SEARCH · USGS Science

Results for “Remote Sensing”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources

USGS2002

Thermal infrared spectroscopy of experimentally shocked anorthosite and pyroxenite: Implications for remote sensing of Mars

The feldspar and pyroxene mineralogies on Mars revealed by the Thermal Emission Spectrometer (TES) on Mars Global Surveyor likely record a variety of shock effects, as suggested by petrologic analyses of the Martian meteorites and the abundance of impact craters on the planet's surface. To study the effects of shock pressures on thermal infrared spectra of these minerals, we performed shock recovery experiments on orthopyroxenite and anorthosite samples from the Stillwater Complex (Montana) over peak pressures from 17 to 63 GPa. We acquired emissivity and hemispherical reflectance spectra (350–1400 cm −1 ; ∼7–29 μm) of both coherent chips and fine-grained powders of shocked and unshocked samples. These spectra are more directly comparable to remotely sensed data of Mars (e.g., TES) than previously acquired absorption or transmission spectra of shocked minerals. The spectra of experimentally shocked feldspar show systematic changes with increasing pressure due to depolymerization of the silica tetrahedra. For the spectra of chips, this includes the disappearance of small bands in the 500–650 cm −1 region and a strong band at 1115 cm −1 , and changes in positions of a strong band near 940 cm −1 and the Christiansen feature near 1250 cm −1 . Spectra of the shocked powders show the gradual disappearance of a transparency feature near 830 cm −1 . Fewer changes are observed in the pyroxene spectra at pressures as high as 63 GPa. Spectra of experimentally shocked minerals will help identify more precisely the mineralogy of rocks and soils not only from TES but also from Mars instruments such as miniTES and THEMIS.

Journal of Geophysical Research E: Planets↗

USGS2018

Springs as hydrologic refugia in a changing climate? A remote sensing approach

Spring‐fed wetlands are ecologically important habitats in arid and semi‐arid regions. Springs have been suggested as possible hydrologic refugia from droughts and climate change; however, springs that depend on recent precipitation or snowmelt for recharge may be vulnerable to warming and drought intensification. Springs that are expected to maintain their ecohydrologic function in a warmer, drier climate may be priorities for conservation and restoration. Identifying such springs is difficult because many springs lack hydrologic records of adequate temporal extent and resolution to assess their resilience to water cycle changes. This study demonstrates proof‐of‐concept for the assessment of certain spring types (i.e., helocrene, hypocrene, and hillslope springs) in terms of hydrologic and ecological resilience to climatic water stress using freely available remote‐sensing and climate data. We used the Normalized Difference Vegetation Index (NDVI) from 1985 through 2011 to delineate surface‐moisture zones (SMZs) associated with 39 clusters of 172 springs in a montane sage‐steppe landscape in southeastern Oregon, USA. We developed and synthesized seven NDVI‐based indicators of SMZ resilience to interannual changes in water availability: (1) mean and (2) standard deviation of July NDVI; (3) mean difference in July NDVI and (4) difference in coefficient of variation for July NDVI between each SMZ and its surrounding watershed; (5) response of SMZ July NDVI to 90‐day antecedent precipitation; (6) response of SMZ July NDVI to the previous winter's snowpack; and (7) range of NDVI values from an exceptionally wet year followed by three dry years. Because all resilience indicators were highly inter‐correlated, we derived an overall metric of SMZ resilience using principal components analysis that accounted for 66% of total variance. This overall resilience score was positively correlated with SMZ elevation, slope, mean annual precipitation, and with the number of associated springs. Resilience was greater for SMZs on topographically shaded, north‐facing slopes. Several high‐resilience SMZs were located immediately below persistent snowbanks, suggesting a possible source of steady recharge throughout the growing season. The approach presented here—if combined with field assessments of spring hydrogeology, discharge, and groundwater age—could help identify spring‐fed wetlands that are most likely to serve as hydrologic refugia from climate change.

Oregon↗

USGS2017

Assessment of phytoplankton resources suitable for bigheaded carps in Lake Michigan derived from remote sensing and bioenergetics

We used bioenergetic simulations combined with satellite-measured water temperature and estimates of algal food availability to predict the habitat suitability of Lake Michigan for adult silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis). Depending on water temperature, we found that bigheaded carp require ambient algal concentrations between 1 and 7 μg chlorophyll/L or between 0.25 × 105 and 1.20 × 105 cells/mL Microcystis to maintain body weight. When the bioenergetics model is forced with the observed average annual temperature cycle, our simulations predicted silver carp bioenergetics predicted annual weight change ranging from 9% weight loss to 23% gain; bighead carp ranged from 68 to 177% weight gain. Algal concentrations b4 μg chlorophyll/L and b200,000 cells/mL were below the detection limits of the remote sensing method. However, all areas with detectable algae have sufficient concentrations of algal foods for bigheaded carp weight-maintenance and growth. Those areas are predominately along the nearshore areas.

