RELATION OF THE SPATIAL AND TEMPORAL DISTRIBUTION OF WATER QUALITY PARAMETERS TO HYDROGEOLOGY AT INDIAN

Transcription

1 RELATION OF THE SPATIAL AND TEMPORAL DISTRIBUTION OF WATER QUALITY PARAMETERS TO HYDROGEOLOGY AT INDIAN RIVER BAY, DELAWARE: FIELD OBSERVATIONS AND MODELING by Cristina Fernandez A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Master of Science in Geology Spring Cristina Fernandez All Rights Reserved

2 RELATION OF THE SPATIAL AND TEMPORAL DISTRIBUTION OF WATER QUALITY PARAMETERS TO HYDROGEOLOGY AT INDIAN RIVER BAY, DELAWARE: FIELD OBSERVATIONS AND MODELING by Cristina Fernandez Approved: Holly A. Michael, Ph.D. Professor in charge of thesis on behalf of the Advisory Committee Approved: Susan McGeary, Ph.D. Chair of the Department of Geological Sciences Approved: Nancy M. Targett, Ph.D. Dean of the College of Earth, Ocean and Environment Approved: Charles G. Riordan, Ph.D. Vice Provost for Graduate and Professional Education

3 ACKNOWLEDGMENTS I would like to take this opportunity to thank everyone that helped me during my research. This thesis would not have been finished without your help. First of all, I would like to thank my academic advisor, Dr. Holly A. Michael for her guidance during these past three years. You believed in my potential from the start and extended me a hand after graduating from my BS. Your knowledge, talent, and dedication to your research and students inspired me these years. Many times when I thought I was not going to make it or my goals were unreachable, you made me see the brighter side of things and pointed my to the right direction. I thank you for providing me the tools to reach my goals and for giving me the opportunity to work in this project. I would like to thank my committee members, Leonard F. Konikow and Dr. Bill Ullman for guiding me through my research and working closely with me to get the results that I wanted. I would also like to thank Kevin Kroeger for helping me interpreting my data and revising my thesis drafts. I would like to thank my research group, Christopher Russoniello, James Heiss, Fang Tan, Mahfuzur Khan and Audrey Sawyer for creating a great working environment and expanding my knowledge in different aspects of hydrogeology. Your comments and suggestions throughout these years were very helpful. I would like to thank my field assistants Andrew Musetto, Kevin Myers, Deon Knights, Nicholas Spalt, David Wessell, Joshua Humberston, Suzanne McCormick, Sean Krepski, Lindsay Byron, Beau Croll, Maryam Akhavan, and Christopher Bason. iii

4 Your hard work in the field was invaluable for my research. I would also like to thank Joanna York for helping in the laboratory with nutrients analyzes and Scott Andres for installing the wells. I would like to thanks my funding sources The National Science Foundation (EAR ), Department of Geological Sciences at the University of Delaware, ORAU Powe Award and the SMART Scholarship. Finally, I would like to thank my family for their unconditional love and support: Mom, Dad, Sebastian, and Wally. Mom and Dad, you hard work and dedication is reflected in everything that you do and have been an inspiration in my life. You have taught me that anything is possible in life with the right mind, willingness, and perseverance. I would also like to thank Jose Rivera for his love, support, and patience. You have shown me what it is really important in life and I will always be thankful for having you in my life. iv

5 TABLE OF CONTENTS LIST OF TABLES... vii LIST OF FIGURES... viii ABSTRACT... xiii Chapter 1 INTRODUCTION Motivation Background Objectives and Scope STUDY AREA Hydrogeology Relevant Studies at Indian River Bay METHODS Spatial Distribution of Salinity and Nutrients Temporal Variability in Salinity and Nutrients Tidal Cycle Experiments: Short-Term Variability in Salinity and Field Parameters Lunar tidal cycles: Neap and Spring Tide Model Setup RESULTS Spatial Distribution of Salinity, Nutrients and Field Parameters Temporal Variability of Salinity, Nutrients and Field Parameters Tidal Variations Seasonal Variations Modeling Results v

6 4.3.1 Effects of Paleochannel DISCUSSION Comparison of Porewater Salinity and Resistivity Measurements Discussion of Field Measurements Geologic Controls on Flow and Salinity Nutrient Distribution Discussion of Temporal Variability of Field Parameters Discussion of Modeling SUMMARY AND CONCLUSIONS REFERENCES Appendix A MULTILEVEL WELL SAMPLING B SPECIFICATIONS OF YSI INTRUMENT C WATER QUALITY AND NUTRIENT DATA vi

7 LIST OF TABLES Table 3.1 Sampling schedule of monitoring wells Table 3.2 Sampling schedule of multilevel wells Table 3.3 Parameters used in simulations Table 4.1 Average values of salinity, nutrients concentration and field parameters for onshore monitoring wells over different seasons. Refer to Table 3.1 for sampling schedule of monitoring wells Table 4.2 Average and standard deviation of salinity, nutrients and field parameters from MLW2 and MLW6 sampled during neap tide (September 27, 2010). Measurements were averaged at each depth for four different sampling times during half of a tidal cycle. Nutrients were only analyzed at low tide. YSI Professional Pro Instrument general specifications are included in Appendix B. SW= surface water Table 4.3 Average and standard deviation of salinity, nutrients and field parameters from MLW2 and MLW6 on spring tide experiment (October 8, 2010). SW= surface water. Measurements were averaged at each depth for three different sampling times during half of a tidal cycle. Nutrients were only analyzed at high tide and low tide Table 4.4 Nutrient concentration in monitoring wells for different months, October 2010 and March/April Table B.1 Professional Plus system specifications. Table was adapted from YSI website ( 111 Table C.1 Water quality and nutrient data for monitoring wells reported by month sampled Table C.2 Water quality and nutrient data for MLWs reported by month sampled Table C.3 Spring and neap tide water quality and nutrient data for MLW2 and MLW vii

8 LIST OF FIGURES Figure 1.1 Figure 1.2 Figure 1.3 Conceptual model of coastal aquifers and processes that control SGD and salinity distributions. Process 1 represents fresh groundwater discharging at the coast driven by upland gradients. Process 2 represents saline circulation due to density differences along the mixing zone. Source of saline groundwater is surface water. Process 3 represents induced movement of the mixing zone due to changes in tidal stage and fluctuations of the water table Nitrogen transformations that occur at salinity transition zones where redox gradients exit (modified from Santoro, 2010) Conceptual model of a heterogeneous aquifer where SGD is affected by a low-permeability layer (dark gray). Fresh groundwater does not discharge at the coast, but instead it flows further offshore creating a complex salinity distribution in the subsurface. a) Shore perpendicular view and b) shore parallel cross-section. Fresh groundwater offshore would mix with saline groundwater before discharge along the edges of the paleovalley Figure 2.1 Map and photos of the Holts Landing State Park study site Figure 2.2 Figure 2.3 Figure 2.4 Idealized stratigraphic sequence of a paleovalley fill. Yellow color in background represents aquifer material consisting primarily of sands. (Modified from Banaszak, 2011) Geologic control of subsurface resistivity offshore of Holts Landing State Park: a) interpretation of paleovalleys and interfluves from seismic reflectors; b) relationship of resistivity and paleovalley cap. Note that high porewater resistivity coincides with paleovalleys which are capped with low-permeability sediments (J. Bratton, personal communication) Interpretation of paleovalley and interfluve system offshore of Holts Landing State Park from seismic data collected in summer Contours at 1m interval representing the depth to the Holocene/pre- Holocene boundary. Two individual paleovalleys are separated by an interfluve. The paleovalleys merge offshore. Depths are relative to the seafloor (D. Krantz and J. Banaszak, personal communication) viii

9 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 3.5 Figure 3.6 Figure 4.1 Map showing location of monitoring wells and multilevel wells (MLW) Gauge height during neap (September 27, 2010) and spring tide (October 8, 2010) experiments. Blue and red markers indicate neap and spring tidal height, respectively. Arrows refer to approximate time of sampling of multilevel wells (MLW2 and MLW6). Refer to Figure C.3 (Appendix C) for exact sampling times and depth at each M LW. Gauge height data was obtained from the United States Geological Survey (USGS) tidal station at Rosedale Beach, Indian River Bay ( USGS&referred_module=sw) a) Domain of watershed scale model (C. Russoniello, personal communication) showing area where particles were placed; b) model domain for this study chosen based on pathlines (blue lines) Geometry of model domain showing boundary conditions, hydraulic conductivity, and geometry of features. a) boundary conditions, b) low-k cap extending onland and offshore (not cropped), b) high-k channel in Unit 3 (cropped at 0.7 z-direction). Vertical exaggeration is 30x.boundary conditions, b) low-k cap extending onland and offshore (not cropped), b) high-k channel in Unit 3 (cropped at 0.7 z- direction). Vertical exaggeration is 30x a) Map showing location of model domain, b) grid was refined from 100 m to 10 m in the shore-perpendicular direction. The grid discretized into 77 columns, 105 rows and 12 layers, c) elevation of top of Unit 1. High-K channel follows low relief areas onland along the center of model (turquoise blue areas) Picture of a core taken along the shore of Holts Landing State Park showing peats and clays filling paleovalleys Average values of salinity of onshore monitoring wells over different sampling times. Numbers in parenthesis indicate depth to the bottom of the screen relative to land surface. Screens intervals are 1.5 m Figure 4.2 Map showing location of multilevel wells (MLWs) Figure 4.3 Depth profiles of salinity, nutrients and field parameters from MLW1 at Holts Landing. Points at a depth above 0 m indicate baywater values ix

10 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Depth profiles of salinity, nutrients and field parameters from MLW2 at Holts Landing. September 2010 data are from the tidal experiment on neap tide Depth profiles of salinity, nutrients and field parameters from MLW3 at Holts Landing Depth profiles of salinity, nutrients and field parameters from MLW4 at Holts Landing Depth profiles of salinity, nutrients and field parameters from MLW5 at Holts Landing Depth profiles of salinity, nutrients and field parameters from MLW6 at Indian River Bay. September 2010 data are from the tidal experiment on neap tide Depth profiles of salinity, nutrients and field parameters from MLW7 at Holts Landing Figure 4.10 Depth profiles of salinity, nutrients and field parameters from MLW8 at Holts Landing Figure 4.11 Coefficient of variation for salinity measurements with depth for neap (September 27, 2010) and spring (October 8, 2010) tidal cycle experiments. Depth profiles show coefficient of variation < 0.1 which means that the variability in salinity was very low Figure 4.12 Nutrient concentration profile of MLW2 and MLW6 at neap (September 27, 2010) and spring tide (October 8, 2010). Nutrient concentrations are very similar with depth at each tidal cycle experiment. On neap tide, nutrients are reported at low tide. For spring tide, nutrient concentrations were average at high and low tide and plotted with depth. Neap and spring data are circles and crosses, respectively. MLW2 and MLW6 are represented in blue and red, respectively Figure 4.13 Profiles of salinity from MLWs from Indian River Bay over different months x

11 Figure 4.14 Top view of salinity distribution for simulation without a highpermeability channel. Dashed line represents the location of the transect shown in cross-section (see Figure 4.15). Figure is cropped at 0.6 in the z-direction using Model Viewer software (Hsieh & Winston, 2002); the top 40% of the model thickness is cropped away Figure 4.15 Cross-section view of salinity distribution for simulation without high-permeability channel. Location of cross-section is indicated in Figure 4.14 with a dashed line. Vertical exaggeration is 30x Figure 4.16 Top view of salinity distribution for simulation with a highpermeability channel (cropped at 0.6 in the z-direction). Dashed line represents the location of the transect shown in cross-section (see Figure 4.17) Figure 4.17 Cross-section view of salinity distribution for simulation with highpermeability channel. Location of cross-section is indicated in Figure 4.14 with a dashed line. Vertical exaggeration is 30x Figure 5.1 Figure 5.2 Figure 5.3 Figure 5.4 Figure 5.5 Map showing resistivity image (10 m depth) and location of multilevel wells (MLW). Red colors represent freshwater and purple colors saline water. East-west continuous resistivity tracklines are shown in purple Comparison of continuous resistivity lines (a, c) and porewater resistivity (b, d) of MLW2, MLW6 and MLW7. Porewater resistivity shows variations with depth not captured with resistivity images Comparison of continuous resistivity lines (a) and porewater resistivity (b) of MLW8. Measured porewater resistivity decreases with depth while resistivity images show the opposite trend Resistivity image (10 m depth) and a) thickness of Holocene sediments. Interfluve (east) is cover by < 1 m thick low-permeability sediments and paleovalleys (west) are capped with > 1 m thick lowpermeability sediments. Note location of the fresh plume coincides with location of paleovalley. b) Location of multilevel wells relative to resistivity Nitrate (a) and ammonium (b) concentrations for onshore monitoring wells, offshore multilevel well and baywater. Arrows show outliers and the actual data is shown in parenthesis. Color of arrows matches color of markers in the legend. Monitoring wells are located onshore and multilevel wells offshore. Refer to Figure 3.1 for well location xi

