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At least 1,027 records · Page 57Linked to original sources
USGS2017

HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios

The Hazard Exposure Reporting and Analytics (HERA) dynamic web application was created to provide a platform that makes research on community exposure to coastal-flooding hazards influenced by sea level rise accessible to planners, decision makers, and the public in a manner that is both easy to use and easily accessible. HERA allows users to (a) choose flood-hazard scenarios based on sea level rise and storm assumptions, (b) appreciate the modeling uncertainty behind a chosen hazard zone, (c) select one or several communities to examine exposure, (d) select the category of population or societal asset, and (e) choose how to look at results. The application is designed to highlight comparisons between (a) varying levels of sea level rise and coastal storms, (b) communities, (c) societal asset categories, and (d) spatial scales. Through a combination of spatial and graphical visualizations, HERA aims to help individuals and organizations to craft more informed mitigation and adaptation strategies for climate-driven coastal hazards. This paper summarizes the technologies used to maximize the user experience, in terms of interface design, visualization approaches, and data processing.

Computers & Geosciences↗
USGS2020

Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers

Quantifying suspended-sediment transport is critical for a variety of disciplines related to the management of water resources. However, the number of gauging stations and monitoring networks in most rivers around the world is insufficient to improve understanding of river dynamics and support water resource management decisions. This is mainly due to the high operational costs and intensive labor involved in traditional sediment measurement techniques, especially in sand bed rivers where coarse material varies spatially in the river cross section. Recently, the acoustic surrogate method has received attention as a potentially accurate surrogate technology for estimating suspended-sediment concentrations. In addition, the acoustic surrogate method, through use of acoustic Doppler current profilers (ADCPs), has the advantage of being able to simultaneously measure the flow velocity field and cross-sectional area when moving-boat measurements are performed. In spite of the important advances made in the implementation of this technique, there are no widely-available, free tools for processing the ADCP acoustic signal cross section measurements which include options to extrapolate velocity and sediment in unmeasured ADCP zones and develop calibrations with physical samples. This paper presents a new software called Acoustic Sediment Estimation Toolbox (ASET), which enables the user to develop a calibration between the acoustic signal collected with a down-looking Teledyne RD Instruments ADCP and sediment concentrations determined using traditional sediment sampling techniques. Moreover, ASET software uses dynamic ADCP measurements to estimate the total suspended-sediment transport through a river cross section. The theoretical framework and data processing routines applied by each module in ASET are presented. Finally, a comparison is made between the results obtained by ASET and by traditional methodologies for computing suspended-sediment transport in a large river system (Paraná River, Argentina).

Computers & Geosciences↗
USGS2015

Sulfate and sulfide sulfur isotopes (δ34S and δ33S) measured by solution and laser ablation MC-ICP-MS: An enhanced approach using external correction

Isotope ratio measurements using a multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS) commonly use standard-sample bracketing with a single isotope standard for mass bias correction for elements with narrow-range isotope systems measured by MC-ICP-MS, e.g. Cu, Fe, Zn, and Hg. However, sulfur (S) isotopic composition (δ 34 S) in nature can range from at least − 40 to + 40‰, potentially exceeding the ability of standard-sample bracketing using a single sulfur isotope standard to accurately correct for mass bias. Isotopic fractionation via solution and laser ablation introduction was determined during sulfate sulfur (S sulfate ) isotope measurements. An external isotope calibration curve was constructed using in-house and National Institute of Standards and Technology (NIST) S sulfate isotope reference materials (RM) in an attempt to correct for the difference. The ability of external isotope correction for S sulfate isotope measurements was evaluated by analyzing NIST and United States Geological Survey (USGS) S sulfate isotope reference materials as unknowns. Differences in δ 34 S sulfate between standard-sample bracketing and standard-sample bracketing with external isotope correction for sulfate samples ranged from 0.72‰ to 2.35‰ over a δ 34 S range of 1.40‰ to 21.17‰. No isotopic differences were observed when analyzing S sulfide reference materials over a δ 34 S sulfide range of − 32.1‰ to 17.3‰ and a δ 33 S range of − 16.5‰ to 8.9‰ via laser ablation (LA)-MC-ICP-MS. Here, we identify a possible plasma induced fractionation for S sulfate and describe a new method using external isotope calibration corrections using solution and LA-MC-ICP-MS.

Chemical Geology↗
USGS2021

Terrestrial ecological risk analysis via dietary exposure at uranium mine sites in the Grand Canyon watershed (Arizona, USA)

The U.S. Department of the Interior recently included uranium (U) on a list of mineral commodities that are considered critical to economic and national security. The uses of U for commercial and residential energy production, defense applications, medical device technologies, and energy generation for space vehicles and satellites are known, but the environmental impacts of uranium extraction are not always well quantified. We conducted a screening-level ecological risk analysis based on exposure to mining-related elements via diets and incidental soil ingestion for terrestrial biota to provide context to chemical characterization and exposures at breccia pipe U mines in northern Arizona. Relative risks, calculated as hazard quotients (HQs), were generally low for all biological receptor models. Our models screened for risk to omnivores and insectivores (HQs>1) but not herbivores and carnivores. Uranium was not the driver of ecological risk; arsenic, cadmium, copper, and zinc were of concern for biota consuming ground-dwelling invertebrates. Invertebrate species composition should be considered when applying these models to other mining locations or future sampling at the breccia pipe mine sites. Dietary concentration thresholds (DCTs) were also calculated to understand food concentrations that may lead to ecological risk. The DCTs indicated that critical concentrations were not approached in our model scenarios, as evident in the very low HQs for most models. The DCTs may be used by natural resource and land managers as well as mine operators to screen or monitor for potential risk to terrestrial receptors as mine sites are developed and remediated in the future.

Arizona↗
USGS2024

Determination and prediction of micro scale rare earth element geochemical associations in mine drainage treatment wastes

Acid mine drainage (AMD) has been proposed as a novel source of rare earth elements (REE), a group of elements that includes critical metals for clean energy and modern technologies. REE are sequestered in the Fe–Al–Mn-rich precipitates produced during the treatment of AMD. These AMD solids are typically managed as waste but could be a REE source. Here, results from AMD solids characterization and geochemical modeling are presented to determine the minerals/solid phases that are enriched in REE and identify the mechanism(s) of REE attenuation. AMD solids collected from limestone-based AMD treatment systems were subjected to sequential extraction and synchrotron microprobe analyses to characterize the binding nature of the REE. The results of these analyses indicated REEs were mainly associated with Al or Mn phases. Only selected REE (Gd, Dy) were associated with Fe phases, which were less abundant than Al and Mn phases in analyzed samples. The sequential extractions demonstrated that acidic and/or reducing extractions effectively mobilize REE from the AMD solids evaluated. The observed element associations in solids are consistent with geochemical model results that indicate dissolved REE can be effectively attenuated by adsorption on freshly precipitated Fe, Al, and Mn oxides/hydroxides. The model, which simulates dissolution of CaCO 3 and the precipitation of Fe, Al, and Mn oxides with increased pH, accurately predicts the pH dependent accumulation of dissolved REE with Al, Mn, and Fe oxides/hydroxides in the studied AMD treatment systems. The methods and results presented here can be used to identify conditions favorable for accumulation of REE-enriched AMD solids and possible passive or active treatment(s) to extract REE from AMD. This information can be used to design AMD treatment systems for the recovery of REE and is an opportunity to transform the challenges of addressing polluted mine drainage into an environmental and economic asset.

Pennsylvania↗
USGS2009

Integrated treatment process using a natural Wyoming clinoptilolite for remediating produced waters from coalbed natural gas operations

Coalbed natural gas (CBNG) development in western U.S. states has resulted in an increase in an essential energy resource, but has also resulted in environmental impacts and additional regulatory needs. A concern associated with CBNG development relates to the production of the copious quantities of potentially saline-sodic groundwater required to recover the natural gas, hereafter referred to as CBNG water. Management of CBNG water is a major environmental challenge because of its quantity and quality. In this study, a locally available Na-rich natural zeolite (clinoptilolite) from Wyoming (WY) was examined for its potential to treat CBNG water to remove Na+ and lower the sodium adsorption ratio (SAR, mmol1/2 L- 1/2). The zeolite material was Ca-modified before being used in column experiments. Column breakthrough studies indicated that a metric tonne (1000??kg) of Ca-WY-zeolite could be used to treat 60,000??L of CBNG water in order to lower SAR of the CBNG water from 30 to an acceptable level of 10??mmol1/2 L- 1/2. An integrated treatment process using Na-WY-zeolite for alternately treating hard water and CBNG water was also examined for its potential to treat problematic waters in the region. Based on the results of this study, use of WY-zeolite appears to be a cost-effective water treatment technology for maximizing the beneficial use of poor-quality CBNG water. Ongoing studies are evaluating water treatment techniques involving infiltration ponds lined with zeolite. ?? 2008 Elsevier B.V. All rights reserved.

