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At least 397 records · Page 22Linked to original sources
USGS2015

csa2sac—A program for computing discharge from continuous slope-area stage data

Introduction Continuous Slope-Area (CSA) gages were developed by the Arizona Water Science Center to enable the estimation of hydrographs when direct measurements of discharge cannot be made (Smith and others, 2010). CSA gages extend standard U.S. Geological Survey (USGS) methods for determining peak discharges to mid and high flows over a hydrograph computed at regular intervals with indirect measurement methods (Benson and Dalrymple, 1967; Dalrymple and Benson, 1967). CSA gages combine continuous stage records at two or more (typically three or four) cross sections with crosssection surveys and estimates of channel roughness to compute discharge over a range of flows. With standard indirect methods of determining peak discharge, water-surface elevation in the study reach at the peak flow is estimated from surveys of debris associated with the peak-flow water line. With CSA gages, stages are continuously measured at the cross sections, at regular and synchronized intervals (typically 5 minutes) over a flow event, and discharge can be calculated at each interval. Calculation of discharge using indirect methods has been automated with the slope-area computation (SAC) program (Fulford, 1994). SAC is a widely used program within the USGS; it is easily run and displays output in a clear and convenient format, which includes flags that alert the user to shortcomings in the calculation. Use of SAC has been facilitated by SACGUI (Bradley, 2012; SACGUI uses a version of SAC called SAC7), a user interface that directly reads and displays survey data, allows for specification of water-surface slope and channel roughness, writes the input file for SAC7, runs SAC7, and displays SAC7 output. csa2sac is a program (appendix 1) that repeatedly runs SAC7 using stage data and a SAC7 input template file to compute the discharge at CSA gages. It is written in the C programming language, and is compatible with 64-bit Windows operating systems. The program reads a SAC7 input file and a file containing stage-data time series. It writes a new version of the SAC7 input file with the stage data for one time step, runs SAC7, then extracts computed discharges from the SAC7 output file and collates the discharges and stages to a separate file. It repeats these steps for each time interval in the stage file to produce a discharge time series from the stage data. csa2sac has been tested with two, three, four, and six cross sections and found to operate successfully. By running SAC7, csa2sac maintains consistency and comparability of both discharges calculated from CSA gages and of standard USGS methods for computing discharges indirectly. Brown and Metcalfe (2014) have made available alternative software for producing CSA discharges. In addition to csa2sac, the SAC7 program is required. It is the same as the original SAC program, except that it is compiled for 64-bit Windows operating systems and has a slightly different command line input. It is available online (http://water.usgs.gov/software/SAC/) as part of the SACGUI installation program. The program name, “SAC7.exe,” is coded into csa2sac, and must not be changed.

Open-File Report↗
USGS2006

A 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska

The U.S. Geological Survey (USGS) has developed a 16-year time series of vegetation condition information for the conterminous United States and Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometric measurements obtained from wide field-of-view observations, and the geometric registration accuracy. The conterminous United States and Alaska data sets have an atmospheric correction for water vapor, ozone, and Rayleigh scattering and include a cloud mask derived using the Clouds from AVHRR (CLAVR) algorithm. In comparison with other AVHRR time series data sets, the conterminous United States and Alaska data are processed using similar techniques. The primary difference is that the conterminous United States and Alaska data are at 1 km resolution, while others are at 8 km resolution. The time series consists of weekly and biweekly maximum normalized difference vegetation index (NDVI) composites.