12 Figure 5.6 Figure 5.7 Figure 5.8 Figure 5.9 Map of two shore perpendicular transects and one parallel transect. Gray, orange and blue lines represent Transects 1, 2, and 3, respectively Transect 1 showing (a) salinity, (b) nitrate concentration, (c) ammonium concentration, and (d) Eh from Pi53-13 to MLW8. Refer to Figure 5.6 for a map showing transects. March 2011 and June 2011 data were used to make contour plots Transect 2 showing (a) nitrate concentration, (b) ammonium concentration and (c) Eh from Cluster 1 to MLW5. Salinities are not shown since all values are less than 4 along the transect. March 2011 and June 2011 data were used to make contour plots. Refer to Figure 5.6 for a map showing transects Transect 3 showing (a) salinity, (b) nitrate concentration, (c) ammonium concentration, and (d) Eh. This is a shore parallel transect from MLW5 to MLW1. Refer to Figure 5.6 for a map showing transect Figure 5.10 Long term record of water level data for Qi This well is located south of Holts Landing State Park on Holts Landing Road. Yellow arrows represent sample times. Seasonal amplitude was not large over the sample period Figure 5.11 Comparison of salinity profiles of MLWs. (a) Observed salinity for June (b) Simulated salinity from grid cell containing observation wells Figure A.1 Illustration of multilevel well (MLW) sampling and protective casing.107 Figure A.2 Picture of protective case for MLW tubing Figure A.3 Set up of equipment used for sampling of MLWs from the boat. Sample bottles used to collect water for nutrient analysis xii

13 ABSTRACT Submarine groundwater discharge (SGD) has been recognized as a major contributor of inorganic nutrients and other dissolved constituents to coastal waters. The composition of SGD and the resulting nutrient flux is largely determined by the geochemical reactions that occur in the subsurface prior to discharge, especially in zones where redox gradients exist. These zones can be affected by heterogeneity and transient forcing which can potentially enhance mixing between groundwater of different chemistry, causing chemical reactions that may decrease nutrient concentrations. This field study aims to understand how tides, seasonal fluctuations of the water table and geologic heterogeneities affect the distribution of salinity, nutrients, and field parameters in the subsurface and their variation in time. The study site is located at Holts Landing State Park in Indian River Bay, Delaware; an estuary affected by nutrients derived from SGD. The geology of the study site is characterized by a paleovalley/interfluve system which has an important effect on groundwater flow and SGD. The paleovalley infill sequence, coarse sediments at the bottom overlain by low-permeability sediments, allows the flow of fresh groundwater offshore by impeding discharge nearshore. This has resulted in a freshwater plume which has been imaged with resistivity surveys and extends ~ 1 km offshore beneath the bay. Thirteen monitoring wells on land and eight multilevel wells (MLW) offshore within and away from this freshwater plume were sampled for salinity, ph, oxidation-reduction potential (ORP), dissolved oxygen (DO) and nutrients. Selected MLWs were sampled over a tidal cycle on neap and spring tide. In xiii

14 addition, onshore monitoring wells and offshore MLWs were sampled every four months and monthly, respectively. Salinity measurements corroborate electrical resistivity data which mapped the geometry of the freshened groundwater plume offshore beneath the paleovalley cap. Salinity profiles from offshore MLWs show salinity gradients where shallow fresh groundwater (~2 ) underlies saline groundwater (~25 ) and show that transition zones do not move substantially in response to seasonal fluctuations in the water table elevation, tidal fluctuations or amplitude. Likewise, nutrient concentrations were stable over time. Fresh groundwater onshore had higher dissolved oxygen levels and ORP than groundwater offshore, independent of salinity. Ammonium was the dominant species in saline groundwater. Onshore shallow wells near the marsh and brackish wells also had high ammonium concentrations. The highest nitrate concentrations (755 μm) were observed in fresh groundwater onshore at a depth >12 m, while nitrate was nearly absent in groundwater offshore. The apparent nonconservative behavior of nitrate indicates that nutrients fluxes may be lower than expected when fresh flow paths are longer under paleovalley caps. Direct discharge of nitrate to the bay can occur if nitrate-bearing groundwater does not come into contact with reducing conditions. A numerical groundwater model was constructed with SEAWAT to simulate 3D, variable-density groundwater flow with site specific parameters of the field site. Simulation results support the influence of geologic heterogeneity on the subsurface salinity distribution. Models that included the paleochannel feature consisting of a high-permeability channel overlain by a low-permeability cap were able to reproduce patterns in observed salinities offshore. In contrast, models with the low-permeability xiv

15 cap without the high-permeability channel did not produce the offshore fresh plume. Modeling results indicate that the paleochannel feature strongly controls subsurface salinity and provides evidence that the sediments at the base of the channel are more permeable than the surrounding aquifer. This investigation highlights the importance of geologic heterogeneity in controlling salinity distributions in the subsurface. The research demonstrated that transient forcing is not as important as the spatial variability in salinity and nutrients near shore at our field site. The non-conservative behavior of nitrate suggests that denitrification can occur along fresh groundwater flow paths beneath the paleovalley cap. It is possible that direct discharge of nitrate to the bay can occur if nitrate-bearing groundwater does not come into contact with reducing conditions. Saline groundwater offshore is a significant source ammonium and may be the dominant N-species in SGD in the vicinity of the paleochannel feature. xv

16 Chapter 1 INTRODUCTION 1.1 Motivation Eutrophication, resulting from excess input of nutrients to surface waters, is one of the most important causes of water quality deterioration in many coastal water bodies around the world. Nutrients can reach coastal waters via riverine inputs, atmospheric deposition and submarine groundwater discharge (SGD). Groundwater flow to coastal waters consist of both freshwater and recirculated seawater, and studies have shown that fluxes are up to 40% of riverine inputs (Moore, 1996). The fresh component of SGD is generally a source of new nutrients. Thus, it is of significant ecological importance, especially where fresh groundwater concentrations are several orders of magnitude higher than receiving water (Johannes, 1980; Valiela et al., 1990). Chemical reactions in the subsurface alter nutrient concentrations in groundwater, in turn affecting nutrient fluxes to coastal waters. Beck and others (2007) showed that high nutrient concentrations were altered along flowpaths prior to discharge. For example, phosphorous is attenuated in fresh groundwater by the adsorption onto iron and aluminum-oxides in sediments (Spiteri et al., 2008), decreasing phosphorous loading in fresh SGD. Nitrate in fresh groundwater can be converted to N 2 (g), a less bioavailable form, via denitrification as groundwater comes into contact with low oxygen levels and organic-rich sediments within the aquifer. Mixing zones of freshwater and saline groundwater near the coast are particularly active zones where geochemical transformation can take place (Moore, 1

17 1999; Slomp and Van Cappellen, 2004). Nutrient dynamics in mixing zones and associated fluxes are strongly affected by the redox conditions in the salinity transition zone (Spiteri et al., 2008; Slomp and Van Cappellen, 2004). Slomp and Cappellen (2004) suggested that at the salinity transition zone where oxic groundwater meets with anoxic saline groundwater, significant nitrate could be removed. Other studies have found that Fe and Mn (hydr)oxides can form when reduced groundwater mixes with oxygenated seawater and have the potential to remove dissolved chemical constituents such as P, Th, and Ba (Charette and Sholkovitz, 2002; Charette et al., 2005). Therefore, salinity transition zones are hotspots for reaction in coastal areas and are important in determining the chemical composition of SGD. The objective of this study is to characterize the hydrogeologic control on the spatial and temporal distributions of salinity, field parameters, and nutrients at Holts Landing State Park, Delaware. This was accomplished with spatially-distributed onshore and offshore groundwater sampling repeated on tidal to seasonal timescales as well as numerical model simulations. 1.2 Background Submarine groundwater discharge (SGD) refers to the flow of both fresh and recirculated seawater from the seabed to the ocean (Burnett et al., 2003; Moore, 2010) and has been identified as an important transport pathway for dissolved chemical constituents and nutrients (Charette and Sholkovitz, 2006). The source of the discharging water is important in determining the nutrient composition of SGD. Fresh groundwater, driven by a hydraulic gradient (Figure 1.1), can introduce new nutrients to support productivity to surface waters. In some areas, the flux of fresh SGD can be relatively low and saline SGD may comprise a significant portion of the total SGD and 2

18 contribute significant recycled nutrients (Michael et al., 2005; Santos et al., 2009). Higher nutrient concentrations in groundwater than adjacent surface water has been documented in many locations (Slomp and Cappellen, 2004); thus even in areas where the magnitude of SGD is low compared to surface water inputs, groundwater may be a significant contributor of nutrients to coastal waters. Estimating groundwater-derived nutrients fluxes to coastal waters can be challenging, however, because chemical transformations occurring along complex groundwater flow paths and salinity transition zones can be difficult to observe and quantify. Nutrient fluxes via SGD are often estimated from the concentration of dissolved constituents from fresh groundwater and total SGD rates (Giblin and Gaines, 1990; Beck et al., 2007). The concentration of the constituent of interest is then multiplied by the water flux to obtain the chemical flux. There are underlying assumptions and uncertainties associated with this approach. First, groundwater flow rates can vary significantly over time and space (Stieglitz et al., 2008; Taniguchi et al., 2006; Santos et al., 2009). Second, the concentration of the dissolved constituent in fresh groundwater is assumed to be the same as in the discharging groundwater. Last, the chemical contribution by the saline component of SGD is ignored. Several numerical and field studies have shown that SGD rates are highly heterogeneous in space (Michael et al., 2003; Taniguchi et al., 2006) as well as the fresh and saline component of SGD. In heterogeneous aquifers, groundwater can flow through preferential flow paths resulting in highly variable SGD rates near shore (Stieglitz et al., 2008). Concentrations along groundwater flow paths in several studies have been shown to be different onshore and offshore (Beck et al., 2007). Consequently, these assumptions do not always hold true for coastal systems. 3

19 Subsurface heterogeneities can directly affect SGD and salinity distributions, which could cause large uncertainties in discharge rates that are often estimated based on uniform geologic conditions. Lithological changes in the aquifer can create preferential flow paths that may be overlooked if SGD fluxes determined from direct measurements are averaged over large areas. Geophysical methods used in a study off the coast of South Carolina reveal that variations in resistivity along shore correlated spatially to geologic features in the subsurface which include paleochannels, breaching confining units and outcropping of seismic reflector on the sea floor (Viso el at., 2010). Offshore the North Carolina coast, breaching of confining units by a paleochannel has been proposed as a likely mode of groundwater/seawater exchange (Mulligan et al., 2007). Numerical simulation showed that the freshwater/saltwater transition zone occurs landward below the channel and showed that SGD occurs along the channel margins while seawater recharge occurs along the channel axis (Mulligan et al., 2007). SGD investigations from a fractured basement rock aquifer system in Flamengo Bay, Brazil, identified preferential flow patterns and paths of fresh groundwater using geophysical methods and seepage meter measurements (Stieglitz et al., 2008). SGD rates at this site would have been underestimated if the spatial variability of SGD due to heterogeneity were not taken into account. Estimating fluxes is further complicated by the transient nature of coastal systems. Transient forcing mechanisms affect rates of SGD and act at different time scales. Using a theoretical model for SGD, Li et al. (1999) demonstrated that wave setup and tidal pumping may be the largest contributors to the large SGD rates reported by Moore (1996). The authors reported that 96 % of the total SGD was recirculated seawater while 4 % was fresh SGD. Continuous seepage meters 4

20 measurements in Osaka Bay, Japan revealed an inverse correlation of SGD rates and tidal forcing (Taniguchi, 2002). His results showed that SGD rates decreased with increasing tidal level because the hydraulic gradient between groundwater and seawater is lowered as water level increases during high tide. Using field methods and numerical simulations, Michael et al. (2005) showed that large saline discharge was controlled by movement of salinity transition zone due to seasonal fluctuations of the water table. The effects of interannual climate oscillations on rates of SGD have recently been studied on barrier islands in the southeastern United States which are affected by El Nino-Southern Oscillation (ENSO) (Anderson and Emmanuel, 2010). Numerical simulations showed that fresh and recirculated SGD significantly correlated with ENSO. Anomalies of 35 % between El Nino and La Nina for up to 5 months lag can have significant impact in hydrologic and biogeochemical conditions in ENSOinfluenced coastal systems (Anderson and Emmanuel, 2010) Several methods are used to estimate rates of SGD. Among the most used methods to measure SGD are seepage meters and natural tracers. Several seepage meter studies have focus on characterizing the spatial and temporal variability of SGD (Burnett et al., 2006; Michael et al., 2003; Taniguchi et al., 2006) with direct measurements. A study conducted off the coast of Kyushu Island in Japan used seepage meters to evaluate spatial distributions of SGD and found that fresh SGD rate decreases away from the coast while recirculated SGD was highest near shore due to wave setup and tidal pumping (Taniguchi et al., 2006). On the other hand, a seepage meter investigation in Waquoit Bay found that SGD was highly variable and high saline discharge occurs a distance from shore (Michael et al., 2003). Natural tracers have also been widely used to estimate discharge. Moore (1996) attributed the large 5

