CHARACTERIZATION OF A HIGHLY ACID WATERSHED
LOCATED MAINLY IN PERRY COUNTY, OHIO
A Thesis Presented to
The Faculty of the
Fritz J. and Dolores H. Russ College of Engineering and Technology
Ohio University
In Partial Fulfillment
of the Requirement for the Degree
Master of Science
by
Ryan J. Eberhart
August, 1998 ACKNOWLEDGEMENTS
I would like to thank Dr. Kenneth B. Edwards for all of the time spent guiding me through the course of this thesis project and all of the hours spent out in the field collecting data. I would also like to thank Branko Olujic for the many hours spent out in the field taking water samples and measuring flowrates and for writing the computer program to calculate flowrates. Next, I would like to thank Dr. Ben J. Stuart for all of his contributions to the project and Dr. Mary Stoertz and the Geology Department for allowing us to use their flume, probes, and pygmy meters.
A special thanks goes to Hocking College for all of their help with collecting water samples and measuring flowrates out in the field. Also, I would like to thank Dr.
James K. Lein for serving on my graduate committee and for his Geography 579 class notes regarding ARC/INFO, which I referenced in my thesis.
Lastly, this project would not have been possible without assistance from the
Ohio Department of Natural Resources, who fbnded this project and the Department of
Civil Engineering at Ohio University who gave me the opportunity to work on this thesis project. "To Robyn, Taylor, and my parents" TABLE OF CONTENTS
Chapter
I . INTRODUCTION...... I
I1 . LITERATUREREVIEW ...... 3
Coal Mining in Ohio ...... Mining Legislation ...... ImpactofMining ...... Important Studies Relevant to Moxahala Creek Project ...... Impact of Coal Mining on Three Ohio Watersheds-Surface .... Water Hydrology Watershed Selected for National Program ...... Water Quality and Biological Goals for an Ohio Watershed .... Damaged by Coal Mining GIs Helps Water Supplier Meet Objectives Cost-Effectively... AMD: U.S. Bureau of Mines Researches and Develops...... Control Methods for Both Coal and Metal Mines WVU Cleans AMD from the Casselman River ...... Mine Pollution Case Lingers ...... Fledgling Remediation Firm Stakes Claim at Bunker Hill ...... Aquatic Ecological Risk ...... The Surface Mining Control and Reclamation Act of 1977..... Release of Sorbed Sulfate from Iron Oxyhydroxides ...... Precipitated from AMD Associated with Coal Mining Previous Work in the Moxahala Creek Watershed ...... Creek Characteristics...... Site History ...... *Erosion...... Sedimentation...... Loss of Usehl Land ...... Mine Drainage Pollution ...... Chapter
Remediation Techniques...... 33 Active Treatment Systems...... 34 Alkaline Additions (Chemical Treatment) ...... 34 FBC Ash Grouting ...... 37 Passive Treatment Systems...... 39 Sulfate Reduction ...... 39 Constructed Wetlands ...... 41 Anoxic Limestone Drains (ALDs) ...... 42 *Summary...... 44 Purpose of Present Research Project ...... 45
I11 . FIELDDATA...... 47 Identification of Flows ...... 47 Sampling Equipment ...... 51 Flow Measurement Methods ...... 53 Cutthroat Flume ...... 53 PygmyMeter...... 56 Bucket and Stopwatch ...... 58 Water Quality and Flowrate Data ...... 60
IV . GEOGRAPHIC INFORMATION SYSTEM...... 61 Data Collection and Map Digitization...... 61 Building Topology ...... 62 ArcViewGIS ...... 63 Creating Maps ...... 64 Performing Searches and Queries ...... 68 Conclusion...... 71
V . DISCUSSION ...... MoxahalaCreek ...... Andrew Creek ...... McCluney Creek ...... BlackFork ...... Chemical Loading Analysis ...... *Acidity ...... Sulfate...... Metals (Fe, Al, and Mn) ...... Chapter Paae
Water Quality Predictions ...... 92 Methods for Prediction ...... 92 Prediction Results ...... 93 Andrew Creek Project ...... 98 Data Collection and Water Sampling...... 100 Flow Measurement Methods ...... 101 Water Quality Data Analysis...... 102
VI . CONCLUSIONS ...... 106
REFERENCES ...... 11 1
APPENDIX ...... 116 LIST OF TABLES
Table P-
1. Brief Description of How to Get to Each of the 32 Sampling Locations .... 49
2 . USEPA Test Methods for Various Analytes ...... 52
3 . Flow Measurement Methods for Each Sampling Location for Each Month . . 54
4 . Monthly Water Quality Data for Moxahala Creek Sampling Locations ..... 78
5 . Effect of Andrew Creek on Moxahala Creek's pH ...... 80
6 . Effect of Andrew Creek on Moxahala Creek's Specific Conductivity ...... 80
7 . Water Budget for the Confluence of Andrew Creek and Moxahala Creek ... 80
8 . Average Effect of Black Fork on Specified Water Quality Characteristics... 83 of Moxahala Creek
9 . Acid Loads of the Tributaries to Moxahala Creek ...... 86
10. Sulfate Loads of the Tributaries to Moxahala Creek ...... 88
11. Iron Loads of the Tributaries to Moxahala Creek ...... 89
12. Aluminum Loads of the Tributaries to Moxahala Creek ...... 90
13. Manganese Loads of the Tributaries to Moxahala Creek ...... 91
14. Average Iron and Aluminum Concentrations of all Tributaries to ...... 94 Moxahala Creek
15. Average Iron and Aluminum Concentrations of Moxahala Creek ...... 95 Table
16. Average Iron and Aluminum Concentrations of all Tributaries to...... 96 Moxahala Creek After Complete Hypothetical Restoration of Andrew Creek, Bear Creek, McCluney Creek, and Black Fork
Average Water Quality Characteristics of Moxahala Creek Over its...... 107 Final 20 Miles (afier junction with Andrew Creek)
Computer Program to Calculate Flowrate ARer Measuring Velocity and. . . 117 Area with a Pygmy Meter
Water Quality Data for the Moxahala Creek Watershed for April 1997. . . . 120
Water Quality Data for the Moxahala Creek Watershed for May 1997. . . . 121
Water Quality Data for the Moxahala Creek Watershed for June 1997. . . . 122
Water Quality Data for the Moxahala Creek Watershed for July 1997. . . . . 123
Water Quality Data for the Moxahala Creek Watershed for August 1997. . 124
Water Quality Data for the Moxahala Creek Watershed for September 1997 125
Water Quality Data for the Moxahala Creek Watershed for October 1997. . 126
Water Quality Data for the Moxahala Creek Watershed for November 1997. 127
Water Quality Data for the Moxahala Cieek Watershed for December 1997 128
Water Quality Data for the Moxahala Creek Watershed for January 1998. . . 129
Water Quality Data for the Moxahala Creek Watershed for February 1998. . 130
A. 13. Water Quality Data for the Andrew Creek Watershed for February 1997. . 13 1 LIST OF FIGURES
1. Location Map of the Moxahala Creek Watershed ...... 26
2 . Location Map of the Moxahala Creek Watershed (Within USGS 7.5...... 26 Minute Quadrangles)
3 . Moxahala Creek Watershed Sampling Locations ...... 48
4 . Sample Calculation for Determining Flowrate Using the Velocity-Area ..... 59 Method
5 . Underground Mines Located Within the Moxahala Creek Watershed ...... 65
6 . Surface Mines Located Within the Moxahala Creek Watershed ...... 66
7 . Both Underground and Surface Mines Located Within the Moxahala ...... 67 Creek Watershed
8 . Streams Having a pH < 4.0 in August 1997...... 69
9 . Various pH Levels for those Streams Having a pH < 4.0 in August 1997.... 70
10. Average pH of All Months for Moxahala Creek ...... 74
11 . Average Specific Conductivity of All Months for Moxahala Creek ...... 75
12. Average Acidity of All Months for Moxahala Creek ...... 76
13 . Average Sulfate Concentration of All Months for Moxahala Creek ...... 77
14 . Preliminary Sampling Locations and Underground Mines Within the ...... 99 Andrew Creek Watershed
15. Andrew Creek Watershed Sampling Locations ...... 103 xi
Figure Paae
A . 1. Moxahala Creek pH (April 1997 through September 1997)...... 132
A.2. Moxahala Creek Specific Conductivity (April 1997 through September 1997). . 133
A.3. Moxahala Creek Acidity (April 1997 through September 1997)...... 134
A.4. Moxahala Creek Sulfate Concentration (April 1997 through September 1997). 135
A.5. Moxahala Creek pH (October 1997 through February 1998)...... 136
A.6. Moxahala Creek Specific Conductivity (October 1997 through February 1998) . 137
A.7. Moxahala Creek Acidity (October 1997 through February 1998)...... 138
A .8 . Moxahala Creek Sulfate Concentration (October 1997 through February 1998). 139 CHAPTER I
INTRODUCTION
The Moxahala Creek watershed, located mainly in Perry County, Ohio, has become severely contaminated by acid mine drainage (AMD) from past underground and surface mining operations performed in the watershed. This paper discusses the complete characterization of the watershed and singles out those areas mainly responsible for the contamination.
After highlighting the history of coal mining in Ohio, a literature review addresses various aspects of the Moxahala Creek watershed. Legislation passed to control the impacts of mining, the impacts of mining themselves, and a background on AMD chemistry are also discussed in the chapter. After looking at some published articles related to various aspects of the watershed study, an in-depth look at the site location, history, and characteristics is taken. Next, the literature review focuses on some of the remediation techniques that can and have been used to clean up contaminated watersheds. Although devising a restoration plan was not part of this research project, the techniques mentioned are all possibilities when and if a scheme is employed. Lastly, the purpose and objectives of the current research project are fully explained.
Chapter I11 discusses all of the data that was collected in the field, as well as how it was taken. It discusses how water quality sampling locations were determined, the sampling equipment used, and the different methods used for measuring flowrates at the 2 various streams within the watershed. Finally, the lab methods used for water quality analysis are covered. This section also presents all of the water quality data collected during the 11 months of sampling of the Moxahala Creek watershed and the one month of sampling of a specific sub-watershed (Andrew Creek).
The next chapter discusses geographic information systems (GIs) in general and the details of the GIs that was constructed for the Moxahala Creek watershed. Methods for creating the GIs using ARC/INFO and ArcView GIs, for creating various types of maps explaining the data, and for performing searches and queries on the collected data are all hlly explained. Lastly, some of the capabilities and advantages of using a GIs are discussed.
Chapter V presents a discussion of the water quality data collected and pinpoints the tributaries that most affect Moxahala Creek's water quality. A close look at the water quality characteristics of those tributaries that degrade or enhance Moxahala
Creek's water quality is taken. The chemical loads that each of these tributaries contributes to Moxahala Creek are also presented.
The final chapter presents the conclusions of the research project and also provides some recommendations for future research within the watershed. Hopehlly, as a result of these conclusions, a restoration plan will be devised and implemented to remediate the Moxahala Creek watershed and improve the creek's water quality. CHAPTER I1
LITERATURE REVIEW
The most relevant studies regarding the Moxahala Creek watershed are presented in this chapter. Past coal mining operations in Ohio are discussed along with the legislation passed to control them. The Moxahala Creek watershed's location and site description are given, as well as the impact that mining operations and AMD have had on the watershed itself Finally, published articles relevant to various aspects of the
Moxahala Creek project are reviewed, as are some of the remediation techniques that are being employed to enhance and restore contaminated watersheds.
Coal Mining in Ohio
The first record of coal mining in the United States is for Virginia in 1702
(Humphrey, 1959). Although the existence of coal was noted by frontiersmen as early as
1748, the first reported production of coal in Ohio was in 1800. Perry County, where the Moxahala Creek watershed is mainly located, started producing coal in 1816 and is the fourth highest coal-producing county historically in Ohio (Crowell, 1995).
Coal production in Ohio increased steadily but very slowly until the mid-1 800s.
However, during the mid-1800s Ohio transformed from an agricultural economy to an industrial economy. This change helped develop Ohio's coal industry, making Ohio one of the largest coal-producing and coal-consumiilg states in the nation. As the demand for coal increased during the 1800s, underground mines were developed to extract the 4 coal without removing the overburden and soil. This industrial development was mainly due to the manufacturing of railroad equipment, farm machinery, and supplies for the
Civil War, (Noble and Korsok, 1975) and because coal was an abundant, accessible, and inexpensive fuel. In the production of steel, large amounts of coal are used to make coke, the fuel used in blast furnaces.
From the Civil War times to the 1930s, Ohio's coal production increased steadily and rapidly due to improved methods of transportation and mining. Due to the World
War I effort in 1918, the coal work force in Ohio reached its peak level of more than
50,000 workers, more than 12 times the 1993 level. Despite slumping coal production between World War I and World War 11, production increased steadily from the mid
1940s until 1970. This happened despite a 90% decrease in the number of underground mines from 1950 to 1970. The decreases in number of mines and workers occurred due to the emergence of surface coal mining (Crowell, 1995).
Surface mining made a significant rise after World War I1 due to the development of very large and efficient earth moving equipment that allowed coal near the surface to be mined more easily, inexpensively, and with fewer workers than underground mines.
Despite challenges from petroleum in the form of diesel power to become the nation's dominant hel, coal survived and Ohio's coal production peaked at 55 million tons in
1970 (Crowell, 1995).
Since 1970, though, Ohio's annual coal production has declined over 50% to the
1993 level of 27.6 tons, its lowest level since 1941. This decrease was due to the 5 increasing regulation of surface mining, health and safety issues, increased transportation costs, and mainly due to the implementation of the Federal Clean Air Act in 1970. This act placed strict controls on SO2 emissions from burned coal. The Clean Air Act of 1990 placed hrther controls on emissions and caused a continued decline in Ohio's coal production (Crowell, 1995). An amazing fact is that approximately 3.4 billion tons of coal has been mined in Ohio through 1993, yet the state's remaining coal reserves in the ground are estimated at 1 1.8 billion tons (Energy Information Administration, 1993).
Coal is a sedimentary rock formed by the accumulation, alteration, and compaction of plant remains in a reducing environment such as a swamp. Until 1948, underground mining was the principal method for coal mining in Ohio. Drift mines were the predominant types of underground mines used in Ohio. A drift opening, being a horizontal passageway, is able to exploit coal seams where they crop out. The most popular method of underground coal mining in Ohio has been the room-and-pillar method, where the coal is mined in rooms separated at regular intervals by roof- supporting pillars (Crowell, 1995).
