harry kessels msc thesis proposal 7574252 final dec … kessels_… · adaptive management...

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University of Ottawa

Faculty of Graduate and Post-‐Doctoral Studies

Systems Science Program

MSc. Thesis Proposal

Adaptive Management Strategies

In Canada’s Boreal Ecosystem Systems Modelling Applications in Wildfire Management and Hydrofracturing

Student 7574252

Henricus Kessels

Thesis Supervisor: Dr. Daniel E. Lane

Telfer School of Management – University of Ottawa

Thesis Co-‐Supervisor: Dr. Richard H. Moll

Telfer School of Management, University of Ottawa

December 2014

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Abstract

There is growing recognition of the importance of preserving Canada’s boreal ecosystems. The boreal region is Canada’s largest ecoregion, covering 58.5 percent of the country, or 584 million square kilometers from Yukon Territory to Newfoundland. Canada has the second-‐largest area of boreal forests, after Russia. It contains ninety percent of Canada’s remaining large intact forest and approximately a quarter of the world’s remaining large intact forests (Lee, 2004.) Canadian ecosystems and communities have been subject to increasing risks rising from natural and man-‐made hazards. These trends are notable in increased frequency and severity of natural disasters and extreme weather patterns (The Pembina Institute and Canada’s Boreal Initiative, 2005.) Community profiles were quantified in two rural areas in western Canada in order to assess their vulnerability to specific natural and man-‐made hazards. The objectives of this proposed thesis research are to:

1. Describe community profiles and ecoregions with special reference to economic, environmental, social and cultural components.

2. Analyze geographical data to quantifying the probability distribution of hazards caused by wildfires and hydrofracturing activities.

3. Simulate disaster scenarios to assess the impact and opportunity cost of various adaptive management strategies. Provide tools and recommendations for employing economic, environmental, social and cultural capital to reduce risk.

Results of this proposed thesis research can be used to improve capabilities in using existing data to derive specific capital deployment strategies to reduce risks.

Keywords: geographic information systems, geo-‐statistics, hydrofracturing, adaptive management strategies, simulation modelling, spatial data modelling, wildfire management

Adaptive Management Strategies in Canada’s Boreal Ecosystem MSc Thesis Proposal

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Glossary of Terms, Acronyms and Symbols The following section itemizes common abbreviations found in the writing of this document. AAC Annually Allowable Cut CERT Community Emergency Response Team CNFDB The Canadian National Fire Database (CNFDB) – Fire Point and Polygon Data is a

collection of forest fire locations and fire perimeters as provided by Canadian fire management agencies including provinces, territories, and Parks Canada.

DFA Defined Forest Area DPI Disaster Preparedness Index EMBC Emergency Management British Columbia EPA Environmental Protection Agency ESRI Environmental Systems Research Institute FERP Federal Emergency Response Plan FEMA Federal Emergency Management Agency FREP Forest and Range Evaluation Program, led by led by the B.C. Ministry of Forests, Lands

and Natural Resource Operations (FLNRO), in collaboration with the Ministry of Environment (MOE).

FSI Fire Susceptibility Index FLNRO Ministry of Forests, Lands and Natural Resource Operations FPI Fire Potential Index: a moisture-‐based vegetation flammability indicator. It is a function

of current living vegetation greenness as a proportion of maximum greenness, and current 10-‐h dead fuel moisture as a proportion of the moisture of extinction. The FPI is calculated for different areas and time periods by the Wildland Fire Assessment System (WFAS) for the continental U.S.

LUF Land Use Framework MOE Ministry of Environment NGO Non-‐governmental Organization PAG Public Advisory Group SD System Dynamics SDM Spatial Data Modeller SDEV Standard Deviation SFRM Sustainable Forest Management Plan TSA Timber Supply Area UN/ISDR United Nations International Strategy for Disaster Reduction UNESCO United Nations Education, Science and Cultural Organization WFAS Wildland Fire Assessment System


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Table of Contents

Abstract .................................................................................................................................... 2

Glossary of Terms, Acronyms and Symbols ............................................................................... 3

List of Figures ........................................................................................................................... 6

List of Tables ............................................................................................................................. 7

1. Introduction .......................................................................................................................... 8 1.1 Background and Motivation .................................................................................................. 8 1.2 Research questions ............................................................................................................. 10 1.3 Research objectives ............................................................................................................ 10 1.4 Proposal outline .................................................................................................................. 11

2. Literature Review ............................................................................................................... 12 2.1 Resource management levels in forestry .................................................................................. 12 2.2 Wildfire adaptive management strategies ................................................................................ 13 2.3 Hydrofracturing: process and challenges .................................................................................. 18 2.4 Hydrofracturing Adaptive Management Strategies in the Upper Athabasca Region .................. 21 2.5 Software Applications for Geographic Analysis and Modelling .................................................. 25

2.5.1 Introduction .............................................................................................................................. 25 2.5.2 ArcGIS ....................................................................................................................................... 25 2.5.3 R Software ................................................................................................................................ 25

3. Methodology ...................................................................................................................... 27 3.1 Introduction ............................................................................................................................. 27 3.2 Data Requirements in the Nechako Lakes District ..................................................................... 27 3.3 Data Requirements in the Upper Athabasca Watershed and Yellowhead County ..................... 29 3.4 Research Process ...................................................................................................................... 30

4. Expected Analysis and Results ............................................................................................ 32 4.1 Community Profiling ................................................................................................................. 32

4.2 Simulation Modelling ................................................................................................................... 34 4.2.1 Baseline case ............................................................................................................................. 34 4.2.2 Simulation scenarios and impacts ............................................................................................ 34 4.2.3 Alternative adaptive strategies and impacts ............................................................................ 34 4.2.4 Compare, contrast and rank strategies .................................................................................... 34

5. Discussion ........................................................................................................................... 36 5.1 Data availability ....................................................................................................................... 36 5.2 Sensitivity Analysis ................................................................................................................... 36 5.3 Ranking Procedure and Decision Support ................................................................................. 36 5.4 Policy Implications for Adaptive Management .......................................................................... 36


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6. Conclusions and Recommendations .................................................................................... 36

7. Proposed Research Project Plan and Timeline ..................................................................... 37

Bibliography ........................................................................................................................... 40


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List of Figures

FIGURE 2.1 REGIONAL AND DISTRICT BOUNDARIES AND OFFICES IN B.C. 15 FIGURE 2.2 NATURAL RESOURCE DISTRICTS IN B.C. 16 FIGURE 2.3 ELECTORAL DISTRICTS OF BRITISH COLUMBIA: NECHAKO LAKES DISTRICT 17 FIGURE 2.4 NORTHERN INTERIOR FOREST REGION, B.C. 18 FIGURE 2.5 TYPICAL COMPOSITION OF FRACTURING FLUID (ADAPTED FROM ARTHUR ET AL, 2009) 19 FIGURE 2.6 ILLUSTRATION OF A HORIZONTAL WELL SHOWING THE WATER LIFECYCLE IN HYDROFRACTURING 21 FIGURE 2.7 MUNICIPALITIES IN THE UPPER ATHABASCA WATERSHED. 23 FIGURE 3.1 HIGH-‐LEVEL RESEARCH PROCESS 30 FIGURE 3.2 PROCESS DIAGRAM FOR DERIVING BURN PROBABILITY IN THE NECHAKO LAKES DISTRICT 31 FIGURE 4.1 WILDFIRE HISTORY (1917-‐2013) IN NECHAKO LAKES ELECTORAL DISTRICT. 35 FIGURE 6.1 DETAILED DESCRIPTION OF PROPOSED RESEARCH PROJECT PLAN. 38 FIGURE 6.2 TIMELINE AND GANTT CHART OF ACTIVITIES 39


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List of Tables

TABLE 2.1 ADAPTIVE MANAGEMENT STRATEGIES ADDRESSING WILDFIRE HAZARDS .............................................. 14 TABLE 2.2 ADAPTIVE MANAGEMENT STRATEGIES ADDRESSING HYDROFRACTURING HAZARDS ............................. 24 TABLE 3.1 DATA REQUIREMENTS FOR THE NECHAKO LAKES DISTRICT ...................................................................... 27 TABLE 3.2 CANADIAN NATIONAL FIRE DATABASE SELECTION ................................................................................... 28 TABLE 3.3 CANADIAN NATIONAL FIRE DATABASE SELECTION ................................................................................... 29 TABLE 4.1 COMMUNITY DATA PROFILE ITEMS (BEIGZADEH, 2014; HARTT, 2011; LANE AND WATSON, 2011) ........ 32 TABLE 4.2 COMMUNITY PROFILES OF NECHAKO LAKES (B.C.) AND YELLOWHEAD COUNTY (ALBERTA) ................... 33


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1. Introduction

1.1 Background and Motivation There is growing recognition of the importance of preserving Canada’s boreal ecosystems. The boreal region is Canada’s largest ecoregion, covering 58.5 percent of the country, or 5.8 million square kilometers stretching from Yukon Territory to Newfoundland. Canada has the second-‐largest area of boreal forests, after Russia. It contains ninety percent of Canada’s remaining large intact forest and approximately a quarter of the world’s remaining large intact forests (Lee, 2004.) Canadian ecosystems and communities have been subject to increasing risks rising from natural and man-‐made hazards. These trends are notable in increased frequency and severity of natural disasters and extreme weather patterns (The Pembina Institute and Canada’s Boreal Initiative, 2005.) Climate change is likely to have a major impact on wildfire activity across Canada. While the trend is clear and well accepted, there is uncertainty about the rate and duration of change, in part because these factors depend on future emissions scenarios. On average, wildfire threatens about 20 communities and 70,000 people annually in Canada, and fire management costs Canada about $700 million a year. Both the area burned and costs will rise as a result of climate change. In British Columbia, fire records show that the wildfire season has been increasing in length by one to two days a year since at least 1980 (BC Ministry of Forests and Range Wildfire Management Branch, 2009.)

In recent years, especially British Columbia has been subject to increased wildfire activity. The 2003 wildfire season in British Columbia for example, was particularly dramatic. More than 2500 wildfires caused unprecedented damage to homes, business and public infrastructure. As a result of these so-‐called firestorms, three pilots lost their lives, 334 homes and businesses were destroyed and 4500 people were evacuated from their homes. The total cost of these fires was estimated at $ 700 million (Filmon, 2003, Richardson, 2003.)

The recent development of shale gas extraction has been met with significant public and political debate over the potential effects, which the hydrofracturing (also referred to as “hydrofracturing”) process may have on the subsurface. During the hydraulic stimulation process, hydraulic fracture paths have traditionally been difficult to predict due to their complex interaction with the natural fracturing of surrounding formations. It is this uncertainty, which has led to concern that hydrofracturing may create preferential pathways for hydraulic fluid migration to conductive faults and aquifers, and in turn generate unforeseen seismic activity or impact on quality and quantity of subsurface water reservoirs (Cottrell and Kaniewska, 2013.)


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Recent scientific studies from the U.S. EPA and the Energy Institute at the University of Texas appear to have reached opposite conclusions on whether hydrofracturing events themselves cause groundwater contamination. However, a careful review reveals that both reports appear to indicate that hydrofracturing at relatively shallow depths may increase the risk of contamination of public drinking water supplies.

Proponents of hydrofracturing emphasize safety due to the large vertical separation of impermeable rock between the zone that is being hydraulically fractured and the public drinking water supply aquifer. The extensive distance between the aquifer and development zone, often in multiple thousands of feet, are said to result in little or no risk of contamination of potable aquifers used by the public. Opponents of hydrofracturing argue that the practice is not safe and that it is a risk to public supplies of drinking water. Reliance often is made on detections of chemicals alleged to be associated with shale development or anecdotal reports of decreases in water quality.

