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Results for “Journal of Time Series Analysis”

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At least 55 records · Page 3Linked to original sources
USGS2008

Agreement evaluation of AVHRR and MODIS 16-day composite NDVI data sets

Satellite-derived normalized difference vegetation index (NDVI) data have been used extensively to detect and monitor vegetation conditions at regional and global levels. A combination of NDVI data sets derived from AVHRR and MODIS can be used to construct a long NDVI time series that may also be extended to VIIRS. Comparative analysis of NDVI data derived from AVHRR and MODIS is critical to understanding the data continuity through the time series. In this study, the AVHRR and MODIS 16-day composite NDVI products were compared using regression and agreement analysis methods. The analysis shows a high agreement between the AVHRR-NDVI and MODIS-NDVI observed from 2002 and 2003 for the conterminous United States, but the difference between the two data sets is appreciable. Twenty per cent of the total difference between the two data sets is due to systematic difference, with the remainder due to unsystematic difference. The systematic difference can be eliminated with a linear regression-based transformation between two data sets, and the unsystematic difference can be reduced partially by applying spatial filters to the data. We conclude that the continuity of NDVI time series from AVHRR to MODIS is satisfactory, but a linear transformation between the two sets is recommended.

International Journal of Remote Sensing↗
USGS2013

Pre-eruption deformation caused by dike intrusion beneath Kizimen volcano, Kamchatka, Russia, observed by InSAR

Interferometric synthetic aperture radar (InSAR) images reveal a pre-eruption deformation signal at Kizimen volcano, Kamchatka, Russia, where an ongoing eruption began in mid-November, 2010. The previous eruption of this basaltic andesite-to-dacite stratovolcano occurred in 1927–1928. InSAR images from both ascending and descending orbital passes of Envisat and ALOS PALSAR satellites show as much as 6 cm of line-of-sight shortening from September 2008 to September 2010 in a broad area centered at Kizimen. About 20 cm of opening of a nearly vertical dike provides an adequate fit to the surface deformation pattern. The model dike is approximately 14 km long, 10 km high, centered 13 km beneath Kizimen, and strikes NE–SW. Time-series analysis of multi-temporal interferograms indicates that (1) intrusion started sometime between late 2008 and July 2009, (2) continued at a nearly constant rate, and (3) resulted in a volume expansion of 3.2 × 10 7 m 3 by September 2010, i.e., about two months before the onset of the 2010 eruption. Earthquakes located above the tip of the dike accompanied the intrusion. Eventually, magma pressure in the dike exceeded the confining strength of the host rock, triggering the 2010 eruption. Our results provide insight into the intrusion process that preceded an explosive eruption at a Pacific Rim stratovolcano following nearly a century of quiescence, and therefore have implications for monitoring and hazards assessment at similar volcanoes elsewhere.

Kamchatka, Kizimen Volcano↗
USGS1991

Single-station decomposition of seismograms for subevent time histories

We have adapted an iterative least-squares inversion with positivity constraints to the problem of deconvolving the recordings of a small earthquake from the recordings of a large composite earthquake. The inversion uses an F test to minimize the number of non-zero amplitudes or subevents in the solution set, by requiring each added subevent to reduce the variance significantly. We apply this inversion to the analysis of strong motion recordings of a set of moderate-sized (4.0 ≤ M L ≤ 6.4) aftershocks of the 1976 Friuli earthquake. The earthquake pairs are selected by comparing S trigger times and polarization diagrams. The deconvolved time series are interpreted as the time history of slip events or stress release in the composite earthquake, depending on whether the recordings of the small earthquake are unfiltered or filtered to simulate the waveforms radiated by subevents. Deconvolving with the filtered recordings reduces the variance more rapidly, as a function of the number of subevents, than deconvolving with the unfiltered recordings. The deconvolved time series for three of the four earthquakes analysed indicate that the rupture processes resemble the failure of asperities where the initial subevent has the largest stress drop and the later subevents have longer durations and weaker stress drops.