Due to the high-strength steels produced during World War 11, large surface mining equipment was able to be built. Surface mining is simply the extraction of coal by removing the surface of the ground. Modern machinery, called draglines, are now able to remove up to a depth of 200 feet in a single pass. Because surface mine operators were not required to restore disturbed mine lands before the enactment of federal legislation, they simply left the overburden rock behind (Ctcnet, 1998). Mining; Legislation
In 1939, the first legislation to control surface mining in the nation was enacted in
West Virginia. Mine operators were required to pay bonds of $150 per acre to help ensure reclamation, an amount that would increase to $1000 per acre by 1977 following the Surface Mining Control and Reclamation Act (SMCRA) of 1977. SMCRA required mine operators to obtain a mine permit, indicating information about the site such as geology, soils, vegetation, and water resources. The permit is also to include a mining operation plan, methods and procedures to reduce and control environmental impacts during mining, and a reclamation plan. Final reclamation included the backfilling and grading of overburden. Additionally, the mine operator must revegetate the reclaimed land and maintain it for five years, attempting to achieve premining water quality.
Finally, the operator must also determine a use for this reclaimed land (Skousen, 1995).
Ohio passed its first mining reclamation law in 1948. The Strip Coal Mining Act required mine operators to get a mining license and post a bond of $100 per acre to ensure reclamation of their mined lands. This reclamation simply involved leveling off the tops of spoil piles and the revegetation of mined lands. The Coal Strip Mine Land
Reclamation Act was passed six months later, creating the Division of Reclamation within the Ohio Department of Agriculture. Besides increasing the bond rate, it also suggested reclamation plans for auger mining operations. In 1959, some additional amendments were passed, one allowing the state to take over unreclaimed mine lands and use bond forfeiture funds to perform reclamation. Amendments enacted in 1965 and 7
1971 increased bond and license fees. Before the enactment of SMCRA in 1977, Ohio passed its most stringent law in 1972 requiring reclamation plans, bonds equal to the reclamation cost, and stricter water pollution prevention practices. Ohio passed additional stringent legislation involving coal mining since SMCRA was enacted. Ohio
Revised Code Chapter 1513 contains the complete set of revised Ohio laws involving coal mining.
Impact of Mining
Coal mining disturbs large amounts of geologic material and exposes them to the environment. When this material is exposed to air and water, iron sulfide (pyrite) from the coal deposits is oxidized, resulting in acid mine drainage (AMD). These conditions lower pH, increase acidity, increase dissolved metals, and lead to an overall degradation of water quality. AMD is a low pH, high sulfate water with high acidity usually due to oxidation of iron, aluminum, or manganese and also due to hydrogen ions.
Approximately 12,500 miles (20,000 km) of streams and rivers in the United States are impacted by AMD, and about 85 to 90% of these streams receive AMD from old, abandoned surface and deep mines (Skousen, 1995). Due to the high costs involved for reclaiming abandoned mine lands, AMD continues to contaminate numerous surface and groundwater supplies.
Although sulfide minerals have a relatively low solubility in water, they are unstable in the presence of dissolved oxygen and/or ferric iron. Dissolved oxygen and ferric iron can oxidize sulfide minerals such as pyrite, as demonstrated in equations (1) and (2) (Sobek et al., 1978):
FeS2 + 3.502 + H20 Fe2' + SO? + 2~' (1)
FeS2 + 14~e~'+ 8H20 j 15Fe2' +2~0~~-+ 16Hf (2)
Note that eight times more acidity is produced when ferric iron oxidizes pyrite (2) than when dissolved oxygen is the oxidant (1).
Following either of the preceding reactions, ferrous iron is then oxidized to ferric iron in the presence of oxygen, and it consumes acidity, as seen in equation (3) (Sobek et al., 1978):
~e~'+ 0.2502 + H' j Fe3' + 0.5H20 (3)
This reaction is the rate-limiting step in the production of AMD in the pH range from 2 to 9 (Moses and Herman, 199 1).
Certain bacteria called Thiobacillus and Leptospirillum are able to derive energy from the conversion of ferrous to ferric iron (Stewart and Severson, 1994). Reaction (3) proceeds slowly at pH values less than 4, but the presence of these bacteria can speed the reaction up by a million times (Stewart and Severson, 1994). These bacteria thrive where mining has taken place as long as there is minimal oxygen present. Thus, AMD generation can be a very rapid process. At pH values greater than 4 when these bacteria are present, the reaction is very fast, resulting in the precipitation of iron hydroxides, as seen in equation (4) (Sobek et al., 1978):
Fe3' +3H20 Fe(OH)3 + 3~' (4) Important Studies Relevant to Moxahala Creek Project
The following reviews of published articles relate to various aspects of the
Moxahala Creek project. Some of the topics discussed are mining laws, geographic information systems, aquatic survival requirements, surface water hydrology, and various
AMD remediation techniques. Most of these articles show the importance of and need for watershed characterization and restoration.
Impact of Coal Surface Mining on Three Ohio Watersheds - Surface Water Hydrology(Bonta et al., 1997)
A project fbnded by the U.S. Bureau of Mines and the USDA-Agricultural
Research Service was undertaken to evaluate the impacts of surface coal mining and reclamation on surface and groundwater hydrology and water quality in small watersheds. The main goal of the project was to determine the effects of mining and reclamation on seasonal variations in the response of watershed runoff volume to precipitation, on the distributions of watershed flow volumes through the entire project period, and on watershed peak-flow rates. A hrther purpose was to evaluate the effects that drastic land disturbances have on the response of an entire watershed, not just individual watershed processes that may have caused observed effects.
Three experimental watersheds were monitored during three phases of watershed disturbance: before mining (Phase I), during mining and reclamation activities (Phase 2), and after reclamation (Phase 3). The study sites underwent drastic changes in shape, location, and topography and also in surface drainage network. Changes in the distribution of daily watershed stream flow volumes due to mining and reclamation were 10 evaluated by creating flow-duration curves for each phase of disturbance. Also, changes in watershed responses due to mining and reclamation were evaluated for rainfall intensities that produced larger peak flows. The ratio of peak-flow rate to the corresponding causal rainfall intensity is a measure of how responsive the watershed is to high rainfall intensities, and it incorporates the effects of rainfall duration and watershed features.
Based on the six years of data taken at these three approximately 40-acre watersheds, the following conclusions were drawn. First, slightly frequent higher daily volumes occurred during Phases 2 and 3 compared with Phase 1. However, baseflow responses to mining and reclamation showed no consistent pattern. But mining and reclamation activities did cause a reduction in seasonal variability of runoff volumes due to lack of vegetation. Also, reclamation can restore the seasonal variation in rainfall- runoff watershed processes, but the effect was not apparent at all sites. Finally, watershed peak-flow response to rainfall intensity increased between Phases 1 and 3, but generally decreased between Phases 1 and 2. Although the Moxahala Creek watershed is 106 square miles and much larger than these experimental watersheds, the same principles and findings of this study apply to it.
Watershed Selected for National Propram (Bona and Murray, 1993)
The Rouge River watershed in southeastern Michigan was selected for a federally funded national demonstration program addressing urban runoff and combined sewer overflows (CSO). The program evaluates the watershed and the contaminant sources that impact river water quality, and its main goal is to determine the measures for the greatest water quality improvements at reasonable costs. The program, which began in late 1992, will last three years and quantifL and define contaminant loadings from wet weather sources. Reduction of contamination will be monitored throughout the program.
A geographic information system (GIs) will be developed and will identify the river's tributaries, display existing and anticipated water quality data, identi@ storm discharge locations, relate land use and potential contaminant sources to river location and water quality studies, and present different types of geographic and water quality data in comparable formats. The GIs allows for analytical data from water quality studies to be stored, sorted, and displayed in map formats. This same sort of information and setup will be used in the GIs constructed for the Moxahala Creek watershed. The final goal of the GIs for Rouge River's watershed is to use the results of various computer models to produce a water quality model that will predict the quality of water throughout the watershed during and after storms. Computer models will also be used to determine the effects of physical changes that will most improve the watershed's overall water quality.
Samples will be collected to determine Rouge River's baseline water quality levels before any remediation occurs. They will be taken regularly at various locations throughout the watershed and will help locate and quantify contamination sources.
Samples will also be taken after various remedial activities to assess the effectiveness of each action. They will estimate the nonpoint source contamination attributable to atmospheric deposition and the extent and severity of contaminants in sediments.
Concurring with NPDES permit requirements, construction of CSO abatement facilities will occur as a result of this study. All future CSO facilities in the watershed will be designed accordingly. The program also calls for contaminant land assessment of the identified nonpoint sources and alternative methods for reducing contamination.
Finally, sediment contamination will be evaluated to estimate its water quality impacts during wet weather.
Water Quality and Biological Goals for an Ohio Watershed Damaged bv Coal Mining (Stoertz and Burling, 1996)
Monday Creek drains a 117 square mile watershed in southeast Ohio and has been impacted greatly by past underground and surface mining. Due to acid mine drainage from these mines, the water quality of Monday Creek has suffered and aquatic life has been impaired in much of the creek. Therefore, the water quality of Monday
Creek must be improved if fish are to prosper in it.
The Monday Creek Restoration Project began in 1994 and established the long- term goal of making the stream "fishable." The water quality goals that are needed to completely restore the stream are: (pH > 6.5, ~a'~> 2 mgll, alkalinity > 5 mg/l, ~1'~<
5pg/l, and Fe < 1 mg/l). Because these parameters are correlated, water quality goals may be viewed in terms of only pH and alkalinity.
Local assessment of healthy streams aided in the determination of the stated water quality goals. The primary technical goal of the project is restoration of a normal 13 fish population in the stream, mainly through neutralizing sources of acid mine drainage.
The acid sources must be prioritized and then selected for miles of stream recoverable, because severely degraded headwaters may contaminate many miles of downstream water. Therefore, some of the high acidity sources are not worth treating individually at this time and should be treated when restoration has more momentum. Once all of the acid sources have been identified and prioritized, the neutralization of the acid mine drainage can begin, and the goal of a fishable stream can become a reality.
GIs Helps Water Supplier Meet Obiectives Cost-Effectively (Chernin, 1996)
The Massachusetts Water Resources Authority (MWRA) is responsible for the protection and maintenance of more than 800 square miles of service area and watersheds, 780 miles of pipeline, dozens of pumping stations, and many treatment works. Thus, the MWRA has developed a GIs to support its enormous project operations and planning needs. The GIs has developed into an information management system that supports automated mapping, hydraulic modeling, site-specific analysis, maintenance, and facilities management.
MWRA utilized the value of GIs mapping to describe the potential impacts of watershed protection legislation that it was sponsoring. They have also collected the data developed for study, planning, and design projects, put it into GIs format; and saved and managed the data for hture use.
MWRA7sfirst applications of GIs involved watershed protection to maintain the quality of its two own reservoir sources. Due to the large number of water sources and land areas, a GIs was used for data management analysis and mapping. It also delineated surface and groundwater zones recommended for protection. After potential contamination sources were identified, the GIs was used to establish a spatial and tabular database and class@ them in order of highest concern based on their adverse effects on water quality.
After determining that one of the reservoirs did not meet Safe Drinking Water
Act requirements, MWRA pursued the siting and design of a new water filtration plant.
It manipulated GIs data by selecting exclusionary and preference criteria. Exclusionary criteria such as excessive land slope, bedrock at shallow depths, and residential density would exclude areas from hrther consideration. Preference criteria such as publicly- owned land tracts, protected open space around the site, and short driving distance to major roads would help select the most appropriate site location for the plant.
In another GIs development, MWRA has taken the sewer system records and automated the records of every pipe, valve, meter, and fitting in the distribution system.
Now, when MWRA users click on a pipe drawing, instead of only being able to access the drawing, users can choose from a menu of options regarding the land records, model scenarios, and the physical condition and maintenance history of the pipe. As can be seen, GIs is an invaluable tool for organizing and manipulating data for many different types and sizes of projects. AMD: U.S. Bureau of Mines Researches and Develops Control Methods for Both Coal and Metal Mines (Kleinmann, 1989)
The mining industry in the United States spends over $1 million every day to treat acidic mine water. AMD continues to be a problem at abandoned mines, even those inactive for over a century. Environmentally, these abandoned mines are a blemish on the industry's image and an impediment to future mining operations. Therefore, the former Bureau of Mines (BOM) desired to reduce costs and future liability of treating acidic mine water and develop ways to mitigate AMD from abandoned mines. They addressed low-cost alternatives to control AMD at its source and the problem of predicting AMD before mining begins.
Research has produced two low-cost alternatives to conventional neutralization.
The first, the In-Line Aeration and Neutralization System (ILS), is a pipeline version of a conventional water treatment system that uses a jet pump to entrain the air and alkaline chemical by Venturi action, and a static mixer. Operating by water pressure generated by the existing mine-water pumps, the ILS is more efficient than conventional treatment systems and less expensive to install, operate, and maintain. Since the ILS homogeneously mixes and aerates all of the AMD, the pH does not have to be raised as much. Tests with acidic coal mine drainage support the increased efficiency due to better aeration.
The other inexpensive alternative is biological treatment through the use of wetlands. The BOM's wetlands contain cattails and a six inch limestone base. Twelve to 18 inches of composted organic material is then placed above this base as a substrate for the plants. Six inches or less of water above this material assures good contact between contaminated water and the biologically active zone. A final chemical treatment is usually needed, as wetlands systems usually do not meet effluent standards.
The most accepted method of stopping AMD at its source is to inundate pyritic material, thereby eliminating pyrite oxidation. Inundation must be complete for this to work. Another approach involves the use of anionic surfactants (cleansing detergents) to inhibit the iron-oxidizing bacteria responsible for rapid pyrite oxidation. The surfactants decrease the activity of these bacteria and thus retard pyrite oxidation.
Further approaches include chemical additions to provide in-place neutralization and the retardation of pyrite oxidation by armoring or precipitating reactants. The problem with this is that all of the acidic water must be neutralized. Therefore, due to short residence times and heterogeneous flow, this method is relatively inapplicable for surface mines. However, it may be used in underground mines where large pools of acid water could be periodically neutralized.
Pyrite-water contact reduction can also reduce the formation of AMD. After determining leak zones by geophysical methods the fractured stream bed is mended by injecting a polyurethane grout beneath the sediment-water interface. The cost per linear foot is as low as half that of conventional stream repair. Tests by the BOM above active longwall operations and an old, abandoned room-and-pillar mine have been extremely successful. Due to the large potential liability that AMD can carry, the ability to predict water quality during and after mining is desirable. However, the BOM has found that coal mine predictions are not very useful. New methods of overburden analysis can be implemented into the predictive process. AMD is obviously a problem that has no one solution. All of the recommendations mentioned have shown promise in solving the problems caused by AMD and repairing the harm that it has done to the environment.
WWCleans AMD from the Casselman River (Larchmont, 1995)
AMD from abandoned deep mines has contaminated the once pristine Casselman
River watershed in West Virginia. Mine seals were constructed during the Depression years and gradually improved water quality, but the seals blew out, contaminating 47 miles of the Casselman River.
The National Mine Land Reclamation Center (NMLRC) at West Virginia
University (WVU) received a $450,000 grant from the federal government through the
United States Environmental Protection Agency (USEPA) to clean up the Casselman
River watershed. This involves protecting it from hrther degradation and restoring its waters to a pH that can once again support aquatic life.
