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Using a crop growth simulation model for evaluating irrigation practices
Agricultural Water Management, 5 (1982) 253--268
253
Elsevier Scientific Publishing Company, Amsterdam - - Printed in The Netherlands
USING A CROP GROWTH SIMULATION MODEL FOR EVALUATING IRRIGATION PRACTICES
S.S. K U N D U
~, G.V. S K O G E R B O E
2 and W.R. W A L K E R
3
'Irrigationand Industrial Development Corporation, 260 Madison Avenue, N e w York, N Y 07009 (U.S.A.) 2Department of Agricultural and Chemical Engineering, Colorado State University, Fort Collins, C O 80523 (U.S.A.) 3Department of Agricultural and IrrigationEngineering, Utah State University, Logan, UT 84322 (U.S.A.) (Accepted 22 February 1982)
ABSTRACT
Kundu, S.S., Skogerboe, G.V. and Walker, W.R., 1982. Using a crop growth simulation model for evaluating irrigation practices. Agric. Water Manage., 5 : 253--268. Water management decisions are dependent on crop variety, soil and climatic conditions. A properly structured plant growth simulation model which takes these factors into account can be successfully used to quantify the effects of irrigation practices on crop yields. The use of such a simulation model will be considerably less expensive and time consuming than conducting field experiments. This paper reports the results of using such a model for making important water management decisions, such as determining: (a) optimum soil moisture depletion and replenishment levels; and (b) timing and a m o u n t of irrigation during different crop growth stages.
INTRODUCTION
In the last two decades, agronomists and irrigation engineers have developed crop yield models relating crop yield and water use (Barrett and Skogerboe, 1980). Although these models serve a meaningful purpose, they are limited in their application as yield predictive models. More specific relationships between crop yield and growth factors are presented by water production functions. Some o f these models include factors such as fertilizer, plant population, soil properties and climatic conditions (Hexem and Heady, 1978). In spite of including other factors besides water and fertilizer, these production functions are not generalized functions. One o f the logical approaches in the direction of quantifying the effects of environmental variables on yield is using a crop growth simulation model
0378-3774/82/0000--0000/$02.75 © 1982 Elsevier Scientific Publishing Company
254
{Brouwer and De Wit, 1969; Splinter, 1964; Duncan, 1975; Feddes et al., 1978). Such a model must be able to translate the complex interactive nature of the soil-plant-atmospheric system. A model, developed by Childs et al. {1977) and later modified by Tscheschke and Gilley (1979), successfully predicted grain yields of corn for several varieties, sites, years, and irrigation treatments. This model (CORNGRO) was further modified by Kundu {1981). The overall prediction results indicated that this model can be effectively used to provide insight regarding water management policies. The primary objective of this paper is to show that a reliable crop growth simulation model can be used for making water management decisions, such as determining: (a) optimum soil moisture depletion and replenishment levels; (b) timing and amount of irrigation during different crop growth stages; and (c) for developing site and crop specific yield -- water use relationships. Another objective is to show that such a model also helps to explain the effects of different water management policies. BRIEF DESCRIPTION OF THE CORNGRO MODEL
A concise flow chart of the CORNGRO model is presented in Fig. 1. The input data requirements for the model may be broadly classified as: (a) plant charaeterization parameters; (2) irrigation and daily climatic data; and (3) soil characteristics. Basically, the model consists of two major parts: (1) moisture flow program; and (2) plant growth program. The model initially separates the daily input potential evapotranspiration into potential evaporation and transpiration. The actual evaporation during each time step is calculated based on plant leaf-area cover, the potential evaporation rate for the time step, and the soil moisture status in the top two soil nodes from where no water is assumed to be extracted by the plant root system. Actual transpiration is determined from the minimum leaf water potential attained during the time step, potential transpiration rate, soil moisture contents in the depth nodes, and the root water extraction pattern. Soil moisture content at the end of each time step is calculated based on the root water extraction pattern and solving a tridiagonal matrix of a set of equations using the soil matric potential. Unlike the soil moisture flow calculations, which are based on variable time steps, the plant growth calculations are made for every even hour starting at dawn (06:00). Growth respiration for each hour is calculated using the photosynthetic rate, total plant dry weight, air temperature, available carbohydrate in the tissues of the plant, and plant leaf area. The plant dry matter accumulation is estimated by a relationship using growth respiration and leaf area. The leaf and stem growth is considered to continue until the accumulated degree days is equal to the input degree days for tasseling and, from then on, ear growth continues until maturity.
255
I Input data and initialization
I
oo,,, Looo
Separation of Potential Evaporation and Transpiration
r ,=--,
I
I Root Growth ~ I
--I
Small Time Increment Loop
Actual Evaporation Rate Calculation
i Actual Transpiration Rote Root Water Extraction
I
1
Soil MoistureFlow i
Shorten time increment
1~ J
Plant Growth
k
1
Yes
I
I Check for Tasseling or Crop Maturity.Compute Cumulative soil water change and Plant Growth Parameters Present Output Data and Predictions
Fig. 1. Concise flow chart of the CORNGRO model (modified from Childs et al., 1977). CONQ is the maximum allowable change in the soil moisture content at any soil depth node.
256 APPLICATIONS OF THE MODIFIED CORNGRO MODEL
Optimum soil moisture depletion level One of the c o m m o n questions is "at what level of available soil moisture content should irrigation be initiated for a specific crop variety in a specific location?" The specificities of the variety and location arise from knowledge regarding the influence of different crop varieties and soil properties u p o n plant growth processes. To illustrate this point, t w o different corn varieties and locations are considered where plants are irrigated at different levels of total available water {TAW). The input data for corn variety, soil and climatic conditions at Grand Junction, CO (Barrett, 1977) and Davis, CA (Stewart et al., 1977) were used for this purpose. Seven levels of allowable soil moisture depletion were considered for the simulation runs to determine the water use efficiencies at different levels of allowable soil moisture depletion. The water use efficiency (WUE) is commonly defined as the weight of dry matter or marketable crop produced per unit volume of water. In this paper, WUE will be considered in terms of both grain and total dry matter yields and will be designated as GWUE and DMWUE, respectively. The relationships between seasonal ET and both grain and total dry matter yields are presented in Fig. 2 for the crop variety (Pioneer 3367A) at Grand Junction during 1976. This relationship is more vivid for total dry matter (TDM) yields than for grain yields. Closer observation of these curves indicate that the increase in yields with ET would also be fitted by straight lines for allowable TAW depletion levels between 40 and 90%. The maximum GWUE and DMWUE were found at 40% allowable TAW depletion level (shown by the straight lines plotted through the origin and tangent to the curves). The water budget presented in Table I reveals additional information. This table shows that both seasonal ET and transpiration during the pollination period are higher than in the other two growth periods. This would be expected because the transpiration rate is directly related to the leaf area index and the average leaf area index during the pollination period is at a maxim u m value. Field data presented by Stewart et al. (1977) does n o t consistently support this trend in ET. The reason behind this discrepancy may be attributed to the differences in the crop varieties, soil and climatic conditions, and the lengths of crop growth stages used in the computer simulation runs and in the field experiments reported by these researchers. The seasonal evaporation (which is ET minus transpiration values presented in Table I) increased with more frequent irrigation (i.e., irrigations scheduled at lower allowable TAW depletion levels). The more frequent irrigations kept the surface soil moister for longer time periods, which induced higher evaporation rates. However, in spite of higher seasonal evap-
257 14
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Fig. 2. Relationships between seasonal evapotranspiration and corn yields derived by the modified CORNGRO model for various levels of soil moisture depletion before irrigating at Grand Junction, CO, 1976. oration, irrigations at 40% allowable TAW depletion level could be justified for growing corn at the Grand Junction site in view of the higher percent increase in both grain and TDM yields compared to the increase in seasonal ET requirement. The curves in Fig. 3 for the corn variety (Funk 4444) at the Davis site show that no marked benefit in yields can be expected by irrigating at allowable TAW depletion less than 60%. Practically no increase in yields are visible with irrigations at lower allowable depletion levels. Practically no increase in GWUE and DMWUE occurred with irrigations at TAW depletion ranging from 90 to 40%. This p h e n o m e n o n m a y be explained by the water budget presented in Table II, which shows that little increase in transpiration resulted from more frequent irrigations; the increase in ET was caused by higher seasonal evaporation with increasing n u m b e r of irrigations. Table II also indicates that higher ET was concomitant with higher depletions from the soil moisture profile. The results o f extensive field experiments (Stewart et al., 1977) conducted at the Davis site supports this phenomenon. Stewart et al. (1977) reported that the water holding capacity of the Davis soil is high and if the entire soil profile is at field capacity at planting time, then root exploration alone satisfied a sufficient fraction of crop water needs in each growth stage to assure healthy growth. They also suggested that the soil at Davis is such that the water extraction pattern for the same variety o f
258 TABLE 1 G r a i n a n d t o t a l d r y m a t t e r yields, a n d w a t e r b u d g e t a ofsyntheticirrigationsat water (TAW} for Grand Junction, C O , 1 9 7 6
differentailowable depletionlevels oftotalavailable
Allowable depletion(%)
Yield (t/ha)
Irrigation (rata)
Rainfall (mra)
ET (mm)
Grain Total dry matter
25
40
50
60
70
80
8.437 13.746
8.058 13.141
7.214 11.734
6.763 10.823
6.580 10.588
6.447 10.063
90 5.936 9.469
V P M
177 217 18]
118 167 192
161 113 118
95 127 143
117 165 166
0 159 191
0 190 213
S
575
477
392
365
448
350
403
V P M
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
S
38
38
38
38
38
38
38
V P M
197 -245 197
-191 230 -173
167 -220 -163
-156 -205 157
145 212 157
145 195 -152
-145 186 -150
S
-639
594
-550
518
514
--492
-481
Transp~ation
V
(mra)
P M
143 --197 -160
r141 -199 -150
-126 187 151
120 -180 --140
120 179 139
-120 -173 135
-120 -165 -135
S
-500
--490
-464
440
-428
-420
V P M
3 4 4
3 5 5
3 6 5
3 6 5
3 7 5
3 7 5
3 6 6
S
5
7
8
8
9
9
9
V P M
0 14 8
13 89 32
42 63 13
9 34 16
-126 - 20 40
-126 - 15 70
S
22
28
10
41
Drainage (ram)
Profile b
depletion (rata)
-
35 50 26
-
59
-108
438
-118
-
a Negative signs indicate water went out of the soil profile. b p r o f i l e d e p l e t i o n w a s calculated after accounting for the error in moisture balance equation of the p r o g r a m . V , v e g e t a t i v e ; P, p o l l i n a t i o n ; M, m a t u r a t i o n ; S, s e a s o n a l .
