The relative influence of local and regional environmental drivers of algal biomass (chlorophyll-a) varies by estuarine location

A major question in restoring estuarine water quality is whether local actions to manage excess nutrients can be effective, given that estuaries are also responding to tidal inputs from adjacent water bodies. Several types of statistical analysis were used to examine spatially-detailed and long-term water quality monitoring data in eight sub-estuaries of Chesapeake Bay. These sub-estuaries are likely to be similar to other shallow systems with moderate to long water residence times. Statistical cluster analysis of spatial water quality data suggested that estuaries had spatially distinct water quality zones and that the peak algal biomass (as measured by chlorophyll-a) was most often controlled by local watershed inputs in all but one estuary, although mainstem inputs affected most estuaries at some times and places. An elasticity indicator that compared inter-annual changes in sub-estuaries to parallel changes in the mainstem Chesapeake Bay supported the idea that water quality in sub-estuaries was not strongly coupled to the mainstem. A cross-channel zonation of water quality observed near the mouth of estuaries suggested that Bay influences were stronger on the right side of the lower channel (looking up estuary) at times in all estuaries, and was most common in small estuaries closest to the mouth of the primary water source to the estuary. Where Bay influences were strong, estuarine water quality would be expected to be less responsive to nutrient reductions made in the local watershed. Regression analysis was used to evaluate hypothesized relationships between environmental driver variables and average chlorophyll-a (chl-a) concentrations. Chl-a values were calculated from unusually detailed levels of spatial sampling, potentially providing a more comprehensive view of system conditions than that provided by traditional sparse sampling networks. The univariate models with the best data support to explain variability in averaged chl-a concentration were those that reflected water residence time. Of the land cover variables tested, septic density in the riparian zone explained the most variance in chl-a. The multivariate models that most improved upon the residence time effect added TN or TP flows (normalized by volume) and suggested that chl-a will be less responsive to nutrient reductions in estuaries that are poorly flushed. (C) 2016 Elsevier Ltd. All rights reserved.