scholarly journals Trolley Operated Automatic Discharge System (TOADS)—An automated system for horizontal profiling of water velocity and river discharge measurements

Fact Sheet ◽  
2021 ◽  
Author(s):  
Kevin K. Johnson ◽  
Clayton J. Bosch
Keyword(s):  
River Discharge ◽  
Water Velocity ◽  
Automated System ◽  
Discharge System ◽  
Discharge Measurements

scholarly journals Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

2014 ◽  
Vol 18 (11) ◽  
pp. 4467-4484 ◽  
Author(s):  
B. Revilla-Romero ◽  
J. Thielen ◽  
P. Salamon ◽  
T. De Groeve ◽  
G. R. Brakenridge
Keyword(s):  
Real Time ◽  
River Discharge ◽  
Detection System ◽  
Poor Performance ◽  
Model Verification ◽  
Area Index ◽  
General Terms ◽  
Skill Scores ◽  
Flood Detection ◽  
Discharge Measurements

Abstract. One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real-time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real-time ground observations are not available. These include several international river locations in Africa: the Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (random forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measure\\-ment sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1km; a large floodplain area and in flooded forest, a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; leaf area index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. This work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

Optimizing river discharge measurements using Monte Carlo Markov Chain

2012 ◽  
Vol 450-451 ◽  
pp. 199-205 ◽  
Author(s):  
Borko D. Stošić ◽  
José Rodrigo Santos Silva ◽  
Moacyr Cunha Filho ◽  
Jose Ramon Barros Cantalice
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
River Discharge ◽  
Monte Carlo Markov Chain ◽  
Discharge Measurements

Methodology for improving reliability of river discharge measurements

2019 ◽  
Vol 247 ◽  
pp. 371-384 ◽  
Author(s):  
E.S. Bekri ◽  
P.C. Yannopoulos ◽  
P. Economou
Keyword(s):  
River Discharge ◽  
Discharge Measurements

scholarly journals Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin

2018 ◽  
Author(s):  
Jiawei Hou ◽  
Albert I. J. M. van Dijk ◽  
Luigi J. Renzullo ◽  
Robert A. Vertessy
Keyword(s):  
Surface Water ◽  
River Discharge ◽  
Water Resource Management ◽  
Amazon Basin ◽  
Water Cycle ◽  
Detection System ◽  
Optical Data ◽  
Large Area ◽  
Discharge Measurements

Abstract. River discharge measurements have proven invaluable to monitor the global water cycle, assess flood risk, and guide water resource management. However, there is a delay and overall decline in the availability of gauging data and stations are highly unevenly distributed globally. While not a substitute for river discharge measurement, remote sensing is a cost-effective technology to acquire information on river dynamics. The general approach has been to relate satellite observation to discharge measured in situ, which prevents its use for ungauged rivers. Alternatively, hydrological models are now available that can be used to estimate river discharge globally. While subject to greater errors and biases than measurements, model estimates of river discharge do expand the options for applying satellite-based discharge monitoring in ungauged rivers. Our aim was to test this approach. We used gridded surface water extent information from two sources: (1) Global Flood Detection System (GFDS) passive microwave data; and (2) MODIS optical data. The data were available for the common period of 2000–2014. The hydrological model used was the World-Wide Water (W3) model version 2, providing river discharge from 1980 to 2014. We designed and compared two methods to relate simulated storage and discharge to MODIS and GFDS surface water extent fraction for developing satellite gauging reaches (SGRs), and applied the best performing method to construct SGRs across the Amazon Basin. River discharge estimates from MODIS SGRs, GFDS SGRs, and the W3 model were evaluated with in situ river discharge measurements. The results showed SGRs can be successfully established over a large area using MODIS and GFDS water extent and modelled discharge, and used to estimate river discharge at both gauged and ungauged sites.

scholarly journals Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

2014 ◽  
Vol 11 (7) ◽  
pp. 7331-7374 ◽  
Author(s):  
B. Revilla-Romero ◽  
J. Thielen ◽  
P. Salamon ◽  
T. De Groeve ◽  
G. R. Brakenridge
Keyword(s):  
Real Time ◽  
River Discharge ◽  
Detection System ◽  
Poor Performance ◽  
Model Verification ◽  
Area Index ◽  
General Terms ◽  
Skill Scores ◽  
Flood Detection ◽  
Discharge Measurements

Abstract. One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real time ground observations are not available. These include several international river locations in Africa: Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (Random Forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measurement sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1 km; a large floodplain area and in flooded forest; with a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; Leaf Area Index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. The work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

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