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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Spatio–Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology

Integrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow–CLM model across the contiguous US. We compare convolutional neural networks like ResNet and UNet run autoregressively against our novel architecture called the Forced SpatioTemporal RNN (FSTR). The FSTR model incorporates separate encoding of initial conditions, static parameters, and meteorological forcings, which are fused in a recurrent loop to produce spatiotemporal predictions of groundwater. We evaluate the model architectures on their ability to reproduce 4D pressure heads, water table depths, and surface soil moisture over the contiguous US at 1 km resolution and daily time steps over the course of a full water year. The FSTR model shows superior performance to the baseline models, producing stable simulations that capture both seasonal and event–scale dynamics across a wide array of hydroclimatic regimes. The emulators provide over 1,000× speedup compared to the original physical model, which will enable new capabilities like uncertainty quantification and data assimilation for integrated hydrologic modeling that were not previously possible. Our results demonstrate the promise of using specialized deep learning architectures like FSTR for emulating complex process–based models without sacrificing fidelity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Root traits reveal safety and efficiency differences in grasses and shrubs exposed to different fire regimes

Plant roots are important components of terrestrial ecosystems, but little is known about how root traits differ between plant species or vary across space in natural ecosystems. In this study, we investigated how root traits vary across grasses and woody shrubs in a tallgrass prairie located in Manhattan, KS, USA. Specifically, were interested in understanding how anatomical traits vary across these different plant groups, across different depths in the soil, and also across multiple areas of tallgrass prairie that are burned at different frequencies. We compared traits that allow roots to use soil water efficiently and those that help roots persist through extended periods of drought. We found that woody roots exhibited traits that allow them to use water efficiently in shallow soils but persist through drought in deeper soil. Here, these traits may allow shrubs to transport water from shallow soils to deeper soil after large rain events and resist extended periods without rain when soils become dry, which may allow woody plants to successfully compete for water in less frequently burned, more diverse plant communities. Grasses had traits that allow them to use water efficiently but also tolerate drought in shallow soils, regardless of fire treatment. This unique trait combination likely gives grasses a competitive advantage over other tallgrass prairie plants across different fire regimes. Together, these results show that anatomical root traits can be used to enhance mechanistic understanding of plant functioning in dynamic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A general mechanistic framework for cross-scale understanding of hot spots and hot moments in carbon and water fluxes

Semi-arid ecosystems, like those in the American Southwest, exert a massive impact on the interannual variability of carbon and water cycling. Unfortunately, these carbon and water fluxes are notoriously difficult to predict due to their high spatial and temporal variability, which is poorly captured by the current generation of vegetation models. Indeed, this region is exemplified by the ‘hot spots and hot moments’ concept, which states that small areas in space (‘hot spots’) and transient moments in time (‘hot moments’) exert an outsized influence on biogeochemical cycling. However, the factors that regulate these pulses in biogeochemical activity are unknown, as is their variability across space and time. These uncertainties severely limit efforts to better represent hot spots and hot moments in models. Here, we seek to develop a generalized method for detecting and quantifying the importance of hot spots and hot moments from individual plant to regional scales. Underpinning this method is our recently developed statistical approach for identifying hot spots and hot moments. By applying this method to semi-continuous measurements of plant water status, a depth profile of soil water potential, and ecosystem fluxes via eddy covariance, we will track the fate of water through the soil-plant-atmosphere continuum and identify the mechanistic drivers of these transient pulses in biogeochemical activity. Then, we will expand this approach across a broad network of Ameriflux towers, and apply a machine learning approach that will allow us to upscale measurements of hot spots and hot moments across the American Southwest and quantify their impact on carbon and water cycles. These products will allow us to identify hot spots and hot moments across spatio-temporal scales and will serve as crucial data sources for validating a new generation of models that can better capture highly dynamic carbon and water fluxes. The proposed method will be easily transferable across biomes and will serve as a framework for future research on hot spots and hot moments across the plant ecophysiology, biometeorology, and vegetation modeling communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Functional-type modeling approach and data-driven parameterization of methane emissions in wetlands (Final Technical Science Report)

Our goals are to improve understanding and quantitative representation of the multiple processes that affect methane emissions at a high (patch level, vertically detailed) spatial resolution, and translate this understanding to improved modeling capability of coastal wetland fluxes using the E3SM Land Model (ELM v1) wetland CH4 biogeochemistry module. We propose an experimental approach to identify and parameterize uncertainties in ELM. Understanding of methane emissions can be improved along three conceptual axes: (i) horizontal (ecohydrological patch resolution), (ii) vertical (through the depth of the soil column), and (iii) process level (e.g., resolving microbial pathways, vegetation specific transport pathways). Along each of the three axes, we will characterize, quantify, and model, the key ecological, hydrological, and meteorological controls of methane (CH4) flux heterogeneity in four model coastal wetlands.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

