scholarly journals High-frequency monitoring of stream water physicochemistry on sub-Antarctic Marion Island

Water SA ◽  
2018 ◽  
Vol 44 (2 April) ◽  
Author(s):  
M-J Stowe ◽  
DW Hedding ◽  
FD Eckardt ◽  
W Nel
Keyword(s):  
Electrical Conductivity ◽  
High Resolution ◽  
Water Temperature ◽  
Total Variation ◽  
High Frequency ◽  
Stream Water ◽  
Precipitation Event ◽  
Induced Response ◽  
Marion Island ◽  
Frequency Monitoring

Given the remoteness and challenging environmental conditions on sub-Antarctic Marion Island, continuous high-resolution studies of the island’s natural water systems are rare. Subsequently, current understanding of the island’s hydrochemistry is based entirely on manual point-based measurements. To address this research gap we analysed continuous, in-situ high-frequency physicochemical measurements (pH, water temperature, dissolved oxygen (DO), and electrical conductivity (EC)) from the Soft Plume River over the period 21 April 2015–26 April 2015. We observed a sharp, short-term response from all measurements to a precipitation event that was superimposed on consistent but subtle diel (i.e. 24 h) cycles throughout the study. Total variation in pH and electrical conductivity amounted to 1.3 units and 27.7 μS/cm respectively. Stream water temperature was less variable (6.2°C) than air surface temperature (14.2°C). Total variation in DO was 2.0 mg/L. Aside from the precipitation-induced response, diel oscillations were small and only visible through the use of continuous, high-resolution monitoring. Findings highlight the advantages of continuous high-frequency monitoring in capturing the range of daily variation and elucidating diel cycles in stream water physicochemistry on sub-Antarctic Marion Island that have not previously been accounted for.

scholarly journals High-resolution monitoring of nutrients in groundwater and surface waters: process understanding, quantification of loads and concentrations, and management applications

2016 ◽  
Vol 20 (9) ◽  
pp. 3619-3629 ◽  
Author(s):  
Frans C. van Geer ◽  
Brian Kronvang ◽  
Hans Peter Broers
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Temporal Trends ◽  
Surface Water Quality ◽  
Mitigation Measures ◽  
Nutrient Concentrations ◽  
Special Issue ◽  
Monitoring Strategies ◽  
Frequency Monitoring ◽  
Water Quality And Quantity

Abstract. Four sessions on "Monitoring Strategies: temporal trends in groundwater and surface water quality and quantity" at the EGU conferences in 2012, 2013, 2014, and 2015 and a special issue of HESS form the background for this overview of the current state of high-resolution monitoring of nutrients. The overview includes a summary of technologies applied in high-frequency monitoring of nutrients in the special issue. Moreover, we present a new assessment of the objectives behind high-frequency monitoring as classified into three main groups: (i) improved understanding of the underlying hydrological, chemical, and biological processes (PU); (ii) quantification of true nutrient concentrations and loads (Q); and (iii) operational management, including evaluation of the effects of mitigation measures (M). The contributions in the special issue focus on the implementation of high-frequency monitoring within the broader context of policy making and management of water in Europe for support of EU directives such as the Water Framework Directive, the Groundwater Directive, and the Nitrates Directive. The overview presented enabled us to highlight the typical objectives encountered in the application of high-frequency monitoring and to reflect on future developments and research needs in this growing field of expertise.

scholarly journals Karst hydrogeology of Lamprechtsofen (Leoganger Steinberge, Salzburg)

2019 ◽  
Vol 112 (1) ◽  
pp. 50-61 ◽  
Author(s):  
Katharina Gröbner ◽  
Wolfgang Gadermayr ◽  
Giorgio Höfer-Öllinger ◽  
Harald Huemer ◽  
Christoph Spötl
Keyword(s):  
Electrical Conductivity ◽  
Water Temperature ◽  
Water Level ◽  
Stream Water ◽  
Tracer Tests ◽  
Karst Water ◽  
Stream Flows ◽  
Surface Precipitation ◽  
Mineralized Water ◽  
Show Cave

