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At least 37 records · Page 2Linked to original sources
USGS2026

Evaluating chlorophyll fluorescence sensors as a proxy for chlorophyll a concentrations in the Illinois River, Illinois, water years 2018–24

The U.S. Geological Survey deployed instream chlorophyll fluorescence sensors on the Illinois River in Illinois to better understand the formation, dynamics, and persistence of riverine algal blooms. At five sensor locations across four U.S. Geological Survey streamgages, chlorophyll fluorescence (fChl) sensors were set to measure instantaneous fChl in micrograms per liter as chlorophyll at 15-minute intervals. These sensors estimate fChl based on the fluorescence response of algal pigments but do not directly measure chlorophyll a (Chl) concentrations or algal biomass. To evaluate the reliability of fChl as a proxy for Chl, fChl measurements were compared to laboratory-measured Chl concentrations. These Chl concentrations were obtained from water-quality samples collected at the sensor locations and analyzed using the standard chromatographic-fluorometric method with acetone extraction. A total of 209 paired fChl and Chl observations were analyzed using Pearson’s correlation and model II regression. Statistically significant, positive correlations (Pearson’s correlation coefficient of 0.68–0.95) were detected at all sensor locations, indicating that fChl generally tracked with Chl. However, model II regression detected proportional and fixed bias at three of the five locations and proportional bias at another location. At locations with proportional biases, model II regression slopes were less than 1, indicating that fChl increasingly underestimated Chl as concentrations increased; however, paired observations at high Chl concentrations were sparse. Substantial variability in bias was also observed across sensor locations with slopes ranging from 0.43 to 0.93. Overall, the results indicated that fChl correlates well with Chl in the Illinois River, but fChl may not reliably represent Chl concentrations without adjustment. For applications requiring accurate Chl estimates, a sensor location-specific surrogate model could be beneficial. These findings underscore the importance of field validation, consistent sensor placement, and careful interpretation of fChl data, particularly when reported in micrograms per liter.

Illinois, Indiana, Wisconsin↗
USGS2025

Absolute radiometric calibration evaluation of Uncrewed Aerial System (UAS) Headwall and MicaSense sensors and improving data quality using the Empirical Line Method

The use of Uncrewed Aerial Systems (UASs) for remote sensing applications has increased significantly in recent years due to their low cost, operational flexibility, and rapid advancements in sensor technologies. In many cases, UAS platforms are considered viable alternatives to conventional satellite and crewed airborne platforms, offering very high spatial, spectral, and temporal resolution data. However, the radiometric quality of UAS-acquired data has not received equivalent attention, particularly with respect to absolute calibration. In this study, we (1) evaluate the absolute radiometric performance of two commonly used UAS sensors: the Headwall Nano-Hyperspec hyperspectral sensor and the MicaSense RedEdge-MX Dual Camera multispectral system; (2) assess the effectiveness of the Empirical Line Method (ELM) in improving the radiometric accuracy of reflectance products generated by these sensors; and (3) investigate the influence of calibration target characteristics—including size, material type, reflectance intensity, and quantity—on the performance of ELM for UAS data. A field campaign was conducted jointly by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the USGS National Uncrewed Systems Office (NUSO) from 15 to 18 July 2023, at the USGS EROS Ground Validation Radiometer (GVR) site in Sioux Falls, South Dakota, USA, over a 160 m × 160 m vegetated area. Absolute calibration accuracy was evaluated by comparing UAS sensor-derived reflectance to in situ measurements of the site. Results indicate that the Headwall Nano-Hyperspec and MicaSense sensors underestimated reflectance by approximately 0.05 and 0.015 reflectance units, respectively. While the MicaSense sensor demonstrated better inherent radiometric accuracy, it exhibited saturation over bright targets due to limitations in its automatic gain and exposure settings. Application of the ELM using just two calibration targets reduced discrepancies to within 0.005 reflectance units. Reflectance products generated using various target materials—such as felt, melamine, or commercially available validation targets—showed comparable agreement with in situ measurements when used with the Nano-Hyperspec sensor. Furthermore, increasing the number of calibration targets beyond two did not yield measurable improvements in calibration accuracy. At a flight altitude of 200 ft above ground level (AGL), a target size of 0.6 m × 0.6 m or larger was sufficient to provide pure pixels for ELM implementation, whereas smaller targets (e.g., 0.3 m × 0.3 m) posed challenges in isolating pure pixels. Overall, the standard manufacturer-recommended calibration procedures were insufficient for achieving high radiometric accuracy with the tested sensors, which may restrict their applicability in scenarios requiring greater accuracy and precision. The use of the ELM significantly improved data quality, enhancing the reliability and applicability of UAS-based remote sensing in contexts requiring high precision and accuracy.