The reports recently issued by the EPA and the Energy Institute at the University of Texas indicate that the depth at which the hydrofracturing is conducted and its vertical separation from the fresh water aquifers are important risk factors related to the ultimate question of whether hydrofracturing is a risk to the public water supply. While the EPA may be perceived to be more aggressive in terms of detecting environmental issues, the Energy Institute’s study may be viewed by many as a more impartial assessment of the underlying concern over water supply impacts (DiGiulio et al, 2011.)

Various adaptive management strategies for hydrofracturing activities have been reviewed. Dusseault et al (2014) quantify the risks of wellbore leakage and provide recommendations for long-‐term wellbore integrity. With an ever-‐expanding scale of exploitation, growing environmental concerns have invariably pointed to the need for further quantitative research on the risks associated with these activities (Saba et al, 2011; US EPA, 2008.)


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1.2 Research questions

The main focus of this research is to increase our understanding and improve existing adaptive

management strategies in dealing with natural and man-‐made hazards faced by Canadian

communities.

The research questions are:

1. What are the characteristics of an effective risk management framework in view of protecting Canada’s boreal ecosystem and its communities from hazards caused by wildfires and hydrofracturing activities?

2. How can risk management strategies be evaluated and ranked to enhance protection of these rural communities from above-‐mentioned hazards?

1.3 Research objectives

The research objectives, each covered by a chapter in this proposed thesis, are as following: 1. Perform a literature review on wildfire management in British Columbia and watershed

management in Alberta. Explain the concepts and methodology of hydrofracturing applications. Review software applications in geographic information systems and geo-‐statistics.

2. Describe community profiles and ecoregions with special reference to economic, environmental, social and cultural components.

3. Analyze geographical data to quantify the probability distribution of hazards caused by wildfires and hydrofracturing activities.

4. Simulate disaster scenarios to assess the impact and opportunity cost of various adaptive management strategies. Provide tools and recommendations for evaluating the impact on economic, environmental, social and cultural capital toward improving protection opportunities for rural communities.


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1.4 Proposal outline

The topics in this proposed thesis have been arranged as follows including a brief description of chapter contents:

Chapter 1. Introduction. Provide background information on wildfire management and watershed monitoring in

Canada. Motivate the undertaking of this study.

Chapter 2. Literature Review Perform a literature review on wildfire management in British Columbia and watershed management in Alberta. Explain the concepts and methodology of hydrofracturing applications. Review software applications in geographic information systems and geo-‐statistics.

Chapter 3. Methodology Outline of research methodology. Describe community profiles and ecoregions with special reference to economic, environmental, social and cultural components. Assess specific rural communities in British Columbia and Alberta in terms of their vulnerability to incidents caused by respectively wildfires and hydrofracturing.

Chapter 4. Expected Analysis and Results Analyze geographical data to quantify the probability distribution of hazards caused by wildfires and hydrofracturing activities. Simulate disaster scenarios to assess the impact and opportunity cost of various adaptive management strategies. Establish a Baseline Case, validated by historical data. Generate different controllable and uncontrollable simulation scenarios and impacts. Simulate, evaluate and compare alternative adaptive strategies and their impact. Compare, contrast and rank adaptive management strategies. Provide tools and recommendations for employing economic, environmental, social and cultural capital to reduce risk.

Chapter 5. Discussion Discuss the research outcomes. Data availability. Sensitivity Analysis. Ranking Procedure

and Decision Support. Policy Implications for Adaptive Management

Chapter 6. Conclusions and recommendations Provide a summary of conclusions along with policy recommendations for future work.

Timeline and Project Plan Provide a timeline and project plan of the scheduled activities as part of this research.


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2. Literature Review

2.1 Resource management levels in forestry

In business, military and government planning, a critical distinction is often made between strategic, tactical and operational resource planning. Strategic planning involves the long-‐term vision and mission of an entity, where tactical planning deals with the actual steps needed to achieve that vision. Operational planning regulates the day-‐to-‐day output relative to schedules, specifications, and costs (Mintzberg and Quinn, 1996; Boundless, 2006)

In forestry management, strategic planning is conducted to facilitate decisions on forestry within legislative and policy constraints (Martell et al, 1998; Gunn, 1991; Gunn, 2004; Gunn, 2007.) The time window for strategic planning in forestry is partially dependent on the rotational cycle of the forest. Strategic forest planning is generally concerned with macro-‐level investment decisions such as mill capacity, spraying and infrastructure (Moll, 1991.) Planning windows of up to 100 years have been commonly used (Andersson, 2005.)

In tactical planning, the purpose is to schedule harvest operations to specific areas and on a finer time scale than for strategic planning. Tactical planning occurs at the stand level with the coordination of silvicultural activities such as cutting, thinning and planting. The tactical planning model enables measurement of the impact of local investment decisions associated with these silvicultural activities (Martell et al., 1998; Moll, 1991; Weintraub et al, 1985.)

At the tactical and operational level, a multitude of scientific endeavours has been undertaken Remote sensing techniques to compute ignition probabilities and compare fire risk across ecoregions (Dasgupta et al., 2005.) A so-‐called Fire Susceptibility Index (FSI) was demonstrated to be a good estimator of fire risk, when using fuel moisture and fuel temperature as inputs and validating the results with the Fire Potential Index (FPI). The FSI has also been modelled and linked to pre-‐emptive measures enabling land managers to reduce the likelihood that an area will be burned by wildfire (Beverly et al., 2009.) Their research results demonstrate the complexity of factors determining fire susceptibility. Modelled fire susceptibility was high affected by fuel composition and –arrangement as well as topography. In prioritizing and evaluating strategic fuel management strategies require an understanding of variations in weather and local topography. Their simulations demonstrated the effective use of prescribed fire treatments to reduce forest fire susceptibility.