Photogrammetric Engineering and Remote Sensing↗
USGS2003

Long-term, high-frequency current and temperature measurements along central California: Insights into upwelling/relaxation and internal waves on the inner shelf

Thermistor chains and acoustic Doppler current profilers were deployed at the northern and southern ends of Monterey Bay to examine the thermal and hydrodynamic structure of the inner (h ??? 20 m) shelf of central California. These instruments sampled temperature and current velocity at 2-min intervals over a 13-month period from June 2000 to July 2001. Time series of these data, in conjunction with SST imagery and CODAR sea surface current maps, helped to establish the basic hydrography for Monterey Bay. Analysis of time series data revealed that depth integrated flow at both sites was shore parallel (northwest-southeast) with net flows out of the Bay (northwest). The current and temperature records were dominated by semi-diurnal and diurnal tidal signals that lagged the surface tides by 3 h on average. Over the course of an internal tidal cycle these flows were asymmetric, with the flow during the flooding internal tide to the southeast typically lasting only one-third as long as the flow to the northwest during the ebbing internal tide. The transitions from ebb to flood were rapid and bore-like in nature; they were also marked by rapid increases in temperature and high shear. During the spring and summer, when thermal stratification was high, we observed almost 2000 high-frequency (Tp ??? 4-20 min) internal waves in packets of 8-10 following the heads of these bore-like features. Previous studies along the West Coast of the US have concluded that warm water bores and high-frequency internal waves may play a significant role in the onshore transport of larvae.

Continental Shelf Research↗
USGS2014

A quasi-global precipitation time series for drought monitoring

Estimating precipitation variations in space and time is an important aspect of drought early warning and environmental monitoring. An evolving drier-than-normal season must be placed in historical context so that the severity of rainfall deficits may quickly be evaluated. To this end, scientists at the U.S. Geological Survey Earth Resources Observation and Science Center, working closely with collaborators at the University of California, Santa Barbara Climate Hazards Group, have developed a quasi-global (50°S–50°N, 180°E–180°W), 0.05° resolution, 1981 to near-present gridded precipitation time series: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data archive.

Data Series↗
USGS1999

A weighted least-squares approach to temporal NDVI smoothing

Satellite imagery provides a unique vantage point for observing seasonal dynamics of the landscape that have implications for global change issues. An objective evaluation of surface conditions may be performed using the normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration advanced very high resolution radiometer data. NDVI data are typically very noisy, affected by a number of phenomena including cloud contamination, atmospheric perturbations, and variable illumination and viewing geometry, each of which usually reduces the NDVI. This work describes a weighted least-squares linear regression approach to temporal NDVI smoothing to more efficiently reduce contamination in the NDVI signal. This approach uses a moving window operating on temporal NDVI to calculate a regression line. The window is moved one period at a time, resulting in a family of regression lines associated with each point; this family of lines is then averaged at each point and interpolated between points to provide a continuous temporal NDVI signal. Also, since the factors that cause contamination usually serve to reduce NDVI values, the system applies a weighting factor that favors peak points over sloping or valley points. A final operation assures that all peak NDVI values are retained. The resulting relationship between the smoothed curve and the original data is statistically based. The smoothed data may be used to improve applications involving time-series NDVI data, such as land cover classification, seasonal vegetation characterization, and vegetation monitoring

Conference Paper↗
USGS2006

Quantifying surface water–groundwater interactions using time series analysis of streambed thermal records: Method development

We present a method for determining streambed seepage rates using time series thermal data. The new method is based on quantifying changes in phase and amplitude of temperature variations between pairs of subsurface sensors. For a reasonable range of streambed thermal properties and sensor spacings the time series method should allow reliable estimation of seepage rates for a range of at least ±10 m d −1 (±1.2 × 10 −2 m s −1 ), with amplitude variations being most sensitive at low flow rates and phase variations retaining sensitivity out to much higher rates. Compared to forward modeling, the new method requires less observational data and less setup and data handling and is faster, particularly when interpreting many long data sets. The time series method is insensitive to streambed scour and sedimentation, which allows for application under a wide range of flow conditions and allows time series estimation of variable streambed hydraulic conductivity. This new approach should facilitate wider use of thermal methods and improve understanding of the complex spatial and temporal dynamics of surface water–groundwater interactions.