21 enrichment of 226 Ra to groundwater discharge along the South Atlantic Bight and concluded that groundwater flux was about 40% of the surface water flux. Another indirect method that is often used in SGD studies is electrical resistivity surveys, which detect changes in the electrical conductivity of the porewater and lithology. These, used in conjunction with direct and tracer measurements, provide information on porewater salinity and can indicate locations of fresh SGD and the response of the subsurface freshwater-saltwater interface to temporal forcing (Manheim et al., 2004; Swarzenski et al., 2006). In situ porewater salinity measurements and vibradrilling have proven to be useful to ground-truth resistivity measurements that corresponded to fresh or saline groundwater in sediments of contrasting characteristics (Manheim et al., 2004). Time series resistivity and geochemical tracers were used at Dor Beach, Israel to calculate rates of SGD and both methods yielded similar groundwater exchange rates (Swarzenski et al., 2006). Other investigations have monitored the development of a freshwater plume over a tidal cycle using resistivity surveys and were able to show that SGD responded significantly to tidal stage (Swarzenski et al., 2007). Numerical groundwater flow modeling has been used to estimate SGD and investigate the effects of hydrologic forcing on rates and composition of SGD. Previously, numerical simulations have focused on the effects of tides and waves on groundwater flow and SGD in coastal aquifers and have concluded that recirculated seawater (Figure 1.1) is a significant component of SGD (Li et al., 1999; Robinson et al., 2007, Xin et al., 2010). Numerical models have also been used to compare SGD estimates with direct measurements of SGD. A density dependent groundwater model used to predict SGD in Florida concluded that the magnitude and spatial distribution 6

22 of SGD reported by seepage meters could not be explained by steady-state flow conditions and suggested that forcing mechanisms acting at other time scales contributed to the total SGD (Smith and Zawadzki, 2003).Numerical simulations are very useful tools for studying the processes controlling SGD, but they are often too simplified and, therefore, do not adequately represent hydrologic conditions and geologic heterogeneities present in many coastal aquifers. Not only fluid fluxes are necessary to estimate chemical fluxes, but also concentrations and understanding transformation prior to discharge. One of the primary factors controlling nutrient fluxes is the redox conditions in the aquifer (Slomp and Cappellen, 2004; Spiteri et al., 2008). Redox gradients are usually found at the mixing zone where oxic freshwater encounters anoxic saline groundwater (Figure 1.2) (Slomp and Cappellen, 2004). In this case, aerobic degradation of organic matter in the saline porewater creates anoxic conditions. Nitrate from freshwater may undergo denitrification along the edge of the freshwater plume. Denitrification, the reduction of nitrate to N 2(g) is a favorable N transformation because it converts inorganic nitrogen (nitrate) to a less bioavailable form (N 2 ). The reduction process occurs under anoxic conditions and where organic matter is available. Another process that can occur at the salinity transition zone and within saline sediments is the breakdown of nitrogenous organic matter, which releases ammonium under anoxic conditions - a process termed ammonification or nitrogen mineralization. Ammonium can accumulate in saline groundwater when organic matter and dissolved oxygen concentrations are low. Consequently, biogeochemical reactions in the subsurface control the concentrations of dissolved inorganic nitrogen and can determine the fate of N-species prior to discharge (Slomp and Cappellen, 2004; Spiteri et al., 2008). 7

23 Figure 1.1 Conceptual model of coastal aquifers and processes that control SGD and salinity distributions. Process 1 represents fresh groundwater discharging at the coast driven by upland gradients. Process 2 represents saline circulation due to density differences along the mixing zone. Source of saline groundwater is surface water. Process 3 represents induced movement of the mixing zone due to changes in tidal stage and fluctuations of the water table. 8

24 Figure 1.2 Nitrogen transformations that occur at salinity transition zones where redox gradients exit (modified from Santoro, 2010). 9

25 Figure 1.3 Conceptual model of a heterogeneous aquifer where SGD is affected by a low-permeability layer (dark gray). Fresh groundwater does not discharge at the coast, but instead it flows further offshore creating a complex salinity distribution in the subsurface. a) Shore perpendicular view and b) shore parallel cross-section. Fresh groundwater offshore would mix with saline groundwater before discharge along the edges of the paleovalley. 10

26 1.3 Objectives and Scope The objective of this study is to characterize the relation between geologic features and spatial distributions of salinity, field parameters, and nutrients at Holts Landing State Park, Delaware. Groundwater samples were collected from offshore and onshore wells at different time scales (tidal to seasonal) to determine the effect of transient forcing on salinity and nutrient distributions. A 3D variable-density groundwater model with site-specific parameters was used to simulate observed salinity patterns in the subsurface. One innovative aspect of this study is that it incorporates long term (greater than one year) time series measurements of salinity and nutrients. The work also provides evidence of non-conservative transport of nutrients along flow paths and identifies locations where nitrogen transformations can occur, potentially reducing nutrient loads to the bay. 11

27 Chapter 2 STUDY AREA The study site is Holts Landing State Park (38 35'30'' N, 75 7'47''W), on the southern margin of Indian River Bay, DE (Figure 2.1). Indian River Bay is a tidal estuary with an average tidal amplitude of < 1 m. Exchange with the Atlantic Ocean occurs through Indian River Inlet. Indian River Bay is connected to the north to Rehoboth Bay and to the south through a canal with Little Assawoman Bay (not shown on Figure 2.1). Indian River Bay is a drowned river valley that trends perpendicular to the coast. The morphology of the other two bays is largely controlled by the formation of landward migrating barrier beach complexes. Indian River Bay is very shallow with bottom elevations ranging from -2 m to -6 m relative to mean low water (MLW). Maximum depths (< -30 m, MLW) are found at the inlet. The average salinity of the lower parts of the Bay is 28. Indian River Bay is highly eutrophic due to nutrient over-enrichment. Freshwater enters the bay from tributaries, runoff, and direct groundwater discharge, the latter being the focus of this study. Fresh groundwater discharge to the bay comes primarily from the Columbia aquifer, which is the surficial aquifer in the region. Direct discharge of fresh groundwater is one of the main nutrient sources to Indian River Bay (Andres, 1987; Bason, 2011). Human related activities such as development, agriculture, agroindustry, and waste management practices within the watershed have increased the risk of contamination of the surficial aquifer. In 2007, more than a quarter of the land in the watershed was used for agriculture (Bason, 12

28 2011). Among the most common land uses in region are croplands and chicken production, which contribute significant amounts of nitrogen to groundwater (Bason, 2011). 13

29 14 Figure 2.1 Map and photos of the Holts Landing State Park study site.

30 2.1 Hydrogeology The surficial aquifer is the unit of interest in this study because it is the primary source of fresh groundwater to Indian River Bay. The thickness of the unconfined aquifer is ~25m at Holts Landing State Park. The primary geologic units that compose the surficial aquifer are: 1) Holocene low-permeability marsh sequences, organic-rich muds and estuarine deposits (Chrzastowski, 1986); 2) the Pliocene Beaverdam Formation, which is characterized by fine to coarse sands with interbedded silts and clays (Andres, 2004). 2.2 Relevant Studies at Indian River Bay During the Wisconian glaciation, Indian River Bay, as many other bays in the eastern United States, was above sea level. The ancestral Indian River channel and its tributaries occupied what today is Indian River Bay (Chrzastowski, 1986). These fluvial systems carved down channels (paleovalleys) into the exposed coastal plain sediments. Paleovalleys are common features at Indian River Bay (J. Bratton, personal communication) and other areas (Snyder et at, 1994; Zhang and Li, 1996), but the infill sequence of these paleovalleys can vary from place to place depending on the geologic history. In general, paleovalley infill sequences are characterized by coarser sediments deposited during active fluvial regimes. At Indian River Bay as sea level rose, these incised valleys were infilled with primarily fine-grained and organic-rich sediments overlying fluvial coarse sands (Figure 2.2) (Chrzastowski, 1986). The distribution of the incised-valley infill sequences and the local hydrologic regime will determine the preferential pathways for submarine groundwater discharge (SGD) to Indian River Bay. 15

31 Previous investigations at Indian River Bay have identified geologic features that were inferred to control groundwater flow, mixing and SGD (Bratton et al., 2004; Krantz et al., 2004; Manheim et al., 2004). Generally, fresh groundwater discharges near shore due to contrasting density of fresh and saline waters, but geologic heterogeneities at Indian River Bay have modified flow and discharge patterns. Streaming offshore resistivity surveys conducted at Indian River Bay along with high resolution CHIRP seismic surveys and drilling have provided insight into the geologic controls of SGD and the spatial distribution of fresh and saline groundwater (Bratton et al., 2004; Krantz et al., 2004, Manheim et al., 2004). A high resistivity zone offshore of Holts Landing State Park was interpreted as a fresh groundwater plume that extended ~ 1 km from the shoreline beneath the bay (Manheim et al., 2004). The presence of freshened groundwater coincided with buried incised paleovalleys interpreted from seismic tracklines (Figure 2.3). The paleovalleys are filled with coarse fluvial sands and capped with low-permeability sediments in the upper 1 m which act as a semi-confining layer at the seafloor. The permeability contrast of subsurface sediments near shore impedes discharge of fresh groundwater at the shoreline, and instead, forces fresh groundwater to flow offshore through the Holocene sediments. Seismic data obtained in summer 2010 was used to create a map of the depth to the Holocene/pre-Holocene contact, which was interpreted as the base of the paleovalley/interfluve system offshore of Holts Landing State Park (Figure 2.4). Salinity and nutrient distributions have been studied at Indian River Bay to provide additional information about the groundwater flow system and the chemical transformation occurring prior to discharge (Bratton et al., 2004). Salinity and nutrient measurement were obtained from four temporary wells that were removed after 16

32 groundwater samples were collected. Therefore, they only captured a snapshot of the salinity and geochemical environment and were not able to evaluate any responses to transient temporal forcing. Nitrate and N 2 were found in fresh groundwater while ammonium was nearly absent. Brackish groundwater had primarily ammonium and no nitrate. The source of nitrate in fresh groundwater was the surficial aquifer which carries dissolved nutrients from upland regions. Ammonium in saline groundwater is produced within organic-rich sediments and transported by the cyclic downward movement of baywater through the subsurface which eventually discharge to the bay. Direct discharge of nitrate-bearing groundwater to Indian River Bay was not evident. However, there was enough evidence (presence of N 2 ) to suggest that most of the nitrate in fresh groundwater was denitrified before mixing with saline groundwater or prior discharge. In this study, I intend to expand the understanding of the local groundwater systems by characterizing the salinity and nutrient distributions in three dimensions in the vicinity of the paleovalley feature, as well as the response to tides and seasonal fluctuations in the water table and sea level, which was not done in previous studies at this site. This site provides a unique opportunity to study the effects of large- and small-scale geologic heterogeneities on the processes that affect salinity and nutrient distributions. 17

33 Figure 2.2 Idealized stratigraphic sequence of a paleovalley fill. Yellow color in background represents aquifer material consisting primarily of sands. (Modified from Banaszak, 2011) 18

34 Figure 2.3 Geologic control of subsurface resistivity offshore of Holts Landing State Park: a) interpretation of paleovalleys and interfluves from seismic reflectors; b) relationship of resistivity and paleovalley cap. Note that high porewater resistivity coincides with paleovalleys which are capped with low-permeability sediments (J. Bratton, personal communication). 19

35 Figure 2.4 Interpretation of paleovalley and interfluve system offshore of Holts Landing State Park from seismic data collected in summer Contours at 1m interval representing the depth to the Holocene/pre- Holocene boundary. Two individual paleovalleys are separated by an interfluve. The paleovalleys merge offshore. Depths are relative to the seafloor (D. Krantz and J. Banaszak, personal communication). 20

36 Chapter 3 METHODS Field methods and computer simulations were used to characterize the temporal and spatial distribution of submarine groundwater discharge (SGD), subsurface salinity, and porewater chemistry. Field methods consisted of repeated porewater sampling of multilevel wells (MLW) and monitoring wells and were used to characterize the subsurface distribution of salinity and nutrients, to ground-truth geophysical resistivity profiles, and to compare observed salinities with model results. The SEAWAT code (Guo and Langevin, 2002) was used simulate 3D variable-density groundwater flow in a model with site-specific parameters reflecting conditions at the Holts Landing field site. 3.1 Spatial Distribution of Salinity and Nutrients Holts Landing State Park was instrumented with 13 onshore monitoring wells and 8 multilevel wells (MLW) with penetration depths ranging from 3 to 22 m from land surface. The multilevel well system allowed groundwater sampling of discrete zones along a single borehole. These systems consist of 9 cm screens placed at different depths. The MLW tubes are segmented into seven channels to allow groundwater sampling at up to 7 depth-discrete zones. Polyethylene (¼ outside diameter) sample tube extended above the baywater (Appendix A). The annular space at the screen depths were filled with play sand to allow groundwater to flow easily. In 5 multilevel wells (MLW3, 4, 5, 6, and 8), bentonite clay was emplaced at the top of the hole and between ports to avoid connection with ports above or below. Multilevel wells 1, 2, and 7 do not have bentonite seals and therefore may experience some short- 21

