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New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.
Precision irrigation management and crop water stress assessment rely on accurate estimation of root zone soil moisture. However, only the top 5cm soil moisture can be estimated using the two current passive microwave satellite missions, Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), which operate at L-band (wavelength of ~21cm). Since the contributing depth of the soil to brightness temperature increases with observation wavelength, it is expected that a P-band (wavelength of ~40cm) radiometer could potentially provide soil moisture information from deeper layers of the soil profile. Moreover, by combining both L- and P- bands, it is hypothesized that the soil moisture profile can be estimated even beyond their individual observation depths. The aim of this study was to demonstrate the potential of combined L-band and P-band radiometer observations to estimate the soil moisture profile under flat bare soil using a stratified coherent forward model. Brightness temperature observations at L-band and P-band from a tower based experimental site across a dry (April 2019) and a wet (March 2020) period, covering different soil moisture profile shapes, were used in this study. Results from an initial synthetic study showed that the performance of a combined L-band and P-band approach was better than the performance of using either band individually, with an average depth over which reliable soil moisture profile information could be estimated (i.e. with a target root mean square error (RMSE) of less than 0.04 m3/m3) being 20cm for linear and 15cm for second-order polynomial functions. Other functions were also tested but found to have a poorer performance. Applying the method to the tower-based brightness temperature achieved an average estimation depth of 28cm (20cm) and 5cm (5cm) during the dry and wet periods respectively when using a second-order polynomial (linear) function. These findings highlight the opportunity of a satellite mission with L-band and P-band observations to accurately estimate the soil moisture profile to as deep as 30cm globally.
The shape of the nonlinear relationship between evapotranspiration and soil moisture (the "ET-W relationship") helps control the evolution of soil moisture with time. Together, the shape of the relationship and the magnitude of the soil moisture anomaly at the beginning of a subseasonal forecast help determine whether a given anomaly will still be present at subseasonal leads, allowing it to contribute to skill in subseasonal temperature and precipitation prediction at those leads. In this study we examine subseasonal prediction in the context of soil moisture initialization using a suite of forecasts performed with the NASA GEOS seasonal forecast system. Large soil moisture anomalies are in fact found to be harbingers of increased skill in the subseasonal forecasts. Furthermore, accounting explicitly for the nonlinear shape of the ET-W relationship improves our ability to quantity the increase in forecast reliability associated with soil moisture initialization.
This report summarizes the research completed during the project entitled "The weathered bedrock vadose zone: A hidden control on water availability in the western United States" (Award: DE-SC0018039). The report covers work completed between 9/15/17 and 9/14/20. The objective of the exploratory project work was to evaluate the overarching hypothesis that the subsurface underlying actively eroding landscapes is systematically structured as a result of a balance between weathering and erosion and that this structure leads to dynamic moisture storage within weathered rock. To accomplish project objectives, we characterized hillslope weathering profile structure and conducted subsurface moisture monitoring across four study sites with comparable bedrock types but differing erosion rate and hydroclimate: The Angelo Coast Range Reserve (ACRR), Sagehorn-Russell Ranch (SRR), Antelope Valley Ranch (AVR), and the LBNL Watershed Function Scientific Focus Area (SFA). New characterization and monitoring infrastructure at the AVR and SFA sites was established through this project and enables long-term monitoring of hydrologic and carbon fluxes at the sites for comparison with long-term monitoring in other sites. Deep drilling, downhole logging, and characterization of chemistry and porosity of rock recovered from drilling reveals two weathering fronts across the sites. A shallower front is marked by the extent of pervasive fracturing and oxidation of pyrite and organic carbon. A deeper weathering front is marked by the appearance of open fractures and discoloration. At the AVR site, multiple ridge tops of different hillslope length were investigated to establish the relationship between the weathering front and topography. Drilling reveals that the fraction of the hillslope relief that is weathered scales with hillslope length, consistent with the theoretical framework that guided the project relating groundwater drainage with landscape evolution. With the establishment of new boreholes, we have documented significant water storage in weathered bedrock using low-field borehole nuclear magnetic resonance (NMR) across all four sites. In the upper 4 m of bedrock, the average water contents at ACRR, AVR, SRR, and SFA are approximately 25%, 16%, 25%, 23% respectively. At the ACRR site, where long-term monitoring via neutron probe surveys and time-domain transmission sensors are available, we have demonstrated that NMR reliably records moisture content and importantly, moisture content dynamics in weathered bedrock. Across all sites, our NMR monitoring has also revealed that a considerable fraction of the water storage occurs in fractures or pores that are significantly larger than the fine-grained bedrock matrix of the parent rock. To identify the proportion of water storage occurring in fractures and large pores, we analyzed the NMR signal by evaluating both the sum of echoes and an inversion of the NMR signal for a distribution of T2 relaxation times. Both methods reveal that at least 20% of the water storage occurs in fractures and larger pores across all sites. To constrain the interpretation of the in-situ field-scale NMR measurements, we compare the NMR response in the field to independent pore-structure information obtained via helium pycnometry. Results support the inference that dynamic seasonal water storage is dominantly restricted to the fracture network, which can reach 7% of the total volume. This dynamic range in water content is comparable to that of some soils, underscoring the need to understand how this region of the Earth System is structured, and functions as a hydrologic reservoir.