Water Resources Research↗
USGS2001

Time series of suspended-solids concentration, salinity, temperature, and total mercury concentration in San Francisco Bay during water year 1998

Many physical processes affect how constituents within San Francisco Bay vary. Processes and their associated time scales include turbulence (seconds), semidiurnal and diurnal tides (hours), the spring-neap tidal cycle (days), freshwater flow (weeks), seasonal winds (months), ecological and climatic changes (years), and geologic changes (thousands of years). Continuous time series of data on basic state variables of the bay, such as suspended-solids concentration (SSC), salinity, and water temperature, provide insight on the effect and relative importance of physical processes on the bay. SSC time series and Regional Monitoring Program (RMP) water-quality data can be used to calculate time series of some traceelement concentrations (Schoellhamer, 1997a, 1997b). The purpose of this chapter is to describe qualitatively time series of SSC, salinity, water temperature, and mercury during water year 1998 (October 1997 through September 1998). Salinity, temperature, and sediment are important components of the San Francisco Bay estuarine system. Salinity and temperature affect the hydrodynamics (Monismith et al., 1996; Schoellhamer and Burau, 1998), geochemistry (Kuwabara et al., 1989), and ecology (Cloern, 1984; Nichols et al., 1986; Jassby et al., 1995) of the bay. Suspended sediments limit light availability in the bay, which, in turn, limits primary production (Cloern, 1987; Cole and Cloern, 1987), and thus food for higher trophic levels. Sediments deposit in ports and shipping channels, which must be dredged to maintain navigation (U.S. Environmental Protection Agency, 1992). Potentially toxic substances, such as metals and pesticides, adsorb to sediment particles (Kuwabara et al., 1989; Domagalski and Kuivila, 1993; Flegal et al., 1996; Schoellhamer, 1997a, 1997b). The transport and fate of suspended sediments are important factors in determining the transport and fate of constituents adsorbed on the sediments. For example, the concentration of suspended particulate chromium in the bay appears to be controlled primarily by sediment resuspension (Abu-Saba and Flegal, 1995). Concentrations of dissolved trace elements are greater in South Bay than elsewhere in San Francisco Bay, and bottom sediments are believed to be a significant source (Flegal et al., 1991). The sediments on the bay bottom provide habitat for benthic communities that can ingest these substances and introduce them into the food web (Luoma et al., 1985; Brown and Luoma, 1995, Luoma 1996). Bottom sediments also are a reservoir of nutrients that contribute to the maintenance of estuarine productivity (Hammond et al., 1985).

California↗
USGS2020

Using the Lomb-Scargle method for wave statistics from gappy time series

Sandwich Town Neck Beach in Sandwich, MA, has experienced substantial erosion and has been the subject of efforts by the town and private landowners to limit the sand loss. Erosion has been particularly dramatic in the past five years with the loss of dwellings. Sandwich's nourishment efforts presented a unique opportunity for scientists at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center to monitor beach morphology and to test new technologies and techniques such as geo-referenced drone imaging. Two bottom lander deployments were performed in Cape Cod Bay at a location that was key to model the fate of waves at Sandwich Town Neck Beach and to support the study of beach morphological evolution. The study period was after the town nourished the beach and during a time when several intense winter storms reshaped the beach and removed much of the nourished sand. A TRDI Workhorse Sentinel V ADCP was used for both deployments. For wave bursts, the instruments collected 2048 samples at 2 Hz every hour. The first deployment during the winter of 2016 returned good quality data. The second deployment during the following winter had gaps throughout the time series from a wiring problem in the external battery pack. The timing of the gaps was random, the duration approximately 100 s. While most of the bursts started at the top of each hour, many had 1-3 gaps within. Time series data with random gaps are problematic for computing spectral density, and thus, wave statistics. This kind of situation is familiar in other scientific disciplines such as astrophysics [1], where techniques exist to find stationary signals in sparse data. One of these methods is the Lomb-Scargle technique for computing periodograms. The most useful feature of the Lomb-Scargle (LS) method is that it allows the spectral analysis of incomplete records, without having to manipulate the record to extrapolate from or replace missing data. We compared the effectiveness of LS against common methods of averaging Fourier transforms such as a simple un-windowed Fast Fourier transform (FFT), Welch's method, and TRDI's Wavesmon software; methods that are commonly used in oceanography for non-gappy data. Synthetic data series that have been artificially modified to introduce gaps were used to evaluate the performance of each method. The LS approach was able to recover spectral density even with several 100-s gaps present. The method was applied here to the gappy and non-gappy data from both Sandwich deployments, and wave statistics were obtained and compared to the wave-buoy data. LS was used to process data that contains gaps that was rejected by Wavesmon, which was approximately 39% of the dataset. Significant wave height and peak period from LS compared well with buoy data. Mean period computed on gappy data using LS produced values biased low, compared with other methods when gaps were filled with the mean value. The LS technique has potential to uncover low-frequency signals such as infragravity waves from gappy records where the non-gappy segments are not long enough to resolve them. It has potential to unlock new information from older data sets.