Remote Sensing↗
USGS2008

Evaluation and comparison of the IRS-P6 and the landsat sensors

The Indian Remote Sensing Satellite (IRS-P6), also called ResourceSat-1, was launched in a polar sun-synchronous orbit on October 17, 2003. It carries three sensors: the highresolution Linear Imaging Self-Scanner (LISS-IV), the mediumresolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide-Field Sensor (AWiFS). These three sensors provide images of different resolutions and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to images from the Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus (ETM+) sensors. The approach involves calibration of surface observations based on image statistics from areas observed nearly simultaneously by the two sensors. This paper also evaluated the viability of data from these nextgeneration imagers for use in creating three National Land Cover Dataset (NLCD) products: land cover, percent tree canopy, and percent impervious surface. Individual products were consistent with previous studies but had slightly lower overall accuracies as compared to data from the Landsat sensors.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2015

Validation of mercury tip-switch and accelerometer activity sensors for identifying resting and active behavior in bears

Activity sensors are often included in wildlife transmitters and can provide information on the behavior and activity patterns of animals remotely. However, interpreting activity-sensor data relative to animal behavior can be difficult if animals cannot be continuously observed. In this study, we examined the performance of a mercury tip-switch and a tri-axial accelerometer housed in collars to determine whether sensor data can be accurately classified as resting and active behaviors and whether data are comparable for the 2 sensor types. Five captive bears (3 polar [ Ursus maritimus ] and 2 brown [ U. arctos horribilis ]) were fitted with a collar specially designed to internally house the sensors. The bears’ behaviors were recorded, classified, and then compared with sensor readings. A separate tri-axial accelerometer that sampled continuously at a higher frequency and provided raw acceleration values from 3 axes was also mounted on the collar to compare with the lower resolution sensors. Both accelerometers more accurately identified resting and active behaviors at time intervals ranging from 1 minute to 1 hour (≥91.1% accuracy) compared with the mercury tip-switch (range = 75.5–86.3%). However, mercury tip-switch accuracy improved when sampled at longer intervals (e.g., 30–60 min). Data from the lower resolution accelerometer, but not the mercury tip-switch, accurately predicted the percentage of time spent resting during an hour. Although the number of bears available for this study was small, our results suggest that these activity sensors can remotely identify resting versus active behaviors across most time intervals. We recommend that investigators consider both study objectives and the variation in accuracy of classifying resting and active behaviors reported here when determining sampling interval.

Ursus↗
USGS2009

Global Positioning System surveys of storm-surge sensors deployed during Hurricane Ike, Seadrift, Texas, to Lake Charles, Louisiana, 2008

The U.S. Geological Survey installed a network of pressure sensors at 65 sites along the Gulf Coast from Seadrift, Texas, northeast to Lake Charles, Louisiana, to record the timing, areal extent, and magnitude of inland storm surge and coastal flooding caused by Hurricane Ike in September 2008. A Global Positioning System was used to obtain elevations of reference marks near each sensor. A combination of real-time kinematic (RTK) and static Global Positioning System surveys were done to obtain elevations of reference marks. Leveling relative to reference marks was done to obtain elevations of sensor orifices above the reference marks. This report summarizes the Global Positioning System data collected and processed to obtain reference mark and storm-sensor-orifice elevations for 59 storm-surge sensors recovered from the original 65 installed as a necessary prelude to computation of storm-surge elevations. National Geodetic Survey benchmarks were used for RTK surveying. Where National Geodetic Survey benchmarks were not within 12 kilometers of a sensor site, static surveying was done. Additional control points for static surveying were in the form of newly established benchmarks or reestablished existing benchmarks. RTK surveying was used to obtain positions and elevations of reference marks for 29 sensor sites. Static surveying was used to obtain positions and elevations of reference marks for 34 sensor sites; four sites were surveyed using both methods. Multiple quality checks on the RTK-survey and static-survey data were applied. The results of all quality checks indicate that the desired elevation accuracy for the surveys of this report, less than 0.1-meter error, was achieved.

