better prediction parameter than rainfall (r 2 = 0" 13) for the corn yields at the A u r o r a plot area. Two independent sites were then selected to test the R A I N S T O R variable as a predictor of corn yields. The first test site selected was the nearly-level Canton plot area with Niagara Variant soil. A total of 19 years of corn yield and climate data were available for the site. The soil was sampled and tested. The rooting depth was determined to be 95 cm and the water storage capacity, 16 cm. Table 2 contains the corn yields, rainfall and R A I N S T O R data for the Canton plot area. The initial correlation analyses showed an r 2 of 0.03 between rainfall and corn yield. After using the rainfall-soil storage equations to calculate R A I N S T O R values, the R A I N S T O R versus corn yield relationship had an r 2 of 0.70 (Fig. 2). The second test site selected was the nearly-level Miner plot area with R a y n h a m Variant soil. Corn yields and climate data were available for nine years. The soil was characterized and the rooting depth was determined to be 100 cm and the water storage capacity was calculated to be 23cm. The plot area was in a depression with a significant lateral recharge. A 30~o increase in effective rainfall was projected to be
TABLE 2 C o r n Yields, Rainfall a n d R A I N S T O R D a t a at the C a n t o n Plot Area ( N i a g a r a Variant Soil)
Year
Corn yield ('M,g/ha)
Rainfall (cm)
RAINSTOR (cm)
1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1974 1975 1976 1977 1978 -1979 1980 1981
6.23 6-60 4.84 4.97 6.04 8.36 6.98 7.86 7.29 5.85 4.34 3.90 6-10 6.10 7-11 5.91 4.91 5.47 6.35
29.89 34-90 36.37 25.25 32.02 31.12 29-31 38.71 34.62 34.01 50.77 39.09 22.71 48.64 32-36 31-75 29.21 27,68 35,56
+0.18 + 5-18 - 9.19 - 4.47 - 0.25 + 9.02 + 5.49 + 7-01 + 4.90 + 4.29 - 5-05 - 6-63 - 7.01 - 2.92 + 2.64 + 0.23 - 1-91 - 1.96 + 3.23
•10 8
r 2 =
•
0, 2
.70
Y=6.03+0,19X I -10
I -5
I 5
0 RAINSTOR
I 10
(cm)
Fig. 2. R A I N S T O R effects o n c o r n yields at C a n t o n plot area.
234
K. R. Olson, G. W. Olson TABLE 3
Corn Yields, Rainfall and RAINSTOR Data for the Miner Plot Area (Raynham Variant Soil) Year
Corn yield (Mg/ha)
Rainfall" (cm)
1973 1974 1975 1976 1977 1978 1979 1980 1981
2.00 3.64 9.79 9.16 8-66 8.28 6.77 6.84 6.77
51.1 34.8 21.1 42.4 27.7 24.9 25-7 21.8 45.5
RAINSTOR (cm) + + + + + + -
22.52 4"65 3.02 10.46 9-65 9,42 8.97 4.01 13.28
"Value increased by 30 ~o to reflect lateral recharge. a p p r o p r i a t e . This was d o n e b y increasing the coefficient in 0.05 i n c r e m e n t s until the m a x i m u m r 2 c o r r e l a t i o n b e t w e e n rainfall a n d c o r n yield o c c u r r e d . T h e r 2 w a s e q u a l to 0.31 with a 30 ~ increase in effective rainfall ( T a b l e 3). A f t e r using the r a i n f a l l - s o i l s t o r a g e e q u a t i o n s to calculate R A I N S T O R values, the R A I N S T O R versus c o r n yield r e l a t i o n s h i p h a d an r 2 o f 0.61 (Fig. 3). 12-
u.i 7.
/
8-
r 2 = .61
Y= 6 . 7 7 + 0 . 1 7 X
! -20
I -10
0
RAINSTOR
Fig. 3.
I 10
i 20
(cm)
RAINSTOR effects on corn yields at Miner plot area.
A soil-climate index to predict corn yield
235
The calculated R A I N S T O R values did prove to be a much better indicator of corn yields than rainfall for the initial and both test plots. The r 2 values were improved from the 0.03 to 0.31 range for rainfall to between 0-61 and 0.80 for R A I N S T O R . The equations were developed for one soil and location but tested at two distant sites located in New York State. Monthly rainfall data for the May 1st to August 31st period did provide a reliable data base for predicting corn yields in the humid climate of New York State. One would expect that daily, rather than monthly, rainfall and R A I N S T O R data might be better, but an initial check at the Aurora plot area did not significantly improve the r 2 value from the 0-80 for monthly data (was 0.83). In addition, daily weather summaries are more difficult to obtain and utilize. They may also require a computer to analyze up to 20 years of daily weather data for each site and they are not readily available in all parts of the world.
