Southern Illinois University Carbondale
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Dissertations
Theses and Dissertations
8-1-2015
Restoration and Water Management in the
Atchafalaya River Basin, Louisiana
Justin Peter Kozak
Southern Illinois University Carbondale, [email protected]
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Kozak, Justin Peter, "Restoration and Water Management in the Atchafalaya River Basin, Louisiana" (2015). Dissertations. Paper 1068.
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RESTORATION AND WATER MANAGEMENT IN THE ATCHAFALAYA RIVER BASIN,
LOUISIANA
By
Justin P. Kozak
B.A., University of Illinois Urbana-Champaign, 2007
M.S., Southern Illinois University Carbondale, 2009
A Dissertation
Submitted in Partial Fulfillment of the Requirements for the
Doctor of Philosophy
Environmental Resources and Policy
In the Graduate School
Southern Illinois University Carbondale
August 2015
DISSERTATION APPROVAL
RESTORATION AND WATER MANAGEMENT IN THE ATCHAFALAYA RIVER BASIN,
LOUISIANA
By
Justin P. Kozak
A Dissertation Submitted in Partial
Fulfillment of the Requirements
For the Degree of
Doctor of Philosophy
In the field of Environmental Resources and Policy
Approved by:
Dr. Christopher L. Lant, Co-chair
Dr. Jonathan W.F. Remo, Co-chair
Dr. Lizette R. Chevalier
Dr. Leslie A. Duram
Dr. Bryan P. Piazza
Graduate School
Southern Illinois University Carbondale
June 22, 2015
AN ABSTRACT OF THE DISSERTATION OF
Justin Peter Kozak, for the Doctor of Philosophy degree in ENVIRONMENTAL RESOURCES
AND POLICY, presented on June 9, 2015, at Southern Illinois University Carbondale.
TITLE: RESTORATION AND WATER MANAGEMENT IN THE ATCHAFALAYA RIVER
BASIN, LOUISIANA
MAJOR PROFESSORS: Dr. Christopher L. Lant and Dr. Jonathan W.F. Remo
Environmental restoration in aquatic systems requires innovative approaches that
combine scientific understanding, socioeconomic demands, and local stakeholder values into
decisions. However, changing approaches to water management to address these requirements is
difficult because of scientific and socioeconomic uncertainty and institutional barriers that can
prevent implementation of alternative water management approaches. Current restoration efforts
in the Atchafalaya River Basin (ARB) of Louisiana are faced with this challenge. Water
management in the ARB has evolved from strong federal control to establish the ARB as a
primary floodway of the Mississippi River and Tributaries Project to a state and federal
collaboration to accommodate fish and wildlife resource promotion, recreational opportunities,
and economic development. While management policy has expanded to include a growing
number of stakeholders, the decision-making process has not kept pace. Current conflicts among
many local stakeholder groups, due in part to their lack of involvement in the decision-making
process, impede restoration efforts. The absence of a long-term collective vision for the ARB by
both local stakeholder groups and numerous management agencies further confounds these
efforts. Here, I propose a process to apply a structured decision making framework, a valuesbased approach that explicitly defines objectives, to promote stakeholder-driven restoration
efforts in the ARB and to better prepare for and manage long-term environmental issues. The
goals of this approach are: 1) to create a process founded on stakeholder values and supported by
i
rigorous scientific assessment to meet management agency mandates and 2) to establish a
structure for restoration planning in the ARB that incorporates current and future nongovernmental stakeholders into a transparent decision-making process. Similar frameworks have
been successful in other river basins and the structure of current restoration efforts in the ARB is
well-suited to adopt a values-focused management framework.
Next, I use flow-ecology relationships to evaluate ecosystem service trade-offs and
complementarities in the ARB to assess the potential impacts of water management decisions.
Flow-ecology relationships were used to explore complementary and trade-off relationships
among 12 ecosystem services and related variables in the ARB. Results from Indicators of
Hydrologic Alteration were reduced to four management-relevant hydrologic variables using
principal components analysis. Multiple regression was used to determine flow-ecology
relationships and Pearson correlation coefficients, along with regression results, were used to
determine complementary and trade-off relationships among ecosystem services and related
variables that were induced by flow. Seven ecosystem service variables had significant flowecology relationships for at least one hydrologic variable (R2 =0.19-0.64). River transportation
and blue crab (Callinectes sapidus) landings exhibited a complementary relationship mediated
by flow; whereas transportation and crawfish landings, crawfish landings and crappie (Pomoxis
spp.) abundance, and blue crab landings and blue catfish (Ictalurus furcatus) abundance
exhibited trade-off relationships. Other trade-off and complementary relationships among
ecosystem services and related variables, however, were not related to flow. These results give
insight into potential conflicts among stakeholders, can reduce the dimensions of management
decisions, and provide initial hypotheses for experimental flow modifications.
ii
The final study in this dissertation proposes an environmental flow prescription for the
highly altered ARB. The development of the ARB into a floodway has contributed to hydrologic
changes basin-wide that have altered the river-floodplain interface threatening important
ecosystems, notably the expansive baldcypress-water tupelo swamp forests. Analysis of the
current flow regime reveals a 12-92% increase in mean monthly discharge over the past 80+
years, but a 24-43% decrease in mean monthly stage in large portions of the basin over the past
50+ years. Current restoration efforts only address the spatial distribution of water in local areas
of the basin; however the timing, frequency, magnitude, and duration of ecologically important
high and low flows are determined at the basin-wide scale by the daily implementation of a
federal flow mandate that limits available water management options. We used current
hydrologic conditions and established flow-ecology relationships from the literature to develop
an environmental flow prescription for the ARB that provides basin-wide flow targets to
complement ongoing restoration efforts. The result is an adaptive flow regime that strives to
balance important flow-ecology relationships within a decision space limited by a federal flow
mandate. We found that lengthening the implementation of the current flow mandate to monthly
or quarterly time scales has high potential for success in meeting both the flow mandate and
important flow-ecology relationships.
iii
ACKNOWLEDGEMENTS
First and foremost, I would like to thank my wife Julie, whose love, support, and
encouragement was with me every step of the way.
Also, I thank my mother, whose selflessness allowed me to undertake this endeavor.
I would also like to thank my co-advisors Christopher Lant and Jonathan Remo for their
guidance and lessons throughout this process. I am also grateful for the suggestions and
comments from my committee members Leslie Duram, Lizette Chevalier, and Bryan Piazza.
