# Impact of Subsurface Drainage System Design on Nitrate Loss and Crop Production
## 2 Materials and Methods
### Data Collection, System Monitoring, and Statistical Analysis  
To obtain the meteorological data, we used two different data sources. The first data source was the Champaign station data, obtained from the Water and Atmospheric Resources Monitoring Program at the Illinois State Water Survey, located 4 km away from the study area. Another source of data was from field measurements collected by the WatchDog weather station near our site, located 1.6 km away. The daily meteorological data from both stations were used to validate the data and also fill in the missing values. The collected meteorological data were used to calculate the water balance for each water year from 1 October to 30 September. We also obtained the remotely sensed evapotranspiration data to calculate the water balance. We collected MODIS Evapotranspiration data (MOD16A2 product) from the NASA Distributed Active Archive Center (DAAC), which  
Figure 2: Field boundaries and surface flow line of CS-field with Lidar DEM (**left**) and Topographic Position Index (TPI) map (**right**).  
had a 500 m spatial resolution and an 8-day data gap [29]. The product is based on the algorithm of the Penman-Monteith equation and uses the meteorological reanalysis data and 8-day remotely sensed vegetation property dynamics from MODIS to calculate 8-day evapotranspiration [29].  
Each monitoring station was equipped with a v-notch weir and logger for monitoring daily drainage flow and recording water pressure at the outlet of subsurface drainage systems. The station was instrumented to measure the flow rate at 10-min intervals using a Hobo water level logger (Onset U20-001-01, Bourne, MA, USA). Two barometric sensors were installed in the control structure CS-1 and CS-6 for recording atmospheric pressure, which was used to compensate for reading errors by the individual water depth sensors at both sites.  
Sensor data were downloaded once a month, and drainage flow rates were calculated using a calibrated V-notch weir equation as described by [30]. Water samples were collected twice a week (Tuesdays and Fridays) from March to October and once a week (Fridays) from November to February using the grab sampling method. Additional water samples were collected following extreme rainfall events. The collected water samples were analyzed for NO\({}_{3}\)-N in the Water Quality Laboratory of the Department of Agricultural and Biological Engineering at the University of Illinois. The samples were stored at a temperature of 4 \({}^{\circ}\)C until the time of analysis in the laboratory. The hydrazine sulfate reduction method with an auto-analyzer was used to determine the nitrate-N concentrations of the water samples. The detection limit for nitrate-N was 0.07 mg L\({}^{-1}\). The measured stage and time of the recorded stages were utilized to calculate subsurface flow rates and volumes. Nitrate-N loads were calculated using nitrate-N and concentrations and computed tile flow volume based on the flow-weighted mean concentrations method. The mass loss for each plot was divided by the area of each plot and reported in kilograms per hectare (kg ha\({}^{-1}\)).  
A single-factor ANOVA was performed to determine the difference in the drained water flow and nitrate-N loads and concentration, followed by [PERSON]'s honest, significant test. A single-factor ANOVA determines whether there are statistically significant differences between the means of three or more independent groups, but it does not confirm where those differences lie. [PERSON]'s HSD test was performed to confirm which specific group's means were different. A 95% confidence interval was adopted for both ANOVA and Tukey tests.