Geophysical Journal International↗
USGS2009

Effects of highway construction on stream water quality and macroinvertebrate condition in a mid-Atlantic highlands watershed, USA

Refining best management practices (BMPs) for future highway construction depends on a comprehensive understanding of environmental impacts from current construction methods. Based on a before-after-control impact (BACI) experimental design, long-term stream monitoring (1997–2006) was conducted at upstream (as control, n = 3) and downstream (as impact, n = 6) sites in the Lost River watershed of the Mid-Atlantic Highlands region, West Virginia. Monitoring data were analyzed to assess impacts of during and after highway construction on 15 water quality parameters and macroinvertebrate condition using the West Virginia stream condition index (WVSCI). Principal components analysis (PCA) identified regional primary water quality variances, and paired t tests and time series analysis detected seven highway construction-impacted water quality parameters which were mainly associated with the second principal component. In particular, impacts on turbidity, total suspended solids, and total iron during construction, impacts on chloride and sulfate during and after construction, and impacts on acidity and nitrate after construction were observed at the downstream sites. The construction had statistically significant impacts on macroinvertebrate index scores (i.e., WVSCI) after construction, but did not change the overall good biological condition. Implementing BMPs that address those construction-impacted water quality parameters can be an effective mitigation strategy for future highway construction in this highlands region.

West Virginia↗
USGS2022

Quantifying status and trends from monitoring surveys: Application to Pygmy Whitefish (Prosopium coulterii) in Lake Superior

Population assessments of fish species often rely on data from surveys with different objectives, such as measuring biodiversity or community dynamics. These surveys often contain spatial–temporal dependencies that can greatly influence conclusions drawn from analyses. Pygmy whitefish (PWF, Prosopium coulterii ) populations in Lake Superior were recently assessed as Threatened by the Committee on the Status of Endangered Species in Canada, which motivated a thorough analysis of available data to improve our understanding of its population status. The US Geological Survey conducts annual bottom trawl surveys in Lake Superior that commonly capture PWF. We used these data (1989–2018) to model temporal trends in PWF biomass density and make lake-wide population projections. We used a Bayesian approach, integrated nested Laplace approximation (INLA), and compared the impact of including different random structures on model fit. Inclusion of spatial structure improved model fit and conclusions differed from models omitting random effects. PWF populations have experienced periodic fluctuations in biomass density since 1989, though 2018 may represent the lowest density in the 30-year time series. Lake-wide biomass was estimated to be 71.5 t.

Lake Superior↗
USGS1982

An analysis of howling response parameters useful for wolf pack censusing

Gray wolves ( Canis lupus ) were studied from April-1972 through April 1974 in the Superior National Forest in northeastern Minnesota by radio-tracking and simulated howling. Based on replies during 217 of 456 howling sessions, the following recommendations were derived for using simulated howling as a census technique: (1) the best times of day are dusk and night; (2) July, August, and September are the best months; (3) precipitation and winds greater than 12 km/hour should be avoided; (4) a sequence of 5 single howls should be used, alternating 'flat' and 'breaking' howls; (5) trials should be repeated 3 times at about 2-minute intervals with the first trial at lower volume; and (6) the trial series should be repeated on 3 nights as close to each other as possible. Two censuses are described: a saturation census and a sampling census.

Minnesota↗
USGS2020

Riverbank stability assessment of lower Osage River during hydro-peak flow events: The lower Osage River case (Missouri, USA)

The fluctuation of water level downstream from dams due to hydropower flow releases can negatively affect riverbank stability. This research aims to investigate riverbank instability resulting from the outflow variation of hydropower plants, using Bagnell Dam and the lower Osage River (Missouri, USA) as the basis of analysis. The effects of the water releases from the Bagnell Dam were investigated by computing a series of safety factors in relation to outflow events for 78 cross sections along the 130-km stretch of the lower Osage River using the BSTEM algorithm integrated into the HEC-RAS model package. The results showed that the rate of change in the flow magnitude at each cross section impacts the calculated safety factor. The flow release fluctuations will change the value of the safety factor along the river over time, as the safety factor value closely follows the variation in the flow rate. Also, the results show that the cross sections closer to Bagnell Dam are subjected to be more unstable than those farther downstream of Osage River.

