James D. Hagy

Phytoplankton Production and Nutrient Distributions in a Subtropical Estuary: Importance of Freshwater Flow

The relationships between phytoplankton productivity, nutrient distributions, and freshwater flow were examined in a seasonal study conducted in Escambia Bay, Florida, USA, located in the northeastern Gulf of Mexico. Five sites oriented along the salinity gradient were sampled 24 times over the 28-mo period from 1999 to 2001. Water column profiles of temperature and salinity were measured along with surface chlorophyll and surface inorganic nutrient concentrations. Primary productivity was measured at 2 sites on 11 dates, and estimated for the remaining dates and sites using an empirical regression model relating phytoplankton net production to the product of chlorophyll, euphotic zone depth, and daily solar insolation. Freshwater flow into the system varied markedly over the study period with record low flow during 2000, a flood event in March 2001, and subsequent resumption of normal flow. Flushing times ranged from 1 d during the flood to 20 d during the drought. Freshwater input strongly affected surface salinity distributions, nutrient flux, chlorophyll, and primary productivity. The flood caused high turbidity and rapid flushing, severely reducing phytoplankton production and biomass accumulation. Following the flood, phytoplankton biomass and productivity sharply increased. Analysis of nutrient distributions suggested Escambia Bay phytoplankton alternated between phosphorus limitation during normal flow and nitrogen limitation during low flow periods. This study found that Escambia Bay is a moderately productive estuary, with an average annual integrated phytoplankton production rate of 290 g C m−2 yr−1.

A simple model for forecasting the effects of nitrogen loads on chesapeake bay hypoxia

The causes and consequences of oxygen depletion in Chesapeake Bay have been the focus of research, assessment, and policy action over the past several decades. An ongoing scientific re-evaluation of what nutrient load reductions are necessary to meet the water quality goals is needed. While models can provide insights and advice for public policy on load reduction goals, they are caricatures of nature, and it is wise to use independent modeling approaches. In this paper, we describe our simple, biophysically based model that offers a middle ground between statistical models and complex dynamic models. Our model suggests that the target total nitrogen load reduction of 35% will reduce hypoxic volumes by 36–68%, which, on average (53% or 3.4 km3) is lower than values reported for 1950–1970 (4.2 km3), and roughly half of the values reported for 1980–1990 (7.2 km3). By pursuing a simple model construct, we were able to quantify uncertainty to a greater extent than is possible with the more complex numerical models. Yet, by retaining some mechanistic detail we could validate the model against state variables and process rates, an advantage over simple regressions.

Effects of Hurricane Ivan on Water Quality in Pensacola Bay, Florida

Pensacola Bay, Florida, was in the strong northeast quadrant of Hurricane Ivan when it made landfall on September 16, 2004 as a category 3 hurricane on the Saffir-Simpson scale. We present data describing the timeline and maximum height of the storm surge, the extent of flooding of coastal land, and the magnitude of the freshwater inflow pulse that followed the storm. We computed the magnitude of tidal flushing associated with the surge using a tidal prism model. We also evaluated hurricane effects on water quality using water quality surveys conducted 20 and 50 d after the storm, which we compared with a survey 14 d before landfall. We evaluated the scale of hurricane effects relative to normal variability using a 5-yr monthly record. Ivans 3.5 m storm surge inundated 165 km2 of land, increasing the surface area of Pensacola Bay by 50% and its volume by 230%. The model suggests that 60% of the Bays volume was flushed, initially increasing the average salinity of Bay waters from 23 to 30 and lowering nutrient and chlorophylla concentrations. Additional computations suggest that wind forcing was sufficient to completely mix the water column during the storm. Freshwater discharge from the largest river increased twentyfold during the subsequent 4 d, stimulating a modest phytoplankton bloom (chlorophyll up to 18 μg l−1) and maintaining hypoxia for several months. Although the immediate physical perturbation was extreme, the water quality effects that persisted beyond the first several days were within the normal range of variability for this system. In terms of water quality and phytoplankton productivity effects, this ecosystem appears to be quite resilient in the face of a severe hurricane effect.

An approach to developing numeric water quality criteria for coastal waters using the SeaWiFS Satellite Data Record.

Human activities on land increase nutrient loads to coastal waters, which can increase phytoplankton production and biomass and associated ecological impacts. Numeric nutrient water quality standards are needed to protect coastal waters from eutrophication impacts. The Environmental Protection Agency determined that numeric nutrient criteria were necessary to protect designated uses of Florida’s waters. The objective of this study was to evaluate a reference condition approach for developing numeric water quality criteria for coastal waters, using data from Florida. Florida’s coastal waters have not been monitored comprehensively via field sampling to support numeric criteria development. However, satellite remote sensing had the potential to provide adequate data. Spatial and temporal measures of SeaWiFS OC4 chlorophyll-a (ChlRS-a, mg m–3) were resolved across Florida’s coastal waters between 1997 and 2010 and compared with in situ measurements. Statistical distributions of ChlRS-a were evaluated to determine a quantitative reference baseline. A binomial approach was implemented to consider how new data could be assessed against the criteria. The proposed satellite remote sensing approach to derive numeric criteria may be generally applicable to other coastal waters.

Adaptation of a Weighted Regression Approach to Evaluate Water Quality Trends in an Estuary

To improve the description of long-term changes in water quality, a weighted regression approach developed to describe trends in pollutant transport in rivers was adapted to analyze a long-term water quality dataset from Tampa Bay, Florida. The weighted regression approach allows for changes in the relationships between water quality and explanatory variables by using dynamic model parameters and can more clearly resolve the effects of both natural and anthropogenic drivers of ecosystem response. The model resolved changes in chlorophyll-a (chl-a) from 1974 to 2012 at seasonal and multi-annual time scales while considering variation associated with changes in freshwater influence. Separate models were developed for each of the four Bay segments to evaluate spatial differences in patterns of long-term change. Observed trends reflected the known decrease in nitrogen loading to Tampa Bay since the 1970s. Although median chl-a has remained constant in recent decades, model predictions indicated that variation has increased for upper Bay segments and that low biomass events in the lower Bay occur less often. Dynamic relationships between chl-a and freshwater inputs were observed from the model predictions and suggested changes in drivers of primary production across the time series. Results from our analyses have allowed additional insight into water quality changes in Tampa Bay that has not been possible with traditional modeling approaches. The approach could easily be applied to other systems with long-term datasets.

Approach to developing numeric water quality criteria for coastal waters: transition from SeaWiFS to MODIS and MERIS satellites

Abstract States can adopt numeric water quality criteria into their water quality standards to protect the designated uses of their coastal waters from eutrophication impacts. The first objective of this study was to provide an approach for developing numeric water quality criteria for coastal waters based on archived SeaWiFS ocean color satellite data. The second objective was to develop an approach for transferring water quality criteria assessments to newer ocean color satellites, such as MODIS and MERIS. Measures of SeaWiFS, MODIS, and MERIS chlorophyll- a ( Chl RS - a , mgm − 3 ) were resolved across Florida’s coastal waters between 1998 and 2009. Annual geometric means of SeaWiFS Chl RS - a were evaluated to determine a quantitative reference baseline from the 90th percentile of the annual geometric means. A method for transferring to multiple ocean color sensors was implemented with SeaWiFS as the reference instrument. The Chl RS - a annual geometric means for each coastal segment from MODIS and MERIS were regressed against SeaWiFS to provide a similar response among all three satellites. Standardization factors for each coastal segment were calculated based on the differences between 90th percentile from SeaWiFS to MODIS and SeaWiFS to MERIS. This transfer approach was allowed for future assessments, typically with < 7 % difference in the calculated criteria.