Massachusetts↗
USGS2015

Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions

This report describes a series of geoelectrical soundings carried out on and near Mount St. Helens volcano, Washington, in 2010–2011. These soundings used a controlled-source audio-frequency magnetotelluric (CSAMT) approach (Zonge and Hughes, 1991; Simpson and Bahr, 2005). We chose CSAMT for logistical reasons: It can be deployed by helicopter, has an effective depth of penetration of as much as 1 kilometer, and requires less wire than a Schlumberger sounding. This Data Series provides the edited data for these CSAMT soundings as well as several different types of 1-D inversions (where the signal data are converted to conductivity-versus-depth models). In addition, we include a map showing station locations on and around the volcano and the Pumice Plain to the north. The apparent conductivity (or its inverse, apparent resistivity) measured by a geoelectrical system is caused by several factors. The most important of these are water-filled rock porosity and the presence of water-filled fractures; however, rock type and minerals (for instance, sulfides and clay content) also contribute to apparent conductivity. In situations with little recharge (for instance, in arid regions), variations in ionic content of water occupying pore space and fractures sampled by the measurement system must also be factored in (Wynn, 2006). Variations in ionic content may also be present in hydrothermal fluids surrounding volcanoes in wet regions. In unusual cases, temperature may also affect apparent conductivity (Keller, 1989; Palacky, 1989). There is relatively little hydrothermal alteration (and thus fewer clay minerals that might add to the apparent conductivity) in the eruptive products of Mount St. Helens (Reid and others, 2010), so conductors observed in the Fischer, Occam, and Marquardt inversion results later in this report are thus believed to map zones with significant water content. Geoelectrical surveys thus have the potential to reveal subsurface regions with significant groundwater content, including perched and regional aquifers. Reid and others (2001) and Reid (2004) have suggested that groundwater involvement may figure in both the scale and the character of some if not all volcanic edifice collapse events. Ongoing research by the U.S. Geological Survey (USGS) and others aims to better understand the contribution of groundwater to both edifice pore pressure and rock alteration as well as its direct influence on eruption processes by violent interaction with magma (Schmincke, 1998).

Washington↗
USGS1997

Seasonal vegetation characteristics of the United States

The U.S. Geological Survey's EROS Data Center has created a prototype 1‐km resolution data base of vegetation seasonal characteristics. The characteristics are derived from time‐series NDVI data collected by the AVHRR satellite sensor. Information covering the 5 years 1989–1993 is included in the data base. Although quantitative validation of the seasonal characteristics cannot be made until several evaluation efforts are completed, general observations are possible by viewing images of the seasonal parameters. Figures 2 through 8 show several examples of the seasonal characteristics data base.