I would like to acknowledge the faculty, staff, and students of the Environmental
Resources and Policy Program and the SIU IGERT Program in Watershed Science and Policy.
More than just a source of funding, these programs exposed me to a group of people with diverse
backgrounds and interests that helped expand my own understanding of current environmental
and natural resource issues.
I also thank Micah Bennett and Bryan Piazza, two people I’ve worked with continuously
for the past 4 years and have become great collaborators and friends. I hope we have many more
years working together.
iv
PREFACE
This dissertation consists of three separate papers. The first paper (Chapter 2), “A
proposed process for applying a structured decision making framework to restoration planning in
the Atchafalaya River Basin, Louisiana, USA,” is the result of my IGERT internship with The
Nature Conservancy in Baton Rouge, Louisiana. I analyzed the management structure and
decision-making process of the Atchafalaya Basin Program, performed the policy analysis,
designed the proposed process, and determined the implications for practice with the assistance
of co-author, Dr. Bryan P. Piazza. Ms. Jill Andrew at The Nature Conservancy, Louisiana
created the map. This paper has been published in the journal Restoration Ecology.
The second paper (Chapter 3), “Using flow ecology relationships to evaluate ecosystem
service trade-offs and complementarities in the nation’s largest river swamp,” is in press at the
journal Environmental Management. For this manuscript I acquired the data, performed the
analyses, interpreted the results, and formulated the conclusions in collaboration with co-author
Micah G. Bennett. Further assistance was provided by co-authors Anne Hayden-Lesmeister,
Kelley A. Fritz, and Aaron Nickolotsky.
The third paper (Chapter 4), “Towards dynamic flow regime management for ecosystem
restoration in the Atchafalaya River Basin, Louisiana,” has been submitted to the journal
Ecohydrology. I acquired the data, performed the analyses, interpreted the results, and
formulated the conclusions with the assistance of co-authors, Micah G. Bennett, Dr. Bryan P.
Piazza, and Dr. Jonathan W. F. Remo.
v
TABLE OF CONTENTS
CHAPTER
PAGE
ABSTRACT ..................................................................................................................................... i
ACKNOWLEDGEMENTS ........................................................................................................... iv
PREFACE ........................................................................................................................................v
LIST OF TABLES ....................................................................................................................... viii
LIST OF FIGURES ....................................................................................................................... ix
CHAPTERS
CHAPTER 1 – INTRODUCTION ......................................................................................1
CHAPTER 2 – A PROPOSED PROCESS FOR APPLYING A STRUCTURED
DECISION MAKING FRAMEWORK TO RESTORATION
PLANNING IN THE ATCHAFALAYA RIVER BASIN, LOUISIANA,
USA
INTRODUCTION ......................................................................................6
STRUCTURED DECISION MAKING .....................................................7
THE ATCHAFALAYA RIVER BASIN ....................................................9
ATCHAFALAYA RIVER BASIN MANAGEMENT .............................10
APPLYING STRUCTURED DECISION MAKING TO
STAKEHOLDER INVOLVEMENT IN THE ATCHAFALAYA
RIVER BASIN..........................................................................................12
CHAPTER 3 – USING FLOW-ECOLOGY RELATIONSHIPS TO EVALUATE
ECOSYSTEM SERVICE TRADE-OFFS AND
COMPLEMENTARITIES IN THE NATION’S LARGEST RIVER
SWAMP
INTRODUCTION ....................................................................................21
STUDY AREA .........................................................................................24
MATERIALS AND METHODS ..............................................................26
RESULTS .................................................................................................31
DISCUSSION ...........................................................................................34
vi
CHAPTER 4 – TOWARDS DYNAMIC FLOW REGIME MANAGEMENT FOR
ECOSYSTEM RESTORATION IN THE ATCHAFALAYA RIVER
BASIN, LOUISIANA
INTRODUCTION ....................................................................................50
STUDY SYSTEM ....................................................................................52
DATA AND METHODS .........................................................................55
RESULTS .................................................................................................59
DISCUSSION ...........................................................................................63
CONCLUSION .........................................................................................66
CHAPTER 5 – SUMMARY..............................................................................................84
REFERENCES ..............................................................................................................................89
APPENDICES
APPENDIX A – REQUESTS FOR CHANGES TO FLOW DISTRIBUTION AT
OLD RIVER CONTROL COMPLEX .................................................102
APPENDIX B – BIPLOTS OF PRINCIPAL COMPONENTS ANALYSIS
RESULTS .............................................................................................104
VITA ............................................................................................................................................107
vii
LIST OF TABLES
TABLE
PAGE
Table 2.1. Government stakeholder representatives currently serving on the Atchafalaya Basin
Program Technical Advisory Group and Research and Promotion Board ....................................15
Table 2.2. Management plans associated with the Atchafalaya River Basin, Louisiana ..............16
Table 3.1. Hydrologic variables used in analyses and their loadings on the three interpretable
principal component axes ..............................................................................................................41
Table 3.2. Summary and description of ecosystem service variables used in this study..............42
Table 3.3. Significant (p<0.05) multiple regression models relating ecosystem service variables
to selected flow metrics .................................................................................................................43
Table 4.1. U.S. Geological Survey real-time stream gages used in this study .............................68
Table 4.2. Environmental flow targets from scientific literature and reports for the Atchafalaya
River Basin used to create the environmental flow prescription in this study...............................69
Table 4.3. Historic (1930-1962, 1959-1974) and study-period (1988-2012) mean monthly
discharge and mean monthly stage trends at the Simmesport and Butte LaRose gages in the
Atchafalaya River Basin.. ..............................................................................................................70
Table 4.4. Ranges of discharge and stage values (1988-2012) corresponding to the
environmental flow components defined by one-period IHA analysis for the ARB .....................71
Table 4.5. Results of IHA percentile analysis of current flows showing range of discharges,
associated stages at Butte LaRose, and variability of the different environmental flow
components ....................................................................................................................................72
Table 4.6. The environmental flow prescription for the Atchafalaya River Basin, Louisiana .....73
Table 4.7. Annual breakdown of flow prescription volumes relative to actual flows ..................74
Table 4.8. Seasonal breakdown of flow prescription flow volumes relative to actual flows .......75
Table 4.9. Quarterly breakdown of flow prescription volumes relative to actual flows ...............76
Table 4.10. Monthly breakdown of flow prescription volumes relative to actual flows ..............77
viii
LIST OF FIGURES
FIGURE
PAGE
Figure 2.1. The Atchafalaya River Basin of Louisiana including the Atchafalaya and Wax Lake
deltas. The spatial jurisdictions of the various federal and state management plans associated
with the Atchafalaya River Basin are also shown .........................................................................17
Figure 2.2. The structured decision making framework ...............................................................18
Figure 2.3. Mean monthly Atchafalaya River discharge hydrograph, 1963 - 2011 (Simmesport,
Louisiana) ......................................................................................................................................19
Figure 2.4. The proposed incorporation of a stakeholder advisory board in the Annual Plan
process............................................................................................................................................20
Figure 3.1. Simplified example of an n-dimensional decision space (i.e., production possibilities
frontier) for water management where n is the number of socioeconomic and environmental
objectives that must be considered ................................................................................................44
Figure 3.2. The Atchafalaya River Basin in central Louisiana with relevant features shown ......45
Figure 3.3. Mean monthly discharge of the Atchafalaya River at Simmesport, LA and mean
monthly stage of the Atchafalaya River at Butte La Rose, LA, 1980-2011 ..................................46
Figure 3.4. Simple example hydrograph summarizing multiple regression and model selection
results ............................................................................................................................................47
Figure 3.5. Correlation matrix for ecosystem service variables ...................................................48
Figure 3.6. Example daily hydrographs showing years in which important hydrologic variables
were greatest ..................................................................................................................................49
Figure 4.1. The Atchafalaya River Basin (ARB), Louisiana. Also shown are the location of the
basin-wide flood control levees, major floodways within the ARB and the US Geological Survey
gages used in this study..................................................................................................................78
Figure 4.2. The spatial extent of cypress-tupelo swamp forests in the Lower Atchafalaya
Floodway........................................................................................................................................79
Figure 4.3. Specific-stage at Butte LaRose with a discharge of 3100 m3s-1 (~ 80 % flow
exceedance probability) at Simmesport, 1959-2012 ......................................................................80
Figure 4.4. Relationship of discharge at Simmesport and stage at Butte LaRose, 1988-2012 ..... 81
ix
Figure 4.5. Hydrograph of mean daily flows and corresponding water surface elevation (stage at
BLR) for wet, average, and dry years during the study period (1988-2012) .................................82
Figure 4.6. The environmental flow prescription for the Atchafalaya River Basin, Louisiana ....83
x
CHAPTER 1
INTRODUCTION
Rivers provide numerous benefits to society. They are a source of fresh water and food,
they support high levels of biodiversity and nutrient cycling, and they assimilate waste
(Millennium Ecosystem Assessment 2005; Postel & Carpenter 1997). Many rivers have been
altered to ensure a stable supply of benefits, such as navigation, or to provide additional benefits
like power generation, flood protection, and large reserves of fresh water for irrigation and
municipal uses. While these actions undoubtedly improved human welfare in the short-term they
also altered important ecological processes threatening the long-term sustainability of these
systems (Nilsson et al. 2005). Restoring the ecological health and functions of river systems is
now a top priority for natural resource agencies (Bernhardt et al. 2005); however, they are faced
with a significant dilemma: how to restore degraded ecological functions and maintain the
services the river system currently provides society?
A paradigm for river restoration is the natural flow regime which states that the natural
variability of water flows is fundamental to sustaining riverine ecosystems (Poff et al. 1997).
Restoring a natural flow regime is often not feasible because the socioeconomic benefits from
flow alteration and river engineering are still in demand or mandated by law. While this coupling
of natural and human systems complicates river management from a restoration planning and
decision-making perspective, it provides a framework “for exploring what is desired and what is
achievable in a given ecological, social, and political context” (Folke et al. 2002, cited in Poff et
al. 2003, p 302). The ecological context is provided by the natural flow regime and scientific
understanding of flow-ecology relationships – the direct connection between hydrology and the
1
ecological patterns and processes that provide many of the services society demands. The social
context is provided by the objectives of the various users of a river system. While some users are
dependent on natural processes, an overlap of the ecological and social context, others are
dependent on human alteration of the system and may be in conflict with ecological needs. The
political context is the decision space created by government policies that determine the
available alternatives for achieving ecosystem and socioeconomic goals. Managers of river
systems must balance these socioeconomic and environmental goals within a given decision
space where the quality of decisions is dependent on the decision-making process (Gregory &
Keeney 2002) and their understanding of natural flow variability and coincident flow-ecology
relationships (Arthington et al. 2006).
This coupling of natural and human systems is at the forefront of water management and
restoration planning in the Atchafalaya River Basin (ARB) of Louisiana. The ARB is
simultaneously the largest remaining wetland in North America and the keystone of the largest
structural flood-mitigation effort within the United States. It is a place of unique and important
flora and fauna, is home to Cajun culture, and has substantial resource value stemming from a
multitude of market and non-market ecosystem services (Cardoch & Day Jr 2001; Ford &
Nyman 2011). Its designation as a federal floodway and ensuing water management model,
however, have significantly altered the physical landscape threatening the production of
important ecosystem services while also limiting the natural resource management options
available. Looking to the future, the ARB needs a new water management model, as well as a
science-based decision-making process for conservation and restoration that includes local
stakeholder values, to better balance socioeconomic needs with ecological needs over the long
term (Piazza 2014). This research focuses on these needs by analyzing the current restoration
2
planning process, examining the relationships between hydrologic regime and various ecosystem
services, and determining the potential for a water management model that better serves both
ecological and social needs.
This dissertation is comprised of three papers that make up chapters two through four.
Chapter five summarizes the findings of these papers and highlights future research needs. In
chapter two, I provide a critical analysis of the structure and process through which restoration
decisions are currently made in the ARB and present a proposal for improving stakeholder
involvement in the planning process. Because the ARB is a working landscape, restoration
projects have the potential to affect numerous stakeholder groups; however, the process by which
these decisions are made, and the lack of involvement by those who would be affected, has
resulted in conflicts that undermine the quality of decisions and the ability to implement them
(van Maasakkers 2009). Therefore, these conflicts will eventually need to be addressed to serve
the long-term ecological needs of the ARB while preserving the rights of all stakeholders (Don
Haydel, Atchafalaya Basin Program, personal communication). To do so, the restoration
planning process in the ARB must get the participation right through adequate representation that
accounts for the numerous objectives and concerns of stakeholders in the ARB (National
Research Council 1999; Stern & Feinberg 1996). Additionally, the restoration planning process
must get the right participation to ensure that the necessary information and perspectives are
considered before a final decision is made (National Research Council 1999; Stern & Feinberg
1996). The result of this analysis is a proposal for a modified restoration planning process that
merges the need for a scientifically rigorous restoration planning process in order to get the right
participation with the need for a process that incorporates the objectives and conflicting interests
of the ARB’s stakeholders in order to also get the participation right.