37 circuiting during sampling. However, salinity profiles indicate that there is not much communication, as salinities are stable over time regardless of sample volume (see Chapter 4). Monitoring wells were constructed of 2 PVC pipes with 1.5 m screen intervals made of slotted PVC. The onshore monitoring wells are located throughout Holts Landing State Park and are arranged in clusters or solitary (Figure 3.1). Since spring 2010, most of these wells have been instrumented with pressure, conductivity, and temperature dataloggers. Sampling of monitoring wells was conducted in fall 2010, spring 2011, and summer The wells were sampled using either a gaspowered suction pump or a submersible pump. The sampling protocol consisted of pumping at least 3 times the casing volume before sampling to remove standing water in the wells. Groundwater was pumped through polyethylene tubing and passed through a flow-through cell (YSI 3059 flow cell) equipped with conductivity, dissolved oxygen (DO), oxidation reduction potential (ORP), ph, and temperature sensors (YSI Professional Plus). All the sensors were calibrated before use according to the user manual specifications. Additional details about calibration procedures are included in Appendix B. For each water sample, salinity, ph, ORP, DO and temperature were recorded with a YSI instrument with the auto stable option enabled. The auto stable system of the YSI instrument examines the previous five measurements, computing the percent change in the data and comparing the change against a % threshold value selected by the user. The sensitivity used for all measurements was 75 or % data variance threshold. Subsequently, water for nutrient analyses was filtered through a Millipore filter (0.45 µm pore). The sample bottle (Figure A.3, Appendix A) was rinsed at least three times with sample before a 50 ml sample was collected for analysis. Samples were immediately stored in ice and 22

38 then frozen until analysis in a Seal AutoAnalyzer at the University of Delaware, Lewes Campus. The sampling protocol of the MLWs was similar to the monitoring wells. However, MLWs were located offshore and were accessed by boat (Appendix A, Figures A.1, A.2, and A.3). A submersible cover was designed to house and protect the polyethylene tubing that sampled each depth. The cover consisted of an expandable solid drainage pipe attached to the top of a 55-gal drum. Galvanized anchor chains and lead weights (Figure A.2, Appendix A) were attached around the expandable pipe to minimize movement due to currents in the bay. A rake was used to raise the pipe from the bottom (Figure A.1, Appendix A). The pipe was then attached to the boat using a metal wire. Extensions of polyethylene tubing were connected to the MLW tubing for ease of sampling. The volume of water purged from each MLW depended on the depth of the sampling port, approximately ~500 ml for shallow ports and 1 to 2 L for deep ports and the pumping rate was ~500 ml/min. Similarly to monitoring wells, field parameters were measured and water samples were collected. 23

39 Figure 3.1 Map showing location of monitoring wells and multilevel wells (MLW). 24

40 3.2 Temporal Variability in Salinity and Nutrients In order to capture variations in salinity and nutrients due to hydrologic forcing on timescales of tidal cycles and seasons, monitoring wells and MLWs were sampled regularly between summer 2010 and fall 2011 (Tables 3.1 and 3.2). In addition, tidal cycle experiments were performed on MLW2 and MLW6. In November 2010 and May-August 2011, all eight multilevel wells were sampled with the exception of MLW2 in May In other months, selected MLWs were sampled with focus on those displaying salinity gradients with depth Tidal Cycle Experiments: Short-Term Variability in Salinity and Field Parameters Temporal forcing such as tides and waves can induce movement of the freshwater-saltwater interface. In order to understand the effects of tides on the transition zone, MLW2 and MLW6 were selected for diurnal and lunar tidal experiments because their vertical profiles show salinity gradients. They are located approximately 20 m apart and are arrayed parallel to the shoreline (Figure 3.1). MLW2 has 7 sampling ports evenly distributed each with a 9 cm screen located between 0.8 m and 15 m beneath the bay bottom. MLW6 captures the transition zone at much finer scale with sampling ports evenly distributed from 7 m to 15 m beneath the bay bottom. Samples were taken every 2 hours between high and low tide (Figure 3.2). For each water sample, salinity, ph, ORP, DO and temperature were recorded with a YSI Pro Plus instrument. After the parameters were stable, a water sample was filtered through a 0.45µm Millipore filter. Groundwater samples were preserved in ice and subsequently frozen for nutrient analysis. 25

41 3.2.2 Lunar tidal cycles: Neap and Spring Tide Two tidal sampling experiments were conducted during different tidal ranges, neap (September 27, 2010) and spring tide (October 8, 2010), to determine the effect of tidal range on salinity and nutrient distributions. Porewater was sampled and collected every two hours over half of a tidal cycle (falling tide) at MLW2 and MLW6 on neap and spring tide (Figure 3.2). Only one MLW was sampled at a time due to equipment limitations. Therefore, sampling occurred 4 and 3 times over half of a tidal cycle for neap and spring tide, respectively (Figure 3.2). Tidal amplitude at neap tide was 0.33 m and at spring tide 0.47 m (Figure 3.2). On neap tide, sampling began at 0900 and continued until 1815 while spring sampling was much shorter, starting at 1020 and ending at

42 Table 3.1 Sampling schedule of monitoring wells. DGS ID 1 Fall 2010 Spring 2011 Summer 2011 Pi52-07 x x* n/a 4.1 Pi52-08 x x* x* 14.3 Pi52-09 x x* x* 22.3 Pi53-06 x x x* 4.3 Pi53-07 x x x* 14.3 Pi53-08 x x x* 22.3 Pi53-10 x x x* 5.6 Pi53-12 x x x* 4.0 Pi53-13 x x x* 5.5 Pi53-30 x x x* 14.3 Pi53-51 x x x* 4.1 Pi53-52 x x* x* 4.1 Depth of screen bottom** (m) Pi53-53 x x x* Delaware Geological Survey (DGS) identification number * No nutrient analysis ** Depth relative to land surface n/a: no water sample collected 27

43 Table 3.2 Sampling schedule of multilevel wells. DGS ID 1 Jul 2010 Sep 2010 Oct 2010 Nov 2010 Mar 2011 Apr 2011 May 2011 Jun 2011 MLW 1 x* x x x x x MLW 2 x* x** x** x*** x x x x MLW 3 x* x x x x MLW 4 x* x x x x MLW 5 x* x x x x x Aug 2011 MLW 6 x** x** x x x x x x x MLW 7 x* x x x x x x MLW 8 x x x x x x x 1 Delaware Geological Survey (DGS) identification number * Only salinity was measured ** Tidal experiments *** Only deepest port (15 m below bay bottom) was sampled Oct

44 Figure 3.2 Gauge height during neap (September 27, 2010) and spring tide (October 8, 2010) experiments. Blue and red markers indicate neap and spring tidal height, respectively. Arrows refer to approximate time of sampling of multilevel wells (MLW2 and MLW6). Refer to Figure C.3 (Appendix C) for exact sampling times and depth at each M LW. Gauge height data was obtained from the United States Geological Survey (USGS) tidal station at Rosedale Beach, Indian River Bay ( GS&referred_module=sw). 29

45 3.3 Model Setup SEAWAT (Guo and Langevin, 2002), a three-dimensional variable-density groundwater flow and solute transport model, along with the ArgusOne graphical-user interface, were used to create a site-specific model of the unconfined aquifer and shallow geologic heterogeneities at the Holts Landing field site. Model boundaries and extent were chosen based on particle tracking results of a watershed-scale groundwater flow model (C. Russoniello, personal communication) (Figure 3.3). Flowpaths show that groundwater beneath Indian River Bay flows from the southern shore of the bay towards the center of the bay. By delineating our model boundaries as much as possible along flow paths, we were able to assume no-flow conditions along the sides and northern edge of our domain. The model domain extends 2,684 m (north-south) and 778 m (east-west) and narrows from the shoreline to the northern boundary. The base of the model is 28 m below mean sea level (MSL) (Figure 3.4). Lateral boundaries follow flowpaths that terminate near the bay axis (Figure 3.3). The northern boundary coincides with a flow divide at the seaward extent of the model. Surface topography and bathymetry were incorporated in the model as the elevation of the top of the uppermost unit (Figure 3.5). The areal extent and geometry of geologic features were derived from the Holocene/Pre-Holocene interpretation of the paleovalleys and interfluves, core logs and maps of marsh areas at Holts Landing State Park. Low-permeability sediments covered most of the offshore area, except where there were interfluves, which are inferred to be zones where Holocene sediments are thin or nearly absent (Figure 3.4). The low-permeability layer extends onshore, following the marsh geometry since hand cores along the shore showed peats and clays to a depth of ~3 m (Figure 3.6). A higher 30

46 permeability channel was conceptualized under the low-permeability channel fill materials representing fluvial sands at the base of the paleovalleys consistent with a typical infill sequence of an incised valley (Mixon, 1985; Belknap et al., 1994). The higher permeability channel extends farther inland following a low relief area trending north-south onshore (Figure 3.4). Depths to the boundary between the Holocene and Pre-Holocene contact were contoured in ArcMap (Figure 2.4, Chapter 2) and imported to ArgusOne to draw the geometry of the low-k layer. The model boundaries consist of no-flow conditions along the sides and at the base of the unconfined aquifer. The onshore boundary is a prescribed head set to the elevation of the land surface. The choice of prescribed head on land is reasonable, but an upper bound, given that water levels in the surrounding area are usually close to the land surface (~2 to 4 m below land surface). A hydrostatic pressure condition was specified offshore and along the vertical seaward boundary. Fresh and seawater concentrations are 0 and 28 kg/m 3, respectively. The model is discretized into 77 columns, 105 rows and 12 layers with a total of 105,105 finite difference cells (Figure 3.5). The model was divided into four units (Unit 1-4). Unit 1 is a thin (0.1 m) boundary layer on which the prescribed head is applied. The thickness of Unit 2 is 1 m. The elevation of the bottom Units 3 and 4 are -10 m and -28 m, respectively. Units 1 through 4 were vertically discretized into 1, 3, 5, and 4 model layers, respectively. The grid was refined in the shore-perpendicular direction ranging in size from 100 m to 10 m near the paleovalleys/interfluve system (Figure 3.5). We use a constant value for the modeled hydraulic conductivity that falls within the range of measured hydraulic conductivities (1x10-4 m/s). The hydraulic conductivity of the paleochannel sediments was not measured. However, shallow hand 31

47 cores obtained along the shoreline show that shallow sediments consist of lowpermeability peats and clays (Figure 3.6).The horizontal hydraulic conductivity (K x ) of the low-permeability layer was set to 1.1x10-11 m/s, which is consistent with published values for clays (Fetter, 2001). The vertical hydraulic conductivity (K z ) was 100 times lower than K z. This value had to be adjusted during initial models to recreate a freshwater plume offshore. The simulations were run until the total mass in the aquifer did not change, which is indicative of steady-state conditions. For the base case scenario, anisotropy was assumed to be 1:1:0.01 (Kx:Ky:Kz). Longitudinal dispersivity and molecular diffusion coefficients were 1 m and 1x10-10 m 2 /s, respectively. Other parameters are summarized in Table

48 Figure 3.3 a) Domain of watershed scale model (C. Russoniello, personal communication) showing area where particles were placed; b) model domain for this study chosen based on pathlines (blue lines). 33

49 34 Figure 3.4 Geometry of model domain showing boundary conditions, hydraulic conductivity, and geometry of features. a) boundary conditions, b) low-k cap extending onland and offshore (not cropped), b) high-k channel in Unit 3 (cropped at 0.7 z-direction). Vertical exaggeration is 30x.boundary conditions, b) low-k cap extending onland and offshore (not cropped), b) high-k channel in Unit 3 (cropped at 0.7 z-direction). Vertical exaggeration is 30x.

50 Figure 3.5 a) Map showing location of model domain, b) grid was refined from 100 m to 10 m in the shore-perpendicular direction. The grid discretized into 77 columns, 105 rows and 12 layers, c) elevation of top of Unit 1. High- K channel follows low relief areas onland along the center of model (turquoise blue areas). 35

51 Table 3.3 Parameters used in simulations. Parameter Value K (m/s), unconfined aquifer 1x10-4 K (m/s), low-permeability cap 1x10-11 Anisotropy: unconfined aquifer and low-permeability cap (Kz:Ky:Kz) 1:1:0.01 Kx* (m/s), high-permeability channel 0.01 Kz (m/s), high-permeability channel 1x10-7 α L (m), longitudinal dispersivity 1 α T (m), transverse dispersivity (m) 0.01 Molecular diffusion (m 2 /s) 1.5x10-10 Porosity 0.3 *The K value for the high-permeability channel was only used in the simulation with the channel present. 36

52 . Figure 3.6 Picture of a core taken along the shore of Holts Landing State Park showing peats and clays filling paleovalleys. 37

53 Chapter 4 RESULTS The purpose of this section is to present the results of this study obtained from field measurements and variable-density modeling. Results are reported in the following order: 1) spatial distribution of salinity, nutrients and field parameters, 2) temporal variability of salinity, nutrients and field parameters, and 3) modeling. Results from field measurements include data from monitoring wells and offshore multilevel wells (MLWs) that are labeled according to the Delaware Geological Survey database. All data collected in this study are included in Appendix C. The following categories are used to refer to groundwater based on its salinity: Fresh : 0-1 Brackish : > 1 and < 25 Saline: > 25 This classification was chosen based on salinities observed in onshore monitoring wells and surface water. Most wells located landward from the shore have salinities between 0 and 1 and represent fresh groundwater within the upland aquifer. Surface water at Indian River Bay has an average salinity of 28 ±2.1 and represents the highest salinities at this site. 4.1 Spatial Distribution of Salinity, Nutrients and Field Parameters Most of the monitoring wells onshore are fresh (< 0.5 ), with the exception of a few wells close to shore with higher salinity that varies significantly with depth (Table 4.1 and Figure 4.1). Because the salinities do not vary significantly during 38