• . . "corn would occur every year if grown without post-germination irrigation, provided the soil was initially at field capacity." The above results show that the WUE resulting from irrigations at various TAW depletion levels is clearly the result of plant and soil characteristics. It can also be inferred that climatic conditions do not influence water use efficiency per se, since the climatic factors generally also influence the plant growth process with accompanying changes in the evapotranspiration rates.
Partial replenishment of soil moisture depletion Once the question of an optimum allowable TAW depletion level for a specific plant variety and soil type has been answered, another question of
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500 600 700 800 SeQsonol ET, mm Fig. 3. Relationships between seasonal evapotranspimtion and corn yields derived by the
modified CORNGRO model for various levels of soil moisture depletion before irrigating at Davis, CA, 1974. interest would be the effect on yields of applying irrigation water in amounts such that it replenishes only a fraction of the total depletion for each irrigation event. For example, if 40% of the TAW is depleted before an irrigation, h o w much o f the depleted a m o u n t should be replenished in that irrigation. Irrigating to less than field capacity m a y be justified by providing a better r o o t zone environment. Where an impermeable layer exists below the soil profile, like in Grand Junction, it could also be useful to k n o w the effects of over-irrigating. The expected effects of such over-irrigation would be: (a) lowered yields due to anaerobic conditions in the soil for a longer time period; and (b) the subsurface drainage of excess water to the impermeable layer. The input data corresponding to crop and soil characteristics and climatic conditions at the Grand Junction site were used for this purpose. Table III presents grain and total dry matter yields, and water budgets for six different replenishment levels. Each replenishment level consisted of irrigating the desired (10, 20, 30, 40, 50 or 60) percent of the TAW after 40% of TAW is depleted below field capacity. Therefore, the 40% replenishment level in Table III corresponds to field capacity at the completion of an irrigation event. The results o f the simulation runs (Table III) indicate that yields (grain and total dry matter) and seasonal transpiration were barely reduced with lower replenishment levels. Table III also shows that seasonal ET remained almost unchanged for replenishment levels ranging from 10 to 50%. Only very slight reductions in corn yields were found with over-irrigation by 10
260 T A B L E II
Grain and total dry matter yields, and water budget a of synthetic irrigations at different allowable depletion levels of total available water (TAW) for Davis, C A , 1 9 7 4 Allowable depletion (%)
Yield (t/ha)
Irrigation (ram)
Rainfall (ram)
ET (mm)
Transpiration (mm)
Drainage (mm)
Profile b Depletion (mm)
Grain Total dry matter
25
40
50
60
70
80
90
11.073 20.216
11.039 20.078
11.021 20.041
10.953 19.853
10.802 19.523
10.463 18.852
10.555 18.833
V P M
313 128 241
113 196 130
75 252 165
100 161 196
128 -219
193 261
237 ---
S
682
439
492
457
347
454
237
V P M
24
24 .
24
24
S
24
24
24
24
24
24
24
V P M
-301 -200 223
-194 201 -221
180 -200 219
-170 198 219
- 165 193 -220
164 195 206
165 -153 245
S
724
-616
-599
-587
577
-.565
563
V P M
127 186 -202
-128 192 192
129 -184 201
124 180 -204
123 - 184 201
127 177 196
--130 -178 200
S
-515
512
-514
508
508
500
508
V P M
16 1 31
7 - 11 48
7 16 53
6 17 57
6 21 53
6 - 20 66
6 20 65
S
14
52
62
68
68
80
79
V P M
20 74 45
66 6 42
89 70 1
53 20 28
23 172 48
46 85 146
90 139 180
S
9
102
19
45
147
15
-229
.
.
24 . .
24
. .
.
.
.
.
-
24 .
.
.
.
.
a Negative signs indicate water went out of the soil profile. bprofile depletion was calculated after accounting for the error in moisture ablance equation of the program. V , vegetative; P, pollunation; M, m a t u r a t i o n ; S, seasonal.
and 20% of TAW (corresponding to 50 and 60% replenishment levels). The results show that the WUE for irrigations at the 60% replenishment level is slightly higher than that for irrigations at the 40% replenishment level (corresponding to field capacity). Slightly increased WUE due to irrigations at the 60% replenishment level resulted from lower seasonal evaporation (ET minus transpiration) because of fewer irrigations. The irrigation amounts applied at different growth stages do not show any consistent pattern with replenishment levels (Table III). The results of the simulation runs indicate that these inconsistencies were caused by different dates and amounts of irrigations required for different replenishment levels. For example, irrigations at both 40 and 50%, replenishment levels required two irrigations during the pollination period totaling 167 and 217 mm, re-
261 TABLE III
Grain and total dry matter yields, and water budget a of synthetic irrigations a t 4 0 % allowable depletion o f total available water ( T A W ) and various levels of soil moisture replenishment for Grand Junction, C O , 1 9 7 6 Percent o f T A W applied in each irrigation after 40% depletion
Yield (t/ha)
Irrigation (mm)
Rainfall (mm)
ET (mm)
Transpbation (mm)
Drainage (ram)
Profile b
Depietion (ram)
Grain Total dry matter
10
20
30
40 c
50
7.568 12.167
7.965 12.900
8.018 13.072
8.058 13.141
8.031 13.093
60 8.022 13.093
V P M
95 213 184
90 207 193
87 249 142
118 167 192
148 217 119
80 229 142
S
482
490
478
477
484
451
V P M
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
S
38
38
38
38
38
38
V P M
-177 -231 -189
-176 -236 -185
-178 -237 -184
-191 -230 -173
-178 -232 -182
-176 -232 -173
S
-597
-597
-599
-594
-592
-581
V P M
-131 -189 -148
-134 -196 -153
-136 -198 -155
-141 -199 -150
-136 -198 -156
-136 -198 -155
S
-468
-483
-489
-490
--490
-489
V P M
-
2 5 4
2 5 4
S
7
V P M
- 66 4 11
-
S
-
-
81
-
2 5 4
3 6 4
2 5 4
7
7
7
7
64 18 13
- 66 37 39
-
69
- 68
-
-
2 4 5 7
35 49 25
-
1 13 58
-
-
67 15 24
59
-
46
-
76
aNegative sign~ indicate water went out of the profile. b p r o f i l e depletion was calculated after accounting for the error in the moisture balance equation of the program. c Corresponds to field c a p a c i t y . V , v e g e t a t i v e ; P, p o l l i n a t i o n ; M, m a t u r a t i o n ; S, seasonal.