Louisiana, Texas↗
USGS2012

In situ optical water-quality sensor networks - Workshop summary report

Advanced in situ optical water-quality sensors and new techniques for data analysis hold enormous promise for furthering scientific understanding of aquatic systems. These sensors measure important biogeochemical parameters for long deployments, enabling the capture of data at time scales over which they vary most meaningfully. The high-frequency, real-time water-quality data they generate provide opportunities for early warning of water-quality deterioration, trend detection, and science-based decision support. However, developing networks of optical sensors in freshwater systems that report reliable and comparable data across and between sites remains a challenge to the research and monitoring community. To address this, the U. S. Geological Survey (USGS) and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) convened a joint 3-day workshop (June 8-10, 2011) at the National Conservation Training Center in Shepardstown, West Virginia, to explore ways to coordinate development of standards and applications for optical sensors, and improve handling, storing, and analyzing the continuous data they produce. The workshop brought together more than 60 scientists, program managers, and vendors from universities, government agencies, and the private sector. Several important outcomes emerged from the presentations and breakout sessions. There was general consensus that making intercalibrated measurements requires that both manufacturers and users better characterize and calibrate the sensors under field conditions. For example, the influence of suspended particles, highly colored water, and temperature on optical sensors remains poorly understood, but consistently accounting for these factors is critical to successful deployment and for interpreting results in different settings. This, in turn, highlights the lack of appropriate standards for sensor calibrations, field checks, and characterizing interferences, as well as methods for data validation, treatment, and analysis of resulting measurements. Participants discussed a wide range of logistical considerations for successful sensor deployments, including key physical infrastructure, data loggers, and remote-communication techniques. Tools to manage, assure, and control quality, and explore large streams of continuous water-quality data are being developed by the USGS, CUAHSI, and other organizations, and will be critical to making full use of these highfrequency data for research and monitoring.

Open-File Report↗
USGS2015

ShakeNet: a portable wireless sensor network for instrumenting large civil structures

We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software.

Open-File Report↗
USGS2020

Field comparison of five in situ turbidity sensors

Five commercially available turbidity sensors were field tested by the U.S. Geological Survey Hydrologic Instrumentation Facility for accuracy and data comparability. The tested sensors were the Xylem EXO (EXO), the Hach Solitax sc (Solitax), the In Situ Aqua TROLL sensor installed onto a TROLL 600 sonde (TROLL 600), the Campbell Scientific OBS501 (OBS501), and the Observator ANALITE NEP–5000 (NEP–5000). The sensors were deployed at Pearl River at National Space Technology Laboratories Station, Mississippi (U.S. Geological Survey site 02492620), and were serviced weekly. In addition to the five in situ turbidity sensors, corresponding discrete samples were collected and analyzed during the evaluation on a calibrated Hach 2100N benchtop turbidimeter. The OBS501 malfunctioned early in the evaluation and eventually failed, resulting in few data from the sensor. During this study, the four remaining sensors (minus the OBS501) changed similarly throughout the field test; however, sensor data from the EXO consistently demonstrated lower results than the Solitax, TROLL 600, and NEP–5000, possibly because of the variation in raw signal processing among manufacturers. Results from a single factor analysis of variance test and a Tukey Honestly Significant Difference test verified the low bias observed in the EXO data and indicated there was a significant difference between the EXO data and data from the Solitax, TROLL 600, and NEP–5000 but an insignificant difference among the data when the Solitax, TROLL 600, and NEP–5000 were compared to each other.