Michigan, Wisconsin↗

USGS1974

Remote sensing for identification and classification of wetland vegetation

Multispectral photography and ground truth were obtained on an area 12 miles (19.3 km) east of Bemidji, Minnesota, to identify and map wetlands less than 2 acres (0.8 hectare) in size, to map emergent vegetation in lakes, and to explore the feasibility of classifying vegetation from aerial photographs. Wetlands less than 2 acres in size were identified on photography taken in May 1971, and emergent vegetation was recorded on purposely overexposed infrared black and white photography from a flight in September 1971. Several vegetation types and species groups were recognizable with the aid of color, color infrared, and black and white infrared photography. Proper timing of flights, use of multispectral photography, and knowledge of the ecology of the area are considered essential for wetland mapping by remote sensing.

Minnesota↗

USGS2020

Investigation of suitable habitat for the endangered plant Ptilimnium nodosum (Rose) Mathias (harperella) using remote sensing and field analysis—Documentation of methods and results

Ptilimnium nodosum (Rose) Mathias (harperella) is an endangered plant species found in Maryland, Virginia, and West Virginia, as well as in other locations throughout the southeastern United States. The narrow range of habitat characteristics for areas in which harperella has been found makes locating potential occurrence sites difficult and attempts at reintroduction of the plant relatively unsuccessful. Sightings of harperella have been made along the banks and in-channel bars of the Potomac River, along the Chesapeake and Ohio Canal National Historic Park, and within the Sideling Hill Wildlife Refuge near Hancock, Md. The large area covered by these sightings presents logistical challenges for repeat studies of harperella growth within the Park and in nearby areas. This study developed a geospatial method for characterizing harperella habitat through remote sensing, geospatial analysis, and field investigation. A geospatial prediction model was developed to model the habitat characteristics discussed in literature and found at harperella field observation sites in order to narrow the potential area for observation of the plant and its habitat. Analysis of historical aerial imagery was conducted within the space of the Potomac River to observe the persistence and flooding conditions of in-channel bars. The products of the geospatial prediction model and the historical aerial image analysis are a geospatial description of where harperella habitat is most likely to be found, as well as a map of in-channel bar locations and their persistence through time. From these two analyses, areas were identified that merited detailed observation. Very high resolution, unmanned aerial systems imagery was collected for 10 sites within this area in the Potomac River in June 2019. Unmanned aerial systems imagery has the potential to greatly improve detailed study of the harperella plant, as it provides the spatial resolution necessary to catalog detailed vegetation conditions (and potentially species identification). More importantly, the timing of imagery collection can be aligned carefully with the plant’s phenological patterns and local weather conditions to maximize cost-effectiveness of repeated imaging for specific areas.

Maryland, Virginia↗

USGS2013

Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska

Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6 m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes.

Alaska↗

USGS2019

Remote sensing as the foundation for high-resolution United States landscape projections – The Land Change Monitoring, assessment, and projection (LCMAP) initiative

The Land Change Monitoring, Assessment, and Projection (LCMAP) initiative uses temporally dense Landsat data and time series analyses to characterize landscape change in the United States from 1985 to present. LCMAP will be used to explain how past, present, and future landscape change affects society and natural systems. Here, we describe a modeling framework for producing high-resolution (spatial and thematic) landscape projections at a national scale, using a unique parcel-based modeling framework. The methodology was tested by modeling 11 land use scenarios and 3 climate realizations for the U.S. Great Plains. Results demonstrate 1) an ability to balance competing land-use demands from quite variable, complex scenarios, 2) urban growth that matches theoretical future patterns, 3) the value of remote sensing data sources for model parameterization and for deriving landscape parcels, and 4) a pragmatic approach that facilitates the development of high thematic- and spatial-resolution projections at a national scale.

