Cotton yield variability in relation to irrigation rates, soil physical properties and topography

Lack of precipitation and groundwater for irrigation limits crop production in semiarid regions, such as the Southern High Plains (SHP). Advanced technologies and optimized management strategies are required to conserve water and improve water use efficiency for sustainable agricultural production in semiarid regions. Variable rate irrigation (VRI) technology can optimize water application by incorporating field variability to achieve water savings. However, the adoption of VRI is hindered by the lack of on-farm and whole field research. Understanding crop yield response to irrigation rates at different landscape positions, soil physical properties, and their interaction is a prerequisite for developing management strategies to implement VRI. The objectives of this study were to: 1) identify cotton yield variability in response to irrigation rates at different soil physical properties and landscape positions; 2) assess the feasibility of VRI at the field scale. This study was conducted in a 194-ha commercially managed field in Hale County, Texas in 2017. An irrigation treatment with three rates was implemented in a randomized complete block design with two replications in two parts of this field with six 16-row strips. These strips were divided into 50-m subplots. A total of 230 composite soil samples were collected at three depths (0-15 cm, 15-30 cm, and 30-60 cm) in spring 2017. Soil samples were analyzed for texture using the Hydrometer method. Apparent soil electrical conductivity (ECa) was collected using a Veris 3100 EC mapping system. Elevation data was collected using a real-time kinematic GPS (RTK GPS) receiver with centimeter accuracy. A digital elevation model (DEM) was created from the elevation data and a slope grid was derived from this DEM. Cotton lint yield data were collected from the middle eight rows of each strip using strippers equipped with optical yield monitors. A statistical model was developed to assess cotton lint yield variability as affected by irrigation rates, soil physical properties, and topography. The model showed that the effect of irrigation on cotton lint yield depended on its interaction with soil physical properties and topography. Irrigation rates had no significant effect on cotton lint yield, possibly due to greater than long-term average in-season rainfall for 2017. However, cotton lint yield response to same irrigation rate varied with different landscape positions and soil physical properties. This response pattern of yield to irrigation rates suggests that applying irrigation based on the yield response model can be a basis for VRI. This study provides valuable information for site-specific irrigation to optimize crop production in fields with significant variability in soil physical properties and topography.

This thesis won 1st Place in the Texas Tech University Outstanding Thesis and Dissertation Award, Biological Life Sciences, 2019.