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At least 973 records · Page 54Linked to original sources

USGS2007

Design procedure for hooded surface oxygen absorption systems

A design procedure addressing effluent total dissolved gas pressure limits along with standard performance indicators such as oxygen absorption efficiency (kg absorbed/kg applied), and transfer efficiency (kg/kW.h), is presented for surface agitation equipment operating in an oxygen-enriched atmosphere. Application of this contactor type in closed culture systems is attractive given its insensitivity to biological fouling and ability to operate without the need for a significant hydraulic gradient. Performance algorithms were developed through application of chemical reactor theory, Henry's Law and the Ideal Gas Law. In the analysis, gas and liquid phases were treated as being homogeneous. The design steps presented are unique in that required mass transfer coefficients (K L a), operating pressures (CP), and oxygen feed rates (G/L) are calculated for target changes in both dissolved oxygen and nitrogen without the use of iterative numerical procedures. A second calculation sequence establishes the sensitivity of system performance to changes in G/L when CP and K L a are known.

Journal of the World Aquaculture Society↗

USGS2007

A sediment resuspension and water quality model of Lake Okeechobee

ABSTRACT: The influence of sediment resuspension on the water quality of shallow lakes is well documented. However, a search of the literature reveals no deterministic mass-balance eutrophication models that explicitly include resuspension. We modified the Lake Okeechobee water quality model - which uses the Water Analysis Simulation Package (WASP) to simulate algal dynamics and phosphorus, nitrogen, and oxygen cycles - to include inorganic suspend. ed solids and algorithms that: (1) define changes in depth with changes in volume; (2) compute sediment resuspension based on bottom shear stress; (3) compute partition coefficients for ammonia and ortho-phosphorus to solids; and (4) relate light attenuation to solids concentrations. The model calibration and validation were successful with the exception of dissolved inorganic nitrogen species which did not correspond well to observed data in the validation phase. This could be attributed to an inaccurate formulation of algal nitrogen preference and/or the absence of nitrogen fixation in the model. The model correctly predicted that the lake is light-limited from resuspended solids, and algae are primarily nitrogen limited. The model simulation suggested that biological fluxes greatly exceed external loads of dissolved nutrients; and sediment-water interactions of organic nitrogen and phosphorus far exceed external loads. A sensitivity analysis demonstrated that parameters affecting resuspension, settling, sediment nutrient and solids concentrations, mineralization, algal productivity, and algal stoichiometry are factors requiring further study to improve our understanding of the Lake Okeechobee ecosystem.

Journal of the American Water Resources Associatio↗

USGS2007

A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers

ABSTRACT: In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.

Journal of the American Water Resources Associatio↗

USGS2007

Evaluation of Light Detection and Ranging (LIDAR) for measuring river corridor topography

LIDAR is relatively new in the commercial market for remote sensing of topography and it is difficult to find objective reporting on the accuracy of LIDAR measurements in an applied context. Accuracy specifications for LIDAR data in published evaluations range from 1 to 2 m root mean square error (RMSEx,y) and 15 to 20 cm RMSEz. Most of these estimates are based on measurements over relatively flat, homogeneous terrain. This study evaluated the accuracy of one LIDAR data set over a range of terrain types in a western river corridor. Elevation errors based on measurements over all terrain types were larger (RMSEz equals 43 cm) than values typically reported. This result is largely attributable to horizontal positioning limitations (1 to 2 m RMSEx,y) in areas with variable terrain and large topographic relief. Cross-sectional profiles indicated algorithms that were effective for removing vegetation in relatively flat terrain were less effective near the active channel where dense vegetation was found in a narrow band along a low terrace. LIDAR provides relatively accurate data at densities (50,000 to 100,000 points per km 2 ) not feasible with other survey technologies. Other options for projects requiring higher accuracy include low-altitude aerial photography and intensive ground surveying.