This Perspective builds upon insights from the National Institute of Standards and Technology (NIST)-organized workshop, “Materials and Metrology Needs for Advanced Semiconductor Packaging Strategies,” held at the 35th annual Electronics Packaging Symposium in Binghamton, NY, on September 5, 2024. It outlines critical challenges and opportunities related to polymer-based “soft” materials in advanced semiconductor packaging, with emphasis on polymer science, measurement science (metrology), and the strategic development of Research-Grade Test Materials (RGTMs). These efforts, led by the NIST CHIPS team, aim to advance the fundamental understanding of structure-property-processing relationships, promote standardized guidelines and innovative methods for material characterization, and accelerate the development, qualification, and adoption of next-generation packaging materials. The Perspective also distills key insights from the panel discussion with industry experts, emphasizing the need for close collaboration among materials scientists, process engineers, and metrology experts to enable a holistic strategy, further highlighting the importance of cross-sector partnerships among industry, academia, and government to address pressing challenges in packaging materials and processes.
A reliable moisture-indicating capactive sensor is provided with wire electrodes at least one of which includes a coating of moisture-absorbing dielectric material by spirally twisting the wire electrodes about each other, thereby establishing a pair of electrodes in contact with opposite surfaces of a layer of dielectric material, and assuring consistent contact of each electrode with the dielectric material despite changes in environmental conditions.
Soil moisture is an important driver for forest ecosystems, influencing fire occurrence and extent, insect and pathogen impacts, and tree growth, which creates a need for regular, globally extensive soil moisture information that only satellite-based sensors or models can achieve. However, the reliability of soil moisture measurements in forests is not well understood due to a lack of suitable validation sites (especially relative to unforested ecosystems) and interference caused by high vegetation water content on remotely sensed measurements; although recent studies have started to address this gap [1], [2], [3], [4]. Here we validate the performance of multiyear remotely sensed (SMAP/Sentinel), remotely sensed data assimilation modelled (SMAP-L4), and modelled (NLDAS) surface and root zone (0-1 m) soil moisture datasets with data from in-situ sensors at 39 National Ecological Observatory Network (NEON) sites throughout the contiguous US. Due to differences in spatial resolution, NEON soil moisture (~0.2 km measurement zone) correlations were expected to be stronger with the SMAP/Sentinel product (3 km resolution) than with coarser resolution SMAP-L4 (9 km resolution) or NLDAS products (13 km resolution). However, given the sensitivity of satellite measurements to vegetation water content we expected a deterioration in the correlations based on remotely sensed measurements (SMAP/Sentinel and SMAP-L4) as aboveground biomass increased, whereas the model-based data (NLDAS) was expected to be largely insensitive to vegetation type. We recognize that the SMAP/Sentinel product was developed for unforested regions, therefore our application is outside its primary use case. Soil moisture is measured at up to 8 depths in five soil plots spaced up to 40 m apart at each NEON terrestrial site. Correlation parameters were calculated for the three remotely sensed and modelled data products relative to in-situ measurement following Entekhabi et al. [5]. The datasets comprised 94 (SMAP-L4), 28 (SMAP/Sentinel), and 106 (NLDAS) sites-years for surface soils and 13 (SMAP-L4) and 14 (NLDAS) site-years for the root zone. At unforested sites, the performance of the three remotely sensed and modelled data products was similar for surface soils (Table 1). For example, unbiased RMSD (ubRMSD), which SMAP uses as its primary performance metric [6], ranged from 0.05 to 0.06 m3 m-3 (Table 1), indicating the ability of all three products to track changes in soil moisture over time. The performance of the three products deteriorated at forested sites, however, while the difference in performance was modest for SMAP-L4 and NLDAS, the deterioration in SMAP/Sentinel performance was substantial. For instance, SMAP/Sentinel ubRMSD increased from 0.06 to 0.11 m3 m-3 and absolute mean difference (Abs MD; which includes measurement bias and spatial representativeness errors) increased from 0.06 to 0.16 m3 m-3, indicating both a reduction in ability to track temporal changes and absolute amounts of soil moisture in forest ecosystems. SMAP-L4 and NLDAS had lower unbiased RMSD for root zone (0-1 m) than surface soils at both forested and unforested sites (Tables 1 and 2; SMAP/Sentinel does not produce a root zone measurement). However, in most cases the correlation coefficient (r) was lower for the root zone than surface soils, suggesting the lower unbiased RMSD may be attributed to greater temporal stability of soil moisture in