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At least 955 records · Page 53Linked to original sources

Net Ecosystem Production (NEP) of the Great Plains, United States

Gross primary production (GPP) and ecosystem respiration (Re) are the fundamental environmental characteristics that promote carbon exchanges with the atmosphere (Chapin and others, 2009), although other exchanges of carbon, such as direct oxidation (Lovett and others, 2006), can modify net ecosystem production (NEP). The accumulation of carbon in terrestrial ecosystems results in systems in which soil organic matter (SOM) carbon often exceeds biomass carbon (Post and Kwon, 2000). This SOM pool exists at a steady state between GPP and Re in ecosystems unless drivers change or the ecosystem endures environmental perturbations (for example, climatic). As indicated by Wilhelm and others (2011), conversion of grasslands to agriculture and cultivation can result in reduced soil carbon, with the release of carbon dioxide (CO 2 ) to the atmosphere by stimulated oxidation and higher Re; therefore, land-use and land management practices have clear effects on NEP, with potential repercussions on ecosystems. The recent demand for biofuels has changed land-use and cropping patterns, especially in Midwestern United States (Wilhelm and others, 2011). It is important to ensure the sustainability of these and other land uses and to assess the effects on NEP. Flux tower networks, such as AmeriFlux and FLUXNET, consist of a growing number of eddy covariance flux tower sites that provide a synoptic record of the exchange of carbon, water, and energy between the ecosystem and atmosphere at various temporal frequencies. These towers also detect and measure certain site characteristics, such as wind, temperature, precipitation, humidity, atmospheric pressure, soil features, and phenological progressions. Efforts are continuous to combine flux tower network data with remote sensing data to upscale the conditions observed at specific sites to a regional and, ultimately, worldwide scale. Data-driven regression tree models have the ability to incorporate flux tower records and remote sensing data to quantify exchanges of carbon with the atmosphere (Wylie and others, 2007; Xiao and others, 2010; Zhang and others, 2010; Zhang and others, 2011). Previous study results demonstrated the dramatic effect weather has on NEP and revealed specific ecoregions and times acting as carbon sinks or sources. As of 2012, more than 100 site-years of flux tower measurements, represented by more than 50 individual cropland or grassland sites throughout the Great Plains and surrounding area, have been acquired, quality controlled, and partitioned into gross photosynthesis (Pg) and ecosystem Re using detailed light-response, soil temperature, and vapor pressure deficit (VPD) based analysis.

Great Plains↗

A generalized framework for inferring river bathymetry from image-derived velocity fields

Although established techniques for remote sensing of river bathymetry perform poorly in turbid water, image velocimetry can be effective under these conditions. This study describes a framework for mapping both of these attributes: Depths Inferred from Velocities Estimated by Remote Sensing, or DIVERS. The workflow involves linking image-derived velocities to depth via a flow resistance equation and invoking an optimization algorithm. We generalized an earlier formulation of DIVERS by: (1) using moving aircraft river velocimetry (MARV) to obtain a continuous, spatially extensive velocity field; (2) working within a channel-centered coordinate system; (3) allowing for local optimization of multiple parameters on a per-cross section basis; and (4) introducing a second objective function that can be used when discharge is not known. We also quantified the sensitivity of depth estimates to each parameter and input variable. MARV-based velocity estimates agreed closely with field measurements ( R 2 = 0.81 "> R 2 =0.81 ) and the use of DIVERS led to cross-sectional mean depths that were correlated with in situ observations ( R 2 = 0.75 "> R 2 =0.75 ). Errors in the input velocity field had the greatest impact on depth estimates, but the algorithm was not highly sensitive to initial parameter estimates when a known discharge was available to constrain the optimization. The DIVERS framework is predicated upon a number of simplifying assumptions — steady, uniform, one-dimensional flow and a strict, purely local proportionality between depth and velocity — that impose important limitations, but our results suggest that the approach can provide plausible, first-order estimates of river depths.

Alaska↗

Advances in spectroscopic methods for quantifying soil carbon

The current gold standard for soil carbon (C) determination is elemental C analysis using dry combustion. However, this method requires expensive consumables, is limited by the number of samples that can be processed (~100/d), and is restricted to the determination of total carbon. With increased interest in soil C sequestration, faster methods of analysis are needed, and there is growing interest in methods based on diffuse reflectance spectroscopy in the visible, near-infrared or mid-infrared spectral ranges. These spectral methods can decrease analytical requirements and speed sample processing, be applied to large landscape areas using remote sensing imagery, and be used to predict multiple analytes simultaneously. However, the methods require localized calibrations to establish the relationship between spectral data and reference analytical data, and also have additional, specific problems. For example, remote sensing is capable of scanning entire watersheds for soil carbon content but is limited to the surface layer of tilled soils and may require difficult and extensive field sampling to obtain proper localized calibration reference values. The objective of this chapter is to discuss the present state of spectroscopic methods for determination of soil carbon.