A comparison of radiative transfer models for predicting the microwave emission from soils

Noncoherent and coherent numerical models for predicting emission from soils are compared. Coherent models use the boundary conditions on the electric fields across the layer boundaries to calculate the radiation intensity, and noncoherent models consider radiation intensities directly. Interference may cause different results in the two approaches when coupling between soil layers in coherent models causes greater soil moisture sampling depths. Calculations performed at frequencies of 1.4 and 19.4 GHz show little difference between the models at 19.4 GHz, although differences are apparent at the lower frequency. A definition for an effective emissivity is also given for when a nonuniform temperature profile is present, and measurements made from a tower show good agreement with calculations from the coherent model.

Schmugge, T. J.↗
NASA NTRS1982

Sources of atmospheric methane from coastal marine wetlands

Biological methanogenesis in wetlands is believed to be one of the major sources of global tropospheric methane. The present paper reports measurements of methane distribution in the soils, sediments, water and vegetation of coastal marine wetlands. Measurements, carried out in the salt marshes Bay Tree Creek in Virginia and Panacea in northwest Florida, reveal methane concentrations in soils and sediments to vary with depth below the surface and with soil temperature. The fluxes of methane from marsh soils to the atmosphere at the soil-air interface are estimated to range from -0.00067 g CH4/sq m per day (methane sink) to 0.024 g CH4/sq m per day, with an average value of 0.0066 g CH4/sq m per day. Data also demonstrate the important role of tidal waters percolating through marsh soils in removing methane from the soils and releasing it to the atmosphere. The information obtained, together with previous studies, provides a framework for the design of a program based on in situ and remote sensing measurements to study the global methane cycle.

Harriss, R. C.↗
NASA NTRS1982

Applications of remote sensing to geobotanical prospecting for non-renewable resources

Airborne sensors used in the remote detection of geobotanical anomalies are able to locate mineral deposits. Geobotanical stress is manifested in increased visible spectrum reflectance due to a decrease in chlorophyll content which induces chlorosis. The effectiveness of this method is, however, restricted to soils in which plant root structures are embedded in bedrock-derived soils to a depth sufficient for the production of heavy metal stress. It is noted that Landsat remote sensors are inherently better suited to the detection of overall plant density or biomass changes relating to zones of mineralization.

Birnie, R. W.↗
NASA NTRS1988

Radiation protective structure alternatives for habitats of a lunar base research outpost

The solar and galactic cosmic radiation levels on the Moon pose a hazard to extended manned lunar missions. Lunar soil represents an available, economical material to be used for radiation shielding. Several alternatives have been suggested to use lunar soil to protect the inhabitants of a lunar base research outpost from radiation. The Universities Space Research Association has requested that a comparative analysis of the alternatives be performed, with the purpose of developing the most advantageous design. Eight alternatives have been analyzed, including an original design which was developed to satisfy the identified design criteria. The original design consists of a cylindrical module and airlock, partially buried in the lunar soil, at a depth sufficient to achieve adequate radiation shielding. The report includes descriptions of the alternatives considered, the method of analysis used, and the final design selected.

Bell, Fred J.↗
NASA NTRS1991

Airborne Ground Penetrating Radar (GPR) for peat analyses in the Canadian Northern wetlands study

The study was conducted as part of the NASA Biospherics Research on Emissions from Wetlands (BREW) program. An important aspect of the program is to investigate the terrestrial production and atmospheric distribution of methane and other gases contributing to global warming. Multi-kilometer transects of airborne (helicopter) Ground Penetrating Radar (GPR) data were collected periodically along the 100 km distance from the coast inland so as to obtain a regional trend in peat depth and related parameters. Global Positioning System (GPS) data were simultaneously collected from the helicopter to properly georeference the GPR data. Additional 50 m ground-based transects of GPR data were also collected as a source of ground truthing, as a calibration aid for the airborne data sets, and as a source of higher resolution data for characterizing the strata within the peat. In situ peat depth probing and soil characterizations from excavated soil pits were used to verify GPR findings. Results from the ground-based data are presented.