The USEPA has stated that the AMD from abandoned coal mines is the number- one water quality problem in Appalachia. This pioneer project in AMD abatement and watershed restoration will utilize large-scale passive water treatment technologies such as limestone drains, which have never been applied on such a large scale. Researchers think they can be used to restore entire watersheds. The main reason for utilizing passive treatment systems is due to cost. A typical, active chemical water-treatment operation would cost about $500,000 to build and more than $300,000 per year to operate. Scientists agree that the economic advantages of passive systems make them more feasible alternatives for large watershed rehabilitation projects.
Mine Pollution Case Lingers (Travis, 1993)
In August, 1993 a federal jury in Georgia ordered a $45 million damage award against Combustion Engineering (CE), Inc, for polluting creeks near its abandoned mine in the state. Company officials think that the penalty is excessive, and they have filed a motion to a federal district court to dismiss the verdict.
Fifteen landowners claimed in a 1991 lawsuit that CE "wrongfblly allowed acid mine drainage" into creeks that entered their properties. On the 400 acre mine site, CE strip mined pyrite and kyanite before it attempted to sell the mine. After the property was reverted back to CE, they received notice of the lawsuits. Claiming to have lost use and enjoyment of their properties, the 15 landowners received $3 million in punitive damages from CE.
A CE spokesperson claims that these punitive damages are "grossly disproportionate" to actual property damages. Despite spending nearly $2 million on a series of dams and a drainage system to improve the problem, CE is still looking at different alternatives to remedy the situation. CE says they will appeal the decision by the federal district court if the verdict is not in their favor. Fledgling Remediation Firm Stakes Claim at Bunker Hill (Daniels, 1997)
A new remediation technology developed by Klean Earth Environmental
Company (KEECO) is being tested on acid mine drainage at a Superfbnd project near
Kellogg, Idaho. Based in Lynnwood, Washington, KEECO claims that treatment costs well below '/? cent per gallon, which is less than half of what the government now spends to neutralize acid with lime. Because disposing of resulting sludge increases costs hrther for the government, KEECO officials say their in situ technique will eliminate disposal expenses.
KEECO claims that they can produce drinking water from the nation's worst
AMD by implementing their new technology. "The firm adds water to a highly reactive, proprietary chemical powder to form slurries that are injected into contaminated soil, wastewater, or even radioactive waste." This mixture then absorbs suspended metal ions upon contact through a "polymerization without polymers." The process captures metals into an impermeable silica matrix that makes them inert.
After running tests at the Superfimd site in Idaho, KEECO hopes to replace a 23 year old, EPA managed lime plant that is treating water for $50,000 a month. KEECO has a portable plant that mixes the chemical slurry in batches of 1.5 grams per liter of water, pumps in air and injects the mixture through tubes that intercept the stream. The result is clean water. Removing up to 99% of suspended solids from solution, this new process could clean up the Idaho site in as little time as three years. 20
Metcalf and Eddy, a Massachusetts based firm, is negotiating for the rights to the process. They are interested in using it to treat harbor sediments and industrial wastewater, as well as AMD.
Aquatic Ecoloaical Risk (Cardwell et al., 1993)
A three tier aquatic ecological risk assessment methodology was done on a stream impacted by acid mine drainage. Two of the tiers were used to determine the risk to aquatic life from AMD. The first tier tested the stream's 19 metals for toxicity, and only four posed potentially significant risks of acute and chronic toxicity to aquatic life.
The second tier determined the proportion of aquatic population and total number of species affected based on probability distributions for exposure and toxic effects. Tier two also quantified risks with existing data while the third tier did the same with new data that was found.
These assessments were used to evaluate AMD that had surfaced to form a stream running into a scenic river containing a threatened fish species, the roundtail chub. Only the most mobile metals persist in the stream, due to the natural pH neutralization of the AMD.
The tier one assessment showed that four metals - manganese, cobalt, aluminum, and cadmium - posed potential risks to aquatic life, in order of highest to lowest risk.
These metals concentrations suggest a high potential of chronic toxicity. Tier two calculated the risk of the three chemicals of potential concern - aluminum, cobalt, and manganese. EPA acute and chronic water quality criteria and benchmark concentrations of the chemicals of potential concern were used as measurement endpoints. The criterion is intended to protect all but 5% of the species from acute and chronic toxicity.
The results of the risk assessment are as follows: for aluminum, there was limited risk of acute toxicity and no risk of chronic toxicity; for cobalt, there was negligible risk of acute toxicity and high risk of chronic toxicity; for manganese, there were significant risks for both acute and chronic toxicity. A benthic macroinvertebrate biosurvey concluded that the risk predictions were accurate. These risk assessments and predictions play a major role in risk management and making remediation decisions.
The Surface Mining; Control and Reclamation Act of 1977 (Harvey, 1978)
Surface mining replaced underground mining as the predominant method for producing coal in the mid-1970s, and by 1977, coal surface mining disrupted about one thousand acres of land each week. Congress knew that coal mining contributed significantly to the nation's energy requirement, but they also recognized that it caused many problems concerning people, property, and the environment.
Surface mining affects the environment in many different ways. In coalfields, spoil is pushed downslope of mountain mines causing landslides, erosion, sedimentation, and flooding. In addition, unstable highwalls are a hazard to life and property, and they frequently erode from weathering, thus ruining tirainage patterns and adding to water pollution. Surface mining is also completely inappropriate in wilderness areas, parks, and wildlife refuges, and these areas should be protected. 22
Despite all of the problems caused by surface mining, its expansion is necessary to meet the nation's energy needs. It is obvious that unreclaimed or improperly reclaimed surface coal mines pose a serious threat to the environment. Thus, on August
3, 1977 U.S. President Jimmy Carter brought an end to a long battle to enact federal legislation regulating surface coal mining by signing the Surface Mining Control and
Reclamation Act (SMCRA) of 1977 (USDOI, 1988).
Highlighting some of the reasons for establishing SMCRA, the purposes of the
Act are: to establish a nationwide program to protect society and the environment from the adverse effects of surface coal mining operations, to assure that the rights of surface landowners are fully protected from such operations, to assure that surface mining operations are not conducted where reclamation is not feasible, to assure that adequate procedures are undertaken to reclaim surface areas as contemporaneously as possible with the surface coal mining operations, to strike a balance between protection of the environment and agricultural productivity and the Nation's need for coal as an essential source of energy, to assist the States in developing and implementing a program to achieve the purposes of the Act, to promote the reclamation of mined areas left without adequate reclamation prior to the enactment of SMCRA that continue to substantially degrade the quality of the environment, and to provide or supplement programs for research investigations and training in the areas of mining, mineral resources, and new techr~ologiesthat may be implemented. Some of the major provisions of SMCRA involve initial enforcement, state programs, federal programs, application requirements, and reclamation plans. First, the
Act requires that the Secretary of the Interior establishes interim regulations within 90 days of enactment and that permanent regulations must be established within 12 months.
A proper permit is required to conduct surface mining operations on non-federal lands.
All new mines must comply with eight environniental standards, which should help remedy the environmental degradation resulting from current coal surface mining practices. Federal inspections are also made to help enforce and insure the success of the program.
Another section of SMCRA requires states to propose to the Secretary of the
Interior a program that shows that the state has the legal, financial, and administrative capability for carrying out the provisions of the Act if the state wants exclusive jurisdiction in administering surface mining regulation on its non-federal lands. The state program must meet the minimum requirements of SMCRA, but the states reserve the right to develop laws and regulations that are more stringent than federal controls of surface mining and reclamation operations. If a state shows that it cannot regulate surface mining and reclamation by itself, the federal government assumes regulation.
After considering the state's terrain, climate, and physical conditions, the government will implement the most appropriate regulation program.
Application requirements include identification of all parties, corporations, and officials that will be involved, a listing of past mining and reclamation permits, a mining operation plan, a full description of on-and-off site hydrologic consequences of mining and reclamation, and maps and data to describe the surface and subsurface features of the area to be mined. A reclamation plan is also needed that describes the land area that will be mined and also whether the land can, indeed, be reclaimed. Past mining operations on the land must be included, and some alternative reclamation technologies must also be considered in the application.
There are some performance standards that prove to be the substantive heart of
SMCRA. The Act states that mined lands must be restored to a condition capable of supporting the uses that it could support prior to mining. The performance standards involve the approximate original contour with highwalls eliminated, contemporaneous reclamation, revegetation, excess spoil, mountaintop mining, and steep slope mining.
There are specific laws and regulations to be followed in each of these areas.
Some final programs that SMCRA has iinplemented include abandoned land reclamation, a minerals research program, and the establishment of the Ofice of Surface
Mining Reclamation and Enforcement. These programs are hrther efforts to preserving the environment and making it a better place to live.
Release of Sorbed Sulfate from Iron Oxyhydroxides Precipitated from Acid Mine Drainage Associated with Coal Mining (Ghazi and Rose, 1997)
The biogeochemical oxidation of pyrite present in coal spoil results in the production of secondary iron oxyhydroxide phases and elevated hydrogen, sulfate, and metal ion loading. Despite a great deal of research interest in metals associated with
AMD, less attention has been paid to the fate of sulfate. Nevertheless, sulfate 25 contamination often exists and may be the best indicator of the impact of mining on a drainage system. Some recent studies have shown that sulfate present in AMD can sorb to iron oxyhydroxides and precipitate to form a number of minerals. Consequently, aqueous sulfate concentration and ironlsulfate ratios are factors that influence the types of iron oxyhydroxides phases that form in AMD.
In this study, batch experiments were used to investigate the release of sulfate sorbed on amorphous iron oxyhydroxide that formed in AMD (pH = 2.8-3.2) from the
Stearns Coal Belt in Kentucky. Sediments were very high in sulfate concentrations.
Another experiment involving ligand exchange indicated that 60% to 70% of the total sulfate will be retained in the presence of monovalent ligands. This is possibly indicative of a "bidentate" bridging mechanism bonding iron and sulfate. The majority of this sulfate will probably be stable upon the secondary iron oxyhydroxides associated with
AMD. It was also found that sulfate desorption increased directly with pH. At a neutral pH, about 33% - 50% of the total sulfate present in the precipitates was released to solution. The bicarbonate ion released approximately 60% of the total sulfate from one of the AMD precipitates. A conclusion from these results is that acid neutralization methods used to stabilize metals in AMD can have the unwanted effect of raising sulfate concentrations within impacted watersheds.
Previous Work in the Moxahala Creek Watershed
As is seen in Figure 1, the 106-square mile Moxahala Creek watershed is located mainly in Perry County in southeast Ohio. Approximately 25% of the watershed is L CJCleveland I co.
Cincinnati
Figure 1. Location Map of the Moxahala Creek Watershed
Deavertown
Figure 2. Location Map of the Moxahala Creek Watershed (Within USGS 7.5 Minute Quadrangles) located in Muskingum County and about 10% is in Morgan County. Figure 2 also shows that the watershed is located in the four following U. S.G.S. 7.5 minute
Quadrangles: New Lexington, Deavertown, Fultonham, and Crooksville. A more detailed map of the Moxahala Creek watershed can be seen in Figure 3.
Moxahala Creek flows in a northeast direction through the center of the watershed towards Zanesville, Ohio, where it enters the Muskingum River. The
Muskingum River flows southeast, eventually entering the Ohio River.
Creek Characteristics
Moxahala Creek increases tremendously in size due to the approximately 140 miles of tributaries flowing into it over its 25 mile length (USDA, 1985). Having its source near Moxahala, Ohio, the creek has typical flows near 100,000 liters per minute
(Ipm) approximately 20 miles downstream, 5 miles from its junction with the Muskingum
River. Moreover, the average pH at the beginning of the creek is above 6.0 while that near the end is near 4.5. Moxahala Creek is a large creek and will thus have a tremendous impact on its surrounding environment. There are no signs of aquatic life in the creek, and this can be attributed to its low pH, high acidity, and high sulfate concentrations.
Site History
Because of the past mining done and due to the geologic setting of the Moxahala
Creek watershed within Ohio's coal region, many mining-related problems have persisted in the basin. The Moxahala Creek watershed is one of the worst watersheds in the southeastern Ohio coal region in terms of mine drainage impact on water quality and other characteristics. Some other problems facing the basin include erosion, sedimentation, flooding, and the loss of useful land (USDA, 1985).
The geologic formations underlying the Moxahala Creek basin consist mainly of sandstone, shale, limestone, and coal of Mississippian and Pennsylvanian age and glacial deposits of clay, silt, and gravel of Quaternary age (USGS, 1987). These Pennsylvanian age cyclotherms contain mineral assemblages that become extremely unstable when they are exposed to the earth's atmosphere. Because the bedrock in the watershed typically consists of sandstone, there is no natural neutralization of AMD by the sandstone.
Additionally, sandstone actually contains small fragments of pyrite within it. A study has proven that in groundwater flowing through minespoil, heterogeneous sandstone within the spoil has been responsible for the degradation of the water quality in a receiving lake
(Edwards and Turney, 1997). If the bedrock was mainly limestone, there would be some naturally occurring AMD neutralization. Certain chemical and biological reactions also occur that cannot be reversed by natural forces; thus, any changes desired to be made to the degraded environment must be done by human effort. Reclamation activities have brought about remarkable improvements to mine environments, but because funding by
SMCRA to continue reclamation work on orphan mines expired in 1992, there was much pressure to reclaim the high priority watersheds before funding ceased (USDA,
1985). It is interesting to note that there have been some reclamation projects in the 29
Moxahala Creek watershed required by SMCRA, but those areas mined prior to 1977 are the ones that are contributing the most AM) contamination to the watershed.
An assessment of areas in Ohio impacted by abandoned mines was published in
1985 and is still valid today (USDA, 1985). This assessment addressed various characteristics of many of Ohio's watersheds, including the Moxahala Creek watershed.
Erosion
Erosion rates on abandoned strip-mined lands represent by far the highest soil losses on any lands within the state of Ohio. Average erosion rates for the mined watersheds in Ohio with the highest rates were over 50 tons per acre per year (t/a/y).
Because the Moxahala Creek watershed is the fifth ranked watershed in Ohio in terms of highest erosion rates, its rate can be assumed to be well in excess of 50 t/a/y. In general, those areas which are eroding at a rate of 25 t/a/y or greater will never naturally produce a significant vegetative cover of any type. Thus, it is safe to say that the Moxahala
Creek watershed fits this classification and probably needs to be vegetated manually
(USDA, 1985).
The Moxahala Creek watershed's erosion problems are due mainly to the following physical and chemical factors: mine spoil chemistry, physical properties, and physical relief. In the basin, aerobic bacterial digestion of pyrites in mine spoils creates a by-product of sulfbric acid that prevents or retards plant growth and virtually consumes organic detritus. Acid mine spoils also exhibit very high chemical and physical dispersion which causes affected soils to slough (melt) almost like sugar in the presence of water
(USDA, 1985).
Mine spoils usually have very low shear strengths, and studies have shown that the shear strength of mine spoils is a major controlling factor in their development of erosion. In places where running water etches deep into low shear strength spoils, the sideslopes of the gully will collapse into the void at a higher rate than do high shear strength spoils (USDA, 1985).
