Effect of topographical and soil complexity on potato yields in irrigated fields

Abstract

Spatial variation of soil moisture as affected by topography and soil textural patterns is an important control on variability of yields in agricultural fields. Site-specific irrigation management could be a way of increasing water use efficiency and evening out yield variability. A better understanding of regional landscapes is required to identify which types of fields could benefit from SSIM. The causal influence of landscape characteristics on yields under irrigated conditions is poorly understood. Here, a new approach is used to infer the causal impact of topography and soil properties on yields of irrigated potatoes. The analysis comprises a four-year long dataset of potato yield, soil texture, hydrological, topographical, and meteorological variables collected from 99 sites within 19 fields in southern Alberta, Canada, from 2019 to 2022 inclusive. Using a Bayesian linear mixed model, we quantified the effect of topographical complexity (median equal −3.39 MT ha⁻¹), soil texture complexity (median equal −1.97 MT ha⁻¹), and the cases where both were true (median equal −4.47 MT ha⁻¹), on potato yields. Using the same method, we quantified the effect on initial soil water storage with medians equal to −13.1 mm (topographical complexity), 1.7 mm (soil complexity), and −6.7 mm (both). The topographical and soil complexity metrics applied could be used to identify fields that are suitable for SSIM-VRI. Findings are likely specific to the geographical and weather conditions encountered in the study area. We encourage implementation of our method in different regions to determine the generality of our results.