Environmental Modelling and Software↗

USGS2025

Mapping predicted ecological states at landscape scales using remote sensing data and machine learning

Dryland ecosystems, covering 45% of the Earth's land and supporting over one-third of the global population, face significant threats from land degradation and ecological state change. Managing these ecosystems is complex, and science-based frameworks like Ecological Site Descriptions and state-and-transition models are essential tools for guiding decisions to support ecological health while maintaining stakeholder values such as grazing, wildlife, and recreation. However, alignment of these frameworks with smaller scale soil survey maps limits their applicability to broader ecological processes. Here, we extend these frameworks to larger landscapes with a machine learning approach that integrates large-scale, high-resolution vegetation data with identified ecological states from a data-driven state-and-transition model developed for a landscape-scale Ecological Site Group. A “global” model, which used combined inputs from multiple remotely sensed datasets, outperformed individual dataset models based on evaluation with independent data. Ecological state maps generated through this approach broaden the utility of state-and-transition models across Ecological Site Groups, providing a more spatially robust tool for land management at watershed and larger landscape scales. These methods, and the associated ecological state maps, can help meet critical needs for improved land condition assessments that support development of resource management plans and help identify priority areas for restoration and conservation.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS1994

Remote sensing and airborne geophysics in the assessment of natural aggregate resources

Natural aggregate made from crushed stone and deposits of sand and gravel is a vital element of the construction industry in the United States. Although natural aggregate is a high volume/low value commodity that is relatively abundant, new sources of aggregate are becoming increasingly difficult to find and develop because of rigid industry specifications, political considerations, development and transporation costs, and environmental concerns, especially in urban growth centers where much of the aggregate is used. As the demand for natural aggregate increases in response to urban growth and the repair and expansion of the national infrastructure, new sources of natural aggregate will be required. The USGS has recognized the necessity of developing the capability to assess the potential for natural aggregate sources on Federal lands; at present, no methodology exists for systematically describing and evaluating potential sources of natural aggregate. Because remote sensing and airborne geophysics can detect surface and nearsurface phenomena, these tools may useful for detecting and mapping potential sources of natural aggregate; however, before a methodology for applying these tools can be developed, it is necessary to understand the type, distribution, physical properties, and characteristics of natural aggregate deposits, as well as the problems that will be encountered in assessing their potential value. There are two primary sources of natural aggregate: (1) exposed or near-surface igneous, metamorphic, and sedimentary bedrock that can be crushed, and (2) deposits of sand and gravel that may be used directly or crushed and sized to meet specifications. In any particular area, the availability of bedrock suitable for crushing is a function of the geologic history of the area - the processes that formed, deformed, eroded and exposed the bedrock. Deposits of sand and gravel are primarily surficial deposits formed by the erosion, transportation by water and ice, and deposition of bedrock fragments. Consequently, most sand and gravel deposits are Tertiary or Quaternary in age and are most common in glaciated areas, alluvial basins, and along rivers and streams. The distribution of potential sources of natural aggregate in the United States is closely tied to physiography and the type of bedrock that occurs in an area. Using these criteria, the United States can be divided into 12 regions: western mountain ranges, alluvial basins, Columbia Plateau, Colorado Plateau and Wyoming basin, High Plains, nonglaciated central region, glaciated central region, Piedmont Blue Ridge region, glaciated northeastern and Superior uplands, Atlantic and Gulf coastal plain, Hawaiian Islands, and Alaska. Each region has similar types of natural aggregate sources within its boundary, although there may be wide variations in specific physical and chemical characteristics of the aggregates within a region. Conventional exploration for natural aggregate deposits has been largely a ground-based operation (field mapping, sampling, trenching and augering, resistivity), although aerial photos and topographic maps have been extensively used to target possible deposits for sampling and testing. Today, the exploration process also considers other factors such as the availability of the land, space and water supply for processing purposes, political and environmental factors, and distance from the market; exploration and planning cannot be separated. There are many physical properties and characteristics by which aggregate material is judged to be acceptable or unacceptable for specific applications; most of these properties and characteristics pertain only to individual aggregate particles and not to the bulk deposit. For example, properties of crushed stone aggregate particles such as thermal volume change, solubility, oxidation and hydration reactivity, and particle strength, among many others, are important consi