Geocarto International↗
USGS2023

Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2021

The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, by 7 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries. This is the sixth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. Prior reports in this series documented data collected from October 2015 to September 2020. This report contains information pertinent to data collection during the 2021 water year, from October 2020 to September 2021. There were no modifications this year to the previously installed monitoring network. Data at each station were compared for the length of the project and on a yearly basis to show the annual variability of discharge and salinity in the project area. Discharge and salinity varied widely during the 2021 water year data collection period, which included above-average rainfall for four of the five counties in the study area. Total annual rainfall for all counties ranked third among the annual totals computed for the 6 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Clapboard Creek, Ortega River, Pottsburg Creek at U.S. 90, Julington Creek, Pottsburg Creek near South Jacksonville, Dunn Creek, Cedar River, and Broward River, whose annual mean discharge was lowest. Annual mean discharge at 7 of the 10 tributary monitoring sites was higher for the 2021 water year than for the 2020 water year, and the computed annual mean flow at Clapboard Creek was the highest over the 6 years considered for this study. The annual mean discharge for each of the main-stem sites was higher for the 2021 water year than for the 2020 water year and ranked second among the annual totals computed for the 6 years considered for this study. Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2020 water year, annual mean salinity at all monitoring locations was lower for the 2021 water year except at the tributary site of Durbin Creek, which remained the same. The 2021 annual mean salinity at all sites ranked second lowest since the beginning of the study in 2016 except at Julington Creek and Racy Point, which tied for lowest, and Durbin Creek, which had the same value for each year.

Florida↗
USGS2012

Seasonal variability in the surface sediments of Mobile Bay, Alabama, recorded by geochemistry and foraminifera, 2009–2010

A study was undertaken in order to document and quantify recent environmental change in Mobile Bay, Alabama. The study was part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project, a regional project funded by the Coastal and Marine Geology Program to understand how natural forcings and anthropogenic modifications influence coastal ecosystems and their susceptibility to coastal hazards. Mobile Bay is a large drowned-river estuary that has been modified significantly by humans to accommodate the Port of Mobile. Examples include repeated dredging of a large shipping channel down the central axis of the bay and construction of a causeway across the head of the bay and at the foot of the bayhead delta. In addition to modifications, the bay is also known to have episodic periods of low oxygen (hypoxia) that result in significant mortality to fish and benthic organisms (May, 1973). For this study a series of surface sediment samples were collected. Surface benthic foraminiferal and bulk geochemical data provide the modern baseline conditions of the bay and can be used as a reference to changing environmental parameters in the past (Osterman and Smith, in press) and into the future. This report archives data collected as part of the Mobile Bay Study that may be used in future environmental change studies.

Alabama↗
USGS2014

Database for the geologic map of upper Eocene to Holocene volcanic and related rocks in the Cascade Range, Washington

This geospatial database for a geologic map of the Cascades Range in Washington state is one of a series of maps that shows Cascade Range geology by fitting published and unpublished mapping into a province-wide scheme of lithostratigraphic units. Geologic maps of the Eocene to Holocene Cascade Range in California and Oregon complete the series, providing a comprehensive geologic map of the entire Cascade Range that incorporates modern field studies and that has a unified and internally consistent explanantion. The complete series will be useful for regional studies of volcanic hazards, volcanology, and tectonics. Originally a project supported by the Geothermal Research Program of the U.S. Geological Survey, the maps emphasize Quaternary volcanic rocks, because large igneous-related hydrothermal systems that have high temperatures are associated with Quaternary volcanic fields. Rocks older than a few million years are also included on the maps as they help to unravel geologic puzzles of the present-day Cascade Range. The deeply eroded older volcanoes found in the Western Cascades physiographic subprovince are analogues of today's snow-covered shield volcanoes and stratovolcanoes. The fossil hydrothermal systems of the Eocene to Pliocene vents now exposed provide clues to processes active today beneath the Pleistocene and Holocene volcanic peaks along the present-day crest of the Cascade Range. Study of these older rocks can aid in developing models of geothermal systems. These rocks also give insight into the origins of volcanic-hosted mineral deposits and even to future volcanic hazards. This digital database contains information used to produce the geologic map published as Sheet 1 in U.S. Geological Survey Miscellaneous Investigations Series Map I-2005. (Sheet 2 of Map I-2005 shows sources of geologic data used in the compilation and is available separately). Sheet 1 of Map I-2005 shows the distribution and relations of volcanic and related rock units in the Cascade Range of Washington at a scale of 1:500,000. This digital release is produced from stable materials originally compiled at 1:250,000 scale that were used to publish Sheet 1. The database therefore contains more detailed geologic information than is portrayed on Sheet 1. This is most noticeable in the database as expanded polygons of surficial units and the presence of additional strands of concealed faults. No stable compilation materials exist for Sheet 1 at 1:500,000 scale. The main component of this digital release is a spatial database prepared using geographic information systems (GIS) applications. This release also contains links to files to view or print the map sheet, main report text, and accompanying mapping reference sheet from Map I-2005. For more information on volcanoes in the Cascade Range in Washington, Oregon, or California, please refer to the U.S. Geological Survey Volcano Hazards Program website.

