Water flow from soil to plants depends on the properties of the soil next to roots, the rhizosphere. Although several studies showed that the rhizosphere has different properties than the bulk soil, effects of the rhizosphere on root water uptake are commonly neglected. To investigate the rhizosphere's properties we used neutron radiography to image water content distributions in soil samples planted with lupins during drying and subsequent rewetting. During drying, the water content in the rhizosphere was 0.05 larger than in the bulk soil. Immediately after rewetting, the picture reversed and the rhizosphere remained markedly dry. During the following days the water content of the rhizosphere increased and after 60 h it exceeded that of the bulk soil. The rhizosphere's thickness was approximately 1.5 mm. Based on the observed dynamics, we derived the distinct, hysteretic and time-dependent water retention curve of the rhizosphere. Our hypothesis is that the rhizosphere's water retention curve was determined by mucilage exuded by roots. The rhizosphere properties reduce water depletion around roots and weaken the drop of water potential towards roots, therefore favoring water uptake under dry conditions, as demonstrated by means of analytical calculation of water flow to a single root.

Abstract. In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.

Summary• Despite the importance of rhizosphere properties for water flow from soil to roots, there is limited quantitative information on the distribution of water in the rhizosphere of plants.• Here, we used neutron tomography to quantify and visualize the water content in the rhizosphere of the plant species chickpea (Cicer arietinum), white lupin (Lupinus albus), and maize (Zea mays) 12 d after planting.• We clearly observed increasing soil water contents (h) towards the root surface for all three plant species, as opposed to the usual assumption of decreasing water content. This was true for tap roots and lateral roots of both upper and lower parts of the root system. Furthermore, water gradients around the lower part of the roots were smaller and extended further into bulk soil compared with the upper part, where the gradients in water content were steeper.• Incorporating the hydraulic conductivity and water retention parameters of the rhizosphere into our model, we could simulate the gradual changes of h towards the root surface, in agreement with the observations. The modelling result suggests that roots in their rhizosphere may modify the hydraulic properties of soil in a way that improves uptake under dry conditions.

Hyporheic exchange transports solutes into the subsurface where they can undergo biogeochemical transformations, affecting fluvial water quality and ecology. A three-dimensional numerical model of a natural in-stream gravel bar (20 m 3 6 m) is presented. Multiple steady state streamflow is simulated with a computational fluid dynamics code that is sequentially coupled to a reactive transport groundwater model via the hydraulic head distribution at the streambed. Ambient groundwater flow is considered by scenarios of neutral, gaining, and losing conditions. The transformation of oxygen, nitrate, and dissolved organic carbon by aerobic respiration and denitrification in the hyporheic zone are modeled, as is the denitrification of groundwater-borne nitrate when mixed with stream-sourced carbon. In contrast to fully submerged structures, hyporheic exchange flux decreases with increasing stream discharge, due to decreasing hydraulic head gradients across the partially submerged structure. Hyporheic residence time distributions are skewed in the log-space with medians of up to 8 h and shift to symmetric distributions with increasing level of submergence. Solute turnover is mainly controlled by residence times and the extent of the hyporheic exchange flow, which defines the potential reaction area. Although streamflow is the primary driver of hyporheic exchange, its impact on hyporheic exchange flux, residence times, and solute turnover is small, as these quantities exponentially decrease under losing and gaining conditions. Hence, highest reaction potential exists under neutral conditions, when the capacity for denitrification in the partially submerged structure can be orders of magnitude higher than in fully submerged structures.

The characteristics of an aboveground cosmic‐ray neutron sensor (CRNS) are evaluated for monitoring a mountain snowpack in the Austrian Alps from March 2014 to June 2016. Neutron counts were compared to continuous point‐scale snow depth (SD) and snow‐water‐equivalent (SWE) measurements from an automatic weather station with a maximum SWE of 600 mm (April 2014). Several spatially distributed Terrestrial Laser Scanning (TLS)‐based SD and SWE maps were additionally used. A strong nonlinear correlation is found for both SD and SWE. The representative footprint of the CRNS is in the range of 230–270 m. In contrast to previous studies suggesting signal saturation at around 100 mm of SWE, no complete signal saturation was observed. These results imply that CRNS could be transferred into an unprecedented method for continuous detection of spatially averaged SD and SWE for alpine snowpacks, though with sensitivity decreasing with increasing SWE. While initially different functions were found for accumulation and melting season conditions, this could be resolved by accounting for a limited measurement depth. This depth limit is in the range of 200 mm of SWE for dense snowpacks with high liquid water contents and associated snow density values around 450 kg m−3 and above. In contrast to prior studies with shallow snowpacks, interannual transferability of the results is very high regardless of presnowfall soil moisture conditions. This underlines the unexpectedly high potential of CRNS to close the gap between point‐scale measurements, hydrological models, and remote sensing of the cryosphere in alpine terrain.

Measurements of root‐zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground‐based vehicle. Recently, concerns have been raised about a potentially biasing influence of local structures and roads. We employed neutron transport simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that roads introduce a substantial bias in the CRNS estimation of field soil moisture compared to off‐road scenarios. However, this effect becomes insignificant at distances beyond a few meters from the road. Neutron measurements on the road could overestimate the field value by up to 40 % depending on road material, width, and the surrounding field water content. The bias could be largely removed with an analytical correction function that accounts for these parameters. Additionally, an empirical approach is proposed that can be used without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between road‐effect corrected measurements and field soil moisture observations. However, if knowledge about the road characteristics is missing, measurements on the road could substantially reduce the accuracy of this method. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field‐scale soil moisture to support applications in hydrology, remote sensing, and agriculture.

No abstract

It has been speculated that during periods of water deficit, roots may shrink and lose contact with the soil, with a consequent reduction in root water uptake. Due to the opaque nature of soil, however, this process has never been observed in situ for living plants. Through x‐ray tomography and image analysis, we have demonstrated the formation and dynamics of air gaps around roots. The high spatial resolution required to image the soil–root gaps was achieved by combining tomography of the entire sample (field of view of 16 by 16 cm, pixel side 0.32 mm) with local tomography of the soil region around the roots (field of view of 5 by 5 cm, pixel side 0.09 mm). For a sandy soil, we found that when the soil dries to a water content of 0.025 m3 m−3, gaps occur around the taproot and the lateral roots of lupin (Lupinus albus L.). Gaps were larger for the taproot than the laterals and were caused primarily by root shrinkage rather than by soil shrinkage. When the soil was irrigated again, the roots swelled, partially refilling the gaps; however, large gaps persisted in the more proximal, older part of the taproot. Gaps are expected to reduce water transfers between soil and roots. Opening and closing of gaps may help plants to prevent water loss when the soil dries, and to restore the soil–root continuity when water becomes available. The persistence of gaps in the more proximal parts is one reason why roots preferentially take up water from their more distal parts.