Open-File Report↗

USGS2011

Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods

Evapotranspiration (ET) is an important hydrological process that can be studied and estimated at multiple spatial scales ranging from a leaf to a river basin. We present a review of methods in estimating basin scale ET and its applications in understanding basin water balance dynamics. The review focuses on two aspects of ET: (i) how the basin scale water balance approach is used to estimate ET; and (ii) how ‘direct’ measurement and modelling approaches are used to estimate basin scale ET. Obviously, the basin water balance-based ET requires the availability of good precipitation and discharge data to calculate ET as a residual on longer time scales (annual) where net storage changes are assumed to be negligible. ET estimated from such a basin water balance principle is generally used for validating the performance of ET models. On the other hand, many of the direct estimation methods involve the use of remotely sensed data to estimate spatially explicit ET and use basin-wide averaging to estimate basin scale ET. The direct methods can be grouped into soil moisture balance modelling, satellite-based vegetation index methods, and methods based on satellite land surface temperature measurements that convert potential ET into actual ET using a proportionality relationship. The review also includes the use of complementary ET estimation principles for large area applications. The review identifies the need to compare and evaluate the different ET approaches using standard data sets in basins covering different hydro-climatic regions of the world.

Hydrological Processes↗

USGS2005

Supergene destruction of a hydrothermal replacement alunite deposit at Big Rock Candy Mountain, Utah: Mineralogy, spectroscopic remote sensing, stable-isotope, and argon-age evidences

Big Rock Candy Mountain is a prominent center of variegated altered volcanic rocks in west-central Utah. It consists of the eroded remnants of a hypogene alunite deposit that, at ∼21 Ma, replaced intermediate-composition lava flows. The alunite formed in steam-heated conditions above the upwelling limb of a convection cell that was one of at least six spaced at 3- to 4-km intervals around the margin of a monzonite stock. Big Rock Candy Mountain is horizontally zoned outward from an alunite core to respective kaolinite, dickite, and propylite envelopes. The altered rocks are also vertically zoned from a lower pyrite–propylite assemblage upward through assemblages successively dominated by hypogene alunite, jarosite, and hematite, to a flooded silica cap. This hydrothermal assemblage is undergoing natural destruction in a steep canyon downcut by the Sevier River in Marysvale Canyon. Integrated geological, mineralogical, spectroscopic remote sensing using AVIRIS data, Ar radiometric, and stable isotopic studies trace the hypogene origin and supergene destruction of the deposit and permit distinction of primary (hydrothermal) and secondary (weathering) processes. This destruction has led to the formation of widespread supergene gypsum in cross-cutting fractures and as surficial crusts, and to natrojarosite, that gives the mountain its buff coloration along ridges facing the canyon. A small spring, Lemonade Spring, with a pH of 2.6 and containing Ca, Mg, Si, Al, Fe, Mn, Cl, and SO 4 , also occurs near the bottom of the canyon. The 40 Ar/ 39 Ar age (21.32±0.07 Ma) of the alunite is similar to that for other replacement alunites at Marysvale. However, the age spectrum contains evidence of a 6.6-Ma thermal event that can be related to the tectonic activity responsible for the uplift that led to the downcutting of Big Rock Candy Mountain by the Sevier River. This ∼6.6 Ma event also is present in the age spectrum of supergene natrojarosite forming today, and probably dates the beginning of supergene alteration at Big Rock Candy Mountain. The δ 34 S value (11.9‰) of alunite is similar to those for replacement alunite from other deposits in the Marysvale volcanic field. The δ 34 S values of natrojarosite (0.7‰ to −1.2‰) are similar to those for aqueous sulfate in Lemonade Spring, but are larger than those in pyrite (0.4‰ to −4.7‰). The δ 34 S and δ 18 O SO 4 values of gypsum show an excellent correlation, with values ranging from 15.2‰ to −5.2‰ and 7‰ to −8.2‰, respectively. The stable-isotope data indicate that the aqueous sulfate for gypsum is a mixture derived from the dissolution of hypogene gypsum and alunite, and from the supergene oxidation of pyrite. The aqueous sulfate for the natrojarosite, however, is derived largely from the supergene oxidation of pyrite, with a minor contribution from the dissolution of alunite and gypsum. The exceptional detailed spectral mapping capabilities of AVIRIS led to the recognition of a small amount of jarosite that is probably the top of the steam-heated system that produced the primary hypogene alteration at Big Rock Candy Mountain.

