Soil Water Content Information Research Articles

Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field.

Gamma-ray spectroscopy (GRS) enables continuous estimation of soil water content (SWC) at the subfield scale with a noninvasive sensor. Hydrological applications, including hyper-resolution land surface models and precision agricultural decision making, could benefit greatly from such SWC information, but a gap exists between established theory and accurate estimation of SWC from GRS in the field. In response, we conducted a robust three-year field validation study at a well-instrumented agricultural site in Nebraska, United States. The study involved 27 gravimetric water content sampling campaigns in maize and soybean and 40K specific activity (Bq kg-1) measurements from a stationary GRS sensor. Our analysis showed that the current method for biomass water content correction is appropriate for our maize and soybean field but that the ratio of soil mass attenuation to water mass attenuation used in the theoretical equation must be adjusted to satisfactorily describe the field data. We propose a calibration equation with two free parameters: the theoretical 40K intensity in dry soil and a, which creates an "effective" mass attenuation ratio. Based on statistical analyses of our data set, we recommend calibrating the GRS sensor for SWC estimation using 10 profiles within the footprint and 5 calibration sampling campaigns to achieve a cross-validation root mean square error below 0.035 g g-1.

Retraction Note: Evaluation of English translation accuracy of green plant surface irrigation and food words based on image processing

China’s agricultural planting area is large, irrigation water consumption is large, and water resources are relatively small. Agricultural irrigation water management can have a huge positive impact on water saving and improvement of water use efficiency. The content of water in the soil is a key focus of irrigation water management. Before irrigating crops, it can not only monitor the current climate conditions but also assess the water demand of crops. After the crops are irrigated with water, the change index of the water content in the soil can help people evaluate the effect of irrigation. Therefore, timely and accurate acquisition of temporal and spatial soil water content information plays an important role in the scientific management of agricultural irrigation water. According to one of the three major irrigation areas in China, as an irrigation area in the experimental area, the 2020 thermal infrared method is used to measure the soil moisture content, and at the same time, the crop water demand estimation model is built, and the remote irrigation area sensor monitoring model and remote sensing irrigation are established. The model estimates crop water demand, area of irrigated area, and irrigation water volume. In addition, in recent years, English has gradually improved its status as the most important language tool in the international communication environment. In this case, more and more attention will be paid to the correctness of English translation. The correctness of English translation is affected by various cultural factors. Therefore, in order to further improve the accuracy of English translation, this article comprehensively analyzes the accuracy of English translation from the cultural background, cognition and thinking habits, and the influence of different cultural factors and proposes corresponding improvement plans for it.

Measuring vertical soil water content profiles by combining horizontal borehole and dispersive surface ground penetrating radar data

ABSTRACTTo investigate transient dynamics of soil water redistribution during infiltration, we conducted horizontal borehole and surface ground penetrating radar measurements during a 4‐day infiltration experiment at the rhizontron facility in Selhausen, Germany. Zero‐offset ground penetrating radar profiling in horizontal boreholes was used to obtain soil water content information at specific depths (0.2, 0.4, 0.6, 0.8 and 1.2 m). However, horizontal borehole ground penetrating radar measurements do not provide accurate soil water content estimates of the top soil (0–0.1 m depth) because of interference between direct and critically refracted waves. Therefore, surface ground penetrating radar data were additionally acquired to estimate soil water content of the top soil. Due to the generation of electromagnetic waveguides in the top soil caused by infiltration, a strong dispersion in the ground penetrating radar data was observed in 500 MHz surface ground penetrating radar data. A dispersion inversion was thus performed with these surface ground penetrating radar data to obtain soil water content information for the top 0.1 m of the soil. By combining the complementary borehole and surface ground penetrating radar data, vertical soil water content profiles were obtained, which were used to investigate vertical soil water redistribution. Reasonable consistency was found between the ground penetrating radar results and independent soil water content data derived from time domain reflectometry measurements. Because of the improved spatial representativeness of the ground penetrating radar measurements, the soil water content profiles obtained by ground penetrating radar better matched the known water storage changes during the infiltration experiment. It was concluded that the combined use of borehole and surface ground penetrating radar data convincingly revealed spatiotemporal soil water content variation during infiltration. In addition, this setup allowed a better quantification of water storage, which is a prerequisite for future applications, where, for example, the soil hydraulic properties will be estimated from ground penetrating radar data.

The integrated water balance and soil data set of the Rollesbroich hydrological observatory

Abstract. The Rollesbroich headwater catchment located in western Germany is a densely instrumented hydrological observatory and part of the TERENO (Terrestrial Environmental Observatories) initiative. The measurements acquired in this observatory present a comprehensive data set that contains key hydrological fluxes in addition to important hydrological states and properties. Meteorological data (i.e., precipitation, air temperature, air humidity, radiation components, and wind speed) are continuously recorded and actual evapotranspiration is measured using the eddy covariance technique. Runoff is measured at the catchment outlet with a gauging station. In addition, spatiotemporal variations in soil water content and temperature are measured at high resolution with a wireless sensor network (SoilNet). Soil physical properties were determined using standard laboratory procedures from samples taken at a large number of locations in the catchment. This comprehensive data set can be used to validate remote sensing retrievals and hydrological models, to improve the understanding of spatial temporal dynamics of soil water content, to optimize data assimilation and inverse techniques for hydrological models, and to develop upscaling and downscaling procedures of soil water content information. The complete data set is freely available online (http://www.tereno.net, doi:10.5880/TERENO.2016.001, doi:10.5880/TERENO.2016.004, doi:10.5880/TERENO.2016.003) and additionally referenced by three persistent identifiers securing the long-term data and metadata availability.

On the use of surface and ground temperature data to recover soil water content information

Ground temperature measurements are largely used in agronomy, hydrology, or climatology. As temperature variations in the subsurface depends on its thermal diffusivity which itself is a function of water content, temperature measurements are also relevant in hydrogeophysics. In this paper, we model surface and underground (60 cm depth) temperature data to analyze the time variations of soil water content over one year. We have considered two modelling approaches. We first invert the data using a homogeneous half-space model to recover the apparent effective soil water saturation. For that, we examine several thermal diffusivity-water content relations and conclude that among them only Johansen's relation is physically acceptable. As expected, the apparent effective saturation is maximal at the beginning of the spring, and then it decreases until the end of the summer. In the second approach, we use a two-layer model with fixed thermal parameters in both layers (top: unsaturated zone; bottom: saturated zone), and invert the data to monitor the time variations of the interface depth. The obtained depths are coherent with the results of the first approach and show that the soil is unsaturated over more than ten centimetres by the end of the summer. Even though more complex multi-layer models including capillary effects would probably be constrained by using temperature data measured at more than two depths, our results on this data set show the usefulness of introducing apparent parameters that provide different simple means to characterize the complex heterogeneous subsurface.