Mississippi↗
USGS2023

Interim guidance for calibration checks on a submersible acoustic backscatter sediment sensor

Over the past two decades, the U.S. Geological Survey (USGS) and other agencies have pioneered the use of active acoustic sensors to monitor suspended-sediment concentrations and particle sizes in rivers and streams at the subdaily time scale. The LISST-ABS submersible acoustic backscatter sediment sensor (or “ABS sensor”) was developed by Sequoia Scientific, Inc., as an alternative to turbidity sensors for monitoring suspended-sediment concentrations in surface waters. The ABS sensor is different than traditional active acoustic instruments because it is small, lower in cost, lightweight, and requires less power; and the sampling volume is within the first 15 centimeters of the transducer face. Initial testing by the USGS indicated the ABS sensor had utility as a novel, cost-effective, off-the-shelf tool for monitoring suspended-sediment concentration in surface waters, and its use within the agency has increased in since its introduction around 2016. However, initial testing did not account for the potential of transducer calibration drift over longer deployments. As part of its mission to unify and standardize research and development activities of Federal agencies involved in fluvial sediment studies, the Federal Interagency Sedimentation Project partnered with the USGS Wyoming-Montana and New Mexico Water Science Centers to examine the potential for use of standard, low-tech laboratory equipment to perform calibration checks on ABS sensors on long-term deployments. The experiments were intended to provide USGS scientists and the public with interim guidance to assist in operating and maintaining the ABS sensor.

Open-File Report↗
USGS1980

Considerations for blending data from various sensors

A project is being proposed at the EROS Data Center to blend the information from sensors aboard various satellites. The problems of, and considerations for, blending data from several satellite-borne sensors are discussed. System descriptions of the sensors aboard the HCMM, TIROS-N, GOES-D, Landsat 3, Landsat D, Seasat, SPOT, Stereosat, and NOSS satellites, and the quantity, quality, image dimensions, and availability of these data are summaries to define attributes of a multi-sensor satellite data base. Unique configurations of equipment, storage, media, and specialized hardware to meet the data system requirement are described as well as archival media and improved sensors that will be on-line within the next 5 years. Definitions and rigor required for blending various sensor data are given. Problems of merging data from the same sensor (intrasensor comparison) and from different sensors (intersensor comparison), the characteristics and advantages of cross-calibration of data, and integration of data into a product matrix field are addressed. Data processing considerations as affected by formation, resolution, and problems of merging large data sets, and organization of data bases for blending data are presented. Examples utilizing GOES and Landsat data are presented to demonstrate techniques of data blending, and recommendations for future implementation of a set of standard scenes and their characteristics necessary for optimal data blending are discussed.

Sixth Annual Pecora Symposium and Exposition↗
USGS2010

Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites

The ability to detect and quantify changes in the Earth's environment depends on sensors that can provide calibrated, consistent measurements of the Earth's surface features through time. A critical step in this process is to put image data from different sensors onto a common radiometric scale. This work focuses on monitoring the long-term on-orbit calibration stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using the Committee on Earth Observation Satellites (CEOS) reference standard pseudo-invariant test sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5). These sites have been frequently used as radiometric targets because of their relatively stable surface conditions temporally. This study was performed using all cloud-free calibrated images from the Terra MODIS and the L7 ETM+ sensors, acquired from launch to December 2008. Homogeneous regions of interest (ROI) were selected in the calibrated images and the mean target statistics were derived from sensor measurements in terms of top-of-atmosphere (TOA) reflectance. For each band pair, a set of fitted coefficients (slope and offset) is provided to monitor the long-term stability over very stable pseudo-invariant test sites. The average percent differences in intercept from the long-term trends obtained from the ETM + TOA reflectance estimates relative to the MODIS for all the CEOS reference standard test sites range from 2.5% to 15%. This gives an estimate of the collective differences due to the Relative Spectral Response (RSR) characteristics of each sensor, bi-directional reflectance distribution function (BRDF), spectral signature of the ground target, and atmospheric composition. The lifetime TOA reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.4% per year in its TOA reflectance over the CEOS reference standard test sites.

