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At least 595 records · Page 33

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

remote sensing↗

Strategies for Validating Satellite Soil Moisture Products Using in Situ Networks: Lessons from the USDA-ARS Watersheds

There are a variety of soil moisture station designs and networks deployed throughout the world, each with varying applications and uses. The purpose of satellite validation of soil moisture products, a dense network of soil moisture networks are required with soil moisture sensors at the near surface (approx. 5 cm or less) to correspond to the satellite footprints and signals. The USDA- Agricultural Research Service operates a collection of soil moisture networks as a part of the Long Term Agro-ecosystem Research (LTAR) network to this end. These networks have been used to validate products from AMSR-E, SMOS, Aquarius, and SMAP. A review of these results and a synopsis of successful scaling strategies are discussed.

soil moisture↗

An Assessment of the Differences Between Spatial Resolution and Grid Size for the SMAP Enhanced Soil Moisture Product over Homogeneous Sites

Satellite-based passive microwave remote sensing typically involves a scanning antenna that makes measurements at irregularly spaced locations. These locations can change on a day to day basis. Soil moisture products derived from satellite-based passive microwave remote sensing are usually resampled to a fixed Earth grid that facilitates their use in applications. In many cases the grid size is finer than the actual spatial resolution of the observation, and often this difference is not well understood by the user. Here, this issue was examined for the Soil Moisture Active Passive (SMAP) enhanced version of the passive-based soil moisture product, which has a grid size of 9-km and a nominal spatial resolution of 33-km. In situ observations from core validation sites were used to compute comparison metrics. For sites that satisfied the established reliability and scaling criteria, the impact of validating the 9-km grid product with in situ data collected over a 9-km versus a 33-km domain was very small for the sites studied (0.039 cu. m/cu. m unbiased root mean square difference for the 9-km case versus 0.037 cu. m/cu. m for the 33-km case). This result does not mean that the resolution of the product is 9-km but that for the conditions studied here the soil moisture estimated from in situ observations over 9-km is a close approximation of the soil moisture estimated from in situ observations over the 33-km resolution. The implication is that using the enhanced SMAP product at its grid resolution of 9-km should not introduce large errors in most applications.

Soil moisture↗

Variability in Modelled Airborne Dust Mineralogy Derived from Global Soil Composition Uncertainties

Dust aerosols consist on a variety of minerals with different physic and chemical properties. As such, they interact with short and long wave radiation, potentially form clouds, act as nutrients modulating biogeochemical cycles, or influence atmospheric chemistry, differently. Most current state-of-the-art Earth System Models (ESMs) neglect the complexity in dust composition, mainly due to computational constraints, but also to the existing uncertainties in the size resolved composition of parent soils, the resulting distribution of minerals in airborne dust, and the scarcity of observations to constrain them. Within this work, we assess the variability of global dust composition due to uncertainties in the characterization of the parent soil mineralogy. To that end, we consider two available global soil mineralogy atlases, developed by Claquin et al. (1999) –C1999- and Journet et al. (2014) –J2014-, which represent respectively 8 and 12 relevant minerals for climate (namely: illite, smectite/montmorillonite, kaolinite, calcite, gypsum, hematite, quartz, and feldspars in C1999, and those plus chlorite, vermiculite, goethite, and mica in J2014). Thanks to a recently developed feature of the MONARCH atmospheric-chemistry model, we are able to explicitly resolve the minerals’ atmospheric cycle. Therefore, we define two global experiments to assess changes on airborne dust composition attributed to the soil mineralogy assumptions and provide a measure of their variability. We also perform a preliminary evaluation of the global mineralogy results against available observations of mineral fractions in surface dust concentration. Our results will inform the climate modelling community about the potential variability in dust composition, an aspect that will gain relevance as ESMs continue growing in complexity and new processes to better characterize aerosols’ forcing or biogeochemical cycles are added. Further observational constraints, such as those that will derive from the EMIT NASA mission on soil composition or the FRAGMENT experimental campaigns on airborne dust characterization, will be key in the near future to improve our understanding of the impact of dust mineralogy on fundamental climate features.

Dust aerosols↗

Evaluation of Extreme Soil Moisture Patterns over the Sahel during the 2020 Growing Season

The African Sahel is an ecologically and climatically sensitive region, and thus is a valuable test case for examination of climate extremes. Above-average rainfall during the 2020 growing season (June-October) led to flooding in the West, Central and East Sahel, with implications for infrastructure, agriculture and disease outbreaks. In this study, we evaluate soil moisture patterns in the region during 2020 to assess and quantify the extremeness of the event. The primary tool is the NASA Soil Moisture Active Passive (SMAP) Level 4 surface soil moisture data. Daily, monthly, and seasonal anomalies are computed relative to SMAP’s long-term mean (2015-2021). Additional comparisons are made with longer-time-series data sets, including surface soil moisture from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2(MERRA-2; 1981-present) and precipitation from the African Rainfall Climatology, Version 2 (ARC2; 1983-present).Possible drivers of the extreme wet event are examined, including potential links to the concurrent 2020-21 La Niña event. Finally, we explore the connections between the extreme soil moisture and vector-borne disease outbreaks in the region in2020, namely, Rift Valley Fever in Mauritania and Chikungunya in Chad.

