Cosmic-ray neutron probes on the high plains of Nebraska: applications to large scale agriculture

Cosmic-rays have some surprising applications in precision agriculture. The cosmic-ray neutron probe (CRNP), when implemented as a roving instrument, can be used to create spatial maps of soil moisture, and from these maps soil hydraulic properties can be inferred. In this work, we combine data from a mobile CRNP with laboratory samples to make spatial predictions of soil hydraulic properties for select field sites around the state of Nebraska. These maps, which focus on wilting point and field capacity, can, in turn, be used to determine the optimal timing and application rates for irrigation farmers, many of whom have the capability to finely tune the spatial distribution of water applied on a field, but currently lack the requisite data to support such management practices. We find that 4 CRNP soil moisture maps are adequate to describe the dominant underlying spatial structure of the field (\u3e75% of variability) using Empirical Orthogonal Functions. The CRNP soil moisture maps combined with an elevation layer provided strong statistical predictors of laboratory measured soil hydraulic properties. The economic viability of the method depends on numerous local cost factors but rising demand for water resources may dictate the need for innovative approaches such as this one to reduce future water use

Calibration and Validation of the Cosmic Ray Neutron Rover for SoilWater Mapping within Two South African Land Classes

Knowledge of soil water at a range of spatial scales would further our understanding of the dynamic variable and its influence on numerous hydrological applications. Cosmic ray neutron technology currently consists of the Cosmic Ray Neutron Sensor (CRNS) and the Cosmic Ray Neutron Rover (CRNR). The CRNR is an innovative tool to map surface soil water across the land surface. This research assessed the calibration and validation of the CRNR at two survey sites (hygrophilous grassland and pine forest) within the Vasi area with an area of 72 and 56 ha, respectively. The assessment of the calibrations showed that consistent calibration values (N0) were obtained for both survey sites. The hygrophilous grassland site had an average N0 value of 133.441 counts per minute (cpm) and an average error of 2.034 cpm. The pine site had an average N0 value of 132.668 cpm and an average error of 0.375 cpm between surveys. The validation of CRNR soil water estimates with interpolated hydro-sense soil water estimates showed that the CRNR can provide spatial estimates of soil water across the landscape. The hydro-sense and CRNR soil water estimates had a R2 of 0.439 at the hygrophilous grassland site and 0.793 at the pine site

Cosmic ray neutrons provide an innovative technique for estimating intermediate scale soil moisture

Soil moisture is an important hydrological parameter, which is essential for a variety of applications, thereby extending to numerous disciplines. Currently, there are three methods of estimating soil moisture: ground-based (in-situ) measurements; remote sensing based methods and land surface models. In recent years, the cosmic ray probe (CRP), which is an in-situ technique, has been implemented in several countries across the globe. The CRP provides area-averaged soil moisture at an intermediate scale and thus bridges the gap between in-situ point measurements and global satellite-based soil moisture estimates. The aim of this study was to test the suitability of the CRP to provide spatial estimates of soil moisture. The CRP was set up and calibrated in Cathedral Peak Catchment VI. An in-situ soil moisture network consisting of time-domain reflectometry and Echo probes was created in Catchment VI, and was used to validate the CRP soil moisture estimates. Once calibrated, the CRP was found to provide spatial estimates of soil moisture, which correlated well with the in-situ soil moisture network data set and yielded an R2 value of 0.845. The use of the CRP for soil moisture monitoring provided reliable, accurate and continuous soil moisture estimates over the catchment area. The wealth of current and potential applications makes the CRP very appealing for scientists and engineers in various fields

Resistivity Arrays as an Early Warning System for Monitoring Runoff Holding Ponds