A qualitative review of the community impacts of wildfire was undertaken by Krishnaswamy, Simmons, & Joseph (2011.) Human impacts were categorized between social, health and safety, social or cultural and between short-‐term and long-‐term.


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When dividing planning into distinct levels, discrepancies between the alignment of strategic and tactical plans may occur. In decision support models, solutions at one level may be inconsistent with the results of another level. When moving from the strategic plan to the tactical plan, three sources of inconsistencies are often present; spatial discrepancies, temporal discrepancies and discrepancies due to different levels of constraint. Depending on the cause, various approaches can be taken to deal with such discrepancies (Andersson, 2005.)

A responsive, evolving natural resource system requires adaptive management strategies that influence, and are influenced by, systems dynamics. Mathematical modelling methodologies have been applied to deal with the complexities of forest management (Moll, 1991.)In order to provide accuracy and insight, decision support models and adaptive management strategies in response to wildfires must be considered at the respective levels of forest management and planning. The scope of this research project is limited to strategic methods related to adaptive management for both wildfire-‐ and hydraulic fracturing.

2.2 Wildfire adaptive management strategies

Wildfire plays a vital role in the conservation of biodiversity of various ecosystems. In order to optimize planning, resource management in fire-‐prone ecosystems requires an understanding of wildfire behaviour and a viable approach to evaluating burn probability. Management strategies have been described in a number of studies (Keane et al, 2014; Parisien et al., 2005.)

The following wildfire management methods have been applied or considered (Daust and Morgan, 2011; Blonski et al, 2002.)

1. Control human access during high hazard times. 2. Reduce post-‐harvest fuels. 3. Create natural fire breaks to increase chance of future fire containment. 4. Provide more and better fire-‐suppression equipment on site. 5. Improve access for fire suppression. 6. Structural enhancement of defensible spaces. 7. Prescribed burning. 8. Change harvesting regimes for trees and vegetation. 9. Use herbivores for fuel management. 10. Enhance biodiversity. 11. Improve forest health. 12. Provision of insurance policies (public or governmental).


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These methods can be applied within the constraints of forest cover requirements, designated wildlife habitat areas and protected areas such as national and provincial parks (BC Ministry of Forests and Range, 2006/2007/2008/2009.)

Table 2.1 summarizes and classifies the adaptive management strategies addressing wildfire hazards.

Table 2.1 Adaptive Management Strategies addressing Wildfire Hazards Risk Adaptive Management Strategy

Classification

Strategic Tactical Operational Risk of human accidents or fatalities. Loss of property, livelihood, quality of life.

Control human access during high hazard times 1) ü ü Reduce post-‐harvest fuels 1) ü ü Create natural fire breaks to increase chance of future fire containment 1) 2)

ü ü

Provide more and better fire-‐suppression equipment on site 1) 2)

ü ü ü

Improve access for fire suppression 1) ü ü ü Structurally enhance defensible spaces 1) 2) ü ü ü Prescribed burning 1) ü ü ü Change harvesting regimes for trees and vegetation 2)

ü ü ü

Use herbivores for fuel management 2) ü ü ü Enhance biodiversity 2) ü ü Improve Forest Health 1) 2) ü ü ü Provision of insurance policies (public or governmental) 2)

ü ü

Source: 1) Blonski et al, 2002 2) Daust and Morgan, 2011

Figure 2.1 shows the regional and district boundaries and offices of the Ministry of Forestry, Lands and Natural Resources Operations in British Columbia. Figure 2.2 is a map of Forest Districts in British Columbia, Canada. The Nechako Lakes Electoral District covers the following five forest districts either partially or entirely, as displayed in Figures 2.3 and 2.5:

• Nadina Resource District • Skeena Stikine Natural Resource District • North Island – Central Coast Natural Resource District • Fort St. James Natural Resource District • Vanderhoof Natural Resource District

The Nadina Natural Resource District is the largest area within the Nechako Lakes District, and consists of the Morice and Nechako Lakes Timber Supply Areas (TSA.) These TSA’s are two of thirteen TSAs comprising the Northern Interior Forest Region which in turn is one of three designated forest regions in British Columbia, as shown in Figure 2.4. Lying along the western edge of British Columbia's Interior Plateau, the 1.12-‐million-‐hectare Nechako Lakes TSA


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includes the communities of Burns Lake and Grassy Plains. The slightly larger Morice TSA covers 1.5 million hectares, immediately northwest of the Lakes TSA. Its major communities include Houston, Granisle, and Topley. The topography of the area is rolling and gentle to the north and east, and more mountainous in the southwest. Both timber supply areas are bordered by Tweedsmuir Provincial Park to the south, and are covered by a number of water bodies: three major rivers—Bulkley, Morice, and Nadina—and three major lakes: Babine, in the north (the longest and largest freshwater lake in British Columbia), and Francois and Ootsa lakes (part of the Nechako Reservoir) in the south.

Figure 2.1 Regional and District boundaries and offices in B.C.


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Figure 2.2 Natural Resource Districts in B.C.


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Figure 2.3 Electoral Districts of British Columbia: Nechako Lakes District


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Figure 2.4 Northern Interior Forest Region, B.C.

2.3 Hydrofracturing: process and challenges

Hydrofracturing (also called ‘fracking’) has been applied since 1947 when it was first performed experimentally. The first commercial application followed in 1949. As of 2012, 2.5 million hydrofracturing operations had been performed worldwide on oil and gas wells; over one million of those within the U.S. (King, 2012; IEA, 2012.)

Hydrofracturing is a stimulation operation in which fluids are pumped at sufficiently high pressure through a well casing to create new fractures in rock or to open existing natural fractures in low permeability formations, so that greater volumes of oil or natural gas can be produced. This technique has led to the development of unconventional gas reservoirs and reassessment of the recoverable reserves of natural gas. In the process of hydrofracturing, sand or tiny ceramic spheres are mixed with a viscous fluid to form a sand-‐fluid mixture called a ‘slurry.’ This slurry is pumped into the gas-‐bearing formation, with the slurry fluid pressure increased until the pressure overcomes the weight of the earth above the formation and the strength of the rock formation. This results in rock cracking or fracturing. Once the rock is fractured, the slurry pressure is reduced so that the gas in the rock can flow through the newly-‐formed fractures and back into the well.