Missouri↗
USGS1997

Correlated errors in geodetic time series: Implications for time-dependent deformation

Analysis of frequent trilateration observations from the two-color electronic distance measuring networks in California demonstrate that the noise power spectra are dominated by white noise at higher frequencies and power law behavior at lower frequencies. In contrast, Earth scientists typically have assumed that only white noise is present in a geodetic time series, since a combination of infrequent measurements and low precision usually preclude identifying the time-correlated signature in such data. After removing a linear trend from the two-color data, it becomes evident that there are primarily two recognizable types of time-correlated noise present in the residuals. The first type is a seasonal variation in displacement which is probably a result of measuring to shallow surface monuments installed in clayey soil which responds to seasonally occurring rainfall; this noise is significant only for a small fraction of the sites analyzed. The second type of correlated noise becomes evident only after spectral analysis of line length changes and shows a functional relation at long periods between power and frequency of 1/ƒ α , where ƒ is frequency and α≈2. With α=2, this type of correlated noise is termed random-walk noise, and its source is mainly thought to be small random motions of geodetic monuments with respect to the Earth's crust, though other sources are possible. Because the line length changes in the two-color networks are measured at irregular intervals, power spectral techniques cannot reliably estimate the level of 1/ƒ α noise. Rather, we also use here a maximum likelihood estimation technique which assumes that there are only two sources of noise in the residual time series (white noise and random-walk noise) and estimates the amount of each. From this analysis we find that the random-walk noise level averages about 1.3 mm/√yr and that our estimates of the white noise component confirm theoretical limitations of the measurement technique. In addition, the seasonal noise can be as large as 3 mm in amplitude but typically is less than 0.5 mm. Because of the presence of random-walk noise in these time series, modeling and interpretation of the geodetic data must account for this source of error. By way of example we show that estimating the time-varying strain tensor (a form of spatial averaging) from geodetic data having both random-walk and white noise error components results in seemingly significant variations in the rate of strain accumulation; spatial averaging does reduce the size of both noise components but not their relative influence on the resulting strain accumulation model.

Journal of Geophysical Research B: Solid Earth↗
USGS2014

Multi-scale observations of the variability of magmatic CO2 emissions, Mammoth Mountain, CA, USA

One of the primary indicators of volcanic unrest at Mammoth Mountain is diffuse emission of magmatic CO 2 , which can effectively track this unrest if its variability in space and time and relationship to near-surface meteorological and hydrologic phenomena versus those occurring at depth beneath the mountain are understood. In June–October 2013, we conducted accumulation chamber soil CO 2 flux surveys and made half-hourly CO 2 flux measurements with automated eddy covariance and accumulation chamber (auto-chamber) instrumentation at the largest area of diffuse CO 2 degassing on Mammoth Mountain (Horseshoe Lake tree kill; HLTK). Estimated CO 2 emission rates for HLTK based on 20 June, 30 July, and 24–25 October soil CO 2 flux surveys were 165, 172, and 231 t d − 1 , respectively. The average (June–October) CO 2 emission rate estimated for this area was 123 t d − 1 based on an inversion of 4527 eddy covariance CO 2 flux measurements and corresponding modeled source weight functions. Average daily eddy covariance and auto-chamber CO 2 fluxes consistently declined over the four-month observation time. Wavelet analysis of auto-chamber CO 2 flux and environmental parameter time series was used to evaluate the periodicity of, and local correlation between these variables in time–frequency space. Overall, CO 2 emissions at HLTK were highly dynamic, displaying short-term (hourly to weekly) temporal variability related to meteorological and hydrologic changes, as well as long-term (monthly to multi-year) variations related to migration of CO 2 -rich magmatic fluids beneath the volcano. Accumulation chamber soil CO 2 flux surveys were also conducted in the four additional areas of diffuse CO 2 degassing on Mammoth Mountain in July–August 2013. Summing CO 2 emission rates for all five areas yielded a total for the mountain of 311 t d − 1 , which may suggest that emissions returned to 1998–2009 levels, following an increase from 2009 to 2011.

California↗
USGS2013

Size distribution of Parkfield’s microearthquakes reflects changes in surface creep rate

The nucleation area of the series of M6 events in Parkfield has been shown to be characterized by low b-values throughout the seismic cycle. Since low b -values represent high differential stresses, the asperity structure seems to be always stably stressed and even unaffected by the latest main shock in 2004. However, because fault loading rates and applied shear stress vary with time, some degree of temporal variability of the b -value within stable blocks is to be expected. We discuss in this study adequate techniques and uncertainty treatment for a detailed analysis of the temporal evolution of b -values. We show that the derived signal for the Parkfield asperity correlates with changes in surface creep, suggesting a sensitive time resolution of the b-value stress meter, and confirming near-critical loading conditions within the Parkfield asperity.

