Trenton E. Franz

Measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources

[1] We present here a simple and robust framework for quantifying the effective sensor depth of cosmic ray soil moisture neutron probes such that reliable water fluxes may be computed from a time series of cosmic ray soil moisture. In particular, we describe how the neutron signal depends on three near-surface hydrogen sources: surface water, soil moisture, and lattice water (water in minerals present in soil solids) and also their vertical variations. Through a combined modeling study of one-dimensional water flow in soil and neutron transport in the atmosphere and subsurface, we compare average water content between the simulated soil moisture profiles and the universal calibration equation which is used to estimate water content from neutron counts. By using a linear sensitivity weighting function, we find that during evaporation and drainage periods the RMSE of the two average water contents is 0.0070 m 3 m � 3 with a maximum deviation of 0.010 m 3 m � 3 for a range of soil types. During infiltration, the RMSE is 0.011 m 3 m � 3 with a maximum deviation of 0.020 m 3 m � 3 , where piston like flow conditions exists for the homogeneous isotropic media. Because piston flow is unlikely during natural conditions at the horizontal scale of hundreds of meters that is measured by the cosmic ray probe, this modeled deviation of 0.020 m 3 m � 3 represents the worst case scenario for cosmic ray sensing of soil moisture. Comparison of cosmic ray soil moisture data and a distributed sensor soil moisture network in Southern Arizona indicates an RMSE of 0.011 m 3 m � 3 over a

The Effect of Atmospheric Water Vapor on Neutron Count in the Cosmic-Ray Soil Moisture Observing System

The cosmic-ray method for measuring soil moisture, used in the Cosmic-Ray Soil Moisture Observing System (COSMOS), relies on the exceptional ability of hydrogen to moderate fast neutrons. Sources of hydrogen near the ground, other than soil moisture, affect the neutron measurement and therefore must be quantified. This study investigates the effect of atmospheric water vapor on the cosmic-ray probe signal and evaluates the fast neutron response in realistic atmospheric conditions using the neutron transport code Monte Carlo N-Particle eXtended (MCNPX). The vertical height of influence of the sensor in the atmosphere varies between 412 and 265m in dry and wet atmospheres, respectively. Model results show that atmospheric water vapor near the surface affects the neutron intensity signal by up to 12%, corresponding to soil moisture differences on the order of 0.10m 3 m 23 . A simple correction is defined to identify the true signal associated with integrated soil moisture that rescales the measured neutron intensity to that which would have been observed in the atmospheric conditions prevailing on the day of sensor calibration. Use of this approach is investigated with in situ observations at two sites characterized by strong seasonality in water vapor where standard meteorological measurements are readily available.

A multi-species synthesis of physiological mechanisms in drought-induced tree mortality

Widespread tree mortality associated with drought has been observed on all forested continents and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere–atmosphere interactions of carbon, water and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analysed across species and biomes using a standardized physiological framework. Here, we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought-induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function.The mechanisms underlying drought-induced tree mortality are not fully resolved. Here, the authors show that, across multiple tree species, loss of xylem conductivity above 60% is associated with mortality, while carbon starvation is not universal.

The future of Earth observation in hydrology

In just the past five years, the field of Earth observation has progressed beyond the offerings of conventional space agency based platforms to include a plethora of sensing opportunities afforded by CubeSats, Unmanned Aerial Vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically on the order of one billion dollars per satellite and with concept-to-launch timelines on the order of two decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturise sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist five years ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of the cost of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-meter resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen-scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the Internet of Things as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which todays hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilise and exploit these new observing systems to enhance our understanding of the Earth and its linked processes.

Combined analysis of soil moisture measurements from roving and fixed cosmic ray neutron probes for multiscale real‐time monitoring

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%.

Field testing of the universal calibration function for determination of soil moisture with cosmic‐ray neutrons

The semitheoretical universal calibration function (UCF) for estimating soil moisture using cosmic-ray neutron sensors was tested by comparing to field measurements made with the same neutron detector across a range of climates, soil, latitude, altitude, and biomass. There was a strong correlation between neutron intensity and the total amount of hydrogen at each site; however, the relationship differed from that predicted by the UCF. A linear fit to field measurements explained 99% of the observed variation and provides a robust empirical means to estimate soil moisture at other sites. It was concluded that measurement errors, neutron count corrections, and scaling to remove altitudinal and geomagnetic differences were unlikely to explain differences between observations and the UCF. The differences may be attributable to the representation of organic carbon, biomass or detector geometry in the neutron particle code, or to differences in the neutron energy levels being measured by the cosmic-ray sensor and modeled using the particle code. The UCF was derived using simulations of epithermal neutrons; however, lower energy thermal neutrons may also be important. Using neutron transport code, we show the differences in response of thermal and epithermal neutrons to the relative size of the hydrogen pool. Including a thermal neutron component in addition to epithermal neutrons in a modified UCF provided a better match to field measurements; however, thermal neutron measurements are needed to confirm these results. A simpler generalized relationship for estimating soil moisture from neutron counts was also tested with encouraging results for low biomass sites.

