ALBERT

Description: Soil CO2 efflux at a field site is often computed as the average of successive chamber measurements at several points to overcome the effects of spatial variability and microclimatic disturbances. As a consequence, the resulting data set has a coarser resolution in space (one average per site) and time than the raw data set. The deviations between raw measurements and the field average may provide additional insights, however, if they can be decomposed into a time-stable part, characterizing the spatial pattern of emission strengths, and a dynamic part, characterizing rapid changes in soil CO2 efflux. We evaluated data from several measurement campaigns in an agricultural landscape. First, we determined the persistence of spatial CO2 efflux patterns and found that [≥]50% of spatial variance was stable for at least 1 d in all examined crop and field types. For fields where vegetation and gradients in soil properties determined the spatial variation in CO2 efflux, some correlation was still found after 10 d. In a next step, we removed the time-stable patterns from the raw time series. The resulting estimate of instantaneous area-average soil respiration closely resembled the conventional spatiotemporal field average on days without rapid changes in meteorologic conditions. On days with fluctuations of radiation and temperature, in contrast, soil respiration reacted on a time scale from instantaneous to about 1 h. Based on a discussion of potential mechanisms underlying these reactions for a wheat (Triticum aestivum L.) and a sugarbeet (Beta vulgaris L. ssp. vulgaris) stand, we suggest that the proposed downscaling methodology, in combination with existing decomposition techniques, may help to examine the short-term dependence of heterotrophic and root respiration on radiation, temperature, and rain.

Description: Plants take up water from the root zone and thus affect the three-dimensional water flow field and solute transport processes in the soil. In this study, the impacts of root architecture, plant solute uptake mechanisms (passive, active, and solute exclusion), and plant transpiration rate on the water flow field in the soil and on solute spreading were simulated. Therefore, a fully mechanistic model was used to simulate water flow along water potential gradients in the root–soil continuum by coupling a three-dimensional Richards equation in the soil with a flow equation in the root xylem vessels. Solute transport was simulated using a three-dimensional random walk particle tracking algorithm. To quantify the effect of root water and nutrient uptake on solute transport, an equivalent one-dimensional flow and transport model was fitted to horizontally averaged simulation results, and the fitted apparent parameters were compared with the parameters of the three-dimensional model. Our simulation results showed that the apparent dispersivity length is affected by the heterogeneous flow field, caused by root water uptake, and changed in a range of 50%, depending on solute redistribution in the root zone that depends on solute uptake type and soil dispersivity length. In addition, simulation results indicate that local concentration gradients within the root zone have an impact on apparent solute uptake rate parameters used in one-dimensional models to calculate uptake rates from spatially averaged concentrations. This shows the importance of small scale three-dimensional water and solute fluxes induced by root water and nutrient uptake.

Description: In this paper we reviewed the use of microwave remote sensing methods for characterizing crop canopies and vegetation water stress related phenomena. Our analysis includes both active and passive systems that are ground-based, airborne, or spaceborne. Most of the published results that have examined crop canopy characterization and water stress have used active microwave systems. In general, quantifying the effect of dynamic vegetation properties, and water stress related processes in particular, on the measured microwave signals can still benefit from improved models and more observational data. Integrated data sets providing information on both soil status and plant status are lacking, which has hampered the development and validation of mathematical models. There is a need to link three-dimensional functional, structural crop models with radiative transfer models to better understand the effect of environmental and related physiological processes on microwave signals and to better quantify the impact of water stress on microwave signals. Such modeling approaches should incorporate both passive and active microwave methods. Studies that combine different sensor technologies that cover the full spectral range from optical to microwave have the potential to move forward our knowledge of the status of crop canopies and particularly water related stress phenomena. Assimilation of remotely sensed properties, such as backscattering coefficient or brightness temperature, in terms of estimating biophysical crop properties using mathematical models is also an unexplored avenue.

Description: Electromagnetic induction is a promising tool for fast electrical conductivity estimation of the near surface. A novel two-layer inversion of calibrated data from two coil orientations, offsets, and frequencies enables the reconstruction of lateral and vertical conductivity variations in the soil, which is in close agreement with ERT inverted data. Electromagnetic induction (EMI) measurements return an apparent electrical conductivity that represents a weighted average of the electrical conductivity distribution over a certain depth range. Different sensing depths are obtained for different orientations, different coil offsets, and different frequencies, which, in principle, can be used for a multi-layer inversion. However, instrumental shifts, which often occur in EMI data, prevent the use of quantitative multi-layer inversion. Recently, a new calibration method was developed that uses electrical resistivity tomography (ERT) inversion results and returns quantitative apparent conductivity values. Here, we introduce an inversion scheme that uses calibrated EMI data and inverts for a two-layer earth. The inversion minimizes the misfit between the measured and modeled magnetic field by a combined global and local search and does not use any smoothing parameter. Application of this new scheme to synthetic data demonstrates its efficacy in providing the required physical property information. Inversion of calibrated experimental EMI data using horizontal coplanar (HCP) and vertical coplanar (VCP) loop configurations, coil offsets of 1 and 1.22 m, and frequencies of 8 and 15 kHz provides lateral and vertical conductivity variations very similar to those observed in an elaborate ERT experiment. The inversion is verified using synthetic EMI data calculated from ERT data. Inverting quantitative EMI data using this two-layer inversion enables the quantitative mapping of lateral and vertical electrical conductivity variations over large areas.

Description: Multicompartment and multiscale long-term observation and research are important prerequisites to tackling the scientific challenges resulting from climate and global change. Long-term monitoring programs are cost intensive and require high analytical standards, however, and the gain of knowledge often requires longer observation times. Nevertheless, several environmental research networks have been established in recent years, focusing on the impact of climate and land use change on terrestrial ecosystems. From 2008 onward, a network of Terrestrial Environmental Observatories (TERENO) has been established in Germany as an interdisciplinary research program that aims to observe and explore the long-term ecological, social, and economic impacts of global change at the regional level. State-of-the-art methods from the field of environmental monitoring, geophysics, and remote sensing will be used to record and analyze states and fluxes for different environmental compartments from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere.