The Pennsylvania State University

The Graduate School

College of Engineering

HYDROLOGIC CONTROLS OF NUTRIENT FLUXES IN GLACIAL MELTWATER

STREAMS AT INTER-ANNUAL, SEASONAL, AND DAILY TIMESCALES

IN THE MCMURDO DRY VALLEYS, ANTARCTICA

A Thesis in

Civil Engineering

by

Mitchell R. Weaver

Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Science

May 2011

The thesis of Mitchell R. Weaver was reviewed and approved* by the following:

Michael N. Gooseff Assistant Professor of Civil Engineering Thesis Advisor

Christopher J. Duffy Professor of Civil Engineering

Peggy A. Johnson Professor of Civil Engineering Head of the Department of Civil Engineering

*Signatures are on file in the Graduate School

iii ABSTRACT

In the McMurdo Dry Valleys of Antarctica, glaciers are hydrologically linked to closed- basin lakes at the valley floor by glacial meltwater streams. Streams flow through porous, well- defined channels with extensive chemically active hyporheic zones. Temporally varying dynamics of meltwater generation and sub-stream thaw depth are thought to control the potential for the hyporheic zone and benthic communities to influence transport of nutrients and dissolved ions downstream. Using the McMurdo LTER database, patterns in stream discharge, electrical conductivity (both with 15-minute sampling intervals), and solute chemistry (weekly sampling intervals) were examined on eight MDV streams from 1990-2008. Discharge and electrical conductivity values were highly variable among streams. Discharge values were highly dependent upon glacial source area, but meteorological and topographical complexities create large variability at all time scales. The longer streams were found to have much higher electrical conductivity values than the shorter streams, suggesting that there are more opportunities for hyporheic weathering reactions along longer stream reaches. Weekly sampled water solutes from each stream‟s entire record were plotted against the discharge recorded at the time when the sample was taken. Silicate concentrations displayed a decreasing logarithmic relationship, while nutrient concentrations had no apparent relationship. This suggests that with the exception to bioreactive solutes, the majority of hyporheic interactions could possibly be characterized by electrical conductivity and discharge. To attain information on in-stream nutrient dynamics and nutrient fluxes, glacial source water at the upper reach of Green Creek and stream outlet water at the lower reach of Green Creek were sampled hourly for two separate diel periods during the 2008-09 austral summer. Both dates were in late January under two distinct flow conditions (~0.5 L/s and ~10 L/s). Under low flow conditions, nutrient cycling was found to be uptake dominated. High flow conditions showed both uptake and regeneration with much higher nutrient loads, but as in the low flow conditions, no apparent temporal trends were found. Nutrient concentrations could not be predicted using the two parameters of discharge and electrical conductivity with in-stream nutrient dynamics likely too complicated at the sub-daily scale.

iv

TABLE OF CONTENTS

LIST OF FIGURES ...... v

LIST OF TABLES ...... vi

ACKNOWLEDGEMENTS ...... vii

Chapter 1 Introduction to Study ...... 1

1.1 McMurdo Dry Valley Background ...... 1 1.2 Hydrologic Cycle: a McMurdo Dry Valley Perspective ...... 5 1.2.1 Glaciers and Snowfields ...... 6 1.2.2 Streams ...... 7 1.2.3 Lakes ...... 7 1.3 Chemical Origin and Transport ...... 8 1.3.1 Chemical Weathering ...... 8 1.3.2 Nutrient Cycling ...... 10 1.4 Discharge and Solute Concentration Relationships ...... 10 1.5 Thesis Approach ...... 11

Chapter 2 Inter-annual Timescale ...... 12

2.1 Site Selection ...... 13 2.2 Background ...... 17 2.3 Methods ...... 17 2.3.1 Field Data Collection ...... 17 2.3.2 Seasonal Summaries ...... 18 2.3.3 Daily Probability of Flow and Mean Daily Statistics ...... 18 2.3.4 Flow/EC Duration Curves ...... 19 2.3.5 Chemistry Statistics ...... 20 2.4 Results ...... 21 2.4.1 Hydrology...... 21 2.4.1.1 Seasonal Summaries ...... 21 2.4.1.2 Probability of Flow ...... 24 2.4.1.3 Flow Duration Curves ...... 25 2.4.2 Electrical Conductivity ...... 31 2.4.3 Chemistty ...... 31 2.5 Discussion ...... 34

Chapter 3 Seasonal Timescale ...... 36

3.1 Methods ...... 37 3.1.1 Daily Statistics...... 37 3.1.2 Discharge and Concentration Relationships with Time ...... 37 3.1.3 Chemistry ...... 39 3.2 Results ...... 39 3.3 Discussion ...... 46

v Chapter 4 Daily Timescale ...... 47

4.1 Methods ...... 49 4.1.1 Experiment ...... 49 4.1.2 Quantifying Hyporheic Influence ...... 50 4.1.3 Nutrients ...... 50 4.2 Results ...... 54 4.2.1 Streamflow and Conductivity ...... 54 4.2.2 Hyporheic Influence ...... 54 4.2.3 Hysteresis ...... 55 4.2.4 Nutrient Fluxes ...... 55 4.2.5 Discharge and Nutrient Relationships ...... 55 4.3 Discussion ...... 62

Chapter 5 Synthesis and Implications of Study ...... 64

References ...... 67

vi

LIST OF FIGURES

Figure 1-1: Maps of the Antarctic continent and the McMurdo region...... 4

Figure 1-2: Conceptual Model of the MDV hydrologic system...... 5

Figure 2-1: Map of stream gauge locations in the MDVs...... 13

Figure 2-2: Map of the Lake Fryxell basin...... 16

Figure 2-3: Long stream seasonal summaries ...... 22

Figure 2-4: Short stream seasonal summaries...... 23

Figure 2-5: Long stream „S‟ curves ...... 26

Figure 2-6: Short stream „S‟ curves...... 27

Figure 2-7: Probability of flow plots...... 28

Figure 2-8: Flow duration curves...... 29

Figure 2-9: Contributing glacial area vs. discharge...... 30

Figure 2-10: Electrical Conductivity Duration Curves...... 30

Figure 3-1: Four dEC/dQ relationships...... 38

Figure 3-2: Crescent Stream daily statistic plots...... 40

Figure 3-3: Aiken Creek daily statistics plots...... 41

Figure 3-4: Canada Stream daily statistic plots...... 42

Figure 3-5: Green Creek daily statistic plots...... 43

Figure 3-6: Green Creek silica concentration vs. discharge...... 44

Figure 3-7: Green Creek nitrate concentration vs. discharge...... 44

Figure 3-8: Green Creek phosphate concentration vs. discharge ...... 45

Figure 3-9: Green Creek ammonium concentration vs. discharge...... 45

Figure 4-1: Example of typical MDV stream‟s diel hydrograph ...... 48

vii Figure 4-2: 2008-09 flow season for Green Creek...... 52

Figure 4-3: Map of Green Creek sampling locations...... 53

Figure 4-4: Discharge, EC, and hyporheic ionic influence...... 57

Figure 4-5: Low flow sampling event hysteresis loops...... 58

Figure 4-6: High flow sampling event hysteresis loops...... 59

Figure 4-7: Ionic fluxes across the stream reach during two different sampling events...... 60

Figure 4-8: Nitrate concentration vs. discharge with early season samples removed...... 61

Figure 4-9: Nitrate concentration vs. discharge with early season removed (08-09 added). .. 61

.

viii

LIST OF TABLES

Table 2-1: Stream characteristics...... 12

Table 2-2: Summary of chemistry statistics...... 33

ix

ACKNOWLEDGEMENTS

This research was funded by the National Science Foundation under grant number ANT

08-32755. The findings, opinions, and conclusions herein do not necessarily represent those of the NSF. Largely in thanks to the NSF and the MCM-LTER, my research objectives were made possible. Never could I have imagined that an organization would actually support me in my adventures and research in one of the most unique places on earth, the McMurdo Dry Valleys of

Antarctica. I would like to thank the McMurdo personnel for helo-support, communications, and general guidance in what was a very strange and new environment to me.

My greatest thanks go out to my advisor, Dr. Michael Gooseff, who not only gave me this unbelievable opportunity, but guided me from start to finish. Mike has been incredibly patient, and has always provided positive encouragement. He somehow manages to be available for guidance even when he is half way around the world. Mike and Lisa, thank you so much for inviting us into your home for meetings and of course the wonderful dinners.

Thank you to the entire MCM-LTER group, especially Diane McKnight for her ever useful wisdom and advice at a moment‟s notice during the 2008-09 field season, and Barry

Lyons, Kathy and Sue Welch, and Deb Leslie for their help in analyzing hundreds of my water samples both in the Crary Lab and at Byrd Polar. Also, thank you Anna Bramucci, for enduring the Antarctic sampling marathons that were the 2008-09 field season. I can‟t even imagine what kind of a mess that would‟ve been without you.

My office mate and friend, Adam Ward, thank you for your willingness to listen to my research problems and offering sound advice in return. Thank you to the entire Water Resource

x Engineering Department at Penn State, my fellow grad students, my instructors, and the ever helpful staff. Special thanks to Dr. Chris Duffy who taught so many of the courses that I took as a grad student, and was so enthusiastic and offered a fresh perspective in approaching Dry Valley hydrologic modeling.

Lastly, thank you to my family and friends for supporting me with everlasting love and encouragement. Like any other accomplishment in my life, I could not have done it without you.

Mitchell R. Weaver

1

Chapter 1

Introduction to Study

1.1 McMurdo Dry Valley Background

Nearly the entire continent of Antarctica is covered by ice. Less than 2% of the continent is ice-free [McKnight et al., 2004], and these areas are mostly present in and around the coastal regions of the continent. The largest of these ice free areas is the McMurdo Dry Valleys (MDVs) of southern Victoria Land (76°30‟S to 78°30‟S, 160°E to 164°E), 2200 miles due south of New

Zealand. The MDVs stretch from the edge of the polar plateau eastward to the Ross Sea encompassing an area of approximately 4800 km2 (Figure 1-1) [Wharton et al., 1993]. The

MDVs are a series of parallel valleys separated by ridges that run perpendicular to the coast. The three largest valleys are Victoria Valley, Wright Valley, and Taylor Valley from north to south.

Victoria Valley and Wright Valley are separated by the Olympus Range, while Wright Valley and

Taylor Valley are separated by the Asgard Range. Both ridges reach elevations over 2000 m above sea level (ASL). Valley floors range in elevation from just above sea level to about 800 m

ASL. Further east across the McMurdo Sound is Ross Island, the location of McMurdo Station,

Antarctica‟s largest research base, maintained by the United States Antarctic Program. The Dry

Valleys are the focus of the McMurdo Long Term Ecological Research (MCM-LTER) program, an interdisciplinary study of the natural ecosystem in the MDVs region.

The MDV ecosystem is vastly different than most ecosystems of the world. Both aquatic and terrestrial ecosystems survive in one of the planets harshest environments. At a latitude of

77°S, the MDVs experience continuous darkness during the austral winter where strong winds

2 and temperatures as low as -60°C preside. From October to February during the austral summer, there is continuous sunlight, generating temperatures up to 5°C [McKnight et al., 2004]. The

MDVs are considered a polar desert, receiving less than 10 cm of precipitation per year. Due to the extremely arid and frigid conditions, nearly all of the snowfall sublimates within days of falling, thus prohibiting any runoff generation. Liquid water occurs in very few locations in the

MDVs ecosystem.

Perennially ice covered endorheic lakes exist on the valley floors of the MDVs. Alpine glaciers situated upon the MDV ridges melt during the austral summer and form ephemeral streams that flow across the landscape and into the lakes. Due to the lack of precipitation and the general aridity of the MDV climate, glacial melt is the only consistent source of water in the

MDVs. Snowfields and snow patches make no significant contribution to lake inflows, with nearly all of the available water sublimating before it reaches the soils. Deep groundwater movement is essentially non-existent, with the presence of a deep immobile frozen groundwater table [Chinn, 1993].

MDV biological communities occur in various locations, but are most prevalent in areas where liquid water is available. Stream channels, lakes, and their surrounding wetted margins, are hotspots for biological activity during the austral summer. Streams and wetted soils support algae, mosses, micro soil invertebrates, and bacteria, while the lakes sustain various phytoplankton populations as well as benthic algal mats. Although life is most abundant in the streams and lakes, biology is not limited to these locations.

Approximately 95% of MDV soils below 1000 m ASL are considered arid [Berkins et al.,

2001] with an average moisture content of 1% [Campbell et al., 1997], yet soil biological communities are found throughout the landscape, typically in the upper 5-10 mm of soil. Some

MDV species, particularly algae, have the ability to go years without water in a desiccated state

3 only to revive once re-wetted, a process known as anhydrobiosis [Treonis et al., 2000, 2005;

McKnight et al., 2007; Vincent and Howard-Williams 1986; Hawes et al., 1992].

In addition to the available water content, soil chemistry is an important control on the terrestrial ecosystem of the MDVs. MDV soils consist of unconsolidated glacial till and are devoid of vascular plants. Due to this lack of vegetation, MDV soils can be described as ahumic, containing less than 1% organic carbon (0.01-0.03% organic matter by weight)[Campbell and

Claridge, 1987]. MDV soils typically have high salinity, a product of marine aerosol deposition as well as large evaporation rates, which cause evapoconcentration of dissolved salts Evaporation occurs on the surface, drying out the underlying soils and creating a large matric potential. This matric potential causes melted ground ice to rise to the surface where it then evaporates. This induces the upward migration of any dissolved salts, which creates a salinity profile that is greatest at the surface [Claridge et al., 1999]. Often in MDV soils salt crusts are visibly present at the surface.

The MDV ecosystem is defined by low precipitation rates, high evaporation rates, and extremely low temperatures, creating a general lack of liquid water. Salt concentrations are high within soils, and organic carbon is almost non-existent. It is only because of high inputs of solar energy and the glacial melt it induces during the austral summer that these biological communities are able to survive. Not only do the streams supply liquid water to down-gradient stream and soil habitats, but they also transport dissolved solutes that are vital to metabolic processes for terrestrial biota on the valley floors as well as aquatic biota within the lakes.

4

Figure 1-1: Maps of the Antarctic continent and McMurdo region. The McMurdo Dry Valleys are located within the black box, which is an enlarged map of the McMurdo region. The scale and north arrow pertain to the enlarged map only.

5 1.2 Hydrologic Cycle: a McMurdo Dry Valley Perspective

The MDV hydrologic cycle is somewhat simplified compared to most temperate environments. In addition to groundwater systems being generally absent, the absence of a vegetation canopy means that interception and transpiration are nonexistent in the MDVs. Most importantly, however, the MDVs are closed systems with no outflow to the ocean due to the presence of a coastal ridge. MDV hydrology can be divided into three major active and interconnected parts: glaciers and snowfields, streams, and lakes. Water cycles from the atmosphere to glaciers and snowfields when precipitation accumulates at high elevations, then melts to form streams that travel down the valleys and into the lakes. Water returns to the atmosphere through all three parts of the cycle by means of evaporation and sublimation.

Figure 1-2: Conceptual model of the MDV hydrologic process.

6 1.2.1 Glaciers and Snowfields

Over long periods of time, glaciers develop in locations where solid precipitation accumulation exceeds ablation losses (melting, evaporation, and sublimation). This phenomena, known as glaciation, is complex within the MDVs, but it is largely a factor of both climate and topography. Most glaciers exhibit a gradient of mass-balance with elevation, where accumulation

(mass gain) occurs above the equilibrium elevation and ablation (mass loss) occurs below it

[Fountain et al., 1998]. Snowfields typically develop as a result of the collection of wind-blown snow in the lee of topographic features [Gooseff et al., 2003]. Glaciers and snowfields may undergo sublimation year-round, but only during austral summer months when solar radiation reaches its highest levels do they begin to melt. The rate at which these sources melt depends on multiple factors: surface albedo, solar angle, solar intensity, and topographic shading. Wind- blown sediment may often accumulate on the surface of glaciers and snowfields. These sediments decrease the surface albedo, increasing the amount of solar radiation that is absorbed.

The angle of incidence between the sun and the land surface determines the directness of solar radiation. A more perpendicular angle will receive more direct radiation. This is why glacier cliffs melt more intensely throughout the summer than other glacier surfaces [Fountain et al.,

1998]. Incoming solar radiation is reflected by the atmosphere, as well as clouds and aerosols, and its intensity can be diminished before it reaches the surface. Lastly, the sun‟s position in the sky compounded with topographic features will also affect the directness of solar radiation.

Glaciers on the valley floor will receive solar radiation throughout the entire day, while glaciers situated on the slopes of the ridges will receive radiation for only a portion of the day.