54 different seasons (Section 4.2 and Appendix C), the measured salinities are reported as an average over different sampling months for onshore monitoring wells. Two wells (Pi53-13 and Pi53-52) are brackish with average salinity values of 1 and 2, respectively. At Cluster 3, the shallow well (Pi53-10) is brackish (~2.3 ), the intermediate well (Pi53-30) is fresh, and the deep well (Pi53-53), screened between 20 m and 22 m, has the highest salinity (~22 ) of all monitoring wells onshore, showing a significant variation with depth at this location (Figure 4.1). The field parameters, redox potential (Eh), dissolved oxygen (DO), and ph were also measured in samples from onshore monitoring wells (Table 4.1). Generally, shallow (< 6 m) fresh groundwater had lower Eh and DO than groundwater sampled from monitoring wells screened at 12 m below the land surface, suggesting that shallow fresh groundwater close to the marsh was more reducing than intermediatedeep fresh groundwater reflecting contrasting sources and biogeochemical history. The highest average DO values (6.3 mg/l) were found at Pi52-08 and the lowest (0.5 mg/l) at Pi Brackish groundwater was characterized by having low Eh and DO and higher ph (~ 6.3) values than fresh groundwater. Nitrate was the dominant inorganic nitrogen form in fresh groundwater at depths >12 m below the ground surface (Table 4.1). High ammonium concentrations (> 3 μm) were generally found in shallow fresh and brackish groundwater. Ammonium concentration was also high at Pi53-53, which has an average salinity of 22. Average phosphate concentration in monitoring wells was low (< 2 μm), except at Pi Silicate concentrations at monitoring wells varied significantly, ranging from 11 μm to 177 μm. Highest silicate concentrations were measured in brackish groundwater at Pi

55 Unlike the onshore monitoring wells, groundwater sampled from offshore MLWs shows salinity variations laterally and with depth. For MLWs, results are not averaged, but instead are presented as depth profiles for each sampling month (Figures ). A map of the location of each MLW is also provided for reference (Figure 4.2). The temporal variability in salinity, nutrients, and field parameters is discussed in Section 4.2. MLW1 (Figure 4.3) is fully saline (28 ) from 1.2 m to 7.6 m below the bay bottom. Porewater salinity at this well is very similar to the average salinity of Indian River Bay, 28 (Figure 4.3). For this study, three sampling locations (MLW 3-5) were sited in a freshened groundwater zone characterized by salinity > 1 and < 3 from 1 m to 15 m below the bay bottom (Figures 4.5, 4.6, and 4.7). The other MLWs (MLW2 and MLW6-8) capture salinity gradients that show fresher groundwater overlying brackish to saline groundwater (Figures 4.4, 4.7, 4.9, and 4.10). The salinity decreased gradually with depth at these four sites from ~ 2 to ~25 with sampling locations at depths ranging from 1 m to 16 m below the bay bottom. The freshwater overlying saline groundwater is thickest at MLW2 and thins farther offshore. Farthest from the shore at MLW8, the salinity profile shows two zones of freshened porewater, one at 11 m and the other on at 15 m. Geophysical logs at this site show interbedded sands and silty sand at depths > 2 m below the bay bottom. Groundwater may flow preferentially through high-permeability sediments, resulting in variations in salinity observed in MLW8. Although no salinities were measured <1 m below the bay bottom, a shallow salinity transition zone is expected to exist between the fresh groundwater zone and bay water. Groundwater sampled at offshore MLWs was generally reducing with low concentration of nitrate and high ammonium (Figures ). Eh values and DO 40

56 were low regardless of the salinity of the groundwater offshore. Nitrate concentrations were generally low, but in zones where freshened groundwater was present, nitrate concentrations were ~ 50 μm (Figures 4.6, 4.5, and 4.10). Ammonium concentration increased with increasing salinity (Figures 4.4, 4.8, 4.9, and 4.10). Along salinity transition zones, concentrations of ammonium in brackish groundwater at depth were at least one order of magnitude higher than in overlying fresher groundwater. At MLW1, ammonium concentration was ~ 120 μm and nitrate was absent. In groundwater sampled offshore, phosphate was generally low (< 10 μm) and silicate ranged from 0 μm to 100 μm. Phosphate and silicate tend to increase with increasing salinity along transition zones (Figures 4.4, 4.8, 4.9, and 4.10). 41

57 Table 4.1 Average values of salinity, nutrients concentration and field parameters for onshore monitoring wells over different seasons. Refer to Table 3.1 for sampling schedule of monitoring wells. 42 Depth to Salinity Eh DO NO 3 NH 4 PO 4 Si screen DGS ID ph bottom* ( ) (mv) (mg/l) (µm) (µm) (µm) (µm) (m) Pi Pi Pi Pi Pi Pi Pi Pi Pi Pi Pi Pi Pi * Depths are relative to land surface.

58 43 Figure 4.1 Average values of salinity of onshore monitoring wells over different sampling times. Numbers in parenthesis indicate depth to the bottom of the screen relative to land surface. Screens intervals are 1.5 m.

59 44 Figure 4.2 Map showing location of multilevel wells (MLWs).

60 depth (m) depth (m) Salinity Eh MLW1 Dissolved Oxygen mv mg/l ph Jul 2010 Nov 2010 Mar 2011 May 2011 Jun 2011 Aug 2011 SW Nov10 SW Mar NO 3 - NH 4 + PO 4-3 Si µm µm µm µm Figure 4.3 Depth profiles of salinity, nutrients and field parameters from MLW1 at Holts Landing. Points at a depth above 0 m indicate baywater values.

61 depth (m) depth (m) Jul 2010 Sep 2010 Nov 2010 Mar 2011 Apr 2011 Jun 2011 Aug Salinity Eh MLW2 Dissolved Oxygen mv mg/l ph NO 3 - µm NH 4 + µm PO 4-3 µm Si µm Figure 4.4 Depth profiles of salinity, nutrients and field parameters from MLW2 at Holts Landing. September 2010 data are from the tidal experiment on neap tide.

62 47 Figure 4.5 Depth profiles of salinity, nutrients and field parameters from MLW3 at Holts Landing.

63 48 Figure 4.6 Depth profiles of salinity, nutrients and field parameters from MLW4 at Holts Landing.

64 depth (m) depth (m) Salinity Eh MLW5 Dissolved Oxygen mv mg/l ph Jul 2010 Oct 2010 Nov 2010 May 2011 Jun 2011 Aug NO 3 - µm NH 4 + µm PO 4-3 µm Si µm Figure 4.7 Depth profiles of salinity, nutrients and field parameters from MLW5 at Holts Landing.

65 depth (m) depth (m) Salinity Eh MLW6 Dissolved Oxygen mv mg/l ph May 2011 Oct NO 3 µm NH 4 + µm PO 4-3 µm Si µm Figure 4.8 Depth profiles of salinity, nutrients and field parameters from MLW6 at Indian River Bay. September 2010 data are from the tidal experiment on neap tide.

66 depth (m) depth (m) Salinity Eh MLW7 Dissolved Oxygen mv mg/l ph Sep 2010 Nov 2010 Mar 2011 Apr 2011 May 2011 Jun 2011 Aug NO 3 - µm NH 4 + µm PO 4-3 µm Si µm Figure 4.9 Depth profiles of salinity, nutrients and field parameters from MLW7 at Holts Landing.

67 depth (m) depth (m) Salinity Eh MLW8 Dissolved Oxygen mv mg/l ph Sep 2010 Nov 2010 Mar 2011 Apr 2011 May 2011 Jun 2011 Aug NO 3 - µm NH 4 + µm PO 4-3 µm Si µm Figure 4.10 Depth profiles of salinity, nutrients and field parameters from MLW8 at Holts Landing.

68 4.2 Temporal Variability of Salinity, Nutrients and Field Parameters The temporal variability in subsurface salinity was assessed on tidal and seasonal timescales (Tables 4.2, 4.3, and 4.4, Figure 4.13). MLW2 and MLW6 were chosen for the tidal experiments because they are close to each other and they span a transition zone; salinity increases with depth in both. Fluctuations of the transition zone due to tides would enhance mixing of fresh and saline groundwater and it would be reflected in salinity changes. The head difference between freshwater and seawater is altered with the rise and fall of the surface water. We would expect that the increasing head at high tide induces saline groundwater movement towards land resulting in an increase in salinity at the interface. At low tide, the transition zone would retreat seaward because the difference in head between freshwater and baywater heads is greatest. However, results from repeat groundwater sampling show that the temporal variability is not significant at this site at the depths and locations sampled Tidal Variations Groundwater was sampled over a tidal cycle on neap (September 27, 2010) and spring (October 8, 2010) tide to further investigate the effects of tidal stage and tidal magnitude on the transition zone and to determine how mixing affects nutrient distributions. Tidal amplitude on neap tide was 0.33 m and on spring tide 0.47; the difference between neap and spring tidal amplitudes is not large at this site. Sampling occurred mostly on a falling tide (see Section 3.2, Chapter 3). The average salinity at each depth over a tidal cycle shows very little variation in salinity (Tables 4.2 and 4.3) for both neap and spring tide. Figure 4.11 shows a depth profile of the coefficient of 53

69 variation defined as the standard deviation over the mean of salinity. In this study, it was used as a measure of variability in salinity at each depth for each tidal experiment, neap and spring. The coefficient of variation at all depths was very low (< 0.1) indicating that there was no significant temporal variation in salinity. A coefficient of variation closer to 1 would indicate that there was greater variability in salinity. Similar to salinity, nutrient concentrations offshore were not greatly affected by temporal forcing (Tables 4.2 and 4.3). Since no salinity changes were observed in MLW2 and MLW6, we did not expect major changes in nutrient concentrations or field parameters at different tidal stage and tidal magnitude (Figure 4.12). For this reason, only selected samples were analyzed for nutrients, low tide on neap tide and high and low tide on spring tide. Nitrate was low (<2 μm), but it shows a peak at ~ 12 m. Ammonium, phosphate and silicate increase with depth, a trend observed on neap and spring tide Seasonal Variations On seasonal timescales, the salinity transition zone can shift landward or seaward in response to seasonal changes in the water table. In the summer, evapotranspiration is higher and groundwater recharge is therefore lower causing the water table to decline and the transition zone to move landward as the freshwater hydraulic gradient decreases. On the other hand, the water table rises in the winter and spring because evapotranspiration is weaker, causing the transition zone to move seaward. Movement of the transition zone can be evaluated by measuring porewater salinity during different seasons, similarly to movement over tidal cycles. The water table at this site fluctuates seasonally (see Chapter 5, Section 5.3); however, monthly monitoring of porewater from MLWs suggests that there are not significant monthly 54

70 or seasonal changes in porewater salinity in most locations at Holts Landing (Figure 4.13). Porewater samples collected at MLW1-6 show nearly constant salinity with depth from July 2010 to October 2011 (Figure 4.13; refer to Table 3.2 for actual sample months). The only exceptions were MLW7 and MLW8 in which porewater salinity for September and November 2010 was different from other months. In addition, data from the location farthest from the shore, MLW8, indicates that porewater salinity varied at ~11 m by fluctuating between between April 2011 and August These local variations in salinity were not related to transient forcing. However, changes in salinity may reflect groundwater in disequilibrium after well installation. The seasonal variability in nutrient concentration is also small. Only three MLWs (MLW1, 2, and 6) have nutrient concentration from different months. MLW3 had additional nutrient data for July, 2010 which was performed at the Agricultural Laboratory, University of Delaware. Silicate concentrations obtained from the Agricultural Laboratory were almost two orders of magnitude higher than those measured at the Lewes Laboratory, where we performed all nutrient analyses. Because of a differences in analytical methodology (Inductively Coupled Argon Plasma Emission Spectrometry use by the Agricultural Laboratory) that measures total dissolved silica rather than bioreactive silicate (measured by molybdenum blue at the Lewes laboratory), the data from the two laboratories are not directly comparable. The data from the Agricultural Laboratory are not used in the present analysis, but are reported in Appendix C). 55

71 The largest difference in nutrient concentration is observed at MLW6. At MLW6, phosphate concentration on September 2010 increased with depth, a trend not observed in other months. On September, 2010, Eh was ~ 100 mv higher (less reducing) than measurements taken on October and November, The lowest ph values (~4.5) were measured on September, The change in phosphate concentration at MLW6 on September 2010 seems to be controlled by a localized redox change based on Eh and ph rather than salinity changes because salinity was generally constant over time. In general, variations in Eh, DO and ph during different months were observed in all MLWs, but the variations did not follow any trends in time. The variations were difficult to interpret because salinities were generally stable over time and nutrient analyses were limited. Onshore monitoring wells did not show any significant changes in salinity over the period analyzed except for Pi53-53, where salinity decreased from 25 in October 2010 to 21 in March 2011 (Appendix C). Most of the onshore wells are screened in fresh groundwater zones far from saline groundwater, so we would not expect to see any major changes in salinity. Nutrient concentrations are mostly of the same magnitude over different seasons with silicate showing the most variability (Table 4.4). Results of phosphate and silicate will not be discussed further because the nutrients of interest for this study are the inorganic forms of nitrogen. 56

72 Table 4.2 Average and standard deviation of salinity, nutrients and field parameters from MLW2 and MLW6 sampled during neap tide (September 27, 2010). Measurements were averaged at each depth for four different sampling times during half of a tidal cycle. Nutrients were only analyzed at low tide. YSI Professional Pro Instrument general specifications are included in Appendix B. SW= surface water. 57 Port No. Well ID Salinity ( ) Eh (mv) DO (mg/l) ph NO 3 (μm) NH 4 + (μm) PO 4-3 (μm) Si (μm) Depth to screen* (m) SW n/a 30.0 ± ± ± ± MLW2 1.2 ± ± ± ± MLW2 1.3 ± ± ± ± MLW2 1.3 ± ± ± ± MLW2 1.5 ± ± ± ± MLW2 1.7 ± ± ± ± MLW2 2.7 ± ± ± ± MLW ± ± ± ± MLW6 2.1 ± ± ± ± MLW6 1.8 ± ± ± ± MLW6 6.5 ± ± ± ± MLW ± ± ± ± MLW ± ± ± ± MLW ± ± ± ± * Depths are relative to bay bottom.

