The results indicated that the introduction of an amplification factor can effectively improve model performances both in terms of soil moisture and runoff simulation. To test the usefulness of this approach, continuous 3D hydrological simulations were conducted with different spatial resolutions in the highly instrumented Wüstebach catchment. The loss of information content of terrain curvature as consequence of spatial aggregation was used to determine an amplification factor for soil hydraulic conductivity to compensate the resulting retardation of water flow. Information entropy concept was employed for the scale dependent parameterization of soil hydraulic conductivity. To further investigate how the reduction of local hydraulic gradients due to spatial aggregation can be partially compensated by increasing soil hydraulic conductivity. This study demonstrates the usefulness of the EOF and wavelet coherence methods for a more in-depth validation of spatially highly resolved hydrological 3D models. ![]() The wavelet coherence analysis indicates that wet and dry seasons have significant effect on temporal correlation between observed and simulated soil moisture and ET. The EOF analysis of temporal-spatial patterns of simulated and observed soil moisture revealed that introduction of heterogeneity in the soil porosity effectively improves estimates of soil moisture patterns. For a detail investigation of the model results the empirical orthogonal function (EOF) and wavelet coherence methods were applied. Different anisotropies of hydraulic conductivity were investigated to analyze how fast lateral flow processes above the underlying bedrock affect the simulation results. The simulated soil moisture dynamics, as well as evapotranspiration (ET) and runoff, were compared with long-term field observations to illustrate how well the model was able to reproduce the water budget dynamics. The estimated parameters were then used for 3D simulations of water transport using the integrated parallel simulation platform ParFlow-CLM. Soil hydraulic parameters were derived using inverse modeling with the Hydrus-1D model using the global optimization scheme SCE-UA and soil moisture data from a wireless soil moisture sensor network. In this study, high resolution long-term simulations were conducted in the highly instrumented TERENO hydrological observatory of the Wüstebach catchment. Unfortunately, it is not clear how to parameterize hydrological processes as a function of scale, and how to test deterministic models with regard to epistemic uncertainties. This dilemma can be circumvented by the adjustment of certain model parameters. However, aggregated data may be too coarse for the parametrization of the processes represented. ![]() In distributed hydrological modelling one often faces the problem that input data need to be aggregated to match the model resolution. Multiple methods have been applied for more accurate parameterizations. High reliability simulation of soil water content using various kinds of numerical modeling tools has been studied in recent years. There is a grand need to increase global-scale hyper-resolution water-energy-biogeochemistry land surface modelling capabilities. ![]() Soil moisture plays a key role in the water and energy balance in soil, vegetation and atmosphere systems.
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