Utah↗

USGS2022

What determines the effectiveness of Pinyon-Juniper clearing treatments? Evidence from the remote sensing archive and counter-factual scenarios

In the intermountain western US, expansion of Pinyon ( Pinus edulis) and Juniper ( Juniperus spp. ) woodlands (PJ) into grasslands and shrublands is a pervasive phenomenon, and an example of the global trend towards enhanced woody growth in drylands. Due to the perceived impacts of these expansions on ecosystem services related to biodiversity, hydrology, soil stability, fire prevention, and livestock forage, mechanical and chemical PJ reduction treatments have been a long-standing practice in the region. More recently, PJ reduction practices have come under enhanced public scrutiny, due to potential impacts on PJ-dependent wildlife, risk of erosion due to soil disturbance, and cost effectiveness due to variable rates of long-term success. Moreover, there is growing interest in understanding the biotic, abiotic, and management conditions under which PJ reduction treatments are effective. Here, we evaluated PJ reduction treatment outcomes leveraging large, curated databases of land treatments, new remotely sensed fractional cover time-series products, gridded climate and soils data, and analytical approaches adopted from the econometric literature. From 302 treatment events and 1569 distinct treatment polygons we found evidence that treatments reduced tree cover and largely increased shrub and perennial herbaceous cover for 10 or more years. However, treatments were also associated with increases in annual, likely non-native, herbaceous cover . Importantly, we noted treatment outcomes varied by landscape context, with some soil and geomorphic settings exhibiting consistent returns to pre-treatment conditions within 10–15 years, and others exhibiting more persistent changes in functional type composition. Despite the overall trends we observed, there was considerable unexplained variability in outcomes from treatment to treatment, highlighting the need for caution and attention to local geomorphic and biological context in planning future treatments.

Arizona, Colorado, New Mexico, Utah↗

USGS2015

Remote sensing to monitor cover crop adoption in southeastern Pennsylvania

In the Chesapeake Bay Watershed, winter cereal cover crops are often planted in rotation with summer crops to reduce the loss of nutrients and sediment from agricultural systems. Cover crops can also improve soil health, control weeds and pests, supplement forage needs, and support resilient cropping systems. In southeastern Pennsylvania, cover crops can be successfully established following corn (Zea mays L.) silage harvest and are strongly promoted for use in this niche. They are also planted following corn grain, soybean (Glycine max L.), and vegetable harvest. In Pennsylvania, the use of winter cover crops for agricultural conservation has been supported through a combination of outreach, regulation, and incentives. On-farm implementation is thought to be increasing, but the actual extent of cover crops is not well quantified. Satellite imagery can be used to map green winter cover crop vegetation on agricultural fields and, when integrated with additional remote sensing data products, can be used to evaluate wintertime vegetative groundcover following specific summer crops. This study used Landsat and SPOT (System Probatoire d’ Observation de la Terre) satellite imagery, in combination with the USDA National Agricultural Statistics Service Cropland Data Layer, to evaluate the extent and amount of green wintertime vegetation on agricultural fields in four Pennsylvania counties (Berks, Lebanon, Lancaster, and York) from 2010 to 2013. In December of 2010, a windshield survey was conducted to collect baseline data on winter cover crop implementation, with particular focus on identifying corn harvested for silage (expected earlier harvest date and lower levels of crop residue), versus for grain (expected later harvest date and higher levels of crop residue). Satellite spectral indices were successfully used to detect both the amount of green vegetative groundcover and the amount of crop residue on the surveyed fields. Analysis of wintertime satellite imagery showed consistent increases in vegetative groundcover over the four-year study period and determined that trends did not result from annual weather variability, indicating that farmers are increasing adoption of practices such as cover cropping that promote wintertime vegetation. Between 2010 and 2013, the occurrence of wintertime vegetation on agricultural fields increased from 36% to 67% of corn fields in Berks County, from 53% to 75% in Lancaster County, from 42% to 65% in Lebanon County, and from 26% to 52% in York County. Apparently, efforts to promote cover crop use in the Chesapeake Bay Watershed have coincided with a rapid increase in the occurrence of wintertime vegetation following corn harvest in southeastern Pennsylvania. However, despite these increases, between 25% and 48% of corn fields remained without substantial green vegetation over the wintertime, indicating further opportunity for cover crop adoption.