Remote Sensing of Environment↗
USGS2013

Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations

The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. The results indicate that the TOA reflectance measurements for ALI agree with those of ETM+ and MODIS to within 5% after the application of SBAF.

Arabia↗
USGS2019

Landsat 1-5 Multispectral Scanner System (MSS) sensors radiometric calibration update

First launched in 1972, the Landsat satellite sensors have provided the longest continuous record of high quality images of the Earth’s surface that are used in both civilian and military applications. The Landsat Multispectral Scanner (MSS) sensor was on-board Landsat-1 through Landsat-5. In fact, the MSS sensors provide the only systematic global multispectral space-based imagery of the Earth’s surface from 1972 to 1982. This paper focuses on the radiometric calibration update of the Landsat 1-5 MSS sensors. The radiometric calibration was performed in both radiance and reflectance-based scales through cross-calibration approach. Simultaneous or a near simultaneous image collections were available for MSS sensor pairs and used for the cross-calibration. The estimated uncertainties for this calibration update exhibit progressively decreasing calibration accuracy, ranging from 5.1% for MSS 5 to 8.8% for MSS-1 in the Green spectral band, for example. Lastly, the new radiometric calibration coefficients were validated through the use of pseudo invariant calibration sites (PICS). The temporal TOA Radiance and TOA Reflectance over the Sonoran Desert were plotted with the purpose of verifying the lifetime radiometric stability of MSS sensors. With the previous calibration, the agreement between the measurements of TOA Reflectance over the Sonoran Desert was around 7.5% for all spectral bands. With the calibration update implemented in this study, the agreement between MSS sensors is 3.6%, 2.9%, 3.5% and 5.9% for the Green, Red, NIR-1 and NIR 2 spectral bands, respectively. This study ties all the Landsat legacy instruments from Landsat-1 MSS through Landsat-8 OLI to a consistent radiometric scale.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2015

Laboratory and field tests of the Sutron RLR-0003-1 water level sensor

Three Sutron RLR-0003-1 water level sensors were tested in laboratory conditions to evaluate the accuracy of the sensor over the manufacturer’s specified operating temperature and distance-to-water ranges. The sensor was also tested for compliance to SDI-12 communication protocol and in field conditions at a U.S. Geological Survey (USGS) streamgaging site. Laboratory results were compared to the manufacturer’s accuracy specification for water level and to the USGS Office of Surface Water (OSW) policy requirement that water level sensors have a measurement uncertainty of no more than 0.01 foot or 0.20 percent of the indicated reading. Except for one sensor, the differences for the temperature testing were within 0.05 foot and the average measurements for the sensors were within the manufacturer’s accuracy specification. Two of the three sensors were within the manufacturer’s specified accuracy and met the USGS accuracy requirements for the laboratory distance to water testing. Three units passed a basic SDI-12 communication compliance test. Water level measurements made by the Sutron RLR-0003-1 during field testing agreed well with those made by the bubbler system and a Design Analysis Associates (DAA) H3613 radar, and they met the USGS accuracy requirements when compared to the wire-weight gage readings.

Open-File Report↗
USGS2016

Laboratory evaluation of the Design Analysis Associates DAA H-3613i radar water-level sensor—Results of temperature, distance, and SDI-12 tests

The Design Analysis Associates (DAA) DAA H-3613i radar water-level sensor (DAA H-3613i), manufactured by Xylem Incorporated, was evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to manufacturer’s accuracy specifications for measuring a distance throughout the sensor’s operating temperature range, for measuring distances from 3 to 15 feet at ambient temperatures, and for compliance with the SDI-12 serial-to-digital interface at 1200-baud communication standard. The DAA H-3613i is a noncontact water-level sensor that uses pulsed radar to measure the distance between the radar and the water surface from 0.75 to 131 feet over a temperature range of −40 to 60 degrees Celsius (°C). Manufacturer accuracy specifications that were evaluated, the test procedures that followed, and the results obtained are described in this report. The sensor’s accuracy specification of ± 0.01 feet (± 3 millimeters) meets USGS requirements for a primary water-stage sensor used in the operation of a streamgage. The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during temperature testing at a distance of 8 feet from the target over its temperature-compensated operating range of −40 to 60 °C, except at 60 °C. At 60 °C, about half the measurements exceeded the manufacturer’s accuracy specification by not more than 0.005 feet.The sensor met the manufacturer’s stated accuracy specifications for water-level measurements during distance-accuracy testing at the tested distances from 3 to 15 feet above the water surface at the HIF.