spectively; whereas, at the 30% replenishment level, four irrigations were required totaling 249 mm of water application. Lower irrigation amounts during the pollination period at the 40% replenishment level and during the vegetative period at the 60% replenishment level resulted in higher root zone depletions during these growth stages. Similarly, lower irrigation application amounts during the maturation period at the 50% replenishment level resulted in higher root zone depletions during this growth stage. The results show that lower replenishment amounts for each irrigation event require more frequent irrigations which increase seasonal evaporation and decrease WUE. The results also indicate that irrigating strictly on the basis of replenishment level may result in a lower irrigation application during a critical growth stage (e.g., the pollination period). Therefore, criti-
262 cality of different growth stages should be taken into account to determine the optimum replenishment level. The overall conclusion of the above analysis is that the optimum level of depletion from total available water (TAW) for the Grand Junction site is 40%.
Partial replenishment at different crop growth stages To take the above conclusion one step further, it is instructive to verify the effects of levels of depletion and replenishment with reference to irrigation events occurring at different crop growth stages. For this purpose, irrigation treatments were defined with reference to the growth stages of the crop. A treatment consisted of applying irrigation water (I) during one or more of the three growth stages and withholding irrigation (0) in the others. To reduce the computer costs, only treatment II0 and 010 were considered. Barrett and Skogerboe (1978) observed that treatments 000,010 and II0 gave the maximum water use efficiency with respect to grain yield. In addition, since the optimal level of TAW depletion before irrigating was found to be 40% at the Grand Junction site, it was decided to synthetically schedule the irrigation events for these two treatments (treatments II0 and 010) in such a way that the plants are irrigated whenever TAW is 60%. However, each irrigation event will apply only 10, 20, 30 or 40% (replenishment level) of the TAW. Analysis of the water budget and final yields of tl~e t w o treatments (Table IV) show that there is no definite correlation between replenishment level and yields for either of the two treatments. But in both cases, yields are well-correlated with the corresponding values of seasonal transpiration. The results of the simulation runs indicate that the apparent incoherence in the relationships of yields both with seasonal ET and irrigation replenishment levels can be attributed to the date and replenishment level of each irrigation event. Especially, when no irrigation is applied during the maturation period, the last date of irrigation during the pollination period becomes most important. The date and amount of this irrigation event determines how much soil moisture will be available during the maturation period for grain formation. For example, Table IV shows that there is a considerable difference between grain yields at the 30 and 40% irrigation replenishment levels for treatment 010, whereas stover yields (total dry matter minus grain yields) are unchanged at 3.965 t/ha. The last irrigation dates for these t w o cases were 29 July and 7 August, respectively, while the corresponding irrigation amounts were 64 and 92 mm. Table IV also indicates that at the end of the pollination period, soil moisture depletion from the soil profiles for the two cases were 111 and 56 mm, respectively, which resulted from the timing of the last irrigation event as explained above and the total irrigation amount during the pollination period. Prior to the last irrigation event in a growth stage, the dates of other irriga-
263 TABLE IV
Grain and total dry matter yields, and water b u d g e t a o f synthetic irrigations a t 4 0 % depletion level o f T A W a n d various levels of soil moisture replenishment for treatments I I 0 a n d 010 a t G r a n d Junction, CO, 1 9 7 6 . Treatment II0
Treatment 0 1 0
Percent o f T A W replenished in each irrigation after 40% depletion 10
Yield (t/ha)
Irrigation (mm)
Rainfall (mm)
Grain Total dry matter
20
6.275 10.878
6.680 11.619
124 173
30
40
6.394 11.45
6.931 12.018
V P M
95 188 .
S
283
297
264
265
V P M
22 13 3
22 13 3
22 13 3
22 13 3
.
87 177 .
118 167 .
.
10
20
5.957 9.918
. 253
30
6.401 10.375
.
.
40
5.729 9.694
6.631 10.596
.
251 .
219
285
253
251
219
285
22 13 3
22 13 3
22 13 3
22 13 3
.
.
S
38
38
38
38
38
38
38
38
ET (mm)
V P M
177 -231 143
176 236 148
-178 -234 -143
-182 - 230 152
-146 241 133
146 226 138
146 217 124
146 --223 141
S
-551
560
- 555
564
- 520
- 510
487
- 510
Transpi-
V P M
131 189 -142
-134 196 146
. -136 198 142
-136 199 150
120 178 132
120 178 136
120 178 123
120 178 138
S
462
-476
476
-485
430
-434
-421
436
V P
2 6
2 5
2 5
2 5
M
5
6
6
S
9
9
9
V P
- 66 - 29 -135
- 30 - 52 -140
66 - 32 135
230
222
233
ration (mm)
Drainage (ram)
Profileb Depletion (mm)
M S
2 4
2 4
2 5
6
6
6
6
6
9
8
8
8
8
25 50 144
-126 25 -124
-126 46 129
126 15 116
-126 70 132
- 219
225
209
227
188
-
-
-
2 4
a Negative signs indicate water went out of the soil profile equation of the program. b p r o f i l e depletion was calculated after accounting for the error in the moisture b a l a n c e . V , v e g e t a t i v e ; P, p o l l i n a t i o n ; M, m a t u r a t i o n ; S, seasonal.
tion events do not indicate any appreciable affect on the physiological growth of corn, which seems to be one of the limitations of the CORNGRO model. However, the amount of each irrigation is important. Higher replenishment levels result in higher average soil matric potentials during the irrigation interval. Since the photosynthetic rate is directly related to a function of soil matric potential in the CORNGRO model (Tscheschke and Gilley, 1979), therefore, higher average soil matric potentials during the irrigation interval contribute to higher photosynthetic rates and therefore, to increased plant growth. The results of treatment II0 can be analyzed in a manner similar to those of treatment 010. In this treatment, the seasonal ET and yields at the 30% TAW replenishment level were higher than those at the 10% TAW replenish-
264
ment level. This resulted from the higher average soil matric potential at the 60% level as compared with the 10% level during the first two growth stages. Also, the increase in stover yield resulted from higher average soil matric potentials at the higher replenishment levels during the vegetative period. In summary, the results of the various irrigation treatments based on depletion of available soil moisture indicate that it is not only possible to use a crop growth simulation model for making water management decisions, but such a model is also helpful in explaining the effects of different water management policies.
Evapotranspiration and yields To further demonstrate the applicability of a crop growth simulation model for water management purposes, the effects of irrigating corn at different growth stages can be derived. The literature suggests that the relationships between seasonal ET and grain yield (GY) or total dry matter yield (TDMY) of corn are linear in nature (for more detail, see Barrett and Skogerboe, 1980}. In general, researchers have observed that this linearity is stronger between seasonal ET and TDMY than between seasonal ET and GY. Severe water stress during a critical growth period may result in considerable data scatter (Stewart et al., 1975) because the effect of the severity of stress on corn yields is dependent on the varietal characteristics and soil properties (Stewart et al., 1977). The CORNGRO model (Kundu, 1981) was used to study the relationship between seasonal ET and yields in relation to the site conditions at Grand Junction in 1976. Seven irrigation treatments based on several combinations of weekly irrigations during different growth stages were chosen. For each irrigation event, four levels of irrigation water application were employed. Treatment 000 was excluded from this particular investigation since it does not involve any irrigation. The water application levels comprised of weekly irrigations during the desired growth stage(s) in amounts equal to 25, 50, 75 and 100% replenishment of the soil moisture depleted during the period prior to irrigation as determined by the moisture balance equation. When the water application level is equal to 100% during a growth stage, it implies that there is essentially no soil moisture stress during that growth stage. But, whenever the water application level is less than 100%, the soil moisture deficit would gradually increase during the growth stage and result in moisture stress conditions if the water application level is too low. The results of the synthetically scheduled irrigations are presented in Table V. Figs. 4 and 5 show the relationships of seasonal ET with grain and total dry matter yields, respectively. Both curves show strong linearity between seasonal ET and yields. For grain yield the relationship is slightly weaker (r 2 = 0.913} than that for the total dry matter yield (r 2 --- 0.979}. In general, the data scatter is narrower than those observed from field data by other researchers (Stewart et al., 1977; Barrett and Skogerboe, 1978).