The weight of the earth above the rock formations tends to cause the fractures to close up. The purpose of the sand or minute ceramic spheres is to “prop” the fracture open so that gas can continue flowing through the fracture; thus, the sand or spheres are referred to as ‘proppants.’ After fracturing, large quantities of hydrofracturing fluid containing residual chemicals are recovered, handled, and disposed. There are several alternatives for handling these flow back hydrofracturing fluids: local subsurface disposal, offsite disposal, or reuse. While reusing fluids


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may be attractive to reduce the total volume of fluids needed, these fluids eventually will need to be disposed.

Hydrofracturing is highly controversial, with proponents stressing the economic benefits of readily accessible hydrocarbons, while opponents are more concerned about contamination of ground water, depletion of fresh water, degradation of air quality, increased probability of earthquakes, noise pollution, surface pollution and the consequential risks to health and the environment (Hillard Huntington et al., 2013.)

Typical hydrofracturing and flow-‐back slurry is about 99% water and sand/micro-‐spheres, as shown schematically in Figure 2.5 (Arthur et al., 2009.)

Figure 2.5 Typical composition of fracturing fluid (Adapted from Arthur et al, 2009)

The remainder of the mixture consists of additives. The functional types of additives and their purposes include the following (Halliburton 2011): • Gelling agents and cross-‐linkers, which provide viscosity to the water to carry the

proppants. Example chemicals include guar gum (liquid thickener). In some cases and because of operational needs and cost reduction considerations related to the cost of transportation of gelling agents to a hydrofracturing site, diesel fuel is mixed with the gelling agent instead of water (U.S. EPA 2004).

• Breakers and friction reducers to release the proppants after fracturing and reduce viscosity to enhance flow back.

• Potassium chloride (KCl) to stabilize any clay in the formation. • Acids (such as hydrochloric acid, acetic anhydride or acetic acid) to clean up residual cement

and other debris in the perforations and around the well. • Biocides to prevent bacterial corrosion.


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• Scale inhibitors, like ammonium chloride, prevent scale and particulate buildup that may plug fractures.

• Corrosion inhibitors such as propargyl alcohol and methanol to prevent general corrosion of wellbore casing and tubing.

• Oil, gas, and water from drilling and production operations may also contain naturally occurring radioactive materials in production waters, called “NORM”. NORM contains the element radium, a radioactive decay product of naturally occurring uranium and thorium.

The volume of water and other fluids used in a horizontal fracture job is extremely high, as illustrated in Figure 2.4 (EPA, 2011.) Because these large volumes are injected into the ground, there is a public concern for contact with drinking water supplies and other environmental media. Releases of hydrofracturing fluids from holding ponds and the resulting groundwater contamination have supported citizen concerns about hydrofracturing operations and the risk of exposure to chemicals that might be present in some fluids (e.g., Plagianos 2010). Because the U.S. Environmental Protection Agency (EPA) classifies benzene as a human carcinogen, exposure to BTEX compounds (benzene, toluene, ethyl benzene, and xylenes) is of particular concern (ATSDR 2007). In addition, the radioactive materials that may be contained in hydrofracturing fluids have been reported to increase the risk of cancers (U.S. EPA 2011). Along with the potential risks associated with transport and exposure to hydrofracturing fluids at the surface, drilling operations and well construction design came under scrutiny as potential causes of subsurface migration of natural gas from deeper formations to shallower drinking water aquifers and residential water wells.


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Figure 2.6 Illustration of a horizontal well showing the water lifecycle in hydrofracturing (Source: EPA, 2014)

Hydrofracturing is under international scrutiny, restricted in some countries, and banned altogether in others. Some countries have repealed bans on hydrofracturing in favour of regulation. The European Union is drafting regulations that would permit controlled application of hydrofracturing (European Union, 2014.)

2.4 Hydrofracturing Adaptive Management Strategies in the Upper Athabasca Region

Alberta has used hydrofracturing for oil and gas recovery since the 1950s, many of which are smaller conventional fractures (Environment Alberta, 2013.) Since then, approximately 174,000 wells have been drilled using the technology. The Alberta government has proactively tracked water use for oil and gas development since the 1970s. The increasing use of brackish/saline groundwater resources should be carefully studied and managed given the potential for brackish water to be used in the future for drinking water. Withdrawals of brackish groundwater can also adversely impact interconnected freshwater resources (Environment Alberta, 2013.)


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The Government of Alberta has established seven land-‐use regions and is developing a regional plan for each region (Land Use Secretariat, 2010.) As set out in the provincial Land-‐use Framework, the regional boundaries are based upon aquifers and adjusted to align with municipal boundaries. Regional plans will integrate provincial policies at the regional level, set out regional land-‐use objectives and provide the context for future land-‐use decisions reflecting the goals and priorities of the region within a provincial policy context. Municipalities and provincial departments and agencies will be required to comply with the directions in the regional plan in their decision-‐making once the plan is completed (Government of Alberta, 2008.)

The Athabasca River watershed within Alberta is approximately 159,000 square kilometers, covering approximately 24% of Alberta (Natural Regions Committee, 2006.) It drains all precipitation into the Athabasca River which ends up in Lake Athabasca which is connected downstream to the Arctic Ocean. The confluence of the Athabasca River watershed and Peace River watershed into Lake Athabasca forms the Peace-‐Athabasca delta. This delta is one of the world’s ecologically significant wetlands and is designated as a World Heritage Site by the United Nations Education, Scientific and Cultural Organization (UNESCO) (Pavelsky and Smith, 2009.)

