scholarly journals Flexible nonstationary spatiotemporal modeling of high‐frequency monitoring data

2021 ◽  
Author(s):  
Christopher J. Geoga ◽  
Mihai Anitescu ◽  
Michael L. Stein
Keyword(s):  
High Frequency ◽  
Monitoring Data ◽  
Spatiotemporal Modeling ◽  
Frequency Monitoring

The effect of sampling frequency and strategy on water quality modelling driven by high-frequency monitoring data in a boreal catchment

2019 ◽  
Vol 579 ◽  
pp. 124186 ◽  
Author(s):  
Mikołaj Piniewski ◽  
Paweł Marcinkowski ◽  
Jari Koskiaho ◽  
Sirkka Tattari
Keyword(s):  
Water Quality ◽  
High Frequency ◽  
Sampling Frequency ◽  
Monitoring Data ◽  
Water Quality Modelling ◽  
Frequency Monitoring

scholarly journals A New Machine‐Learning Approach for Classifying Hysteresis in Suspended‐Sediment Discharge Relationships Using High‐Frequency Monitoring Data

2018 ◽  
Vol 54 (6) ◽  
pp. 4040-4058 ◽  
Author(s):  
Scott D. Hamshaw ◽  
Mandar M. Dewoolkar ◽  
Andrew W. Schroth ◽  
Beverley C. Wemple ◽  
Donna M. Rizzo
Keyword(s):  
Machine Learning ◽  
Suspended Sediment ◽  
High Frequency ◽  
Monitoring Data ◽  
Learning Approach ◽  
Sediment Discharge ◽  
Machine Learning Approach ◽  
Frequency Monitoring ◽  
New Machine

scholarly journals Estimation of nonlinear water-quality trends in high-frequency monitoring data

2020 ◽  
Vol 715 ◽  
pp. 136686 ◽  
Author(s):  
Guoxiang Yang ◽  
Douglas L. Moyer
Keyword(s):  
Water Quality ◽  
High Frequency ◽  
Monitoring Data ◽  
Frequency Monitoring ◽  
Water Quality Trends

scholarly journals Spatial interpolation of high-frequency monitoring data

2009 ◽  
Vol 3 (1) ◽  
pp. 272-291 ◽  
Author(s):  
Michael L. Stein
Keyword(s):  
High Frequency ◽  
Spatial Interpolation ◽  
Monitoring Data ◽  
Frequency Monitoring

scholarly journals Analysis of slope processes in the Vallcebre landslide (Eastern Pyrenees, Spain) by means of Cross Correlation Function applied to high frequency monitoring data

2016 ◽  
Author(s):  
Marco Mulas ◽  
Jordi Corominas ◽  
Alessandro Corsini ◽  
Jose Moya
Keyword(s):  
Time Series ◽  
Correlation Function ◽  
High Frequency ◽  
Cross Correlation ◽  
Cross Correlation Function ◽  
Monitoring Data ◽  
Eastern Pyrenees ◽  
Landslide Mass ◽  
Frequency Monitoring ◽  
Landslide Zone

Abstract. The Vallcebre landslide is a large slow moving translational slide in the Eastern Pyrenees (Spain). In this work, the Cross-Correlation Function (CCF) method was used in order to quantitatively investigate the time-lagged correlation between high frequency monitoring data on rainfall, piezometric and displacement with the objective to evidence hydro-mechanical processes occurring along the slope. The CCF is a signal processing tool for measuring similarities of time-series waveforms as function of an applied time-lag. Specifically, it was applied in Vallcebre landslide to a 3 years long time series of monitoring data, from 1999 to 2001, with a sampling frequency of 20 minutes. Data were measured in three boreholes instrumented with automated wire-extensometers and piezometers and a rain gauge. The boreholes are lined up down the slope and following the displacement direction, which allowed investigating transfer of landslide mass and groundwater along the slide. Several combinations of time series were analysed: rainfall vs. displacement; rainfall vs. piezometric depth; piezometric depth vs. displacement. Moreover, correlation analysis of displacement and piezometric depth between boreholes was also performed. The CCF analysis highlighted and constrained in time a dual triggering mechanism in which factors controlling movement change along the slide: movement in the lower landslide zone is predominantly influenced by toe erosion whereas in the intermediate and upper landslide zone movement is mostly controlled by groundwater recharge and flow.

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.

Application of High Frequency Monitoring for Classification of Rolling Element Bearing Failures

2001 ◽  
Vol 204-205 ◽  
pp. 173-184 ◽  
Author(s):  
E.D. Price ◽  
A.W. Lees ◽  
Michael I. Friswell
Keyword(s):  
High Frequency ◽  
Rolling Element Bearing ◽  
Bearing Failures ◽  
Rolling Element ◽  
Frequency Monitoring ◽  
Element Bearing
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