AbstractThe Leoganger Steinberge are a heavily karstified massif largely composed of Dachstein dolomite and limestone hosting the deepest through-trip cave in the world, Lamprechtsofen, whose frontal parts are developed as a show cave. Many parts of this 60 km-long and 1724 m-deep system are hydrologically active. 1.5 km behind the lower cave entrance Grüntopf stream and Kneippklamm stream merge to form the main cave stream. Another underground stream, Stainerhallen stream, flows through the eponymous hall of the show cave. Since 2007 water temperature, electrical conductivity and water level have been monitored in the Grüntopf and Kneippklamm stream. Water temperature and water level in the Stainerhallen and main cave stream have been measured since 2016.The long-term dataset (2013–2017) shows that the water temperature of the cave streams (Grüntopf stream: 3.7–5.2°C; Kneippklamm stream: 5.1–5.9°C) is largely invariant, but the electrical conductivity varies strongly (Grüntopf stream: 107–210 µS/cm; Kneippklamm stream: 131–248 µS/cm) in response to snowmelt and precipitation events. The event water of the Kneippklamm stream is characterized by a low electrical conductivity and is then followed by slightly warmer and higher mineralized water derived from the phreatic zone. This dual flow pattern also explains the asymmetrical changes of the water level during snowmelt: the fast event water flows directly through vadose pathways to the measurement site, whereas the hydraulic (phreatic) response is delayed. The Grüntopf stream reacts to precipitation and snowmelt events by changes in the karst-water table, which can be explained by a piston flow-model. The Kneippklamm stream reveals evidence of a lifter system.The altitude of the catchments was calculated using δ18O values of water samples from the underground streams and from surface precipitation. The Grüntopf stream shows the highest mean catchment (2280 m a.s.l.), which is in agreement with its daily fluctuations of the water level until August caused by long-lasting snowmelt. The Stainerhallen stream has the lowest catchment (average 1400 m a.s.l.). The catchments of the other two streams are at intermediate elevations (1770–1920 m a.s.l.). The integration of the catchment analyses and observations from tracer tests conducted in the 1970s showed that the latter reflected only one aspect of the karst water regime in this massif. During times of high recharge the water level rises, new flow paths are activated and the karst watershed shifts.

scholarly journals Successful forecasting of harmful cyanobacteria blooms with high frequency lake data

2019 ◽  
Author(s):  
M.J. Kehoe ◽  
B.P. Ingalls ◽  
J.J. Venkiteswaran ◽  
H.M. Baulch
Keyword(s):  
Water Temperature ◽  
High Frequency ◽  
Cyanobacterial Blooms ◽  
Forecasting Accuracy ◽  
Forecasting Models ◽  
Treatment Processes ◽  
Cyanobacteria Blooms ◽  
Frequency Monitoring ◽  
Sparse Measurements ◽  
Derivatives Of

AbstractCyanobacterial blooms are causing increasing issues across the globe. Bloom forecasting can facilitate adaptation to blooms. Most bloom forecasting models depend on weekly or fortnightly sampling, but these sparse measurements can miss important dynamics. Here we develop forecasting models from five years of high frequency summer monitoring in a shallow lake (which serves as an important regional water supply). A suite of models were calibrated to predict cyanobacterial fluorescence (a biomass proxy) using measurements of: cyanobacterial fluorescence, water temperature, light, and wind speed. High temporal autocorrelation contributed to relatively strong predictive power over 1, 4 and 7 day intervals. Higher order derivatives of water temperature helped improve forecasting accuracy. While traditional monitoring and modelling have supported forecasting on longer timescales, we show high frequency monitoring combined with telemetry allows forecasting over timescales of 1 day to 1 week, supporting early warning, enhanced monitoring, and adaptation of water treatment processes.

scholarly journals High resolution monitoring of nutrients in groundwater and surface waters: process understanding, quantification of loads and concentrations and management applications

2016 ◽  
Author(s):  
F. C. van Geer ◽  
B. Kronvang ◽  
H. P. Broers
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Spatial Scales ◽  
Temporal Trends ◽  
Surface Water Quality ◽  
Mitigation Measures ◽  
Nutrient Concentrations ◽  
Special Issue ◽  
Frequency Monitoring ◽  
Eu Directives

Abstract. Four sessions on "Monitoring Strategies: temporal trends in groundwater and surface water quality and quantity" at the EGU-conferences in 2012, 2013, 2014 and 2015 and a special issue of HESS form the background for this overview of the current state of high resolution monitoring of nutrients. The overview includes a summary of technologies applied in high frequency monitoring of nutrients in the special issue. Moreover, we present a new assessment of the objectives behind high frequency monitoring as classified into three main groups: (i) improved understanding of the underlying hydrological, chemical and biological processes (PU); (ii) quantification of true nutrient concentrations and loads (Q); (iii) operational management, including evaluation of the effects of mitigation measures (M). The contributions in the special issue focus on the implementation of high frequency monitoring within the broader context of policy making and management in Europe for support of EU Directives such as the Water Framework Directive, the Groundwater Directive and the Nitrate Directive. The overview presented based on the special issue and the presentations at the four EGU sessions enabled us to highlight the typical objectives encountered in the application of high frequency monitoring to support EU Directives, to assess the temporal and spatial scales and to reflect on future developments and research needs in this growing field of expertise.

