Michael Herbst

Temporal Stability of Soil Water Contents: A Review of Data and Analyses

Temporal stability (TS) of soil water content (SWC) has been observed throughout a wide range of spatial and temporal scales. Yet, the evidence with respect to the controlling factors on TS SWC remains contradictory or nonexistent. The objective of this work was to develop the first comprehensive review of methodologies to evaluate TS SWC and to present and analyze an inventory of published data. Statistical analysis of mean relative difference (MRD) data and associated standard deviations (SDRD) from 157 graphs in 37 publications showed a trend for the standard deviation of MRD (SDMRD) to increase with scale, as expected. The MRD followed generally the Gaussian distribution with R 2 ranging from 0.841 to 0.998. No relationship between SDMRD and R 2 was observed. The smallest R 2 values were mostly found for negatively skewed and platykurtic MRD distributions. A new statistical model for temporally stable SWC fields was proposed. The analysis of the published data on seven measurement-, terrain-, and climate-related potentially controlling factors of TS SWC suggested intertwined effects of controlling factors rather than single dominant factors. This calls for a focused research effort on the interactions and effects of measurement design, topography, soil, vegetation and climate on TS SWC. Research avenues are proposed which will lead to a better understanding of the TS phenomenon and ultimately to the identification of the underlying mechanisms.

The influence of the spatial structure of soil properties on water balance modeling in a microscale catchment

Abstract The study investigates the impact of the spatial variability of soil hydraulic properties on hydrologic fluxes of the microscale Berrensiefen catchment (28.6 ha). In a first step the Mualem/VanGenuchten parameters are calculated from a point data set of soil properties using a pedotransfer function. In a second step, we estimated the Mualem/VanGenuchten parameters at unsampled locations using four different regionalization procedures: multiple regression, ordinary kriging, external drift kriging and regression kriging. The regression kriging results are taken as the reference distribution for a model study. A modified version of the 3d finite element model SWMS_3d is applied to simulate the water fluxes. With the model study the importance of the spatial features of soil hydraulic properties is quantified. Four spatial concepts are tested: a choropleth map of soil units, a catchment average, a spatial random distribution and a stochastic simulation approach. We particularly investigated the influence of the spatial concept on the modeled runoff generation. We quantified the sensitivity of runoff to the frequency distribution and to the spatial structure of the soil hydraulic properties. The frequency distribution mainly affects the amounts of the fast runoff components (surface and macropore flow) while the organized spatial variability affects the modeled temporal concentration of the fast runoff components. The effect on the calculated actual evapotranspiration is rather small.

Comment on "Global convergence in the temperature sensitivity of respiration at ecosystem level".

Mahecha et al. (Reports, 13 August 2010, p. 838) estimated the temperature sensitivity of ecosystem respiration (Q10) and showed that temperature sensitivity and its site-to-site variability are lower than previously reported. We demonstrate that their Q10 value of 1.4 is an underestimate if interpreted as the averaged sensitivities of all ecosystem components, because fast temperature fluctuations penetrate poorly into the soil.

Short Note: On preconditioning for a parallel solution of the Richards equation

In this paper, we present a class of preconditioning methods for a parallel solution of the three-dimensional Richards equation. The preconditioning methods Jacobi scaling, block-Jacobi, incomplete lower-upper, incomplete Cholesky and algebraic multigrid were applied in combination with a parallel conjugate gradient solver and tested for robustness and convergence using two model scenarios. The first scenario was an infiltration into initially dry, sandy soil discretised in 500,000 nodes. The second scenario comprised spatially distributed soil properties using 275,706 numerical nodes and atmospheric boundary conditions. Computational results showed a high efficiency of the nonlinear parallel solution procedure for both scenarios using up to 64 processors. Using 32 processors for the first scenario reduced the wall clock time to slightly more than 1% of the single processor run. For scenario 2 the use of 64 processors reduces the wall clock time to slightly more than 20% of the 8 processors wall clock time. The difference in the efficiency of the various preconditioning methods is moderate but not negligible. The use of the multigrid preconditioning algorithm is recommended, since on average it performed best for both scenarios.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives

Soil, through its various functions, plays a vital role in the Earths ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration and organic carbon content, root density and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves, link to model result files in NetCDF format

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids 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 uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller–Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves 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 parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25 at https://doi.org/10.1594/PANGAEA.870605.