Figure 2.7 shows the Integrated Regional Plan Boundaries of Alberta. It also displays the 11 municipalities, counties and districts within the Upper Athabasca watershed. Table 2.2 summarizes adaptive management strategies addressing hydrofracturing hazards, categorized at strategic, tactical and operational levels.


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Figure 2.7 Municipalities in the Upper Athabasca watershed.


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Table 2.2 Adaptive Management Strategies addressing hydrofracturing hazards Risk Adaptive management Strategy Classification

Strategic Tactical Operational Public non-‐ or disinformation, lack of awareness and education,

Public disclosure of all chemicals used in fracturing

ü ü

Scientific research, training and extension

ü ü

Wellbore stress cracking and corrosion failures in gas environments

Well-‐designed and implemented cement jobs around wellbores. Selection of casing, tubing, and completion equipment materials

ü ü

Use of tight threaded gas connections to prevent seepage of either gas or fracturing fluids

ü ü

Using cement bond logs to check the quality of the cement job

ü ü

Control of the pumping rate of fluids. ü ü Careful formation rock characterization and testing, geological characterization and logging of the region under development

ü

Modeling of the fracture geometry ü Change the fracturing method to reduce the amount of wastewater

ü ü

Distribution of carcinogenic and radio-‐active substances from gas extraction by hydrofracturing, into the environment.

Moratorium on Hydrofracturing ü Regulate the injection of diesel fuels and other materials as part of the hydrofracturing process

ü ü

Increase borehole depth ü ü Treatment of radium-‐contaminated wastes

ü ü

Waste material disposition and migration into the environment

Impose restrictions on how and where hydrofracturing waste is disposed

ü ü

Waste treatment and disposal control. Treat produced water down to a maximum allowed concentration of total dissolved solids

ü ü

Ecosystem monitoring, damage prevention and control

Carbon and hydrogen isotope analysis. ü ü


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2.5 Software Applications for Geographic Analysis and Modelling

2.5.1 Introduction The first known use of the term ‘geographic information system’ was by the Canadian scientist Roger Tomlinson in the year 1968 (Tomlinson, 1962.) The term describes an information system used to integrate, store, edit, analyze and share geographic information. Geographic information science is the science underlying geographic concepts, applications, and systems (Goodchild, 2010.)

2.5.2 ArcGIS

ArcGIS is a geographic information system (GIS) software developed by the Environmental Systems Research Institute (ESRI) based in Redlands, California, U.S.A. It is a scalable system used for discovering, analyzing, creating, compiling and sharing geographic information. Maps and geographic information is used in a range of applications and managed in a relational database. The software provides an infrastructure for making maps and geographic information available throughout an organization, across a community, and openly on the Web. The product is available as a server-‐based product, or can be run on a desktop, laptop or PDA.

Extensions are available and can be installed in the form of Toolsets. One example of a Toolset is Spatial Data Modeller (SDM). This is a collection of geo-‐processing tools for adding categorical maps with interval, ordinal, or ratio scale maps to produce a predictive map of where something of interest is likely to occur. The tools include the data-‐driven methods of Weights of Evidence, Logistic Regression, neural network methods, and categorical tools for a knowledge-‐driven method Fuzzy Logic. These categorical fuzzification tools complement the early SDM Fuzzy Logic tools. All of the tools have help files that include references to publications discussing the applications of the methods implemented in the tool. Several of the tools create output rasters, tables, or files. New additions also include step-‐by-‐step tutorials, innovative validation tools and new modelling tools, including the Self Organizing Map (SOM) neural net, Support Vector Machine and Genetic Algorithms (Sawatzky et al., 2008.)

2.5.3 R Software

R is a free software environment for statistical computing and graphics. It is an integrated suite of software facilities for data manipulation, calculation and graphical display. R compiles and runs on a wide variety of platforms. It is a language and environment for statistical computing and graphics. It provides a wide variety of statistical and graphical techniques, and is highly extensible. One of R's strengths is the ease with which well-‐designed publication-‐quality plots can be produced, including mathematical symbols and formulae where needed. Great care has


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been taken over the defaults for the minor design choices in graphics, but the user retains full control. R is available as Free Software in source form. It includes:

• an effective data handling and storage facility, • a suite of operators for calculations on arrays, in particular matrices. • a large, coherent, integrated collection of intermediate tools for data analysis. • graphical facilities for data analysis and display either on-‐screen or on hardcopy, and • a well-‐developed, simple and effective programming language which includes

conditionals, loops, user-‐defined recursive functions and input and output facilities.

R can be characterized as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software. It has been designed around a true computer language and allows users to add functionality by defining new functions. R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.


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3. Methodology

3.1 Introduction

In this chapter, the data requirements for the areas in scope are defined, followed by the modelling methodology. Paragraphs 3.2 and 3.3 provide details on the datasets and GIS-‐files covering respectively the Nechako Lakes District (B.C.) and the Upper Athabasca Region (Alberta.) These datasets and GIS-‐files form the inputs for the research activities and modelling cycles described in paragraph 3.3.

These data were obtained from various public sources as indicated. Spatial layers in these maps were available as Environmental Systems Research Institute (ESRI) shapefiles, point files and rasters to support detailed analyses and geo-‐referenced mapping. They enable geo-‐statistical analysis and modelling using various spatial toolsets available as part of the ESRI-‐software.

3.2 Data Requirements in the Nechako Lakes District

Table 3.1 lists the data requirements for the Nechako Lakes Districts in this study. The national fire database is a major and essential reference in deriving predictive factors to be applied in the simulation modelling cycles. The main criterion in the data selection process is that the data must reflect ecological and/or community elements that are either affected by, or controlled in various adaptive strategies in scope for our research (see Table 2.1.) Some of the data can be used for predictive purposes using methods such as logistic regression and so-‐called ‘weights of evidence’ in Spatial Data Modeller in ArcGIS. These elements include water bodies, land use data, cadastral information, elevation, climatological data and topography.