3
In chapter three, I analyze the relationship between components of the flow regime
relevant to water managers in the ARB and several ecosystem services and related variables that
are important to local stakeholders. Despite a large and growing scientific literature on the
current state of the ARB’s biotic and abiotic systems there is still uncertainty regarding the
relationship between flow regime and the provisioning of the basin’s many ecosystem services
(See: Piazza 2014). This uncertainty extends to the ARB’s stakeholders who feel a change in
water management is needed but are unsure of the potential consequences for others (Louisiana
Crawfish Promotion & Research Board 2009; Water in the Basin Committee 2002). The primary
objective of this chapter was to identify flow-related complementarities and trade-offs among 12
ecosystem services and related variables in the ARB. The concept of ecosystem services – the
fundamental benefits that ecological systems provide to humans through natural functions and
processes (Millennium Ecosystem Assessment 2005) – provides a means to link the social and
ecological context of water management issues by connecting them with human welfare (Daily
1997; National Research Council 2005). Flow conditions that provide optimal conditions for the
services examined in this study, which include commercially and recreationally important fish
species, are likely complementary with other non-represented supporting and regulating
ecosystem services. The results contribute to the understanding of general relationships among
locally important ecosystem services in the ARB and also provide an approach that can make
complex flow-ecology relationships more accessible to stakeholders and more useful to water
managers when considering changes to water management.
There have been many considerations for changes to water management in the ARB since
the current flow policy was mandated in 1963 (Reuss 2004); however, no significant changes
were made despite considerable changes to the physical system and persistent concerns from the
4
basin’s stakeholders. The ARB has been optimized for flood mitigation and flood mitigation
remains the primary management objective. But what about when flood waters are absent? Can
flow regime in the ARB be managed to better serve ecological needs and current restoration
efforts while maintaining the flood control mission? The primary objective of chapter four was to
assess the potential for water management to better serve the long-term ecological needs of the
ARB in the current political and social context. A hydrologic analysis was used to determine the
current range of flow variability in the ARB. This was then compared to the flow needs of
baldcypress-water tupelo forests, a primary target of current restoration efforts in the ARB. The
overlap of the current range of flow variability and the flow needs of baldcypress-water tupelo
forests was essential for modeling environmental flows that are complementary to the flood
mitigation mission and have the potential to work within the current federal flow mandate. As
the complete reestablishment of a natural flow regime is not a feasible management option, the
modeled environmental flows seek to restore characteristics of the natural flow regime to support
biodiversity, ecological function, and desired ecosystem services in the ARB. The result is a
flexible flow management framework that has a high potential for success in the given
ecological, social, and political context of the ARB.
5
CHAPTER 2
A PROPOSED PROCESS FOR APPLYING A STRUCTURED DECISION MAKING
FRAMEWORK TO RESTORATION PLANNING IN THE ATCHAFALAYA RIVER BASIN,
LOUISIANA, USA.
Introduction
Anthropogenic modifications in rivers worldwide have disconnected floodplain wetlands
and changed flow regimes affecting habitat and biodiversity and altering biotic communities
(Poff et al. 2007). The continued use of water resources by humans and the irreversible character
of many hydrologic alterations requires innovative management approaches to protect, restore,
and manage river systems (Irwin & Freeman 2002). From an ecological perspective, effective
management re-establishes environmental gradients, connectivity, and natural ecosystem
dynamics. From a socioeconomic perspective, management supports use of water resources by
numerous stakeholders. Natural resource managers must balance these requirements but are
routinely faced with two fundamental obstacles: conflicting water resource uses and uncertainty
in the system.
Usually, natural resource management involves varied, often piecemeal approaches with
physical and social scientists providing discipline-specific input, despite acknowledgement that
scientific studies and economic analyses alone fail to capture all decision-relevant stakeholder
values. Overcoming this management dilemma requires a sense of common purpose among
stakeholder constituencies for addressing shared problems, which warrants their involvement, to
varying degrees, in the structure and process of natural resource management (Durant et al.
2004). Benefits of stakeholder involvement in natural resource management are well6
documented and credited with: (1) facilitating trust and legitimacy (Wondolleck & Yaffee 2000);
(2) leveraging public resources (Selin et al. 2007); (3) facilitating conflict resolution (Gregory et
al. 2001); (4) increasing transparency and improving substantive decision quality (Gregory &
Keeney 2002); (5) increasing commitment to, and acceptance of, decisions, and (6) strengthening
management resilience (Irwin & Freeman 2002). Further, participatory processes can increase
the robustness of natural resource management decisions through consideration of multiple
ecological, economic, and social impacts; however, this improvement is dependent on the quality
of the decision-making process (Gregory & Keeney 2002).
We propose a process to apply a structured decision making framework to restoration
planning in the Atchafalaya River Basin (ARB) of Louisiana (Figure 2.1) where a lack of
participation by non-governmental stakeholders in the decision-making process has led to
mistrust resulting in conflict that undermines the development of solutions for larger, long-term
resource management problems. In addition to its role in freshwater resource issues in Louisiana,
the ARB is now becoming central to coastal restoration, hurricane protection, coastal hypoxia,
and agricultural water supply (Piazza 2014). Future restoration decisions in the ARB will need to
be made within this larger management framework, requiring that management structures be
expanded to include more actors and longer-term objectives. Our goal is to include nongovernmental stakeholders in a collaborative decision-making process that builds trust, reduces
conflict, and establishes a values-based, transparent process for restoration decisions.
Structured Decision Making
Structured decision making (SDM) is a decision-focused framework for incorporating
uncertainty and multiple stakeholder objectives into the decision-making process (Gregory et al.
2001). It allows stakeholders and decision-makers to collectively consider natural resource
7
management issues and increase understanding through reasoned discourse and scientific
modeling to arrive at substantive decisions that are backed by rigorous, scientific methods (Irwin
& Kennedy 2008).
The steps of SDM (Figure 2.2) provide a process for decision-making that clarifies
objectives in a meaningful, inclusive, and manageable way. Decisions are broken down into
interdependent parts that help identify roles for a consensus decision. Stakeholders articulate
objectives and goals; experts model consequences and quantify uncertainties of various
management alternatives in an open forum; and both agree to an acceptable decision. The SDM
framework helps improve stakeholder understanding of the uncertainties involved in decisions,
and the transparent process can open lines of communication to repair relationships, build trust,
and reduce conflict (McDaniels et al. 1999).
The application of SDM to river restoration is not a new approach (e.g., see Hostmann et
al. 2003; Kiker et al. 2005; Reichert et al. 2007). We patterned our process after a similar valuesfocused effort on a southeastern U.S. river (Tallapoosa River, Alabama; Irwin & Freeman 2002;
Irwin & Kennedy 2008) and chose SDM because it is practiced and taught by the U.S. Fish and
Wildlife Service and the U.S. Geological Survey, two agencies with decision-making roles in the
ARB. Stakeholder attitudes and management issues discussed in this paper come from the
literature, planning documents, stakeholder assessments of current management practices, and
personal communication with individuals involved in management of the ARB (Atchafalaya
Basin Advisory Committee 1998; Reuss 2004; van Maasakkers 2009; Consensus Building
Institute 2010; Isaacs & Lavergne 2010).
8
The Atchafalaya River Basin
Approximately 225 km long and bounded by guide levees 24-40 km apart, the ARB
(Latitude: 30.281389° N, Longitude: 91.686667° W) drains into the Gulf of Mexico (Gulf)
through the Atchafalaya River and Wax Lake outlets, the only areas of the Louisiana coast
actively building land. The ARB is a principal floodway in the Mississippi River and Tributaries
Project. Flows enter the ARB through the Red River and the Old River Control Complex at a
static allocation of 30% of the combined daily flow of the Mississippi and Red rivers keeping the
system in a flow cycle that mirrors the Mississippi River and results in seasonal flooding of
floodplain forests and riverine wetlands (Figure 2.3).
Over 4,000 km2 in size, the ARB is about half privately owned and only seven percent of
the publicly owned lands are actively managed as conservation lands. A valuable landscape and
a biodiversity hotspot of global importance (Piazza 2014), it contains the largest remaining
coastal Taxodium distichum (baldcypress)- Nyssa aquatica (water tupelo) swamp in North
America, and produces $16 million USD per year of finfish and shellfish and one-million barrels
of oil and 3,680 m3 of natural gas per month (Carlson et al. 2012). It is a major shipping route,
connecting petrochemical processing facilities on the Mississippi River with extraction facilities
in the Gulf. It is the most popular freshwater fishery in Louisiana and is central to Cajun culture.
As access to the ARB has improved, its popularity for recreation and ecological education is
expanding to other stakeholder groups that are relatively new to the ARB (Atchafalaya Basin
Program 2012).
Management issues in the ARB stem from two conflicting resource-use complexes (van
Beek et al. 1977). The first includes natural resources like food, raw materials, and recreation
that are maintained by natural processes (natural overbank flooding and dewatering regimes).
9
The second complex includes navigation, flood control, and mineral extraction that require
human alteration of the environment (channelization and dredging). Current restoration efforts
strive for compatible use of ARB resources, but conflicting uses and altered hydrology have
resulted in a watershed that is in a state of ecological decline (Piazza 2014).
Atchafalaya River Basin Management
The ARB that exists today began with designation as a federal floodway in 1928. In the
1960s, in response to a rapidly changing system, the State and various interest groups became
more involved in the management of the ARB. This brought more stakeholders, governmental
and non-governmental, into the management structure as it evolved towards a multi-use
management framework (Reuss 2004).
In 1998 the Atchafalaya Basin Program (ABP) was created within the Louisiana
Department of Natural Resources (LDNR) to coordinate state and federal restoration planning
efforts. Its main responsibility was to implement and update (every 15 years) the Atchafalaya
Basin Master Plan. Though the Master Plan was drafted with admirable non-governmental
stakeholder involvement (Atchafalaya Basin Advisory Committee 1998), limited stakeholder
involvement in its implementation has eroded stakeholder trust in the managing agencies
(Consensus Building Institute 2010).
To address the lack of a stakeholder-manager dynamic, the Louisiana Legislature adopted
Act 606 in 2008, shifting policy to a more holistic, ecosystem restoration approach (Atchafalaya
Basin Program 2012). The Act overhauled the ABP’s management structure and decisionmaking process by requiring the development of Annual Plans composed of individual projects
for water management, water quality, recreation, and public access. Act 606 aligned the duties of
the ABP’s oversight board – the Research and Promotion Board (RPB) – and a newly established
10
Technical Advisory Group (TAG; Table 2.1) composed of subject area experts from agencies
and academia to ensure only scientifically-valid projects are approved for the Annual Plan.
Further, Act 606 requires two sets of public hearings during the development of the Annual Plan.
The first set of hearings solicits project proposals from stakeholders, which are subsequently
developed by the TAG and approved by the RPB. The second set of public hearings presents
approved projects for public review and comment.
Despite these changes, stakeholders remain frustrated with the ABP’s planning efforts,
citing jurisdictional confusion, agency bias, and a back-end inclusion of ideas (van Maasakkers
2009; Consensus Building Institute 2010). Multiple agencies and management plans at work in
the ARB are, by mandate, limited to addressing specific issues. This limits the scope and
flexibility of management decisions to address interdependent socioeconomic and environmental
issues and contributes to confusion over shifting boundaries between issues (Table 2.2, Figure
2.1; van Maasakkers 2009). Further, despite broad agreement by stakeholders on the state of the
ARB’s ecological problems, there is disagreement regarding the prevailing water management
model and the impacts of restoration projects on stakeholder livelihoods (Louisiana Department
of Natural Resources 2002; van Maasakkers 2009). This structural uncertainty is at the core of
the conflicts in the ARB. For example, stakeholders that propose a project often oppose the same
project once developed by the TAG, citing disagreement with proposed project features and
expected results. Hence, many consider the current planning process a waste of time and no
longer participate.