Book chapter↗

South Florida Everglades: satellite image map

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

IMAP↗

The Tetracorder user guide: version 4.4

Imaging spectroscopy mapping software assists in the identification and mapping of materials based on their chemical properties as expressed in spectral measurements of a planet including the solid or liquid surface or atmosphere. Such software can be used to analyze field, aircraft, or spacecraft data; remote sensing datasets; or laboratory spectra. Tetracorder is a set of software algorithms commanded through an expert system to identify materials based on their spectra (Clark and others, 2003). Tetracorder also can be used in traditional remote sensing analyses, because some of the algorithms are a version of a matched filter. Thus, depending on the instructions fed to the Tetracorder system, results can range from simple matched filter output, to spectral feature fitting, to full identification of surface materials (within the limits of the spectral signatures of materials over the spectral range and resolution of the imaging spectroscopy data). A basic understanding of spectroscopy by the user is required for developing an optimum mapping strategy and assessing the results.

Open-File Report↗

Estimating seasonal evapotranspiration from temporal satellite images

Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed images. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of satellite overpass using eight Landsat images during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement ( R 2 = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference ( P > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.

Irrigation Science↗

Non-invasive exploration in an environmentally sensitive world

Modern remote sensing provides a means for locating and characterizing exposed mineralized systems in many parts of the world. These capabilities are non-invasive and help target specific areas for more detailed exploration. An example of how remote sensing technology can be used is evident from a study of the Questa Mining District, New Mexico. Analysis of low spectral resolution data from the Landsat Thematic Mapper satellite system clearly shows the regional distribution of two broad mineral groups often associated with mineralized systems: clay-carbonate-sulfate and iron oxides-iron hydroxides. Analysis of high spectral resolution data from the Airborne Visible and Infrared Imaging System (AVIRIS) shows the occurrence and distribution of many individual mineral species that characterize the pattern of hydrothermally altered rocks in the district.

Conference Paper↗

System characterization report on the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS)

Executive Summary This report addresses system characterization of the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present the methodology and procedures for characterization and the technical and operational information about the specific sensing system being evaluated. These reports also provide a description of data measurements, data retention practices, and data analysis results and provide system characterization conclusions. In partnership with Teledyne Brown Engineering, DLR built the DESIS hyperspectral instrument, which Teledyne Brown Engineering then integrated onto its International Space Station-based imaging platform, the Multi-User System for Earth Sensing. DLR developed the processing software and, together with Innovative Imaging and Research, completes the validation and calibration of the data products. DESIS was launched in 2018, and the data are used for scientific research in atmospheric physics and Earth sciences. The DESIS sensor contributes to the scientific and commercial utilization of the International Space Station and helps to further hyperspectral remote sensing technologies for future satellites. More information on DLR satellites and sensors is included within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at https://www.dlr.de/DE/Home/home_node.html . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that DESIS has an interior geometric performance of less than a 3.30-meter (less than 0.11 pixel) root mean square error in band-to-band registration, an exterior geometric performance in the range of a 2.40- (0.08 pixel) to 17.40-meter (0.58 pixel) offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.013 to 1.011 (offset and slope), and a spatial performance for band 130 of 1.5 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency of 0.167.

Open-File Report↗

Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications

Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r 2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.

Nature Water↗

The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong ( R 2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.

Great Basin↗

Clarifying regional hydrologic controls of the Marañón River, Peru through rapid assessment to inform system-wide basin planning approaches

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.

Marañón River↗

Visual interpretation of high-resolution aerial imagery: A tool for land managers

Remotely sensed imagery from various collection platforms (e.g., satellites, crewed and uncrewed aircraft) are used by biologists and other conservation personnel to support management activities ranging from monitoring invasive species to assessing land cover and vegetation characteristics. Although remote sensing–based vegetation indices and models have been developed and used for some management applications, straightforward visual interpretation of imagery by on-the-ground personnel may be a pragmatic approach for obtaining time-sensitive and spatially relevant information to support and guide local management activities. Our primary objective was to qualitatively assess our ability to identify patches of target invasive plant species based on simple visual interpretation of high-resolution aerial imagery. We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery by using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species had a relationship to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. Our straightforward, qualitative assessment suggests that visual interpretation of high-resolution imagery, but not some lower-resolution imagery, may be an efficient and effective tool for supporting local invasive species management through activities such as monitoring known patches, identifying undetected infestations, assessing management actions, guiding field work, or prioritizing on-the-ground monitoring activities.

Journal of Fish and Wildlife Management↗

The ASTER data system: An overview of the data products in Japan and in the United States

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data system is a cooperative system, which is operated jointly by Japan’s Ministry of Economy, Trade, and Industry (METI) through its Earth Remote Sensing Data Analysis Center (ERSDAC), and by the National Aeronautics and Space Administration (NASA) primarily through its Goddard Space Flight Center (GSFC) and Land Processes (LP) Distributed Active Archive Center (DAAC). ASTER is a moderate-resolution land remote sensing system onboard the Earth Observing System (EOS) Terra spacecraft. ASTER-acquired data are received at the White Sands, New Mexico, ground receiving station, and then transmitted via land network to the EOS Data and Operations System (EDOS) within the Goddard DAAC, located at the GSFC. EDOS pre-processes raw ASTER data to Level-0 (L0) data, and sends them via the high-speed Asia-Pacific Advanced Network (APAN) to the ASTER Ground Data System (GDS) in Japan. ASTER GDS processes the L0 data to level-1 (L1) datasets; they distribute these data to users, and also use them to generate higher-level products for their user community. ASTER GDS sends a copy of all L1A data they produce to NASA’s LP DAAC, located at the U.S. Geological Survey’s Center for Earth Resources Observation and Science (EROS) near Sioux Falls, South Dakota. All L1 data received from Japan are ingested, archived, and available for users at LP DAAC. The LP DAAC also generates and distributes higher-level products from L1 data based on requests from users. To meet time-critical needs related to sensor health and performance, natural disasters, national emergencies, and certain field campaigns, the ASTER Expedited Data System (EDS) was developed, and is operated jointly by U.S. and Japanese partners.

Book chapter↗

Dynamics of submarine groundwater discharge and associated fluxes of dissolved nutrients, carbon, and trace gases to the coastal zone (Okatee River estuary, South Carolina)

Multiple techniques, including thermal infrared aerial remote sensing, geophysical and geological data, geochemical characterization and radium isotopes, were used to evaluate the role of groundwater as a source of dissolved nutrients, carbon, and trace gases to the Okatee River estuary, South Carolina. Thermal infrared aerial remote sensing surveys illustrated the presence of multiple submarine groundwater discharge sites in Okatee headwaters. Significant relationships were observed between groundwater geochemical constituents and 226 Ra activity in groundwater with higher 226 Ra activity correlated to higher concentrations of organics, dissolved inorganic carbon, nutrients, and trace gases to the Okatee system. A system-level radium mass balance confirmed a substantial submarine groundwater discharge contribution of these constituents to the Okatee River. Diffusive benthic flux measurements and potential denitrification rate assays tracked the fate of constituents in creek bank sediments. Diffusive benthic fluxes were substantially lower than calculated radium-based submarine groundwater discharge inputs, showing that advection of groundwater-derived nutrients dominated fluxes in the system. While a considerable potential for denitrification in tidal creek bank sediments was noted, in situ denitrification rates were nitrate-limited, making intertidal sediments an inefficient nitrogen sink in this system. Groundwater geochemical data indicated significant differences in groundwater chemical composition and radium activity ratios between the eastern and western sides of the river; these likely arose from the distinct hydrological regimes observed in each area. Groundwater from the western side of the Okatee headwaters was characterized by higher concentrations of dissolved organic and inorganic carbon, dissolved organic nitrogen, inorganic nutrients and reduced metabolites and trace gases, i.e. methane and nitrous oxide, than groundwater from the eastern side. Differences in microbial sulfate reduction, organic matter supply, and/or groundwater residence time likely contributed to this pattern. The contrasting features of the east and west sub-marsh zones highlight the need for multiple techniques for characterization of submarine groundwater discharge sources and the impact of biogeochemical processes on the delivery of nutrients and carbon to coastal areas via submarine groundwater discharge.

South Carolina↗

Summary mineral resource appraisal of the Richfield 1° x 2° quadrangle, west-central Utah

The mineral resource potential of the Richfield 1° x 2° quadrangle, Utah, has been appraised using geological, geophysical, geochemical, and remote-sensing techniques. These studies have led to many publications giving basic data and interpretations; of these, a series of 18 maps at 1:250,000 and 1:500,000 scales summarizing aspects of the geology, geophysics, geochemistry, and remote sensing is designated the CUSMAP (Conterminous United States Mineral Appraisal Program) folio. This circular uses the data shown on these maps to appraise the mineral resource potential of the quadrangle. The oldest rocks exposed in the Richfield quadrangle are small patches of Early Proterozoic (1.7 billion years old) gneiss and schist on the west side of the Mineral Mountains. These rocks presumably formed the basement on which many thousands of meters of Late Proterozoic, Paleozoic, and lower Mesozoic sedimentary strata were deposited. These rocks were deformed during the Late Cretaceous Sevier orogeny when Precambrian and Paleozoic strata in the western part of the quadrangle were thrust relatively eastward across Paleozoic and Mesozoic strata in the eastern part of the quadrangle. Late Cretaceous and early Tertiary highlands above the overthrust belt were eroded and much of the debris was deposited in broad basins east of the belt. Volcanism in Oligocene and earliest Miocene time formed an east-northeast-trending belt of calcalkalic volcanoes across the southern half of the quadrangle. In early Miocene time, the composition of the volcanic rocks changed to a bimodal assemblage of mafic rocks and high-silica alkali rhyolite that has been erupted episodically ever since. Syngenetic mineral resources developed during formation of both sedimentary and volcanic rocks. These include limestone and dolomite, silica-rich sandstone, metalliferous black shale, evaporite deposits, zeolite deposits, pumice, cinders and scoria, and evaporitic or diagenetic deposits in playa environments. Most of these deposits need to have markets established, or extraction and fabrication techniques developed, for them to be utilized. Most epigenetic deposits are of volcanogenic-hydrothermal origin. Deposits associated with calc-alkalic igneous activity largely contain Cu, Pb, Zn, Au, and Ag, and occur in a variety of types zoned around core intrusions. Younger deposits are mostly associated with silicic igneous centers belonging to the bimodal mafic-silicic igneous association. Resources associated with this latter group are likely to contain one or more of the elements Mo, W, U, Sn, Be, and F, as well as Pb, Zn, Au, and Ag. Alunite and kaolinite deposits are found at many mineralized centers. Most epigenetically mineralized areas expose only the upper, near-surface parts of the different hydrothermal systems; most of whatever mineral deposits formed in these systems probably still exist at depth, awaiting discovery. Our conclusion is that many mineralized areas have excellent possibilities for the occurrence of mineral resources. Each of the many identified centers of mineralization is discussed briefly in this report and an estimate made of its resource potential.

Utah↗

Multi-species telemetry quantifies current and future efficacy of a remote marine protected area

Large-scale marine protected areas (LSMPAs; > 1000 km 2 ) provide important refuge for large mobile species, but most do not encompass species' ranges. To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements ( n = 83; tracking duration range: 0.5–350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1–2.6, “Sustainability”; SSP 3–7.0, “Rocky Road”), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040–2050, followed by an equilibrium response and regained habitat by 2090–2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future.

Kingman Reef, Palmyra Atoll, U.S. Pacific Islands ↗

Applying satellite technology to energy and mineral exploration

IGCP Project 143 ("Remote Sensing and Mineral Exploration"), is a worldwide research project designed to make satellite data an operational geological tool along with the geologic pick, hand lens, topographic map, aerial photo and geophysical instruments and data that comprise the exploration package. While remote sensing data will not replace field exploration and mapping, careful study of such data prior to field work should make the effort more efficient.

Episodes↗

Postwildfire measurement of soil physical and hydraulic properties at selected sampling sites in the 2011 Las Conchas wildfire burn scar, Jemez Mountains, north-central New Mexico

The generation of runoff and the resultant flash flooding can be substantially larger following wildfire than for similar rainstorms that precede wildfire disturbance. Flash flooding after the 2011 Las Conchas Fire in New Mexico provided the motivation for this investigation to assess postwildfire effects on soil-hydraulic properties (SHPs) and soil-physical properties (SPPs) as a function of remotely sensed burn severity 4 years following the wildfire. A secondary purpose of this report is to illustrate a methodology to determine SHPs that analyzes infiltrometer data by using three different analysis methods. The SPPs and SHPs are measured as a function of remotely sensed burn severity by using the difference in the Normalized Burn Ratio (dNBR) metric for seven sites. The dNBR metric was used to guide field sample collection across a full spectrum of burn severities that covered the range of Monitoring Trends in Burn Severity (MTBS) and Burned Area Reflectance Classification (BARC) thematic classes from low to high severity. The SPPs (initial and saturated soil-water content, bulk density, soil-organic matter, and soil-particle size) and SHPs (field-saturated hydraulic conductivity and sorptivity) were measured under controlled laboratory conditions for soil cores collected in the field. The SHPs were estimated by using tension infiltrometer measurements and three different data analysis methods. These measurements showed large effects of burn severity, focused in the top 1 centimeter (cm) of soil, on some SPPs (bulk density, soil organic matter, and particle sizes). The threshold of these bulk density and soil organic matter effects was between 300 and 400 dNBR, which corresponds to a MTBS thematic class between moderate and high burn severity and a BARC4 thematic class of high severity. Gravel content and the content of fines in the top 1 cm of soil had a higher threshold value between 450 and 500 dNBR. Lesser effects on SPPs were observed at depths of 1–3 cm and 3–6 cm. In contrast, SHPs showed little effect from dNBR or from MTBS/BARC4 thematic class. Measurements suggested that 4 years of elapsed time after the wildfire may be sufficient for SHP recovery in this area. These measurements also indicated that SPP differences as a function of burn severity cannot be used as reliable indicators of SHP differences as a function of burn severity.

New Mexico↗