Premium
Transient Hypoxia Extent Off Changjiang River Estuary due to Mobile Changjiang River Plume
Author(s) -
Zhang Wenxia,
Wu Hui,
Zhu Zhuoyi
Publication year - 2018
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2018jc014596
Subject(s) - hypoxia (environmental) , estuary , plume , environmental science , stratification (seeds) , bottom water , estuarine water circulation , ecosystem , oxygen , oceanography , salinity , hydrology (agriculture) , discharge , spatial variability , geology , ecology , meteorology , chemistry , geography , biology , germination , seed dormancy , drainage basin , botany , geotechnical engineering , cartography , organic chemistry , dormancy , mathematics , statistics
Observed oxygen concentrations collected at discrete locations during research cruises were conventionally used to estimate spatial extents of bottom low‐oxygen/hypoxia. Yet observed oxygen concentrations were often not quantitatively representative of spatial patterns in instantaneous oxygen concentrations in coastal oceans, especially when the bottom hypoxia was transient. Over the Changjiang River estuary and its adjacent sea, research cruises could easily be longer than the time scale of variability of bottom hypoxia extent. The Changjiang River plume is extremely mobile due to changes in wind magnitude and direction, and the redistribution of this freshwater cap strongly regulates vertical stratification on which bottom hypoxia formation depends. A high‐resolution ecosystem model was developed, which successfully reproduced observed temperature, salinity, and bottom oxygen concentration. This model suggested fast response of bottom oxygen to vertical stratification evolution (generally ∼6–50 hr) and a transient spatial extent of summer bottom hypoxia off the Changjiang River estuary. Comparisons between observed and modeled oxygen concentrations implied that the hypoxic area calculated from dissolved oxygen at discrete locations often had possible errors and the estimated magnitude of hypoxic area which depended on the chronological order of observations. Therefore, it is risky to estimate the spatial extent of hypoxic area based on observations exclusively, and the relevant quantification of annual hypoxia area trend is also questionable. Integration of quasi‐simultaneous observations is required to advance the understanding of oxygen dynamics, to minimize observational uncertainties. The development of skillful ecosystem models that profit from ample observations and have the power to reproduce dissolved oxygen is indispensable.