A simple empirical optical model for simulating light attenuation variability in a partially mixed estuary |
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| Authors: | Jiangtao Xu Raleigh R Hood Shenn-Yu Chao |
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| Institution: | (1) Balaton Limnological Research Institute of the Hungarian Academy of Sciences, P.O.Box 35, 8237 Tihany, Hungary |
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| Abstract: | Representation of the subsurface light field is a crucial component of pelagic ecosystem and water quality models. Modeling
the light field in estuaries is a particularly complicated problem due to the significant influence of high concentrations
of dissolved and particulate matter that are derived from both terrestrial and estuarine sources. The goal of this study was
to develop a relatively simple but effective way to model light attenuation variability in a turbuid estuary (Chesapeake Bay,
United States) in a coupled physical-biological model. We adopted a simple, nonspectral empirical approach. Surface water
quality data (salinity was used as a proxy of chromophoric dissolved organic matter CDOM]) and light measurements from the
Chesapeake Bay Program were used to determine the absorption coefficients in a linear attenuation model using regression methods.
This model predicts Kc (specific attenuation due to phytoplankton/chlorophylla chla]), Kt (specific attenuation due to total suspended solids), and Ks (a function of specific attenuation coefficients of CDOM in relation to salinity). The Bay-wide fitted relation between the
light attenuation coefficient and water quality concentrations gives generally good estimates of total light attenuation,
Kd. The direct inclusion of salinity in the relationship has one disadvantage: it can yield negative values for Kd at high salinities. We developed two separate models for two different salinity regimes. This approach, in addition to solving
the negative Kd problem, also accounts for some changes in specific light absorption by chla, seston (nonphytoplankton particulate matter), and CDOM that apparently occur in different salinity regimes in Chesapeake
Bay. The resulting model predicts the statistical characteristics (i.e., the mean and variance) of Kd quite accurately in most regions of Chesapeake Bay. We also discuss in this paper the feasibility and caveats of using Kd converted from Secchi depth in the empirical method. |
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