Responses of streambed bacterial groups to cycles of low‐flow and erosive floods in a small peri‐urban stream

Ecohydrology ◽  
2020 ◽  
Vol 13 (4) ◽  
Author(s):  
O. Navratil ◽  
M.A. Boukerb ◽  
F. Perret ◽  
P. Breil ◽  
C. Caurel ◽  
...  
Keyword(s):  
Low Flow ◽  
Urban Stream ◽  
Bacterial Groups

Nitrogen patterns in subsurface waters of the Yzeron stream: effect of combined sewer overflows and subsurface–surface water mixing

2013 ◽  
Vol 68 (12) ◽  
pp. 2632-2637 ◽  
Author(s):  
A. M. Aucour ◽  
T. Bariac ◽  
P. Breil ◽  
P. Namour ◽  
L. Schmitt ◽  
...  
Keyword(s):  
Surface Water ◽  
Cold Season ◽  
Low Flow ◽  
Subsurface Water ◽  
Urban Stream ◽  
Nitrogen Forms ◽  
Combined Sewer Overflows ◽  
Combined Sewer ◽  
Subsurface Waters ◽  
Sewer Overflows

Urbanization subjects streams to increased nitrogen loads. Therefore studying nitrogen forms at the interface between urban stream and groundwater is important for water resource management. In this study we report results on water δ18O and nitrogen forms in subsurface waters of a stream (Yzeron, France). The sites studied were located upstream and downstream of combined sewer overflows (CSO) in a rural area and a periurban area, respectively. Water δ18O allowed us to follow the mixing of subsurface water with surface water. Dissolved organic nitrogen and organic carbon of fine sediment increased by 20–30% between rural and periurban subsurface waters in the cold season, under high flow. The highest nitrate levels were observed in rural subsurface waters in the cold season. The lowest nitrate levels were found in periurban subsurface waters in the warm season, under low flow. They corresponded to slow exchange of subsurface waters with channel water. Thus reduced exchange between surface and subsurface waters and organic-matter-rich input seemed to favor nitrate reduction in the downstream, periurban, subsurface waters impacted by CSO.

scholarly journals Artificial Neural Network for Daily Low Stream Flow Rate Prediction of Perigiali Stream, Kavala City, NE Greece

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 578
Author(s):  
Thomas Papalaskaris ◽  
Theologos Panagiotidis
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Flow Rate ◽  
Stream Flow ◽  
Low Flow ◽  
Urban Stream ◽  
Neural Network Modeling ◽  
Rate Data ◽  
Artificial Neural

Only a few scientific research studies with reference to extremely low stream flow conditions, have been conducted in Greece, so far. Forecasting future low stream flow rate values is a crucial and desicive task when conducting drought and watershed management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low flow indices, separating groundwater base flow and storm flow of storm hydrographs etc. Artificial Neural Network modeling simulation method generates artificial time series of simulated values of a random (hydrological in this specific case) variable. The present study produces artificial low stream flow time series of both a part of the past year (2016) as well as the present year (2017) considering the stream flow data observed during two different respecting interval period of the years 2016 and 2017. We compiled an Artificial Neural Network to simulate low stream flow rate data, acquired at a certain location of the partly regulated semi-urban stream which runs through the eastern exit of Kavala city, NE Greece, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The observed data were plotted against the predicted one and the results were demonstrated through interactive tables providing us the ability to effectively evaluate the ANN model simulation procedure performance. Finally, we plot the recorded against the simulated low stream flow rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metrics and calculate the derived model statistics featuring the comparison between the recorded and the forecasted low stream flow rate data.

scholarly journals Stochastic Generation of Low Stream Flow Data of Iokastis Stream, Kavala City, NE Greece

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 579
Author(s):  
Thomas Papalaskaris ◽  
Theologos Panagiotidis
Keyword(s):  
Stream Flow ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Specific Area ◽  
Low Flow ◽  
Urban Stream ◽  
Flow Data ◽  
Goodness Of Fit Tests ◽  
Chi Squared ◽  
Anderson Darling

