Spatial Variation in Stream Water Quality in Relation to Riparian Buffer Dimensions in a Rural Watershed of Eastern New York State

2007 ◽  
Vol 14 (4) ◽  
pp. 605-618 ◽  
Author(s):  
Sean S. Madden ◽  
George R. Robinson ◽  
John G. Arnason
2010 ◽  
Vol 10 (3) ◽  
pp. 727-733 ◽  
Author(s):  
Christopher P. Tran ◽  
Robert W. Bode ◽  
Alexander J. Smith ◽  
Gary S. Kleppel

2014 ◽  
Vol 80 (16) ◽  
pp. 4814-4820 ◽  
Author(s):  
Lisa A. Jones ◽  
Randy W. Worobo ◽  
Christine D. Smart

ABSTRACTIn the United States, surface water is commonly used to irrigate a variety of produce crops and can harbor pathogens responsible for food-borne illnesses and plant diseases. Understanding when pathogens infest water sources is valuable information for produce growers to improve the food safety and production of these crops. In this study, prevalence data along with regression tree analyses were used to correlate water quality parameters (pH, temperature, turbidity), irrigation site properties (source, the presence of livestock or fowl nearby), and precipitation data to the presence and concentrations ofEscherichia coli,Salmonellaspp., and hymexazol-insensitive (HIS) oomycetes (PhytophthoraandPythiumspp.) in New York State surface waters. A total of 123 samples from 18 sites across New York State were tested forE. coliandSalmonellaspp., of which 33% and 43% were positive, respectively. Additionally, 210 samples from 38 sites were tested for HIS oomycetes, and 88% were found to be positive, with 10 species ofPhytophthoraand 11 species ofPythiumbeing identified from the samples. Regression analysis found no strong correlations between water quality parameters, site factors, or precipitation to the presence or concentration ofE. coliin irrigation sources. ForSalmonella, precipitation (≤0.64 cm) 3 days before sampling was correlated to both presence and the highest counts. Analyses for oomycetes found creeks to have higher average counts than ponds, and higher turbidity levels were associated with higher oomycete counts. Overall, information gathered from this study can be used to better understand the food safety and plant pathogen risks of using surface water for irrigation.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1123 ◽  
Author(s):  
Yu Song ◽  
Xiaodong Song ◽  
Guofan Shao ◽  
Tangao Hu

The land use and land cover changes in rapidly urbanized regions is one of the main causes of water quality deterioration. However, due to the heterogeneity of urban land use patterns and spatial scale effects, a clear understanding of the relationships between land use and water quality remains elusive. The primary purpose of this study is to investigate the effects of land use on water quality across multi scales in a rapidly urbanized region in Hangzhou City, China. The results showed that the response characteristics of stream water quality to land use were spatial scale-dependent. The total nitrogen (TN) was more closely related with land use at the circular buffer scale, whilst stronger correlations could be found between land use and algae biomass at the riparian buffer scales. Under the circular buffer scale, the forest and urban greenspace were more influential to the TN at small buffer scales, whilst significant positive or negative correlations could be found between the TN and the areas of industrial land or the wetland and river as the buffer scales increased. The redundancy analysis (RDA) showed that more than 40% variations in water quality could be explained by the landscape metrics at all circular and riparian buffer scales, and this suggests that land use pattern was an important factor influencing water quality. The variation in water quality explained by landscape metrics increased with the increase of buffer size, and this implies that land use pattern could have a closer correlation with water quality at larger spatial scales.


River Systems ◽  
2010 ◽  
Vol 19 (1) ◽  
pp. 75-94 ◽  
Author(s):  
Steven W. Effler ◽  
Anthony R. Prestigiacomo ◽  
Adam J.P. Effler ◽  
Charles Driscoll

2017 ◽  
Author(s):  
Kristina M. Gutchess ◽  
◽  
Li Jin ◽  
José L.J. Ledesma ◽  
Jill Crossman ◽  
...  

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