Because strip mining usually occurs on hillsides, mine spoils are generally elevated 50 feet to 300 feet above the local stream base level. Due to rapid and turbulent water runoff, steep sideslopes may be undercut causing blocks of mine spoil to shear off or slide into gullies. This process goes unchecked and remains one of the main reasons why erosion rates within the Moxahala Creek watershed are so high.
Sedimentation
Sediment deposition in Moxahala Creek and its adjacent floodplain is a significant visible problem. Strip mining is a leading cause of sediment deposition in stream channels. Because sediment deposition reduces the capacity of these channels, an increase in the frequency and severity of flooding results. Thus, land adjacent to floodplains that was once used for agricultural purposes can now only be used for less intensive purposes. Needless to say, the impact that sedimentation has on landowners is severe. 3 1
The basic cause of sedimentation is the massive erosion of strip mine spoil and deep mine gob piles. Sedimentation adversely affects water quality, mainly through the presence of acid, and secondarily by the presence of mineral sediments themselves. As was the case in regard to erosion, the Moxahala Creek watershed is ranked sixth among those watersheds studied in most sediment deposition. As can be expected, sediment deposition is a direct result of erosion. The Moxahala Creek watershed contains large areas of deposition that are basically sterile due to high acidity content. Most stream systems that are associated with significant areas of deposition are either totally sterile or are marginal for the support of aquatic flora and fauna (USDA, 1985).
Because highwall pits and minor depressional areas are the only traps in mining areas and are filled quickly, the next sediment trap downstream is usually a natural flat section in the lower valley area which may be constricted at its lower end. Areas above road fills which cross the lower valley are usually major depositional areas. Flows within the Moxahala Creek watershed are first restricted after a culvert becomes clogged with sediment, and the sediment laden water backs up in the valley. The sediment source area is usually less than one mile from the major depositional areas. Those sediments that are not trapped near the erosional sources are transported predominantly to the Ohio River, where they must be continuously removed by dredging (USDA, 1995).
Loss of Usefbl Land
For the purpose of the study, a change from cropland, grassland, and/or forest land to either barren land, wetland, pits, or developed land constituted the loss of usefbl land due to mining. The Moxahala Creek watershed has lost over 99% of its croplands,
84% of its grasslands, has had a 16% increase in forest land, and its barren lands have increased from 38 acres to 6377 acres. There has also been an increase in pits from 0 acres to 857 acres (USDA, 1985). As is clearly seen from these numbers, mining is responsible for a huge loss of land in the Moxalrala Creek watershed.
Mine Drainage Pollution
A variable number of water samples were taken in each of the 30 watersheds studied. The number of water samples taken depended on the number of abandoned mines possibly contributing chemical andlor physical pollutants to the streams. Those samples were taken on three separate dates in 1983 (USDA, 1985).
Water quality was assessed to determine the severity of mine drainage pollution in each drainage basin and to also determine the miles of stream affected by mine drainage in each basin. The level of chemical contamination was determined by evaluating levels of the following characteristics: pH, iron, manganese, sulfate, and specific conductivity. Computations for quantitative mine drainage pollution were made using the qualitative data that was collected. This data was then analyzed to determine the miles of each stream that had been chemically and physically contaminated.
The Moxahala Creek watershed was classified as being impacted severely by mine drainage both chemically and physically. The study showed that Moxahala Creek and its tributaries are chemically polluted along 100 of their 166 miles in length. This 33 equates to 60.5% of Moxahala Creek being chemically polluted and makes it the fourth worst among the creeks studied in terms of stream length polluted.
The study also determined that Moxahala Creek and its tributaries contained sedimentation along 82 of their 166 miles. This equates to 49% contamination and ranks
Moxahala Creek second among the watersheds studied in terms of sedimentation.
These numbers are completely understandable, because the Moxahala Creek watershed contains 8,307 acres of land where coal was strip mined and 8,484 acres of land where coal was deep mined (USDA, 1985). These numbers show that approximately 25% of the entire watershed has been mined. They also rank the watershed second and fourth, respectively, in terms of acreage strip mined and deep mined among the watersheds studied. This study has shown that the Moxahala Creek watershed has been severely impacted chemically and physically from the significant amount of mine drainage that has resulted from past surface and underground mining activities within the watershed.
Remediation Techniques
"Upon reaching a stream, AMD alters the chemical balance: it consumes alkalinity, introduces metal ions, and generally degrades its biological activity. If sufficiently severe, AMD will also render the receiving waters unfit for human, agricultural, industrial, or recreational use" (Ziemkiewicz, 1996). Since the harm that
AMD causes to the environment has been discussed, now the focus is on the various remediation techniques that have been employed to eliminate AMD. Many studies and tests that have been conducted using the various methods of control are presented to show the effectiveness of each technique. These are some, not all, of the treatment processes for remediating AMD.
Active Treatment Svstems
Active treatment systems either involve the addition of alkalinity into AMD-laden receiving waters to neutralize their acidity or addressing AMD at its source by implementing man-made methods to reduce its impact on the environment. Various forms of lime are commonly used in active treatment systems and grouting is commonly used to seal mines to prevent formation and seepage of AMD.
Alkaline Additions (Chemical Treatment)
There are countless numbers of alkalis that have been tested as a neutralizing agent of AMD. However, only the more practical and commonly used alkalis are discussed. These alkalis include quicklime, hydrated lime, limestone, and soda ash.
Alkaline addition to AMD is a very effective way to neutralize its acidity. When selecting an alkali to use in treating AMD, its cost, suitability, reactivity, availability, ease of use, and sludge volume should be considered. Each treatment system must consist of an alkali to neutralize the AMD, the oxidation of ferrous iron to the insoluble ferric form, and removal of the resulting metal precipitates by a sedimentation process (Escher,
1983).
Lime is a term that refers to only the burned forms of limestone. The two most commonly used forms of lime in AMD treatment are quicklime and hydrated lime. "More than 90% of all facilities treating acid mine drainage utilize a form of lime"
(Escher, 1983). Quicklime (CaO) is the product of the calcination of limestone. When limestone is burned and carbon dioxide is driven off, calcium oxide (CaO), or quicklime, is produced. To be efficient in neutralizing AMD, quicklime must be slaked, which refers to the combination of varying proportions of water and quicklime to yield a lime slurry. Some of the factors that influence slaking are the quicklime's reactivity, particle size, optimum water amount, water temperature and agitation. The slaking process must be carefblly monitored to ensure efficient neutralization. Quicklime, combined with a good slaking operation, offers a low unit cost per gram of acidity neutralized. Some disadvantages of a quicklime system are the high costs of a slaker and grit remover, the close operational control needed, and the possibility of severe burns (Escher, 1983).
Hydrated lime (Ca(0H)Z) is the most commonly used alkali for neutralizing acid mine drainage in existing treatment plants. It is commonly used when the cost for a slaking system is prohibitive and when lime consumption rates are low. Hydrated lime is much purer than quicklime because most of the impurities are rejected. Most existing
AMD treatment processes use dry lime in a slurry before it is introduced to the contaminated water. Today, however, designers are beginning to feed dry hydrated lime directly to the acid water. This eliminates a slurry feed system. Dry lime feed has been used when the drainage streams are small and mildly acidic. The major advantage that hydrated lime has over quicklime is that a slaker is not needed, which reduces the cost of the treatment system (Escher, 1983). 36
Despite the fact that limestone is available at about 30% of the cost of quicklime and hydrated lime, there are several disadvantages to using limestone to neutralize and treat AMD. To use limestone as a neutralizing agent, certain criteria must be met. An early two-year study by Bituminous Coal Research (BCR) concluded that limestone is only effective when it has a minimum particle size of 0.044mm7a high calcium content, low magnesium content, and a high surface area (Escher, 1983). Finding a limestone that meets all of these criteria can be difficult.
An EPA study by Wilmoth indicates that treating ferrous streams with limestone is possible, but economically undesirable. Due to its slow reactivity and inability to increase the pH above 7.0, longer aeration times are needed. This increases costs by needing a larger aeration unit, and the longer detention times prohibit good settling.
Therefore, a coagulant needs to be added to achieve proper settling (Wilmoth, 1977).
The additional capital investment for enlarged process units and power costs totally invalidates the practicality of the limestone treatment system for high ferrous iron drainages (Escher, 1983). Wilmoth, however, realized that treating ferric iron with limestone was much more economically feasible than treating ferrous iron (Wilmoth,
1977). The fact remains, though, that the use of limestone does not seem to be a very practical or economical method for totally remediating AMD. Despite this fact, a look at the success of using limestone in passive treatment systems is later taken.
Another alkali that is used in the neutralization of AMD is soda ash (Na2C03).
"Due to its high cost of $280/ton and limited availability, soda ash is usually used only for treatment of low-flow drainages that contain little ferrous iron such as would occur in surface mines" (Escher, 1983). Soda ash is produced in a solid pellet form called a prill.
These prills are immersed in a wire basket in the flowing drainage to initiate treatment.
Wilmoth, in conducting a study using soda ash, was able to produce a quality effluent, but the costs were impractical (Wilmoth, 1977). Lovell found that soda ash has only a 56% use-efficiency in treating AMD, which means that twice the theoretical soda ash requirement would be required (Lovell, 1973).
It must be remembered that in most AMD treatment systems, it is extremely important to oxidize any ferrous iron to the ferric form so it can be effectively removed at a lower pH. This is an advantage because ferric iron fblly precipitates around pH 8.0 as opposed to ferrous iron precipitating fblly near pH 12.0. Therefore, less alkali is needed due to the lower pH that need be attained. Methods used to oxidate are aeration, chemical oxidation, and biological systems.
FBC Ash Grouting
Between 1974 and 1977 in Clinton County, PA, a large surface coal mine was mined and then reclaimed. Afler many fish were killed in 1978, acidic discharges from the reclamation backfill were realized. Black shale was believed to be the producer of pyrite and acids. Once the pyrite was located, a method to isolate the pyrite from oxygen and water needed to be devised (Schueck et al., 1996).
A grout that was composed of fluidized bed combustion (FBC) ash and water was used in two differing approaches to isolate the pyrite from water and oxygen. FBC 3 8 ash was chosen primarily because of its pozzolanic (or cementitious) properties as well as for economic reasons. The approach involved pressure injecting the grout into the pyrite-filled pods as a way to surround the pyritic material with a cementitious coating.
Because some of the pods were filled with a clay matrix, they were capped with the grout to isolate the pyrite from any percolating water. Further goals of the grouting were to create low permeability zones and redirect the groundwater flow, reducing its contact with pyrite. The ultimate goal of this project was to improve the quality of the discharges from the buried piles of refuse, thus improving the quality of the receiving streams (Schueck et a]., 1996).
It was found that combining injection grouting with capping produced the best results because this approach inhibits contact between water, oxygen, and pyrite by limiting infiltration as well as diverting lateral flow around the pods. Use of the FBC ash grouting process on this site resulted in an overall improvement in water quality.
Concentrations of the common AMD parameters decreased by 30-40% and reduction of trace was usually higher. All improvements in water quality were assumed to be permanent due to the cementitious nature of the grout. Although the study was not completely successfbl, it was determined that FRC grouting is a good option for sites that meet certain criteria. These sites include reclaimed sites, active surface mines, and refbse disposal sites (Schueck et a]., 1996). The Moxahala Creek watershed would be a good candidate for this technique due to its reclaimed lands and its current active strip mines. Passive Treatment Svstems
The remaining methods of AMD treatment discussed are all passive treatment systems. These passive systems are on the average less expensive due to the use of limited equipment and no monitoring requirement. The methods discussed include wetlands, sulfate reduction by waste organic matter, and anoxic limestone drains.
Sulfate Reduction
Wetland treatment systems (WTS) have been constructed over the past 10 to 15 years for treating AMD. These WTS have had variable success and have been inconsistent in meeting certain effluent limits. The varying degree of success is probably due to the many different types of wetland designs and sizes and the different types of material used to treat the AMD. Although treatment success is variable, all constructed
WTS have, at a minimum, been successhl in reducing chemical costs with AMD treatment and pollutant loading to receiving streams (Hellier, 1996). Due to the large costs of AMD treatment systems, passive treatment methods have become popular in the treatment of waters that are not horribly contaminated by AMD.
The first constructed wetlands project examined is one that incorporates sulfate- reducing bacteria (SRB) in the removal of metal contamination from AMD. The
Burleigh Tunnel in Silver Plume, CO contains very low levels of sulfate (350 mg/L to
550 mgL) that may limit the production of hydrogen sulfide by SRB, which limits metal removal by the system. Therefore, the USEPA set up a subsurface flow system at the site to channel the mine drainage through compost, which has a very high organic content. SRB within the compost produce hydrogen sulfide that reacts with the dissolved metals to form insoluble or slightly soluble metal sulfides. The metal sulfides precipitate and are filtered from the water by the compost (Stalker et al., 1996).
An eight week study was conducted using two continuous flow bioreactors packed with compost to simulate a wetland. The composted mixture contained 96% manure and paper products and 4% hay. Flowrates of the AMD were regulated using pumps to obtain a residence time of between 50 and 100 hours in the bioreactors.
Influent and effluent water samples were taken and analyzed using proper USEPA methods (Stalker et al., 1996).
Sulfate reduction occurs when several species of bacteria obtain metabolic energy by reacting sulfate with simple organic compounds, such as ethanol. They require an anaerobic environment because aerobic bacteria will deplete the amount of organic substrate. If this would occur, the SRB would not be able to utilize the substrate. In general, the SRB produce hydrogen sulfide (H2S) and alkalinity (HC037. The hydrogen sulfide reacts with dissolved iron to precipitate iron sulfide (FeS) or a similar compound
(Schmidt, 1996). Now that this process has been documented, the results of the study can be discussed.
The results of the study show that the compost and hay reactors sufficiently removed zinc, arsenic, cadmium, nickel, and silver. When looking at the removal of zinc and cadmium, there are high removal rates initially (90 to 95%) followed by a severe drop in removal efficiency, followed by a gradual increase in removal. The initial high 41 removal rate occurs due to sorption of the metals to the compost, and once sorption sites are filled, removal efficiency drops. Then SRB gradually become established and the metal removal rates become consistent with the rate of sulfate reduction. Results also show that zinc and cadmium were 99% removed after eight weeks while manganese had a removal near 90% (Stalker et al., 1996).
Measurements of sulfate concentrations in the smaller reactor over the final three weeks of the study showed that sulfate-reduction activity had stabilized, and the bacteria were converting an average 254 mg/l of the 429 mg/l available sulfate or roughly 60%.
Sulfate use in the larger reactor was near 78% between days 29 and 46. These results suggest that sulfate use is a satisfactory indicator of sulfate-reducing activity (Stalker et al, 1996). This study also proves that composted wetlands are an efficient means of reducing metal concentrations in AMD.
Constructed Wetlands
In the case of the abandoned Bark Camp deep mines in Clearfield County, PA, acid mine drainage having a moderate acidity of less than 300 mgll as CaC03 and a moderate iron concentration of less than 30 mg/l indicated that there was a good possibility that constructed wetlands could improve the quality of the degraded stream.