Monitoring wells are installed to intercept contaminants inadvertently discharged from inground structures designed to retain salt-affected wastewaters; however, several difficulties with collection and data interpretation limit their effectiveness. Therefore, improved monitoring methods are needed. The objective of this study was to evaluate the effectiveness of resistivity array technology as an early warning system to monitor for unintended basin discharge. Subsurface resistivity arrays were installed at two Nebraska sites: a beef cattle feedyard located at the U.S. Meat Animal Research Center, Clay Center, Nebraska (FyA) and a commercial cattle feeding operation (FyB). Monitoring well data did not identify any unintended discharge events during the study period. However, the resistivity array (RA) system detected a discharge event that was localized in the non-saturated zone adjacent to the pond at FyB within one day following a precipitation event. Monitoring the unsaturated portion allows the RA system a capacity beyond traditional monitoring wells, which can only intercept discharge carried in groundwater. Also, the RA system effectively measured a larger area (i.e., a virtual curtain) compared to the point measure typical of monitoring wells. Therefore, RA technology provides broader coverage and is more tolerant to placement issues for intercepting discharge. Finally, the capacity to automate the RA system provides a means to continuously monitor unintended subsurface discharge from runoff holding ponds. This continuous monitoring system is more likely to detect discharge events than the bi-annual sampling typically required for monitoring wells. Automatic and continuous monitoring provides feedyard operators options to better manage environmental impacts associated with runoff holding ponds

Revisiting the definition of field capacity as a functional parameter in a layered agronomic soil profile beneath irrigated maize

The soil water content at the condition of field capacity (θFC) is a key parameter in irrigation scheduling and has been suggested to be determined by running a synthetic drainage experiment until the flux rate (q) at the bottom of the soil profile achieves a predefined negligible value (qFC). We question the impact of qFC on the assessment of field capacity. Moreover, calculating θFC as the integral mean of the water content profile when q is equal to qFC is strictly valid only for uniform soil profiles. By contrast, this practice is ambiguous and biased for stratified soil profiles due to the soil water content discontinuity at the layer interfaces. In this study, the concept of field capacity was revisited and adapted to practical agronomic heuristics. By resorting to the assessment of root-zone water storage capacity (W), we envision field capacity as a functional hydraulic parameter derived from synthetic irrigation scheduling scenarios to minimize drought stress, drainage, and nitrate leachate below the root zone. A functional analysis was carried out on a 135-cm-thick layered soil profile beneath maize in eastern Nebraska. Onfarm irrigation scheduling applications and agricultural practices were recorded for 20 years (2001–2020) at a daily time step. Hydrus-1D was calibrated and validated with direct measurements of the soil water retention curve and soil water content data, respectively, in each soil layer. A set of functional field capacity values was derived from 24 irrigation scheduling scenarios, and the optimal water storage capacity at field capacity (WFC) was approximately 50 cm (corresponding to about 80% saturation in the soil profile). An average irrigation amount of 217.5 mm distributed over 21 events was obtained by using optimal irrigation scheduling, which was initiated when the matric pressure head took on a value of - 700 cm and the irrigation rate was set at 1.0 cm d-1. This irrigation practice ensured water storage at approximately the same level (ideally at WFC) by sustaining only evapotranspiration fluxes in the uppermost portion of the root zone and by limiting excessive drainage. This protocol can be transferred to other agricultural fields

A profile shape correction to reduce the vertical sensitivity of cosmic-ray neutron sensing of soil moisture

n recent years, cosmic-ray neutron sensing (CRNS) has shown a large potential among proximal sensing techniques to monitor soil moisture noninvasively, with high frequency and a large support volume (radius up to 240 m and sensing depth up to 80 cm). This signal is, however, more sensitive to closer distances and shallower depths. Inherently, CRNS-derived soil moisture is a spatially weighted value, different from an average soil moisture as retrieved by a sensor network. In this study, we systematically test a new profile shape correction on CRNS-derived soil moisture, based on additional soil moisture profile measurements and vertical unweighting, which is especially relevant during pronounced wetting or drying fronts. The analyses are conducted with data collected at four contrasting field sites, each equipped with a CRNS probe and a distributed soil moisture sensor network. After applying the profile shape correction on CRNS-derived soil moisture, it is compared with the sensor network average. Results show that the influence of the vertical sensitivity of CRNS on integral soil moisture values is successfully reduced. One to three properly located profile measurements within the CRNS support volume improve the performance. For the four investigated field sites, the RMSE decreased 11–53% when only one profile location was considered. We therefore recommend to install along with a CRNS at least one soil moisture profile in a radial distanceProfile-shape-corrected, CRNS-derived soil moisture is an unweighted integral soil moisture over the support volume, which is easier to interpret and easier to use for further applications

Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land–atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASA’s Land Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high-resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily timescales. In addition, this study uses point and gridded soil moisture observations from fixed and roving cosmic-ray neutron probes and co-located human-practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation for accurate simulation of water and energy states and fluxes over cropland