Though Act 606 brought the different perspectives and fragmented responsibilities of the
multiple agencies working in the ARB into one management group with a common vision, it did
not provide a mechanism to reduce structural uncertainty among stakeholders. Non-
11
governmental stakeholders are not directly represented by the RPB or TAG (Table 2.1), and their
absence precludes meaningful participation in the Annual Plan process. Project proposals for the
Annual Plan begin as a bottom-up, stakeholder-driven process but become a top-down process
when proposals are developed by the TAG and subject to agency directives and institutional
biases. As a result, the approved project may be incongruous with the original stakeholder
objective. This disconnect contributes to the conflicts between stakeholders and the ABP
rendering the public hearings ineffective for determining stakeholder objectives and values and
producing more posturing and divisiveness than dialogue and collaboration. Our proposed
approach seeks to build upon the institutional inertia towards adaptive management by
incorporating a diverse group of stakeholders into the structure and process of restoration
planning in the ARB.
Applying Structured Decision Making to Stakeholder Involvement in the Atchafalaya
River Basin
Restoration projects in the ARB have the potential to impact economic competition
among stakeholders, giving them a vested interest in management decisions. Overlapping
stakeholder concerns and the potential for the use of consensus-building methods (Consensus
Building Institute 2010) suggest a larger-scale visioning process that engages all stakeholders.
Because the SDM framework emphasizes the fundamental objectives of decisions and forecasts
results through the use of models, it can provide a context to individual projects that
complements individual stakeholders’ long-term goals, despite the presence of trade-offs in the
short term. In contrast to rule-making and legal actions, the SDM approach to restoration efforts
can benefit from incorporating more traditional knowledge sources while creating a deliberative
forum for addressing long-standing inter-stakeholder conflicts.
12
To establish the SDM process, we suggest using a professional, neutral facilitator with
applied SDM experience to develop and lead a stakeholder workshop (e.g., see Irwin & Kennedy
2008). A facilitator is essential due to the Basin’s history, resource value, broad stakeholder use,
and current conflicts. A facilitator’s commitment to the process helps control the posturing and
grandstanding prevalent in public hearings and creates a deliberative space by establishing
ground rules and respecting each party’s ability to learn and identify values and interests.
The workshop should 1) teach the SDM process; 2) develop shared, fundamental
objectives for the ARB; 3) incorporate stakeholder values and objectives into a structured
decision model for making decisions and assessing management progress; and 4) create a
Stakeholder Advisory Board (Board). The workshop should be representative of all stakeholder
constituencies, provide an opportunity for real, substantive involvement, and serve as the
beginning of the conflict management process. Once objectives are established, participants
develop a decision support model that: 1) integrates stakeholder objectives (values) with
scientific data and local knowledge; 2) incorporates uncertainty; and 3) explores alternative
restoration actions. The decision model provides a new way for managers and stakeholders to
collectively visualize and process decisions in the face of uncertainty and establishes a process
for adaptive management.
The workshop is a starting point, but for long-term success it needs to address the
shortcomings of the current decision-making process -- exclusion of non-governmental
stakeholders. The Board should be composed of one representative from each participating
stakeholder group to supplement the current TAG and RPB and be responsible for developing
management alternatives and project proposals that are linked to fundamental objectives. The
TAG would continue to inform management through scientific findings in an effort to reduce
13
uncertainty related to current projects, but would work closely with the Board to pass
recommendations through as a collective body (Figure 2.4). This shared learning by stakeholders
and managers is necessary for successful adaptive management and the shared responsibility for
management decisions can help overcome current problems of legitimacy. The TAG currently
performs these tasks so minimal institutional changes are required to expand their scope of
collaboration. Guided by a collective vision and shared learning, scientific analyses will take on
a new context that is more attuned to stakeholder preferences and scientific monitoring and
learning (adaptive management). This arrangement would allow stakeholders, experts, and
managers to interact regularly -- a necessary dynamic for effective, well-received decisions
(National Research Council 1999). The strength of the SDM approach is that it improves
thinking by reducing uncertainty and sharpening communication about the critical elements of
natural resource management decisions. This is needed to manage uncertainty and conflicting
water resource uses over the long term, and is critical to developing a sense of common purpose
among stakeholders.
14
Table 2.1. Government stakeholder representatives currently serving on the Atchafalaya Basin
Program Technical Advisory Group (TAG) and Research and Promotion Board (RPB). Also
shown is a summary of the agency mission, as it relates to management and restoration of the
Atchafalaya River Basin. A single asterisk denotes membership, and a double asterisk denotes
the agency that chairs the board. Note the absence of no non-governmental stakeholder
representation on either board.
Member Agency
1
TAG
RPB
US Fish and Wildlife Service
*
US Geological Survey
*
US Army Corps of Engineers
*
LA Dept. Natural Resources
*
**
LA Dept. Wildlife Fisheries
**
*
LA Dept. Env. Quality
*
*
LA Dept. Ag. Forestry
*
*
LA Dept. Health Hospitals
LA. Dept. Culture,
Recreation, Tourism
LA Dept. Transportation
Development
*
State Land Office
*
Office of Governor
*
LSU School of Renewable
Natural Resources
Atchafalaya Levee Board
2
Parish (county)
*
*
*
*
*
Mission/Objective
Manage and administer the fish and wildlife resources
for the public.
Provide scientific fact-finding to manage natural
resources and mitigate natural disasters.
Provide public engineering services to strengthen
national security and reduce disaster risk.
Manage non-renewable natural resources for
economic benefit.
Manage fish and wildlife resources and habitats for
social and economic benefit and public use.
Provide comprehensive environmental protection to
promote and protect health, safety, and welfare.
Promote, protect and advance agriculture, forestry,
and soil and water resources.
Protect and promote health of citizens.
Preserve, showcase and market cultural heritage
within and outside of state.
Deliver transportation and public works systems that
enhance quality of life and facilitate economic growth.
Identify, administer, and manage State public lands
and water bottoms for revenue and public use.
Promote and manage effective partnerships for the
betterment of the State.
Advance and disseminate knowledge in conservation,
restoration, and sustainable use of forest, wetland,
and aquatic resources.
Provide levee maintenance for Basin parishes.
Represent interests of parish residents.
1
Member agencies are listed in order of Federal Agencies, State Agencies, and Local Agencies. This
listing does not reflect importance or influence over management activities.
2
Four ARB floodway parishes (counties) are allotted one, annually rotating representative.
15
Table 2.2. Management plans associated with the Atchafalaya River Basin, Louisiana.
Title
Atchafalaya Basin
Louisiana Project,
1928
Atchafalaya Basin
Floodway System
Project, Louisiana
Master Plan, 2012
Atchafalaya Basin
Floodway System
Louisiana Project
State Master Plan,
1998
Agency
Spatial scope
West Atchafalaya,
Morganza, and Lower
Atchafalaya floodways,
Old River Control
Complex
Cycle
U.S. Army
Corps of
Engineers
Lower Atchafalaya
Basin Floodway
12
years
Flood control, water
management, public
access, fish and wildlife
enhancement
LA - Dept. of
Natural
Resources
Atchafalaya Basin from
Simmesport to Morgan
City and areas adjacent
to levees
15
years
Water management,
recreation, public access,
environmental restoration
and conservation
U.S. Army
Corps of
Engineers
----
Objectives
Flood control
Atchafalaya
National Heritage
Area Management
Plan, 2011
National Park
Service, LA Dept. of Culture,
Recreation, and
Tourism
14 Atchafalaya Basin
parishes
15-20
years
Build understanding,
identity, and awareness;
economic growth; natural
resource-based
recreation
Louisiana's
Comprehensive
Master Plan for a
Sustainable Coast,
2012
LA - Coastal
Protection and
Restoration
Authority
Coastal LA, Southern
Atchafalaya River Basin
5
years
Flood protection; coastal
restoration; commercial
and recreational activity
promotion
16
Figure 2.1. The Atchafalaya River Basin of Louisiana. Shown are the Atchafalaya Basin
Floodway and the Atchafalaya and Wax Lake deltas. The spatial jurisdictions of the various
federal and state management plans associated with the Atchafalaya River Basin are also shown.
17
Figure 2.2. The structured decision making framework. Stakeholders begin by defining the
problem based on a collective vision. Problem definitions guide the process and are often revised
during the process. Next, stakeholders generate a set of fundamental objectives that capture the
importance of the future decision. All structured decision steps build from these objectives.
Alternatives are developed to accomplish the objectives. Alternatives reveal uncertainty in
system response, challenge perceived constraints and conflicts, and help stakeholders visualize
solutions. Scientific information (e.g., decision support tools, scientific analysis, and modeling)
is used to assess consequences, weigh alternatives, and evaluate tradeoffs. At this stage, expert
guidance is used to construct scientifically-testable decision models that illustrate results,
identify optimal solutions, and develop a decision point. If no alternative presents an acceptable
course of action the process cycles back to reevaluate objectives and alternatives until a decision
can be made. Adapted from: Runge et al. 2011.
18
12000
Discharge (m3 s-1)
10000
8000
6000
4000
2000
0
OCT NOV DEC
JAN
FEB
MAR APR MAY
JUN
JUL
AUG SEP
Figure 2.3. Mean monthly Atchafalaya River discharge hydrograph, 1963 - 2011 (Simmesport,
Louisiana; USGS 07381490). Daily flows into the Atchafalaya River Basin (ARB) floodway
through the Old River Control Structure Complex are held at 30% of the daily latitude flow of
the Mississippi and Red rivers. This flow allocation keeps the ARB floodway in a quasi-natural
seasonal flow regime that follows flows on the Mississippi River but does not allow for extremes
in seasonal variability. Annual mean discharge in the Atchafalaya main channel is 6,500 m3 s-1;
range 600–19,800 m3s-1).
19
Figure 2.4. The proposed incorporation of a stakeholder advisory board in the Annual Plan
process. The stakeholder advisory board would be appointed during the stakeholder workshop,
with each representative chosen by their constituents and firmly committed to managing the
Atchafalaya River Basin in a manner consistent with the collective vision. Their appointment
should be a concerted effort to represent the full range of stakeholder perspectives, integrate
scientific information with local knowledge and values, and bring the voices of moderation into
the process.
20
CHAPTER 3
USING FLOW-ECOLOGY RELATIONSHIPS TO EVALUATE ECOSYSTEM SERVICE
TRADE-OFFS AND COMPLEMENTARITIES IN THE NATION’S LARGEST RIVER
SWAMP
Introduction
Environmental issues in large river systems are inextricably linked with social systems;
consequently decisions must be made within a given ecological, social, and political framework
that often defies objective, technical resolution (Ludwig 2001; Folke et al. 2002). Since the
objectives of numerous stakeholders place competing demands on water resources, managers of
large river systems need a strong conceptual understanding of ecosystem function (e.g., the
natural flow regime, nutrient cycling) and must also accommodate policy constraints and
stakeholder expectations. The challenge is merging human needs with ecological needs for
water. Attempts to do so range from requiring environmental flows to recognizing the
environment as a legitimate user of water in decision-making (Rowlston & Palmer 2002;
Arthington & Pusey 2003). Part of the challenge is that, compared to social and economic values
for water, ecological values are less intuitive and often not well quantified, making them less
accessible to stakeholders and less useful to managers (Bunn & Arthington 2002). This
conceptual roadblock can lead to conflict where stakeholders feel ecosystem needs are placed
above human needs for fresh water (Poff et al. 2003; Richter et al. 2003) and attempts to simplify
flow-ecology relationships – the direct connection between hydrology and ecological patterns
and processes - to make them more accessible and useful have been criticized for providing little
insight into complex ecosystem dynamics (Richter et al. 1997). The derivation of flow-ecology
21
relationships is necessary to assess potential impacts of water management decisions, but
translating complex flow-ecology relationships into stakeholder-relevant information remains a
struggle.
An ecosystem services approach can provide a bridge between flow-ecology relationships
and stakeholder-relevant data because it integrates economics and ecology and connects them
with human welfare (Daily 1997; National Research Council 2005). Ecosystem services are the
fundamental benefits that ecological systems provide to humans through natural functions and
processes (Millennium Ecosystem Assessment 2005). Some ecosystem services, like food, raw
materials, and energy production, have direct market value; others, like water purification,
nutrient cycling, and cultural significance, have readily identifiable social value, but lack a direct
market value. In river systems, many of these services are directly influenced by the flow regime.
Socioeconomic data associated with the ecosystem services of river systems can be used to
establish relationships between social benefits, ecological function, and characteristics of the
flow regime that are meaningful to stakeholders and decision-makers alike (Arthington et al.
2006; Sanderson et al. 2012). Data availability and model complexity determine if these
relationships can be quantified (dollars, production level of a good or service) or simply qualified
(increase or decrease of a good or service).