Journal of the American Water Resources Associatio↗

USGS2006

Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin

The ability to apply a hydrologic model to large numbers of basins for forecasting purposes requires a quick and effective calibration strategy. This paper presents a step wise, multiple objective, automated procedure for hydrologic model calibration. This procedure includes the sequential calibration of a model's simulation of solar radiation (SR), potential evapotranspiration (PET), water balance, and daily runoff. The procedure uses the Shuffled Complex Evolution global search algorithm to calibrate the U.S. Geological Survey's Precipitation Runoff Modeling System in the Yampa River basin of Colorado. This process assures that intermediate states of the model (SR and PET on a monthly mean basis), as well as the water balance and components of the daily hydrograph are simulated, consistently with measured values.

Journal of the American Water Resources Associatio↗

USGS2011

Spatial capture-recapture models for search-encounter data

1. Spatial capture–recapture models make use of auxiliary data on capture location to provide density estimates for animal populations. Previously, models have been developed primarily for fixed trap arrays which define the observable locations of individuals by a set of discrete points. 2. Here, we develop a class of models for 'search-encounter' data, i.e. for detections of recognizable individuals in continuous space, not restricted to trap locations. In our hierarchical model, detection probability is related to the average distance between individual location and the survey path. The locations are allowed to change over time owing to movements of individuals, and individual locations are related formally by a model describing individual activity or home range centre which is itself regarded as a latent variable in the model. We provide a Bayesian analysis of the model in WinBUGS, and develop a custom MCMC algorithm in the R language. 3. The model is applied to simulated data and to territory mapping data for the Willow Tit from the Swiss Breeding Bird Survey MHB. While the observed density was 15 territories per nominal 1 km 2 plot of unknown effective sample area, the model produced a density estimate of 21∙12 territories per square km (95% posterior interval: 17–26). 4. Spatial capture–recapture models are relevant to virtually all animal population studies that seek to estimate population size or density, yet existing models have been proposed mainly for conventional sampling using arrays of traps. Our model for search-encounter data, where the spatial pattern of searching can be arbitrary and may change over occasions, greatly expands the scope and utility of spatial capture–recapture models.

Methods in Ecology and Evolution↗

USGS2016

Temperature is better than precipitation as a predictor of plant community assembly across a dryland region

Question How closely do plant communities track climate? Research suggests that plant species converge toward similar environmental tolerances relative to the environments that they experience. Whether these patterns apply to severe environments or scale up to plant community-level patterns of relative climatic tolerances is poorly understood. Using estimates of species' climatic tolerances acquired from occurrence records, we determined the contributions of individual species' climatic niche breadths and environmental filtering to the relationships between community-average climatic tolerances and the local climates experienced by those communities. Location Southwestern United States drylands. Methods Interspecific variation in niche breadth was assessed as a function of species' climatic optima (median climatic niche value). The relationships between climatic optima and tolerances were used as null expectations for the relationship between abundance-weighted mean climatic tolerances of communities and the local climate of that community. Deviations from this null expectation indicate that species with greater or lesser climatic tolerances are favoured relative to co-occurring species. The intensity of environmental filtering was estimated by comparing the range of climatic tolerances within each community to a null distribution generated from a random assembly algorithm. Results The temperature niches of species were consistently symmetrical and of similar breadths, regardless of their temperature optima. In contrast, precipitation niches were skewed toward wetter conditions, and niche breadth increased with increasing precipitation optima. At the community level, relationships with climate were much stronger for temperature than for precipitation. Furthermore, cold and heat were stronger assembly filters than drought or precipitation, with the intensity of environmental filtering increasing at both ends of climatic gradients. Community-average climatic tolerances did deviate significantly from null expectations, indicating that species with higher or lower relative climatic tolerances were favoured under certain conditions. Conclusions Despite strong water limitation of plant performance in dryland ecosystems, communities tracked variation in temperature much more closely, intimating strong responses to anticipated temperature increases. Furthermore, abundance distributions were biased toward species with higher or lower relative climatic tolerances under different climatic conditions, but predictably so, indicating the need for assembly models that include processes other than simple environmental filtering.