Pennsylvania↗

USGS2006

Remote sensing and geophysical investigations of glacial buried valleys in northeastern Kansas

Aquifers found in glacial buried valleys are a major source of good-quality ground water in northeastern Kansas. The extent and character of many of these deposits are not precisely known, so a detailed study of the buried valleys was undertaken. Test drilling, Landsat imagery, shallow-earth temperature measurements, seismic refraction, surface electrical resistivity, and gravity data were used to evaluate two sites in Nemaha and Jefferson Counties. Tonal patterns on springtime Landsat imagery and winter/summer anomalies in shallow-earth temperatures were quick and inexpensive methods for locating some glacial buried aquifers and suggested areas for more intensive field studies. Reversed seismic refraction and resistivity surveys were generally reliable indicators of the presence or absence of glacial buried valleys, with most depth determinations being within 25% of test-drilling results. The effectiveness of expensive test-hole drilling was greatly increased by integrating remote sensing, shallow-earth temperature, seismic, and resistivity techniques in the two buried valley test areas. A gravity profile allowed precise definition of the extent of one of the channels after the other techniques had been used for general information.

Kansas↗

USGS2024

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Sardon catchment↗

USGS1977

Application of remotely sensed land-use information to improve estimates of streamflow characteristics

Land-use data derived from high-altitude photography and satellite imagery are presented for 49 basins in Delaware, and eastern Maryland and Virginia. Based on 1:100,000 scale maps from high-altitude photography, basin land cover was extracted at the generalized Level I and the more detailed Level II classification categories. Level I land-use data summaries were prepared for 46 of the basins using the 1:250,000 scale maps derived from Landsat imagery. Land cover in the basins ranged from 93.9 percent urban at Little Falls Branch near Bethesda, Maryland, to 96.2 percent agricultural at Morgan Creek near Kennedyville, Maryland. Applying multiple regression techniques to a network of gaging stations monitoring runoff from 39 of the basins, it was demonstrated that land-use data from high-altitude photography provides an effective means of significantly improving estimates of streamflow. Forty streamflow-characteristics equations incorporating remotely sensed land-use information, were compared with a control set of equations using map derived land cover. (Woodard-USGS)

Open-File Report↗

USGS2020

Combining ash analyses with remote sensing to identify juvenile magma involvement and fragmentation mechanisms during the 2018/19 small eruption of Peteroa volcano (Southern Andes)

The Planchón Peteroa Volcanic Complex (PPVC) is located on the border of Chile and Argentina, and is one of the most active volcanic systems in the Andes. Holocene activity has included magma-water interaction with an evolving series of crater lakes, mainly sourced from Peteroa volcano. This study examines data from the 2018/19 eruption, together with the volcanic history of the PPVC, to elucidate the complex interplay between magmatic activity and summit water and ice. From February 2016 to mid-2019, three seismic swarms occurred in the PPVC, preceding the explosive eruption from September 2018 to April 2019. The activity originated from a small vent nested within the easternmost crater, the most active portion of the complex (Peteroa). The explosions interacted with a crater lake, producing ash plumes up to 2 km above the crater and building a small tephra cone. To investigate the eruption mechanisms, we performed remote sensing analysis of plume dispersal, thermal anomalies and ground deformation, and characterized the volcanic products, including grain size, componentry, morphology, internal textures, composition and mineralogy. Our results suggest that the precursory seismicity beginning in 2016 was related to the intrusion of a new magma batch that reached the surface during the 2018/19 eruption. The eruption was also preceded by thermal anomalies, geomorphic changes and increased hydrothermal activity at the surface, though without any ground deformation recognized through radar interferometry (InSAR). The eruption initially produced predominantly recycled ash (phreatic activity), then evolved to increasing proportions of juvenile magma (phreatomagmatic) by April 2019. The juvenile clasts had a trachyandesite composition (~59 wt% SiO 2 ), with vesicular and dense scoria containing plagioclase and pyroxene. The ash surfaces show external quenching cracks and step fractures consistent with phreatomagmatic fragmentation within the active crater lake. Textural characteristics also point to a slowly ascending batch of magma that was relatively viscous by the time it interacted with water in the crater lake. Notably, these juvenile particles are distinctive from the pre-2018 products. Ash erupted from 2010/11 did not contain recognizable juvenile material, and is inferred to have been a mainly phreatic eruption. Our findings suggest that the interplay between phreatic and phreatomagmatic eruptions fed by small magma batches intruding at shallow levels characterize much of the eruptive behavior of the PPVC during the last three decades. Multi-parametric assessment is a powerful tool to discriminate between phreatic and phreatomagmatic eruptions.

Southern Andes↗

USGS1996

Using remote sensing and GIS techniques to estimate discharge and recharge fluxes for the Death Valley regional groundwater flow system, USA

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were used to calculate discharge volumes for these area. An empirical method of groundwater recharge estimation was modified to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Application of geographic information systems in h↗