73 Table 4.3 Average and standard deviation of salinity, nutrients and field parameters from MLW2 and MLW6 on spring tide experiment (October 8, 2010). SW= surface water. Measurements were averaged at each depth for three different sampling times during half of a tidal cycle. Nutrients were only analyzed at high tide and low tide. 58 Port No. Well ID Salinity ( ) Eh (mv) DO (mg/l) ph NO 3 - (μm) NH 4 + (μm) PO 4-3 (μm) Si (μm) SW n/a 27.5 ± ± ± ± n/a 29.9 n/a 0.8 n/a 56.1 n/a 0 1 MLW2 1.1 ± ± ± ± ± ± ± ± MLW2 1.2 ± ± ± ± ± ± ± ± MLW2 1.3 ± ± ± ± ± ± ± ± MLW2 1.4 ± ± ± ± ± ± ± ± MLW2 1.7 ± ± ± ± ± ± ± ± MLW2 2.8 ± ± ± ± n/a 2.4 n/a 0.1 n/a 11.2 n/a MLW ± ± ± ± ± ± ± ± MLW6 1.9 ± ± ± ± ± ± ± ± MLW6 1.8 ± ± ± ± ± ± ± ± MLW6 4.0 ± ± ± ± ± ± ± ± MLW ± ± ± ± ± ± ± ± MLW ± ± ± ± ± ± ± ± MLW ± ± ± ± ± ± ± ± * Depths are relative to bay bottom. Depth to screen* (m)

74 59 Figure 4.11 Coefficient of variation for salinity measurements with depth for neap (September 27, 2010) and spring (October 8, 2010) tidal cycle experiments. Depth profiles show coefficient of variation < 0.1 which means that the variability in salinity was very low.

75 depth (m) NO - 3 µm NH 4 + µm PO 4-3 µm Si µm neap MLW2 neap MLW6 spring MLW2 spring MLW Figure 4.12 Nutrient concentration profile of MLW2 and MLW6 at neap (September 27, 2010) and spring tide (October 8, 2010). Nutrient concentrations are very similar with depth at each tidal cycle experiment. On neap tide, nutrients are reported at low tide. For spring tide, nutrient concentrations were average at high and low tide and plotted with depth. Neap and spring data are circles and crosses, respectively. MLW2 and MLW6 are represented in blue and red, respectively.

76 depth (m) depth (m) MLW1 Salinity MLW2 Salinity MLW3 Salinity MLW4 Salinity Jul 2010 Jul 2010 Sep 2010 Nov 2010 Nov 2010 Mar 2011 Jul 2010 Mar 2011 May 2011 Nov Sep 2010 Apr 2011 Jun 2011 May Nov Jun Aug 2011 Jun Mar Jul 2011 Aug SW Nov10 Aug Sep Apr Oct SW Mar Nov May Nov Mar Jun May May Apr Aug Jun Oct May Aug 2011 Jun 2011 Aug MLW5 Salinity MLW6 Salinity MLW7 Salinity MLW8 Salinity Figure 4.13 Profiles of salinity from MLWs from Indian River Bay over different months.

77 Table 4.4 Nutrient concentration in monitoring wells for different months, October 2010 and March/April DGS ID October 2010 March/April 2011 Salinity NO 3 NH 4 PO 4 Si Salinity - + NO 3 NH 4 ( ) (µm) (µm) (µm) (µm) ( ) (µm) (µm) PO 4-3 (µm) Si (µm) Pi n/a n/a n/a n/a Pi n/a n/a n/a n/a Pi n/a n/a n/a n/a Pi Pi Pi Pi Pi n/a n/a n/a n/a Pi Pi n/a n/a n/a n/a Pi Pi Pi n/a indicates that no nutrient analysis was performed.

78 4.3 Modeling Results Effects of Paleochannel The purpose of the model was to asses conditions in which a salinity distribution similar to the observed would be reproduced. A simple model was developed and tested in which the surficial aquifer was simulated as homogeneous with a low-hydraulic conductivity (K) cap offshore. The low-permeability sediments that cap the high-permeability channel are present throughout the bay and in marsh areas onland. This simulation was run for ~ 130 years until a steady-state salinity distribution was reached. Modeled salinities are shown in Figures 4.14 and The model was divided in four units. The first unit is a thin (0.1 m) boundary layer on which the prescribed head is applied. The thickness of Unit 2 is 1 m. The elevation of the bottom Unit 3 and 4 are -10 m and -28 m, respectively. For the simplest case, the simulated salinities do not match observed salinities at MLWs. In the absence of the high-permeability channel, fresh groundwater does not flow offshore and instead discharges along the shoreline (Figures 4.14 and 4.15). The fresh groundwater plume does not form offshore and the salinity transition zone is close to the shoreline as in a typical coastal system (Figure 4.15). A second simulation included geologic conditions associated with paleovalleys and interfluves in which the infill sequence is characterized by fluvial sands (coarser sediments than the surrounding aquifer) underlying low-permeability sediments. To simulate this sequence, a second model was run with a high-permeability channel along the center of the model domain, capped with the same shallow low-permeability sediments as in the initial simulation. The high-permeability channel originates onland 63

79 and extends ~400 m offshore at 10m. The model was run for ~ 180 years until a steady-state salinity distribution was reached. Simulation results show fresh groundwater preferentially flowing through the high-permeability channel offshore instead of discharging at the coastline. This leads to formation of a freshwater plume offshore (Figures 4.16 and 4.17) consistent with observations. In the simulation with the high-permeability channel, the salinity transition zone occurs farther offshore along the channel axis than in areas where the channel is absent (Figure 4.17). Estimated fresh recharge for this simulation (with high-k channel) is 1.8x10-9 m/s. Recharge values that have been used in watershed scale models of the region range between 9.6x10-9 m/s and 1.5x10-8 m/s (12-19 inches/year) (C. Russoniello, personal communication). It is important to note that during trial runs (not shown) hydraulic conductivities (K x and K y ) of the low-k cap were an order of magnitude higher than the simulations reported here and did not satisfactorily reproduce the freshwater plume. In addition to the high-k channel, it was necessary to decrease K x, K y, and increase anisotropy within the low-permeability cap to reproduce the freshwater. The results of these simulations indicate that a unique geologic framework and suitable hydrologic conditions must be present to reproduce the observed salinities from MLWs. 64

80 Figure 4.14 Top view of salinity distribution for simulation without a highpermeability channel. Dashed line represents the location of the transect shown in cross-section (see Figure 4.15). Figure is cropped at 0.6 in the z-direction using Model Viewer software (Hsieh & Winston, 2002); the top 40% of the model thickness is cropped away. 65

81 66 Figure 4.15 Cross-section view of salinity distribution for simulation without high-permeability channel. Location of crosssection is indicated in Figure 4.14 with a dashed line. Vertical exaggeration is 30x.

82 Figure 4.16 Top view of salinity distribution for simulation with a high-permeability channel (cropped at 0.6 in the z-direction). Dashed line represents the location of the transect shown in cross-section (see Figure 4.17). 67

83 68 Figure 4.17 Cross-section view of salinity distribution for simulation with high-permeability channel. Location of crosssection is indicated in Figure 4.14 with a dashed line. Vertical exaggeration is 30x.

84 Chapter 5 DISCUSSION 5.1 Comparison of Porewater Salinity and Resistivity Measurements In coastal systems with high salinity contrasts, electrical resistivity is primarily controlled by interstitial salinity (Manheim et al., 2004). Electrical resistivity measurements detect variations in the conductivity of subsurface water and porous media. A 2D image is created of the apparent resistivity with depth, which is then inverted to true resistivity. Continuous resistivity surveys were used to site the multilevel wells (MLW). Three-dimensional interpretation of the resistivity data indicates that the freshwater plume offshore of Holts Landing State Park is at least 10 m thick, ~650 m wide, and may extend ~400 m offshore. Porewater sampling of MLWs confirms the lateral distribution of fresh and saline groundwater depicted in resistivity images (Figure 5.1). MLW 1 was sited in a low-resistivity zone interpreted as saline groundwater. A salinity profile at this site shows saline (~ 28 ) groundwater to 8 m below the bay bottom (see Chapter 4, Figure 4.13). Three wells (MLW3, 4, and 5) were sited along a high-resistivity freshwater plume (Figure 5.1). Salinity measurements at these locations are < 3 to a depth of 16 m (see Chapter 4, Figure 4.13) and confirm the presence of fresh groundwater offshore. The remaining multilevel wells (MLW2, 6, 7, and 8) were sited along the edge of the high-resistivity groundwater zone. As expected, salinity profiles show transitions from fresh (~ 3 ) groundwater to saline (~ 25 ) groundwater at depths. 69

85 For this investigation, resistivity images were compared in more detail to porewater resistivity measurements of MLW2, 6, 7, 8 to verify the presence of high resistivity (fresher) water offshore underlain by low resistivity porewater and to explore the resolution of the resistivity sections (Figures 5.2 and 5.3). In order to compare resistivity data and porewater salinity, specific conductance of the porewater at MLW2, 6, 7, and 8 were converted to resistivity (ohm-m) by inverting the specific conductance. Converted porewater resistivity were plotted and compared with the closest resistivity profile (Figures 5.1, 5.2, and 5.3). However, the vertical changes in resistivity at MLW2, 6, 7, and 8 (decreasing resistivity with depth) observed from porewater measurements are not depicted in resistivity sections (Figures 5.2 and 5.3). The resistivity surveys do not capture changes in resistivity at the resolution of porewater sampling and the trends seem opposite, possibly due to surface water interference and the inversion process of the resistivity surveys. Although resistivity surveys did not capture changes in resistivity with depth, this method was useful to map the lateral distribution of fresh and saline groundwater offshore. In this study, resistivity surveys were essential for siting wells. Resistivity surveys cover large areas with minimum effort and in a relatively short amount of time, producing 2D continuous representations of large-scale changes in subsurface salinity distributions. On the other hand, offshore porewater sampling is significantly more time consuming and provides locally-accurate and higher resolution information about groundwater salinity. Each method has advantages and disadvantages, but when combined, resistivity and porewater salinity measurements provide a detailed description of subsurface salinity distributions. 70

86 Figure 5.1 Map showing resistivity image (10 m depth) and location of multilevel wells (MLW). Red colors represent freshwater and purple colors saline water. East-west continuous resistivity tracklines are shown in purple. 71

87 a c b d 72 Figure 5.2 Comparison of continuous resistivity lines (a, c) and porewater resistivity (b, d) of MLW2, MLW6 and MLW7. Porewater resistivity shows variations with depth not captured with resistivity images.