The initial characteristics of the stream before the project began were: pH = 5.5, acidity
= 22 mg/l, ~e'~= 7.1 mg/l, A1 = 2.7 mg/l, Mn = 0.9 mg/l, and SOi = 186 mgll. Median values of the mine discharges, into the stream were as follows: pH = 3.0, acidity = 202 42 md, ~e'?= 22.9 mgA, ~e'~= 0.8 mg/l, A1 = 10.9 mgll, Mn = 2.0 mg/l, and SO1. = 592 mg/l (Hellier, 1996).
Six constructed wetlands were built containing a substrate of 50% horse manure and 50% river gravel. They were designed to achieve uniform flow through the substrate. The results of the 806 day study included an effluent which was alkaline to neutral with a pH near 6.0. Iron and aluminum were both efficiently removed, but effluent manganese was higher than in the influent. However, the performance of the wetland declined after about one year, which can be attributed to the substrate constituents. The goal of this study was to obtain an acidity removal rate within the standard guidelines (5.5 g/day*m2 as CaC03) (Hellier, 1996). As is seen by this example, constructed wetlands are an effective method for remediating AMD with a moderate acidity and iron concentration level.
Anoxic Limestone Drains (ALDs)
Yet another passive treatment for AMD is through the use of anoxic limestone drains (ALDs) to add alkalinity to the mine drainage. The theory of ALDs is quite simple. Acid water is directed through a buried limestone-gravel bed. The dissolution of limestone will raise the pH and add bicarbonate alkalinity to the water, which encourages metals precipitation in a receiving pond or wetland. The anoxic conditions in the limestone bed prevents iron oxidation and limestone armoring. Because limestone is inexpensive and has limited solubility, ALDs may be constructed to last for decades in some cases. However, due to concerns about the armoring of limestone with ferric hydroxide, the plugging of flow paths with aluminum hydroxide, and the limited solubility of calcite, the applications of ALDs are limited. Therefore, because the solubility of limestone in a particular AMD cannot be predicted from mine water chemistry, there is always a danger that exists that the ALD will not generate sufficient alkalinity to completely neutralize the acidic water (Schmidt, 1996).
In an attempt to remove this uncertainty, limestone incubation tests and pilot scale ALD tests were conducted to evaluate the parameters needing assessed in the construction of a 4000 ton ALD in East Central Tennessee. The results of the cubitainer test showed that near-maximum alkalinity was accomplished after the first 48 hours of the test period. Since these results agreed with past research done by the U.S. Bureau of
Mines, it can be assumed that a properly sized and constructed ALD would achieve similar alkalinity. Next, a pilot-scale ALD test was performed to evaluate variable flow conditions. A 65-ton ALD was constructed, containing a control valve in the influent line to adjust the flow rate. The results of this test showed that alkalinity decreased as flow rate increased, which was expected. With an expected maximum flow rate of 8 gpm in the planned ALD, alkalinity concentrations from the pilot test predicted net alkalinity at the flow rate. Thus, these two tests seem to be an effective way to predict the success that the constructed ALD will achieve. Constructing the ALD based on these tests, initial results of the full scale ALD have had similar results to the two small- scale tests (Schmidt, 1996). Summary
Each of these treatment systems has its own applications in certain situations.
Using one method alone will usually not achieve required effluent limits. However, coupling one or more of these systems together can achieve additional acidity and metals removal. The primary application of most passive treatment systems will be on watershed restoration projects, acidic mine lands, and perhaps for pretreatment for active treatment systems using chemicals (Ziemkiewicz, 1996). It seems that the passive treatment systems are more commonly studied in research by colleges due to the lower costs of the systems. It is known that active chemical treatment systems can remediate the AMD, but the challenge remains to find a passive system that can achieve total acidity and metals removal.
Although new mining laws have been passed in recent years to help reduce
AMD, the problem still remains. Chemical treatment systems are very expensive and are difficult to install in most cases. Due to these two factors, the development of passive treatment systems is being researched heavily to attempt to lessen the harm caused to receiving waters by the AMD. With all of the mining activity that has taken place in this country in the past, AMD is not a problem that will soon be solved. Therefore, research efforts will continue to develop the most cost-effective methods to reduce AMD and better the environment. Purpose of Present Research Proiect
As has been mentioned, the effects of mining can have drastic impacts on the environment. The presence of AMD can lead to the degradation of streams and can fbrther cause the inability of biological survival. Most fish need a minimum pH in order to exist, and the addition of AMD into creeks, streams, and lakes in many cases has caused the pH to be below this minimum. The goals needed to restore a stream to make it "fishable" are a water quality of (pH > 6.5, ~a'~> 2 mg/l, alkalinity > 5 mg/l, kJ3
< 5 pg/l, and Fe < 1 mg/l) (Stoertz and Burling, 1996). Water quality requirements for fish survival and reproduction are much more stringent than human drinking water standards (Ohio EPA, 1996). AMD also causes unsightly aesthetic conditions in water bodies such as orange-colored streambeds due to iron precipitation and unpleasant smells due to the presence of sulhr. If severe, the presence of AMD in receiving waters can render them unfit for human, agricultural, industrial, or recreational uses. Therefore, steps must be taken to remediate these contaminated water bodies by identieing where the AMD originates and developing ways to limit its hazardous effects. The first step to doing this is to characterize the contaminated watershed. Once water quality data has been taken, the watershed properties and characteristics can then be analyzed.
Moxahala Creek's water quality suffers mainly due to contamination by AMD.
Thus, a project was undertaken to study its watershed and investigate the extent and causes of its water quality problems. The overall goals of this study are to determine the tributaries contributing the most poor quality water so that a remediation strategy can be 46 developed to target these tributaries and clean up the watershed. Finally, the Andrew
Creek sub-watershed was also sampled for one period to investigate its own water quality problems. CHAPTER I11
FIELD DATA
The monthly data collected was the basis for the analysis of the Moxahala Creek watershed, and it is examined throughout the course of this paper. By viewing the changes in water quality data over the 11 month sampling period, important trends and discoveries within the data could be found. The Andrew Creek sub-watershed was also specifically sampled intensely for one period.
Identification of Flows
The focal point of a watershed characterization is water quality data. In order to obtain data, the most critical flows in the Moxahala Creek watershed needed to be determined. Thirty-two flows were selected. Initially, the watershed was traversed and nearly 50 of Moxahala Creek's tributaries were measured for pH, specific conductivity, and temperature using hand-held probes, and their flowrates were visually estimated. By examining this preliminary data, the 24 most influential tributaries were selected as sampling locations based mainly on the guidelines of highest flows, lowest pH, or highest conductivity. Eight locations along Moxahala Creek were also selected in order to document changes in water quality along its 25 mile length. The 32 numbered sampling locations can be seen in Figure 3. Table 1 gives a description of how to get to each of the 32 sampling locations within the watershed. Locations not selected were of insignificant flow and had satisfactory water quality. The U.S. Department of the Figure 3. Moxahala Creek Watershed Sampling Locations Table 1. Brief Description of How to Get to Each of the 32 Sampling Locations
Location # Directions or Location Description 1 Route 93 North, Right on Lambert Road just south of Avondale,OH 2 Route 93 North, Right on Lambert Road just south of Avondale, OH (Moxahala Creek) 9 Route 93 North, Right on Ceramic Road into Roseville, Left on Marietta Road, Bridge near oil well 10 Route 93 North, Right on Road into Roseville, Near RR Bridge 11 Route 93 North, Right on Road into Roseville, Near RR Bridge (Moxahala Creek) 12 Route 93 North, Right on Lambert Road for about 2.5 miles, Bridge near yard with firewood 14 Route 93 North, Right on Lambert Road for about 2 miles, Bridge at Baughman Rd. Intersection 18 Route 93 North, Left on Ceramic Road, First Bridge 19 Route 93 North, Right on Ceramic Road, Culvert underneath Ceramic Rd. in yard of first house on the left 20 Route 93 North, Right on Ceramic Road for about 1 mile, Near 2 gray buildings 2 1 Route 93 North, Right on Ceramic Road for about 1.5 miles, Near Certified Gas (Burley Run) 22 Route 93 North, Right on Main St. in Crooksville, Left on N. State St., Bridge at Harrison Township Rd. 23 Route 93 North, Right on Main St. in Crooksville, Left on N. State St., 0.25 mile past #22, Near Auto Garage 24 Route 93 North, Right on Road across from Crooksville H.S., Make First Left 0.5 miles at Bridge (Black Fork) 25 Route 93 North about 0.5 mile past Crooksville High School, On right side of road (Moxahala Creek) 26 Route 93 North, Right on Main St. in Crooksville, Right at first Light, 0.25 miles on the left 27 Route 93 North about 1 mile past Crooksville H.S., Cinder Parking Area on Right, Bridge over 93 28 Route 93 North, Large culvert underneath 93 near #25 29 Route 93 North about 0.1 mile past Crooksville High School, Large submerged culvert underneath 93 30 Route 93 North about 1 mile south of Crooksville H.S., Bridge over 93 (McCluney Creek) 3 3 Route 93 North about 0.25 mile south of #30, DafFy Duck 3 5 Route 93 North, Right on Bearfield Township Rd., Bridge (Moxahala Creek) 36 Route 93 North, 0.75 mile past 13,93 intersection, Near Midway Race Track and Driving Range 37 Route 93 North, 0.5 mile past 13,93 intersection, Bridge near open grassy field on left 38 Route 13 Nor* Right at 13,93 intersection, Small culvert near abandoned parking lot on the right 39 Route 13 North, Right at 13,93 intersection, Bridge over Moxahala Creek (Moxahala Creek) 40 Route 13 North, Bridge over 13 just about 0.1 mile south of 13,93 intersection (Bear Creek) 49 Route 13 North for about 2 miles past Moxahala RR tracks, Right on gravel road about 0.2 mile, Culvert 55 Route 13 North just after the Moxahala RR tracks, Walk through open field, Sinking culvert (Moxahala Creek) 56 Route 13 North about 0.1 mile south of Moxahala RR tracks, Bridge (Andrew Creek) 57 Route 13 North, Left on Marietta Rd. in Moxahala, 0.5 miles near softball field (Moxahala Creek) 60 Route 13 North, Left on Marietta Rd. in Moxahala about 5 miles, Source of Moxahala Creek (Moxahala Creek) Interior classifies mine-related drainage as those water sources having a specific
conductivity > 1000 pSIcm @ 25"C, pH < 6 0, and a red or orange staining of the ground or streambed (indicator of large iron concentrations) (Blevins, 1989). These guidelines were followed when selecting the tributaries that would adversely affect
Moxahala Creek's water quality.
Once the 32 sampling locations were chosen, 11 monthly sampling events
occured from April 1997 to February 1998. Water samples fiom tributaries were taken as near to where they entered Moxahala Creek as was possible without being influenced by water fiom Moxahala Creek. Also, pH, specific conductivity, temperature, and flowrates were measured in the field at each sampling location. Most months, all samples and flows were collected on one day, but some months of sample collection spanned three days. However, in those periods, the weather (precipitation) conditions were similar for all days of sampling.
As mentioned, two water samples were taken at each sampling location. One was taken in a one liter cubitainer and the second was taken in a 250 ml HDPE (High
Density Polyethylene) plastic bottle preserved with 5 ml of nitric acid. The nitric acid lowered the pH of the water sample to less than 2.5 so that the dissolved metals would remain in solution prior to lab analysis. Once these two samples were taken in the field, they were immediately placed in coolers on site and transported to Coshocton
Environmental Testing, Inc. in Coshocton, Ohio. At the testing lab, the water samples were tested for acidity, alkalinity, pH,
specific conductivity, TSS, TDS, sulfate, chloride, calcium, magnesium, sodium,
potassium, total iron, manganese, aluminum, and hardness. After testing a certain
sample, the lab technician checked the charge balance error to make sure that it was less than 10%. The EPA methods that were used ta test each analyte are designated by
number and test methods in Table 2 (USEPA, 1983).
Sampling Equipment
Measurements of pH were taken at the various sampling locations with either the
Hanna Instruments pHep 1 or pHep 3 pH meter or the Corning Check-Mate 90 pH meter. All of these probes are accurate to +I- 0.1 pH units. They were all calibrated in pH 4 and pH 7 buffers before each sampling event, and after use, the electrodes were rinsed with water to minimize contamination.
Specific conductivity measurements were made with the Hach conductivityITDS meter, the Corning Check-Mate 90 conductivity meter, the Hanna Instruments DIST-
WP 1, or the Omega CDH-1X TDS probe. The Hach meter is accurate to +1% of the reading while the Omega TDS probe is accurate to 540 mgll. The Hach meter and
DIST-WP 1 could measure from 0 to 2000 pS/cm, while the other two could measure,
in addition, conductivities greater than 2000 pS/cm. The Omega TDS measurements needed to be doubled to obtain the proper conductivity reading in pS/cm. These latter two probes were used to measure samples from the tributaries with the highest
conductivities. All four of these conductivity meters were calibrated before each Table 2. USEPA Test Methods for Various Analytes
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(USEPA, 1983) sampling event with a small screwdriver to turn the calibration trimmer to match the
standard 1413 pS/cm solution.
Flow Measurement Methods
Flowrates were measured at the sampling locations using one of three methods.
Depending on the stream width and depth and the actual volume of the flow, a cutthroat
flume, a pygmy meter, or a bucket and stopwatch was used to determine the flowrate at
each of the locations. Typically, the cutthroat flume was used to measure flows at
sampling locations that were shallow in depth and narrow in width. The pygmy meter
was generally used to measure flows that were deeper and/or wider than those measured
with the flume. Finally, a bucket and stopwatch were used to measure the flow of free- flowing culverts or at locations where a weir was installed. Table 3 shows which method
of flow measurement was used at each sampling location for each month.
Cutthroat Flume
The eight inch throat width cutthroat flume was used at sampling locations in
narrow streams with flows ranging from 75 lpm to 3800 lpm. The 19 inch entrance wing walls on the flume allowed it to be used in streams up to three or four feet in width. The flume needed to be placed in a level position front to back and side to side at a location
in the stream where critical flow through the flume could occur. Once the upstream staff
gauge on the flume was read, it was a simple calculation to arrive at the corresponding
flowrate in the proper units (Bask;, Inc., 1995). Table 3. Flow Measurement Methods for Each Sampling Location for Each Month
P = F'ygmy Meter F = Cutthroat Flume B/S(C) = Bucket & StopwatckiCulvert B/S(W) = Bucket & StopwatchiWeir E = Visual Estimation
NM = No Measurement Taken The cutthroat flume is constructed with a flat horizontal floor and a throat formed by the intersection in plan of a uniformly converging inlet section and a uniformly
diverging outlet section. The cutthroat flume is most accurate when operated in the undrowned mode. This was the case in all measurements taken at the various sampling locations. When undrowned, the flow passes from a subcritical state upstream, through a critical control at some point downstream of the throat, to supercritical flow downstream (Keller, 1984).