265
TABLE V Seasonal ET and corn yields of various synthetically irrigated treatments (input data from Grand Junction, Colorado, 1976) (From Barrett, (1977) Treatment
ET replenished each irrigation (%)
Seasonal (mm )
Grain yield (t/ha)
TDM yield (t/ha)
HI
25 50 75 100
360 514 587 658
2.665 5.334 6.897 8.138
6.222 9.486 11.513 13.172
II0
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352 454 556 622
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6.195 8.338 10.644 12.604
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364 492 553 618
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6.832 9.557 10.682 11.972
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367 496 538 571
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I00
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307 348 388 442
2.319 2.480 2.924 3.600
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354 435 510 530
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00I
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359 430 449 459
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7.162 8.817 9.203 9.257
T h e values o f t h e positive i n t e r c e p t o n t h e seasonal E T axis (abscissa) o f Figs. 4 and 5 indicate t h a t n o grain o r t o t a l d r y m a t t e r yields will a c c r u e b e l o w t h e respective i n t e r c e p t values o f ET. These i n t e r c e p t s s h o w t h a t m o r e seasonal E T ( 1 8 4 m m ) is r e q u i r e d t o p r o d u c e a n y grain t h a n t o p r o d u c e a n y d r y m a t t e r (45 m m ) w h i c h is o b v i o u s since grain p r o d u c t i o n starts a f t e r t h e vegetative g r o w t h stage. F r o m these o b s e r v a t i o n s , it m a y be inferred t h a t
266
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300 400 500 600 700 Seasonal ET, mm Fig. 4. Relationship between seasonal evapotranspiration and corn grain yield predicted by the modified CORNGRO model for various irrigation treatments at Grand Junction, CO, 1976. Each irrigation treatment consisted of weekly irrigations to replenish ET and drainage as determined by the moisture balance equation; four levels of replenishment consisting of 25, 50, 75 and 100% replenishment of ET plus drainage during the period preceding the irrigation. a b o u t 45 m m o f soil m o i s t u r e would e v a p o r a t e b e t w e e n t h e planting and g e r m i n a t i o n dates u n d e r climatic c o n d i t i o n s similar t o G r a n d J u n c t i o n , 1976, p r o v i d e d t h e initial soil m o i s t u r e profile is at field capacity. These d a t a also indicate t h a t u n d e r m o i s t u r e stress c o n d i t i o n s at least a n o t h e r 139 m m o f e v a p o t r a n s p i r a t i o n would o c c u r b e f o r e grain p r o d u c t i o n would start. While c o m p a r i n g t h e c o r r e s p o n d i n g values o f seasonal E T i n t e r c e p t s pres e n t e d b y S t e w a r t et al. ( 1 9 7 7 ) and B a r r e t t and S k o g e r b o e (1978), it was observed t h a t at several instances t h e i n t e r c e p t values o n the seasonal E T axis for t o t a l d r y m a t t e r yields were higher t h a n the c o r r e s p o n d i n g values for grain yields. T h e r e a s o n b e h i n d this d i s c r e p a n c y m a y be a t t r i b u t e d t o the wider scatter o f field observed yield d a t a for t h e various irrigation treatments. CONCLUSIONS
T h e results o f s y n t h e t i c a l l y irrigating at several d e p l e t i o n and replenishm e n t levels s h o w t h a t a c r o p g r o w t h s i m u l a t i o n m o d e l can be effectively used t o schedule irrigation events with respect t o the c r o p variety, soil and
267 14
,
,
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• IO0
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400 500 ET, mm
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Fig. 5. Relationship between seasonal evapotranspiration and total dry matter yield of corn predicted by the modified CORNGRO model for various irrigation treatments at Grand Junction, Colorado, 1976. Each irrigation treatment consisted of weekly irrigations to replenish ET and drainage as determined by the moisture balance equation; four levels of replenishment consisting of 25, 50, 75 and 100% replenishment of ET plus drainage during the period preceding the irrigation. climatic conditions. The results showed t h a t the m a x i m u m water use efficiency, WUE, for Grand J u n c t i o n conditions can be obtained if corn plants are irrigated when 40% of total available water is depleted, when the root zone is replenished to field capacity by each irrigation. For the Davis site, the r o o t growth and soil characteristics are such that the depletion level of 60% or less results in practically no reduction in WUE provided the soil was at field capacity at the time of planting. For depletion levels greater than 60%, the WUE was sharply reduced. The results of synthetically irrigating at several replenishment levels to different irrigation treatments also indicate t h a t yields are n o t appreciably affected by increasing the n u m b e r of irrigations during one or more growth stages. Rather, the date and a m o u n t of the last irrigation is more important if no irrigation would be applied in the following growth stage. The simulation results for synthetically scheduled weekly irrigations for various water treatments showed t h a t both grain and total dry matter yields are linearly related to seasonal ET. This conclusion substantiates the observations of other researchers (Stewart et al., 1977; Barrett and Skogerboe, 1978, 1980). The results of the synthetic irrigation runs show that the resolution in
268
using a plant growth simulation model, such as CORNGRO, for water management purposes is not only feasible but also highly promising.
REFERENCES
Barrett, J.W.H., 1977. Crop yield functions and the allocation and use of irrigation water. Unpublished Ph.D. Dissertation, Colorado State University, Fort Collins, CO, 210 pp. Barrett, J.W.H. and Skogerboe, G.V., 1978. Effect of irrigation regime on maize yields. J. Irrig. Drainage Div., ASCE, 104 (IR2): 179--194. Barrett, J.W.H. and Skogerboe, G.V., 1980. Crop production functions and the allocation and use of irrigation water. Agric. Water Manage., 3: 53--64. Brouwer, R. and De Wit, C.T., 1969. A simulation model of plant growth with special attention to root growth and its consequences. In: W.J. Whittington (Editor), Root Growth. Butterworths, London, pp. 224--244. Childs, S.W., Gilley, J.R. and Splinter, W.E., 1977. A simplified model of corn growth under moisture stress. Trans. ASAE, 20(5): 858--865. Duncan, W.G., 1975. Maize. In: L.T. Evans (Editor), Crop Physiology. Cambridge University Press, London/New York, pp. 23--50. Feddes, R.A., Kowalik, P.J. and Zaradny, H., 1978. Simulation of Field Water Use and Crop Yield. John Wiley and Sons, New York/Toronto, 188 pp. Hexem, R.W. and Heady, E.O., 1978. Water Production Functions for Irrigated Agriculture. Iowa University Press, Ames, IO, 215 pp. Kundu, S.S., 1981. Corn yield predictions by plant growth simulation. Unpublished Ph.D. Dissertation, Colorado State University, Fort Collins, CO, 264 pp. Splinter, W.E., 1974. Modeling of plant growth for yield prediction. Agric. Meterol., 14: 243--253. Stewart, J.I., Misra, R.D., Pruitt, W.O. and Hagan, R~I., 1975. Irrigating corn and grain sorghum with a deficient water supply. Trans. ASAE, 18(2): 270--280. Stewart, J.J., Hagan, R.M., Pruitt, W.O., Danieison, R.E., Frankling, W.T., Hanks, R.J., Riley, J.P. and Jackson, E.B., 1977. Optimizing crop production through control of water and salinity levels in the soil. Report PRWG151-1, Utah Water Research Laboratory, Utah State University, Logan, UT, 191 pp. Tschesehke, P.D. and Gilley, J.R., 1979. Status and verification of Nebraska's corn growth model--CORNGRO. Trans. ASAE, 22(6): 1329--1337.
