Short-term water quality variability in two tropical estuaries, central Sumatra

Estuaries ◽  
2003 ◽  
Vol 26 (1) ◽  
pp. 156-165 ◽  
Author(s):  
P. G. Sanderson ◽  
D. M. Taylor
Keyword(s):  
Water Quality ◽  
Short Term ◽  
Tropical Estuaries ◽  
Central Sumatra

Oil pollution and fisheries

1982 ◽  
Vol 297 (1087) ◽  
pp. 401-411 ◽  
Keyword(s):  
Water Quality ◽  
Adverse Effects ◽  
Oil Pollution ◽  
Coastal Areas ◽  
Short Term ◽  
Fish Stocks ◽  
Local Impacts ◽  
Reduced Water ◽  
Long Term Adverse Effects

The term ‘pollution’ is taken in its broadest sense and effects are recognized to be due to interference, tainting and toxicity. Each of these types of impact is discussed and assessed. It is concluded that no long-term adverse effects on fish stocks can be attributed to oil but that local impacts can be extremely damaging in the short term and that produce from specific localities can be tainted and unmarketable for long periods. In some coastal areas oil can be one among several contributors to reduced water quality, and the implications of this are discussed.

scholarly journals Catchment water quality in the year preceding and immediately following restoration of a drained afforested blanket bog

2021 ◽  
Author(s):  
Paul P. J. Gaffney ◽  
Mark H. Hancock ◽  
Mark A. Taggart ◽  
Roxane Andersen
Keyword(s):  
Water Quality ◽  
Nutrient Release ◽  
Pass Rate ◽  
Future Research ◽  
Negative Effects ◽  
Short Term ◽  
Peatland Restoration ◽  
Blanket Bog ◽  
Quality Threshold ◽  
Policy Incentives

AbstractThe restoration of drained afforested peatlands, through drain blocking and tree removal, is increasing in response to peatland restoration targets and policy incentives. In the short term, these intensive restoration operations may affect receiving watercourses and the biota that depend upon them. This study assessed the immediate effect of ‘forest-to-bog’ restoration by measuring stream and river water quality for a 15 month period pre- and post-restoration, in the Flow Country peatlands of northern Scotland. We found that the chemistry of streams draining restoration areas differed from that of control streams following restoration, with phosphate concentrations significantly higher (1.7–6.2 fold, mean 4.4) in restoration streams compared to the pre-restoration period. This led to a decrease in the pass rate (from 100 to 75%) for the target “good” quality threshold (based on EU Water Framework Directive guidelines) in rivers in this immediate post-restoration period, when compared to unaffected river baseline sites (which fell from 100 to 90% post-restoration). While overall increases in turbidity, dissolved organic carbon, iron, potassium and manganese were not significant post-restoration, they exhibited an exaggerated seasonal cycle, peaking in summer months in restoration streams. We attribute these relatively limited, minor short-term impacts to the fact that relatively small percentages of the catchment area (3–23%), in our study catchments were felled, and that drain blocking and silt traps, put in place as part of restoration management, were likely effective in mitigating negative effects. Looking ahead, we suggest that future research should investigate longer term water quality effects and compare different ways of potentially controlling nutrient release.

scholarly journals Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2699 ◽  
Author(s):  
Jian Li ◽  
Liqiao Tian ◽  
Qingjun Song ◽  
Zhaohua Sun ◽  
Hongjing Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Lake Area ◽  
Short Term ◽  
Chl A ◽  
Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

Short-term variability of water quality and its implications on phytoplankton production in a tropical estuary (Cochin backwaters—India)

2009 ◽  
Vol 170 (1-4) ◽  
pp. 287-300 ◽  
Author(s):  
N. V. Madhu ◽  
K. K. Balachandran ◽  
G. D. Martin ◽  
R. Jyothibabu ◽  
Shoji D. Thottathil ◽  
...  
Keyword(s):  
Water Quality ◽  
Phytoplankton Production ◽  
Tropical Estuary ◽  
Short Term ◽  
Cochin Backwaters ◽  
Short Term Variability
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