When properly installed, the flume is completely level, the channel slope is no greater than I%, and the channel width is 1.5 to 2 times the front width. Once the cutthroat flume was properly installed into the stream channel and undrowned flow occurred, the upstream gauge height (ha) in feet was read from the side of the flume.
This value was then be easily converted to a flowrate (Q) in cubic feet per second (cfs), using the equation:
Q = 4.22 h: (5)
Determining flowrate using the 8 inch cutthroat flume can be seen in the following sample calculation:
ha= 0.15 fi.
Plugging ha into the equation, Q = 4.22 h: = (0.09493'sec
Field tests showed that accuracy in flowrate increases as ha increases.
Pyamy Meter
A pygmy meter was used to determine flowrates for the larger, wider streams,
including the Moxahala Creek locations. The pygmy meter was used to measure the
velocity of streams at certain locations along the stream's cross section. After measuring
the velocity of the stream at specified increments and also measuring the water depth at these measurement points, the velocity-area method was then used to calculate the total flowrate of the stream (ASTM, 1990).
The principal of the velocity-area method consists in effectively and accurately measuring the flow velocity and cross-sectional area of an open channel or stream. The total flow or discharge (Q) measurement is the summation of the products of partial
areas (a) of the flow cross section and their respective average velocities (v). The
equation representing the computation is:
Q = Z (av) (6)
The Price pygmy meter, a rotating-element meter, was used to determine water velocity for each partial section of each stream. The rotor assembly of the pygmy meter
is 2 inches in diameter, and the rotor assembly is formed with six hollow metal cone-
shaped cups. The Price pygmy meter is generally used when the average depth in a stream cross-section is less than 1.5 feet and velocity is below 2.5 feet per second
(ASTM, 1990). Because fairly smooth cross-sections were used and fairly uniform velocity distributions occcurred, a smaller number of partial sections could be measured.
Therefore, a minimum of five partial sections were measured. The larger, wider streams had, on average, near 10 partial areas measured. For more details on pygmy meters and the velocity-area method, the ASTM standards can be consulted (ASTM, 1990).
The pygmy meter can determine how many revolutions the rotor-element makes in 40 seconds. By using headphones that connect to the pygmy meter, the number of revolutions were counted, as a tic noise occurred after each revolution of the rotor. By using the number of revolutions (R) in the following equation, the velocity (V) in feet per second for each partial section can be determined from a table given by the manufacturer or (for our Price pygmy meter) the equation:
V = 0.977 R + 0.028 (7)
Once the velocity is determined and the water depth and width of each partial section is measured, the flowrate (Q) can be determined.
All velocities were measured at a location 60% of the total depth from the stream's bottom, and there was a minimum of five measurement points along each stream's cross section. A computer program, written in conjunction with ASTM standards for open-channel flow measurement of water by velocity-area method, aided in the flow calculations of the larger streams (ASTM, 1990). A sample calculation of flowrate using the velocity-area method can be seen in Figure 4 and the computer program code is listed in Table A. 1 in the Appendix.
Bucket and Stopwatch
The final method used for determining flowrates was the bucket and stopwatch method. This method was used at sampling locations where there was an elevated culvert and thus a free flowing waterfall, which allowed for the collection of flow using a graduated bucket. A bucket was also used to catch the flow from weirs that were installed in certain streams prior to the use of the cutthroat flume. A stopwatch was simply used to determine the time it took to fill the bucket to a certain volume. To minimize human error, at least three trials were performed at each location and averaged to obtain an accurate flowrate. Flowrates were easily calculated since volume and time were known. This is the most reliable method for determining flowrate and it was used whenever it was plausible. Determining flowrate using a bucket and stopwatch is shown in the following sample calculation:
Trial Liters Seconds 1 8.00 5.50 2 7.50 5.14 3 8.00 5.58 Distance from Bank (ft.) Water Depth (ft.) Probe Reading (Rev140sec) 0 - - 1 0.5 32 2 0.5 50 3 0.2 0 4 -
= (0.5 ft.)(l ft.) - (0.5)(0.25 ft.)(0.5 ft.) = 0.4375 A.~ = (0.5 ft.)(l ft.) - (0.5)(0.15 ft.)(0.5 ft.) = 0.4375 ft.2 = (0.2 ft.)(lft.) + (0.5)(0.15 ft.)(0.5 ft.) - (0.5)(0.1 ft.)(0.5 ft.) = 0.2125 fI2
Ql = 0.354 cfs Q2 = 0.578 cfs Q3 = 0.000 cfs
Figure 4. Sample Calculation for Determining Flowrate Using the Velocity-Area Method Water Ouality and Flowrate Data
After water samples were taken at each of the determined locations, they were sent to an environmental testing lab. In the environmental testing lab, the water samples were tested for pH, acidity, alkalinity, specific conductivity, total dissolved solids, sulfate, chloride, calcium, magnesium, sodium, potassium, iron, manganese, aluminum, and hardness as discussed above. Once the water quality data was received back from the testing lab, it was entered into spreadsheets by month. Chemical loads were determined by multiplying flowrate by chemical concentrations for each of the sampling locations and a sample calculation is shown below:
Flowrate = 500 Ipm, Acidity = 100 mg/L
Acid Load = (Flowrate) x (Acidity)
AcidLoad = - (-lo?) ( o$m) (&I (%I [24r1
I Acid Load = 72 kg/& I
Table A.2 through Table A. 12 in the Appendix show the water quality data for
April 1997 through February 1998, respectively. All of the collected data was analyzed to determine the tributaries that adversely affect the water quality of Moxahala Creek and will be discussed in Chapter V. CHAPTER IV
GEOGRAPHIC INFORMATION SYSTEM
A geographic information system (GIs) is a computer-based information system
that enables capture, modelling, manipulating, retrieval, analysis, and presentation of geographically referenced data (Worboys, 1995). A GIs has many uses and has been
used in many different areas, including geography, the environmental sciences, and
computer sciences. In this case, a GIs is used to assist in the characterization of a watershed. By collecting data, digitizing maps, and enhancing these maps, a GIs
accesses and displays data like no other method. A GIs was developed for the
Moxahala Creek watershed and was a valuable tool in examining and analyzing the collected water quality data.
Data Collection and Map Dinitization
The first step to creating a GIs is to collect data that can be used in the system.
The water quality data collected within the Moxahala Creek watershed is the cornerstone
of the GIs, so it is important to take care in collecting data and in entering the data into
spreadsheets. Once the purpose and plan of the GIs has been determined, the map
coverages to be used must be digitized.
A map is the best medium for visually understanding the data that has been
collected. Therefore, a map needs to be digitized so that this medium can be created.
The ARCIINFO program is used to digitize the various coverages (layers) of the map. This program is a command based vector GIs that can be conceptualized as a system
consisting of the user, the software, the map file, and the attribute file. The various
coverages of the map are the watershed boundary, streams, roads, underground mines,
surface mines, lakes, and the sampling point locations. Since the watershed boundary,
roads, streams, and lakes coverages were already created for the Moxahala Creek
watershed by a state organization, only the underground mines, surface mines, and
sampling locations needed to be digitized.
Digitizing is simply using a puck (mouse-type device) to click on an actual map
to create a map on a computer. By creating points, arcs, and polygons with the puck, an
exact replica of a map on paper can be created on a computer. Using U. S.G.S. 7.5 minute quadrangle underground and surface mine maps for the study area, the mine layers and sampling point layer were digitized. Once all errors were corrected, the layers needed to be built to create a topology.
Building Topolom
The ARCIINFO system represents map features by sets of lines and label points and as relationships between connected or adjacent lines and points. The relationships used to represent the connectivity of these features is referred to as topology. Topology explains the highest level of generalization at which geographic features can be stored.
The BUILD command automatically creates and/or updates the map topology stored in
an arc attribute table for a line or polygon coverage. Generally, the BUILD command is used to create a point attribute table (PAT) for a coverage that contains point features, to create an arc attribute table (AAT) for a coverage composed of arcs such as roads or rivers, and to create a polygon topology and a polygon attribute table (PAT) for a coverage such as underground mines. Once all of the coverages are digitized, they are built to create topology so that a certain point, arc, or polygon can be associated with a certain identifier in its attribute table. These attribute tables are later used in connecting these geographic features with the collected water quality data.
ArcView GIs
Another way to view GIs is as a system that contains spatially referenced data that can be analyzed and converted to information for a specific set of purposes. The key feature of a GIs is the analysis of data to produce new information (Antenucci,
1991). Now that the map has been created and all of the data has been collected, these two features need to be combined so that data analysis can produce new information.
The use of ArcView GIs allows for this link of features and creation of new information
(ESRI, 1995).
Once the map is created in ARCIINFO format, it is imported into the ArcView format. Now tabular data, such as dBASE files, can be added into the system so that it can display, query, summarize, and organize the data geographically. The software's true power lies in how easily it enables the user to solve problems by uncovering and analyzing trends and patterns (ESRI, 1996). Examples of maps representing certain queries performed will later be shown, and the process of creating and enhancing these maps will also be discussed. Creating Maps
First, the dBASE file containing all relevant data had to be created. Therefore, the water quality data for each of the 11 months was combined into one large file. The file was then edited so that each sampling location had the same date for each month.
For example, all sampling dates in December were changed to December 11 so that querying by month was easier. Once the Excel file was saved as a dBASE file, it was then added as a table to each particular project. Since this file was the basis for all data analysis, it needed to be added to every project where a query or search was performed.
Next, each of the layers desired to be shown on a map needed to be imported to the project. This was done by adding themes to the project. All of the themes (layers) were saved to the hard drive in some location so they could simply be retrieved from that location and added to the project. Once the themes were added to the project, I was ready to perform analyses on the collected water quality data.
I had the option of showing certain layers on the map while hiding others. By simply showing certain layers, maps of the Moxahala Creek watershed could be created and displayed. Text and legends could be added to each map to hrther describe and enhance it. Figure 3 on p. 48 shows the Moxahala Creek watershed with the numbered sampling locations. It also shows the streams that exist within the watershed. Figure 5 has added the underground mines to the previous map, while Figure 6 shows the watershed and its surface mines. Figure 7 shows both the underground and surface mines on the same map. The roads coverage can be added but does not pertain much to Figure 5. Underground Mines Located Within the Moxahala Creek Watershed Figure 6. Surface Mines Located Within the Moxahala Creek Watershed Figure 7. Both Underground and Surface Mines Located Within the Moxahala Creek Watershed 68 the project. If two layers are active at the same time on a map, the layer that is nearest to the top of the legend overlaps any layer beneath it, and so on. Therefore, the watershed layer was made white in color and was placed at the bottom of the legend when creating each individual map. Now that some basic maps have been created, the data next needs to be integrated with the maps so that the results of various searches and
queries can be seen.
Performing Searches and Queries
The water quality data was associated to the map by linking the dBASE data file with the attribute file of either the streams or the sampling points. Linking them by a common data field allowed each sampling location to be associated with a certain stream
or sampling point on the map. For example, if the data file was linked to the streams attribute file and a query was performed, those streams meeting the criteria given were highlighted within the water quality data file and the associated streams could later be
highlighted on the map. Figure 8 shows a map that has highlighted all streams during the month of August with a pH lower than 4.0. All types of queries can be performed using the data fields within the water quality data file as criteria.
Further editing may be done to Figure 8 so that the highlighted streams can be
shaded with different colors according to various levels of pH. This can be seen in
Figure 9. If the user wants to perform a certain query for a certain month, all streams
during the given month can be shaded according to their various levels of pH, acidity, Figure 8. Streams Having a pH < 4.0 in August 1997 Mst reams
/ 2.8 - 2.9 2.9 - 3.1
/ '\ '\/1' 3.1 - 3.3 3.3 - 3.5 3.5 - 3.7 Mwtshd
Figure 9. Various pH Levels for those Streams Having a pH < 4.0 in August 1997 71 specific conductivity, etc. Also, the sampling points on the map can be highlighted as opposed to having the streams be highlighted. The choices and options are endless.
Finally, if the user simply wants to perform a search for all sampling locations for all months that have a pH less than 3.0 and a specific conductivity greater than 1800 pS/cm, it can be done. However, with this type of search, ArcView GIs only highlights those sampling locations within the data file that meet the criteria. It would be difficult to map this search, because sampling locations could meet the criteria more than once (in different months).
Conclusion
ArcView GIs allows the user to perform any query desired and allows for the creation of a map displaying the results of the query. For the purposes of the Moxahala
Creek watershed characterization project, the GIs will be extremely valuable when devising a restoration plan for the watershed. The water quality data collected is the most extensive and thorough on record, and implementing this data into a GIs provides a very organized means by which to view and analyze the data. ArcView GIs provides a tremendous environment for analyzing and mapping data. The constructed GIs for the
Moxahala Creek watershed will undoubtedly play a major role in deciding why and where a reclamation project shall commence. CHAPTER V
DISCUSS [ON
By analyzing the collected water quality data, the tributaries that contribute the most poor quality water to Moxahala Creek can be determined. By viewing the pH, specific conductivity, and chemical loads of the tributaries and the effects that they have on Moxahala Creek's water quality, this can be done. The averages presented in this chapter are the average values of the 11 monthly sampling events for various water quality characteristics. As was mentioned, sampling occurred from April 1997 to
February 1998.
After viewing flowrate data for each month at all of the sampling locations, there was significant change in the flowrates spatially and temporally so as to suggest that they are primarily influenced by rainfall events. If a sampling location had a relatively constant flowrate each month, then it would likely be dominated by groundwater flow.
However, this was never the case for any locations sampled. The water quality of the main channel, Moxahala Creek, will be discussed followed by that of the most important tributaries to Moxahala Creek.
Moxahala Creek
First, the deterioration of Moxahala Creek's water quality must be documented.
The average pH over the 11 months of sampling of Moxahala Creek at its beginning is above 6.0 and is about 4.5 near its end. Its conductivity also increases from an average 73 of 637 pS/cm up to 1026 pS1cm near its end. These two trends are shown in Figures 10 and 1 1. Figures 12 and 13 also show the large increases in acidity and sulfate concentrations over Moxahala's length. The average monthly data for each of these parameters is shown in Table 4. This actual monthly data is graphed in Figures A. 1 through Figure A.8 in the Appendix. The drastic changes in pH and conductivity from source to mouth are caused by the extremely poor water quality of tributaries flowing into Moxahala Creek. Due to an average of near 100,000 Ipm discharging from
Moxahala Creek, there is a great amount of poor quality water flowing from Moxahala
Creek into the Muskingum River and thus polluting it. Therefore, the investigation aims to find the tributaries causing most of this contamination.
Andrew Creek
It is very interesting to view the drastic change in pH, specific conductivity, acidity, and sulfate concentration between sampling locations #57 and #55 on Moxahala
Creek. As can be seen on the map in Figure 3 on p. 48, location #57 is located 4.8 miles from Moxahala Creek's source and location #55 is one mile downstream from location
#57. From Table 5, it can be seen that pH drops an average of 2.02 units from #57 to
#55. Specific conductivity also increases an average of 71 1 pS/cm between the two points, as evidenced in Table 6. The reason for these drastic changes is that Andrew
Creek (location #56) flows into Moxahala Creek just upstream of location #55.