Open-File Report↗
USGS2017

Evaluation of the Hydrolab HL4 water-quality sonde and sensors

The U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility evaluated three Hydrolab HL4 multiparameter water-quality sondes by OTT Hydromet. The sondes were equipped with temperature, conductivity, pH, dissolved oxygen (DO), and turbidity sensors. The sensors were evaluated for compliance with the USGS National Field Manual for the Collection of Water-Quality Data (NFM) criteria for continuous water-quality monitors and to verify the validity of the manufacturer’s technical specifications. The conductivity sensors were evaluated for the accuracy of the specific conductance (SC) values (conductance at 25 degrees Celsius [ o C]), that were calculated by using the vendor default method, Hydrolab Fresh. The HL4’s communication protocols and operating temperature range along with accuracy of the water-quality sensors were tested in a controlled laboratory setting May 1–19, 2016. To evaluate the sonde’s performance in a surface-water field application, an HL4 equipped with temperature, conductivity, pH, DO, and turbidity sensors was deployed June 20–July 22, 2016, at USGS water-monitoring site 02492620, Pearl River at National Space Technology Laboratories (NSTL) Station, Mississippi, located near Bay Saint Louis, Mississippi, and compared to the adjacent well-maintained EXO2 site sonde. The three HL4 sondes met the USGS temperature testing criteria and the manufacturer’s technical specifications for temperature based upon the median room temperature difference between the measured and standard temperatures, but two of the three sondes exceeded the allowable difference criteria at the temperature extremes of approximately 5 and 40 ºC. Two sondes met the USGS criteria for SC. One of the sondes failed the criteria for SC when evaluated in a 100,000-microsiemens-per-centimeter (μS/cm) standard at room temperature, and also failed in a 10,000-μS/cm standard at 5, 15, and 40 ºC. All three sondes met the USGS criteria for pH and DO at room temperature, but one sonde exceeded the allowable difference criteria when tested in pH 5.00 buffer and at 40 ºC. The USGS criteria and the technical specifications for turbidity were met by one sonde in standards ranging from 10 to 3,000 nephelometric turbidity units (NTU). A second sonde met the USGS criteria and the technical specifications except in the 3,000-NTU standard, and the third sonde exceeded the USGS calibration criteria in the 10- and 20-NTU standards and the technical specifications in the 20-NTU standard. Results of the field test showed acceptable performance and revealed that differences in data sample processing between sonde manufacturers may result in variances between the reported measurements when comparing one sonde to another. These variances in data would be more pronounced in dynamic site conditions. The lack of a wiper or other sensor-cleaning device on the DO sensor could prove problematic, and could limit the use of the HL4 to profiling applications or at sites with limited biofouling.

