Abstract
The wheat production variability is not well-understood in hilly region, especially in loess-derived soils of Golestan province in Iran with a sub-humid climate. Topography can greatly influence the production of agricultural crops by affecting soil quality. A study area located in Golestan province was selected in order to assess the spatial variability of wheat production and to develop regression models between the crop, soil properties, and topography attributes. The samples of wheat and soil were randomly taken from 100 points at different hillslope positions (i.e., shoulder, back-, foot-, and toe-slope). The soil physicochemical analysis and the measurement of wheat yield components were conducted. The digital elevation model (DEM; 10 m resolution) was used, and the topographic attributes (i.e., elevation, slope, wetness index, stream power index, curvature, erosivity factor, and watershed specific area) were calculated. The results showed that the greatest total yield and the highest grain yield were estimated to be 14.53 and 4.41 ton ha−1, respectively, in areas with a slope of less than 10%, which were significantly higher than those in the steep areas (slope classes of 10–30% and > 30%). The highest and the lowest total yields, with average values of 15.82 and 5.68 ton ha−1, were observed in the toeslope and shoulder slope positions, respectively. The greatest grain yields were obtained from the foot- and toeslope positions with the average values of 4.61 and 4.66 ton ha−1, respectively. The topographic curvature and wetness index had a significant correlation with the yield of wheat. According to the regression equations, topographic indexes can well justify the spatial variability of wheat yield, indicating the importance of these factors by influencing the distribution of moisture during the process of wheat production in the study region. The enhancements of wheat yield components in the lower slope positions could be attributed to an increase in soil depth and plant available water as well as to the accumulation of further soil organic matter and nutrient elements, including nitrogen and potassium, in such positions as a result of soil redistribution. Moreover, the results illustrated that by using easy accessable, cheap, and none destructive data (DEM derivatives and soil properties); it is possible to predict the production yield of wheat with a reliable estimation. We concluded that for better farming management and productivity in hilly regions, topographic attributes should be considered for plantation. Therefore, this study introduces the most suitable slope positions and topographic attributes for crop production with the least soil degradation. Shoulder and backslope positions are the most unsuitable slopes possibly better for orchards while toeslopes and footslopes could be used for intensive crop production.
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