Characterisation and assessment of spatiotemporal variations in nutrient concentrations and fluxes in an urban watershed: Passaic River Basin, New Jersey, USA

Du, Juan; Feng, Huan; Nie, Jing; Li, Yuanyi; Witherell, B. B.

doi:10.1504/ijep.2018.097310

Cited by 6 publications

(2 citation statements)

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“…Many efforts have been made to describe the major sources of N and P throughout the MARB and evaluate the effectiveness of nutrient reduction strategies [4]. Because of the randomness in the observations of nutrient loads [5], various statistical methods have been implemented to analyze trends in nutrient loads [6][7][8][9][10][11][12]. Linear regression was used to study yields throughout the MARB, considering various environmental impacts [13], and to identify the relative importance of sources and land use in nutrient delivery [14,15].…”

Section: Introductionmentioning

confidence: 99%

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

Zhen,

Feng,

Yoo

2023

Environments

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To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO3-NO2), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

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Section: Introductionmentioning

confidence: 99%

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

Zhen,

Feng,

Yoo

2023

Environments

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“…The "hypoxic zone" refers to a specific water area where the dissolved oxygen concentration is less than 2 mg/L, and to hypoxia associated with excess nutrient input, such as nitrogen and phosphorus, which can yield serious environmental, economic, and social impact. A variety of sources, which are related to economic activities and population growth, can contribute to the elevated nutrient concentrations in rivers (e.g., agricultural activities, industrial point-discharge, urban runoff, natural deposition, and domestic waste, such as household cleaning products; [1][2][3][4][5][6]. Water quality from the Mississippi-Atchafalaya river basin to the Northern Gulf of Mexico has been improved since the enactment of the 1972 Clean Water Act (CWA) and other regulations by the Environmental Protection…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of Nutrient Loads from the Mississippi-Atchafalaya River Basin (MARB) to the Gulf of Mexico

et al. 2020

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This study investigated the annual and seasonal variations in nutrient loads (NO2− + NO3− and orthophosphate) delivered to the Gulf of Mexico from the Mississippi-Atchafalaya River Basin (MARB) and examined the water quality variations. The results indicate that (1) annually, the mean NO2− + NO3− and orthophosphate loads showed a steady increase during 1996–1999, a persistent level during 2000–2007, and a moderate increase during 2008–2016; (2) seasonally, NO2− + NO3− and orthophosphate in MARB in spring and summer were higher than those in autumn and winter. Analysis of variance (ANOVA) identified highly significant differences among seasonal loads; and (3) the median value of NO2− + NO3− in normal weather conditions were higher than that during and right after the hurricanes, while the median value of orthophosphate loads in normal weather conditions was higher than that during the hurricanes, but higher than that right after hurricanes. The two-sample t-test indicates a significant difference (p < 0.046) in orthophosphate loads before and after Hurricane Katrina. Moreover, it is found that there is a significant (p < 0.01) increase in nutrient loads during normal weather conditions. The results indicate that hurricane seasons can significantly influence the nutrient loads from the MARB to the Gulf of Mexico.

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Hydrodynamics and water circulation in the New York/New Jersey Harbor: A study from the perspective of water age

Feng

Haiwen

et al. 2019

Journal of Marine Systems

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Characterisation and assessment of spatiotemporal variations in nutrient concentrations and fluxes in an urban watershed: Passaic River Basin, New Jersey, USA

Cited by 6 publications

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Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

Statistical Analysis of Nutrient Loads from the Mississippi-Atchafalaya River Basin (MARB) to the Gulf of Mexico

Hydrodynamics and water circulation in the New York/New Jersey Harbor: A study from the perspective of water age

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