## 3 Results and Discussion
### Sensitivity Analysis  
The scatter plot for the DRAINMOD output with the change in input parameters for CS-3 suggests that the daily flow was most sensitive to the drainage design parameters such as drain spacing and depth. The parametric variation from \(-80\%\) to \(0\) had much steeper slopes (Figure 4) than the variation from \(0\) to \(80\%\). This finding indicates that the daily flow pattern, both in terms of closeness (NSE) as low as \(0.4\) and correlation (RSQ) as low as \(0.6\), are much different at the lower drain spacing and drain depth. However, the close drain spacing than the field settings (1220 cm) did not impact the overall cumulative flow much, as shown by the cumulative flow and PBIAS plot. A possible reason could be the sufficiency of the drainage system to remove the infiltrated water at this design. On the other hand, drain depth depicted remarkable effects in both daily flow and cumulative water balance, as well as the relative yield of corn. A decrease in drain depth by \(80\%\) yielded \(30\%\) less flow, and relative yield decreased to \(20\%\). The yield is impacted by drought or excessive water conditions, salinity, and planting delay. However, in this study, the effects of salinity and planting delay were not evaluated. The reduction in the relative yield is solely attributed to the excessive water stress on the crop due to ineffective removal at the root zone. Drainage coefficient (DC), a parameter indicating the capacity of drainage removal, impacted the flow to a specific range only. For instance, in CS-3 (Figure 4), figures for NSE and RSQ had a sharp drop from \(-50\%\) to \(-80\%\) due to the tile drains' limiting  
Figure 3: Observed and simulated daily drainage flow for CS-3 (**upper**), CS-4 (**lower**) for study period. hydraulic capacity to remove the maximum infiltration volume to transport away from the field. Kirkham depth impacted the cumulative flow results even if the daily flow indicators had the same output, while surface storage and slope did not vary the model outputs significantly at the given range. Soil parameters such as lateral conductivity of two different soil types had varying effects on both flow and relative yield. The lateral hydraulic conductivity of the third layer (LK3) from the surface impacted outputs of CS-3, while that of other layers was insignificant. However, for CS-4 (Figure 5), LK3 and LK2 were insignificant, while LK5, LK4, and LK1 held viable impacts on the flow and yield outputs. This was mainly due to the varying thickness of each layer for Drummer and Flanagan soil types. For instance, in Drummer soil, the thickness of the first layer was 18 cm while that in Flanagan was 46 cm. More variability in output was observed due to the change in the lateral conductivity of layer 1 in Flanagan. Layer 4, which was the layer consisting of tile drains, and layer 5, which was a layer just below the tile drains, had a notable effect on the model output of CS-4. For Drummer soil, layer 5 was the thickest layer and consisted of tile drains. However, it did not impact the local sensitivity of outputs. However, it played a significant role during model calibration using Monte Carlo simulation. This phenomenon is shown due to the non-additive and non-linearity of the model, whose sensitivity is only realized from global sensitivity analysis using the interaction of multiple parameters at once. Figure 4: DRAINMOD output sensitivity with parametric variation for field CS-3. Soil temperature parameters such as CICE, CDEG, and ZA did not impact the relative yield but significantly affected the flow outputs. The effects were more notable on the water balance as represented by a steep gradient for cumulative flow (Figures 4 and 5). CICE is associated with the critical ice content above, which infiltration stops, and CDEG with the rate of ice melt, which plays a role in water balance in the soil layers during winters. Thus, these parameters do not contribute to the relative yield of corn.