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Published byHenry Helling Modified over 9 years ago
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Optimizing Crop Management Practices with DSSAT
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Our Goal With increasing population and climate change, the ability to maximize crop production is essential. We want to be able to predict optimal management practices for a variety of situations, including under environmental stresses such as during a drought, while minimizing pollution from unused fertilizer. We will use DSSAT to simulate crop growth under a range of management practices and determine the combination that produces the largest yield with the smallest nitrogen pollution. Find areas of DSSAT that can be improved.
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Sensitivity Analysis Variables examined: o Days between irrigations 1 – 14 in increments of 1, 15 to 21 in increments of 3 o Total amount of water applied in irrigations throughout the growing season 200 to 500 mm in increments of 10 o Number of applications of Nitrogen as fertilizer 0 to 3 in increments of 1 o Total amount of nitrogen applied throughout the growing season 50 to 290 kg/ha in increments of 10, 300 to 400 in increments of 50 o Number of applications of Phosphorus as fertilizer 0 to 2 in increments of 1 o Total amount of phosphorus applied throughout the growing season 5 to 20 kg/ha in increments of 5, 40 to 100 in increments of 20
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Sensitivity Analysis Maize simulated in Ghana without precipitation Planting date: June 17, 2004 Harvest date: September 6, 2004
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Sensitivity Analysis
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Harvest: 7860 kg/ha Water amount: 320 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Optimal conditions:
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Harvest: 4160 kg/ha Water amount: 200 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Under-watered conditions:
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Harvest: 6375 kg/ha Water amount: 500 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Overwatered conditions:
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Harvest: 6198 kg/ha Water amount: 320 mm Days between irrigations: 15 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Infrequently watered conditions:
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Harvest: 5918 kg/ha Water amount: 320 mm Days between irrigations: 5 N applied: 100 kg N applications: 3 P applied: 40 kg P applications: 2 Sensitivity Analysis Fertilizer deprived conditions:
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Harvest: 4160 kg/ha Water amount: 200 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Under-watered conditions:
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Effects of Water Deficiency Optimal Conditions Under-watered Conditions
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Effects of Water Deficiency Optimal Conditions Under-watered Conditions
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Harvest: 6375 kg/ha Water amount: 500 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Overwatered conditions:
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Effects of Over-watering Optimal Conditions Over-watered Conditions
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Effects of Water Deficiency Optimal Conditions Over-watered Conditions
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Harvest: 6198 kg/ha Water amount: 320 mm Days between irrigations: 15 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Infrequently watered conditions:
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Effects of Watering Too Infrequently Optimal Conditions Infrequently watered Conditions
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Optimal Conditions Infrequently watered Conditions Effects of Watering Too Infrequently
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Harvest: 5918 kg/ha Water amount: 320 mm Days between irrigations: 5 N applied: 100 kg N applications: 3 P applied: 40 kg P applications: 2 Sensitivity Analysis Fertilizer deprived conditions:
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Effects of Fertilizer Deficiency Optimal Conditions Fertilizer Deprived Conditions
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Effects of Fertilizer Deficiency Optimal Conditions Fertilizer Deprived Conditions
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LAI vs harvest Days between irrigations Linear fit: LAI = 0.85858 + 0.00034544*harvest R squared value: 0.729
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Unused nitrogen vs harvest Unused nitrogen = nitrogen applied in fertilizer – cumulative nitrogen uptake
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Conclusion Performed exhaustive sensitivity analysis across six degrees of freedom. This can be used to help identify optimal management practice strategies. These simulations and optimizations can be reproduced with different crop types, weather information, and soil properties. Can help identify weaknesses in DSSAT – for example, LAI values seem to be off.
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Mysteries of DSSAT Why does overwatering reduce yield? o Water pushes nutrients deeper into the soil faster than roots can grow down? Why is there a spike in minimum harvest weight when nitrogen is added in two applications? Why is there a plateau in cumulative nitrogen uptake? o Crop doesn’t need more nitrogen in that growth stage? Why does nitrogen spontaneously appear in the top soil layer when water deprived? o Nitrogen from second layer is brought up along with water? Why does an LAI of three seem to be the maximum attainable value?
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LAI vs harvest Days between irrigations
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Unused nitrogen vs harvest Days between irrigations Unused nitrogen = nitrogen applied in fertilizer – cumulative nitrogen uptake
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Sensitivity Analysis
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