Washington↗
USGS1977

Descriptions and chemical analyses for selected wells in eastern Sacramento Valley, California

The Sacramento Valley occupies the northern one-third of the Great Central Valley of California. The study area of this report includes about 1,300 square miles in the eastern part of the Sacramento Valley, extending from the latitude of Roseville on the south to the latitude of Chico on the north and bounded on the east by the foothills of the Sierra Nevada and on the west by the Sacramento River, in Yolo, Yuba, Placer, Sutter, and Butte Counties. Between February and July 1976, 809 wells were canvassed, and during August and September 1976, water samples were collected for chemical analysis from 222 of the wells. Field determinations of alkalinity, conductance, pH, and temperature were made on the site at the time of sampling. The samples were then field prepared for shipment and analysis for selected constituents and properties at the Geological Survey Central Laboratory, Arvada, Colo. Descriptive data for water wells, chemical data, and the location of wells are presented. This is the third in a series of data reports showing baseline well data and water-quality data in the Sacramento Valley and is in cooperation with the California Department of Water Resources. (Woodard-USGS)

Open-File Report↗
USGS2020

A synthesis of evidence of drivers of amphibian declines

Early calls for robust long-term time series of amphibian population data, stemming from discussion following the first World Congress of Herpetology, are now being realized after 25 yr of focused research. Inference from individual studies and locations have contributed to a basic consensus on drivers of amphibian declines. Until recently there were no large-scale syntheses of long-term time series data to test hypotheses about the generality of factors driving population dynamics at broad spatial scales. Through the U.S. Geological Survey's Powell Center for Analysis and Synthesis, we brought together a group of scientists to elucidate mechanisms underlying amphibian declines in North America and Europe. We used time series of field data collected across dozens of study areas to make inferences with these combined data using hierarchical and spatial models. We bring together results from four syntheses of these data to summarize our state of knowledge of amphibian declines, identify commonalities that suggest further avenues of study, and suggest a way forward in addressing amphibian declines—by looking beyond specific drivers to how to achieve stability in remaining populations. The common thread of the syntheses is that declines are real but not ubiquitous, and that multiple factors drive declines but the relative importance of each factor varies among species, populations, and regions. We also found that climate is an important driver of amphibian population dynamics. However, the direction and magnitude of sensitivity to change vary among species in ways unlikely to explain overall rates of decline. Thirty years after the initial identification of a major catastrophe for global biodiversity, the scientific community has empirically demonstrated the reality of the problem, identified putative causes, provided evidence of their impacts, invested in broader-scale actions, and attempted meta-analyses to search out global drivers. We suggest an approach that focuses on key demographic rates that may improve amphibian population trends at multiple sites across the landscape.