Only a few scientific research studies, especially dealing with extremely low flow conditions, have been compiled so far, in Greece. The present study, aiming to contribute in this specific area of hydrologic investigation, generates synthetic low stream flow time series of an entire calendar year considering the stream flow data recorded during a center interval period of the year 2015. We examined the goodness of fit tests of eleven theoretical probability distributions to daily low stream flow data acquired at a certain location of the absolutely channelized urban stream which crosses the roads junction formed by Iokastis road an Chrisostomou Smirnis road, Agios Loukas residential area, Kavala city, NE Greece, using a 3-inches conventional portable Parshall flume and calculated the corresponding probability distributions parameters. The Kolmogorov-Smirnov, Anderson-Darling and Chi-Squared, GOF tests were employed to show how well the probability distributions fitted the recorded data and the results were demonstrated through interactive tables providing us the ability to effectively decide which model best fits the observed data. Finally, the observed against the calculated low flow data are plotted, compiling a log-log scale chart and calculate statistics featuring the comparison between the recorded and the forecasted low flow data.

scholarly journals Seasonal dynamics of nutrients and organic matter in urban stream

2020 ◽  
Vol 163 ◽  
pp. 03004
Author(s):  
Oxana Erina ◽  
Dmitriy Sokolov ◽  
Maria Tereshina ◽  
Jessica Vasil’chuk ◽  
Nikolay Kasimov
Keyword(s):  
Organic Matter ◽  
Seasonal Dynamics ◽  
Organic Matter Content ◽  
Matter Content ◽  
Point Sources ◽  
Low Flow ◽  
Urban Stream ◽  
Multiple Point ◽  
Nitrogen And Phosphorus ◽  
Sources Of Pollution

The study presents the results of water quality evaluation in the Setun River watershed, located entirely within the limits of the Moscow City. Multiple point and non-point sources of pollution cause the nutrient and organic matter content of the river and its tributaries to significantly differ from the natural background. Maximum nitrogen and phosphorus concentrations were observed at the upper reaches of the river during the summer low flow due to the landfill impact. Because of the extreme nutrient pollution at the river’s upper course, subsequent water inflow, even from significantly polluted tributaries, has a diluting effect, and the nutrient concentration decreases downstream. The effect of urbanization on the organic matter content is reflected in elevated COD and BOD values that exceed the national environmental guidelines. Seasonal dynamics of organic matter content includes increased organic matter during snowmelt and its relatively low content during summer.

scholarly journals Assessment of an Ultrasonic Water Stage Monitoring Sensor Operating in an Urban Stream

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4689
Author(s):  
Yiannis Panagopoulos ◽  
Anastasios Papadopoulos ◽  
Georgios Poulis ◽  
Emmanouil Nikiforakis ◽  
Elias Dimitriou
Keyword(s):  
Pressure Transducer ◽  
Ultrasonic Sensor ◽  
Low Flow ◽  
Urban Stream ◽  
Dry Period ◽  
Marine Research ◽  
Increased Sensitivity ◽  
Water Stage ◽  
One Year ◽  
Contact Sensors

The monitoring of the water stage in streams and rivers is essential for the sustainable management of water resources, particularly for the estimation of river discharges, the protection against floods and the design of hydraulic works. The Institute of Marine Biological Resources and Inland Waters of the Hellenic Centre for Marine Research (HCMR) has developed and operates automatic stations in rivers of Greece, which, apart from their monitoring role, offer opportunities for testing new monitoring equipment. This paper compares the performance of a new ultrasonic sensor, a non-contact water stage monitoring instrument, against a pressure transducer, both installed at the same location in an urban stream of the metropolitan area of Athens. The statistical and graph analysis of the almost one-year concurrent measurements from the two sensors revealed that stage differences never exceeded 7%, while the ultrasonic measurements were most of the time higher than the respective pressure transducer ones during the low flow conditions of the dry period and lower during the wet period of the year, when high flow events occurred. It is also remarkable that diurnal air temperature variations under stable hydrologic conditions had an impact on the measured stage from the ultrasonic sensor, which varied its stage measurements within a small but non-negligible range, while the pressure transducer did not practically fluctuate. Despite a slightly increased sensitivity of the ultrasonic sensor to meteorological conditions, the paper concludes that non-contact sensors for the monitoring of the water stage in rivers can be useful, especially where danger for possible damage of submersible instruments is increased.