the root zone rather than improved data product performance. Mean difference and absolute mean difference, which encompass measurement bias and spatial representativeness errors, were greater for root zone than surface soils at unforested sites for both data products, but the opposite was generally true at forested sites. As with surface soils, there was relatively little change in the performance of SMAP-L4 and NLDAS between the unforested and forested sites. In summary, all three data products were able to adequately represent soil moisture at unforested sites, at least when aggregating across sites. However, while the performance of all three products deteriorated at forested sites, SMAP-L4 and NLDAS maintained sufficient performance to remain suitable for some use cases (ubRMSD <0.06 m3 m-3 and RMSD <0.13 m3 m-3). In contrast, the relatively poorer performance of the SMAP/Sentinel product at forested sites seems insufficient for most use cases (ubRMSD >0.1 m3 m-3 and RMSD >0.2 m3 m-3). We attribute the large reduction in the performance of the SMAP/Sentinel product in forests to its use of C-band wavelengths, which are particularly sensitive to vegetation interference, and apparently outweighed any gains provided by its higher spatial resolution. A combined SMAP/NISAR soil moisture product may provide improved performance relative to SMAP/Sentinel due to NISAR’s use of L-band wavelengths, which are less sensitive to vegetation (NISAR is scheduled for launch in early 2024).
In the presence of contaminants, moisture probes can give false moisture readings and have shorter lifetimes. Absolute humidity probes are composed of porous, hygroscopic metallic oxide thin films (Al 2 O 3 ) coupled to electrodes (e.g. Au and Al). While these materials provide absolute humidity readings at low water levels at a relatively low cost, they are sensitive to the presence of contaminants, especially ammonia, due to its high hygroscopicity and ability to bind to the probe. Without frequent recalibration, especially in the presence of contaminants, the humidity levels are inaccurately reported due to measurement drift that occurs when the pores close, changing the impedance of the probe. The goal of this project was to improve the stability and reliability of these moisture probes by incorporating a molecular sieve into the probe to allow only the water to reach the sensor. Molecular sieves contain pores that allow molecule specific permeation. Two dimensional inorganic nanosheets (e.g. BN, MoO 2 , MoS 2 ) have recently been shown to behave as molecular sieves for water. Compared to zeolites, nanoporous materials have higher flux rates through the pores, leading to faster water permeation. Graphene oxide sheets have also been successfully employed for unimpeded water permeation; however, at lower humidity levels, the structure is unstable and the pores shrink, preventing the sieving of molecules. Compared to graphene oxide, sheets based off of inorganic materials, such as molybdenum, have been found to be more stable at lower humidity levels and have faster permeation rates. By creating a barrier in before the Al 2 O 3 sensor chip to prevent the permeation of contaminants into the probe, the lifetime of the probe will be extended. While the molybdenum sheets are a promising material for this application, their performance against ammonia and tritiated compounds have not yet been evaluated. This technology can be applied to other applications, including gas and liquid purification for environmental remediation, single molecule sensors, field effect transistors, and catalysts.
A cooperative experiment was conducted by teams from the U.S. and U.S.S.R. to evaluate passive microwave instruments and algorithms used to estimate surface soil moisture. Experiments were conducted as part of an interdisciplinary experiment in an arid rangeland watershed located in the southwest United States. Soviet microwave radiometers operating at wavelengths of 2.25, 21 and 27 cm were flown on a U.S. aircraft. Radio frequency interference limited usable data to the 2.25 and 21 cm systems. Data have been calibrated and compared to ground observations of soil moisture. These analyses showed that the 21 cm system could produce reliable and useful soil moisture information and that the 2.25 cm system was of no value for soil moisture estimation in this experiment.
Aircraft observations of the surface temperature were made by measurements of the thermal emission in the 8-14 micrometers band over agricultural fields around Phoenix, Arizona. The diurnal range of these surface temperature measurements were well correlated with the ground measurement of soil moisture in the 0-2 cm layer. The surface temperature observations for vegetated fields were found to be within 1 or 2 C of the ambient air temperature indicating no moisture stress. These results indicate that for clear atmospheric conditions remotely sensed surface temperatures are a reliable indicator of soil moisture conditions and crop status.
Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.
Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA - a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.