Applied Clay Science↗
USGS2013

Development of web-based organic petrology photomicrograph atlases and internet resources for professionals and students

With advances in web applications, organic petrography and other related disciplines are in need of updated online resources and educational tools to aid professionals and students in the identification and interpretation of macerals. The U.S. Geological Survey (USGS) Organic Petrology Laboratory along with USGS Eastern Energy Resources Science Center Information Technology staff have developed five web atlases containing images of organic matter in geologic materials: 1. an American Society for Testing and Materials (ASTM) Atlas, 2. an Organic Petrology Taxonomy for International Classification (OPTIC) of Coal Macerals Atlas, 3. an Interactive Gulf Coast Photomicrograph Web Atlas (I-Map), 4. an Organic Material in Shales Atlas (Shale), and 5. an interactive Blue/White/Ultraviolet (UV) Light Atlas (Light). Each web atlas contains images of macerals with associated sample and petrographic data collected by the USGS. These webpages will provide means to preserve and circulate petrographic data collected by the USGS for coal and shale samples from all over the world.

International Journal of Coal Geology↗
USGS2013

Coal resources, reserves and peak coal production in the United States

In spite of its large endowment of coal resources, recent studies have indicated that United States coal production is destined to reach a maximum and begin an irreversible decline sometime during the middle of the current century. However, studies and assessments illustrating coal reserve data essential for making accurate forecasts of United States coal production have not been compiled on a national basis. As a result, there is a great deal of uncertainty in the accuracy of the production forecasts. A very large percentage of the coal mined in the United States comes from a few large-scale mines (mega-mines) in the Powder River Basin of Wyoming and Montana. Reported reserves at these mines do not account for future potential reserves or for future development of technology that may make coal classified currently as resources into reserves in the future. In order to maintain United States coal production at or near current levels for an extended period of time, existing mines will eventually have to increase their recoverable reserves and/or new large-scale mines will have to be opened elsewhere. Accordingly, in order to facilitate energy planning for the United States, this paper suggests that probabilistic assessments of the remaining coal reserves in the country would improve long range forecasts of coal production. As it is in United States coal assessment projects currently being conducted, a major priority of probabilistic assessments would be to identify the numbers and sizes of remaining large blocks of coal capable of supporting large-scale mining operations for extended periods of time and to conduct economic evaluations of those resources.

International Journal of Coal Geology↗
USGS2017

Enhanced coal-dependent methanogenesis coupled with algal biofuels: Potential water recycle and carbon capture

Many coal beds contain microbial communities that can convert coal to natural gas (coalbed methane). Native microorganisms were obtained from Powder River Basin (PRB) coal seams with a diffusive microbial sampler placed downhole and used as an inoculum for enrichments with different nutrients to investigate microbially-enhanced coalbed methane production (MECoM). Coal-dependent methanogenesis more than doubled when yeast extract (YE) and several less complex components (proteins and amino acids) were added to the laboratory microcosms. Stimulated coal-dependent methanogenesis with peptone was 86% of that with YE while glutamate-stimulated activity was 65% of that with YE, and a vitamin mix had only 33% of the YE stimulated activity. For field application of MECoM, there is interest in identifying cost-effective alternatives to YE and other expensive nutrients. In laboratory studies, adding algal extract (AE) with lipids removed stimulated coal-dependent methanogenesis and the activity was 60% of that with YE at 27 d and almost 90% of YE activity at 1406 d. Analysis of British Thermal Unit (BTU) content of coal (a measure of potential energy yield) from long-term incubations indicated > 99.5% of BTU content remained after coalbed methane (CBM) stimulation with either AE or YE. Thus, the coal resource remains largely unchanged following stimulated microbial methane production. Algal CBM stimulation could lead to technologies that utilize coupled biological systems (photosynthesis and methane production) that sustainably enhance CBM production and generate algal biofuels while also sequestering carbon dioxide (CO 2 ).

International Journal of Coal Geology↗
USGS2022

Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA

Rare earth elements and yttrium (REYs) are critical elements and valuable commodities due to their limited availability and high demand in a wide range of applications and especially in high-technology products. The increased demand and geopolitical pressures motivate the search for alternative sources of REYs, and coal, coal waste, and coal ash are considered as new sources for these critical elements. This research evaluates the REY potential of coals from Indiana (USA). However, although coal data revealed REY potential, it suffered from sparse samples with complete REY measurements. Therefore, we explore the applicability of machine learning (ML) models and data augmentation techniques to demonstrate their applicability to evaluate REY potential in Indiana, and other areas in coal basins, using selected coal parameters (Al2O3, Fe2O3, C, Ash, S, P, Mo, Zn, and As contents) as covariates (indicators). Due to the relatively small sample size with complete REY data in the Indiana Coal Database, two data augmentation techniques (Random Over-Sampling Examples and Synthetic Minority Over-Sampling Technique) were used. Four machine learning algorithms (linear discriminate analysis, support vector machine, random forest, and artificial neural networks) were applied for modeling REY potential as a classification problem. The results show that application of Synthetic Minority Over-Sampling Technique prior to development of the support vector machine (SVM) models generated the best REY classification with an accuracy of 95%. The encouraging results based on Indiana coal data may suggest that a similar approach can be used for other coal basins for screening the locations with REY potential. Those locations then can be targeted for more detailed geochemical surveys to identify most promising areas and evaluate overall REY resources.

