Stormwater Dissolved Organic Matter: Influence of Land Cover and Environmental Factors

2013 ◽  
Vol 48 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Shawn P. McElmurry ◽  
David T. Long ◽  
Thomas C. Voice

2009 ◽  
Vol 43 (13) ◽  
pp. 4973-4978 ◽  
Author(s):  
Yuping Qiu ◽  
Xiaoyu Xiao ◽  
Haiyan Cheng ◽  
Zunlong Zhou ◽  
G. Daniel Sheng


2020 ◽  
Vol 717 ◽  
pp. 137165 ◽  
Author(s):  
Oliva Pisani ◽  
David D. Bosch ◽  
Alisa W. Coffin ◽  
Dinku M. Endale ◽  
Dan Liebert ◽  
...  


2018 ◽  
Vol 19 (1) ◽  
pp. 274-281 ◽  
Author(s):  
Jiang Chen ◽  
Weining Zhu ◽  
Yuhan Zheng ◽  
Yong Q. Tian ◽  
Qian Yu

Abstract Remote sensing is an effective tool for studying CDOM (colored dissolved organic matter) variations and its relevant environmental factors. Monitoring CDOM distribution and dynamics in small water is often limited by the coarse spatial resolution of traditional ocean color sensors. In this study, because of its high spatial resolution of 30 m, Landsat-8 data were used to assess seasonal variations of CDOM in the Saginaw River, by using an empirical statistic model. Pearson correlation analysis between CDOM variations and other environmental factors, such as temperature, discharge, and dissolved oxygen, shows that temperature was negatively correlated to CDOM variations and discharge played a positive role. We also calculated the monthly mean aCDOM(440) (the absorption coefficient of CDOM at 440 nm) for the Saginaw River between April and November from 2013 to 2016. This study demonstrates a good example for future applications in small waters: observing CDOM variations and other relevant environmental factors change by using Landsat remote sensing, so that we can know more about water quality and ecosystem health of small waters as well as the climate change impact on regional watersheds.



2019 ◽  
Vol 64 (6) ◽  
pp. 2328-2340 ◽  
Author(s):  
Christopher A. Yates ◽  
Penny J. Johnes ◽  
Alun T. Owen ◽  
Francesca L. Brailsford ◽  
Helen C. Glanville ◽  
...  


2017 ◽  
Vol 24 (16) ◽  
pp. 14124-14141 ◽  
Author(s):  
Shatrughan Singh ◽  
Padmanava Dash ◽  
Saurav Silwal ◽  
Gary Feng ◽  
Ardeshir Adeli ◽  
...  


2021 ◽  
Author(s):  
Francesca L. Brailsford ◽  
Helen C. Glanville ◽  
Miles R. Marshall ◽  
Christopher A. Yates ◽  
Alun T. Owen ◽  
...  


Author(s):  
Zeliang Zhang ◽  
Weining Zhu ◽  
Jiang Chen ◽  
Qian Cheng

Abstract Freshwater lakes are facing increasingly serious water quality problems. Remote sensing techniques are effective tools for monitoring spatiotemporal information of chromophoric dissolved organic matter (CDOM), a biochemical indicator for water quality. In this study, the Gradient Boosting Regressing Tree (GBRT) model and Sentinel-2A/B image were combined to estimate low CDOM concentrations (0.003 m−1 < aCDOM(440) <1.787 m−1) in Xin'anjiang Reservoir, an important drinking water resource in Zhejiang Province, China, providing the CDOM distributions and dynamics with high spatial (10 m) and temporal (5 days) resolutions. The possible environmental factors that may affect CDOM spatiotemporal patterns and dynamics were analyzed using Sentinel-2 image-observed data in 2018. Results showed that CDOM in the reservoir exhibited a clear increased gradient from its transition and lacustrine zones to the riverine zones, indicating that the rivers carried a substantial load of organic matter to the lake. The precipitation may increase CDOM concentrations but it has a delay effect, while it may also shortly decrease CDOM concentrations due to the rainwater dilution. We also found that the correlations between CDOM and water temperature, air pressure, and wind speed were very low, indicating that these factors may not have significant impacts on CDOM variations in the reservoir. This study demonstrated that the GBRT model and Sentinel-2 imagery have the potential to accurately monitor CDOM spatiotemporal variations in reservoirs with low CDOM concentrations, which advancing our understanding on the relations between the dissolved organic matter and its coupling environmental factors in river-reservoir systems.



2019 ◽  
Vol 570 ◽  
pp. 281-291 ◽  
Author(s):  
Margot Sepp ◽  
Toomas Kõiv ◽  
Peeter Nõges ◽  
Tiina Nõges


2015 ◽  
Vol 120 (8) ◽  
pp. 1491-1505 ◽  
Author(s):  
Dolly N. Kothawala ◽  
Xing Ji ◽  
Hjalmar Laudon ◽  
Anneli M. Ågren ◽  
Martyn N. Futter ◽  
...  


Ecosystems ◽  
2014 ◽  
Vol 17 (8) ◽  
pp. 1413-1425 ◽  
Author(s):  
James H. Larson ◽  
Paul C. Frost ◽  
Marguerite A. Xenopoulos ◽  
Clayton J. Williams ◽  
Ana M. Morales-Williams ◽  
...  


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