Herpetologica↗
USGS2006

Optimal interpolation analysis of leaf area index using MODIS data

A simple data analysis technique for vegetation leaf area index (LAI) using Moderate Resolution Imaging Spectroradiometer (MODIS) data is presented. The objective is to generate LAI data that is appropriate for numerical weather prediction. A series of techniques and procedures which includes data quality control, time-series data smoothing, and simple data analysis is applied. The LAI analysis is an optimal combination of the MODIS observations and derived climatology, depending on their associated errors σ o and σ c . The “best estimate” LAI is derived from a simple three-point smoothing technique combined with a selection of maximum LAI (after data quality control) values to ensure a higher quality. The LAI climatology is a time smoothed mean value of the “best estimate” LAI during the years of 2002–2004. The observation error is obtained by comparing the MODIS observed LAI with the “best estimate” of the LAI, and the climatological error is obtained by comparing the “best estimate” of LAI with the climatological LAI value. The LAI analysis is the result of a weighting between these two errors. Demonstration of the method described in this paper is presented for the 15-km grid of Meteorological Service of Canada (MSC)'s regional version of the numerical weather prediction model. The final LAI analyses have a relatively smooth temporal evolution, which makes them more appropriate for environmental prediction than the original MODIS LAI observation data. They are also more realistic than the LAI data currently used operationally at the MSC which is based on land-cover databases.

Remote Sensing of Environment↗
USGS2002

Geographic techniques and recent applications of remote sensing to landscape-water quality studies

This article overviews recent advances in studies of landscape-water quality relationships using remote sensing techniques. With the increasing feasibility of using remotely-sensed data, landscape-water quality studies can now be more easily performed on regional, multi-state scales. The traditional method of relating land use and land cover to water quality has been extended to include landscape pattern and other landscape information derived from satellite data. Three items are focused on in this article: 1) the increasing recognition of the importance of larger-scale studies of regional water quality that require a landscape perspective; 2) the increasing importance of remotely sensed data, such as the imagery-derived normalized difference vegetation index (NDVI) and vegetation phenological metrics derived from time-series NDVI data; and 3) landscape pattern. In some studies, using landscape pattern metrics explained some of the variation in water quality not explained by land use/cover. However, in some other studies, the NDVI metrics were even more highly correlated to certain water quality parameters than either landscape pattern metrics or land use/cover proportions. Although studies relating landscape pattern metrics to water quality have had mixed results, this recent body of work applying these landscape measures and satellite-derived metrics to water quality analysis has demonstrated their potential usefulness in monitoring watershed conditions across large regions.

Water, Air, & Soil Pollution↗
USGS1993

Effects of advanced treatment of municipal wastewater on the White River near Indianapolis, Indiana: Trends in water quality, 1978-86

The City of Indianapolis has constructed state-of-the-art advanced municipal wastewater-treatment systems to enlarge and upgrade the existing secondary-treatment processes at its Belmont and Southport treatment plants. These new advanced-wastewater-treatment plants became operational in 1983. A nonparametric statistical procedure--a modified form of the Wilcoxon-Mann-Whitney rank-sum test--was used to test for trends in time-series water-quality data from four sites on the White River and from the Belmont and Southport wastewater-treatment plants. Time-series data representative of pre-advanced- (1978-1980) and post-advanced- (1983--86) wastewater-treatment conditions were tested for trends, and the results indicate substantial changes in water quality of treated effluent and of the White River downstream from Indianapolis after implementation of advanced wastewater treatment. Water quality from 1981 through 1982 was highly variable due to plant construction. Therefore, this time period was excluded from the analysis. Water quality at sample sites located upstream from the wastewater-treatment plants was relatively constant during the period of study (1978-86). Analysis of data from the two plants and downstream from the plants indicates statistically significant decreasing trends in effluent concentrations of total ammonia, 5-day biochemical-oxygen demand, fecal-coliform bacteria, total phosphate, and total solids at all sites where sufficient data were available for testing. Because of in-plant nitrification, increases in nitrate concentration were statistically significant in the two plants and in the White River. The decrease in ammonia concentrations and 5-day biochemical-oxygen demand in the White River resulted in a statistically significant increasing trend in dissolved-oxygen concentration in the river because of reduced oxygen demand for nitrification and biochemical oxidation processes. Following implementation of advanced wastewater treatment, the number of river-quality samples that failed to meet the water-quality standards for ammonia and dissolved oxygen that apply to the White River decreased substantially.

Indiana↗