Soil Moisture↗

Local Scale (3-M) Soil Moisture Mapping Using SMAP and Planet Superdove

A capability for mapping meter-level resolution soil moisture with frequent temporal sampling over large regions is essential for quantifying local-scale environmental heterogeneity and eco-hydrologic behavior. However, available surface soil moisture (SSM) products generally involve much coarser grain sizes ranging from 30 m to several 10s of kilometers. Hence a new method is proposed to estimate 3-m resolution SSM using a combination of multi-sensor fusion, machine- learning (ML) and Cumulative Distribution Function (CDF) matching approaches. This method established favorable SSM correspondence between 3-m pixels and overlying 9-km grid cells from overlapping Planet SuperDove (PSD) observations and NASA Soil Moisture Active-Passive (SMAP) mission products. The resulting 3-m SSM predictions showed improved accuracy by reducing ab- solute bias and RMSE by ~0.01 cm3/cm3 over the original SMAP data in relation to in-situ soil moisture measurements for the Australian Yanco region, while preserving the high sampling frequency (1-3 day global revisit) and sensitivity to surface wetness (R 0.865) from SMAP. Heterogeneous soil moisture distributions varying with vegetation biomass gradients and irrigation regimes were generally captured within a selected study area. Further algorithm refinement and implementation for regional applications will allow for improvement in water resources management, precision agriculture, and disaster forecasts and responses.

soil moisture↗

The Changing Influence of Precipitation on Soil Moisture Drought With Warming in the Mediterranean and Western North America

Anthropogenic climate change has already affected drought severity and risk across many regions, and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below-normal precipitation and terminated by average or above-normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming-driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought. Here, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29% in the Mediterranean and 32% and 6% in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts.

drought↗

Soil mechanics results of Luna 16 and Lunokhod 1: A preliminary report

The physical and mechanical properties of the lunar soil, as determined by Luna 16 and Lunokhod 1 experiments, are discussed. Data are included for interactions between vehicle wheels and the lunar soil, compressibility, resistance to penetration, and friction characteristics of the soil. The shear strength of the returned lunar soil for various bulk densities is also examined. Several potential spacecraft materials were tested in contact with lunar soil to determine their friction and wear characteristics.

Johnson, S. W.↗

Enzyme activity in terrestrial soil in relation to exploration of the Martian surface

Urease activity in soil is persistent for long periods under low water, low temperature, and sterile regimes, and it was suggested that some form of enzyme-protective mechanism exists in soil. Dublin soil was extracted by sonication in water followed by adding a mixture of salts. Urease activity is associated with the organo-mineral complex thus obtained and is resistant to the activities of proteolytic enzymes. Clay free soil organic matter prepared subsequently by filtration also exhibits urease activity which is resistant to proteolysis. Models consisting of enzymes with bentonite and lignin were found to mimic this resistance to proteolysis. A model system is presented which suggests both the origin and location of soil ureases and a reason for their persistence in nature.

Ardakani, M. S.↗

Dielectric constants of soils at microwave frequencies

A knowledge of the complex dielectric constant of soils is essential in the interpretation of microwave airborne radiometer data of the earth's surface. Measurements were made at 37 GHz on various soils from the Phoenix, Ariz., area. Extensive data have been obtained for dry soil and soil with water content in the range from 0.6 to 35 percent by dry weight. Measurements were made in a two arm microwave bridge and results were corrected for reflections at the sample interfaces by solution of the parallel dielectric plate problem. The maximum dielectric constants are about a factor of 3 lower than those reported for similar soils at X-band frequencies.

Geiger, F. E.↗

General soil map Lower Pantano wash area, Pima County, Arizona

High altitude color photography was used to determine soil type variation over large areas at a contact print scale of 1:125,000. It was found that color variation and land form could be used as a basis for assigning seven soil mapping units to the area as depicted on stereoscopic pairs of the color photography. A unit is assigned by soil scientists on the basis of similarity of soil features in the area to predetermined physical and chemical characteristics of the same soil type.

Richardson, M. L.↗

Soil moisture measurements with microwave, radiometers

One technique of measuring moisture content that appears promising is that of microwave radiometry. In the microwave region of the spectrum, the emissivity of water is approximately 0.4, whereas that of dry soil is approximately 0.9. Therefore, the emissivity of the soil can range from about 0.6 to 0.9 as the soil changes from a wet to a dry condition. Recent ground base measurements have demonstrated emissivity changes of this magnitude. To test the use of this approach for remote sensing of soil moisture, flights were made over agricultural test sites in the vicinity of Phoenix, Ariz., during late February 1971. On the same day, soil moisture measurements were made on the ground for 200 fields. On board the aircraft were six microwave radiometers, ranging in wavelength from 21 cm to 8 mm. The results of one of these radiometers are presented.

Schmugge, T. J.↗

Soil mechanical properties at the Apollo 14 site.

The Apollo 14 lunar landing provided a greater amount of information on the mechanical properties of the lunar soil than previous missions. Measurements on core-tube samples and the results of transporter track analyses indicate that the average density of the soil in the Fra Mauro region is in the range from 1.45 to 1.60 g/cu cm. The soil strength appears to be higher in the vicinity of the site of the Apollo 14 lunar surface experiments package, and trench data suggest that strength increases with depth. Lower-bound estimates of soil cohesion give values of 0.03 to 0.10 kN/sq m, which are lower than values of 0.35 to 0.70 kN/sq m estimated for soils encountered in previous missions. The in situ modulus of elasticity, deduced from the measured seismic-wave velocity, is compatible with that to be expected for a terrestrial silty fine sand in the lunar gravitational field.

Mitchell, J. K.↗

Utilization of ERTS data to detect plant diseases and nutrient deficiencies, soil types and moisture levels

The author has identified the following significant results. A significant finding is the identification and delineation of a large soil association in Obion County, West Tennessee. These data are now being processed through the scanner and computer and will be included in the next report along with pictures of printout and imagery. Channel 7 appears to provide the most useful imagery related to soil differences. Soil types have been identified through the use of aircraft imagery. However, a soil association map appears to be the best that space imagery will provide. The exception to this will be large areas of a uniform soil type as occurs in the great plains.

Parks, W. L.↗

Application of multispectral remote sensing to soil survey research in Indiana

Computer-implemented mappings based on spectral properties of bare soil surfaces were compared with mapping units of interest to soil surveyors. Some soil types could be differentiated by their spectral properties. In other cases, soils with similar surface colors and textures could not be distinguished spectrally. The spectral maps seemed useful for delineating boundaries between soils in many cases.

Zachary, A. L.↗

Definition of spectrally separable classes for soil survey research

A procedure is outlined for defining spectral classes such that the differences between classes can be quantified. It also facilitates determination of a number of classes such that the classes are spectrally discriminable. This is accomplished by partitioning the data into many classes and then combining similar spectral classes on the basis of appropriate criteria. Multispectral data were collected over a 12-mile flightline in White County, Indiana, in connection with the 1971 Corn Blight Watch Experiment. Data were collected in May by the University of Michigan airborne scanning spectrometer at an altitude of 5000 feet. Spectral maps resulting from the analysis were compared to existing soil surveys of the National Cooperative Soil Survey. The method should help determine the extent to which spectral properties of soil surfaces can be associated with morphologic and topographic differences of interest to soil surveyors engaged in operational soil mapping.

Cipra, J. E.↗

Utilization of ERTS data to detect plant diseases and nutrient deficiencies, soil types and moisture levels

The author has identified the following significant results. A significant finding to date is the delineation of the Memphis soil association in Obion County, Dyer County, and in portions of Kentucky. This soil association was delineated mechanically through the use of imagery in the digital tape format, appropriate computer software, and an IBM/360/05 computer. The Waverly-Swamp association as well as the Obion River have been identified on the ERTS-1 imagery as well as on the computer printout. These findings demonstrate the feasibility of delineating major soil associations through vegetative cover common to the association. Channel 7 provides the most information for studies of this type. Computer density printouts assist markedly in making density separations and delineating major soil moisture differences; however, signatures for soil moisture classification for this area of mixed land uses in relatively small tracts have not yet been developed.

Parks, W. L.↗

Delineation of major soil associations using ERTS-1 imagery

The delineation of a major soil association in the loess region of Obion County has been accomplished using ERTS-1 imagery. Channel 7 provides the clearest differentiation. The separation of other smaller soil associations in an intensive row crop agricultural area is somewhat more difficult. Soil differentiation has been accomplished visually as well as electronically using a scanning microdensitometer. Lower altitude aircraft imagery permits a more refined soil association identification and where imagery is of sufficient scale, even individual soils may be identified.

Parks, W. L.↗