88 a b Figure 5.3 Comparison of continuous resistivity lines (a) and porewater resistivity (b) of MLW8. Measured porewater resistivity decreases with depth while resistivity images show the opposite trend. 73

89 5.2 Discussion of Field Measurements Geologic Controls on Flow and Salinity Fresh groundwater flows from the recharge areas on land toward Indian River Bay. In homogeneous systems, fresh SGD is expected to occur near the shore; the position of the saltwater-freshwater interface is controlled by the flow and the width of the discharge zone. Brackish to saline SGD occurs beyond the transition zone. In the presence of paleovalleys filled with coarser sediments and capped with lowpermeability sediments, fresh groundwater does not discharge near the coast, but instead flows offshore. This is evident from the offshore freshwater plume at our site (Figure 5.4). Eventually, fresh and saline groundwaters are expected to mix and discharge as brackish SGD along the edges of the plume (see Chapter 1, Figure 1.3). Both of the above flow regimes are identified at our site based on salinity measurements and understanding of the geology. Two distinct geologic zones were identified; these have important effects on subsurface salinity and SGD: 1) the western zone where low-permeability sediments capping a paleovalley are present and 2) the eastern interfluves zone, where low-permeability sediments are thin or absent. Porewater salinity and seepage meter measurements provide evidence of complex groundwater flow and SGD at Indian River Bay controlled by geologic heterogeneity. On the eastern part of our study site where an interfluve is present and the low-permeability sediments are thin, we expect fresh SGD to occur near the coast. Seepage meter measurements show a zone of fresh focused discharge just offshore of Pi53-12 where 43 % of the total discharge is fresh (Russoniello et al., in preparation). Porewater salinity measurements at MLW1 (see Chapter 4, Figure 4.2), just offshore 74

90 of the zone of fresh focused discharge, suggest that the salinity transition zone occurs shoreward of MLW1 and penetrates inland based on brackish (~ 22 ) groundwater at Pi53-53, below freshwater at Pi53-30 (see Chapter 4, Figure 4.1). In the western part of the study site, the presence of coarser sediments filling the paleovalleys capped with low-permeability silts and muds control the salinity distribution and SGD west of the pier. Fresh groundwater flowing toward the bay does not discharge at the shore because the low-permeability sediments act as a cap to impede fresh SGD. The fresh groundwater mixes with saline groundwater prior to discharging along the contact between this paleovalley and interfluve (see Chapter 1, Figure 1.3). Freshened SGD was observed from seepage meter measurements along the channel flanks (Russoniello et al., in preparation), which is consistent with our conceptualization of the flow dynamics. Deeper fresh groundwater encounters the classical transition zone where it mixes with saline groundwater and can also discharge as brackish SGD Nutrient Distribution Groundwater flow dynamics at this site can have significant implications for the nutrient concentrations in SGD and consequently affect the water quality of Indian River Bay. Porewater sampling and nutrient analyses suggest that 1) nitrate is dominant in fresh groundwater in the surficial aquifer, 2) ammonium is highest in saline groundwater and in shallow fresh groundwater near marsh sediments; the source is the decomposition of marine organic matter, 3) nitrate concentrations are higher in fresh groundwater on land and lower in fresh groundwater offshore, and 4) redox gradients exist at freshwater-saltwater mixing zones and along freshwater flow paths. 75

91 Nitrate is the dominant inorganic form of nitrogen in fresh groundwater (Figure 5.5). Figure 5.5 shows concentration of nitrate as a function of salinity for all the data. Nitrate is highest in samples with salinity between 0 and 5 and is depleted at higher salinity. Fresh groundwater transports nitrate from the watershed to the coast; sources to groundwater include fertilizer application to cropland and animal waste from poultry. Nitrate measured in fresh groundwater in six of the thirteen onshore monitoring wells exceeded the estimated natural level of 28 µm. At one site (Pi52-09), the concentration exceeded 713 µm, the U.S. Environmental Protection Agency (USEPA) maximum concentration level (MCL) for drinking water. Five of these six wells are screened at depths >12 m and are located throughout Holts Landing State Park, which suggests that fresh groundwater carrying nitrate is a common occurrence in the surficial aquifer. Nitrate was observed in offshore multilevel wells in brackish groundwater (~ 3 ) at concentrations < 60 μm (Figure 5.5). Nitrate concentrations measured in brackish to saline groundwater offshore are very low (< 10 μm). Ammonium was predominantly found in brackish to saline groundwater (Figure 5.5) and its source is likely remineralization of organic matter in marine sediments. Ammonium concentration in groundwater from offshore MLWs was highly variable, but generally increased with increasing salinity (Figure 5.5). The lowest ammonium concentration measured at salinities above 15 was ~ 15 μm. At salinities < 5, ammonium concentrations were as high as ~ 40 μm and coincided with high nitrate groundwater of MLWs. These groundwaters rich in both nitrate and ammonium are characterized by being highly reducing and contain low DO. Where nitrate and ammonium co-exist and DO concentrations are low, suitable geochemical 76

92 conditions are present to promote denitrification. Ammonium was undetected in fresh groundwater (< 1 ) from monitoring wells onshore. However, ammonium concentrations > 50 μm were measured at monitoring wells Pi53-10 and Pi53-13 which have salinities ranging between 1 and 3. Both wells (Pi53-10 and Pi53-13) are screened at shallow depths (~5 m below land surface) and are located near the marsh. The degradation of organic-rich sediments from the marsh could account for the high ammonium concentrations at these two wells (Pi53-13 and Pi53-10). Moreover, higher salinity indicates increasing ion content in groundwater that would compete with ammonium for exchange sites and could result in higher concentrations of dissolved ammonium in groundwater. The distribution of nutrients at our field site is largely controlled by geologic heterogeneity. Because fresh groundwater travels from land to the shore, we determine that Transects 1 (Figure 5.7) and Transect 2 (Figure 5.8) are approximately representative of flow paths. Transect 1 (Figure 5.7) shows salinity, nutrients and Eh distribution in a shore-perpendicular direction from Pi53-13 to MLW8. This transect is located along the edge of the freshwater plume which is the contact between the paleovalley and interfluve and may also have a component of flow perpendicular, at least offshore. Transect 1 (Figure 5.7) shows a freshwater plume overlying saline groundwater. Nitrate was present in fresh groundwater onshore at depths > 12 m and was nearly depleted in groundwater offshore, independent of the salinity. Ammonium was higher in saline groundwater offshore. Eh measurements show that groundwater offshore is more reducing than fresh groundwater from land. Along Transect 1 (Figure 5.7), highly reducing saline groundwater mixes with oxic, nitrate bearing groundwater as the saline groundwater circulates from the surface and mixes with fresh 77

93 groundwater as it flows along the transition zone. The ammonium in saline groundwater can mix with fresh groundwater providing a constant supply of this constituent to potentially drive nitrification, while denitrification can proceed under low-oxygen levels decreasing nitrate concentrations offshore. Although nitrate-bearing groundwater may directly discharge via SGD shoreward of Cluster 3 and landward of MLW2 (Figure 5.7), we would expect that reducing conditions near shore favor denitrification and decrease nutrient loads to Indian River Bay. The distribution of nitrate along shore-perpendicular transects suggests that nitrate does not behave conservatively along flow paths (Figures 5.7 and 5.8). At Transect 2 (Figure 5.8), the salinity distribution is not shown because it is < 3. Nitrate is present onshore at depths > 12 m and nearly depleted offshore similar to Transect 1. High nitrate concentration (~ 750 μm) coincides with high Eh values (400 mv), which indicates that oxidizing conditions are prevalent onshore (Figure 5.8). Ammonium was absent in fresh groundwater onshore and was observed offshore at low concentration (< 3 μm). Fresh groundwater is present from Cluster 1 to MLW5, so the redox gradients observed along this transect are not a result of fresh groundwater mixing with saline groundwater, but could be the result of fresh groundwater coming into contact with organic-rich sediments. Decomposition of organic-rich sediments near the marsh and peats that cap the paleovalleys may account for the reducing conditions observed along fresh groundwater flowpaths, which could provide favorable geochemical conditions for denitrification. The fact that fresh groundwater offshore is depleted of nitrate suggests that nitrate is removed/consumed along the flowpath, which could potentially decrease nitrate loading to Indian River Bay. Co-occurrence of nitrate and ammonium (> 2 µm) both onshore and offshore 78

94 was observed in 11 % of the samples analyzed for nutrients. The presence of both inorganic forms of nitrogen is very unstable and could suggest that these zones are potential hot-spots for nitrogen transformations (Kroeger and Charette, 2008). Transect 3 (Figure 5.9) is located parallel to the shore and runs from east to west including MLW5 to MLW1. This transect shows in more detail the geochemical conditions from the center of the plume and the edges of the mixing zone. The salinity transition zone is observed between MLW2, 6 and MLW1. Nitrate was high (~50 μm) at MLW5, located near the center of the plume, and decreased toward MLW1. It is possible that geochemical conditions along the center of the plume are different than at the edges where there is substantial mixing with saline groundwater. The highest concentration of ammonium was found at MLW4 near the bay bottom. MLW4 has salinity of ~ 3, indicating some degree of mixing with saline groundwater and suggests that saline groundwater was the source and mixed with fresh. Higher salinity groundwater is highly reducing and has lower dissolved oxygen concentration compared with fresh groundwater, which provides suitable conditions for ammonium to accumulate (Figures 5.7, 5.8, and 5.9). Even though nutrient fluxes were not estimated in this study, nutrient concentrations in the subsurface suggest that nitrate fluxes to Indian River Bay could be lower than ammonium fluxes under paleovalley features. Fresh groundwater under paleovalley caps has longer fresh flow paths and more time for transformations. Fresh groundwater underneath the paleovalley cap is low in nitrate; this discharges along the edges of the plume as brackish to saline SGD. Bay water recirculates through the subsurface, accumulating ammonium along its flowpath before discharging. Because ammonium is the dominant inorganic form in saline groundwater and nitrate is almost 79

95 absent along mixing zone, we would expect ammonium concentration in the discharging water to be much higher than nitrate. Direct discharge of nitrate-bearing fresh groundwater could occur in the eastern part of the study site where nitrate is supplied from the surficial aquifer, fresh SGD rates are highest (Russoniello et al., in preparation), and low-permeability sediments are absent. The closest freshwater well to the shore in the eastern part of our study site (Pi53-12) has high nitrate concentration (~400 μm), which indicates significant nitrate is supplied from the surficial aquifer. Nitrate concentration measured in discharging groundwater with a field probe was ~200 μm (K. Kroeger, personal communication), which is much higher than any nitrate concentration measured offshore at MLWs. Organic rich-sediments are thin or nearly absent along the interfluve, which would suggest that relatively oxidizing conditions must be present that favor nitrate stability prior to discharge. Additional sampling sites north of Pi53-12 will provide detailed information about the fate of nitrate in fresh groundwater and would corroborate our understanding of nutrient dynamics and groundwater flow. The hydrogeologic setting at our study site may not be unique to Holts Landing State Park. These features are ubiquitous in the Inland Bays (J. Bratton, personal communication), but how they control SGD, flow paths, and salinity and nutrient distributions is still not well understood. Our data suggests that the these features can have significant effects on the composition of SGD. High nitrate onshore and low offshore along fresh groundwater flow paths suggest that nitrate fluxes via SGD may be small, except in areas where low-permeability sediments are absent and fresh SGD rates are high. On the other hand, ammonium was nearly absent in fresh 80

96 groundwater onshore and was primarily found in saline groundwater offshore. We would expect the contribution of ammonium by circulating seawater to be more significant than the contribution of new nitrate via fresh SGD to Indian River Bay. Our findings highlight the importance of characterizing the hydrogeology and its potential effects on nutrient concentration. Future investigations should focus on sampling along groundwater flow paths and near discharge locations to obtain better estimates of chemical composition of SGD and fluxes to the bay. 81

97 a b Figure 5.4 Resistivity image (10 m depth) and a) thickness of Holocene sediments. Interfluve (east) is cover by < 1 m thick low-permeability sediments and paleovalleys (west) are capped with > 1 m thick low-permeability sediments. Note location of the fresh plume coincides with location of paleovalley. b) Location of multilevel wells relative to resistivity. 82

98 a b Figure 5.5 Nitrate (a) and ammonium (b) concentrations for onshore monitoring wells, offshore multilevel well and baywater. Arrows show outliers and the actual data is shown in parenthesis. Color of arrows matches color of markers in the legend. Monitoring wells are located onshore and multilevel wells offshore. Refer to Figure 3.1 for well location. 83

99 Figure 5.6 Map of two shore perpendicular transects and one parallel transect. Gray, orange and blue lines represent Transects 1, 2, and 3, respectively. 84

100 a b c d Figure 5.7 Transect 1 showing (a) salinity, (b) nitrate concentration, (c) ammonium concentration, and (d) Eh from Pi53-13 to MLW8. Refer to Figure 5.6 for a map showing transects. March 2011 and June 2011 data were used to make contour plots. 85

101 a b c Figure 5.8 Transect 2 showing (a) nitrate concentration, (b) ammonium concentration and (c) Eh from Cluster 1 to MLW5. Salinities are not shown since all values are less than 4 along the transect. March 2011 and June 2011 data were used to make contour plots. Refer to Figure 5.6 for a map showing transects. 86

102 a b c d Figure 5.9 Transect 3 showing (a) salinity, (b) nitrate concentration, (c) ammonium concentration, and (d) Eh. This is a shore parallel transect from MLW5 to MLW1. Refer to Figure 5.6 for a map showing transect. 87

103 5.3 Discussion of Temporal Variability of Field Parameters One of the primary objectives of this study was to capture movement of the salinity transition zone due to transient forcing. Tidal cycle and monthly monitoring of groundwater at Indian River Bay from summer 2010 to fall 2011 provide time-series data of salinity, water quality, and nutrients and their response to tidal stage and amplitude (spring vs. neap) and seasonal forcing. Several field and numerical studies have observed and demonstrated movement of the salinity transition zone due to oceanic and terrestrial forcing (Michael et al., 2005; Kim et al., 2005, Robinson et al., 2007). Results of densitydependent groundwater models indicate that large tidal forcing (tidal amplitude > 1m) induce seaward movement of transition zone (Robinson et al., 2007). During a tidal cycle, the transition zone can shift landward at high tide and seaward at low tide due the disequilibrium in offshore heads with respect to onland heads. Similarly, the transition zone can respond to seasonal fluctuations in recharge (Michael et al., 2005). As the freshwater table rises in spring, the transition zone can be forced seaward. In the summer, due to increasing evapotranspiration, recharge is the lowest and the salinity transition zone can migrate landward. Indian River Bay is subject to oceanic and marine forcing that can potentially affect the position of the interface and nutrient dynamics. Tidal amplitude in the bay is usually <1 m (Figure 3.2, Chapter 3) and the water table elevation onshore can vary as much as 2 m from spring to summer (Figure 5.10). Despite the finding at other sites, our results suggest that the salinity transition zone at Holts Landing is not measurably influenced by tidal forcing and seasonal variability in recharge. One possible explanation is that the tidal amplitude at Indian River Bay is not large enough to cause 88

104 any movement of the transition zone at the depths sampled. Monthly sampling of MLWs indicates that the salinity transition zone does not respond to seasonal water table fluctuations with the exception of MLW8. The low topography near the shore may not allow for great seasonality. Additionally, the water table fluctuations during the monitored period (summer fall 2011) were lower than previous year (Figure 5.10). We would expect a movement of the transition zone under extreme hydrologic conditions; for example, years characterized by precipitation and/or evapotranspiration well above average. It is evident that at our study site, salinity and nutrients are quite stable over time. These findings suggest that the temporal variability is not as important as the spatial distribution of salinity and nutrients. Despite the lack of response of the deep transition zone, the shallow transition zone between the freshwater plume and bay water and the circulation cell in the intertidal zone may still respond to short timescale temporal forcing such as waves and tides (Robinson et al., 2007; Li et al., 2009). Future investigation should focus more on characterizing the salinity and nutrient distribution and how the geology controls the composition of SGD, rather than the temporal variability in response to transient forcing. 89

105 90 Figure 5.10 Long term record of water level data for Qi This well is located south of Holts Landing State Park on Holts Landing Road. Yellow arrows represent sample times. Seasonal amplitude was not large over the sample period.

