This dataset provides global maps (in GeoTIFF format) of mean values and coefficients of variation of saturated moisture content (cm3/cm3), field capacity (cm3/cm3), and permanent wilting point (cm3/cm3) estimated from 13-PTF ensemble model in 10 km resolution for surface soils (0-5cm). The R code used to compute the ensemble PTF models is also provided. Calculations are based on the methods developed in the paper entitled "Development of Hierarchical Ensemble Model and Estimates of Soil Water Retention with Global Coverage". The dataset is in GeoTIFF format, which can be read by R, Python, Matlab, etc, and most GIS software. Please cite our publication, if you use the dataset, ^_^ . Yonggen Zhang, Marcel G. Schaap, and Zhongwang Wei, (2020). Development of Hierarchical Ensemble Model and Estimates of Soil Water Retention with Global Coverage, Geophysical Research Letter.
<p>Accurately mapping soil water retention parameters is vital for modeling atmosphere-land interactions but is challenged by limited measurements and simulations globally. Ensemble pedotransfer functions (PTFs) have been highly recommended for use due to the higher reliability of ensemble models and the error compensation among ensemble members. However, conventional ensemble approaches assign a fixed weight to each PTF and may not fully utilize the strengths of individual PTFs. In this work, we developed a new ensemble approach based on an automated machine learning workflow to assign varying weights to assemble 13 widely used PTFs. The AutoML-assisted ensemble approach (AutoML-Ens), as well as the simple average (MEAN), Bayesian Model Average (BMA), and the hierarchical multi-model ensemble approach (HMME), were evaluated using the global coverage National Cooperative Soil Surbey (NCSS) Soil Characterization Database. Results indicate that AutoML-Ens approach performs better than the conventional approaches in terms of the coefficient of determination (R<sup>2</sup>) and root mean square error (RMSE). Three soil hydraulic parameters, i.e., saturated water content, field capacity, and wilting points, and their corresponding uncertainties, were further derived through the AutoML-Ens approach at a 30&#8217;&#8217;&#215;30&#8217;&#8217; geographical spatial resolution based on a global soil composition database (SoilGrids), which can be applied in the Earth System Modeling. This study demonstrated the necessity of dynamic weights assigning in ensemble approaches and the great potential of coupling data-driven (here, the AutoML) and modeling (empirically or physically-based PTFs) approaches in mapping global soil water retention-like parameters.</p>
Increasing evidence indicates that microscale heterogeneity is critical to interpret and predict macroscopic soil processes and functions. However, the difficulty of measuring soil characteristics, such as soil organic carbon (SOC) and microbe, at the micron level greatly hinders our understanding of how microscale soil heterogeneity quantitatively regulates macroscopic soil behaviors. Here, we investigated the effect of microscale distributions of soil water saturation (S), SOC content (CSOC), and microbial biomass (CMB) on soil heterotrophic respiration (SHR) using a microscale process- based model, which accounted for key aerobic processes controlling microbial decomposition of SOC. The microscale distributions of S, CSOC, and CMB in a heterogenous soil core were mathematically determined by assuming that they varied linearly with local soil porosity, which was derived from X-ray computed tomography (XCT), and the effect of soil microscale heterogeneity on SHR rates was thoroughly examined under different macroscale soil water saturation levels and carbon availabilities. The simulation results show that soil microscale heterogeneity stimulated macroscopic SHR only when it alleviated resource limits or environmental stress. For instance, the heterogeneous S improved the SHR rate by reducing microbial water stress or enhancing dissolved organic carbon (DOC) diffusion, whereas the heterogeneous CSOC enhanced CO2 flux by increasing DOC availability. In addition, the heterogeneous CMB promoted CO2 flux by increasing microbial accessibility of substrates. The interactions among water, SOC, and microbes at the micron scale may stimulate or restrict CO2 emission, depending on soil water saturation level and DOC availability. Furthermore, compared with the homogeneous distributions of S, CSOC, and CMB commonly used in current models, their heterogeneous distributions generated a more reasonable distribution of SOC decomposition rate. Given the nature of soil heterogeneity at the micron scale and the challenge of measuring microscale soil characteristics, this study unraveled essential microscale mechanisms controlling macroscale soil behaviors and provides a feasible approach to quantify the impacts of microscale soil heterogeneity by combining microscale modeling and XCT imaging.
Preferential flow is common in clay or expansive clay soils, involving water bypassing a large portion of the soil matrix. Dye tracer experiment and numerical modeling are used to simulate the surface runoff and subsurface preferential flow patterns influenced by the soil fracture network of a relatively steep hillslope system (slope angle equals to 10 degrees). The result of the experiments indicates that part of the water is infiltrated through cracks, leading to the delay of the initial runoff-yielding time and reduction of the discharge of the surface runoff. The soil water flow is mainly in the matrix when the intensity of precipitation is low. With the increasing of precipitation, soil water movement may become in the form of preferential flow through cracks. In addition, the nonuniformity of soil water infiltration and the depth of the average water infiltration increase as the precipitation intensity increases. To this end, the complete coupling model was established by using the surface-matrix-crack (SMC) model to simulate water flow within discrete fracture as well as to simulate water flow in the soil matrix based on the concept of dual permeability using the traditional Richards’ equation. In this model, the “cubic law” of fluid motion in cracks within smooth parallel plates and the two-dimensional diffusion wave approximation to Saint-Venant equations with momentum term ignored (two-dimensional shallow water equations) were used. The model divides soil water infiltration into two forms and uses the overall method to calculate the exchange of water between the crack networks and matrix regions as well as the exchange water between surface runoff and infiltration water. Results indicate that the SMC model has better performance compared with the traditional equivalent continuum model when those models are used to simulate the surface runoff movement and the soil water movement in the presence of cracks.
Abstract The driving forces, kill and recovery mechanisms for the end-Permian mass extinction (EPME), the largest Phanerozoic biological crisis, are under debate. Sedimentary records of mercury enrichment and mercury isotopes have suggested the impact of volcanism on the EPME, yet the causes of mercury enrichment and isotope variations remain controversial. Here, we model mercury isotope variations across the EPME to quantitatively assess the effects of volcanism, terrestrial erosion and photic zone euxinia (PZE, toxic, sulfide-rich conditions). Our numerical model shows that while large-scale volcanism remains the main driver of widespread mercury enrichment, the negative shifts of Δ 199 Hg isotope signature across the EPME cannot be fully explained by volcanism or terrestrial erosion as proposed before, but require additional fractionation by marine mercury photoreduction under enhanced PZE conditions. Thus our model provides further evidence for widespread and prolonged PZE as a key kill mechanism for both the EPME and the impeded recovery afterward.
In this paper, genetic algorithms and Collins method (GAs-Collins) are integrated to compute unit hydrograph (UH). On the basis of entropy principle and distribution function, this method regards hydrological system of the basin as a generalized set, simulates the UH of the runoff-routing with distribution function, searches the distribution function parameters with genetic algorithms(GAs), and the initial UH(IUH) can be obtained. Then, the Collins method is used to complete the final UH. According to the comparative analysis of actual case study, the GAs-Collins method has a more precise result than the other methods and it can also reveal the runoff-routing rule.
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