7 1.2.2 Streams

Soon after solar radiation induces glacial melt, meltwater flows off of the glaciers and onto valley sediments. If enough melt is generated, open-channel streamflow will begin to occur within the well-established streambeds. A large expanse of the dry, porous, and unconsolidated alluvial sediments adjacent to the stream channels must be filled to continue open-channel flow down to the lakes. This sediment is known as the hyporheic zone. The hyporheic zone includes sediments adjacent to and underneath the stream channel, and is confined by a lower layer of permafrost that progressively deepens through the austral summer from 3 to 60 cm [Conovitz et al., 2006; McKnight et al., 2007]. There are no lateral inflows to MDV streams [McKnight et al.,

2007]. Evaporation occurs along the entire reach of the stream, including from the wetted soils surrounding the stream. Therefore, the discharge (volumetric flow, Q) is greatest at the source glacier, and the least at its outlet into the lake.

1.2.3 Lakes

MDV lakes have no outflows and are considered closed basin lakes. Lake surfaces are covered by 3 to 5 m of ice year round. These permanent ice covers develop as a result of winter freeze exceeding summer ablation. During summer months, small moats appear around the perimeter of the lakes [Chinn, 1993]. Solar energy is conducted through the surrounding soils, melting up to a few meters of ice, leaving a small fraction of the lake water exposed.

The MDV lake mass-balance is defined by inflows from glacial meltwater streams and losses from sublimation and evaporation. Ablation of the lake ice- cover occurs year-round and is fairly constant, while stream inflows are highly variable inter-annually, seasonally, and daily

8 [Chinn, 1993; Conovitz et al., 1998]. Lake levels will rise if stream inflow exceeds ablation, and inversely fall if ablation is greater than inflow.

1.3 Chemical Origin and Transport

MDV streams not only play a hydrologic role in supplying the lakes, but a chemical one as well. Chemical transport from the glaciers and sediments to the lakes is facilitated by MDV streams. Essential ions and nutrients that sustain lake biological communities are delivered to the lakes by the streams. Therefore, the substrate that MDV streams traverse determines the available ions and nutrients that are supplied to the lakes.

The MDV landscape has a geology composed of a wide variety of minerals due to the numerous glacial advances of both local alpine glaciers and the West Antarctic Ice Sheet [Pewe,

1960]. As the glaciers advance they scour out and tear up the geology below through processes known as glacial abrasion and plucking. Glacier till can range from large boulders to clay particles. This glacial history is evident in the landscape of the MDVs, as sands and clays appear to be randomly interbedded with cobbles and boulders. MDV glacial till is comprised of granite, dolerite, marble, gneiss, and sandstone [Pewe, 1960]. Previous glacial lakes have also deposited lacustrine carbonate sediments consisting of algal casts [Hendy et al., 1979]. Nitrate and sulfate salts are present in the valley soils, and have been proven to have atmospheric sources [Bao et al.,

2000; Sheppard et al., 2002; Witherow et al., 2006].

1.3.1 Chemical Weathering

Liquid water facilitates chemical weathering, and therefore is localized in the MDVs.

Since liquid water only occurs in streambeds and their adjacent hyporheic zones, chemical

9 weathering generally occurs in these locations [Lyons et al., 1997; Nezat et al., 2001]. The extent of chemical weathering in the MDVs is confined to silicate hydrolysis and salt dissolution [Nezat et al., 2001]. Nezat et al. [2001] and Lyons et al. [1997] examined the chemical denudation rates of Taylor Valley watersheds determined from H4SiO4 and HCO3 stream solute fluxes. H4SiO4 and HCO3, reactive silicate and bicarbonate, respectively, are both indicators of silicate hydrolysis. Silicate hydrolysis is the reaction between water, atmospheric carbon dioxide, and silicate minerals produce mineral cations, reactive silicate, and bicarbonate [Nezat et al., 2001].

Lyons et al. [1997] found that chemical weathering rates in the MDVs were equal to or greater than those of temperate watersheds in Alabama. It was previously believed that chemical denudation rates were directly correlated to temperature [Drever and Zobrist, 1992; Velbel, 1993;

Brady and Carrol, 1994] and precipitation [White and Blum, 1995]. With the finding of Lyons et al. [1997], it is clear that this is not necessarily the case, with the MDVs being one of the coldest and driest places on earth. Nezat et al. [2001] had similar findings, suggesting that high stream discharge, high rates of physical weathering (e.g. frost action, salt weathering), and the interaction between streams and hyporheic zones contribute to the high chemical denudation rates in MDV streams.

According to Runkel et al. [1998] hyporheic exchange is considerable in MDV streams and occurs at a fairly rapid rate due to high stream gradients and extremely porous alluvium.

These findings supported the hypothesis that solute concentrations were greater in longer MDV streams. Gooseff et al. [2002] further tested the hypothesis that weathering reactions in the hyporheic zone control stream chemistry downstream. They found that the rapid exchange between hyporheic and stream waters enhanced weathering by introducing greater amounts of dilute stream water into the hyporheic zone, thus increasing dissolved solute concentrations.

10 1.3.2 Nutrient Cycling

Green et al. [1988] suggested that the source for NO3 in the MDVs is the leaching of wet atmospheric deposition, and that the source for PO4 is the weathering of apatite. Maurice et al.

[2002] identified denitrifying bacteria in the hyporheic zone suggesting that NO3 may be transformed within the streambed. Algal mats and mosses in MDV streams are also believed to control stream nutrient concentrations. Howard-Williams et al. [1989] concluded that nitrogen cycling in MDV streams were comparable to rates in temperate streams despite low temperatures, short periods of water availability, and low nitrogen fixation rates. McKnight et al. [2004] and

Gooseff et al. [2004] conducted studies to examine the extent of interaction between benthic algal mat microbial processes and hyporheic water that would influence nutrient concentrations in

MDV streams. By conducting stream-tracer experiments and injecting nutrients into an MDV stream, they found that nutrient uptake was occurring within algal communities and the hyporheic zone. The results showed that nutrient fluxes into MDV lakes are controlled by hyporheic exchange and nutrient uptake by algal mats.

1.4 Discharge and Solute Concentration Relationships

In temperate watersheds, when there is an episodic “storm” event of increased discharge, there is typically a chemical response associated with it. The same should hold true in event responses in MDV streams, both on a seasonal and daily timescales due to the patterns of glacial meltwater production at these timescales.

Solute concentration (C) and discharge (Q) relationships have been observed to often times have loop-like patterns with a different solute concentration at the beginning of an event than at the end of an event even though discharge values are the same. This looping pattern, or

11 hysteresis, occurs whenever there is a difference in the relative timing of solute-discharge responses [Walling and Webb, 1986]. Evans and Davies [1998] examined the relationship between separate components mixing and the resultant C/Q hysteresis using a simple 3- component model and a 2-component model. They found that the C/Q hysteresis can take on a range of characteristic forms dependent upon the timing of the different components, and the relative solute concentrations between the different components. Using only incoming component hydrographs, they predicted the relative solute concentrations based on the modeled form of the C/Q hysteresis. Chanat et al. [2001] further examined the 2- and 3-component models that Evans and Davies [1998] proposed could predict C/Q hysteresis. They found that with storm to storm variability (i.e. different end-member volumes, timing, and concentrations), the characteristic C/Q hysteresis forms took on several more shapes, even ones that did not resemble the commonly observed loop-like patterns.

1.5 Thesis Approach

In-stream dynamics are very important in determining the amount of vital nutrients and major ions that are delivered to MDV lakes. However, little is known about the specific dynamics of nutrient cycling in MDV streams, and what is known (i.e. McKnight et al.,2004 tracer experiment) is just a snapshot in time, that does not describe possible daily or seasonal controls to nutrient cycling.

Streamflow in the MDVs is extremely variable at inter-annual, seasonal, and daily timescales, yet we expect that discharge events induced by temporal differences in glacial melting have a predictable effect on in-stream chemistry. The purpose of this study is to document Q and

C patterns at all three timescales and attempt to model nutrient responses to temporally different melt water events.

12 Chapter 2

Fluxes on Inter-annual Time Scales

The MCM-LTER maintains systematic long term monitoring of glaciers, streams, lakes, biology, and climate in the MDV region. The USGS in cooperation with the MCM-LTER have maintained stream flow gauges on seventeen streams in both the Wright and Taylor Valleys in the

MDVs since 1990 (Figure 2-1). This stream flow record includes discharge, stream temperature, specific electrical conductivity (EC), and select stream chemistry. Two gauges are located in the

Wright Valley on the Onyx River, the longest flowing stream in Antarctica. A gauge is located at the stream‟s origin, the outlet of Lake Brownworth, and another gauge is located at its terminus just before Lake Vanda. The remainder of the gauged streams are located in the Taylor Valley which consists of three major endorheic basins from west to east: Bonney, Hoare, and Fryxell.

Commonwealth Stream is the only gauged stream that flows into New Harbor (Ross Sea). Nine of seventeen gauged streams in Taylor Valley are located in the Fryxell Lake basin, more than any other MDV lake. In this section, the entire stream flow record and available chemistry will be analyzed for eight Fryxell basin streams at an inter-annual timescale.

Table 2-1: Stream Characteristics.

Glacial Avg. Length Average Average Stream Area Duration (km) Start Date End Date (km2) (days) Aiken 4.29 6.07 December 15 January 27 42.8 Canada 1.15 3.73 November 27 February 13 79.0 Crescent 5.37 4.51 December 20 February 4 46.5 Delta 5.23 7.74 December 17 February 4 49.7 Green 0.73 1.44 December 3 January 31 58.6 Huey 2.18 1.14 December 17 January 24 38.1 Lost Seal 1.45 36.33 December 7 January 30 54.5 Von Guerard 5.20 3.18 December 17 January 28 42.0

13

Figure 2-1: Map of stream gauge locations in the MDVs.

2.1 Site Selection

The Lake Fryxell basin was selected as the focus of this study for its abundance of gauged streams within a single basin with relative regional proximity. These streams have subtle differences in the terrain they flow over, their source glaciers, and other geomorphological features. A total of ten streams flow into Lake Fryxell, but only eight were selected for this study. McKnight Stream and Harnish Creek were not included in this analysis because of inconsistency of flow and/or a lack of data availability. The eight streams included have been numbered clockwise around the Fryxell basin (Table 2-1 and Figure 2-2):

14 1. Canada Stream

Canada Stream drains the Canada Glacier‟s eastern face and empties into Lake

Fryxell on the north shore. It is an incised shallow gradient stream with meltwater

contributions all along the glacier face. A large portion of Canada Glacier receives

very little topographic shading due to its location on the valley floor.

2. Huey Creek

Huey Creek runs south to Lake Fryxell‟s northern shore from a large snowfield

located to the west of Falconer Ridge in the Asgard Range. It is the only Fryxell

basin stream with a snowfield as its source. Huey has a steep straight scree channel

once it leaves the snowfield, but eventually flattens as it flows to the lake. Huey

often does not flow during the austral summer, possibly due to its source being a

snowfield which depends on wind-blown sediment to decrease its albedo, thus

increasing its melt generation.

3. Lost Seal Stream

Lost Seal Stream drains the entire west face of the Commonwealth Glacier, and has a

very wide and flat channel. It empties into Lake Fryxell on its eastern end, opposite

that of Canada and Green. The Commonwealth Glacier extends onto the valley floor

and receives very little topographic shading. Lost Seal Stream has the largest

potential glacial area input, but because of the low elevation in the ablation zone at

which melt exceeds evaporation and sublimation, a large portion of this is not

accessed.

15 4. Aiken Creek

Aiken Creek has two sources, and two very different channels through which the

source meltwater flows. A short low gradient channel drains portions of the southern

face of the Commonwealth Glacier. A much longer steeper channel drains alpine

glaciers in the Kukri Hills to the south. These streams meet at Many Glaciers Pond

where they then flow into the eastern most end of Lake Fryxell.

5. Von Guerard Stream

Von Guerard Stream drains the Von Guerard Glacier in the Kukri Hills and flows

northward into Lake Fryxell‟s southern shore. It has a very steep gradient below the

glacier and flows through a large boulder field before reaching a broad alluvial

section where its slope drastically decreases. It continues to flow through a series of

ponds before it straightens and flows toward the lake. The Von Guerard Glacier, like

the Crescent Glacier, is a concave alpine glacier. Von Guerard Stream also has

considerable losses in streamflow to Harnish Creek through the Relict Channel.

6. Crescent Stream

Crescent Stream drains Crescent Glacier in the Kukri Hills and runs northward to

empty into the south shore of Lake Fryxell. The reach is very steep coming off the

glacier, but is shallow over the majority of its length. The Crescent Glacier is an

alpine glacier with a concave shape, and therefore experiences considerable

topographic shading. Some streamflow from Crescent Stream is naturally diverted

into Harnish Creek.

16 7. Delta Stream

Delta stream‟s main source is the Howard Glacier in the Kukri Hills. The stream

drains large snowfields to the west of the Howard Glacier, making it potentially the

longest stream in the Fryxell Basin, however these sources are rarely accessed. The

main channel has a uniform mild to shallow gradient from source to outflow.

8. Green Creek

Green Creek is the shortest of all the Fryxell Basin streams. It drains the southern

face of the Canada Glacier and flows eastward, emptying into Lake Fryxell‟s south

shore. Green Creek is a very low gradient stream that empties from a series of glacial

pools at the top of its reach.

Figure 2-2: Map of the Lake Fryxell basin.

17 2.2 Background

Conovitz et al. [1998] analyzed 5 Fryxell Basin streams (Canada, Lost Seal, Von

Guerard, Crescent, and Delta) at an inter-annual timescale. At the time of the study, stream flow had only been monitored for 5 flow seasons. Examining streamflow totals for the available record, they found that inter-annual streamflow was highly variable. Total discharge can vary by up to a few orders of magnitude between two different years on any given stream. Conovitz et al.

[1998] concluded that the total volume of annual streamflow must be considered when evaluating streamflow characteristics for any given year.

2.3 Methods

Austral summer streamflow records are available for the eight selected streams for every flow season since 1990, with the exception of the 1992-93 austral summer. Some records are incomplete and missing certain seasons of data due to either equipment malfunctions or an absence of streamflow. A number of analyses of these records were conducted in conjunction with annual streamflow total observations. The methods utilized to perform these analyses are reported in the following sub-sections. Streamflow records from the 1990-91 to 2006-07 austral summers were utilized.

2.3.1 Field Data Collection

Stream stage, electrical conductivity (EC), and temperature measurements are made by in-stream probes every 15 minutes and stored on Campbell CR-10X data loggers. Stage is converted to a discharge record through standard field measurements and rating curves. Gauges are located near the mouths of the streams before they discharge into receiving lakes. A control

18 structure (Parshall flume or sandbag weir) is located at the gauge where nitrogen pressure transducers measure stage through the control structure. Stream chemistry samples are taken when a field team visits the gauge to maintain the gauge and make flow measurements. This is not always on a regular interval. Stream water samples are filtered and returned to an analytical lab for processing and analysis of major ions, nutrients, and dissolved organic carbon (DOC).

This data, as well as daily streamflow statistics computed from the 15-minute data, are available on the McMurdo LTER website (http://www.mcmlter.org).

2.3.2 Seasonal Summaries

Each austral summer‟s melt intensity can be described by a total melt water volume that reaches the MDV lakes. For each stream a cumulative stream flow can be generated by integrating the observed hydrograph with respect to time. We completed this integration using a trapezoidal approximation for each fifteen-minute measurement at each gauge and summing over the flow season. The starting and ending dates for each year‟s flow season were determined from the first and last non-zero instantaneous flow value in the 15-minute data. Season durations were determined by difference of the start and end dates. The dates are reported relative to the beginning of a typical U.S. water year, and water years are referenced with respect to the year in the latter part of the flow season (i.e., October 1, 1998 is the first day of the 1999 water year).

2.3.3 Daily Probability of Flow and Mean Daily Statistics

In the MDVs, stream flow does not always reach stream gauges, and hence streams do not always produce inflow to the lakes. Furthermore, streamflow is inconsistent; even in the middle of a typical flow season stream flow can cease if temperatures drop substantially or snow

19 falls on the glaciers, reflecting solar input more efficiently than the glacier surface. We estimated the probability of streamflow for each day of a typical flow season by totaling the number of non- zero flow values for that day in each year of the record and dividing it by the total number of years of record. Equipment malfunctions were corrected for so that if our estimates reflect actual lack of flow only. For the days that have a non-zero flow probability, mean daily flow and mean daily EC values were calculated. These values however are heavily weighted by the number of non-zero flow days for a specific date. Dates with lower flow probabilities will have more heavily weighted values from a few measurements for those dates.

2.3.4 Flow/EC Duration Curves

With up to sixteen years of flow records, MDV streams can begin to be characterized more accurately from the discharge measurements that are made each year. One way to do this is with a flow duration curve (FDC), in which discharge values are plotted against the probability that they are exceeded. Our FDCs were created for discharge values from zero to the maximum instantaneous fifteen minute measurement, making sure that no bin size contributed greater than

10% of the total population. Zero flow values were not included unless they were bound within the season start and end dates. Hence, our FDCs do not include non-flow season values of no flow. We then characterized streams based on their exceedence probabilities at median flow, high flow, and low flow conditions.

Electrical conductivity duration curves (ECDCs) were created in the same way, but for only four of the Fryxell Basin streams. Delta, Huey, Lost Seal, and Von Guerard have insufficient EC records to generate these exceedence probabilities.