Journal of Vegetation Science↗

USGS2016

Prestoration: Using species in restoration that will persist now and into the future

Climate change presents new challenges for selecting species for restoration. If migration fails to keep pace with climate change, as models predict, the most suitable sources for restoration may not occur locally at all. To address this issue we propose a strategy of “prestoration”: utilizing species in restoration for which a site represents suitable habitat now and into the future. Using the Colorado Plateau, USA as a case study, we assess the ability of grass species currently used regionally in restoration to persist into the future using projections of ecological niche models (or climate envelope models) across a suite of climate change scenarios. We then present a technique for identifying new species that best compensate for future losses of suitable habitat by current target species. We found that the current suite of species, selected by a group of experts, is predicted to perform reasonably well in the short-term, but that losses of prestorable habitat by mid-century would approach 40%. Using an algorithm to identify additional species, we found that fewer than ten species could compensate for nearly all of the losses incurred by the current target species. This case study highlights the utility of integrating ecological niche modeling and future climate forecasts to predict the utility of species in restoring under climate change across a wide range of spatial and temporal scales.

Arizona, Colorado, New Mexico, Utah↗

USGS2017

Northern tamarisk beetle (Diorhabda carinulata) and tamarisk (Tamarix spp.) interactions in the Colorado River basin

Northern tamarisk beetles (Diorhabda carinulata) were released in the Upper Colorado River Basin in the United States in 2004–2007 to defoliate introduced tamarisk shrubs (Tamarix spp.) in the region’s riparian zones. The primary purpose was to control the invasive shrub and reduce evapotranspiration (ET) by tamarisk in an attempt to increase stream flows. We evaluated beetle–tamarisk interactions with MODIS and Landsat imagery on 13 river systems, with vegetation indices used as indicators of the extent of defoliation and ET. Beetles are widespread and exhibit a pattern of colonize–defoliate–emigrate, so that riparian zones contain a mosaic of completely defoliated, partially defoliated, and refoliated tamarisk stands. Based on satellite data and ET algorithms, mean ET before beetle release (2000–2006) was 416 mm/year compared to postrelease (2007–2015) ET of 355 mm/year (p<0.05) for a net reduction of 61 mm/year. This is lower than initial literature projections that ET would be reduced by 300–460 mm/year. Reasons for the lower-than-expected ET reductions are because baseline ET rates are lower than initially projected, and percentage ET reduction is low because tamarisk stands tend to regrow new leaves after defoliation and other plants help maintain canopy cover. Overall reductions in tamarisk green foliage during the study are 21%. However, ET in the Upper Basin has shown a steady decline since 2007 and equilibrium has not yet been reached. Defoliation is now proceeding from the Upper Basin into the Lower Basin at a rate of 40 km/year, much faster than initially projected.

Colorado River↗

USGS2018

Evaluating potential distribution of high-risk aquatic invasive species in the water garden and aquarium trade at a global scale based on current established populations

Aquatic non‐native invasive species are commonly traded in the worldwide water garden and aquarium markets, and some of these species pose major threats to the economy, the environment, and human health. Understanding the potential suitable habitat for these species at a global scale and at regional scales can inform risk assessments and predict future potential establishment. Typically, global habitat suitability models are fit for freshwater species with only climate variables, which provides little information about suitable terrestrial conditions for aquatic species. Remotely sensed data including topography and land cover data have the potential to improve our understanding of suitable habitat for aquatic species. In this study, we fit species distribution models using five different model algorithms for three non‐native aquatic invasive species with bioclimatic, topographic, and remotely sensed covariates to evaluate potential suitable habitat beyond simple climate matches. The species examined included a frog (Xenopus laevis), toad (Bombina orientalis), and snail (Pomacea spp.). Using a unique modeling approach for each species including background point selection based on known established populations resulted in robust ensemble habitat suitability models. All models for all species had test area under the receiver operating characteristic curve values greater than 0.70 and percent correctly classified values greater than 0.65. Importantly, we employed multivariate environmental similarity surface maps to evaluate potential extrapolation beyond observed conditions when applying models globally. These global models provide necessary forecasts of where these aquatic invasive species have the potential for establishment outside their native range, a key component in risk analyses.