Effects of Urbanization on Stream Ecosystems

2005 ◽  
Keyword(s):  
Urban Development ◽  
Urban Streams ◽  
Base Flow ◽  
Low Flow ◽  
Urban Stream ◽  
Stream Ecosystems ◽  
Physical Habitat ◽  
Spatial And Temporal Patterns ◽  
Biological Responses ◽  
Additional Reference

<em>Abstract.</em>—Urban development modifies the production and delivery of runoff to streams and the resulting rate, volume, and timing of streamflow. Given that streamflow demonstrably influences the structure and composition of lotic communities, we have identified four hydrologic changes resulting from urban development that are potentially significant to stream ecosystems: increased frequency of high flows, redistribution of water from base flow to storm flow, increased daily variation in streamflow, and reduction in low flow. Previous investigations of streamflow patterns and biological assemblages provide a scale of ecological significance for each type of streamflow pattern. The scales establish the magnitude of changes in streamflow patterns that could be expected to produce biological responses in streams. Long-term streamflow records from eight streams in urbanizing areas of the United States and five additional reference streams, where land use has been relatively stable, were analyzed to assess if streamflow patterns were modified by urban development to an extent that a biological response could be expected and whether climate patterns could account for equivalent hydrologic variation in the reference streams. Changes in each type of streamflow pattern were evident in some but not all of the urban streams and were nearly absent in the reference streams. Given these results, hydrologic changes are likely significant to urban stream ecosystems, but the significance depends on the stream’s physiographic context and spatial and temporal patterns of urban development. In urban streams with substantially altered hydrology, short-term goals for urban stream rehabilitation may be limited because of the difficulty and expense of restoring hydrologic processes in an urban landscape. The ecological benefits of improving physical habitat and water quality may be tempered by persistent effects of altered streamflow. In the end, the hydrologic effects of urban development must be addressed for restoration of urban streams.

scholarly journals Artificial Neural Network for Daily Low Stream Flow Rate Prediction of Iokastis Stream, Kavala City, NE Greece, NE Mediterranean Basin

2020 ◽  
Vol 2 (1) ◽  
pp. 70
Author(s):  
Thomas Papalaskaris
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Flow Rate ◽  
Stream Flow ◽  
Low Flow ◽  
Urban Stream ◽  
Neural Network Modeling ◽  
Rate Data ◽  
Artificial Neural

Only a few scientific research studies referencing extremely low flow conditions have been conducted in Greece so far. Forecasting future low stream flow rate values is a crucial and decisive task when conducting drought and watershed management plans by designing construction plans dealing with water reservoirs and general hydraulic works capacity, by calculating hydrological and drought low flow indices, and by separating groundwater base flow and storm flow of storm hydrographs, etc. The Artificial Neural Network modeling simulation method generates artificial time series of simulated values of a random (hydrological in this specific case) variable. The present study produces artificial low stream flow time series of part of 2015. We compiled an Artificial Neural Network to simulate low stream flow rate data, acquired at a certain location of the entirely regulated, urban stream, which crosses the roads junction formed by Iokastis road and an Chrisostomou Smirnis road, Agios Loukas residential area, Kavala city, Eastern Macedonia & Thrace Prefecture, NE Greece, during part of July, August, and part of September 2015, until 12 September 2015, using a 3-inches conventional portable Parshall flume. The observed data were plotted against the predicted one and the results were demonstrated through interactive tables by providing us the ability to effectively evaluate the ANN model simulation procedure performance. Finally, we plotted the recorded against the simulated low stream flow rate data by compiling a log-log scale chart, which provides a better visualization of the discrepancy ratio statistical performance metrics and calculated further statistic values featuring the comparison between the recorded and the forecasted low stream flow rate data.

