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BEETSOIL: a decision support tool for forecasting the impact of soil conditions on sugar beet harvest

Gabarron-Galeote, Miguel A., Hannam, Jacqueline A., Mayr, Thomas, Jarvis, Patrick J.
Soil & tillage research 2019 v.191 pp. 131-141
autumn, decision support systems, field capacity, harvest date, models, prediction, rain, soil compaction, soil erosion, soil quality, soil water, soil water balance, soil water content, stickiness, sugar beet, texture, topsoil, trafficability, winter, United Kingdom
Sugar beet in the UK is harvested in autumn and winter, when soil moisture is usually close to field capacity. This, together with the heavy machinery used can lead to serious environmental problems such as topsoil disturbance, subsoil compaction and soil erosion. BEETSOIL is a decision support tool (DST) developed to help plan the sugar beet harvest campaign by assessing if soil conditions are suitable for harvest whilst minimising the occurrence of soil damage. The core of BEETSOIL is a soil water balance model that, using a rainfall source selected by the user, predicts soil water content in a determined prediction window. The resulting soil water content is used to predict soil trafficability, wheel sinkage, soil stickiness and soil loss due to harvest on a daily basis. The soil water balance module was validated with measured soil water content at three field sites with contrasting clayey, silty and sandy textures and showed RMSE of 0.91%, 0.96% and 0.52%, respectively. The sensitivity of the trafficability modules of BEETSOIL were tested using several scenarios using different initial soil water contents at the start of the harvest campaign combined with rainfall amounts that simulate wet, median and dry conditions during the harvest period. Analysis of the scenarios showed the trafficability module was very sensitive to changes in texture, initial soil water content of the simulation and rainfall. This information can be used to assess the suitability of new sugar beet growing areas, where the proportion of time during which fields can be trafficked by vehicles (harvested effectively) can be predicted under different scenarios and therefore give an indication of any consistent harvest difficulties. The model outputs of sinkage, trafficability and soil loss by harvest have yet to be validated, but the first outputs provide indications of how the DST can be used across the whole growing area to schedule harvest operations to target areas that can be harvested most effectively.