Comparative analysis of nutrient data in the lower Mississippi River

Bollinger, James E.; Steinberg, Laura J.; Harrison, Martha Jane; Crews, James P.; Englande, A. J.; Velasco-Gonzales, Cruz; White, LuAnn; George, William J.

doi:10.1016/s0043-1354(99)00117-7

Cited by 21 publications

(21 citation statements)

References 7 publications

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“…The dry season trophic state of the tropical lakes is more advanced because of the dilution factor by rain water (Offem et al 2011). A representative and reliable estimation of the quality of surface water is crucial due to the spatial and temporal variations in water chemistry (Bollinger et al 1999). Several authors have introduced different criteria for the classification of freshwater trophic level; most of them are based on phosphorus, nitrogen compounds and chlorophyll a concentrations (e.g., Vollenwieder 1998;Wetzel 1983;Molisani et al 2010;Sheela et al 2011).…”

Section: Resultsmentioning

confidence: 99%

Water quality of tropical reservoir based on spatio-temporal variation in phytoplankton composition and physico-chemical analysis

Maznah

Makhlough²

2014

Int. J. Environ. Sci. Technol.

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This study assessed the water quality of Mengkuang Reservoir, Penang, Malaysia, by its trophic status according to a Carlson Modified Trophic Index (CMTSI) and by its biological parameters using Shannon-Wiener diversity index (H 0 ) and saprobic index. The study conducted from August 2005 to July 2006 showed that mean values of CMTSI (nutrients), CMTSI (chlorophyll a) and CMTSI (Secchi depth) were 27.18 ± 8.73, 40.63 ± 7.12 and 41.74 ± 6.38, respectively. The mean values of CMTSI indicated that the reservoir was oligotrophic. Mean value of H 0 was 2.15 bits/individual, showing that the water quality based on H 0 value was in class III (slightly polluted). Saprobic index value (2.24) also revealed that the reservoir was moderately polluted (class II). The occurrence of Anabaena, Microcystis, Oscillatoria, Nostoc, Dinobryon, Chroococcus, Staurastrum paradoxum and Mallomonas which are indicators of toxic and polluted waters was also recorded. This study therefore showed the importance of phytoplankton composition and community structure as a reliable and important tool to assess the degree of pollution in Mengkuang Reservoir. Long-term assessments of biological and chemical parameters in the reservoir are necessary, and phytoplankton community structure as bioindicator provides unique information about the ecosystem. This information is potentially useful as an early warning sign of deteriorating condition and thus gives insight into the overall ecology of lakes and will assist in the future conservation and management of this lentic ecosystem.

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Section: Resultsmentioning

confidence: 99%

Water quality of tropical reservoir based on spatio-temporal variation in phytoplankton composition and physico-chemical analysis

Maznah

Makhlough²

2014

Int. J. Environ. Sci. Technol.

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“…Described below are the results of comparisons between the various agencies collecting nutrient data, and observations of similarities and differences in nutrient concentrations between river segments. The results of similar, but less statistically rigorous comparisons, have been published elsewhere (Bollinger et al, 1999). The end results of these comparisons are used for the characterization of nutrient loads, Si:N:P ratios and a summary of trends in the limiting nutrient, using an integrated set of data from a large number of sources and locations on the lower Mississippi River.…”

Section: Study Area Hydrographymentioning

confidence: 99%

NUTRIENT LOAD CHARACTERIZATION FROM INTEGRATED SOURCE DATA FOR THE LOWER MISSISSIPPI RWER¹

Bollinger¹,

Steinberg²,

Englande³

et al. 2000

J American Water Resour Assoc

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Nutrient data from all available sources for the lower Mississippi River were examined for potential differences among sampling agencies and geographic locations for the period between 1960 and 1998. Monthly means grouped by parameter, sampling location and agency, were calculated and compared as paired sets, excluding those months where data were not available for both sets. Some significant differences were found between various agencies collecting nutrient data on the river, as well as between various stretches of river, especially in the case of phosphorus nutrient data. Results were used to synthesize data sets from which a history of nutrient loading in the Mississippi River was determined. General trends in nitrate+nitrite, total Kjeldahl nitrogen, orthophosphate, total phosphorus and silica loads, as well as changes in nutrient proportions and the specific limiting nutrient (by month) are reported. This study provides a useful summary of contemporary and historical nutrient data that may assist in the evaluation of Mississippi River water quality and its potential effect on the Gulf of Mexico.

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“…Population growth, environmental pollution from discharge of urban and industrial sewage, and runoff have increased pollution and limited available water resources (Simeonov et al 2003;Sánchez et al 2007). Monitoring and controlling surface waters are necessary and vital to assure the availability of high-quality water for its many uses (Bollinger et al 1999;Sánchez et al 2007). One of simple methods that can recount the qualitative conditions of water is the use of water quality indexes (Hoseinzadeh et al 2015;Barakat et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Water quality evaluation using water quality index and multivariate methods, Beheshtabad River, Iran

2018

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Rivers are critical to agriculture, industry, and the needs of humans and wildlife. This study evaluates the water quality of the Beheshtabad River in Iran's Chaharmahal and Bakhtiari Province, using water quality index and multivariate statistical methods. Nitrate, temperature, phosphate, turbidity, dissolved oxygen, biological oxygen demand, electrical conductivity, total solids, and pH were measured at five selected stations along the river over 6 months using standard methods. Water quality index results demonstrated that water quality varied in the selected stations between average and good and that pollution in this section of the Beheshtabad River increases from upstream to downstream. Clustering and principal component analysis were also utilized. Multivariate statistical methods were used to analyze water conditions for efficient management of surface water quality. Agricultural fertilizers, upstream wastewater discharge, and fish farms constitute the main elements that decrease the water quality of the Beheshtabad River. To preserve this water resource against pollution, the implementation of stringent rules and guidelines are needed to enhance health and preserve water resources for future generations.

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Comparative analysis of nutrient data in the lower Mississippi River

Cited by 21 publications

References 7 publications

Water quality of tropical reservoir based on spatio-temporal variation in phytoplankton composition and physico-chemical analysis

Water quality of tropical reservoir based on spatio-temporal variation in phytoplankton composition and physico-chemical analysis

NUTRIENT LOAD CHARACTERIZATION FROM INTEGRATED SOURCE DATA FOR THE LOWER MISSISSIPPI RWER¹

Water quality evaluation using water quality index and multivariate methods, Beheshtabad River, Iran

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Comparative analysis of nutrient data in the lower Mississippi River

Cited by 21 publications

References 7 publications

Water quality of tropical reservoir based on spatio-temporal variation in phytoplankton composition and physico-chemical analysis

Water quality of tropical reservoir based on spatio-temporal variation in phytoplankton composition and physico-chemical analysis

NUTRIENT LOAD CHARACTERIZATION FROM INTEGRATED SOURCE DATA FOR THE LOWER MISSISSIPPI RWER1

Water quality evaluation using water quality index and multivariate methods, Beheshtabad River, Iran

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NUTRIENT LOAD CHARACTERIZATION FROM INTEGRATED SOURCE DATA FOR THE LOWER MISSISSIPPI RWER¹