On the spatio-temporal dynamics of soil moisture at the field scale

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.

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

One of the issues hampering progress in modelling greenhouse gas (GHG) emissions from soils is a lack of co-ordination between models originating from different disciplines: soil physics and soil biology. We have reviewed recent advances in modelling both gaseous transport and the biochemical processes in the soil that lead to the emission of the main biogeneic GHGs: CO2, N2O, and CH4. The precise coupling of gaseous transport and biochemistry is necessary because CH4 and N2O can be both produced and consumed in soil, and eventual flux to the atmosphere depends on the position of reaction sites and the escape pathways for these gases. The CO2 production rate depends in turn on the efficiency of oxygen transport in the soil. Principles leading to successful simulation are: keeping a balanced level of detail in coupled model systems describing biochemical reactions and transport; reduction of unnecessary complexity by means of using the most essential relationships elucidated by comprehensive statistical model testing; consideration of all transport mechanisms in relation to prevailing ecological conditions, i.e., diffusion and convection in the air and liquid phases, plant-mediated transport and ebullition. It is important to model all three major GHG in accord with the description of O2 and N2 transport and concentration in soil. This helps: i) to estimate the full global warming potential; ii) to apply the model algorithms considering partial gas pressure and gas species interactions; iii) to describe the O2 effect on the biochemical processes in soil. We discuss the approaches linking the simple and more complex process-oriented models, and propose a strategy for up-scaling model results from soil aggregate to profile and to the field/catchment.

Soil physics meets soil biology: Towards better mechanistic prediction of greenhouse gas emissions from soil

https://cyberleninka.org/article/n/1253087.pdf

Spatio-temporal soil moisture patterns - A meta-analysis using plot to catchment scale data

Mapping of anthropogenic trace elements inputs in agricultural topsoil from Northern France using enrichment factors

Soil respiration is known to be highly variable with time. Less is known, however, about the spatial variability of heterotrophic soil respiration at the plot scale. We simultaneously measured soil heterotrophic respiration, soil temperature, and soil water content at 48 locations with a nested sampling design and at 76 locations with a regular grid plus refinement within a 13- by 14-m bare soil plot for 15 measurement dates. Soil respiration was measured with a closed chamber covering a surface area of 0.032 m 2 . A geostatistical data analyses indicated a mean range of 2.7 m for heterotrophic soil respiration. We detected rather high coefficients of variation of CO 2 respiration between 0.13 and 0.80, with an average of 0.33. The number of observations required to estimate average respiration fluxes at a 5% error level ranged between 5 and 123. The analysis of the temporal persistence revealed that a subset of 17 sampling locations is sufficient to estimate average respiration fluxes at a tolerable root mean square error of 0.15 g C m −2 d −1 . Statistical analysis revealed that the spatiotemporal variability of heterotrophic soil respiration could be explained by the state variables soil temperature and water content. The spatial variability of respiration was mainly driven by variability in soil water content; the variability in the soil water content was almost an order of magnitude higher than the variability in soil temperature.

Characterization and Understanding of Bare Soil Respiration Spatial Variability at Plot Scale

Multivariate conditional stochastic simulation of soil heterotrophic respiration at plot scale

On the spatial variation of soil rhizospheric and heterotrophic respiration in a winter wheat stand

Analyzing spatiotemporal variability of heterotrophic soil respiration at the field scale using orthogonal functions

Bare soil evaporaƟ on was measured with the eddy-covariance method at the Selhausen fi eld site. The site has a disƟ nct gradient in soil texture, with a considerably higher stone content at the upper part of the fi eld. We invesƟ gated the eff ect of diff erent soil properƟ es in the upper and lower parts of the fi eld on evaporaƟ on using eddy covariance (EC) measurements that were combined with a footprint model. Because only one EC staƟ on was available, simultaneous evaporaƟ on measurements from the two fi eld parts were not available. Therefore, measurements were put into the context of meteorologic and soil hydrologic condiƟ ons. Meteorologic condiƟ ons were represented by the potenƟ al evaporaƟ on, i.e., the maximum evaporaƟ on that is determined by the energy available for evaporaƟ on. The infl uence of precipitaƟ on and soil hydrologic condiƟ ons on the actual evaporaƟ on rate was represented by a simple soil evaporaƟ on model. The amount of water that could be evaporated at the potenƟ al rate from the lower part of the fi eld was found to be large and considerably larger than from the upper part of the fi eld. The diff erence in evaporaƟ on led to threefold larger predicted percolaƟ on or runoff in the upper than the lower part of the fi eld. SimulaƟ ons using the Richards equaƟ on were able to reproduce the diff erences in evaporaƟ on between the lower and upper parts of the fi eld and relate them to the diff erent groundwater table depths in the two parts of the fi eld.

N. Prolingheuer

Papers

Characterization and Understanding of Bare Soil Respiration Spatial Variability at Plot Scale

Multivariate conditional stochastic simulation of soil heterotrophic respiration at plot scale

On the spatial variation of soil rhizospheric and heterotrophic respiration in a winter wheat stand

Analyzing spatiotemporal variability of heterotrophic soil respiration at the field scale using orthogonal functions

Within-Field Variability of Bare Soil Evaporation Derived from Eddy Covariance Measurements