253
Elsevier Scientific Publishing Company, Amsterdam - - Printed in The Netherlands
USING A CROP GROWTH SIMULATION MODEL FOR EVALUATING IRRIGATION PRACTICES
S.S. K U N D U
~, G.V. S K O G E R B O E
2 and W.R. W A L K E R
3
'Irrigationand Industrial Development Corporation, 260 Madison Avenue, N e w York, N Y 07009 (U.S.A.) 2Department of Agricultural and Chemical Engineering, Colorado State University, Fort Collins, C O 80523 (U.S.A.) 3Department of Agricultural and IrrigationEngineering, Utah State University, Logan, UT 84322 (U.S.A.) (Accepted 22 February 1982)
ABSTRACT
Kundu, S.S., Skogerboe, G.V. and Walker, W.R., 1982. Using a crop growth simulation model for evaluating irrigation practices. Agric. Water Manage., 5 : 253--268. Water management decisions are dependent on crop variety, soil and climatic conditions. A properly structured plant growth simulation model which takes these factors into account can be successfully used to quantify the effects of irrigation practices on crop yields. The use of such a simulation model will be considerably less expensive and time consuming than conducting field experiments. This paper reports the results of using such a model for making important water management decisions, such as determining: (a) optimum soil moisture depletion and replenishment levels; and (b) timing and a m o u n t of irrigation during different crop growth stages.
INTRODUCTION
In the last two decades, agronomists and irrigation engineers have developed crop yield models relating crop yield and water use (Barrett and Skogerboe, 1980). Although these models serve a meaningful purpose, they are limited in their application as yield predictive models. More specific relationships between crop yield and growth factors are presented by water production functions. Some o f these models include factors such as fertilizer, plant population, soil properties and climatic conditions (Hexem and Heady, 1978). In spite of including other factors besides water and fertilizer, these production functions are not generalized functions. One o f the logical approaches in the direction of quantifying the effects of environmental variables on yield is using a crop growth simulation model
0378-3774/82/0000--0000/$02.75 © 1982 Elsevier Scientific Publishing Company
254
{Brouwer and De Wit, 1969; Splinter, 1964; Duncan, 1975; Feddes et al., 1978). Such a model must be able to translate the complex interactive nature of the soil-plant-atmospheric system. A model, developed by Childs et al. {1977) and later modified by Tscheschke and Gilley (1979), successfully predicted grain yields of corn for several varieties, sites, years, and irrigation treatments. This model (CORNGRO) was further modified by Kundu {1981). The overall prediction results indicated that this model can be effectively used to provide insight regarding water management policies. The primary objective of this paper is to show that a reliable crop growth simulation model can be used for making water management decisions, such as determining: (a) optimum soil moisture depletion and replenishment levels; (b) timing and amount of irrigation during different crop growth stages; and (c) for developing site and crop specific yield -- water use relationships. Another objective is to show that such a model also helps to explain the effects of different water management policies. BRIEF DESCRIPTION OF THE CORNGRO MODEL
A concise flow chart of the CORNGRO model is presented in Fig. 1. The input data requirements for the model may be broadly classified as: (a) plant charaeterization parameters; (2) irrigation and daily climatic data; and (3) soil characteristics. Basically, the model consists of two major parts: (1) moisture flow program; and (2) plant growth program. The model initially separates the daily input potential evapotranspiration into potential evaporation and transpiration. The actual evaporation during each time step is calculated based on plant leaf-area cover, the potential evaporation rate for the time step, and the soil moisture status in the top two soil nodes from where no water is assumed to be extracted by the plant root system. Actual transpiration is determined from the minimum leaf water potential attained during the time step, potential transpiration rate, soil moisture contents in the depth nodes, and the root water extraction pattern. Soil moisture content at the end of each time step is calculated based on the root water extraction pattern and solving a tridiagonal matrix of a set of equations using the soil matric potential. Unlike the soil moisture flow calculations, which are based on variable time steps, the plant growth calculations are made for every even hour starting at dawn (06:00). Growth respiration for each hour is calculated using the photosynthetic rate, total plant dry weight, air temperature, available carbohydrate in the tissues of the plant, and plant leaf area. The plant dry matter accumulation is estimated by a relationship using growth respiration and leaf area. The leaf and stem growth is considered to continue until the accumulated degree days is equal to the input degree days for tasseling and, from then on, ear growth continues until maturity.
255
I Input data and initialization
I
oo,,, Looo
Separation of Potential Evaporation and Transpiration
r ,=--,
I
I Root Growth ~ I
--I
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Actual Evaporation Rate Calculation
i Actual Transpiration Rote Root Water Extraction
I
1
Soil MoistureFlow i
Shorten time increment
1~ J
Plant Growth
k
1
Yes
I
I Check for Tasseling or Crop Maturity.Compute Cumulative soil water change and Plant Growth Parameters Present Output Data and Predictions
Fig. 1. Concise flow chart of the CORNGRO model (modified from Childs et al., 1977). CONQ is the maximum allowable change in the soil moisture content at any soil depth node.
256 APPLICATIONS OF THE MODIFIED CORNGRO MODEL
Optimum soil moisture depletion level One of the c o m m o n questions is "at what level of available soil moisture content should irrigation be initiated for a specific crop variety in a specific location?" The specificities of the variety and location arise from knowledge regarding the influence of different crop varieties and soil properties u p o n plant growth processes. To illustrate this point, t w o different corn varieties and locations are considered where plants are irrigated at different levels of total available water {TAW). The input data for corn variety, soil and climatic conditions at Grand Junction, CO (Barrett, 1977) and Davis, CA (Stewart et al., 1977) were used for this purpose. Seven levels of allowable soil moisture depletion were considered for the simulation runs to determine the water use efficiencies at different levels of allowable soil moisture depletion. The water use efficiency (WUE) is commonly defined as the weight of dry matter or marketable crop produced per unit volume of water. In this paper, WUE will be considered in terms of both grain and total dry matter yields and will be designated as GWUE and DMWUE, respectively. The relationships between seasonal ET and both grain and total dry matter yields are presented in Fig. 2 for the crop variety (Pioneer 3367A) at Grand Junction during 1976. This relationship is more vivid for total dry matter (TDM) yields than for grain yields. Closer observation of these curves indicate that the increase in yields with ET would also be fitted by straight lines for allowable TAW depletion levels between 40 and 90%. The maximum GWUE and DMWUE were found at 40% allowable TAW depletion level (shown by the straight lines plotted through the origin and tangent to the curves). The water budget presented in Table I reveals additional information. This table shows that both seasonal ET and transpiration during the pollination period are higher than in the other two growth periods. This would be expected because the transpiration rate is directly related to the leaf area index and the average leaf area index during the pollination period is at a maxim u m value. Field data presented by Stewart et al. (1977) does n o t consistently support this trend in ET. The reason behind this discrepancy may be attributed to the differences in the crop varieties, soil and climatic conditions, and the lengths of crop growth stages used in the computer simulation runs and in the field experiments reported by these researchers. The seasonal evaporation (which is ET minus transpiration values presented in Table I) increased with more frequent irrigation (i.e., irrigations scheduled at lower allowable TAW depletion levels). The more frequent irrigations kept the surface soil moister for longer time periods, which induced higher evaporation rates. However, in spite of higher seasonal evap-
257 14
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Fig. 2. Relationships between seasonal evapotranspiration and corn yields derived by the modified CORNGRO model for various levels of soil moisture depletion before irrigating at Grand Junction, CO, 1976. oration, irrigations at 40% allowable TAW depletion level could be justified for growing corn at the Grand Junction site in view of the higher percent increase in both grain and TDM yields compared to the increase in seasonal ET requirement. The curves in Fig. 3 for the corn variety (Funk 4444) at the Davis site show that no marked benefit in yields can be expected by irrigating at allowable TAW depletion less than 60%. Practically no increase in yields are visible with irrigations at lower allowable depletion levels. Practically no increase in GWUE and DMWUE occurred with irrigations at TAW depletion ranging from 90 to 40%. This p h e n o m e n o n m a y be explained by the water budget presented in Table II, which shows that little increase in transpiration resulted from more frequent irrigations; the increase in ET was caused by higher seasonal evaporation with increasing n u m b e r of irrigations. Table II also indicates that higher ET was concomitant with higher depletions from the soil moisture profile. The results o f extensive field experiments (Stewart et al., 1977) conducted at the Davis site supports this phenomenon. Stewart et al. (1977) reported that the water holding capacity of the Davis soil is high and if the entire soil profile is at field capacity at planting time, then root exploration alone satisfied a sufficient fraction of crop water needs in each growth stage to assure healthy growth. They also suggested that the soil at Davis is such that the water extraction pattern for the same variety o f
258 TABLE 1 G r a i n a n d t o t a l d r y m a t t e r yields, a n d w a t e r b u d g e t a ofsyntheticirrigationsat water (TAW} for Grand Junction, C O , 1 9 7 6
differentailowable depletionlevels oftotalavailable
Allowable depletion(%)
Yield (t/ha)
Irrigation (rata)
Rainfall (mra)
ET (mm)
Grain Total dry matter
25
40
50
60
70
80
8.437 13.746
8.058 13.141
7.214 11.734
6.763 10.823
6.580 10.588
6.447 10.063
90 5.936 9.469
V P M
177 217 18]
118 167 192
161 113 118
95 127 143
117 165 166
0 159 191
0 190 213
S
575
477
392
365
448
350
403
V P M
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
S
38
38
38
38
38
38
38
V P M
197 -245 197
-191 230 -173
167 -220 -163
-156 -205 157
145 212 157
145 195 -152
-145 186 -150
S
-639
594
-550
518
514
--492
-481
Transp~ation
V
(mra)
P M
143 --197 -160
r141 -199 -150
-126 187 151
120 -180 --140
120 179 139
-120 -173 135
-120 -165 -135
S
-500
--490
-464
440
-428
-420
V P M
3 4 4
3 5 5
3 6 5
3 6 5
3 7 5
3 7 5
3 6 6
S
5
7
8
8
9
9
9
V P M
0 14 8
13 89 32
42 63 13
9 34 16
-126 - 20 40
-126 - 15 70
S
22
28
10
41
Drainage (ram)
Profile b
depletion (rata)
-
35 50 26
-
59
-108
438
-118
-
a Negative signs indicate water went out of the soil profile. b p r o f i l e d e p l e t i o n w a s calculated after accounting for the error in moisture balance equation of the p r o g r a m . V , v e g e t a t i v e ; P, p o l l i n a t i o n ; M, m a t u r a t i o n ; S, s e a s o n a l .
