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Version: publishedVersion × Subject: Parameter uncertainty ×

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    Simultaneous Calibration of Grapevine Phenology and Yield with a Soil–Plant–Atmosphere System Model Using the Frequentist Method
    (Basel : MDPI, 2021-8-20) Yang, Chenyao; Menz, Christoph; Fraga, Helder; Reis, Samuel; Machado, Nelson; Malheiro, Aureliano C.; Santos, João A.
    Reliable estimations of parameter values and associated uncertainties are crucial for crop model applications in agro-environmental research. However, estimating many parameters simultaneously for different types of response variables is difficult. This becomes more complicated for grapevines with different phenotypes between varieties and training systems. Our study aims to evaluate how a standard least square approach can be used to calibrate a complex grapevine model for simulating both the phenology (flowering and harvest date) and yield of four different variety–training systems in the Douro Demarcated Region, northern Portugal. An objective function is defined to search for the best-fit parameters that result in the minimum value of the unweighted sum of the normalized Root Mean Squared Error (nRMSE) of the studied variables. Parameter uncertainties are estimated as how a given parameter value can determine the total prediction variability caused by variations in the other parameter combinations. The results indicate that the best-estimated parameters show a satisfactory predictive performance, with a mean bias of −2 to 4 days for phenology and −232 to 159 kg/ha for yield. The corresponding variance in the observed data was generally well reproduced, except for one occasion. These parameters are a good trade-off to achieve results close to the best possible fit of each response variable. No parameter combinations can achieve minimum errors simultaneously for phenology and yield, where the best fit to one variable can lead to a poor fit to another. The proposed parameter uncertainty analysis is particularly useful to select the best-fit parameter values when several choices with equal performance occur. A global sensitivity analysis is applied where the fruit-setting parameters are identified as key determinants for yield simulations. Overall, the approach (including uncertainty analysis) is relatively simple and straightforward without specific pre-conditions (e.g., model continuity), which can be easily applied for other models and crops. However, a challenge has been identified, which is associated with the appropriate assumption of the model errors, where a combination of various calibration approaches might be essential to have a more robust parameter estimation.
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    Noninvasive Estimation of Water Retention Parameters by Observing the Capillary Fringe with Magnetic Resonance Sounding
    (Hoboken, NJ : Wiley, 2014) Costabel, Stephan; Günther, Thomas
    The magnetic resonance sounding (MRS) method is usually applied for delineation and characterization of aquifer system stratification. Its unique property, distinct from other hydrogeophysical methods, is the direct sensitivity to water content in the subsurface. The inversion of MRS data yields the subsurface water content distribution without need of a petrophysical model. Recent developments in instrumentation, i.e., decreased instrumental dead times and advanced noise cancellation strategies, enable the use of this method for investigating the vadose zone. A possible way to interpret MRS measurements with focus on water retention (WR) parameters is an inversion approach that directly provides WR parameters by modeling the capillary fringe (CF inversion). We have developed this kind of inversion further to account for different WR models and present a sensitivity study based on both synthetic and real field data. To assess the general applicability of the CF inversion, we analyzed the resolution properties for different measurement layouts and the parameter uncertainties for different realistic scenarios. Under moderate noise conditions and if the water table position is known, all WR parameters except the residual water content can be reliably estimated. The relative accuracy of the estimated pore distribution index estimation is better for larger CF. Small measurement loops of 5-m diameter achieve the best resolution for shallow investigation depths of <10 m.