ALBERT

Description: In this database we present and analyze a global database of soil infiltration measurements, Soil Water Infiltration Global (SWIG) database, for the first time. In total, 5023 infiltration curves were collected across all continents. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and USA. In addition to its global spatial coverage, the collected infiltration curves cover a time span of research from 1976 to late 2017. In addition to infiltration data, basic information of the measurement location, the measurement method, soil properties, and land use were collected, which makes the database valuable for the development of pedo-transfer functions for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on the land use is available for 76 % of experimental sites with agricultural land use as the dominant type (~40%). We are convinced that the SWIG database will allow for a better parametrization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for use by public domain only and can be copied freely by referencing it. Data quality assessment is strongly advised prior to any use of this database. New data are welcomed to extend/update SWIG.

Description: Climate and numerical weather prediction models, re-analyses, as well as agroecosystem models, require adequate parameter values for soil hydraulic properties (describing e.g. the shape of the soil water retention and hydraulic conductivity curves) at the global scale. Resampling of soil hydraulic properties to a model grid is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce imprecision and parameter value discrepancies throughout spatial scales due to nonlinear shape of the hydraulic conductivity and water retention curves. Therefore, we developed a method to scale van Genuchten hydraulic parameters (theta_s, theta_r, alpha, n, Ks) to individual model grids and provide a global data set that overcomes the mentioned problems. The data set is based on the ROSETTA pedotransfer function of Schaap et al. (2001, doi:10.1016/S0022-1694(01)00466-8) applied to the SoilGrids1km data set of Hengl et al. (2014, doi:10.1371/journal.pone.0105992). The approach is based on Miller-Miller scaling that fits the shape parameters of the water retention curve to all sub-grid water retention curves to provide the best-fit parameter values for the grid cell at model resolution, here 0.25°; at the same it maintains the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local scaling parameters are also valid for this function. In addition, information on global sub-grid scaling variance is given that enables modelers to improve dynamical downscaling of (regional) climate models or to perturb soil hydraulic parameters for model ensemble generation. These improvements should allow for more informed studies of the effects of variability in soil physical properties on land surface-atmosphere exchange.

Description: Several studies currently strive to improve the spatial resolution of coarse scale high temporal resolution global soil moisture products of the satellite missions SMOS (Soil Moisture and Ocean Salinity), SMAP (Soil Moisture Active and Passive) and ASCAT (Advanced Scatterometer). Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability. The approach is based on a method that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. We provide a look-up table map that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set helps identifying adequate regions to validate coarse scale soil moisture products by providing a measure of representativeness of small-scale measurements for the coarse grid cell. Moreover, it contains important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions.

Description: We revisited the Vereecken database, which has been used to derive pedotransfer functions (PTFs) to estimate the soil hydraulic parameters of Belgian soils. We developed new PTFs based on the Mualem-van Genuchten model, constraining m = 1 - 1/n and using fewer parameters. The goodness-of-fit was similar to the one originally obtained by Vereecken. We used a one-step procedure that allows direct quantification of the correlation matrix and the uncertainties of the estimated parameter values. The coefficients of the new PTFs were estimated using a global search algorithm and they were validated against independent data. The PTFs have a wider range of applicability since: (i) they allow the use of the closed-form solution of the unsaturated hydraulic conductivity in the Mualem-van Genuchten model; and (ii) they consider the effect of macroporosity. We determined that the hydraulic conductivity measured close to saturation could not be estimated based on the available estimators; however, the hydraulic conductivity in the matrix domain was predicted with high accuracy.

Description: The kinetic fractionation factor (αK) controls to a large extent the isotopic enrichment of surface waters during evaporation (E). In contrast to the well-known vapor-to-liquid isotopic equilibrium fractionation factor, αK has still not yet been properly characterized for soil water evaporation. In this study, we investigated the αK daily dynamics during a series of three laboratory experiments differing in soil water availability and aerodynamic conditions. For this, we applied a commonly-used isotopic evaporation model and tested it in two different approaches. First, a two-end member mixing model ("Keeling plot") was fitted to the measured isotopic composition of the laboratory air water vapor to obtain αK. In a second approach, αK was obtained from the slope of the "evaporation line" in a dual isotopic coordinate system. For both methods, the isotopic composition of the soil water was determined non-destructively and online by sampling the soil water vapor with gas-permeable microporous tubing. Results highlighted the limitation of the first approach, as the determination of the isotopic composition of E with the Keeling plot was challenging with the laboratory setup. The second approach provided αK values within the range reported in the literature and pointed to the prevalence of turbulent water vapor transport under water-saturated soil conditions, but also at soil water content significantly lower than the saturated value. In a third experiment, temporal dynamics of the atmospheric water vapor intrusion in the topmost soil layer could be observed during an isotopic labeling pulse.