The distribution of Van Genuchten model parameters on soil-water characteristic curves in Chinese Loess Plateau and new predicting method on unsaturated permeability coefficient of loess
Abstract:The unsaturated permeability coefficients are often used to solve geotechnical problems associated with unsaturated soils. But it is very difficult to measure. However, the unsaturated permeability coefficients can be predicted by the Soil-water Characteristic Curves (SWCCs). The Van Genuchten Model (VG model) is very rife as it’s smooth and good fitting, thus, it has the most research data. Therefore, the research data on VG model parameters (α, n, θs and θr) of Malan loess in Chinese Loess Plateau are collec… Show more
“…The results show that the spatial distribution of θ s , θ r , , and n all have zonal characteristics, exhibiting obvious spatial heterogeneity. Moreover, θ s , α, and n have similar spatial distribution characteristics with existed investigation results 60 in most areas within the LP, which validates the reliability of our survey to some extents. Fig.…”
Soil hydraulic parameters are vital for precisely characterizing soil hydrological processes, which are critical indicators for regulating climate change effects on terrestrial ecosystems and governing feedbacks between water, energy, and carbon–nitrogen cycles. Although many studies have integrated comprehensive soil datasets, data quality and cost challenges result in data completeness deficiencies, especially for deep soil information. These gaps not only impede methodological endeavours but also constrain soil parameter-based ecosystem process studies spanning from local profiles to global earth system models. We established a soil dataset across the entire Yellow River Basin (YRB) (795,000 km2) using high-density in situ field sampling. This observation-based dataset contains records of soil texture (2924), bulk density (2798), saturated hydraulic conductivity (2782), and water retention curve parameters (1035) down to a maximum depth of 5 m. This dataset, which extends the recorded data range for deep soil hydraulic parameters, is valuable as a direct data resource for environmental, agronomical and hydrological studies in the YRB and regions with similar pedological and geological backgrounds around the world.
“…The results show that the spatial distribution of θ s , θ r , , and n all have zonal characteristics, exhibiting obvious spatial heterogeneity. Moreover, θ s , α, and n have similar spatial distribution characteristics with existed investigation results 60 in most areas within the LP, which validates the reliability of our survey to some extents. Fig.…”
Soil hydraulic parameters are vital for precisely characterizing soil hydrological processes, which are critical indicators for regulating climate change effects on terrestrial ecosystems and governing feedbacks between water, energy, and carbon–nitrogen cycles. Although many studies have integrated comprehensive soil datasets, data quality and cost challenges result in data completeness deficiencies, especially for deep soil information. These gaps not only impede methodological endeavours but also constrain soil parameter-based ecosystem process studies spanning from local profiles to global earth system models. We established a soil dataset across the entire Yellow River Basin (YRB) (795,000 km2) using high-density in situ field sampling. This observation-based dataset contains records of soil texture (2924), bulk density (2798), saturated hydraulic conductivity (2782), and water retention curve parameters (1035) down to a maximum depth of 5 m. This dataset, which extends the recorded data range for deep soil hydraulic parameters, is valuable as a direct data resource for environmental, agronomical and hydrological studies in the YRB and regions with similar pedological and geological backgrounds around the world.
“…However, certain similarities emerged, particularly in the case of the saturated hydraulic conductivity (K s ) between BEST and Rosetta and the shape parameter (n) between A-P and Rosetta. It is noteworthy that the scale parameter (α), which governs the retention curve, typically reflects the pore size distribution and is closely tied to pore air entry pressure [64]. Considering the variability of soil texture, the extremely low dispersion of scale parameter α obtained using the Rosetta method raises significant concerns regarding its accuracy.…”
The hydrological cycle is strongly affected by climate changes causing extreme weather events with long drought periods and heavy rainfall events. To predict the hydrological functioning of Tunisian catchments, modelling is an essential tool to estimate the consequences on water resources and to test the sustainability of the different land uses. Soil physical properties describing water flow are essential to feed the models and must therefore be determined all over the watershed. A simple but robust ring infiltration method combined with particle size distribution (PSD) analysis (BEST method) was used to evaluate and derive the retention properties and the hydraulic conductivities. Physically based and statistical pedotransfer functions based on PSD were compared to test their potential use for different types of Tunisian soils. The functional sensitivity of these parameters was assessed by employing the Hydrus-1D software (PC Progress, Prague, Czech Republic) for water balance computations. This evaluation process involved testing the responsiveness and accuracy of the parameters in simulating various water balance components within the model. The evaluation of soil hydraulic parameters across the three used models highlighted significant variations, demonstrating distinct characteristics in each model. While notable differences were evident overall, intriguing similarities emerged, particularly regarding saturated hydraulic conductivity between BEST and Rosetta, and the shape parameter (n) between Arya–Paris and Rosetta. These parallels indicate shared hydraulic properties among the models, underscoring areas of agreement amid their diverse results. Significant differences were shown for scale parameter α for the various methods employed. Marginal differences in evaporation and drainage were observed between the BEST and Arya–Paris methods, with Rosetta distinctly highlighting a disparity between physically based models and statistical models.
“…The VG parameters of the entire vertical soil profile was set the same and kept constant (Mirus, 2015). According to the soil texture datasets of our sampled soils, the Rosetta model by Zhang and Schaap (2017) was selected to predict the VG parameters (i.e., α , n , θ r , and θ s ) and the estimated values were 0.006 cm −1 , 1.66, 0.06 cm 3 cm −3 , and 0.40 cm 3 cm −3 , respectively (Bai et al, 2020; Fang et al, 2023; Qiao et al, 2018). Manning's roughness coefficient was set at 0.04 through the whole catchment and kept constant for all scenarios as well, representing the vegetated land surface (Li & Pan, 2020; Lou et al, 2023; Zhang & Hu, 2019).…”
Since 1999, large‐scale ecosystem restoration has been implemented in the Loess Plateau, effectively increasing regional vegetation coverage. Vegetation restoration has significantly elevated the saturated hydraulic conductivity (Ks) of the near‐surface soil layers and increased the vertical heterogeneity of the Ks profile. Many studies have examined the change of runoff due to revegetation, yet the impacts of Ks profile on the soil moisture distribution and runoff generation processes were less explored. In this study, numerical simulations were conducted to investigate how changes in the Ks profile caused by vegetation restoration influenced the hydrological responses at event scale. The numerical simulation results show that the increase of surface Ks caused by vegetation restoration can effectively reduce runoff at event scale. Moreover, the enhancement of vertical heterogeneity of Ks profiles can significantly change the vertical profile of soil water content, prompting more water to percolate into the deep soil layer. When rainfall exceeds a threshold, the accumulation of soil water above the relatively less permeable layer can cause short‐term saturation in shallow soil layers, resulting in a transient perched water table. As a result, after the vegetation restoration in the Loess Plateau, though Horton overland flow is still the main runoff generation mechanism, there is a possibility of the emergence of Dunne overland flow under the high vegetation coverage (e.g., NDVI larger than 0.5). This emergence of new runoff generation mechanism, saturation excess runoff, in the Loess Plateau due to the vegetation restoration could provide scientific guidance for water and sediment movement, soil and water conservation practices, and desertification control in the Loess Plateau.
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