Root-Zone Soil Moisture (RZSM) (moisture profile in the top meter of soil) and Snow Water Equivalent (SWE) (total snow pack water content) are identified as priority target variables in the ESAS 2017 decadal survey [1] with critical roles in hydrology and water management. RZSM estimates are vital for understanding multiple Earth system processes and forecasting (for example, droughts [2]). Simultaneous knowledge of surface and RZSM could enable a breakthrough in estimating key unobserved hydrologic fluxes and reduce uncertainty in net ecosystem exchange (NEE), carbon balance [3] discharge estimates, and crop yield forecasts [4] .With the high albedo and insulating properties of snow, monitoring, SWE accumulation would provide a key constraint on the potential runoff during spring ablation while monitoring SWE disappearance rates would provide a key constraint on SWE partition into runoff vs. infiltration/recharge. [5] demonstrated that knowledge of early-spring SWE generally contributes most to streamflow forecast skill in the Western U.S. SWE is also a source of water storage that provides the water resources during spring snowmelt. Despite such potentially transformative contributions, accurate RZSM and SWE measurements are unattainable with current technology. While active/passive L-band methods (e.g. SMAP, SMOS) can reliably retrieve surface soil moisture in the top 5 cm of soil [6], [7]. RZSM estimates are only available through model assimilation of brightness temperatures with a radiative transfer and land surface models [8]. SWE estimation uses multi-frequency passive microwave techniques (e.g. [9]-[11]), which have significant problems with deeper snow and in forested and mountainous environments [12]. Signals of opportunity (SoOp) in P-band (200-400 MHz) is a new remote sensing technique with the capability of estimating both essential hydrologic variables, RZSM and SWE, circumventing many of the aforementioned limitations under all weather conditions day and night. SoOp is the re-utilization of existing powerful satellite transmissions within bands allocated for communications or navigation. P-band SoOp sensitivity to soil moisture has been demonstrated in an airborne experiment over Oklahoma in 2016 [13]. Recent theory [14] and experiments [15] have also confirmed that the reflection coefficient phase is proportional to SWE.
Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.
Researchers goals are to describe the information content of Vertical Atmospheric Sounder (VAS) radiance data, especially the 6.7 micrometers water vapor channel, to better interpret the atmosphere's water vapor structure from 6.7 micrometers imagery, and to investigate new analysis and forecasting techniques utilizing retrieved VAS soundings. Researchers made major progress toward these goals during FY-85. They are investigating 6.7 micrometer imagery on 6 to 7 March 1982, a day when special mesoscale ground truth data were collected during the 1982 atmospheric variability experiment/vertical amospheric sounder (AVE/VAS) field experiment. A dark (dry) image streak having mesoscale details was located over the special data region, and it provides the major focus of the case study. Mesoscale radiosonde-derived humidity data are found to verify fine scale features of the image that are not evident from the standard National Weather Service network. Thus, VAS imagery is a reliable detector of mesoscale moisture structure during this case. To investigate causes for the image streak, researchers are calculating water vapor budgets. Subsidence is found to be a factor in the current case as well; however, patterns of descent are not related to the jet streak according to traditional conceptual models. Thus, it appears that more research into jet stream dynamics is needed in order to better interpret 6.7 micrometer imagery.
One of the most striking features of the planet's long-time average cloudiness is the zonal band of concentrated convection lying near the equator. Large-scale variability of the Intertropical Convergence Zone (ITCZ) has been well documented in studies of the planetary spatial scales and seasonal/annual/interannual temporal cycles of convection. Smaller-scale variability is difficult to study over the tropical oceans for several reasons. Conventional surface and upper-air data are virtually non-existent in some regions; diurnal and annual signals overwhelm fluctuations on other time scales; and analyses of variables such as geopotential and moisture are generally less reliable in the tropics. These problems make the use of satellite data an attractive alternative and the preferred means to study variability of tropical weather systems.
The Soil Moisture Active Passive (SMAP) mission developed and deployed a system to autonomously handle most routine commanding of the observatory. This system of ground software is able to build commands, validate them, and radiate the commands to the spacecraft, all without human interaction. In the case of an off -nominal scenario, the system will abort gracefully and notify the mission operations team of the problem. The system was phased into operations during the first three months of the SMAP mission and handles over 90% of the weekly commanding of the vehicle. The gradual introduction of the automation in flight, along with an extensive test campaign, was instrumental in the success of the software. The automation has enabled substantial efficiencies in operations team staffing and has improved reliability by removing the potential for human error. The system also allows the SMAP project to be more responsive which has shown significant benefits in areas of data latency and science accuracy.
Terrestrial gamma radiation data and independent ground-based core soil moisture data are analyzed. They reveal the possibility of using natural terrestrial gamma radiation collected from a low-flying aircraft to make reliable real-time soil moisture measurements for the upper 20 cm of soil. The airborne data were compared to the crude ground-based soil moisture data set collected at the core sites.