Spatial and temporal variations of nitrogen pollution in Wen-Rui Tang River watershed, Zhejiang, China

Lu, Ping; Mei, Kun; Zhang, Yujin; Liao, Lejian; Long, Bibo; Dahlgren, Randy A.; Zhang, Minghua

doi:10.1007/s10661-010-1802-z

Cited by 31 publications

(35 citation statements)

References 30 publications

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“…In addition, several other explanatory variables, such as topographic and landscape indexes, are commonly applied as potential explanatory variables (Chen et al, 2002;Pratt and Chang, 2012;Sun et al, 2014). However, our previous research did not find strong relationships between these subcatchment characteristics and water quality in the Wen-Rui Tang River watershed (Mei et al, 2014;Lu et al, 2011).…”

Section: Variable Selectionmentioning

confidence: 83%

“…To avoid multicollinearity, a manual variable excluding-selecting method was utilized: (1) all of the explanatory variables were entered to develop OLS functions for each water quality indicator, and Spearman coefficients for both dependent and independent variables were calculated; (2) pairwise land-use variables in the OLS model with higher correlations were selected and variables with weaker correlations in the pair were removed; (3) the independent variable with the highest variance inflation factor (VIF) was removed (if the maximum VIF value was b 2, then jump to the fourth step); and (4) the OLS model was reformulated with the independent variables having the highest impact on selected water quality indicators according to our previous findings (Lu et al, 2011;Mei et al, 2014). If there was a significant correlation among variables, step 2 was repeated until all argument VIF values were b 2.…”

Section: Modeling Methodsmentioning

confidence: 99%

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Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Chen

Mei

Dahlgren

et al. 2016

Science of The Total Environment

Self Cite

160

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• The modified GWR models had higher R 2 and reflected the actual spatial features.• A manual variable excluding-selecting method is explored to avoid multicollinearity.• Influences of the dominant indicator on water quality varied with space and seasons.• Protection policies need consider sitespecific conditions and seasonal variations. G R A P H I C A L A B S T R A C Ta b s t r a c t a r t i c l e i n f o As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2~5 9.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use Contents lists available at ScienceDirectScience of the Total Environment j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s c i t o t e n v conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations.

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Section: Variable Selectionmentioning

confidence: 83%

Section: Modeling Methodsmentioning

confidence: 99%

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Chen

Mei

Dahlgren

et al. 2016

Science of The Total Environment

Self Cite

160

View full text Add to dashboard Cite

show abstract

“…To identify the spatial similarity of the sampling sites, hierarchical cluster analysis was performed on catchment-wide land use data by means of Ward's method, using Euclidean distances as a measure of similarity [44][45][46]. This method uses an analysis of the variance to evaluate the distances between clusters in an attempt to minimize the sum of squares of any two possible clusters that can be formed at each step.…”

Section: Discussionmentioning

confidence: 99%

Impacts of Land Use on Surface Water Quality in a Subtropical River Basin: A Case Study of the Dongjiang River Basin, Southeastern China

Ding

Jiang

Fu³

et al. 2015

Water

158

103

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Abstract:Understanding the relationship between land use and surface water quality is necessary for effective water management. We estimated the impacts of catchment-wide land use on water quality during the dry and rainy seasons in the Dongjiang River basin, using remote sensing, geographic information systems and multivariate statistical techniques. The results showed that the 83 sites can be divided into three groups representing different land use types: forest, agriculture and urban. Water quality parameters exhibited significant variations between the urban-dominated and forest-dominated sites. The proportion of forested land was positively associated with dissolved oxygen concentration but negatively associated with water temperature, electrical conductivity, permanganate index, total phosphorus, total nitrogen, ammonia nitrogen, nitrate nitrogen and chlorophyll-a. The proportion of urban land was strongly positively associated with total nitrogen and ammonia nitrogen concentrations. Forested and urban land use had stronger impacts on water quality in the dry season than in the rainy OPEN ACCESSWater 2015, 7 4428 season. However, agricultural land use did not have a significant impact on water quality. Our study indicates that urban land use was the key factor affecting water quality change, and limiting point-source waste discharge in urban areas during the dry season would be critical for improving water quality in the study area.

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“…Therefore, the goal of this paper was to establish a combined spatial-temporal method to comprehensively explore water quality variations occurring at the rural-suburban-urban interface. We expand on the previous work by Lu et al (2011) and Yang et al (2013) by extending the study period from 1 or 2 to 11 years of water quality monitoring data in the Wen-Rui Tang River watershed of eastern China. Due to rapid economic development, water quality of this river has been severely degraded.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Mei

Liao

Zhu

et al. 2014

Environ Sci Pollut Res

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Water quality degradation is often a severe consequence of rapid economic expansion in developing countries. Methods to assess spatial-temporal patterns and trends in water quality are essential for guiding adaptive management efforts aimed at water quality remediation. Temporal and spatial patterns of surface water quality were investigated for 54 monitoring sites in the Wen-Rui Tang River watershed of eastern China to identify such patterns in water quality occurring across a rural-suburban-urban interface. Twenty physical and chemical water quality parameters were analyzed in surface waters collected once every 4-8 weeks from 2000 to 2010. Temporal and spatial variations among water quality parameters were assessed between seasons (wet/dry) and among major land use zones (urban/suburban/rural). Factor analysis was used to identify parameters that were important in assessing seasonal and spatial variations in water quality. Results revealed that parameters related to organic pollutants (dissolved oxygen (DO), chemical oxygen demand (manganese) (COD Mn ), and 5-day biochemical oxygen demand (BOD 5 )), nutrients (ammonia nitrogen (NH 4 + -N), total nitrogen (TN), total phosphorus (TP)), and salt concentration (electrical conductivity (EC)) were the most important parameters contributing to water quality variation. Collectively, they explained 70.9 % of the total variance. A trend study using the seasonal Kendall test revealed reductions in COD Mn , BOD 5 , NH 4 + -N, petrol, V-phen, and EC concentrations over the 11-year study period. Cluster analysis was employed to evaluate variation among 14 sampling sites representative of dominant land use categories and indicated three, three, and four clusters based on organic, nutrient, and salt water quality characteristics, respectively. Factors that are typically responsible for water quality degradation (including population, topography, and land use) showed no strong correlation with water quality trends implying considerable point source inputs in the watershed. The results of this study help inform ongoing water quality remediation efforts by documenting trends in water quality across various land use zones.

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Spatial and temporal variations of nitrogen pollution in Wen-Rui Tang River watershed, Zhejiang, China

Cited by 31 publications

References 30 publications

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Impacts of Land Use on Surface Water Quality in a Subtropical River Basin: A Case Study of the Dongjiang River Basin, Southeastern China

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

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