106 5.4 Discussion of Modeling Variable-density modeling and groundwater sampling were useful tools for investigating the geologic and hydrologic conditions that could explain the presence of a freshwater plume offshore. The extent and configuration of the model geologic units was based on the interpretation of the paleovalley/interfluve system from seismic data, core logs, resistivity data, porewater sampling, and local hydrology. The primary geologic features of the model are a high-permeability channel underlying a lowpermeability layer. This sequence agrees with the local interpretation of the geology. At Holts Landing State Park there are two individual paleovalleys/channels that are separated by an interfluve. The two channels then merge to one offshore channel (see Figures 2.3 and 2.4, Chapter 2). The paleovalleys then merge with an ancestral Indian River Valley. The channels themselves are thickest along the channel axis (~4 m) and thinnest along the edges (~ 1.5 m). The typical infill sequence of the paleovalley is fluvial sands at the base overlain by a semi-impermeable basal peat, and then capped by fine-grained silts and sands at the top (Krantz et al., 2004; see Figure 2.2, Chapter 2). Based on hand cores and seismic data, we know the low-permeability sediments cover a large area offshore and extend some distance landward, these were replicated in the model. The underlying material within the channel was not sampled directly. We hypothesized that the channel material could be similar or coarser than the surrounding aquifer. The shape of the channel fill material onland was based primarily on the surface topography, which shows a valley characterized by lower elevations along the center of the modeled area, where we propose that the ancestral tributaries could have been located. 91

107 In the model, the hydraulic gradient onshore was chosen to produce a maximum gradient driving subsurface flow through the study site. Because the water table is relatively shallow, the prescribed head onshore was set to the elevation of the land surface. This will create a higher hydraulic gradient than what may actually exist at the site, but represents an upper bound on the hydraulic gradient during wet conditions. However, the recharge calculated from the simulation with the high-k channel and the low-k cap is slightly below the range of recharge values used for the watershed-scale model (C. Russoniello, personal communication).future hydrologic models can be better calibrated to conditions at the field site. Modeling results indicate that permeability of the paleochannel cap and fill material is a primary control on the salinity distributions. We did not formally calibrate the model to field data, but we tried to match the salinities that we observed in the field by adjusting parameter values (primarily hydraulic conductivity of the paleochannel cap and channel fill material). The first model was run without a high-permeability channel and modeled salinities do not match observed (Figure 5.11). The model with the high-permeability channel matches more closely. Numerical experiments indicated that the channel material needed to have a hydraulic conductivity at least 100 times greater than the adjacent aquifer material to reproduce the observed salinity pattern. In addition, model calibration indicated that the hydraulic conductivity of the cap material needed to be seven orders of magnitude smaller than the adjacent aquifer material which it is much lower than what we had expected to reproduce the salinity pattern. Most of the simulated salinity profiles match well with the observed data but there are few differences that should be discussed (Figure 5.11). The simulated salinities of 92

108 MLW1are slightly lower (20 to 25 ) than measured salinities (~28 ), which result from the simulated plume being too wide. Simulated salinities at MLW3, 4, and 5 match well to depths of -12 m. Salinity transition zones at MLW2, 6, 7, and 8 were also simulated, but the highest salinity occurred deeper (below 16 m) than in observed profiles. Greater vertical discretization may provide better resolution for comparison of measurements below 12 m depth. Even though the model with the high-permeability channel was able to reproduce generally the observed salinities, the match could be improved by adjusting parameters and boundary conditions. We could represent the boundary condition better by applying recharge to the top layer and therefore, better match the shape and position of the salinity transition zone and the freshwater plume, but there is much uncertainty in the actual recharge rate. Changing the anisotropy within the different layers of the model could also affect the extent of the freshwater offshore. Dispersion could affect the width of the transition zone and provide better matches to MLWs showing salinity gradients, but model sensitivity tests indicated this was a minor factor. In this study, we used a site-specific model as a first attempt to propose and test a hydrogeologic framework that could explain the observed salinity distribution offshore. The agreement between the observed and simulated salinities suggests that a high-permeability channel with a low-permeability cap is a plausible and important feature in controlling groundwater flow and discharge. Although there are some data available to further calibrate the model, we focused on developing a simple model that reflected general hydrologic conditions of the area that was able to reproduce observed salinities. Future work could focus on incorporating field measurements such as 93

109 pressure, salinity, density, and fluxes to further calibrate the model and to estimate parameters. Flow paths should be analyzed to determine whether they agree with our conceptual model (see Figures 1.2 and 1.3, Chapter 1). In addition, estimated fluxes across the bayfloor can be compared to measured fluxes from seepage meters. 94

110 Figure 5.11 Comparison of salinity profiles of MLWs. (a) Observed salinity for June (b) Simulated salinity from grid cell containing observation wells. 95

111 Chapter 6 SUMMARY AND CONCLUSIONS A conceptual model of groundwater flow at Holts Landing is proposed based on existing seismic and resistivity data and later refined as a result of numerical simulation and measurements of groundwater salinity, field parameters and nutrients. The local stratigraphy is dominated by a paleovalley/interfluve system which is a primary control on groundwater flow and submarine groundwater discharge (SGD). The paleovalleys are infilled with coarse sediments at the bottom and lowpermeability sediments at the top. The hydraulic gradient drives fresh groundwater from the surficial aquifer to Indian River Bay where it discharges. In areas with paleovalleys, fresh groundwater does not discharge near the shore, but instead is forced to flow underneath the bay, eventually mixing with saline groundwater and discharging as brackish and saline SGD. Away from the paleovalleys, fresh SGD occurs near shore. The focus of this study was to characterize the temporal and spatial distribution of salinity, ph, oxidation-reduction potential (Eh), dissolved oxygen (DO) and nutrients within the surficial aquifer and underneath the bay, and to relate these distributions to local geologic heterogeneity. Groundwater sampling in conjunction with geophysical surveys provides a detailed distribution of fresh and saline groundwater onshore at Holts Landing State Park and offshore beneath Indian River Bay, Delaware. Resistivity data showed a freshened groundwater plume extending ~400 m offshore and at least 10 m thick (J. Bratton, personal communication). Groundwater sampled from multilevel wells (MLW) offshore confirmed the presence of fresher groundwater overlying saline 96

112 groundwater and captured salinity transition zones along the edge of the freshwater plume. From this study, we can conclude that porewater sampling provided a higher resolution of the variability in salinity with depth and our findings are consistent with the interpretation of the flow system in which the low-permeability cap impedes fresh discharge at the shore, creating an offshore freshwater plume. Samples show little variability in salinity, field parameters and nutrients at tidal, spring and neap, and seasonal timescales. Small tidal amplitudes (< 1 m) and spring-neap variation (< 1 m difference in amplitude) at Indian River Bay did not induce movement of the transition zone at the depths measured. Despite a seasonal variability in the water table: high water table in spring and low in the summer, there was no significant response of the salinity transition zone. Our findings show that the temporal variability at our site is not as important as the spatial variability. The distribution of inorganic N-species at our study site was mainly controlled by the source of the groundwater. Ammonium was observed primarily in saline groundwater and in shallow fresh groundwater in contact with marsh sediments. Higher salinity groundwater is highly reducing and has lower dissolved oxygen compared with fresh groundwater, which provides suitable conditions for ammonium to accumulate. Saline groundwater is recharged from the bay, which agrees with source of ammonium being the degradation of shallow organic-rich sediments. We would expect ammonium to be the dominant form of nitrogen in saline groundwater flux from offshore sediments to the bay because ammonium concentration in saline groundwater at MLW1 is ~ 120 μm. The highest concentrations of nitrate occurred in onshore fresh groundwater at depths > 12 m, which indicates that fresh groundwater carries nitrate from recharge 97

113 areas within the watershed. Given the agricultural practices in the area, we would expect similar nitrate concentrations within the surficial aquifer throughout the area. However, nitrate was rarely present offshore. The absence of nitrate offshore suggests that nitrate may be denitrified along freshwater flow paths and we would expect less nitrate flux to the bay in areas near the paleochannels compared to areas of shoreline with direct discharge nearshore. On the eastern part of our study site, nitrate in fresh groundwater was high in freshwater wells located ~ 40 m from shore and seepage meter measurements indicated high rates of fresh SGD close to shore. This location coincides with interfluves where low-permeability sediments are thin or nearly absent, which allows the direct discharge of fresh groundwater and inhibits the contact with organic-rich sediments. Although we did not measure nutrient concentration of SGD, we would expect nitrate in SGD to be high or similar in concentration to nearby on land wells. The modeled salinity distribution is consistent with our understanding of the geologic controls of the flow system. Two models with different stratigraphy were developed: 1) without the high-permeability channel and 2) with the highpermeability channel; both had a low-permeability cap. In the absence of a highpermeability channel, the freshwater plume did not develop offshore because the fresh groundwater discharges close to shore around the cap. The results of the model with the high-permeability channel generally and quantitatively matched the observed salinities at multilevel wells. Fresh groundwater did not discharge near shore and instead was forced to flow offshore through the high-permeability channel and underneath the bay. The shape of the plume also qualitatively matched the geometry of the freshwater plume interpreted from resistivity data. 98

114 Future work at this site should focus on characterizing biogeochemical reactions along flow paths. Tracking nitrate plumes from the surficial aquifer to discharge zone will provide additional information about the non-conservative behavior of nitrate and better estimates of groundwater derived nitrate fluxes to the bay. Future sampling at this site could focus on improving the spatial coverage rather than on the temporal changes. Shallower transition zones between the fresh groundwater and the overlying bay water could also be investigated further since these zones have oxygen and redox gradients and can be highly reactive. In addition, a more shallow mixing zone may respond to oceanic forcing such as tidal stage and magnitude, in contrast to a more stationary deep mixing zone. Additional modeling should be done to estimate and compare fluxes with direct measurements and provide better estimates of nutrient fluxes to the bay. In addition, transience should be investigated to determine the temporal component of the system and how it may affect SGD fluxes to the bay. This work has implications for estimating nitrate loads to bays. In areas with abundant paleochannels and offshore fresh discharge, nitrate loads contributed directly by groundwater may be lower than expected. This means that management strategies designed to decrease nitrate loading to Indian River Bay by controlling nitrate application in recharge areas may not be as effective at this site. Coastal managers have a great challenge ahead to provide estimates of nutrient loading to the bays because of the complex flow system associated with geologic heterogeneities. In order to provide an estimate of nitrate fluxes to the bay, the amount of nitrate removed along fresh flow paths and the area affected by paleovalleys should be quantified. This will require mapping of fresh groundwater plumes offshore as well as groundwater 99

115 sampling and nutrient and chemical analyses. In addition, recycled ammonium may be a large contributor of bioavailable nitrogen to surface water, a source that it is difficult to manage. Coastal studies should focus on identifying zones where direct discharge of groundwater occurs. The conservation, restoration and creation of buffer zones around the bay are an alternative management strategy to reduce nutrient loading and ultimately eutrophication in adjacent coastal waters. Human activities such as dredging that breach shallow confining units could actually increase nitrate loads by eliminating offshore fresh flowpaths along which denitrification may occur. 100

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121 Appendix A MULTILEVEL WELL SAMPLING The cover for multi-level wells (MLW) was designed to protect the tubes from waves, currents, and moving objects, and for access in winter without diving. Figure A.1 shows how MLWs were sampled by boat and show the protective cover that was placed on top of the MLWs (Figure A.2). A rake was used to raise the black protective case from the boat and the flexible tubing was temporarily attached to the side of the boat during sampling. Figure A.2 shows the actual cover with the galvanized chains lead weights to impede the movement of the manifold due to currents. Figure A.3 shows how equipment was set up on the boat once the sampling ports were accessed. 106

122 Figure A.1 Illustration of multilevel well (MLW) sampling and protective casing. 107

123 Figure A.2 Picture of protective case for MLW tubing. 108

124 Figure A.3 Set up of equipment used for sampling of MLWs from the boat. Sample bottles used to collect water for nutrient analysis. 109