Management Effects on Relationships of Crop Yields with Topography Represented by Wetness Index and Precipitation

Abstract

Crop yields are highly variable spatially and temporally as a result of complex interactions among topography, weather conditions, and management practices. The objective of this study was to analyze the effects of management practices on the relationship between crop yields and precipitation and crop yields and topography using 10 yr of yield data from a long‐term corn (Zea mays L.)‐soybean [Glycine max (L.) Merr.]‐wheat (Triticum aestivum L.) rotation experiment in southwest Michigan. The four agronomic treatments studied were chisel plowed with conventional chemical inputs (CT), no‐till with conventional chemical inputs (NT), chisel plowed with low chemical input and a winter leguminous cover crop (CTL), and organic‐based chisel plowed with a winter leguminous cover crop (CTO). A nonparametric (spline) regression was used to characterize the relationship between the maximal yields, as characteristics of yield potential, and a wetness index (WI), as an integrative characteristic of topographical features related to water flow, and to compare the yield differences between the treatments across a range of the WI values. Variability of yields in NT and CTO systems was better explained by precipitation in early spring and during pollination and grain fill than that in CT and CTL. No‐till and CTL tended to produce higher maximal yields than CT at the summit/steep‐sloped areas (lower WI), while at intermediate and high WI levels the differences between them were inconsistent. The CTL often produced higher maximal yields than CTO at low and intermediate WI values, while the difference between them was mostly not significant at high WI levels (depression areas). The nonparametric spline regression algorithm used in the study was robust and efficient in comparing the yield differences between treatments across a range of WI values.