Finding Soil Moisture Patterns for Optimal Sensor Placement for Sensor-based Irrigation Scheduling Variable Rate Irrigation System

Understanding the spatial and temporal dynamics of soil water within a field is critical for effective variable rate irrigation (VRI) management. Proper VRI can result in improved protection of the crop from early onset of crop water stress while minimizing runoff and drainage losses. Soil sensors can be utilized to manage irrigation within crops with both volumetric water content (VWC) sensors and matric potential sensors. These sensors can be very costly and cannot completely represent the spatial variation of soil water and crop stress dynamics throughout a field. Understanding how many sensors to place within a field and where to place them can be difficult to assess but can be useful for proper irrigation management. The objectives of this work are (i) find the optimal number of sensors to place in a field based on soil property and topographical differences, and (ii) find the optimal sensor placements in order to make irrigation decisions from those sensors within a field. Soil samples were taken within a 22 ha wheat-wheat-potato rotation field two to four times within a growing season in the years 2016-2019, and 2021 to calculate the spatial variation of VWC. Z-scores of the VWC at each sampling date were calculated and kriged on a 5m grid. A K-means clustering for each soil sampling event was then calculated and compared against other sampling dates throughout each season to find consistencies of VWC in order to find optimal number of sensors and sensor locations for the field. The z-score data of VWC was also combined with elevation and slope data to observe similarities or differences in sensor placements and number of sensors. Results showed no apparent patterns or significant differences. More variables such as topography, soil texture, and weather data will be incorporated into future analysis to find patterns for optimal sensor placements in agricultural fields