In order to interpret the relationship between streamflow and the potential glacial source area, 5% flow exceedence probabilities were compared to contributing glacial area from each

20 stream at maximum elevations from 300 to 700 meters. Glacial area was determined using a one meter high resolution DEM for most of the valley and a fifty meter DEM for the areas outside of the one meter coverage. Different elevations were selected because of the varying melt generating ablation elevation with each austral summer. Five percent exceedence was selected due to the limited data set (16 years), making sure to include a large amount of high flows from many different years, so that one flood year would not skew the results. The same two DEMs were used to determine the shortest flow lengths from source to lake for each stream.

2.3.5 Chemistry Statistics

To provide an overview of the biogeochemical character of these streams, we summarized water quality data from these streams over their record. Water samples are typically collected by the stream team every time a stream gauge site is visited and there is streamflow present at the gauge. Gauge sites are usually visited weekly from late October until late January.

We report mean and variance of analytes with consistent levels above detection. Our summary includes major cations (sodium, potassium, magnesium, and calcium) major anions (chloride and sulfate), nutrients (nitrogen as nitrate and ammonium, and soluble reactive phosphorus [SRP]), silica (as H2SiO4), alkalinity, total dissolved solids (TDS), and Dissolved Organic Carbon (DOC).

21 2.4 Results

2.4.1 Hydrology

2.4.1.1 Seasonal Summaries

The following paragraphs summarize Figure 2-3 and Figure 2-4. Noticeable among all streams that did not have equipment malfunctions during the 2002 season is that it is the highest total discharge for those streams. Notice that this year is not necessarily the longest flow season within the record for several streams. There is very little correlation between flow season duration and cumulative flow for the season (not shown). Other considerable flow seasons were

1991 and 1992. There was generally low flow from 1994 to 2001.

Looking specifically at each stream, Canada and Aiken have the highest total flows, both coming in 2002. Canada and Green appear to be the most consistent contributors to Lake Fryxell, with Canada having the longest average season duration, the earliest average flow start date, and the latest average season end date. For nearly every season, Canada is the first to begin to flow and the last to stop. Huey, Von Guerard, Crescent, and Delta all have many low flow seasons.

Huey has the shortest average season duration among all streams. There are no apparent temporal trends in season start and end dates, as well as in total discharge for any of the eight streams.

22

Figure 2-3: Long Stream Seasonal Summaries. Cumulative Flow and Season Duration are reported for A) Aiken Creek B) Von Guerrard Stream C) Crescent Stream D) Delta Stream.

Asterisks indicate years when measurements were not collected or equipment malfunctioned.

23

Figure 2-4: Short Stream Seasonal Summaries. Cumulative Flow and Season Duration are reported for A) Green Creek B) Huey Creek C) Lost Seal Stream D) Canada Stream. Asterisks indicate years when measurements were not collected or equipment malfunctioned.

24 The cumulative flow „S‟ curves reflect the general low flows at the beginning and end of the season, and high flows in the middle of the season (Figures 2-5 and 2-6). This typical behavior can be explained by the filling of the stream bed and adjacent soils early in the season.

The hyporheic zone must be filled before streamflow can make it to the gauge. In early season this can be observed by the sudden appearance of flow, and in the late season by the drawn out freeze/thaw drainage. Some of the seasonal „S‟ curves end very abruptly suggesting that long periods of low radiation can negate the typical draining pattern. These long periods of low radiation do not always cause the cessation of the flow season, as seen by the step pattern in a few of the seasonal „S‟ curves.

2.4.1.2 Probability of Flow

Analysis of the probability and trends of mean daily flow indicate when a stream is most likely to flow and what discharge values can be expected on those dates. Within the daily flow probability plots, Canada and Huey stand out. Canada has the most days with greater than 50% non-zero flow probability, and Huey has the least. Huey barely reaches above 50% for a few select days, whereas Canada has over two months of 60% probability or greater. Canada, Lost

Seal, and Green all have days where flow probability is 100%, meaning flow has occurred on those dates in every year of the record (Figure 2-7). Von Guerard, Aiken, Delta, and Crescent each display a longer period of low probabilities of flow in the early season and a later early season 50% flow probability, both suggesting the greater role of the hyporheic in longer streams.

Aiken, Canada, Delta, Green, and Lost Seal have average daily flow values that peak above 50

L/s. This may suggest the consistent contributing glacial area each has at lower altitudes where melt generation exceeds evaporation and sublimation. The Howard (Delta), Commonwealth

25 (Aiken and Lost Seal), and Canada (Canada and Green) Glaciers all extend down into the valley at elevations below 300 meters. These are also glaciers with distinct ice cliffs or vertical faces.

2.4.1.3 Flow Duration Curve

The flow duration curves were separated by stream length to read more easily. Among all flow duration curves, Green has the highest 10 L/s probability of exceedence and Huey has the lowest. Aiken, Lost Seal, and Canada also have high 10 L/s probabilities of exceedence. As the probability of exceedence decreases to 10%, Lost Seal has the highest magnitude of flow. At exceedence values less than 10%, Aiken has the largest magnitudes of flow. Aiken, Lost Seal, and Canada all group at an exceedence value of 0.1% grouping in the discharge range of 500-800

L/s, suggesting that they have the highest potential for higher discharges. Crescent, Green, and

Huey have the lowest potential for higher discharges at 0.1% exceedence – grouping in the discharge range of 150-250 L/s.

The 5% exceedence was plotted against glacial area below an elevation of 400 meters where melt can begin to occur on the glaciers without being evaporated as suggested by Fountain et al. [1998] (Figure 2-8). A linear correlation appears between the discharge and the glacial area

(Figure 2-9).

26

Figure 2-5: Long Stream „S‟ Curves. Seasonal „S‟ Curves reported for A) Aiken Creek B)

Crescent Stream C) Delta Stream D) Von Guerard Stream.

27

Figure 2-6: Short Stream „S‟ Curves. Seasonal „S‟ Curves reported for A) Canada Stream B)

Green Creek C) Huey Creek D) Lost Seal Stream.

28

Figure 2-7: Probability of Flow Plots. Probability of Flow (shaded grey), Average Daily Flow (black line), and Average Daily EC (dashed line) are reported above for A) Aiken B) Canada C) Crescent D) Delta E) Green F) Huey G) Lost Seal H) Von Guerard. EC and Q values are plotted against the left axis, while probability is plotted against the right axis.

29

Flow Duration Curves

Short Streams

1000

100

Discharge (L/s) Discharge

Canada Green Huey Lost Seal 10 0.001 0.01 0.1 1 Probability of Exceedence

Long Streams

1000

100

Discharge (L/s) Discharge

Aiken Delta Crescent Von Guerard 10 0.001 0.01 0.1 1 Probability of Exceedence

Figure 2-8: Flow Duration Curves.

30

Glacial Area vs. Discharge

5

)

2 4 Glacial Area vs. Discharge

5 3

)

2 4 2

3

1

glacial area below 400 meters (km area below glacial 2

0 0 50 100 150 200 250 1

glacial area below 400 meters (km area below glacial 5% exceedence flow (L/s)

0 Figure 2-9: Contributing0 Glacial Area50 vs. Discharge.100 150 200 250 Electrical Conductivity5% exceedence flow Duration (L/s) Curve

1000

Electrical Conductivity Duration Curve

1000

S/cm)

100

S/cm)

100

Aiken

Specific Conductivity ( Specific Conductivity Crescent Green Canada Aiken

Specific Conductivity ( Specific Conductivity 10 Crescent 0.01 Green 0.1 1 Canada 10 Probability of Exceedence 0.01 0.1 1 Probability of Exceedence

Figure 2-10: Electrical Conductivity Duration Curve.

31 2.4.2 Electrical Conductivity

EC is essentially a surrogate measure of the dissolved ions within a stream. It is a reasonable indicator of how dilute or concentrated stream water is. Here EC is being used to compare the four streams of substantial EC records amongst each other, as an indicator of comparative amounts of dissolved solutes.

An upper and a lower threshold can be drawn out from the electrical conductivity duration curve for each stream (Figure 2-10). Where the stream‟s EC exceedence probability is approaching 100%, the stream‟s EC is at its minimum value. This lower threshold can be observed as nearly the EC of the stream‟s glacial source and some minimal interaction with the hyporheic zone. Green and Canada, both draining the more inland Canada Glacier, have lower source ECs. Aiken has the highest, consistent with its proximity to the coast. The upper threshold of the ECDC can be observed as a stream‟s chemical weathering potential, through hydrolysis and salt dissolution. Crescent, the longest stream, has the highest EC with the other three streams following in order of length: Aiken, Canada, and Green.