Underground and surface mine maps (Figures 5 and 6 on pp. 65 and 66) show that there was significant mining done in the Andrew Creek watershed in the past (USGS, 1985).
80
Table 5. Effect of Andrew Creek on Moxahala Creek's pH
PH #57 #56 #55 April 6.31 3.38 4.24 May 5.16 2.7 3.14 June 5.87 3.11 3.54 July 6.21 2.8 3.4 August 5.18 3.11 3.4 September 6.3 3.7 3.8 October 5.39 2.94 3.14 November 6.48 4.27 4.08 December 4.9 3.3 3.8 January 5.5 3.53 4.23 February 5.96 3.75 4.1 . Table 6. Effect of Andrew Creek on Moxahala Creek's Specific Conductivity
Specific Conductivity (uS/cm) #57 #56 #55 April 80.1 1968 1170 May 1045 2300 1564 June 600 2000 1432 July 942 2240 1840 August 726 1405 1378 September 890 2170 1930 October 976 2480 2260 November 1125 2370 1952 December 1170 2040 13 12 January 508 1860 1210 February 754 1989 1404
Table 7. Water Budget for the Confluence of Andrew Creek and Moxahala Creek
L Flowrate (Ipm) #57 #56 #55 May 24,100 12,100 39,100 June 1C1,OOO 14,000 23,600 July 3440 7000 16,200 October 1520 5400 7370 November 3020 7000 10,100 December 29,100 8720 44,170 January 19,100 15,400 34,100 February 16,300 12,700 32,400 8 1
Andrew Creek has an average pH of 3.3, specific conductivity of 2070 pS/cm, and an average flowrate of 10,300 lpm where it enters Moxahala Creek. Looking at Table 7, it is noted that Andrew Creek increases Moxahala Creek's flow by an average of approximately 80%. The flows listed in this table do not add up perfectly due to some human error in flow measurement but mainly due to other minor contributions to
Moxahala Creek from small streams between locations #57 and #55.
McCluney Creek
In viewing the monthly data collected, another poor quality tributary of significant flow is McCluney Creek (location #30 in Figure 3 on p. 48). Underground and surface mine maps (Figures 5 and 6 on pp. 65 and 66) once again show that there was considerable mining done in the vicinity of location #30 (USGS, 1985). The average pH of McCluney Creek is 3.2 and its average specific conductivity is near 1475 uS/cm. Combining this data with an average flowrate of 9800 lpm, McCluney Creek has a significant acid load that impacts Moxahala Creek. Because Moxahala Creek's water is already of poor quality where McCluney enters, McCluney Creek does not have the drastic effect that Andrew Creek has on it. Looking back at Figures 10 through 13 on pp. 74-77, McCluney Creek enters at the 11.6 mile mark on Moxahala Creek and does not seem to adversely affect Moxahala's water quality. However, this is due to the fact that Andrew Creek has contaminated Moxahala Creek so badly. If Andrew Creek were to be cleaned up, the effect of McCluney Creek on Moxahala Creek would be much more noticeable. The chemical loads that McCluney Creek is contributing to Moxahala 82
Creek will be discussed later in this paper and will better demonstrate the pollution that it is causing to Moxahala Creek.
Black Fork
Finally, there is a tributary of significant flow that actually increases the pH of
Moxahala Creek. Black Fork (location #24 in Figure 3 on p. 48) enters Moxahala Creek at the 13.4 mile mark and increases its flow by an average of about 50%. Once again,
Figures 10 through 13 on pp. 74-77 show that Black Fork noticeably increases Moxahala
Creek's pH and lowers its acidity and specific conductivity. Table 8 shows these changes by displaying data for locations #25 and #11 on Moxahala Creek and for Black
Fork (#24). Due to Black Fork, Moxahala Creek's pH increases by an average of 0.46 units, its specific conductivity decreases by an average of 232 pS/cm, and its acidity decreases by an average of 26 mg/l. Because Moxahala Creek has increased in average flow to about 45,000 lpm at location #25, these beneficial changes in characteristics are significant.
Now that the three tributaries of highest flowrate and most significant impact have been examined at a glance, an in-depth look at how the chemical loadings of all of the tributaries affecting Moxahala Creek will be taken.
Chemical Loading Analysis
The tributaries most detrimental to Moxahala Creek's water quality are those contributing the largest chemical loads. As contaminated streams flow into larger streams, dilution occurs making the water less toxic. However, natural chemical and Table 8. Average Effect of Black Fork on Specified Water Quality Characteristics of Moxahala Creek
#25 #24 #11 PH 3.77 5.72 4.23 Sp. Cond. (uS/cm) 1325 784 1093 Acidity (mg/l) 73 -4 47 Sulfate (mg/l) 1044 533 563 Flowrate (lpm) 45,300 23,400 106,000 biological reactions cause some neutralization of the acidity and the precipitation of metals (Skousen, 1995).
The 24 tributaries of Moxahala Creek that have the greatest impact on Moxahala
Creek were sampled each month from April 1997 to February 1998. The acid, sulfate, and metal loadings that each tributary contributes to Moxahala Creek for each month were examined. April data was not used due to incomplete flowrate measurements.
Aciditv
Acidity is a measurement of the amount of base needed to neutralize a volume of water. For AMD, acidity usually includes hydrogen ion concentration (low pH) but more importantly, also includes mineral acidity which arises from the presence of many dissolved metals in the water. However, when dealing with AMD from coal mines in the eastern United States, the use of pH, iron, aluminum, and manganese usually accounts for the majority of the acidity (Hedin et al., 1988).
Acid loading involves more than simply the acidity concentration of a tributary.
It is determined by multiplying the acidity concentration (mg/l) of the tributary by its flowrate (Ipm) to obtain a loading (kg/day). Thus, a tributary of extremely high acidity concentration and very low flow is not going to have the same effect on Moxahala Creek as a tributary of lesser acidity concentration and a high flow. So an analysis of the acid loads of each of the 24 tributaries for each month shall pinpoint the main polluters of
Moxahala Creek. Table 9 shows the acid loads of the sampled tributaries for May through
September. From this table, it is obvious that the three main contributors of acid load to
Moxahala Creek are locations #30, #40, and #56. These three tributaries account for an average of 80% of all of the acid loaded into Moxahala Creek, with Andrew Creek (#56) alone accounting for an average of 50%. It is interesting to note that if all of the acidity in these three streams were neutralized, the alkalinity from some of the other tributaries, mainly Black Fork, would reduce the remaining acid load so that an average of 85% of all of the acid loaded into Moxahala Creek would be eliminated. This is a very high number considering that only three of 24 tributaries would need to be treated.
Sulfate
A similar analysis is performed on the sulfate loads of the tributaries. In the ground, sulfate sulhr is usually only found in fresh coal and is commonly the result of weathering and recent oxidation of sulfide sulhr. As seen in equations (1) and (2) on p.
8, sulfate is a reaction product of pyrite oxidation. AMD is commonly neutralized naturally by carbonate rocks or neutral-to-alkaline receiving streams, and most metals will precipitate out of solution. However, carbonate neutralization does not change the concentration of sulfate; thus sulfate is a reliable indicator of mine drainage (Toler,
1980). Further, the Moxahala Creek watershed is dominated by sandstone, rather than limestone bedrock. Sandstone often contains a small fraction of pyrite and itself can be a contributor to AMD.
As is seen in Table 10, locations #30, #40, and #56 are the three main sulfate contributors to Moxahala Creek. However, location #24 (Black Fork) also contributes a tremendous amount of sulfate to Moxahala Creek. These four tributaries account for an average of 78% of all of the sulfate entering Moxahala Creek. Andrew Creek alone accounts for 27%. Ironically, despite Black Fork's high sulfate load, its contribution actually reduces the sulfate concentration of Moxahala Creek. There are a few other locations, such as #18, #2 1, and #37 that have substantial sulfate loads, but the four named previously are the main contributors.
Metal Loads (Fe. Al, and Mn)
In viewing the metal loads for the tributaries of Moxahala Creek, the same tributaries as previously mentioned are the major contributors. Andrew Creek once again contains the highest loads of iron, aluminum, and manganese. Black Fork has the second highest iron load of the four but has the lowest aluminum and manganese loads.
The fact that Black Fork has such a high iron load and such a low acidity is evidence that there is probably some type of alkaline treatment upstream. It also shows that the hydrogen ion controls pH, not dissolved metals concentrations. Tables 1 1, 12, and 13 show that these four tributaries account for an average of 92% of the iron load, 77% of the aluminum load, and 75% of the manganese load. Andrew Creek alone accounts for
64%, 42%, and 38%, respectively.
Aluminum is the metal that most deters aquatic life. It appears that aluminum concentrations above 0.005 mg/l may cause toxic stress to fish (Brocksen et a]., 1992).
92
Toxicity of acid and aluminum appear to be caused by a disruption of the ion balance in fish gills, resulting in suffocation (McDonald, 1983). Increasing the pH of the four major tributaries could reduce the aluminum concentrations to acceptable values by allowing for precipitation and removal of metals.
As was mentioned earlier, these three metals along with pH account for most of the acidity caused by mining in the eastern United States. All of the analyses performed point to Andrew Creek (#56), Bear Creek (#40), McCluney Creek (#30), and Black
Fork (#24) as the main sources of acidity, sulfate, iron, aluminum, and manganese.
Water Quality Predictions
In order to determine whether cleaning up Andrew Creek, Bear Creek,
McCluney Creek, and Black Fork would improve Moxahala Creek's water quality enough to support aquatic life, various calculations need to be performed.
Methods for Prediction
First, iron and aluminum concentrations in Moxahala Creek must be able to be predicted if the iron and aluminum concentrations in the aforementioned tributaries are set equal to 0 mg/l. Therefore, the assumption that all of the tributaries sampled account for all of the iron and aluminum in Moxahala Creek was made. To account for
Moxahala Creek waters before the first tributary, Andrew Creek, enters, location #57 on
Moxahala Creek was also considered a tributary and included in the calculations.
To prove that these assumptions were valid, the average iron and aluminum concentrations of the tributaries sampled were compared to the average iron and aluminum concentrations measured in Moxahala Creek over its final 20 miles. If the average tributary concentration values were similar to the average concentration values measured in Moxahala Creek, then the assumptions made would be valid.
To determine the average iron and aluminum concentrations of the tributaries, the total iron and aluminum loads of the tributaries were divided by the total flow of the tributaries for each month. The results of these calculations are seen in Table 14. The average iron and aluminum concentrations of all of the tributaries were 13.85 mg/l and
5.72 mg/l, respectively. These values compare closely to the average iron concentration of 15.30 mg/l and average aluminum concentration of 5.9 1 mg/l of Moxahala Creek over its final 20 miles. These values along with the average concentration values at each sampling location along Moxahala Creek are shown in Table 15. Because the calculated concentration values of the tributaries are very similar to the actual concentration values measured in Moxahala Creek, setting the iron and aluminum concentrations of Andrew
Creek, Bear Creek, McCluney Creek, and Black Fork equal to 0 mg/l should give an accurate prediction of how Moxahala Creek's water quality would change if these tributaries were to be completely remediated.
Prediction Results
By calculating total iron and aluminum loads of the tributaries less those of the four previously mentioned and then still dividing these values by the total flowrate of all of the tributaries, a new average iron and aluminum concentration was determined for the tributaries and, thus, Moxahala Creek. Table 16 shows the iron and aluminum loads
Table 15. Average Iron and Aluminum Concentrations of Moxahala Creek
Location Iron Concentration Aluminum Concentration @gill (mgil) #5 5 34.00 8.65 #3 9 18.20 6.06 #3 5 14.73 5.67 #25 14.10 6.04 #11 6.19 4.26 #2 4.63 4.80 7
Average Iron Concentration = 15.30 mg/l Average Aluminum Concentration = 5.9 1 mgil Table 16. Average Iron and Aluminum Concentrations of all Tributaries to Moxahala Creek After Complete Hypothetical Restoration of Andrew Creek, Bear Creek, McCluney Creek, and Black Fork
Month Total Flow Total Iron Load of Avg. Iron Conc. Total Aluminum Load Avg. Aluminum Conc. of Tributaries (lpm) Tributaries (kglday) of Tributaries (mgll) of Tributaries (kglday) of Tributaries (mgll) May 209,838 364.5 1.21 478.3 1.58 June 104,942 246.9 1.63 NIA NIA J~Y 46,425 68.6 1.03 45.1 0.67 August 13 1,443 45.5 0.24 59.3 0.3 1 September 48,000 71 1.03 102.6 1.48 October 51,533 43.9 0.59 90.5 1.22 November 30,065 78.2 1.81 95.3 2.20 December 203,457 1164 3.97 271.1 0.93 January 157,570 982 4.33 209.9 0.93 February 154,637 1562 7.01 309.5 1.39
I Avg. Iron Concentration = 2.27 mgli I Avg. Aluminum Concentration = 1.19 mg/i I 97 of the tributaries when the concentration of the four stated tributaries was set equal to 0 mgl. It also shows the predicted concentrations of Moxahala Creek if these four tributaries were restored.
Table 16 shows that the average iron concentration of Moxahala Creek would decrease from 13.85 mg/l to 2.27 mg/l and its average aluminum concentration would decrease from 5.72 mg/l to 1.19 mgll. Although these values would still not allow for aquatic survival in Moxahala Creek, its water quality would be much improved.
Nevertheless, all of the tributaries restored could support aquatic life, and Moxahala
Creek's waters could now be used for human, industrial, agricultural, or recreational purposes. It is possible that if these tributaries were overtreated, the water quality conditions of Moxahala Creek may improve enough to support aquatic life. Also, direct treatment of Moxahala Creek itself or of any other influential tributaries would also hrther improve Moxahala Creek's water quality. Even if Moxahala Creek is not recoverable in terms of allowing for aquatic survival, its waters would still become usefbl if Andrew Creek, Bear Creek, McCluney Creek, and Black Fork were all improved.
Despite a predicted 84% decrease in iron concentration and a 79% decrease in aluminum concentration in Moxahala Creek due to improving the four tributaries, more restoration would be needed to make the creek "fishable." The only way to be sure of these results, though, is to restore the tributaries and then sample Moxahala Creek and note the changes that have occurred. Finally, the amount of money that is willing to be 98 spent on a restoration project will ultimately determine whether or not Moxahala Creek can be completely recovered and become a "fishable" creek.
Andrew Creek Project
A project was proposed in November, 1996 to collect water quality data for the
Unnamed Tributary (UT) of Moxahala Creek in Perry County, Ohio. The Ohio
Department of Natural Resources (ODNR) was hnding Ohio University to conduct a complete watershed characterization for the UT to Moxahala Creek. Since the UT of
Moxahala Creek is its name on maps, we decided to name the tributary Andrew Creek.