• . . "corn would occur every year if grown without post-germination irrigation, provided the soil was initially at field capacity." The above results show that the WUE resulting from irrigations at various TAW depletion levels is clearly the result of plant and soil characteristics. It can also be inferred that climatic conditions do not influence water use efficiency per se, since the climatic factors generally also influence the plant growth process with accompanying changes in the evapotranspiration rates.
Partial replenishment of soil moisture depletion Once the question of an optimum allowable TAW depletion level for a specific plant variety and soil type has been answered, another question of
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500 600 700 800 SeQsonol ET, mm Fig. 3. Relationships between seasonal evapotranspimtion and corn yields derived by the
modified CORNGRO model for various levels of soil moisture depletion before irrigating at Davis, CA, 1974. interest would be the effect on yields of applying irrigation water in amounts such that it replenishes only a fraction of the total depletion for each irrigation event. For example, if 40% of the TAW is depleted before an irrigation, h o w much o f the depleted a m o u n t should be replenished in that irrigation. Irrigating to less than field capacity m a y be justified by providing a better r o o t zone environment. Where an impermeable layer exists below the soil profile, like in Grand Junction, it could also be useful to k n o w the effects of over-irrigating. The expected effects of such over-irrigation would be: (a) lowered yields due to anaerobic conditions in the soil for a longer time period; and (b) the subsurface drainage of excess water to the impermeable layer. The input data corresponding to crop and soil characteristics and climatic conditions at the Grand Junction site were used for this purpose. Table III presents grain and total dry matter yields, and water budgets for six different replenishment levels. Each replenishment level consisted of irrigating the desired (10, 20, 30, 40, 50 or 60) percent of the TAW after 40% of TAW is depleted below field capacity. Therefore, the 40% replenishment level in Table III corresponds to field capacity at the completion of an irrigation event. The results o f the simulation runs (Table III) indicate that yields (grain and total dry matter) and seasonal transpiration were barely reduced with lower replenishment levels. Table III also shows that seasonal ET remained almost unchanged for replenishment levels ranging from 10 to 50%. Only very slight reductions in corn yields were found with over-irrigation by 10
260 T A B L E II
Grain and total dry matter yields, and water budget a of synthetic irrigations at different allowable depletion levels of total available water (TAW) for Davis, C A , 1 9 7 4 Allowable depletion (%)
Yield (t/ha)
Irrigation (ram)
Rainfall (ram)
ET (mm)
Transpiration (mm)
Drainage (mm)
Profile b Depletion (mm)
Grain Total dry matter
25
40
50
60
70
80
90
11.073 20.216
11.039 20.078
11.021 20.041
10.953 19.853
10.802 19.523
10.463 18.852
10.555 18.833
V P M
313 128 241
113 196 130
75 252 165
100 161 196
128 -219
193 261
237 ---
S
682
439
492
457
347
454
237
V P M
24
24 .
24
24
S
24
24
24
24
24
24
24
V P M
-301 -200 223
-194 201 -221
180 -200 219
-170 198 219
- 165 193 -220
164 195 206
165 -153 245
S
724
-616
-599
-587
577
-.565
563
V P M
127 186 -202
-128 192 192
129 -184 201
124 180 -204
123 - 184 201
127 177 196
--130 -178 200
S
-515
512
-514
508
508
500
508
V P M
16 1 31
7 - 11 48
7 16 53
6 17 57
6 21 53
6 - 20 66
6 20 65
S
14
52
62
68
68
80
79
V P M
20 74 45
66 6 42
89 70 1
53 20 28
23 172 48
46 85 146
90 139 180
S
9
102
19
45
147
15
-229
.
.
24 . .
24
. .
.
.
.
.
-
24 .
.
.
.
.
a Negative signs indicate water went out of the soil profile. bprofile depletion was calculated after accounting for the error in moisture ablance equation of the program. V , vegetative; P, pollunation; M, m a t u r a t i o n ; S, seasonal.
and 20% of TAW (corresponding to 50 and 60% replenishment levels). The results show that the WUE for irrigations at the 60% replenishment level is slightly higher than that for irrigations at the 40% replenishment level (corresponding to field capacity). Slightly increased WUE due to irrigations at the 60% replenishment level resulted from lower seasonal evaporation (ET minus transpiration) because of fewer irrigations. The irrigation amounts applied at different growth stages do not show any consistent pattern with replenishment levels (Table III). The results of the simulation runs indicate that these inconsistencies were caused by different dates and amounts of irrigations required for different replenishment levels. For example, irrigations at both 40 and 50%, replenishment levels required two irrigations during the pollination period totaling 167 and 217 mm, re-
261 TABLE III
Grain and total dry matter yields, and water budget a of synthetic irrigations a t 4 0 % allowable depletion o f total available water ( T A W ) and various levels of soil moisture replenishment for Grand Junction, C O , 1 9 7 6 Percent o f T A W applied in each irrigation after 40% depletion
Yield (t/ha)
Irrigation (mm)
Rainfall (mm)
ET (mm)
Transpbation (mm)
Drainage (ram)
Profile b
Depietion (ram)
Grain Total dry matter
10
20
30
40 c
50
7.568 12.167
7.965 12.900
8.018 13.072
8.058 13.141
8.031 13.093
60 8.022 13.093
V P M
95 213 184
90 207 193
87 249 142
118 167 192
148 217 119
80 229 142
S
482
490
478
477
484
451
V P M
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
22 13 3
S
38
38
38
38
38
38
V P M
-177 -231 -189
-176 -236 -185
-178 -237 -184
-191 -230 -173
-178 -232 -182
-176 -232 -173
S
-597
-597
-599
-594
-592
-581
V P M
-131 -189 -148
-134 -196 -153
-136 -198 -155
-141 -199 -150
-136 -198 -156
-136 -198 -155
S
-468
-483
-489
-490
--490
-489
V P M
-
2 5 4
2 5 4
S
7
V P M
- 66 4 11
-
S
-
-
81
-
2 5 4
3 6 4
2 5 4
7
7
7
7
64 18 13
- 66 37 39
-
69
- 68
-
-
2 4 5 7
35 49 25
-
1 13 58
-
-
67 15 24
59
-
46
-
76
aNegative sign~ indicate water went out of the profile. b p r o f i l e depletion was calculated after accounting for the error in the moisture balance equation of the program. c Corresponds to field c a p a c i t y . V , v e g e t a t i v e ; P, p o l l i n a t i o n ; M, m a t u r a t i o n ; S, seasonal.
spectively; whereas, at the 30% replenishment level, four irrigations were required totaling 249 mm of water application. Lower irrigation amounts during the pollination period at the 40% replenishment level and during the vegetative period at the 60% replenishment level resulted in higher root zone depletions during these growth stages. Similarly, lower irrigation application amounts during the maturation period at the 50% replenishment level resulted in higher root zone depletions during this growth stage. The results show that lower replenishment amounts for each irrigation event require more frequent irrigations which increase seasonal evaporation and decrease WUE. The results also indicate that irrigating strictly on the basis of replenishment level may result in a lower irrigation application during a critical growth stage (e.g., the pollination period). Therefore, criti-
262 cality of different growth stages should be taken into account to determine the optimum replenishment level. The overall conclusion of the above analysis is that the optimum level of depletion from total available water (TAW) for the Grand Junction site is 40%.