In the daily probability of flow plots (Figure 2-7), within the 50% probability of flow bounds, the average daily EC values increase as the season continues for both Aiken and

Crescent, but for Canada and Green a slight decreasing trend is observed. Aiken and Crescent average daily EC values are also much more variable.

2.4.3 Chemistry

Among major ions, chloride and sodium concentrations are high in all streams in the

Fryxell Basin except for Canada and Green (Table 2-2). Salt concentrations decrease away from the coast [Lyons et al. 1998] with the reduction of aeolian deposits, and Canada and Green lie at

32 the most inland end of the Fryxell Basin. Silica concentrations appear to be very low in short streams and high in long streams. In longer streams there will be a longer contact, especially through hyporheic sediments, allowing for silicate hydrolysis to occur within the materials of the stream bed. Alkalinity is also high in long streams and low in short streams, which further supports greater chemical weathering in longer streams. Areas with high concentrations of calcium carbonate will also raise alkalinity, as well as Ca2+ concentrations. This could explain the higher alkalinity in Huey Creek, a shorter stream.

Nutrient concentrations are highly variable among most streams for all nutrients. The highest reported mean concentration for nitrate was Huey, while the lowest was Canada. For ammonium, Canada was the peak value and Delta was the lowest, but overall the concentrations were fairly uniform. Soluble reactive phosphorus was highest in Lost Seal and lowest in Delta and Canada.

33 Table 2-2: Summary of Chemistry Statistics. Means, variance, and populations are symbolized with and n respectively.

34 2.5 Discussion

The 16 year streamflow record for the Lake Fryxell Basin streams shows great variability intra-annually in both spatial and temporal aspects. Local climate changes appear to have very different effects on each stream within the basin, but generally, increases in radiation generate proportional increases in total streamflow for all streams. The length of a stream appears to affect its streamflow temporally at the beginning and end of the austral summer, creating some of the discrepancies in streamflow response to radiation. A stream‟s total hyporheic storage appears to inhibit its potential total streamflow magnitude, which is determined by its contributing glacial area. These longer streams with larger hyporheic zones are less probable to flow on any given day during an austral summer, and they tend to begin to flow much later in the season.

Esposito et al [2006] found that with increasing harshness, stream ecosystems‟ diversity decreased. Of the diatoms found in MDV streams, 24 of 40 species are only found in Antarctica.

As harshness increases, these species begin to dominate the diatom population. Harshness is characterized by more days without flow, lower annual maximum flow, and lower annual flow.

Of the streams studied, the longer streams would be expected to have much lower diatom diversity. The exception to this would be Aiken Creek, which has higher annual streamflow, higher maximum flows, and less days with zero flow, most likely because of its source from the

Commonwealth Glacier which flows only 1.8 km until it reaches Lake Fryxell. Huey Creek would likely have lower diatom diversity even though it is a short stream. It has more zero flow days than any other stream, has the smallest glacial source, the lowest probability of flow, and the smallest flood (exceedence) discharges.

Chemical weathering products also appear to be a function of stream length within the

MDVs, but stream location, in both proximity to the coast and soil composition, plays an

35 important role in stream chemistry. Nutrient concentrations are highly variable among MDV streams, and further investigation at the seasonal and daily timescales is needed.

36

Chapter 3

Fluxes at Seasonal Time Scales

The inter-annual analysis showed some intriguing patterns among all seasons regardless of the spatial identity of each stream. „S‟ shaped cumulative flow graphs showed that a flow season could be broken down into three periods. The first and third periods are similar in that they are characterized by having low flow, with a period between them of relatively higher flow.

The low flow periods may suggest that there is a substantial volume of hyporheic sediment that is both thawing and filling in the early season and draining in the latter portion of the season. An inspection of seasonal streamflow statistics may give further insight when compared alongside corresponding electrical conductivity (here EC is used as a surrogate for total ion concentration) data for the same season. Hyporheic exchange is expected to increase EC because of silicate weathering and mixing with solute-enriched water in the hyporheic zone.

Among the eight streams analyzed in the previous chapter, four were selected for seasonal analyses: Aiken Creek, Canada Stream, Crescent Stream, and Green Creek. These are the only stream records with 5 or more years of EC data. Within this set of streams two are short

(Canada, Green) and two are long (Aiken, Crescent). Recall that these streams showed different

ECDC signatures at the inter-annual time scale (Figure 2-10).

37

3.1 Methods

3.1.1 Daily Statistics

Mean daily flows and EC values are used for the seasonal analysis. For each stream and flow season, the MCM-LTER has posted mean daily statistics on its website (www.mcmlter.org).

For each day of flow, mean, standard deviation, maximum, and minimum statistics are reported for three different measurements: discharge, stream temperature, and specific electrical conductivity. The number of 15 minute measurements made per day is also reported (maximum is 96/day). This value is reported in case measurements are missed or if there is an incomplete day of flow (i.e. beginning or end of season).

Ion Flux was calculated for each day by multiplying the mean daily discharge and the mean daily conductivity. Values were then cumulatively added through the season.

3.1.2 Discharge and Concentration Relationships with Time

Rates of change were calculated for both discharge and EC over time. These rates were calculated over a 3-day period, with the mid-point or second day being the quantified value. The value of change over the first and third day is determined and divided by a total of three days.

The result is the rate of change for the second day. Utilizing this 3-day calculation, the first and last days do not have assigned values.

Rates of change for EC and discharge were then compared to determine dEC/dQ. This value is useful because it shows electrical conductivities response to a unit change in discharge.

38 The higher the magnitude of dEC/dQ, the more discharge influences conductivity, suggesting thresholds for hyporheic exchange rates or increased weathering.

For two variables there can be four possible behaviors or relationships among them. The four possible behaviors for dEC/dQ are characterized as Flushing, Dilution, Draining, and

Equilibrium. They are visually represented in Figure 3-1.

The flushing behavior is characterized by both EC and Q increasing over time, suggesting a flux of high concentration fluid from hyporheic storage. Dilution, EC falling with the increase of Q, suggests a larger amount of water is added to a fixed amount of solutes. This behavior indicates increasing dilute glacial contribution to flow with little hyporheic exchange. Draining,

EC rising as Q recedes, implies ion rich subsurface (hyporheic) water leaching downstream.

Equilibrium is described by falling discharge and conductivity. This assumes that well mixed surface water discontinues to flow when there is no solute source left to carry downstream.

Figure 3-1: Four dEC/dQ relationships.

39 3.1.3 Chemistry

Sample chemistry, including all major ions and nutrients above detection limits, was compared to discharge. Instantaneous discharges were determined by taking the 15-min measurement closest in time to when the chemistry sample was taken.

3.2 Results

Daily stream statistics were plotted for the four streams analyzed. High flow, low flow, and average flow seasons were plotted. For all streams, 2001-02 was chosen as the high flow season and 1996-97 was chosen as the low flow season. For Green Creek 2005-06 was chosen as the average flow season due to its equipment malfunction during 2004-05, which was the season chosen for the rest of the streams. Note that negative dEC/dQ behaviors are dominant for most seasons (Figure 3-2,3,4,5). Late season flow appears to be dominated by the draining behavior.

Dilution is evident during mid-season high flows.

Reported in Figure 3-6 is silica concentrations versus instantaneous discharge. Note the strong logarithmic relationship. This same relationship was found for all major ions, but was strongest for silica. Also reported are nutrient concentrations in Figures 3-7,8,9. Note the general spread and lack of correlation between discharge and all nutrient concentrations. However, common among all plots is a slight increase in nutrient concentration with increases in discharge.

40

Figure 3-2: Crescent Stream daily statistics plots for 2001-02 (high flow season), 1996-97 (low flow season), 2004-05 (average flow season). Flushing (black bars) and equilibrium (white bars) dEC/dQ values are positive, dilution (white bars) and draining (black bars) are negative.

41

Figure 3-3: Aiken Creek daily statistics plots for 2001-02 (top, high flow season), 1996-97 (middle, low flow season), and 2004-05 (bottom, average flow season). Flushing (black bars) and equilibrium (white bars) dEC/dQ values are positive, dilution (white bars) and draining (black bars) are negative.

42

Figure 3-4: Canada Stream daily statistics plots for 2001-02 (top, high flow season), 1996-97 (middle, low flow season), and 2004-05 (bottom, average flow season). Flushing (black bars) and equilibrium (white bars) dEC/dQ values are positive, dilution (white bars) and draining (black bars) are negative.