Geophysical Journal International↗
USGS2004

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Journal of Arid Environments↗
USGS2019

Subhourly mesoscale analysis of the 2011-2017 North American monsoon near its northwest boundary

The North American Monsoon (NAM) delivers precipitation to the southwestern USA during the warm-dry summer season. The seasonal extent of NAM precipitation is highly variable and is likely to change under future climate change. Our objective was to determine how large scale monsoonal patterns as well as local variables influence precipitation events near the NAM northwest boundary. Intra- and inter-annual changes in the northwest sector of the NAM were represented by subhourly weather data collected on the Sheep Range (2300 m asl), in the Mojave Desert of southern Nevada, during 2011-2017. Our study site is part of the Nevada Climate-ecohydrological Assessment Network (NevCAN), an automated observing system established in early 2011. Three seasons were classified using the subhourly weather data including: 1) cool season, 2) early warm season, 3) and late warm season, where the transition between early and late warm season was marked by the day when in situ dewpoint temperature first exceeded 9.4 ºC. Based on analysis of covariance (ANCOVA), dewpoint temperature had the greatest relationship with total hourly precipitation, followed by vapor pressure deficit, solar radiation, and air temperature. The only significant interaction term was between hour of the day and dewpoint temperature, highlighting the importance of dewpoint temperature for afternoon thunderstorms, which are typical of monsoonal precipitation. Besides in situ meteorological variables, we also analyzed NCEP/NCAR vertically integrated water vapor transport (IVT) and long-term 800-m PRISM precipitation time series. Regional composites were developed for IVT for the three seasons. Water vapor in the cool and early warm season originated mostly from the Pacific Ocean, while a transition in IVT to a NAM pattern occurred in the late warm season. Overall, this highly instrumented yet remote site was representative of NAM precipitation, despite noticeable variability in its timing and amount.

Nevada↗
USGS2016

Quantifying fish swimming behavior in response to acute exposure of aqueous copper using computer assisted video and digital image analysis

Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction. However, these responses may be subtle, and measurement can be challenging. Using juvenile white sturgeon ( Acipenser transmontanus ) with copper exposures, this paper illustrates techniques used for quantifying behavioral responses using computer assisted video and digital image analysis. In previous studies severe impairments in swimming behavior were observed among early life stage white sturgeon during acute and chronic exposures to copper. Sturgeon behavior was rapidly impaired and to the extent that survival in the field would be jeopardized, as fish would be swept downstream, or readily captured by predators. The objectives of this investigation were to illustrate protocols to quantify swimming activity during a series of acute copper exposures to determine time to effect during early lifestage development, and to understand the significance of these responses relative to survival of these vulnerable early lifestage fish. With mortality being on a time continuum, determining when copper first affects swimming ability helps us to understand the implications for population level effects. The techniques used are readily adaptable to experimental designs with other organisms and stressors.

Journal of Visualized Experiments↗
USGS1980

Comparison of bed form variance spectra within a meander bend during flood and average discharge

Time series analysis of streambed elevation in a meander bend along the Congaree River was used to determine the changes in bed form population succeeding a 16-year flood event. Bed forms observed during the flood event had a significantly greater total height variance than bed forms observed at the same location one week later. Variance spectra were computed for a 595 m longitudinal profile. The data indicate that: a) the bed form variance for the flood record is significantly greater for all wavelengths from 5 to 30 m; b) no well-demarcated bed form classes were present during the survey times, pointing to the possible existence of a continuum of bed form sizes rather than well-defined classes; and c) bed forms produced by the flood discharge were rapidly altered as the stage returned toward average level.