Partial replenishment at different crop growth stages To take the above conclusion one step further, it is instructive to verify the effects of levels of depletion and replenishment with reference to irrigation events occurring at different crop growth stages. For this purpose, irrigation treatments were defined with reference to the growth stages of the crop. A treatment consisted of applying irrigation water (I) during one or more of the three growth stages and withholding irrigation (0) in the others. To reduce the computer costs, only treatment II0 and 010 were considered. Barrett and Skogerboe (1978) observed that treatments 000,010 and II0 gave the maximum water use efficiency with respect to grain yield. In addition, since the optimal level of TAW depletion before irrigating was found to be 40% at the Grand Junction site, it was decided to synthetically schedule the irrigation events for these two treatments (treatments II0 and 010) in such a way that the plants are irrigated whenever TAW is 60%. However, each irrigation event will apply only 10, 20, 30 or 40% (replenishment level) of the TAW. Analysis of the water budget and final yields of tl~e t w o treatments (Table IV) show that there is no definite correlation between replenishment level and yields for either of the two treatments. But in both cases, yields are well-correlated with the corresponding values of seasonal transpiration. The results of the simulation runs indicate that the apparent incoherence in the relationships of yields both with seasonal ET and irrigation replenishment levels can be attributed to the date and replenishment level of each irrigation event. Especially, when no irrigation is applied during the maturation period, the last date of irrigation during the pollination period becomes most important. The date and amount of this irrigation event determines how much soil moisture will be available during the maturation period for grain formation. For example, Table IV shows that there is a considerable difference between grain yields at the 30 and 40% irrigation replenishment levels for treatment 010, whereas stover yields (total dry matter minus grain yields) are unchanged at 3.965 t/ha. The last irrigation dates for these t w o cases were 29 July and 7 August, respectively, while the corresponding irrigation amounts were 64 and 92 mm. Table IV also indicates that at the end of the pollination period, soil moisture depletion from the soil profiles for the two cases were 111 and 56 mm, respectively, which resulted from the timing of the last irrigation event as explained above and the total irrigation amount during the pollination period. Prior to the last irrigation event in a growth stage, the dates of other irriga-
263 TABLE IV
Grain and total dry matter yields, and water b u d g e t a o f synthetic irrigations a t 4 0 % depletion level o f T A W a n d various levels of soil moisture replenishment for treatments I I 0 a n d 010 a t G r a n d Junction, CO, 1 9 7 6 . Treatment II0
Treatment 0 1 0
Percent o f T A W replenished in each irrigation after 40% depletion 10
Yield (t/ha)
Irrigation (mm)
Rainfall (mm)
Grain Total dry matter
20
6.275 10.878
6.680 11.619
124 173
30
40
6.394 11.45
6.931 12.018
V P M
95 188 .
S
283
297
264
265
V P M
22 13 3
22 13 3
22 13 3
22 13 3
.
87 177 .
118 167 .
.
10
20
5.957 9.918
. 253
30
6.401 10.375
.
.
40
5.729 9.694
6.631 10.596
.
251 .
219
285
253
251
219
285
22 13 3
22 13 3
22 13 3
22 13 3
.
.
S
38
38
38
38
38
38
38
38
ET (mm)
V P M
177 -231 143
176 236 148
-178 -234 -143
-182 - 230 152
-146 241 133
146 226 138
146 217 124
146 --223 141
S
-551
560
- 555
564
- 520
- 510
487
- 510
Transpi-
V P M
131 189 -142
-134 196 146
. -136 198 142
-136 199 150
120 178 132
120 178 136
120 178 123
120 178 138
S
462
-476
476
-485
430
-434
-421
436
V P
2 6
2 5
2 5
2 5
M
5
6
6
S
9
9
9
V P
- 66 - 29 -135
- 30 - 52 -140
66 - 32 135
230
222
233
ration (mm)
Drainage (ram)
Profileb Depletion (mm)
M S
2 4
2 4
2 5
6
6
6
6
6
9
8
8
8
8
25 50 144
-126 25 -124
-126 46 129
126 15 116
-126 70 132
- 219
225
209
227
188
-
-
-
2 4
a Negative signs indicate water went out of the soil profile equation of the program. b p r o f i l e depletion was calculated after accounting for the error in the moisture b a l a n c e . V , v e g e t a t i v e ; P, p o l l i n a t i o n ; M, m a t u r a t i o n ; S, seasonal.
tion events do not indicate any appreciable affect on the physiological growth of corn, which seems to be one of the limitations of the CORNGRO model. However, the amount of each irrigation is important. Higher replenishment levels result in higher average soil matric potentials during the irrigation interval. Since the photosynthetic rate is directly related to a function of soil matric potential in the CORNGRO model (Tscheschke and Gilley, 1979), therefore, higher average soil matric potentials during the irrigation interval contribute to higher photosynthetic rates and therefore, to increased plant growth. The results of treatment II0 can be analyzed in a manner similar to those of treatment 010. In this treatment, the seasonal ET and yields at the 30% TAW replenishment level were higher than those at the 10% TAW replenish-
264
ment level. This resulted from the higher average soil matric potential at the 60% level as compared with the 10% level during the first two growth stages. Also, the increase in stover yield resulted from higher average soil matric potentials at the higher replenishment levels during the vegetative period. In summary, the results of the various irrigation treatments based on depletion of available soil moisture indicate that it is not only possible to use a crop growth simulation model for making water management decisions, but such a model is also helpful in explaining the effects of different water management policies.
Evapotranspiration and yields To further demonstrate the applicability of a crop growth simulation model for water management purposes, the effects of irrigating corn at different growth stages can be derived. The literature suggests that the relationships between seasonal ET and grain yield (GY) or total dry matter yield (TDMY) of corn are linear in nature (for more detail, see Barrett and Skogerboe, 1980}. In general, researchers have observed that this linearity is stronger between seasonal ET and TDMY than between seasonal ET and GY. Severe water stress during a critical growth period may result in considerable data scatter (Stewart et al., 1975) because the effect of the severity of stress on corn yields is dependent on the varietal characteristics and soil properties (Stewart et al., 1977). The CORNGRO model (Kundu, 1981) was used to study the relationship between seasonal ET and yields in relation to the site conditions at Grand Junction in 1976. Seven irrigation treatments based on several combinations of weekly irrigations during different growth stages were chosen. For each irrigation event, four levels of irrigation water application were employed. Treatment 000 was excluded from this particular investigation since it does not involve any irrigation. The water application levels comprised of weekly irrigations during the desired growth stage(s) in amounts equal to 25, 50, 75 and 100% replenishment of the soil moisture depleted during the period prior to irrigation as determined by the moisture balance equation. When the water application level is equal to 100% during a growth stage, it implies that there is essentially no soil moisture stress during that growth stage. But, whenever the water application level is less than 100%, the soil moisture deficit would gradually increase during the growth stage and result in moisture stress conditions if the water application level is too low. The results of the synthetically scheduled irrigations are presented in Table V. Figs. 4 and 5 show the relationships of seasonal ET with grain and total dry matter yields, respectively. Both curves show strong linearity between seasonal ET and yields. For grain yield the relationship is slightly weaker (r 2 = 0.913} than that for the total dry matter yield (r 2 --- 0.979}. In general, the data scatter is narrower than those observed from field data by other researchers (Stewart et al., 1977; Barrett and Skogerboe, 1978).