Open-File Report↗
USGS1985

Description and preliminary testing of the CDSN Seismic Sensor Systems

The China Digital Seismograph Network (CDSN) is being designed and installed to provide the People's Republic of China with the facilities needed to create a national digital database for earthquake research. The CDSN, which is being developed jointly by the PRC State Seismological Bureau and the U.S. Geological Survey, will consist initially of nine digitally-recording seismograph stations, a data management system to be used for compiling network-day tapes, and a depot maintenance center. Data produced by the network will be shared with research scientists throughout the world. A national seismograph network must be designed to support a variety of research objectives. From this standpoint, the choices and tradeoffs involved in specifying signal bandwidth, resolution, and dynamic range are the most important decisions in system design. As in the case of the CDSN, these decisions are made during the selection and design of the seismic sensor system and encoder components. The purpose of this report is to describe the CDSN sensor systems, their important signal characteristics, and the results of preliminary tests that have been performed on the instruments. Four overlapping data bands will be recorded at each station: short period (SP), broadband (BB), long period (LP), and very long period (VLP). Amplitude response curves are illustrated in Figure I. Vertical and horizontal components will be recorded for each data band. The SP and LP channels will be recorded with sufficient sensitivities to resolve earth background noise at seismically quiet sites. The BB channels will have a lower sensitivity and are intended for broadband recording of moderate-to-large body-wave signals and for increasing the effective amplitude range in the short- and long-period bands. The VLP channel does not provide additional spectral coverage at long periods; its purpose is to make use of on-site filtration and decimation to reduce post processing requirements for VLP studies. Early plans also included a triaxial set of low-sensitivity accelerometers for recording strong signals from large local and regional earthquakes. The accelerometers are not being installed; however, they may be added in the future. The short-period signals will be derived from a three-component set of PRC-supplied Model DJ-I SP seismometers and US-supplied SP amplifiers. The seismometers will be installed in surface or shallow subsurface vaults, except at two of the stations where they will be installed in boreholes. The BB, LP, and VLP signals will be derived from Streckeisen STS-1 broadband sensor systems installed in vaults, except at one site where the LP signals only will-be derived from a KS-36000 borehole seismometer installed at a depth of 100 meters. Analog signals will be sampled and quantized by an analog-to-digital converter (ADC) that is part of the recording system. Sampling rates chosen for the CDSN are as follows: * SP 40 samples/second * BB 20 samples/second * LP 1 sample/second * VLP 6 samples/minute The ADC 16-bit data word format makes use of 14 bits to quantize the signal and 2 bits to specify an automatically ranged gain of 1, 8, 32, or 128. This will provide 84 dB of resolution and up to 42 dB of gain ranging for a total opera- ting range of 126 dB peak to peak. Magnetic tape cartridges, each having a capacity of 67 megabytes, will be used for recording the digital data. LP and VLP data will be recorded continu- ously. SP and BB data will be processed through an automatic signal detector of the type described by Murdock and Hutt (1983), and only detected events will be stored on tape. Detection parameters, such as turn-on sensitivity and mini- mum recording duration for the SP and BB channels, will be fully programmable and easily changed. One or more of the data channels may also be recorded on analog recorders. A CDSN recording system was not available at the time that the preliminary tests were performed on the CDSN sensor systems. This did not interfere with the principal goals of the testing which were to determine the best sensor installation techniques and to demonstrate the operational performance of the sensor systems, especially with regard to instrument noise and detection capability. When the CDSN recording system is available, additional tests will be performed to measure distortion levels in the full system and components. Distortion tests have been performed on the Streckeisen STS-1 broadband seismometers, the most critical component from the standpoint of linearity, and the results of the tests are reported by Wielandt and Streckeisen (1982). Calibration accuracy and stability are also important sensor system characteristics that cannot be defined without additional testing. These tests will be performed as the instruments are installed at the stations and periodically during operation.

Open-File Report↗
USGS1994

Proceedings of a U.S. Geological Survey pressure-sensor Workshop, Denver, Colorado, July 28-31, 1992

The U.S. Geological Survey (USGS) conducted a Pressure Sensor Workshop, oriented toward the measurement of stage in surface waters, in Denver, Colorado, July 28-31, 1992. Twenty attendees from the U.S. Geological Survey and the National Oceanic and Atmospheric Administration gave presentations concerning their experiences with the use of pressure sensors in hydrologic investigations. This report is a compilation of the abstracts of the presentations made at the workshop. Workshop participants concluded that each of the sensors evaluated by the U.S. Geological Survey has strengths and weaknesses. Personnel contemplating the use of pressure sensors discussed at this workshop should contact workshop attendees and consult with them about their experiences with those sensors. The attendees preferred to use stilling wells with float-operated water-level sensors as the primary means for monitoring water levels. However, pressure sensor systems were favored as replacements for mercury manometers and as alternatives to stilling wells at sites where stilling wells are not practical or cost effective.

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