Table 3.1 Data requirements for the Nechako Lakes District

Dataset Attribute File name Source National Fire Database: Large Fires Shapefile NFDB_poly_20140210.shp cwfis.cfs.nrcan.gc.ca/home

National Fire Database: Small fires Point file NFDB_point_20131108.shp cwfis.cfs.nrcan.gc.ca/home Nechako Lakes District Shapefile NEC_Areal.shp and

BC_Electoral_Districts.shp http://www.bcstats.gov.bc.ca

Towns in the Nechako Lakes District

Shapefile NEC_SVA.shp http://www.bcstats.gov.bc.ca

Land use data Shapefile t.b.d. various

Cadastral Information Shapefile t.b.d. various

Climatological data Shapefile t.b.d. various Topography Shapefile t.b.d. various

Population and social demographics

Shapefile t.b.d. various


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The Canadian National Fire Database (CNFDB)

The Canadian National Fire Database (CNFDB) – Fire Point and Polygon Data is a collection of forest fire locations and fire perimeters as provided by Canadian fire management agencies including provinces, territories, and Parks Canada. The data are collected from Canadian fire management agencies including provinces, territories, and Parks Canada. To create the Canada-‐wide product, the data collected from each agency are projected into a common format and combined with data from other agencies; attribute fields are standardized; agency specific attribute fields are removed; and polygon areas are calculated using GIS. The database is a large collaborative effort by all Canadian fire agencies. Compilation of the Canada-‐wide database was partially supported by the Canadian government programs of ENFOR (Energy from the Forest), the Program on Energy Research and Development, the Climate Change Action Fund, and Action Plan 2000 (Canadian Forest Service, 2013.)

A high-‐level summary of the data files of the National Fire Database is given in Table 3.2. The sub-‐set of these data covering the Nechako Lakes District includes 1376 large fires and 1460 small fires. The overall annual burn probability of all fires in the entire region is 0.2056%. Values for mean and standard deviation per size category will be provided separately.

Table 3.2 Canadian National Fire Database selection

Portion Attribute National Variable Nechako Lakes

Large fires

Large Fires shapefile name NFDB_poly_20140210.shp NFDB_point_20131108.shp Number of large fires (1920-‐2013) 47616 (1920-‐2012) 1376 (1920-‐2012)

Number of years on record LA 92

Total area of Nechako Lakes District (hectares) LB 7341901 Total area (hectares) burned between 1917-‐2012 (96 years) LC 979353

Average total area burned annually (Hectares per year) LD = LC/LA 10531

Burn probability of large fires LP = (LS/(LB)*100% 0.143436965

Small fires

Small fires shapefile name NFDB_point_20131108.shp NFDB_point_20131108.shp

Number of small fires (1950-‐2013) 363516 1460 (1950-‐2012)

Number of years on record SA 63

Total area of Nechako Lakes District (hectares) SB 7341901

Total area (hectares) burned between 1920-‐2012 (93 years) SC

287738

Average total area burned annually (Hectares per year) SD = SC/SA 4567

Burn probability of small fires SP = (SD)/SB)*100% 0.062208273

All fires Average total area burned annually (Hectares per year) TA = LD + SD 15098

Burn probability of all fires TP = LP + SP 0.205645239


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3.3 Data Requirements in the Upper Athabasca Watershed and Yellowhead County

Similar to the data selection process for the Nechako Lakes District, the main criterion in the data selection process for the Upper Athabasca Region is that the data must reflect ecological and/or community elements that are either affected by, or controlled in the various adaptive strategies in scope for our research (see Table 2.2.) These data include borehole locations, records on water and chemical usage per well, fracturing dates, and hydrological as well as topographical information. In terms of community profiles and impact assessment, cadastral information and land use data will be required as well as data on protected areas, water wells, as well as waste treatment and disposal sites.

Table 3.3 Canadian National Fire Database selection Dataset Attribute File name Source

National Parks Shapefile

Alberta Land Use Boundaries Shapefile LUF Integrated Regional Plan Boundaries.shp

www.landusealberta.ca

Municipal Boundaries Shapefile CLAB_2014-‐11-‐05.shp www.landusealberta.ca Land Use Data Shapefile www.landusealberta.ca Parks and protected areas Shapefile Borehole locations Point file or table

Fracturing Liquids used Point file http://www.fracfocus.org/

Water used Point file or table http://www.fracfocus.org/

Last time fractured Point file or table http://www.fracfocus.org/

Cadastral Information Shapefile www.altalis.com Water bodies in Yellowhead County

Shapefile www.altalis.com

Water well locations Point file

Waste treatment and disposal sites Point file or table

Underground reservoirs Shapefile www.altalis.com Digital Elevation data (DEM) Raster LIDAR15_DEM_Coverage

.shp www.altalis.com

Hydrological information Shapefile www.landusealberta.ca

Soil type Shapefile t.b.d. Soil depth Raster t.b.d.


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3.4 Research Process

This section outlines the proposed research process for the application of the simulation and the adaptive strategies impact and evaluation model for the two case studies. Analogous approaches are applicable to both cases and are described briefly for the wildfire case in the paragraphs and figures below.

The high-‐level research process is presented in Figure 3.1. Adaptive management strategies for each community will be leveraged and optimized based on their opportunity cost.

For adaptive management strategies both for wildfires and hydrofracturing, a baseline scenario will provide the expected impact in case of no interventions, by assessing costs and benefits in each component of the community. Defining and refining the application of different management adaptation scenarios will involve an iterative process, by evaluating the opportunity cost and benefit of each strategy. This will provide insight in possibilities for improvement, as certain (combinations of) measures may reveal better results than others, depending on their timing and location.

Figure 3.1 High-‐level Research Process


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A number of studies have explored probability distributions of wildfire characteristics over longer periods of time (Moll, R.H.H., 1991; Schoenberg Peng and Woods, 2001; Schoenberg, Peng, Huang and Rundel, 2001.)

