FIELD-SCALE SPATIAL AND TEMPORAL SOIL WATER VARIABILITY IN IRRIGATED CROPLANDS

This study investigated the spatiotemporal variability and temporal stability of soil water at various depths in two croplands sown in corn and cotton during the 2018 growing season in the Tennessee Valley Region (TVR) of northern Alabama. Classical statistics and relative difference approaches were used to analyze soil water data in this study. In the corn field, the 30-60 cm depth showed the greatest variability, while the cotton field showed the greatest variability at 0-15 cm depth. A decreasing trend was noticed between mean soil water and coefficient of variation for all depths in the cotton field and at 30-60 cm depth in the corn field. However, convex upward, exponential decreasing, or no trends were found between mean soil water and standard deviation at different depths in both fields. The temporal stability analysis showed one representative sensor (S8 in corn and S1 in cotton) for the entire soil profile in both fields. Different statistical tests, i.e., Spearman's correlation (rs), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), etc., were used to reduce uncertainty or increase confidence in the performance of representative sensors. Among various field attributes, topography in corn and soil properties in cotton were determined as significant factors responsible for soil water variability. Crop evapotranspiration (ETc) showed significant negative weak and moderate correlations with soil water in the corn and cotton fields, respectively. However, the mean air temperature showed a significant positive correlation with soil water in the corn field and a significant negative correlation in the cotton field. Solar radiation had a significant negative correlation with soil water in the cotton field and a non-significant correlation in the corn field. Accumulated growing degree days (accGDD) showed a significant negative correlation with soil water in the corn field and a positive correlation in the cotton field. This study gives insights into soil water variability, provides useful information about temporal stability, and identifies significant factors for precision uniform irrigation scheduling.