scholarly journals A Simple Solution for Refining Lake Water Temperature Profiles Data Arrayed from High-Frequency Monitoring Sensors

2021 ◽  
Vol 6 (1) ◽  
pp. 25
Author(s):  
Arianto Budi Santoso ◽  
Endra Triwisesa ◽  
Muh Fakhrudin
Keyword(s):  
Water Temperature ◽  
High Frequency ◽  
Information Filtering ◽  
Temperature Data ◽  
Simple Solution ◽  
Temperature Profiles ◽  
West Sumatra ◽  
Frequency Monitoring ◽  
Water Temperature Data ◽  
Upper Mixed Layer

The revolutionized aquatic monitoring sensors are essential in capturing environmental patterns that traditional discrete samplings might not be able to. They allow scientists to further synthesize and better conclude processes in aquatic ecosystems. These sensors produce high-frequency data that provide information on a fine temporal scale, even near real-time. The massive quantities of the streamed data, however, create challenges for scientists to grasp the concrete information. Filtering data quality, on the other hand, is another problem scientists might have encountered as sensor accuracy and precision may drift along the line. Hence, quality assurance and quality control might be quite labouring owing to the size of datasets to handle. This paper proposed a semi-mechanistic algorithm to improved false water temperature data. Using “theoretical” thermal stratification as a reference, this algorithm fixed sensors error readings. A 5-month dataset of water temperature profiles of Lake Maninjau, West Sumatra, captured every 10 minutes from a set of sensors in thermistor chain was applied. We found that most data fit to the theoretical temperature profile, R<sup>2</sup> = 0.962, RMSE = 0.081<sup>o</sup>C. A number of errors, however, were observed in the upper layer of the lake (&lt;20 m), the most dynamic layer in terms of its thermal variation. Sensor drifts in this active upper mixed layer can be related to the generated errors. Through this simple solution, not only improving the quality of the observed water temperature data, but was also able to identify the most probable source of errors

scholarly journals PCDRN: Progressive Cascade Deep Residual Network for Pansharpening

2020 ◽  
Vol 12 (4) ◽  
pp. 676 ◽  
Author(s):  
Yong Yang ◽  
Wei Tu ◽  
Shuying Huang ◽  
Hangyuan Lu
Keyword(s):  
High Resolution ◽  
Loss Function ◽  
High Frequency ◽  
Experimental Results ◽  
Superior Performance ◽  
Residual Network ◽  
High Quality ◽  
Convolution Approach ◽  
Visual Assessments ◽  
Coarse To Fine

Pansharpening is the process of fusing a low-resolution multispectral (LRMS) image with a high-resolution panchromatic (PAN) image. In the process of pansharpening, the LRMS image is often directly upsampled by a scale of 4, which may result in the loss of high-frequency details in the fused high-resolution multispectral (HRMS) image. To solve this problem, we put forward a novel progressive cascade deep residual network (PCDRN) with two residual subnetworks for pansharpening. The network adjusts the size of an MS image to the size of a PAN image twice and gradually fuses the LRMS image with the PAN image in a coarse-to-fine manner. To prevent an overly-smooth phenomenon and achieve high-quality fusion results, a multitask loss function is defined to train our network. Furthermore, to eliminate checkerboard artifacts in the fusion results, we employ a resize-convolution approach instead of transposed convolution for upsampling LRMS images. Experimental results on the Pléiades and WorldView-3 datasets prove that PCDRN exhibits superior performance compared to other popular pansharpening methods in terms of quantitative and visual assessments.

scholarly journals Miniaturized high frequency phased array devices for high resolution neonatal and intraoperative imaging

1990 ◽  
Vol 15 (2) ◽  
pp. A10 ◽  
Author(s):  
David J. Sahn ◽  
Diana Tasker ◽  
Sandra Hagen-Ansert ◽  
Axel Brisken ◽  
Scott Corbett
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Phased Array ◽  
Intraoperative Imaging
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