Journal of Sedimentary Petrology↗
USGS2018

Evolving environmental and geometric controls on Columbia Glacier’s continued retreat

Geometry strongly controls the dynamic behavior of marine‐terminating (tidewater) glaciers, significantly influencing advance and retreat cycles independent of climate. Yet the recent, nearly ubiquitous retreat of tidewater glaciers suggests that changes in atmospheric and oceanic forcing may also drive dynamic change. To isolate the influence of geometry on tidewater glacier dynamics, we analyzed detailed observational time series from 2012 to 2016 for two tidewater glaciers with shared dynamic histories and environmental forcing: Columbia Glacier and its former tributary (Post Glacier) in southcentral Alaska. We find that although terminus retreat has driven decadal‐scale changes in dynamics of the Columbia‐Post system, environmental factors contribute to short‐term (i.e., seasonal) dynamic variability. In particular, analysis of force balance time series indicates that observed variations in speed result from seasonal changes to the subglacial hydrologic system and associated changes in basal drag. Variations in terminus position only drive noticeable speed change when the terminus retreats from regions of relatively high basal drag. In agreement with long‐term analyses of Columbia Glacier, we find that terminus geometry can perturb the timing of seasonal ice flow patterns. Specifically, our data support the idea that retreat of a glacier terminus into deeper water is accompanied by a shift in the primary control on frontal ablation. Although our analysis focuses on two Alaskan glaciers, our data suggest that changes in the relative importance of surface meltwater and buoyancy effects on submarine melting and/or calving may manifest as a shift in terminus change seasonality and offer a mechanism to identify frontal ablation controls.

Alaska↗
USGS2016

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data

The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi -season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea ( Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary ( kharif ) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second ( rabi ) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.

International Journal of Digital Earth↗
USGS2012

Semi-discrete biomass dynamic modeling: an improved approach for assessing fish stock responses to pulsed harvest events

Continuous harvest over an annual period is a common assumption of continuous biomass dynamics models (CBDMs); however, fish are frequently harvested in a discrete manner. We developed semidiscrete biomass dynamics models (SDBDMs) that allow discrete harvest events and evaluated differences between CBDMs and SDBDMs using an equilibrium yield analysis with varying levels of fishing mortality ( F ). Equilibrium fishery yields for CBDMs and SDBDMS were similar at low fishing mortalities and diverged as F approached and exceeded maximum sustained yield ( F MSY ). Discrete harvest resulted in lower equilibrium yields at high levels of F relative to continuous harvest. The effect of applying harvest continuously when it was in fact discrete was evaluated by fitting CBDMs and SDBDMs to time series data generated from a hypothetical fish stock undergoing discrete harvest and evaluating parameter estimates bias. Violating the assumption of continuous harvest resulted in biased parameter estimates for CBDM while SDBDM parameter estimates were unbiased. Biased parameter estimates resulted in biased biological reference points derived from CBDMs. Semidiscrete BDMs outperformed continuous BDMs and should be used when harvest is discrete, when the time and magnitude of harvest are known, and when F is greater than F MSY .

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2022

From data to interpretable models: Machine learning for soil moisture forecasting

Soil moisture is critical to agricultural business, ecosystem health, and certain hydrologically driven natural disasters. Monitoring data, though, is prone to instrumental noise, wide ranging extrema, and nonstationary response to rainfall where ground conditions change. Furthermore, existing soil moisture models generally forecast poorly for time periods greater than a few hours. To improve such forecasts, we introduce two data-driven models, the Naive Accumulative Representation (NAR) and the Additive Exponential Accumulative Representation (AEAR). Both of these models are rooted in deterministic, physically based hydrology, and we study their capabilities in forecasting soilmoisture over time periods longer than a fewhours. Learned model parameters represent the physically based unsaturated hydrological redistribution processes of gravity and suction. We validate our models using soil moisture and rainfall time series data collected from a steep gradient, post-wildfire site in southern California. Data analysis is complicated by rapid landscape change observed in steep, burned hillslopes in response to even small to moderate rain events. The proposed NAR and AEAR models are, in forecasting experiments, shown to be competitive with several established and state-of-the-art baselines. The AEAR model fits the data well for three distinct soil textures at variable depths below the ground surface (5, 15, and 30 cm). Similar robust results are demonstrated in controlled, laboratory-based experiments. Our AEAR model includes readily interpretable hydrologic parameters and provides more accurate forecasts than existing models for time horizons of 10–24 h. Such extended periods of warning for natural disasters, such as floods and landslides, provide actionable knowledge to reduce loss of life and property.

International Journal of Data Science and Analytic↗