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  • Authors: Brogi, C.;  Advisor: -;  Participants: Huisman, J. A.; Herbst, M.; Weihermüller, L.; Klosterhalfen, A.; Montzka, C.; Reichenau, T. G.; Vereecken, H. (2020)

  • Soil hydraulic parameters were calculated using pedotransfer functions. Simulations of soil water content dynamics performed with the agroecosystem model AgroC were compared with soil water content measured at two locations, resulting in RMSE of 0.032 and of 0.056 cm3 cm−3, respectively. The AgroC model was then used to simulate the growth of sugar beet (Beta vulgaris L.), silage maize (Zea mays L.), potato (Solanum tuberosum L.), winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.), and winter rapeseed (Brassica napus L.) in the 1‐ by 1‐km study area. It was found that the simulated leaf area index (LAI) was affected by the magnitude of simulated water stress, which was a function of both the crop type and soil characteristics. Simulated LAI was generally consist...

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  • Authors: Kaufmann, M.S.;  Advisor: -;  Participants: Klotzsche, A.; Vereecken, H.; van der Kruk, J. (2020)

  • Recently, a novel simultaneous multi‐offset multichannel (SiMoc) GPR system was released, enabling rapid profiling with virtually continuous acquisition of WARR gathers. For this system, we developed a new processing approach. First, time shifts caused by the different cables and receivers were eliminated by a novel calibration method. In the obtained CMP gathers, groundwave and (when present) reflection velocities were determined with an automated semblance approach. The obtained velocity can be converted to permittivity and soil water content. We tested SiMoc GPR with a synthetic study and time‐lapse field measurements. In the synthetic study, the accuracy of velocity and layer thickness were within 0.02 m ns−1 and 2 cm. The SiMoc field results (spatial sampling of 5 cm) are consi...

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  • Authors: Klotzsche, A.;  Advisor: -;  Participants: Lärm, L.; Vanderborght, J.; Cai, G.; Morandage, S.; Zörner, M.; Vereecken, H.; van der Kruk, J. (2019)

  • The SWC data were analyzed for four growing seasons between 2014 and 2017, two soil types (gravelly and clayey–silty), two crops (wheat [Triticum aestivum L.] and maize [Zea mays L.]), and three different water treatments. We acquired more than 150 time‐lapse GPR datasets along 6‐m‐long horizontal crossholes at six depths. The GPR SWC distributions are distinct both horizontally and vertically for both soil types. A clear change in SWC can be observed at both sites between the surface layer (>0.3 m) and subsoil. Alternating patches of higher and lower SWC, probably caused by the soil heterogeneity, were observed along the horizontal SWC profiles. To investigate the changes in SWC with time, GPR and time‐domain reflectometry (TDR) data were averaged for each depth and compared with c...

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