43

Figure 3-5: Green Creek daily statistics plots for 2001-02 (top, high flow season), 1996-97 (middle, low flow season), and 2004-05 (bottom, average flow season). Flushing (black bars) and equilibrium (white bars) dEC/dQ values are positive, dilution (white bars) and draining (black bars) are negative.

44

Figure 3-6: Green Creek silica concentration vs. instantaneous discharge for all grab samples collected since 1993.

Figure 3-7: Green Creek nitrate concentration (N of NO3) vs. instantaneous discharge for all grab samples collected since 1993.

45

Figure 3-8: Green Creek phosphate concentration vs. instantaneous discharge for all grab samples collected since 1993.

Figure 3-9: Green Creek ammonium concentration (N of NH4) vs. instantaneous discharge for all grab samples collected since 1993.

46 3.3 Discussion

At the time scale of a season, mean daily discharge is highly variable. Streams flow for short periods (typically 3-4 weeks) with high flows, and longer periods (typically 6-8 weeks) with low flows, and sometimes have multiple peaks in a season. As was seen with the inter-annual analysis, late season flow slowly recedes for nearly all streams and seasons. This late season recession coincides with a slow rise in electrical conductivity, suggesting that the hyporheic zone is draining after a period of relatively high flow in the middle of the season. Late season dEC/dQ behaviors also coincide, with a common draining behavior (Figures 3-3). An inverse relationship between Q and EC is common, with draining and dilution behaviors dominant.

Relationships between specific solutes and instantaneous discharge provided useful information for geochemistry, but no clear pattern for nutrients. Silica concentrations plotted against instantaneous discharges demonstrate an exponential recession, while nutrient concentrations plotted against instantaneous discharge were arrayed in a general scatter. This suggests that weathering or hyporheic interaction is a function of discharge, while nutrient dynamics are much more complicated. With the presence of algal mats and nitrifying bacteria in- stream, nutrients may be taken up as well as generated. The uptake rates of these organisms may vary under certain conditions. For example, algal mats are distributed in stream as well as on the wetted perimeter of the stream, so depending on the amount of discharge, the water level and velocities are variable, thus affecting the organisms ability to utilize in-stream solutes.

Further insight may be gained on nutrient cycling at the daily timescale. The daily timescale represents more control in discharge levels, seeing only one hydrograph peak a day.

Throughout the course of a day, there may be certain times that are more biologically active depending upon light, temperature, and discharge.

47

Chapter 4

Fluxes at Daily Time Scales

MDV streams undergo diel fluctuations in streamflow as a function of diurnal energy balance changes on glaciers (Figure 4-1). Each day‟s hydrograph will typically peak and trough, similar to a sinusoidal signal. Solar melting peaks when the sun is positioned directly in front of a glacier face. Once the sun makes its way to the opposite position in the sky, the hydrograph will trough due to the topographic shading. In the MDVs, this effect is amplified due to the high peaks and steep walls of the valleys‟ sides. A glacier positioned in the middle of the valley will receive sun nearly all day, where a glacier position on the slope of the valley wall will only receive direct radiation for a few hours. With such low temperatures even during the austral summer, a few hours of overcast weather during what might have been a glacier‟s prime melting window can drastically change streamflow generation. Thus, streamflow is variable over a single day. However, daily streamflow is the most predictable of the three timescales studied in this thesis, and after analysis of both the inter-annual and seasonal timescales it will be the focus of this study.

Glaciers and their melt dynamics have been well-modeled in the MDVs [Bomblies, 1998;

Jaros, 2003; Hoffman et al, 2008], however, they cannot account for stochastic weather processes that may disrupt melt. This is beyond the scope of this thesis. Actual streamflow measurements and their corresponding dissolved chemistry measurements are studied here to determine hydrologic controls on stream chemistry, specifically nutrient dynamics.

48

Figure 4-1: Example of a typical MDV stream‟s diel hydrograph. This specific hydrograph is taken from midnight on January 4, 2004 to midnight on January 5, 2004 at Canada Stream‟s gauge.

49 4.1 Methods

4.1.1 Field Data Collection

During the 2008-09 austral summer, two MDV streams were monitored for 10 days at a location in proximity to their glacial source. Green Creek and Von Guerard Stream were selected for their ease of access and presence of flow, though they are also contrasting streams as Green

Creek is fairly short (1 km) and Von Guerard Stream is long (>5 km). Stream stage and specific electrical conductivity were monitored at 10-minute measurement intervals from January 17-26,

2009 at the heads of these two streams (Figure 4-2). Stage measurements were made by Tru- track pressure transducers and recorded onto Campbell Science CR-10 data loggers.

Conductivity measurements were made by ceramic Campbell Science conductivity probes. Using the upstream site and the USGS gauges at the stream outlets, measurements are compared to determine mass fluxes, as solutes and water.

Five 24-hour sampling events were conducted on separate dates, three on Von Guerard

Stream and two on Green Creek. Samples were taken every hour with acid washed nalgene sampling containers, and personnel wore acid-washed latex gloves. Samples were filtered immediately, and then chilled until they could be frozen at the completion of the experiment.

+ + 2+ 2+ - - 2- Samples were analyzed for major cations (Na ,K ,Mg ,Ca ), major anions (Cl ,F ,SO4 ), silica,

- - + 3- and nutrients (N-NO3 ,N-NO2 ,N-NH4 ,PO4 ).

For analysis, Von Guerard Stream results were not used for several reasons. During the

10 days of measurement, there was a prolonged period of overcast weather. Von Guerard Stream discontinued flow at the downstream gauge for a few days while flow was still being recored upstream. During one of the diel experiments, high stream flow forced sediments into both of the

EC probes causing them to malfunction for a large portion of the event. Upstream samples were

50 also not taken during one of the events because water froze in the tubing of an automated sampler.

4.1.2 Quantifying Hyporheic Influence

Using the upstream stage recordings and the downstream discharge measurements, a lag- time was calculated between hydrograph peaks. EC of the glacier melt water was assumed to be constant (results later show that it is). Flow at the top of the reach was assumed to be equivalent to flow at the downstream gauge. This is a reasonable assumption since the experiment takes place during late season. Most of the hyporheic volume has been filled and thaw depths most likely were no longer changing. Thus hyporheic flux of EC was calculated by multiplying the discharge by the difference between the observed downstream EC and the upstream EC. Under low and moderate flow conditions, the only source of EC should be interaction of stream water with the hyporheic sediments.

4.1.3 Nutrients

Nutrient measurements were compared between the upstream site and the downstream site for each sampling date. The lag time for meltwater to travel the approximate 300 m from the upstream site to the downstream site is likely less than one hour. Since the sampling interval for the nutrients was every hour, nutrient concentrations were compared without considering any lag time. For example, the 0500 upstream sample was compared with the 0500 downstream sample.

Upstream concentrations were subtracted from downstream concentrations, determining any change in concentration as the meltwater moved downstream. These fluxes were then compared to specific conductivity changes from upstream to downstream, determined by considering the

51 15-min lag time that was found previously. Concentrations as well as EC were often multiplied by the discharge at the time of measurement to determine fluxes as an actual solute mass per time.

Nutrient concentrations found during the 2008-09 field season experiments along with their corresponding discharge and conductivity measurements were then grouped and analyzed with all nutrient samples from the entire record. A similar analysis was done removing early season flow nutrient concentrations from the population. This was done to make sure that early season freeze damaged biomass was not biasing the results. To determine which samples were early season and which samples were not, the seasonal Q and EC plots were inspected. Early season was said to discontinue once a moving-averaged first derivative of EC became less than negative 5 µS/cm per day. If first derivative values of EC changes through time (dEC/dt) were of lesser magnitude than negative 5 µS/cm per day, then early season was said to end after the first week of flow or after the first season pulse of flow exceeding 50 L/s; whichever came first.

52

Figure 4-2: 2008-09 flow season for Green Creek. Discharge is in blue and EC is in red. January

17 through January 26 are indicated in green (EC) and pink (Q), indicating time where upstream measurements were also made.

53

Figure 4-3: Map of Green Creek sampling locations.

54

4.2 Results

4.2.1 Streamflow and Conductivity

Due to overcast conditions from January 15th to January 22th streamflow was low (Figure

4-4). There was especially heavy cloud cover from January 15th to January 19th with two separate snowfall events of less than a few centimeters. The hydrograph on the 19th peaked at a value of approximately 20 L/s with just a few hours of unobstructed solar radiation. Partial cloud cover continued until the 23rd when the sky cleared up leaving unobstructed solar radiation for the remainder of the sampling period. Strong down-valley winds were present on the evening of the

22nd and the morning of the 23rd, which coincides with a spike in the hydrograph rising to 165 L/s and dropping back to less than 10 L/s in less than 3 hours. This spike was only present at the downstream monitoring site. Strong diel fluxes were observed for the days following the 23rd.