The potential of the COSMOS network to be a source of new soil moisture information for SMOS and SMAP

The COSMOS network will eventually consist of several hundred sensors throughout the United States that report kilometer-scale soil water content via measurement of the intensity of neutrons immediately above Earths surface. We show that COSMOS sensors must be corrected for the effects of growing vegetation. Once this phenomenon is completely understood the COSMOS network could be a useful source of information for the validation of both soil moisture and vegetation products obtained from current and future microwave remote sensing satellites.

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

With an ever-increasing demand for natural resources and the societal need to understand and predict natural disasters, soil water content (SWC) observations remain a critical variable to monitor in order to optimally allocate resources, establish early warning systems, and improve weather forecasts. However, routine agricultural production practices of soil cultivation, planting, and harvest make the operation and maintenance of direct contact point sensors for long-term monitoring challenging. In this work, we explore the use of the newly established Cosmic-Ray Neutron Probe (CRNP) and method to monitor landscape average SWC in a mixed agricultural land use system in northeast Austria. The calibrated CRNP landscape SWC values compare well against an independent in situ SWC probe network (MAE = 0.0286 m3/m3) given the challenge of continuous in situ monitoring from probes across a heterogeneous agricultural landscape. The ability of the CRNP to provide real-time and accurate landscape SWC measurements makes it an ideal method for establishing long-term monitoring sites in agricultural ecosystems to aid in agricultural water and nutrient management decisions at the small tract of land scale as well as aiding in management decisions at larger scales.

Summer Soil Moisture Spatiotemporal Variability in Southeastern Arizona

AbstractSoil moisture is important for many applications, but its measurements are lacking globally and even regionally. The Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona has measured near-surface 5-cm soil moisture with 19 in situ probes since 2002 within its 150 km2 area. Using various criteria to identify erroneous data, it is found that in any given period from 1 July to 30 September from 2002 to 2011, 13–17 of these probes were producing reasonable data, and this is sufficient to estimate area-averaged seasonal soil moisture. A soil water balance model is then developed using rainfall as its only input to spatially extrapolate soil moisture estimates to the 88 rain gauges located within the watershed and to extend the measurement period to 56 years. The model is calibrated from 2002 to 2011 so that the daily in situ and modeled soil moisture time series have a high average correlation of 0.89 and a root-mean-square deviation of 0.032 m3 m−3. By interpolating modeled soil moisture...

DEVELOPMENT OF NON-COLLINEAR ARRAYS FOR USE NEAR WASTEWATER HOLDING PONDS

Mineral and organic salts from beef manure contained in precipitation runoff from feedlot pen surfaces can alter the conductivity properties of soil and water receiving it. Typically, holding ponds are constructed to control runoff from concentrated animal feeding operations. The integrity of these holding ponds has come under increased scrutiny since subsurface leakage has the potential to affect soil and groundwater quality. Traditionally, ponds are monitored by installing monitoring wells at strategic locations to evaluate the impact of these ponds on the environment. Monitoring wells are expensive to install, costly to sample and the information received is subject to ambiguous interpretation. Researchers from USDA-ARS U.S. Meat Animal Research Center have combined efforts and resources with the Nebraska Cattlemen, the Nebraska Department of Environmental Quality (NDEQ), and AgraTek LLC, to evaluate electronic monitoring of subsurface soils near holding ponds used to contain runoff from beef cattle feedlots. A three year study summarized data from two feedlots and concluded that resistivity array systems were able to adequately measure subsurface dynamics and to alert operators of changes that exceeded nominal operation. Subsequently, two NDEQ provisionally approved systems were installed at a University of Nebraska research site. Unlike previous test installations, each of these new sites required non-collinear installations. This report discusses the theoretical development and testing of non-collinear arrays which proved to be a viable approach to unique array geometries necessitated by feedlot designs.