Differentiating between crop and soil effects on soil moisture dynamics
Abstract. There is urgent need for developing sustainable agricultural land use schemes. On the one side, climate change is expected to increase drought risk as well as the frequency of extreme precipitation events in many regions. On the other side crop production has induced increased greenhouse gas emissions and enhanced nutrient and pesticide leaching to groundwater and receiving streams. Consequently, sustainable management schemes require sound knowledge of site-specific soil hydrological processes, accounting explicitly for the interplay between soil heterogeneities and crops. Here we present a powerful diagnostic tool applied to a highly diversified arable field with seven different crops and two management schemes. A principal component analysis was applied to a set of 64 soil moisture time series.
About 97 % of the spatial and temporal variance of the data set was explained by the first five principal components. Meteorological drivers accounted for 72 % of the variance. Another 17 % was attributed to different seasonal behaviour of different crops. The effect of very low soil moisture in deeper layers at the onset of the growing season explained another 4.1 %, and soil texture 2.2 %. The fifth component represented the effect of soil depth (1.7 %). In contrast, neither topography nor weed control had a significant effect on soil moisture. Contrary to common expectations, soil and rooting pattern heterogeneity seemed not to play a major role in this case study.
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Dataset of TDR soil moisture data from a LoRaWAN based soil sensing network of a selection of sensors at patchCROP for December 2020 to August 2021 for a principal component analysis https://doi.org/10.4228/zalf-3rsc-6c30
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