Indiana↗
USGS2023

Scanning electron microscopic evaluation of broad ion beam milling effects to sedimentary organic matter: Sputter-induced artifacts or naturally occurring porosity?

Research examining organic-matter hosted porosity has significantly increased during the last decade due to greater focus on understanding hydrocarbon migration and storage in source-rock reservoirs, and technological advances in scanning electron microscopy (SEM) capabilities. The examination of nanometer-scale organic-matter hosted porosity by SEM requires the preparation of exceptionally flat geologic samples beyond the abilities of traditional mechanical polishing, which can deform or otherwise obscure organic surfaces. To meet this demand, broad ion beam (BIB) milling was introduced as a sample preparation technique for SEM petrographic analysis of geologic samples. As with any sample preparation technique, there can be unintended consequences. In this study, we examined the development of nanometer-scale sputter-induced voids caused by BIB milling of thermoset plastic binder material [poly(methyl methacrylate), PMMA] used for the mounting of geologic samples, and artifact sputter-induced voids in the organic matter of Green River Formation and Kimmeridge Clay Formation source rocks. Development of artifact sputter-induced voids was evaluated in relation to variations in the slope of the sample examination surface (0.0–4.9% slope), effectively varying the angle of ion incidence. The results indicate that only minor variations in the angle of ion incidence can generate sputter-induced voids in both PMMA (10.0–386.2 nm diameter sputter-induced voids) and sample sedimentary organic matter (solid bitumen; 12.2–103.6 nm diameter sputter-induced voids). Overall, average artifact pore diameters increased with increasing ion incidence angle within PMMA. Although sputter-induced voids within solid bitumen in the Green River Formation sample were only found in limited extent, the size of these void artifacts falls within the same size range as naturally occurring meso-macroporosity. That is, the pore-like artifacts could easily be misconstrued as naturally developed organic porosity, which is a major concern for SEM-based porosity evaluation methods. This study describes the factors that contribute to the creation of artifact sputter-induced voids, their distinguishing characteristics, and best practices for avoiding the creation of ion-induced artifacts.

International Journal of Coal Geology↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

Structure and morphology of chars and activated carbons obtained from thermal treatment of coal and biomass origin materials, including their wastes: Results from the ICCP Microscopy of Carbon Materials Working Group

This paper describes the evaluation of petrographic textures in char and activated carbon derived from coal, coal by-products and biomass, formed during carbonization and activation processes. This work represents the results of interlaboratory exercises from 2016 to 2022 of the Microscopy of Carbon Materials Working Group in Commission III of the International Committee for Coal and Organic Petrology. The interlaboratory exercises were run on photomicrograph samples. For textural characterization of carbon materials, the existing American Society for Testing and Materials (ASTM) classification system for metallurgical coke was applied. Morphological differences were evaluated in 29 carbon material types, including 22 char samples, and 7 activated carbon (AC) samples obtained experimentally using conventional direct/indirect and microwave heating technologies. This approach gives an extended view on the identification of microporous carbons, and how a certain heat treatment develops a certain optical texture and structure in a raw material. The requested evaluation of carbon materials was related to their porosity, origin, extent, and characteristics, which are particular to each carbon material type. Because carbon matrices can form a wide range of optical textures during heat treatment it is important to demonstrate which carbon occurrences will have a crucial role in industrial applications dominated by adsorption phenomena. The interlaboratory exercises included 17 participants from 14 laboratories. Four sets of digital black and white and colour photomicrographs were distributed, which in total comprised 184 fields of different types of carbon material. The results were evaluated based on four levels: (i) optical texture (isotropic/anisotropic), (ii) optical type and size (punctiform, mosaic, fiber, ribbon, domain), iii) morphology (porous, non-porous/massive), and (iv) particle origin (precursor type). The statistical method applied to evaluate the results was based on “raw agreement indices”. Comparative analyses of the average values of the level of overall agreement showed homogeneity in the results, the mean value was 89%, with a minimum value of 87% and a maximum value of 91% for those who participated in at least three out of four exercises.

