Literature DB >> 28535599

Monitoring spatiotemporal variations in nutrients in a large drinking water reservoir and their relationships with hydrological and meteorological conditions based on Landsat 8 imagery.

Yuan Li1, Yunlin Zhang2, Kun Shi3, Guangwei Zhu3, Yongqiang Zhou4, Yibo Zhang4, Yulong Guo5.   

Abstract

Nutrient enrichment is a major cause of water eutrophication, and variations in nutrient enrichment are influenced by environmental changes and anthropogenic activities. Accurately estimating nutrient concentrations and understanding their relationships with environmental factors are vital to develop nutrient management strategies to mitigate eutrophication. Landsat 8 Operational Land Imager (OLI) data is used to estimate nutrient concentrations and analyze their responses to hydrological and meteorological conditions. Two well-accepted empirical models are developed and validated to estimate the total nitrogen (TN) and total phosphorus (TP) concentrations (CTN and CTP) in the Xin'anjiang Reservoir using Landsat 8 OLI data from 2013 to 2016. Spatially, CTN decreased from the transition zone to the riverine zone and the lacustrine zone. On the other hand, CTP decreased from the riverine zone to the transition zone and the lacustrine zone. Temporally, CTN displayed elevated values during the late fall and winter and had lower values during the summer and early fall, whereas CTP was higher during the spring and lower during the winter. Among the environmental factors, the rainfall and the inflow rate have strong positive correlations with the nutrient concentrations. TN is more sensitive to meteorological factors (wind speed, temperature, sunshine duration), and the spatial driving forces vary among the different sections of the reservoir. However, TP is more easily influenced by human activities, such as fishery and agricultural activities. Current results would improve our understanding of the drivers of nutrients spatiotemporal variability and the approach in this study can be applicable to other similar reservoir to develop related strategies to mitigate eutrophication.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Environmental factors; Eutrophication; Landsat 8 OLI; Nutrients; Xin'anjiang Reservoir

Year:  2017        PMID: 28535599     DOI: 10.1016/j.scitotenv.2017.05.075

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Spatiotemporal dynamics of chlorophyll-a in a large reservoir as derived from Landsat 8 OLI data: understanding its driving and restrictive factors.

Authors:  Yuan Li; Yunlin Zhang; Kun Shi; Yongqiang Zhou; Yibo Zhang; Xiaohan Liu; Yulong Guo
Journal:  Environ Sci Pollut Res Int       Date:  2017-10-31       Impact factor: 4.223

2.  Retrieving Inland Reservoir Water Quality Parameters Using Landsat 8-9 OLI and Sentinel-2 MSI Sensors with Empirical Multivariate Regression.

Authors:  Haobin Meng; Jing Zhang; Zhen Zheng
Journal:  Int J Environ Res Public Health       Date:  2022-06-23       Impact factor: 4.614

  2 in total

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