Very low yields ate a shorter duration

[razan-el]

Issues when comparing two simulations with different planting and harvesting dates:

I have two neighboring fields with all of the parameters the same except for the planting and harvesting dates. The planting of the second field is 29 days after the first one and the harvesting is 17 days before it. There is low temperature variation within the season and I used proportionality to alter the phenological state parameters to match the shorter duration of cultivation in the second field. From actual ground truthing I know that for this season the yield in the first and second fields are 2.6 and 2.4 tons/ha respectively. However, when I simulate for the 2 fields I get 2.1 for field 1 which is somehow reasonable but 0.15 for field 2 which is not logical. Can you please suggest to me what might be happening? because all of the other parameters are similar to field 1!

[Paloschi]

Hi Razan-el. When dealing with discrepancies in simulated yields in AquaCrop-OSPy, especially when they're as stark as the difference between 2.1 and 0.15 tons/ha, there are several potential factors to consider that might be influencing the output:

1. Phenological Parameters Adjustment: You mentioned that you used proportionality to alter the phenological state parameters for the shorter growing period in the second field. This method might oversimplify the crop's response to developmental stages, especially under conditions that are not standard (like shorter growing periods). The way in which you've proportionally adjusted parameters like crop coefficient 𝐾𝑐, root growth, or senescence might not fully capture the physiological response of the crop to the altered growing season. I strongly suggest you find out the proper stages from the seed that was used in each field, using the correct duration of maturing, flowering, etc.

2. Crop Development Model: AquaCrop heavily relies on temperature and its impact on phenology. Even though you noted that temperature variation is low, the model's sensitivity to temperature during critical growth phases could still be a factor. For the shorter growing season, it's possible that the model isn't adequately simulating a faster development or failing to accumulate enough biomass due to shortened growth stages, particularly if temperature-driven growth degree days are not being met as expected.

3. Soil Water Dynamics: Even with similar management and environmental settings, the change in planting and harvesting times can significantly affect soil moisture dynamics, which is a critical driver in the AquaCrop model. The earlier planting in the first field may benefit from better soil moisture conditions that aren't as favorable later in the season for the second field, affecting germination and initial growth stages.

4. Stress Factors: Check if any stress factors (like water stress, salinity, or nutrient limitations) are disproportionately affecting the second field due to its shifted growing window. Even minor changes in the timing of stress relative to sensitive growth stages (like flowering or tuber filling) can dramatically impact yield.

5. Model Calibration: Ensure that the model is properly calibrated for the specific crop variety and local conditions. If the model was calibrated primarily under conditions similar to those of the first field, its parameters might not be as applicable to the conditions of the second field.

6. Simulation Settings and Inputs Review: Double-check all input settings and parameters to ensure there's no inadvertent misconfiguration affecting the second field simulation. This includes checking the timing and amount of irrigation applied, the fertility status, and any pest or disease impacts.

To diagnose and address the issue, consider the following steps:

• Reassess the Proportional Adjustments: Review how the phenological adjustments are made and consider if a different approach might better capture the dynamics of the shorter season.

• Detailed Model Outputs: Analyze the detailed daily or weekly growth outputs from AquaCrop-OSPy for both fields to pinpoint where the growth discrepancies are occurring. Look at the biomass accumulation, water productivity, and stress indicators.

• Experiment with Calibration: Try calibrating the model separately for each field based on actual data from previous seasons if available, focusing on adjusting the parameters that are most sensitive to phenological changes.

• Consult Literature or Experts: If available, consult research papers or guides specific to modeling short season crops in AquaCrop or discuss with agronomists who have experience with crop modeling in similar conditions.

By systematically exploring these areas, you should be able to identify the cause of the discrepancy and improve the accuracy of your simulations.