Search

The impacts of extreme weather events on crop production are largely heterogeneous along the timing dimension of the shocks, and the varieties being affected. We investigate the yield-temperature relationships for three categories of earliness of durum wheat: early-maturing, middle-maturing, and late-maturing. We disentangle the time dimension distinguishing five phenological stages, as identified by the Growing Degree Days approach. Our panel regression models show that the starting, growing, and anthesis stages are sensitive to changes in minimum temperatures, regardless of wheat earliness. Raises in maximum temperatures during the starting stage are associated with increases in yields until a certain threshold above of which decrease; the opposite is true for increases in maximum temperatures in the maturity stage for latematuring varieties, and in the end stage for early-maturing varieties. Results imply that farmers and policymakers may adopt ex-ante and ex-post risk management strategies, i.e., choice of variety to avoid severe yield losses and incentives to crop insurance uptake, respectively. [ABSTRACT FROM AUTHOR]

Sensitivity analysis (SA) is increasingly used to explain models behaviour in response to inputs variation. Agrometeorologists are used to apply standard SA methods only on model parameters because of the difficulty of applying standard sampling techniques to derive series of weather data where each value cannot be sampled independently from those of the neighbouring days and from other variables in the same day. The impact of weather variability on a crop model was here analysed by coupling the Morris SA method to a weather generator. Spring barley in northern Italy was simulated and different outputs considered. Under the explored conditions, parameters involved with temperature generation resulted the most relevant in determining yield and maturity date. Radiation-related parameters were high-ranked for cumulated drainage and actual evapotranspiration. According to the author, this is the first time the sensitivity of a cropping system model to weather variables is quantified using standard SA techniques. [ABSTRACT FROM AUTHOR]