Risk Analysis↗

USGS2017

Semi-quantitative assessment of disease risks at the human, livestock, wildlife interface for the Republic of Korea using a nationwide survey of experts: A model for other countries

Wildlife-associated diseases and pathogens have increased in importance; however, management of a large number of diseases and diversity of hosts is prohibitively expensive. Thus, the determination of priority wildlife pathogens and risk factors for disease emergence is warranted. We used an online questionnaire survey to assess release and exposure risks, and consequences of wildlife-associated diseases and pathogens in the Republic of Korea (ROK). We also surveyed opinions on pathways for disease exposure, and risk factors for disease emergence and spread. For the assessment of risk, we employed a two-tiered, statistical K -means clustering algorithm to group diseases into three levels (high, medium and low) of perceived risk based on release and exposure risks, societal consequences and the level of uncertainty of the experts’ opinions. To examine the experts’ perceived risk of routes of introduction of pathogens and disease amplification and spread, we used a Bayesian, multivariate normal order-statistics model. Six diseases or pathogens, including four livestock and two wildlife diseases, were identified as having high risk with low uncertainty. Similarly, 13 diseases were characterized as having high risk with medium uncertainty with three of these attributed to livestock, six associated with human disease, and the remainder having the potential to affect human, livestock and wildlife (i.e., One Health). Lastly, four diseases were described as high risk with high certainty, and were associated solely with fish diseases. Experts identified migration of wildlife, international human movement and illegal importation of wildlife as the three routes posing the greatest risk of pathogen introduction into ROK. Proximity of humans, livestock and wildlife was the most significant risk factor for promoting the spread of wildlife-associated diseases and pathogens, followed by high density of livestock populations, habitat loss and environmental degradation, and climate change. This study provides useful information to decision makers responsible for allocating resources to address disease risks. This approach provided a rapid, cost-effective method of risk assessment of wildlife-associated diseases and pathogens for which the published literature is sparse.

Transboundary and Emerging Diseases↗

USGS2017

Partial polygon pruning of hydrographic features in automated generalization

This paper demonstrates a working method to automatically detect and prune portions of waterbody polygons to support creation of a multi-scale hydrographic database. Water features are known to be sensitive to scale change; and thus multiple representations are required to maintain visual and geographic logic at smaller scales. Partial pruning of polygonal features—such as long and sinuous reservoir arms, stream channels that are too narrow at the target scale, and islands that begin to coalesce—entails concurrent management of the length and width of polygonal features as well as integrating pruned polygons with other generalized point and linear hydrographic features to maintain stream network connectivity. The implementation follows data representation standards developed by the U.S. Geological Survey (USGS) for the National Hydrography Dataset (NHD). Portions of polygonal rivers, streams, and canals are automatically characterized for width, length, and connectivity. This paper describes an algorithm for automatic detection and subsequent processing, and shows results for a sample of NHD subbasins in different landscape conditions in the United States.

Transactions in GIS↗

USGS2020

Improving geospatial query performance of an interoperable geographic situation-awareness system (IGSAS) for disaster response

Disaster response operations require fast and coordinated actions based on the real-time disaster situation information. Although Volunteered Geographic Information (VGI) or crowdsourced geospatial data applications have demonstrated to be valuable tools for gathering real-time disaster situation information, they only provide limited utility for disaster response coordination because of the lack of compatibility and interoperability. VGI based on Geospatial Semantic Web (GSW) technologies has the potential to overcome the incompatibility and heterogeneity problems. However, GSW-based VGI often has poor performance due to complex geometric computation. The objective of this research is to explore how to use optimization techniques to improve performance of an interoperable geographic situation-awareness system (IGSAS) based on GSW technologies for disaster response. We conducted experiments to evaluate various client-side optimization techniques for improving performance of an IGSAS prototype for flooding disaster response in New Haven, Connecticut. Our experimental results show that the developed prototype can greatly reduce the runtime costs of geospatial semantic queries through on-the-fly spatial indexing, tile-based rendering, efficient algorithms for spatial join, and caching, especially for those spatial-join geospatial queries that involve a large number of spatial features and heavy geometric computation.