International Journal of Coal Geology↗
USGS2026

Genetic biocontrol strategy considerations for mosquito control in the Pacific Island Countries and Territories

Mosquito-borne diseases pose an existential threat to the health, economies, and unique ecosystems of Pacific Island Countries and Territories (PICTs). The remoteness of these islands, combined with the presence of highly competent mosquito vectors, complicates disease surveillance and vector control efforts. In response, the PICTs have become a focal point for the development and application of Genetic BioControl (GBC) technologies designed to break vector-borne disease transmission cycles. However, the application of GBC tools in this region warrants careful consideration of its unique history, including a legacy of colonialism, and challenges associated with logistic hurdles. Through meaningful community engagement and authentic collaborations, drawing from local knowledge, and building local capacity, the sustainable, efficient, and effective deployment of GBC tools may be achieved.

Current Opinion in Insect Science↗
USGS2022

New frontiers in bird migration research

Bird migrations are impressive behavioral phenomena, representing complex spatiotemporal strategies to balance costs of living while maximizing fitness. The field of bird migration research has made great strides over the past decades, yet fundamental gaps remain. Technologies have sparked a transformation in the study of bird migration research by revealing remarkable insights into the underlying behavioral, cognitive, physiological and evolutionary mechanisms of these diverse journeys. Here, we aim to encourage broad discussions and promote future studies by highlighting research fields that are characterized by major knowledge gaps or conflicting evidence, namely the fields of navigation, social learning, individual development, energetics and conservation. We approach each topic by summarizing the current state of knowledge and provide a future outlook of ideas and state-of-the-art methods to further advance the field. Integrating knowledge across these disciplines will allow us to understand the adaptive abilities of different species and to develop effective conservation strategies in a rapidly changing world.

Current Biology↗
USGS2006

Aquifer composition and the tendency toward scale-deposit formation during reverse osmosis desalination - Examples from saline ground water in New Mexico, USA

Desalination is expected to make a substantial contribution to water supply in the United States by 2020. Currently, reverse osmosis is one of the most cost effective and widely used desalination technologies. The tendency to form scale deposits during reverse osmosis is an important factor in determining the suitability of input waters for use in desalination. The tendency toward scale formation of samples of saline ground water from selected geologic units in New Mexico was assessed using simulated evaporation. All saline water samples showed a strong tendency to form CaCO3 scale deposits. Saline ground water samples from the Yeso Formation and the San Andres Limestone showed relatively stronger tendencies to form CaSO4 2H2O scale deposits and relatively weaker tendencies to form SiO2(a) scale deposits than saline ground water samples from the Rio Grande alluvium. Tendencies toward scale formation in saline ground water samples from the Dockum Group were highly variable. The tendencies toward scale formation of saline waters from the Yeso Formation, San Andres Limestone, and Rio Grande alluvium appear to correlate with the mineralogical composition of the geologic units, suggesting that scale-forming tendencies are governed by aquifer composition and water-rock interaction. ?? 2006 Elsevier B.V. All rights reserved.

Desalination↗
USGS2017

Gene transcription patterns in response to low level petroleum contaminants in Mytilus trossulus from field sites and harbors in southcentral Alaska

The 1989 Exxon Valdez oil spill damaged a wide range of natural resources, including intertidal communities, and post-spill studies demonstrated acute and chronic exposure and injury to an array of species. Standard toxicological methods to evaluate petroleum contaminants have assessed tissue burdens, with fewer assays providing indicators of health or physiology, particularly when contaminant levels are low and chronic. Marine mussels are a ubiquitous and crucial component of the nearshore environment, and new genomic technologies exist to quantify molecular responses of individual mussels to stimuli, including exposure to polycyclic aromatic hydrocarbons (PAHs). We used gene-based assays of exposure and physiological function to assess chronic oil contamination using the Pacific blue mussel, Mytilus trossulus . We developed a diagnostic gene transcription panel to investigate exposure to PAHs and other contaminants and its effects on mussel physiology and health. During 2012–2015, we analyzed mussels from five field sites in western Prince William Sound, Alaska, with varying oil histories from the 1989 Exxon Valdez oil spill, and from three boat harbors in the area. Gene transcription patterns of mussels from harbors were consistent with elevated exposure to PAHs or other contaminants, whereas transcription patterns of mussels sampled from shorelines in areas affected by the oil spill indicated no PAH exposure.

Alaska↗
USGS2015

Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review

The study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data. In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT.

Earth-Science Reviews↗