(c),(d) Each MVFC area distribution was merged with its corresponding LISST particle area distribution. MVFC images obtained (a) with widespread schlieren effects and b) without schlieren effects at two depths in a profile near the estuary mouth. The effect of LISST overestimating SPM is typical of profiles that have high stratification. The LISST regression equation was from data for which N ≤ 0.05 s −1, but for the profile here, the equation was applied to all in order to calculate SPM.

2 SPM from water samples (asterisks) and the depth range where N > 0.05 s −1 (shaded area). Shown are density (black dotted line) SPM derived from a LISST (curve with open circles), an ac-9 (curve with squares), and a bb2fl (curve with triangles), using equations listed in Fig. The X indicates the log(OP) and Y indicates the log(SPM).Įxample profiles of potential density (kg m −3) and SPM (g m −3) derived from OP, collected at a station near the mouth of the CRE, on. The model II regression line is shown, with its equation and statistics. Term obtained from the LISST only when observations with N ≤ 0.05 s −1 were included. Scatterplots of SPM (g m −3) vs 1-m bin-averaged OP (m −1 for and ) derived from a LISST, an ac-9, and a bb2fl in the CRE transects in log–log space.

The goodness of fit and the statistical significance of regression are expressed as r and p values, respectively. Term r is between TAC and when N ≤ 0.05 s −1, and the correlation coefficient between TAC and, is over the entire range of N. Data collected when N > 0.05 s −1 (gray ×) and N ≤ 0.05 s −1 (black dot). The with N ≤ 0.05 s −1 is well correlated with TAC, and and are strongly correlated with TAC for the full range of N. Scatterplots of 1-m bin-averaged TAC (m −1) with OP (m −1 for and ) derived from (a) a LISST, (b) an ac-9, and (c) a bb2fl.

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