CONCLUSIONS The depth to which roots of corn plants can ramify is quite important. In New York State many soils have root-restricting barriers, including bedrock, fragipans and dense basal till. The total water storage capacity (available water) of a soil can be significantly reduced when rootrestricting layers are present. Soil porosity, bulk density, 33 kPa moisture and 1-5 MPa moisture tests were run to determine rooting depth, rooting volume and the total a m o u n t of water stored in pores (50 #m to 5 #m in diameter). Both droughty and ponding conditions were considered.The most limiting value (maximum stress) was used in the calculations. When the water storage capacity of the soil is combined with the rainfall and evapotranspiration data, this variable (RAINSTOR) becomes a good parameter for predicting yearly corn yields in the udic moisture regime of New York State. After using the rainfall-soil storage (RAINSTOR) equations the R A I N S T O R versus corn yield relationship had an,r 2 = 0.80 for the Aurora plot area. The R A I N S T O R parameter was tested at two additional sites with 18 and 9 years of corn yield and climate data. The r 2 was 0.70 and 0.61, respectively, suggesting the R A I N S T O R parameter was quite useful for predicting yearly corn yields for nearly level soils in New York State.
236
K. R. Olson, G. W. Olson ACKNOWLEDGEMENTS
The authors wish to acknowledge Drs R. F. Lucey, W. D. Pardee and R. B. Musgrave for permitting the use of their corn yield data. Dr B. A. Pack provided the climatic data for the plot areas. Dr G. W. Fick helped in the development of rainfall-soil storage equations.
REFERENCES Baier, W. & Robertson, G. W. (1968). The performance of soil moisture estimates as compared with the direct use of climatological data for estimating crop yields. Agr. Meteorol., 5, 17-31. Bartelli, L. J. & Peters, D. B. (1959). Integrating soil moisture characteristics with classification of some Illinois soils. SoilSci. Soc. Am. Proc., 23, 149.-51. De LaRosa, D. F., Cardona, F. & Almorza, J. (1981). Crop yield predictions based on properties of soils in Sellilla, Spain. Geoderma, 25, 267 74. Denmead, O. T. & Shaw, R. H. (1962). Availability of soil water to plants as affected by soil moisture content and meteorological conditions. Agron. J., 45, 385-90. Dower, M. M. & Olson, K. R. (1980). Revised pipet method oJparticle size analysis. Agron. Mimeo 80-17, Dept. of Agronomy, Cornell Univ., Ithaca NY. 7pp. Gardner, W. R. (1980), Dynamic aspects of water availability to plants. Soil Sci., 89, 63-73. Hillel, D. & Hornberger, G. M. (1979). Physical model of the hydrology of sloping heterogeneous fields. Soil Sci. Soc. Am. J., 43, 434-9. Morris, R. A. (1972). Simulation-model-derived weather indexes Jbr regressing Iowa corn yields on soil management and climatic Jactors. Unpublished. PhD dissertation. Library, Iowa State Univ., Ames. 312 pp. Olson, K. R. (1979). Saran coated method jbr determining bulk densities, soil moisture values and coelfi'cient of linear extensibility. Agron. Mimeo 79 5, Dept. of Agron., Cornell Univ., Ithaca NY. 6pp. Olson, K. R. (1983). Soils and climate effects on yieldsJbr assessment evaluations. Unpublished PhD Thesis, Dept. of Agron., 'Cornell Univ., Ithaca NY. 324 pp. Olson, K. R. (1985). Characterization of pore size distributions within soils by mercury intrusion and water release methods. Soil Sci., 139, 400-4. Parks, W. L. and Knetsch, J. L. (1959). Corn yields as influenced by nitrogen level and drought intensity. Agron. J., 51, 363~,. Shaw, R. H. (1974). A weighted moisture stress index for corn in Iowa State. J. Res., 49, 101-14. Soil Survey Staff (1972). Soil survey laboratory methods and procedures ./'or
A soil-climate index to predict corn yield
237
collecting soil samples. Soil Survey Investigations Report No. 1. Soil Conservation Service, US Dept. of Agric., Gov't. Printing Office, Washington DC. 50 pp. Thompson, L. M. (1963). Weather and technology in the production of corn and soybeans. CAED Report 17. The Center for Agricultural and Economic Development, Iowa State Univ., Iowa. 46 pp.