Soil moisture partly controls land‐atmosphere mass and energy exchanges and ecohydrological processes in natural and agricultural systems. Thus, many models and remote sensing products continue to improve their spatiotemporal resolution of soil moisture, with some land surface models reaching 1 km resolution. However, the reliability and accuracy of both modeled and remotely sensed soil moisture require comparison with ground measurements at the appropriate spatiotemporal scales. One promising technique is the cosmic ray neutron probe. Here we further assess the suitability of this technique for real‐time monitoring across a large area by combining data from three fixed probes and roving surveys over a 12 km × 12 km area in eastern Nebraska. Regression analyses indicated linear relationships between the fixed probe averages and roving estimates of soil moisture for each grid cell, allowing us to derive an 8 h product at spatial resolutions of 1, 3, and 12 km, with root‐mean‐square error of 3%, 1.8%, and 0.9%.

The feedbacks of climate variability on CO2 consumption fluxes and carbon dynamics are thought to play an important role in moderating the global carbon cycle. High‐frequency sampling campaigns and analyses were conducted in this study to investigate temporal variations of river water chemistry and the impacts of climate variability on CO2 consumption fluxes and carbon dynamics for the Xijiang River, Southwest China. Physical processes modify biogeochemical processes, so major ions display different responses to changing discharge. The annual CO2 consumption rate is (6.8 ± 0.2) × 106 ton/year by carbonate weathering and (2.4 ± 0.3) × 106 ton/year by silicate weathering. The annual CO2 consumption flux is much higher than most world rivers, and strong CO2 consumption capacities are observed in catchments in Southwest China. Lower negative δ13CDIC values are found in the high‐flow season which corresponds with high temperatures compared to those in the low‐flow season. High discharge will accelerate material transport, and high temperatures will increase primary production in the catchment, both of which can be responsible for the shift of δ13CDIC values in the high‐flow season. Increased mineral weathering and biological carbon influx in the catchment are the main factors controlling carbon dynamics. Overall, these findings highlight the sensitivity of CO2 consumption fluxes and carbon dynamics in response to climate variability in the riverine systems.

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Abstract. The need for accurate, real-time, reliable, and multi-scale soil water content (SWC) monitoring is critical for a multitude of scientific disciplines trying to understand and predict the Earth's terrestrial energy, water, and nutrient cycles. One promising technique to help meet this demand is fixed and roving cosmic-ray neutron probes (CRNPs). However, the relationship between observed low-energy neutrons and SWC is affected by local soil and vegetation calibration parameters. This effect may be accounted for by a calibration equation based on local soil type and the amount of vegetation. However, determining the calibration parameters for this equation is labor- and time-intensive, thus limiting the full potential of the roving CRNP in large surveys and long transects, or its use in novel environments. In this work, our objective is to develop and test the accuracy of globally available datasets (clay weight percent, soil bulk density, and soil organic carbon) to support the operability of the roving CRNP. Here, we develop a 1 km product of soil lattice water over the continental United States (CONUS) using a database of in situ calibration samples and globally available soil taxonomy and soil texture data. We then test the accuracy of the global dataset in the CONUS using comparisons from 61 in situ samples of clay percent (RMSE  =  5.45 wt %, R2  =  0.68), soil bulk density (RMSE  =  0.173 g cm−3, R2  =  0.203), and soil organic carbon (RMSE  =  1.47 wt %, R2  =  0.175). Next, we conduct an uncertainty analysis of the global soil calibration parameters using a Monte Carlo error propagation analysis (maximum RMSE  ∼  0.035 cm3 cm−3 at a SWC  =  0.40 cm3 cm−3). In terms of vegetation, fast-growing crops (i.e., maize and soybeans), grasslands, and forests contribute to the CRNP signal primarily through the water within their biomass and this signal must be accounted for accurate estimation of SWC. We estimated the biomass water signal by using a vegetation index derived from MODIS imagery as a proxy for standing wet biomass (RMSE  <  1 kg m−2). Lastly, we make recommendations on the design and validation of future roving CRNP experiments.

Metal (carbide)–carbon eutectic fixed points when applied to radiometry should operate at a temperature preferably exceeding 3000 K, have a large aperture, be robust and have long plateau duration. The large-tube-diameter BB3500YY furnace, recently introduced at the National Metrology Institute of Japan (NMIJ), has been tuned for such fixed-point realization. A novel cell structure with an internal insulation of highly purified carbon-composite sheet material was designed and tested. This resulted in improved robustness, immunity to furnace temperature nonuniformity and extended plateau duration. The design was applied to a hyper-eutectic porous ingot cell, and a reproducible plateau was observed. Preliminary results for a large aperture cell with an aperture diameter of 8 mm are also reported.