Pelletier-Travis, Ramona E.↗
NASA NTRS1995

Remote sensing of hydrologic variables in boreal areas, phase 2

During Phase 2 airborne Gamma Radiation measurements were conducted over 48 BOREAS (boreal ecosystem atmosphere study) flight lines. Ground measurements of the soil moisture (SM) of the mineral soil and the depth and water content (WC) of the moss/humus layer were collected for calibration of the flight lines. Special attention has been given to the flight lines over, and near, the primary tower sites in the southern study area (SSA); Old Black Spruce (OBS), Old Jack Pine, Old Aspen, and Young Aspen. Multiple ground surveys (September 1993, July, August, and September 1994) show the variation of the water content of the moss/humus layers and changes in the amount of standing water near the SSA OBS tower during the period September 1993 to September 1994. All ground data, airborne estimates and locations of flight lines and ground sampling points have been submitted to BORIS (BOREAS Information System). On 8-10 September 1994 exceptionally high values of cosmic radiation were observed by the airborne gamma radiation system over the SSA. Follow up investigation has not determined the source of, or what caused, the high cosmic count rates.

Peck, Eugene L.↗
NASA NTRS2014

Current Ground Test Options for Nuclear Thermal Propulsion (NTP)

About 20 different NTP engines/ reactors were tested from 1959 to 1972 as part of the Rover and Nuclear Engine for Rocket Vehicle Application (NERVA) program. Most were tested in open air at test cell A or test cell C, at the Nevada Test Site (NTS). Even after serious engine breakdowns of the reactor (e.g., Phoebus 1A), the test cells were cleaned up for other engine tests. The engine test stand (ETS) was made for high altitude (approximately 1 psia) testing of an NTP engine with a flight configuration, but still had the exhaust released to open air. The Rover/NERVA program became aware of new environmental regulations which would prohibit the release of any significant quantity of radioactive particulates and noble gases into the open air. The nuclear furnace (NF-1) was the last reactor tested before the program was cancelled in 1973, but successfully demonstrated a scrubber concept on how to filter the NTP exhaust. The NF-1 was demonstrated in the summer of 1972. The NF-1 used a 44MW reactor and operated each run for approximately 90 minutes. The system cooled the hot hydrogen exhaust from the engine with a water spray before entering a particle filter. The exhaust then passed through a series of heat exchangers and water separators to help remove water from the exhaust and further reduce the exhaust temperatures. The exhaust was next prepared for the charcoal trap by passing through a dryer and effluent cooler to bring exhaust temperatures close to liquid nitrogen. At those low temperatures, most of the noble gases (e.g., Xe and Kr made from fission products) get captured in the charcoal trap. The filtered hydrogen is finally passed through a flare stack and released to the air. The concept was overall successful but did show a La plating on some surfaces and had multiple recommendations for improvement. The most recent detailed study on the NTP scrubber concept was performed by the ARES Corporation in 2006. The concept is based on a 50,000 lbf thrust engine (approximately 1 GW) with a maximum burn time of 1 hour. The concept utilized lessons learned from NF-1. The strategy breaks down the exhaust into parallel paths to allow flexibility with engine size and mass flow of exhaust. Similar to NF-1, the exhaust is slowed down, cooled, filtered of particulates, filtered of noble gases, and then the clean hydrogen is flared to open air. Another concept proposed by Steve Howe (currently Director of the Center for Space Nuclear Research) to simplify the NTP exhaust filtering is to run the hydrogen exhaust into boreholes underground to filter the exhaust. The two borehole site locations proposed are at the NTS and at the Idaho National Laboratory (INL). At NTS, the boreholes are 8' diameter and 1200' deep. The permeability of hydrogen through the soil and its buoyancy will allow it to rise up through the soil and allow the filtering of noble gases and radioactive particulates. The exhaust needs to be cooled to 600C before entering the borehole to avoid soil glazing. Preliminary analysis shows a small buildup of back pressure with time which depends on permeability. Noble gases entering the borehole walls deep can take a long time before reaching the surface. Other factors affecting permeability include borehole pressure, water saturation, and turbulence. Also, a possible need to pump out contaminated water collected at the bottom of the borehole. At INL, the borehole concept is slightly different. The underground borehole has openings to the soil at special depths which have impermeable interbeds above the water table and below the surface to allow the exhaust to travel horizontal between the impermeable layers. Preliminary results indicate better permeability than at NTS. The last option is total containment of the exhaust during the test run. The concept involves slowing down the flow to subsonic in a water cooled diffuser. The hydrogen is burned off in an oxygen rich afterburner with the only products being steam, oxygen, and some noble gases. A heat exchanger and water spray pulls heat from the steam and lowers the temperature for condensation. The optimum ratio between the two is being investigated, with a goal to minimize the total volume of the water hold tanks. A water tank farm collects the contaminated water. The amount of water produced from burning the hydrogen is approximately 100,000 gallons (not including cooling water) for a 25k lbf engine operating for 50 minutes. Residual gases (e.g., oxygen and some noble gases) can be captured at cryogenic levels with a liquid nitrogen cooled dewar. After a few weeks post-test, the radiation levels can drop to more favorable levels before slowly draining each capture tank and using existing filters. With today's environmental regulations, the NTP exhaust is filtered to meet 10 mrem/year exposure to the general public (at a DOE site) or 100 mrem/year (via NRC when tested elsewhere), when natural background radiation exposure to the general public is 300- 600 mrem per year. The current society feels more comfortable with filtering even lower to as low as reasonably achievable (ALARA).