Transactions in GIS↗

USGS2011

Mapping rice areas of South Asia using MODIS multitemporal data

Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R 2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas.

South Asia↗

USGS2019

Optical characterization of two cyanobacteria genera, Aphanizomenon and Microcystis, with hyperspectral microscopy.

Cyanobacterial blooms are a nuisance and a potential hazard in freshwater systems worldwide. Remote sensing has been used to detect cyanobacterial blooms, but few studies have distinguished between genera of cyanobacteria. Because some genera are more likely to be toxic than others, this is a useful distinction.In this study, hyperspectral imaging reflectance microscopy was used to examine cyanobacteria from Upper Klamath Lake, Oregon, USA, at high spatial and spectral resolution to determine if two species found commonly in the lake, Aphanizomenon flos-aquae and Microcystis aeruginosa, can be separated spectrally. Of the analytical methods applied, a spectral shape algorithm applied to the derivative was found to be most successful in classifying these species in microscope scenes. Further work is required to determine if the spectral characterization of cyanobacterial genera can be scaled up to other remote sensing applications.

Oregon↗

USGS2012

Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States

Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation ( R 2 =0.94, N =24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement ( R 2 =0.98, N =24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C 3 versus C 4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C 3 versus C 4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.

Journal of Applied Remote Sensing↗

USGS2017

Landsat-8 TIRS thermal radiometric calibration status

The Thermal Infrared Sensor (TIRS) instrument is the thermal-band imager on the Landsat-8 platform. The initial onorbit calibration estimates of the two TIRS spectral bands indicated large average radiometric calibration errors, -0.29 and -0.51 W/m 2 sr μm or -2.1K and -4.4K at 300K in Bands 10 and 11, respectively, as well as high variability in the errors, 0.87K and 1.67K (1-σ), respectively. The average error was corrected in operational processing in January 2014, though, this adjustment did not improve the variability. The source of the variability was determined to be stray light from far outside the field of view of the telescope. An algorithm for modeling the stray light effect was developed and implemented in the Landsat-8 processing system in February 2017. The new process has improved the overall calibration of the two TIRS bands, reducing the residual variability in the calibration from 0.87K to 0.51K at 300K for Band 10 and from 1.67K to 0.84K at 300K for Band 11. There are residual average lifetime bias errors in each band: 0.04 W/m 2 sr μm (0.30K) and -0.04 W/m 2 sr μm (-0.29K), for Bands 10 and 11, respectively.

Conference Paper↗

USGS2020

Landsat Collection 2 geometric calibration updates

The U.S. Geological Survey (USGS) changed the management and delivery of Landsat products to the public in its archive through the implementation of Collections. The Collections process ensures consistent data quality through time and across all the Landsat sensors with a few modifications to the metadata. The consistent data products from Collections are more conducive for applications such as time-series analysis, because the data can be used without a need for sensor-specific geometric or radiometric adjustments. The Collections process also allows for calibration improvements from updated reference sources, model trending, and enhanced algorithms that are grouped together and applied at one time, thus limiting the operational impacts to users. The first collection, Collection-1 was released in 2016, and Collection-2 is expected to be released in 2020. This paper addresses the geometric improvements to the Collection -2 dataset. Geometric improvements in Collection-2 include improvements to the geometric accuracy and interoperability of all Landsat products by implementing the Sentinel 2 Global Reference Image (GRI), improved elevation dataset using NASADEM and other sources of Digital Elevation Model (DEM) for terrain correction, improvements to the precision correction process for Enhanced Thematic Mapper Plus (ETM+) and Thematic Mapper (TM) sensors, changes to the Thermal Infrared Sensor (TIRS) to Operational Land Imager (OLI) alignment estimates, thermal band detector alignments and focal plane adjustments for ETM+, and improvements to the ETM+ sensor to attitude control system (ACS).

Conference Paper↗