Separating the Effect of Meteorology on Maize Yield from the Impact of Other Factors in the Yellow River-water Irrigated Regions in Ningxia of China

Abstract

【Objective】 Variation in crop yield is the consequence of many natural and anthropogenic factors, and disentangling their impacts is important for improving agricultural management but difficult. The purpose of this paper is to propose and compared different methods to isolate the impacts of meteorological change on crop yield based on long time series of maize yield in Yellow River-water irrigated region in Ninxia province of China. 【Method】 The analysis is based on maize yield measured from1988 to 2019 in 6 counties located in the Yellow River-watered irrigation areas. We compared three methods for the separation: five -year moving average method, quadratic exponential smoothing method, and five-point quadratic smoothing method. The consistent correlation coefficient, trend coincidence conformity analysis method, consistency of climate change characteristics, which lead to the same rise-fall in meteorological yield, were used as the evaluation criteria. Their applicability and rationality were compared and analyzed. All methods were calibrated based on the relationship between meteorological factors and maize yield. 【Result】 All methods can fit the yield trend well. Compared with the average yield trend, the consistency correlation coefficients of all three methods were >0.5, suggesting that there was no significant difference between these methods for fitting the yield trend. The advantage of the quadratic exponential smoothing method and the five-point quadratic smoothing method is that they accurately describe the change in the yield as affected by national productivity and national policy. The change in the yield due to meteorological factors estimated by the five-point quadratic smoothing method described the effect of inter-annual meteorological factors better, and its associated meteorological yield model is able to describe the relationship between the meteorological factors and the maize yield. 【Conclusion】 Comprehensive analysis showed that the five-point quadratic smoothing method modeled the yield change due to meteorological factors better than the other two methods.

Keywords

• maize
• trend yield
• meteorological-induced yield
• separation methods