Figure 3.2 illustrates the process steps involved in deriving burn probability for the Nechako Lakes District based on historic data from the National Fire Database. Data from the National Database were clipped and the polygon data (large fire data) were converted to rasters each representing 1 year of data on large fires. The point data (small fire data) was also converted into rasters each representing 1 year of data on small fires. Two approaches were followed and compared to derive exact burn probability based on past measurements -‐ one involving kernel density and the other merging the rasters to obtain statistics on fire probability. These were calibrated against the total area burned (see Table 3.2) to produce an overall burn probability.

Figure 3.2 Process diagram for Deriving Burn Probability in the Nechako Lakes District


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4. Expected Analysis and Results

In this chapter, two rural communities will be assessed in terms of their historical probability distribution of hazards caused by respectively wildfires (Nechako Lakes District) and hydraulic fracturing (Yellowhead County.) The scope of this study will include historical data from which probability distribution functions can be derived. This will serve as a foundation for evaluating existing risk management strategies and deriving opportunities for improvement.

4.1 Community Profiling

A community profile is defined as a set of indicators providing a comprehensive picture of a community in terms of its environmental, economic, social, and cultural aspects. These aspects are categorized within four so-‐called “pillars of sustainability”. Each pillar is broken into a number of items (Lane & Watson, 2010) as noted below in Table 4.1 and Table 4.2.

Simulation of various mitigation strategies alongside a baseline scenario will provide impact assessments for these communities. From this, the opportunity cost of different strategies can be compared and the role of the different forms of capital therein, for each of the communities in scope. This will provide tools for employing economic, environmental, social and cultural capital to strengthen their emergency response strategies.

Table 4.1 Community Data Profile Items (Beigzadeh, 2014; Hartt, 2011; Lane and Watson, 2011)

Environmental Economic • Topography • Hydrology • Geomorphology • Habitats and Species • Land Cover • Land Use • Marine Use • Climate • Natural Resources

• Employment and Earnings • Occupation • Industry Sector • Industry Revenues ($) • Real Estate Values ($) • Public Works • Built Environment

Social Cultural

• Population Statistics • Language • Health Status • Education • Employment • Communication Resources

• Places of cultural significance • Community groupings • Cultural events and festivals

(dates, attendance numbers, area) • Governance Systems • Community dynamics

33

Table 4.2 Community profiles of Nechako Lakes (B.C.) and Yellowhead County (Alberta) Pillar Variable Nechako Lakes District

British Columbia Yellowhead County,

Alberta Economic Industry by type

Industry revenues Built environment Public works Real estate values

Environmental (Land Use)

Land area (km2) 73419.01 22359.61 Population 2006 38243 27881 Population 2011 39208 28584 Population increase (%) 2.5 2.5 % Rural 49.6 36.0 Persons / km2 in 2011 0.5 1.3 Topography Hydrology Geomorphology Habitat and species Land cover Land use Natural resources Climate

Social

Population statistics Education Health status Occupations by type Employment rates Labour earnings

Cultural and Recreational

Governance systems Community dynamics Community groupings Communications resources Language Places of significance Cultural events

34

4.2 Simulation Modelling

The simulation process, applied to both cases, will:

1. Establish a Baseline Case, validated by historical data. 2. Generate different controllable and uncontrollable simulation scenarios and impacts. 3. Simulate, evaluate and compare alternative adaptive strategies and their impact. 4. Compare, contrast, and rank strategies.

4.2.1 Baseline case Figure 4.1 provides a visual representation of wildfire history in the period 1950-‐2013 with data from the Canadian National Fire Database (CNFDB.) CNFDB fire point and polygon data are collected from Canadian fire management agencies including provinces, territories, and Parks Canada. (Burton et al., 2008, Parisien et al, 2006, Stocks et al, 2003, Amiro et al, 2001.) To create the Canada-‐wide product, the data collected from each agency are projected into a common format and combined with data from other agencies; attribute fields are standardized; agency specific attribute fields are removed; and polygon areas are calculated using GIS (Canadian Forest Service, 2013.)

4.2.2 Simulation scenarios and impacts

4.2.3 Alternative adaptive strategies and impacts

4.2.4 Compare, contrast and rank strategies


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Figure 4.1 Wildfire history (1917-‐2013) in Nechako Lakes Electoral District.


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5. Discussion

5.1 Data availability

5.2 Sensitivity Analysis

5.3 Ranking Procedure and Decision Support

5.4 Policy Implications for Adaptive Management

6. Conclusions and Recommendations

37

7. Proposed Research Project Plan and Timeline

The various MSc-‐research activities are performed in five distinct phases, as described below and further itemized schematically in Figure 6.1.

In phase 1 (October-‐December 2014, lead time of 3 months,) research activities will focus on obtaining available ArcGIS source files and assembling community profiles. An initial literature review will be undertaken, along with discussions with supervisors and subject matter experts. In this phase, a thesis proposal will be prepared and submitted for approval.

In phase 2 (January-‐April 2015, lead time of 4 months,) the literature review will continue. Wildfire scenarios and hydrofracturing scenarios will be developed. A simulation model will be developed and validated. Research results will be produced and/or interpreted visually in ArcGIS.

Phase 3 (May-‐July 2015 (lead time of 3 months) will involve the attendance and/or participation in World Conference on Natural Resource Modelling (Bordeaux, France) taking place from June 29-‐July 1 2015. Attendance and/or participation in ESRI User Conference (San Diego, U.S.A.) taking place from July 20-‐24 2015.

Phase 4 (August-‐September 2015, lead time of 2 months) will entail the final preparation, submission and defense of the thesis.

Phase 5 (October 2015-‐January 2016, lead time of 3 months) will include attendance and/or participation in the HICCS Conference (Hawaii, U.S.A.) taking place from January 5-‐8, 2016.

Figure 6.2 summaries the proposed research project plan in the Gantt chart timeline.


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Figure 6.1 Detailed description of proposed research project plan.

39

Timeline

Figure 6.2 Timeline and GANTT Chart of Activities


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