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  • Authors: Landl, M.;  Advisor: -;  Participants: Schnepf, A.; Uteau, D.; Peth, S.; Athmann, M.; Kautz, T.; Perkons, U.; Vereecken, H.; Vanderborght, J. (2019)

  • The model was calibrated against observed root length densities in both the bulk soil and biopores by optimizing root growth model input parameters. By implementing known interactions between root growth and soil penetration resistance into our model, we could simulate root systems whose response to biopores in the soil corresponded well to experimental observations described in the literature, such as increased total root length and increased rooting depth. For all considered soil physical (soil texture and bulk density) and environmental conditions (years of varying dryness), we found biopores to substantially mitigate transpiration deficits in times of drought by allowing roots to take up water from wetter and deeper soil layers. This was even the case when assuming reduced root ...

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  • Authors: Cai, C.;  Advisor: -;  Participants: Vanderborght, J.; Couvreur, V.; Mboh, C.M.; Vereecken, H. (2018)

  • These models were implemented in HYDRUS‐1D, and soil hydraulic parameters were optimized by inverse modeling using soil water content and potential measurements and observations of root distributions of winter wheat (Triticum aestivum L.) in horizontally installed rhizotubes. Soil moisture was equally well predicted by the three models, and the soil hydraulic parameters optimized by the models with compensation were comparable. The obtained RWU parameters of the Feddes–Jarvis model were consistent with data reported in the literature, although the pressure heads h3l and h3h for lower and higher transpirations rates, respectively, could not be uniquely identified. Response surfaces of the objective function showed that the root‐related parameters of the Couvreur model could be identi...

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  • Authors: Groh, J.;  Advisor: -;  Participants: Stumpp, C.; Lücke, A.; Pütz, T.; Vanderborght, J.; Vereecken, H. (2018)

  • We used different optimization strategies to investigate which observation types are necessary for simultaneously estimating soil hydraulic and solute transport parameters. Combining water content, matric potential, and tracer (e.g., δ18O) data in one objective function (OF) was found to be the best strategy for estimating parameters that can simulate all observed water flow and solute transport variables. A sequential optimization, in which first an OF with only water flow variables and subsequently an OF with transport variables was optimized, performed slightly worse indicating that transport variables contained additional information for estimating soil hydraulic parameters. Hydraulic parameters that were obtained from optimizing OFs that used either water contents or matric pot...

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  • Authors: Merz, S.;  Advisor: -;  Participants: Balcom, B.J.; Enjilela, R.; Vanderborght, J.; Rothfuss, Y.; Vereecken, H.; Pohlmeier, A. (2018)

  • Evaporation from bare soil surfaces can be restrained to a great extent with the development of a dry layer at the soil surface where capillary hydraulic conductance ceases and water flow proceeds only by gas phase transport. Model calculations and preliminary experiments with model porous media have shown that this surface layer can be very thin. An accurate characterization of these processes is required, which is provided by noninvasive magnetic resonance (MR) methods. The evaporative drying of a silt loam and a sandy loam was monitored at high spatial resolution in laboratory experiments. The MR data were used to assess the performance of two numerical models: (i) the Richards equation, which considers isothermal liquid water flow, and (ii) a coupled soil water, heat, and vapor ...

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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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