Environmental triggers of hypoxia in the Elkhorn Slough Kristy Schmit Civil and Environmental Engineering, Stanford University (2) (2)

Abstract Results The Elkhorn Slough Reserve is one of California’s few remaining coastal wetlands. The reserve is dedicated to research including ecological studies, weather, water quality, erosion as well as other areas of environmental concern. The Elkhorn Slough experiences variations in dissolved oxygen content, DO Daily Minimum and Daily Average Water Temperature sometimes entering the hypoxic range. Hypoxia is an important measure of water quality because of its effect on ish and other benthic organisms. This 24 22

papers look at the effects of meteorological data on hypoxia in the Elkhorn Slough. Water temperature is one variable that is signiicantly correlated to 20

hypoxia. A model is created that may be used to input daily weather forecast information and output a warning signal when it appeared that conditions 18 might reach hypoxia. 16 14

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Introduction Methods and Materials (C) Tempurature 6 This study examines environmental Data was obtained from the National Oceanic and Atmospheric 4 triggers of hypoxia in the Elkhorn Administration’s National Estuarine Research Reserve System Centralized 2 Slough Reserve, speciically in the Data Management Office for the year 2006. The water quality monitoring 0

DO Daily Minimum (mg/L) and Daily Average Water Water Average DO Daily Minimum (mg/L) and 1/1/06 3/2/06 4/1/06 5/1/06 station chosen was the South Marsh (labeled SM in Figure 1) weather 1/31/06 5/31/06 6/30/06 7/30/06 8/29/06 9/28/06 South Marsh region. There are 10/28/06 11/27/06 12/27/06 hundreds of species of wildlife that are station (labeled SM and WS, respectively, in Figure 1.) Water quality data Date was measured at intervals of 30 minutes. Meteorological data was taken sensitive to the water quality of the Daily Avg. Water Temp Daily Max DO Hypoxia Slough, which has been affected by every 15 minutes. anthropologic effects such as Four variables were chosen to correlate with DO: Figure 2. Dissolved oxygen and water temperature over time. agriculture and development.  a1 •Water Temperature (C): the daily arithmetic mean   DO Daily Minimum and Daily Average Air Temperature The goal of this study is to ind a way a 20 •Air Temperature (C): the daily arithmetic mean  2 to predict hypoxia. Often, hypoxia is [y] = [x1x2x3x4 ] + c 18 attributed to eutrophication from •Wind Speed (m/s): the daily arithmetic mean  a3 16 nutrient loading, especially nitrogen •Precipitation (mm): the daily sum    a4 (1). There are studies that also link 14 •DO (mg/L): the minimum daily value Equation 1. Multiple linear model hypoxia to weather parameters. 12 Results have shown that as MatLab was used to smooth the data in the following ways: 10 temperature increases; dissolved Each variable was plotted with DO over time on separate graphs to see 8

oxygen decreases (1). (C) Tempurature where there are significant trends. Linear regression was preformed to 6 This study looks at the effects of calculate R2 values. € 4 meteorological data on hypoxia in the To create a useful tool that could be used as a prediction model, DO was 2 Elkhorn Slough. In order to measure evaluated as a function of all 4 variables in a multiple linear regression

DO Daily Minimum (mg/L) and Daily Average Air Average DO Daily Minimum (mg/L) and 0 hypoxia, the dissolved oxygen (DO) (See Equation 1).

1/1/06 3/2/06 4/1/06 5/1/06 content in mg/L will be used. 1/31/06 5/31/06 6/30/06 7/30/06 8/29/06 9/28/06 A MatLab function called FMINCON was used to solve for the linear 10/28/06 11/27/06 12/27/06 Dates Conditions are considered hypoxic Figure 1 . Map of the Elkhorn Slough Reserve function of the 4 variables in order to minimize the error or achieve a “best when the DO content is below 2mg/L. showing the location of monitoring stations (2). fit” approximation. Daily Avg. Air Temp Daily Min DO Hypoxia Figure 3. Dissolved oxygen and air temperature over time.

There was a stronger correlation with Discussion temperature than with the other parameters, with DO decreasing as temperature increased. The range of daily average DO values is from 0.2 to 14 mg/L, with values dipping into the hypoxic zone in The correlation was strongest with water the summer months (June‐Aug). The average DO value for the year of 2006 is 6.3 mg/L. There were days temperature, as seen in Table 1. where daily DO averages were in the hypoxic range 16.6% of the year (between June 3 and November 11). In Figure 4, the multiple linear regression The strongest correlation was between temperatures and dissolved oxygen was expected. Water model is plotted with the actual measured DO temperature had a stronger effect on DO than air temperature because water temperature directly affects values, and it can be deduced that this model the solubility of oxygen in water. As precipitation and wind increased, DO increased as well. This correlation would be a reasonable tool for predictions. was very small. The model that was created is a step towards creating a useful tool to allow for weather forecast information to predict hypoxia. In addition to showing how well the model predicts DO, the plot in Figure 6 also supports the previous indings of the researchers that DO is affected by temperature, season, and peak References primary production periods. 1. Stow, Craig A., Song S. Qian, and J. Kevin Craig. 2005. Declining Threshold for Hypoxia in the Gulf of Mexico. Environ. Sci. Technol. 2005, 39, 716-723. Conclusions 2. Site Statistical Analysis of Sixteen Years of Water Quality Data Project. (2008) Many Estuarine environments around the world are experiencing a decline in dissolved oxygen content Report to the Elkhorn Slough Foundation and the Community Foundation for and the effects on the ecosystem are of major concern (3). Although there are many factors that inluence Monterey County. Prepared by the University of California at Santa Cruz. dissolved oxygen content, it appears water temperature is one variable that could be used to predict http://www.elkhornslough.org/research/waterquality_volunteer.htm (Accessed on hypoxia. This study shows that as water temperature increases, the likelihood of hypoxia increases. By November 6, 2009.) improving on the model created, it may be possible to create a program that would input daily weather 3. Diaz, Robert J. 2001. Overview of Hypoxia around the World. J. Environ. Qual. forecast information and output a warning signal when it appeared that conditions might reach hypoxia. Figure 4. Multiple linear regression model to predict effects of all four variables: 2001, 30, 275–281. water temperature, air temperature, wind speed, and precipitation.

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