Gerrish, Harold P., Jr.↗
NASA NTRS2021

Evaluation of High Mountain Asia-Land Data Assimilation System (Version 1) from 2003 to 2016, Part I: A Hyper-Resolution Terrestrial Modeling System

This first paper of the two-part series focuses on demonstrating the accuracy of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (∼1-km) and 0.25° (∼25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

Yuan Xue↗
NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domainscale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospherichydrological process within a land surface model for use in HMA.

Yuan Xue↗
NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domain-scale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospheric-hydrological process within a land surface model for use in HMA.

Yuan Xue↗
NASA NTRS2022

Robustness of Vegetation Optical Depth Retrievals Based on L-Band Global Radiometry

Microwave vegetation optical depth (VOD) and soil moisture (SM) can be simultaneously retrieved based on L-band radiometry with polarization information. VOD is indicative of the vegetation water content (VWC) because it captures the extinction of land surface emission. If the connectivity of VOD to VWC is robust, the pair of VWC-SM observations can be viable bases for understanding soil–plant–atmosphere water relations, providing new perspectives on ecosystem science. Simultaneous SM–VOD retrievals are feasible by inverting the τ−ω model with two independent datasets in dual-channel algorithms. However, given correlated satellite vertical and horizontal brightness temperatures (TBs; TB v and TB h ), an ill-posed inverse problem arises where TB errors result in high uncertainties of retrievals. In this study, we apply the degrees-of-information (DoI) metric and propose a signal-to-noise ratio (SNR) metric to assess the “retrievability” of VOD given the Soil Moisture Active Passive (SMAP) TB v –TB h linear dependence. The application of these metrics allows determining where the VOD retrievals are robust and reliable. This is a necessary step in supporting the applications of VOD in ecology and hydrology. Results show that regions with mainly nonwoody vegetation have the best potential for VOD retrievals, though regularization is necessary. We then assess VOD time variations from two regularization products that reduce the impact of underdetermined inversions: the L3 dual-channel algorithm (L3-DCA) and the multitemporal dual-channel algorithm (MTDCA), which constrain VOD time dynamics with and without using a priori VOD climatology, respectively. Though they both reduce noise, especially in the VOD retrievals, they result in differences in VOD seasonal amplitude and coupling to SM at high frequencies as we outline here.

Microwave↗
DOE OSTI2022

Soil moisture, physical and chemical properties coincident with airborne SAR data collections for 2017 and 2019, Seward Peninsula, Alaska

Soil samples were collected coincident with in-situ soil moisture and thaw depth measurements at NGEE Arctic study sites on the Seward Peninsula, Alaska in August 2017 and 2019 Field measurements and flights were conducted during both summers as a collaboration between the NASA ABoVE Project's Airborne SAR Campaign and the NGEE Arctic Project. Airborne overflights of L-band SAR instruments occurred during the soil sampling periods. Laboratory measurements of soil properties include bulk density, volumetric and gravimetric water content, carbon and nitrogen content, and particle size of mineral components. Soil samples processed and reported in this dataset were collected coincident with in situ measurements of soil moisture and thaw depth and airborne P-band and L-band SAR measurements as a collaboration between NGEE Arctic and NASA ABoVE. To learn more about how ABoVE protocols were applied for sampling site selection and making in situ measurements, see the following datasets: (2017: https://doi.org/10.5440/1423892 and 2019: https://doi.org/10.5440/1856042). Contained in this dataset are four .csv data files (including data dictionaries) and one zipped folder of *.pdf files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort (with some overlap with Covid-19 pandemic) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗
NASA NTRS1977

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

Rao, R. G. S.↗