Evaluation of Regression Methodology with Low-Frequency Water Quality Sampling to Estimate Constituent Loads for Ephemeral Watersheds in Texas

2008 ◽  
Vol 37 (5) ◽  
pp. 1847-1854 ◽  
Author(s):  
Gurpal S. Toor ◽  
R. Daren Harmel ◽  
Brian E. Haggard ◽  
Gerd Schmidt
Keyword(s):  
Water Quality ◽  
Low Frequency ◽  
Ephemeral Watersheds

On the value of long-term, low-frequency water quality sampling: avoiding throwing the baby out with the bathwater

2011 ◽  
Vol 25 (5) ◽  
pp. 828-830 ◽  
Author(s):  
T. P. Burt ◽  
N. J. K. Howden ◽  
F. Worrall ◽  
J. J. McDonnell
Keyword(s):  
Water Quality ◽  
Low Frequency

scholarly journals Development of Low Frequency Dielectric Cell for Water Quality Application

2016 ◽  
Vol 148 ◽  
pp. 687-693
Author(s):  
Hashem Al-Mattarneh ◽  
Abdullah Alwadie
Keyword(s):  
Water Quality ◽  
Low Frequency ◽  
Dielectric Cell

scholarly journals AVALIAÇÃO DE MACROINVERTEBRADOS BENTÔNICOS EM VIVEIROS ESCAVADOS EM LONDRINA-PR.

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
Felipe Pinheiro de Souza ◽  
Ed Christian Suzuki de Lima ◽  
Natalia Gonçalves Leite ◽  
Maxwel Bernardo Junior ◽  
Angela Maria Urrea-Rojas ◽  
...  
Keyword(s):  
Water Quality ◽  
Benthic Macroinvertebrates ◽  
Low Frequency ◽  
Water Source ◽  
Organic Pollution ◽  
Fish Farm ◽  
Macroinvertebrate Communities ◽  
Low Oxygen ◽  
Productive Potential ◽  
Abundance And Diversity

Biomonitoring with the use of benthic macroinvertebrates has been an effective tool used to evaluate water quality in several water bodies. In this context, there are several factors that can act on the structure of macroinvertebrate commuinities, with indications of the influence of aquaculture. Therefore, the present study evaluated the composition of macroinvertebrate populations in two earthen ponds of a fish farm in Londrina-PR. Three collections were carried out: in October of 2015 and February and July of 2016, with the use of artificial biocolectors. The macroinvertebrates were quantified and identified, and diversity indexes were calculated with the data obtained. Higher number of taxa, higher number of individuals and greater diversity and uniformity in macroinvertebrate communities were found in pond 1 (water entrance), due mainly to the presence of taxa tolerant or resistant to organic pollution, which may be related to the higher concentration of nutrients and organic matter in this pond. However, in pond 2 (water outlet), individuals of Polycentropodidae (Trichoptera) were found in all collections, in addition to a low abundance of taxa that would indicate organic enrichment, demonstrating better water quality. Furthermore, greater abundance and diversity were observed in the months with higher level of precipitation. From the perspective of aquaculture, the results found in pond 1 can be used as indicative of greater productive potential, however, the low frequency of taxa typical of clean environments may indicate low oxygen levels.These results demonstrate that the position of the pond relative to the water source in a fish farm can influence the water quality, which can be verified through the structure of the benthic macroinvertebrates communities.

scholarly journals A framework for assessing concentration‐discharge catchment behaviour from low‐frequency water quality data

2021 ◽  
Author(s):  
Ina Pohle ◽  
Nikki Baggaley ◽  
Javier Palarea‐Albaladejo ◽  
Marc Stutter ◽  
Miriam Glendell
Keyword(s):  
Water Quality ◽  
Low Frequency ◽  
Quality Data ◽  
Water Quality Data

scholarly journals Improved Representation of Flow and Water Quality in a North-Eastern German Lowland Catchment by Combining Low-Frequency Monitored Data with Hydrological Modelling

2020 ◽  
Vol 12 (12) ◽  
pp. 4812 ◽  
Author(s):  
Muhammad Waseem ◽  
Jannik Schilling ◽  
Frauke Kachholz ◽  
Jens Tränckner
Keyword(s):  
Water Quality ◽  
Low Frequency ◽  
Water Quality Monitoring ◽  
Hydrological Modelling ◽  
Quality Monitoring ◽  
Quality Data ◽  
N Transformations ◽  
Discharge Data ◽  
River Catchment ◽  
Spatio Temporal

Achievements of good chemical and ecological status of groundwater (GW) and surface water (SW) bodies are currently challenged mainly due to poor identification and quantification of pollution sources. A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultural practices, further studies can enhance the better agricultural and water quality management in the study area.

A simulation-based approach to assess the power of trend detection in high- and low-frequency water quality records

2020 ◽  
Vol 192 (10) ◽  
Author(s):  
Shuci Liu ◽  
Danlu Guo ◽  
J. Angus Webb ◽  
Paul J. Wilson ◽  
Andrew W. Western
Keyword(s):  
Water Quality ◽  
Low Frequency ◽  
Trend Detection ◽  
Simulation Based
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