The EC record trends downward through the monitoring period with noticeable diel fluctuations at the downstream site. The upstream site stays fairly constant with a mean of 12 uS/cm. Downstream EC values are consistently almost 5 times the magnitude of upstream values.

4.2.2 Hyporheic Influence

The calculated hyporheic influence plotted against time closely resembles the discharge time-series of the downstream monitoring gauge (Figure 4-4). Large variations in streamflow, sometimes on the order of ± 1000% in a matter of hours, explain the majority of the fluctuations in ion load. Small changes in conductivity (never straying more than 20% from the mean) have

55 little influence on the total ion load with the exception of low flow conditions. Hyporheic ionic flux greatly increased from the 23rd onward, just as discharge increased.

4.2.3 Hysteresis

Hysteresis loops were generated for each sampling event and showed no apparent trends or patterns (Figure 4-5 and Figure 4-6). With the exception of EC, most loops were very complicated, and at times were even hard to follow from beginning to end. During the low flow sampling date (January 17th-18th) (Figure 4-5) Cl- and EC levels were higher than those found during the high flow sampling date (January 23rd-24th) (Figure 4-6). Silica concentrations were much more variable during the high flow event. Both of these are indications of the dilution of weathering solutes with increasing discharge. Higher magnitude flood events also have greater recessions to base flow, explaining the larger variability in silica concentrations.

4.2.4 Nutrient Fluxes

No temporal patterns were observed from the nutrient flux calculations on either sampling date (Figure 4-7). During the low flow sampling event, uptake was evident with most of the changes in nutrient concentration from upstream to downstream being negative. This was not the case for the high flow event, which had a general scatter of values switching from positive to negative several times from hour to hour. Much higher solute fluxes were recorded on the high flow date.

56 4.2.5 Discharge and Nutrient Relationships

Early season nitrate samples were removed from the previous nitrate versus instantaneous discharge plot presented in the previous section (Figure 3-7). Once plotted, a linear regression was fit to the data finding that the R2 value had improved from 0.09 to 0.53 (Figure 4-8).

However, once the late season diel experiment samples of 2008-09 were added to the plot the R2 value dropped to 0.19 (Figure 4-9).

57

165L/s

Figure 4-4: Discharge, EC, and hyporheic ionic flux for the monitoring period from January 17-

26, 2009.

58

Figure 4-5: Low flow sampling event hysteresis loops. Green dots indicate start of sampling and red dots indicate the end. Arrows show the direction of the loop.

59

Figure 4-6: High flow sampling event hysteresis loops. Green dots indicate start of sampling and red dots indicate the end. Arrows show the direction of the loop.

60

Figure 4-7: Nutrient Fluxes and Ionic fluxes between up and downstream sites during two flow conditions. The low flow scenario is plotted on top and the high flow is plotted below that.

Phosphate fluxes are in blue, Ammonium in green, and EC in red.

61

Figure 4-8: Nitrate samples plotted against instantaneous discharge with early season samples removed.

Figure 4-9: Nitrate samples plotted against instantaneous discharge with early season samples removed and late season 2008-09 diel experiment samples added.

62 4.3 Discussion

Although monitoring was only done during late season in the 2008-09 austral summer on a single stream for a short period, some insightful patterns and relationships were observed at the daily and sub-daily scales. The mimicking hyporheic ionic flux with the magnitude and variation of streamflow further suggested the greater chemical weathering and hyporheic influence at higher discharges. A substantial increase (500%) in downstream conductivity was evident over a fairly low gradient short stream reach, suggesting that hyporheic contributions were being made.

On longer and steeper stream reaches, even greater fluxes may be observed.

Hyporheic influence is important in determining nutrient concentrations because of the prolonged contact the subsurface provides water with organisms. The substantially slower movement of water (even during high flow when hyporheic exchange is occurring most) allows sub-stream organisms to better utilize soluble nutrients.

Hysteresis loops demonstrate the complex interactions of end-members at the sub-daily time scales, suggesting that end-member contributions in time and space may be more dynamic than expected. Poor correlation between nutrient concentrations and flow, even after removing early season samples that may have contained freeze damaged biomass, also suggests that nutrient cycling dynamics (i.e. photosynthesis) may have more limiting factors such as solar position and heat intensity. High flow condition fluxes show this as well, with nutrient fluxes having no temporal pattern as well as the lack of uptake or generation dominated regimes.

However, low flow conditions did show that uptake was occurring at a greater rate than generation. This may be due to algal mats‟ better enabled access to dissolved nutrients at slower velocities. The lack of a temporal pattern through the two days of experimentation could be due to the diversity of algal species and their preference at which temperatures they thrive. Some

63 species of diatoms may be psychrophyllic, which would explain the lack of correlation with discharge (warming induced).

64

Chapter 5

Synthesis and Implications of Study

After comparing the 16 year streamflow record of eight MDV streams and their physical properties, it is apparent that streamflow characteristics are highly dependent upon glacial source and stream length. The area or volume of a stream‟s glacial source below the ablation/accumulation equilibrium line is a good indicator of how high discharge values can potentially get for each stream. The flood year of 2001-02 showed exactly that, with Aiken, Lost

Seal, and Canada having the highest flow values. All three of these streams have large portions of their glacial source below 400 m ASL. Just as glacial source plays a large part in high flow potentials, stream length correlates well with a stream‟s median discharge values. Streams have to fill up the surrounding porous soils before they can continue downstream. The longer a stream is, the greater the hyporheic volume is, causing more meltwater to be lost laterally through evaporation. This causes longer streams to take longer to fill in the early season, thus, the much later average start dates for the four longer streams. Longer streams generally flow less intensely and for a shorter portion of the flow season.

Stream length also plays a large role on stream chemistry as well. Electrical conductivity values are elevated due to the greater contact with subsurface soils allowing for more chemical weathering. Weathering solute concentrations were found to be well correlated with discharge, showing a dilution effect with greater discharges. Nutrients however did not appear to have any relationship with discharge at the inter-annual timescale, and little process information was gained.

65 At the seasonal scale, relationships between discharge and electrical conductivity became even more apparent. Early season dilution and late season concentration showed evidence of the filling and draining of the hyporheic zone. However, dilution was found not to be the only process occurring. Either there is a discrepancy in the timing of the kinematic flood wave and the transport of the solutes, or there are more in-stream processes occurring that are altering the electrical conductivity levels. Knowing that there are ecosystems in MDV streams, both of these are likely, therefore inspection of the daily timescale relationships between discharge, electrical conductivity, and nutrient concentrations was needed.

At the daily timescale, hyporheic influence was modeled by calculating electrical conductivity fluxes from upstream to downstream with late season conditions measured in

January of 2009. As expected, the hyporheic influence or ionic load closely mimicked the up and downstream hydrographs. This suggests that the two largest factors in the total solute load to the

MDV lakes are magnitude of discharge and the volume of the hyporheic zone. Determining the size of the hyporheic could be accomplished in future modeling experiments, but was not attempted here. Streams with greater reach lengths but smaller cumulative lake inflows have the potential to deliver an equal solute load to streams with shorter reaches and much higher flow magnitudes.

The nutrient sampling that was done in January of 2009 on Green Creek showed no temporal patterns at an hourly interval. Nutrient fluxes also provided no clear relationships with discharge or electrical conductivity. However, low flow conditions appear to be more uptake dominated, suggesting a possible discharge threshold where in-stream organisms become more or less active. At higher flows, where there is more subsurface forcing and a much larger wetted surface, there were much greater nutrient fluxes, positive (regeneration) and negative (uptake).

Nutrients could not be modeled with the results obtained, however, some clues were uncovered through the sampling and the analysis that followed. These are complex ecosystems, despite the

66 simplicities of the physical processes that drive them. Throughout the austral summer, certain species may become more or less active; now it appears even at the sub-daily scale this may be the case. A finer scale of sampling is needed. Discharge changes quickly over an hour, and surely solute concentrations and microbial activities do as well. It is likely that the process rates at which nutrient cycling and glacial melt occur are slightly different, complicating the sampling results. Spatial complexities may also complicate nutrient dynamics, with micro-ecosystems located in hot spots throughout the stream reach. When these locations are accessed will greatly affect downstream nutrient concentrations.

To successfully model nutrient fluxes in MDV streams, the spatial scale must be reduced.

The species diversity must be reduced as well, maybe by utilizing the harsher long stream environment. An understanding of how a controlled micro-ecosystem reacts to changes in discharge would allow researchers to determine what response certain organisms have during specific conditions, and at what magnitude.

67

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