265
TABLE V Seasonal ET and corn yields of various synthetically irrigated treatments (input data from Grand Junction, Colorado, 1976) (From Barrett, (1977) Treatment
ET replenished each irrigation (%)
Seasonal (mm )
Grain yield (t/ha)
TDM yield (t/ha)
HI
25 50 75 100
360 514 587 658
2.665 5.334 6.897 8.138
6.222 9.486 11.513 13.172
II0
25 50 75 100
352 454 556 622
2.638 4.182 6.025 7.568
6.195 8.338 10.644 12.604
IOI
25 50 75 100
364 492 553 618
3.361 5.535 6.338 7.109
6.832 9.557 10.682 11.972
0II
25 50 75 100
367 496 538 571
2.979 5.604 6.899 7.323
6.740 9.539 10.866 11.297
I00
25 50 75 100
307 348 388 442
2.319 2.480 2.924 3.600
5.794 6.514 7.281 8.476
OIO
25 50 75 100
354 435 510 530
2.822 4.508 6.124 6.858
6.583 8.447 10~93 10.833
00I
25 50 75 100
359 430 449 459
3.621 5.282 5.669 5.724
7.162 8.817 9.203 9.257
T h e values o f t h e positive i n t e r c e p t o n t h e seasonal E T axis (abscissa) o f Figs. 4 and 5 indicate t h a t n o grain o r t o t a l d r y m a t t e r yields will a c c r u e b e l o w t h e respective i n t e r c e p t values o f ET. These i n t e r c e p t s s h o w t h a t m o r e seasonal E T ( 1 8 4 m m ) is r e q u i r e d t o p r o d u c e a n y grain t h a n t o p r o d u c e a n y d r y m a t t e r (45 m m ) w h i c h is o b v i o u s since grain p r o d u c t i o n starts a f t e r t h e vegetative g r o w t h stage. F r o m these o b s e r v a t i o n s , it m a y be inferred t h a t
266
14
I
I
I
I
I
I
Treatment 12
o III [] IIO IOi
I0 Oj.-
eOII
.d
• IO0
• 010
001 .E
E
/
/ /
4 •.,"
V"
O
~m
// // //
0
0
I
,1"
IO0
2 O0
I
1
I
I
300 400 500 600 700 Seasonal ET, mm Fig. 4. Relationship between seasonal evapotranspiration and corn grain yield predicted by the modified CORNGRO model for various irrigation treatments at Grand Junction, CO, 1976. Each irrigation treatment consisted of weekly irrigations to replenish ET and drainage as determined by the moisture balance equation; four levels of replenishment consisting of 25, 50, 75 and 100% replenishment of ET plus drainage during the period preceding the irrigation. a b o u t 45 m m o f soil m o i s t u r e would e v a p o r a t e b e t w e e n t h e planting and g e r m i n a t i o n dates u n d e r climatic c o n d i t i o n s similar t o G r a n d J u n c t i o n , 1976, p r o v i d e d t h e initial soil m o i s t u r e profile is at field capacity. These d a t a also indicate t h a t u n d e r m o i s t u r e stress c o n d i t i o n s at least a n o t h e r 139 m m o f e v a p o t r a n s p i r a t i o n would o c c u r b e f o r e grain p r o d u c t i o n would start. While c o m p a r i n g t h e c o r r e s p o n d i n g values o f seasonal E T i n t e r c e p t s pres e n t e d b y S t e w a r t et al. ( 1 9 7 7 ) and B a r r e t t and S k o g e r b o e (1978), it was observed t h a t at several instances t h e i n t e r c e p t values o n the seasonal E T axis for t o t a l d r y m a t t e r yields were higher t h a n the c o r r e s p o n d i n g values for grain yields. T h e r e a s o n b e h i n d this d i s c r e p a n c y m a y be a t t r i b u t e d t o the wider scatter o f field observed yield d a t a for t h e various irrigation treatments. CONCLUSIONS
T h e results o f s y n t h e t i c a l l y irrigating at several d e p l e t i o n and replenishm e n t levels s h o w t h a t a c r o p g r o w t h s i m u l a t i o n m o d e l can be effectively used t o schedule irrigation events with respect t o the c r o p variety, soil and
267 14
,
,
1
I
I
I
/'
o" 12
9"
Treatment o Ill n IIO
I0
,", IOI o
• Oil /
• IO0
,¢
• 010
._m >- 6
v 001 /
/
/
/
I1"
//
4 / // / // / // // "
/ I
100
I
I
2OO
300 Seosonol
I
I
400 500 ET, mm
I
600
700
Fig. 5. Relationship between seasonal evapotranspiration and total dry matter yield of corn predicted by the modified CORNGRO model for various irrigation treatments at Grand Junction, Colorado, 1976. Each irrigation treatment consisted of weekly irrigations to replenish ET and drainage as determined by the moisture balance equation; four levels of replenishment consisting of 25, 50, 75 and 100% replenishment of ET plus drainage during the period preceding the irrigation. climatic conditions. The results showed t h a t the m a x i m u m water use efficiency, WUE, for Grand J u n c t i o n conditions can be obtained if corn plants are irrigated when 40% of total available water is depleted, when the root zone is replenished to field capacity by each irrigation. For the Davis site, the r o o t growth and soil characteristics are such that the depletion level of 60% or less results in practically no reduction in WUE provided the soil was at field capacity at the time of planting. For depletion levels greater than 60%, the WUE was sharply reduced. The results of synthetically irrigating at several replenishment levels to different irrigation treatments also indicate t h a t yields are n o t appreciably affected by increasing the n u m b e r of irrigations during one or more growth stages. Rather, the date and a m o u n t of the last irrigation is more important if no irrigation would be applied in the following growth stage. The simulation results for synthetically scheduled weekly irrigations for various water treatments showed t h a t both grain and total dry matter yields are linearly related to seasonal ET. This conclusion substantiates the observations of other researchers (Stewart et al., 1977; Barrett and Skogerboe, 1978, 1980). The results of the synthetic irrigation runs show that the resolution in
268
using a plant growth simulation model, such as CORNGRO, for water management purposes is not only feasible but also highly promising.
REFERENCES
Barrett, J.W.H., 1977. Crop yield functions and the allocation and use of irrigation water. Unpublished Ph.D. Dissertation, Colorado State University, Fort Collins, CO, 210 pp. Barrett, J.W.H. and Skogerboe, G.V., 1978. Effect of irrigation regime on maize yields. J. Irrig. Drainage Div., ASCE, 104 (IR2): 179--194. Barrett, J.W.H. and Skogerboe, G.V., 1980. Crop production functions and the allocation and use of irrigation water. Agric. Water Manage., 3: 53--64. Brouwer, R. and De Wit, C.T., 1969. A simulation model of plant growth with special attention to root growth and its consequences. In: W.J. Whittington (Editor), Root Growth. Butterworths, London, pp. 224--244. Childs, S.W., Gilley, J.R. and Splinter, W.E., 1977. A simplified model of corn growth under moisture stress. Trans. ASAE, 20(5): 858--865. Duncan, W.G., 1975. Maize. In: L.T. Evans (Editor), Crop Physiology. Cambridge University Press, London/New York, pp. 23--50. Feddes, R.A., Kowalik, P.J. and Zaradny, H., 1978. Simulation of Field Water Use and Crop Yield. John Wiley and Sons, New York/Toronto, 188 pp. Hexem, R.W. and Heady, E.O., 1978. Water Production Functions for Irrigated Agriculture. Iowa University Press, Ames, IO, 215 pp. Kundu, S.S., 1981. Corn yield predictions by plant growth simulation. Unpublished Ph.D. Dissertation, Colorado State University, Fort Collins, CO, 264 pp. Splinter, W.E., 1974. Modeling of plant growth for yield prediction. Agric. Meterol., 14: 243--253. Stewart, J.I., Misra, R.D., Pruitt, W.O. and Hagan, R~I., 1975. Irrigating corn and grain sorghum with a deficient water supply. Trans. ASAE, 18(2): 270--280. Stewart, J.J., Hagan, R.M., Pruitt, W.O., Danieison, R.E., Frankling, W.T., Hanks, R.J., Riley, J.P. and Jackson, E.B., 1977. Optimizing crop production through control of water and salinity levels in the soil. Report PRWG151-1, Utah Water Research Laboratory, Utah State University, Logan, UT, 191 pp. Tschesehke, P.D. and Gilley, J.R., 1979. Status and verification of Nebraska's corn growth model--CORNGRO. Trans. ASAE, 22(6): 1329--1337.