Screening Deficit Irrigation Strategies Using Crop Growth Simulation
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Screening Deficit Irrigation Strategies Using Crop Growth Simulation R. Louis Baumhardt and Scott A. Staggenborg USDA- ARS Conservation and Production Res. Lab. Bushland , TX Kansas State University Plant Science Center, Manhattan, KS. Depth to Water. Depth to Water.

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Screening Deficit Irrigation Strategies Using Crop Growth Simulation

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Screening deficit irrigation strategies using crop growth simulation

Screening Deficit Irrigation Strategies Using Crop Growth Simulation

R. Louis Baumhardt and Scott A. Staggenborg

USDA-ARS Conservation and Production Res. Lab. Bushland, TX

Kansas State University Plant Science Center, Manhattan, KS


Screening deficit irrigation strategies using crop growth simulation

Depth to Water

Depth to Water

Irrigation Well No. 2 - Bushland, TX

Irrigation Well No. 2 - Bushland, TX

0

0

-50

-50

1957-77

1957-77

-100

-100

65 ft Decline

65 ft Decline

-150

-150

1977-98

1977-98

21 ft Decline

Depth Below Ground - ft

-200

21 ft Decline

Depth Below Ground - ft

-200

-250

-250

Red Bed

Red Bed

-300

-300

(aquifer bottom)

(aquifer bottom)

-350

-350

1955

1965

1975

1985

1995

2005

1955

1965

1975

1985

1995

2005

Year

Year

  • Well capacity has declined with the decreasing water table.

  • The choice is between deficit irrigation or concentrating water to adequately irrigate a portion.


Screening deficit irrigation strategies using crop growth simulation

Irrigation-strategy Question:

  • Will uniformly spreading water resources to deficit irrigate a large area produce more or less crop yield than if that same water resource was concentrated to irrigate a smaller area and averaged with the complementary dryland area?

Uniformly Irrigate

Variably Irrigate


Screening deficit irrigation strategies using crop growth simulation

APPROACH

  • Use crop growth simulators (SORKAM and GOSSYM) and recorded weather at Bushland from 1958-1999 to calculate sorghum grain and cotton lint yields for several deficit irrigation combinations.

  • Determine crop growth and yield response to deficit irrigation levels for various planting practices or cultivar maturity.


Screening deficit irrigation strategies using crop growth simulation

IRRIGATION PARAMETERS

  • Irrigation – 7 d application interval and 4 capacity levels:

    • No – Irrigation = Rain only

    • Irrigation + Rain = 2.5 mm d-1 (2 gpm/ac)

    • Irrigation + Rain = 3.75 mm d-1 (3 gpm/ac)

    • Irrigation + Rain = 5.0 mm d-1 (4 gpm/ac)


Screening deficit irrigation strategies using crop growth simulation

OTHER FACTORS

  • Sorghum:

    • Cultivar Maturity = Early (15-leaf), Medium (17-leaf), Late (19-leaf)

    • PlantingDate = 15 May, 5 June, 25 June

  • Cotton:

    • Irrigation Duration = 4 and 8 weeks


Model validation

MODEL VALIDATION

7000

SIMULATED = 390 + 0.95*MEASURED

r2 = 0.70

6000

RMSE = 903.5 kg ha -1

5000

4000

Simulated Grain Yield, kg ha-1

3000

2000

1:1

1000

0

0

1000

2000

3000

4000

5000

6000

7000

Measured Grain Yield, kg ha-1


Screening deficit irrigation strategies using crop growth simulation

1:1

Dryland

5.0 mmd-1

2:1

3.75 mmd-1

Dryland

UNIFORM

2.5 mmd-1


Screening deficit irrigation strategies using crop growth simulation

1:1

Dryland

5.0 mmd-1

2:1

3.75 mmd-1

Dryland

UNIFORM

2.5 mmd-1


Screening deficit irrigation strategies using crop growth simulation

SUMMARY

  • Simulated grain yield increased with increasing irrigation, but simulations also reflect generally better WUE at 3.75 mm d-1 than at 5.0 mm d-1 irrigation levels.

  • The weighted average grain yield for variable irrigation strategies with a dryland component increased net grain yield from 13% to >20% over uniformly irrigated sorghum.


Screening deficit irrigation strategies using crop growth simulation

CONCLUSION

  • For declining water resources, converting uniform deficit irrigation (water spreading) of a determinate crop like grain sorghum to variable irrigation that concentrates water on smaller areas with a complementary dryland area will increase overall sorghum grain yield.


Screening deficit irrigation strategies using crop growth simulation

4

-

Week irrigation

8

-

Week irrigation

Weighted

Percent

Weighted

Percent

Irrigation

Irrigation

Averag

e

of Base

Average

of Base

Strategy

Capacity

Yield

Yield

Yield

Yield

Yield

Yield

____

____

____

____

mm/d

%

%

kg/ha

kg/ha

UNIFORM

2.5

390

390

87

450

450

100

2:1

3.75

530

425

94

615

480

106

Dryland

220

220

1:1

5.0

660

440

98

7

20

470

104

Dryland

220

220

1:1

Dryland

5.0mm/d

2:1

3.75mm/d

Dryland

UNIFORM

2.5 mm/d

SIMULATED COTTON YIELD vs IRRIGATION STRATEGIES


Screening deficit irrigation strategies using crop growth simulation

CONCLUSION

  • Cotton yield levels are maintained or increased by converting from uniform deficit irrigation (water spreading) to variable irrigation on part of a field (concentrating water) with a complementary dryland area.


Screening deficit irrigation strategies using crop growth simulation

}

YEAR = 3

YEAR = 1

}

2.5”

2.0”

WHEAT

1.5”

O

S

A

N

D

1.0”

J

J

J

F

M

FALLOW

0.5”

A

M

0.0” Rain

A

M

F

M

J

J

SORGHUM

D

J

N

A

O

S

}

FALLOW

O

S

A

N

YEAR = 2

J

D

J

J

F

M

A

M

Wheat-Sorghum-Fallow Rotation

  • Two crops in three years,

  • Storage of precipitation as soil water,

  • Stable grain crop yields


35 11 n 102 5 w elevation 1170 m growing season 181 d

35 11’ N, 102 5’ WElevation = 1170 mGrowing season = 181 d

2500

Pan-Evaporation

2000

Precipitation

1500

WATER DEPTH, mm

1000

500

0

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

MONTH


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