Abstract
Drought can severely limit plant growth, and in turn crop productivity, and poses challenges to global food production. Plant growth can be measured with the Green Leaf Area Index (GLAI), and satellite images offer opportunities to estimate GLAI at field and landscape scales. Analysing satellite-estimated GLAI development at the landscape level could reveal new insights into how soil characteristics influence crop performance under various weather conditions, which in turn could provide information on how to mitigate the impacts of extreme weather. In this study, we quantified winter wheat growing patterns in two years with contrasting weather conditions (2018: early summer drought; 2021: normal growing conditions) on farmers’ fields using Sentinel-2 derived GLAI, and assessed the impacts of drought on GLAI dynamics. Moreover, we tested whether soil properties can explain differences in GLAI dynamics between a dry and a normal weather year. Sentinel-2 scenes were downloaded from Microsoft Planetary Computer and the radiative transfer model PROSAIL was used to estimate GLAI throughout the winter wheat vegetative growing season on farmers’ fields in the south of Sweden. Characteristic GLAI parameters such as growth rate, area under the curve, peak GLAI and timing of the peak were calculated from the GLAI time series. The impact of drought on winter wheat growth was assessed by comparing the GLAI parameters between the dry year 2018 with the normal weather year 2021. In addition, the GLAI parameters were related to several biological, chemical and physical soil properties measured on the farmers’ fields. The results showed lower GLAI parameters during the dry year compared to the normal weather year on the farmer’s fields. For some fields, there was a large difference between the years while for other fields a smaller difference. Plant available water content was found as the most important soil property in explaining the differences in GLAI parameters between the years. Our study demonstrates that satellite image analysis of GLAI dynamics can be used to identify plant stress responses on farmer’s fields. By analysing a dry and a normal year, we show that the impacts of drought can vary considerably between fields, and by combining GLAI estimates with measurements of soil properties, we identified plant available water content as a key soil property to explain differences between years. Thus, our results contribute to knowledge towards developing soil management strategies to mitigate the impacts of extreme weather.
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