UAV monitoring of urban stream restoration sustainability

2021 ◽  
Author(s):  
Jakub Langhammer
Keyword(s):  
High Resolution ◽  
Stream Restoration ◽  
Quantitative Information ◽  
Low Flow ◽  
Urban Stream ◽  
Hydrological Connectivity ◽  
Reliable Technique ◽  
Restoration Success ◽  
Fluvial Dynamics ◽  
Restoration Effect

&lt;p&gt;High-resolution imaging using unmanned aerial vehicles (UAV, UAS, drones) opened up in the last decade a new potential for a detailed, reliable, operable, and affordable approach for riverscape monitoring.&amp;#160;Based on the experience with the pilot research on UAV detection of fluvial dynamics on natural and modified streams, we have proposed a framework for the assessment of the sustainability of stream restoration projects based on UAV imaging and photogrammetry. The approach focuses on aspects where the high-resolution UAV imagery can bring reliable and quantitative information, applicable for assessing restoration success and incorporation into standard assessment schemes.&lt;/p&gt;&lt;p&gt;We distinguish four critical aspects of stream restorations, where the UAV monitoring can provide reliable quantitative information, applicable for assessment of stream restoration success or failure: (i) Restoration effect, (ii) Dynamics of fluvial processes, (iii) Hydrological connectivity, and (iv) Riparian vegetation. For each aspect, there are derived relevant indicators, allowing quantitative assessment and scoring.&lt;/p&gt;&lt;p&gt;We have tested the framework on the evaluation of restorations on three urban streams in the metropolitan area of Prague, Czech Republic, which were subject of revitalization in the past decade. We have maintained regular recurrent UAV monitoring campaigns of these streams over four years, which enabled tracking the restorations since their completion and identifying the positive aspects and the failures in the sustainability of the realized restoration projects.&amp;#160;&lt;/p&gt;&lt;p&gt;UAV monitoring enabled to identify stream restoration features that would be hard or impossible to assess by other mapping techniques. As for the restoration effect, the UAV assessment revealed that although the basic goals of restoration projects were fulfilled, the newly shaped stream patterns significantly differ from the approved restoration plans. The restored channels are typically less complex and featuring simpler geometry than planned. Multitemporal assessment enabled to track stream instability and to measure the extent of bank erosion. UAV monitoring over a low flow period enabled to identify the stream segments where the inappropriate channel transformation led to disruptions in hydrological connectivity, and to detect and measure the extent of eutrophication in the stream and the newly created shallow ponds. UAV monitoring also enabled tracking the progress of vegetation succession after the restoration and quantitatively assessing the extent of riparian shading as a substantial element of sustainability of stream restoration.&lt;/p&gt;&lt;p&gt;Despite the limitations stemming from the nature of optical sensing, UAV monitoring proved to be a highly efficient and reliable technique suitable for evaluating stream restoration projects with versatile applications even in the urban environment&amp;#8217;s specific conditions.&lt;/p&gt;

951: “Experience in the Treatment of Low Flow Priapism”; A Novel, Easy and Effective Technique: A Long-Term, Binational, Multi-Institutional Study in 18 Patients Over 8 Years

2007 ◽  
Vol 177 (4S) ◽  
pp. 314-315
Author(s):  
Jose A. Medina Machuca ◽  
Jose A. Medina Coello ◽  
Hugo Manzanilla ◽  
Francisco A. Gutierrez
Keyword(s):  
Low Flow ◽  
Effective Technique
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