A previous project involving a water quality study done on Howard Williams Lake
(HWL),which discharges into Andrew Creek, showed the overall pH of the lake to be near 3.0 (Edwards et a]., 1996). Having been a reservoir for significant coal washing operations, Howard Williams Lake became very acidic due to the underground, strip, and auger mining performed in its watershed (Edwards and Grube, 1995). Within the
HWL watershed, blasting and subsequent removal of the overburden to expose and remove the coal resulted in the pyritic sandstone and shale overburden materials being highly mixed (Edwards et al., 1998). Prior to embarking on the Moxahala Creek watershed investigation, the Andrew Creek tributary was studied to determine whether it is contaminated solely by HWL or also by acid mine drainage from the many underground mines and strip mines in its watershed.
On March 30, 1996, very preliminary pH and conductivity were taken at 12 points near Andrew Creek. These preliminary points can be seen in Figure 14, along
100 with the surface and underground mines within the watershed. A significant number of poor quality drainages into Andrew Creek were found along with a few good quality drainages. This preliminary study showed the need for further investigation. It was obvious that acid mine drainage was negatively impacting the water quality of the UT to
Moxahala Creek.
Data Collection and Water Sampling
The Andrew Creek study began in earnest in late November of 1996. The four square mile watershed was walked over to get a general lay of the land and to identify all seeps and flows that contribute to Andrew Creek. Field data was taken at nearly 100 locations throughout the watershed. The parameters of pH, conductivity, and water temperature were measured and recorded at each of the points. Low pH values were found at Andrew Creek locations and at many of the tributaries that flow into the creek.
Of all of the points sampled, the 40 most critical locations were specified so that monthly sampling of them could begin as soon as possible. On February 8, 1997, water samples were taken at each of the 40 locations and the flowrates of most of the streams or seeps were also measured. If a pond was sampled, a flowrate was not able to be taken. Once the water samples were analyzed for various chemical concentrations and other characteristics, these chemical concentrations were multiplied by the flowrate to obtain the various chemical loadings contributed by each tributary. Flow Measurement Methods
Various methods were used to determine flowrates at the locations throughout the watershed. If the stream flow was not too large and the stream was not too wide, man-made dams were constructed to measure the flowrate. Sandbags were first filled with mud and then placed in the stream to dam the flow. A round plastic pipe was then placed between the sandbags so that all of the water flowed through the pipe. If the flow was too large for just one pipe, additional pipes were added as needed. Once the dam construction was complete, a bucket and stopwatch were used to determine the flowrate.
At locations where culverts were not submerged, a bucket was simply placed under the culvert to catch the flow. A stopwatch was used to determine flowrates. If the flow out of the culvert was too large to catch in one bucket, wooden pieces were clamped to the culvert to divert the flow into multiple smaller flows. Adding the flowrates together resulted in the total flow at the location.
A final method of determining flowrates in the larger streams and creeks was by using a pygmy meter. Once all of the flowrates were determined and all of the water samples were taken, the results of the water quality analysis performed at the environmental testing lab needed to be studied to determine where the tributaries that most adversely affect Andrew Creek's water quality were located. The Andrew Creek watershed water quality data for samples taken in February 1997 can be seen in Table
A. 13 in the Appendix. Water Ouality Data Analvsis
First, sulfate loadings will be examined. In looking at the data, a maximum loading of 3767 kilograms (kg) of sulfate per day was measured at point #96 on the north side of Andrew Creek, seen in Figure 15. All sampling locations are shown in
Figure 15. There was also a large iron loading here of 378 kg/day, a pH of 3.6, and a total acidity loading of about 11,900 kg/day. The flowrate at point #96 was 1762 lpm.
Another poor quality tributary was at location #105, located to the north of
Andrew Creek. It had a flowrate of 553 Ipm, a sulfate loading of 2150 kg/day, an iron loading of 430 kg/day, and a pH of 4.1. Two other poor quality tributaries were #59 and
#62, both located to the north of Andrew Creek near a past strip mining site. Location
#59 had a large flow of 1206 Ipm, a pH of 4.1, and it contributed 2060 kg of sulfate per day and nearly 350 kg of iron per day to Andrew Creek. Location #62 had a flow of 333
Ipm, a pH of 3.6, and it contributed 1480 kg of sulfate per day and nearly 380 kg of iron per day to Andrew Creek. This water had the highest iron concentration at 790 mg/L and also the highest sulfate concentration at 3080 mg/l. Water at location #62 flows into tributaries at locations #I04 and #107, which also have high conductivities and sulfate concentrations.
All of the flowrates at the various locations were not able to be measured, so some significant flows do not show up in the data and cannot be analyzed. A truly comprehensive study would include actual flowrates of the Andrew Creek locations.
Nonetheless, the poor quality tributaries can be determined as targets for any hture restoration project to improve Andrew Creek's water quality.
The tributaries at locations #59, #62, #96, and #lo5 were by far the worst quality waters in regard to chemical loading contributions to Andrew Creek. Since water from location #62 flows into water at point #105, a considerable improvement in Andrew
Creek's water quality could probably be made by improving only three tributaries.
However, because there was groundwater seeping into Andrew Creek and also some contaminated surface flow tributaries of less significance, cleaning up only these three tributaries would not entirely solve the problem.
There were some other flows contributing to Andrew Creek's poor quality. The tributary at location #40 was an interesting point in that it had a pH of 7.0 yet contributed 33.2 kg of iron per day into Andrew Creek. The water from location #50 was also a heavy contributor of iron at 62 kg /day and a sulfate load of 690 kg/day.
As mentioned earlier, there are only three tributaries contributing sulfate and iron heavily into Andrew Creek. Contributions from other flows may be noteworthy, but they are not significant when compared to these three chemical loadings. Therefore, the restoration and cleanup of these three tributaries should have a significant impact on enhancing Andrew Creek's poor water quality.
Andrew Creek's water quality at its beginning at point #53 had a pH of 3.7, a specific conductivity of 1139 pS/cm, an iron load of 23 kg/day, and a sulfate load of 61 kg/day. At location #2 near the end of Andrew Creek where it flows into Moxahala Creek, it had a pH of 3.2, a specific conductivity of 1600 pS/cm, an iron load of 61 kg/day, and a sulfate load of 813 kg/day. From these numbers, it is clear that the tributaries along Andrew Creek are adversely affecting its quality. Restoring the three tributaries mentioned and also implementing the Howard Williams Lake restoration plan proposed by Ohio University would greatly improve the overall quality of Andrew Creek and, therefore, Moxahala Creek. CHAPTER VI
CONCLUSIONS
The main goal of this watershed study was to determine the tributaries of
Moxahala Creek that most adversely affect the creek's water quality. Once they are
identified, a remediation strategy can be devised and implemented to improve the water
quality of these tributaries and, thus, also improve the water quality of Moxahala Creek.
The water quality characteristics of Moxahala Creek are presently not conducive to fish
survival. As can be seen from Table 17, the conditions of Moxahala Creek over the final
80% of its length are nowhere near where they need to be to support aquatic life.
Average characteristics of Moxahala Creek over its remaining length after Andrew Creek enters are pH = 3.9, alkalinity = 0 mg/l, iron = 15.30 mg/l, and u3= 5.91 mgll.
Therefore, its water quality must be drastically improved to meet the aquatic standards of pH > 6.5, alkalinity = 0 mg/l, iron < 1 mgll, and < 0.005 mg/l. An improved
Moxahala Creek would also be beneficial for human, agricultural, industrial, or recreational purposes.
It is clear that Andrew Creek (#56), Bear Creek (#40), McCluney Creek (#30), and Black Fork (#24) need to be addressed in a restoration plan and treated in order to
greatly improve the water quality of Moxahala Creek over its entire length. A treatment
scheme should be planned based on the highest chemical loads, which usually occur
during high flow. The precipitation and removal of the dissolved metals in the tributaries Table 17. Average Water Quality Characteristics of Moxahala Creek Over its Final 20 Miles (after junction with Andrew Creek) - Location PH Alkalinity Iron Aluminum (mg/l) (mg/l) (ma) #5 5 3.71 0 34.00 8.65 #3 9 3.90 0 18.20 6.06 #3 5 3.82 0 14.73 5.67 #25 3.92 0 14.10 6.04 #11 4.25 0 6.19 4.26 #2 4.50 0 4.63 4.80 are important in reducing acidity and in improving water quality. Overtreating these
tributaries might boost Moxahala Creek's overall pH to obtain the proper alkaline
conditions needed for aquatic life. Even though Black Fork is of such high flow and
does presently have an average pH of 5.72, it should be treated to remove its dissolved
metals. Because Black Fork is already of decent water quality and has such a high flow,
a small amount of alkaline treatment would be needed to hrther improve the creek.
Thus, Black Fork would be a good tributary to treat to help improve Moxahala Creek's
water quality over its final 12 miles. If considerable treatment is implemented at
Andrew, Bear and McCluney Creeks, the water quality of Moxahala Creek will be
greatly improved and maybe someday be able to support aquatic life. These three tributaries account for the majority of the acidity, sulfate, and metal loaded into
Moxahala Creek and should be the main focus of a complete restoration project.
Since Andrew Creek is by far the tributary contributing the most water of poor
quality into Moxahala Creek, it should be the first tributary to be treated. Because
Andrew Creek enters Moxahala Creek only five miles downstream of its source, it is
contaminating the final 80% of the creek. Cleaning up Andrew Creek should be the first
phase of a remediation plan for improving Moxahala Creek. Once Andrew Creek is
improved, hrther water sampling of Moxahala Creek over the final 20 miles of its length
should be performed to determine the effects that the cleanup had on its water quality.
The effects should be very noticeable. 109
Once the changes in Moxahala Creek's water quality are noted, it should then be determined whether or not to implement a second phase of the remediation plan. It should involve improving McCluney Creek's water quality. After this, if need be, Bear
Creek should also be remediated. Once these three tributaries are of good water quality, the improvement in Moxahala Creek's water quality should be great. As mentioned before, treatment of Black Fork will also hrther improve Moxahala Creek, since it increases Moxahala Creek's flow by about 50%. If all of these actions are performed, there is little doubt that Moxahala Creek's water quality will be drastically improved.
Although the predictions made in the last chapter state that Moxahala Creek will still not be able to support aquatic life due to its average aluminum concentration of 1.19 mg/l and average iron concentration of 2.27 mg/l, the creek will still be able to be used for other purposes previously mentioned. Do not forget that all four creeks that were improved would be able to support aquatic life and also be used for other purposes.
For those conducting similar watershed studies in the future, being organized before the first sampling event is very important. We did not know which flow measuring devices we needed to use at each of the sampling locations for the first sampling event, and thus, did not have complete flowrate data for the first month. We also did not start using the cutthroat flume until the third month of sampling. Using the flume instead of installing weirs into the streambed made it much easier to measure the smaller flows and saved us valuable time and hard work. It is also good to remember to have backup probes when sampling, because batteries can go dead out in the field. Finally, make sure that the lids to the sample bottles containing the nitric acid are screwed on tightly when they are received from the test lab. If they are not, the bottles can leak nitric acid, which can cause severe burns to the skin.
Further possible research involving the Moxahala Creek watershed would be to actually design treatment alternatives for improving the watershed. Different schemes may need to be implemented at the various tributaries. Intensive sampling of each of the tributaries would need to be done to determine the most appropriate method for cleaning each of them up. Once this work is done, those tributaries treated and maybe Moxahala
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PROGRAM FLOW
* Defining types of variable values REAL VELOC,Vl,V2,V3,V4,V5,V6,V7,V8,V9,V10,Vll,Vl2,Vl3,Vl4,Vl5, + dl,d2,d3,d4,d5,d6,d7,d8,d9,dl0,dll,d12,d13,d14,d15, + tflow,tflowl,W,a,b,c INTEGER NRl,NR2,NR3,NR4,NRS,NR6,NR7,NR8,NR9,- 1,NR12,NR13, + NR14,NR15,R * Inputing the distance between two pygmy pooints (~nax.15 values) WRITE (*,26) 26 FORMAT(///,lX,'ENTER THE SEGMENT LENGTH (in feet)',F4.2) READ (*,*) W * Inputing the depth of the stream (max. 15 values) WRITE (*,30) 30 FORMAT(//, 1X,'ENTER THE WATER DEPTH (in feet) - total 15 points! ! ! +', 15F5.3) READ (*,*) dl,d2,d3,d4,d5,d6,d7,d8,d9,d10,dll,d12,dl3,dl4,dl5 * Inputing the number of revolutions (max. 15 points) WRITE(*,35) 35 FORMAT(//,lX,'ENTER the # OF REVOLUTIONS (per 40 seconds) - total +15 points! !!', 1513) READ (*,*) NRl,NR2,NR3,NR4,NRS,NR6,NR7,NR8,NR9,~11,NR12, + NR13,NR14,NR15 * Inputing the file: table of velocities = f(revo1utions) - "PYGMY" OPEN (UNIT = 1, FILE = 'pygmy.TXT', STATUS = 'OLD') * Defining Vn for given NRn 42 IF (.NOT. EOF(1)) THEN READ (1,44) R, WLOC 44 FORMAT (13,F5.3) IF (NRl .EQ. R) THEN Vl=VELOC* 1 END IF IF (NR2 .EQ. R) THEN V2=VELOC*1 END IF IF (NR3 .EQ. R)THEN V3=VELOC*1 END IF IF (NR4.EQ. R) THEN V4=vELOC*1 END IF IF (NR5 .EQ. R) THEN VS=VELOC*1 END IF IF (NR6 .EQ. R) THEN V6=VELOC*1 END IF IF (NR7.EQ. R) THEN V7=vELOC*1 END IF IF (NR8.EQ. R) THEN V8=VELOC*l END IF IF (NR9.EQ. R) THEN V9=VELOC*1 END IF IF (NR10 .EQ. R)THEN V10=VELOC*1 END IF IF (NR11 .EQ. R)THEN v1 l=VELOC*1 END IF IF (NR12.EQ. R) THEN V12=vELOC*1 END IF IF (NR13.EQ. R)THEN V13=VELOC*l END IF IF (NR14.EQ. R) THEN V14=vELOC*1 END IF IF (NR1.5.EQ. R)THEN V15=vELOC*l END IF GOT0 42 END IF * Calculation of the total flow a=W*dl*Vl+W*d2*V2+W*d3*V3+W*d4*V4+W*d5*V5+W*d6*V6+W*d7*~7 b=W*d8*V8+W*d9*V9+W*dlO*VlO+W*dll*Vl l+W*dl2*Vl2 c=W*d13*V13+W*d14*V14+W*d15*V15 tflow=a+b+c tflowl=tilow*448.831 WRITE (*, 100) Mow WRITE (*, 102) tflow 1 100 FORMAT(N,'****************************',2X'E=',F10.3,1X,'(cfs
+)I) 102 FORMAT(/,'*****************************'9 2X'EOW =',F10.2,1X,'(gpm) +'I STOP END
+November December +January
Miles
Figure A. 5. Moxahala Creek pH (October 1997 through February 1998) / -b December /
Figure A.6. Moxahala Creek Specific Conductivity (October 1997 through February 1998)