In developed river systems, changes in water management operations occur in response
to new scientific understanding, a change in policy, changing stakeholder preferences, and
changes in river hydraulics or hydrology. Flow modification, briefly, is an attempt to move a
river system to a more desirable state (i.e. maximizes socioeconomic and environmental benefits
and minimizes costs; Poff et al 1997; Richter et al 2003; Arthington et al 2006; Richter et al
2006; King et al 2008). Conceptually, this can be thought of as a multi-criteria optimization
22
problem where decisions are made in the presence of conflicting objectives, scientific
uncertainty, and societal demand for a specific combination of goods and services (Lund &
Palmer 1997; Farber et al. 2006; Harou et al. 2009). The ideal outcome is a Pareto improvement
where there is an increase in socioeconomic or environmental benefits for some stakeholders
without a reduction in benefits for other stakeholders (Figure 3.1). A Pareto efficient frontier
represents optimal states of the system where no objective can be advanced without trade-offs on
other objectives. For example, maintaining river flows to provide habitat for certain species
complements other river services such as waste removal and recreation opportunities. More
often, however, water management decisions result in trade-offs between established economic
uses of water resources and newer socioeconomic and environmental objectives (Lund & Palmer
1997; Baron et al. 2002; Poff et al. 2003). For example, maintaining minimum in-stream flows to
facilitate endangered species survival can have a negative effect on irrigation and municipal
water supply (Rodríguez et al. 2006). Expert understanding of these trade-offs, paired with
stakeholder preferences (represented in Figure 3.1 by social indifference curves), is essential to
provide the highest-value management options for a river system and necessary to adaptively
manage rivers as complex social-ecological systems (Folke et al. 2002; Farber et al. 2006;
Rodríguez et al. 2006; Bennett et al. 2009).
Many hydrologic variables are important to the ecological functioning of channels,
riparian habitat, and floodplain areas (Richter et al. 1996; Poff et al. 1997). Systematically
reducing these variables to a more manageable set can aid in identifying how river flows can be
modified for socioeconomic goals while maintaining an adequate flow regime for the structure
and function of its ecosystems. This study combines ecological and socioeconomic data with
hydrological analysis to characterize and quantify relationships between 12 ecosystem service-
23
related variables and hydrologic characteristics of streamflow in the Atchafalaya River Basin
(ARB), Louisiana. By examining these relationships this study attempts to translate hydrologic
variables in terms that are directly applicable to stakeholder interests while also capturing
components of flow that are important to managers of the ARB. The goal of this study is to
identify flow related complementarities and trade-offs among ecosystem services and related
variables in the ARB and provide a framework for future efforts involving flow management and
large-scale flow experiments.
Study Area
The ARB is located in south-central Louisiana (Figure 3.2) and contains the largest
continuous area of bottomland hardwood forest in the U.S., along with cypress-tupelo swamps,
lakes, marshes, bayous, and man-made canals (Ford & Nyman 2011). The Atchafalaya River is
the largest distributary of the Mississippi River and flow is characterized by high flows in the
spring months and low flows during late summer to early fall (Figure 3.3).
The ARB provides many ecosystem services valued in the billions of dollars annually
(Piazza 2014). Provisioning services provide direct goods and are the most well-known in the
ARB. For instance, fisheries in the ARB produce 5.9-11.5 million kg in landings valued at $8.9$24 million annually (Carlson et al. 2012). Regulating services, those that maintain living
conditions for humans, are less tangible but include well-recognized services in the ARB such as
flood mitigation and water purification. Supporting services are even less apparent, but are the
underlying ecosystem processes that produce direct services. For instance, denitrification
(conversion of nitrate (NO3-) to atmospheric nitrogen (N2 gas)) removes agricultural pollutants
from freshwater ecosystems. Though the ARB was found to be a net source of nitrogen to the
Gulf of Mexico, exporting 2.3% more mass of nitrate and nitrite (NO2-) than entered the ARB
24
from 1978 to 2002 (Xu 2006), the effects of annual hydrologic variability in the ARB on
denitrification have not been fully explored (Bennett et al. in press). Other supporting services
include various nutrient cycles, primary production, and soil formation. Cultural services, such as
aesthetic or spiritual value and recreational opportunities, are also provided by the ARB and are
increasingly recognized as economically important. The ARB is a National Heritage Area, the
most popular recreational fishery in the state, a hunting and birding destination, and home to
Cajun culture, providing significant economic benefits to Louisiana (Gramling & Hagelman
2005).
Ecological functions and resulting services in the ARB are affected by large-scale water
management issues resulting from its primary development and management as the centerpiece
floodway of the Mississippi River and Tributaries project. Further, in the mid-1900s, the ARB
was recognized as the site of an ongoing delta-switching event (Russell 1940; Fisk 1944; Latimer
& Schweitzer 1951; Fisk 1952); it was feared the Mississippi River would permanently change
its course to the Atchafalaya River. The Flood Control Act of 1954 authorized the U.S. Army
Corps of Engineers (USACE) to build the Old River Control Complex (ORCC) to keep the
Mississippi River on its current path to the Gulf of Mexico (Saucier 1998). The ORCC provides
a unique degree of hydrologic control; since 1963 the ARB has received a mandated 30% of the
combined annual flows of the Mississippi and Red Rivers during normal flow conditions (Reuss
2004). As a general practice, this 70-30 split is maintained on a daily basis (Water in the Basin
Committee 2002; Reuss 2004).
Various groups have raised the possibility of altering the flow regime at ORCC, but the
many stakeholders and services in the ARB make such a decision difficult to implement (Reuss
2004). A 2002 report found that user groups in the ARB generally wanted more water in
25
backswamp areas, but felt that timing and duration of such flow events was important and had
serious concerns regarding potential negative impacts to other user groups (Water in the Basin
Committee 2002). The USACE considered 10 different ORCC operation plans in the 1970s and
1980s, but ultimately resisted any major change, allowing only short-term changes to occur
periodically (Reuss 2004). From 1996 - 2013, the flow distribution was altered 7 times through
requests from the Louisiana Governor’s Office to mitigate detrimental environmental and
economic impacts in the ARB; all requests were for more water between February and May
(Don Haydel, Atchafalaya Basin Program, pers. comm.; Appendix A). These deviations
acknowledge the importance of flow-ecology relationships to the ARB as a social-ecological
system; however, a better understanding of flow-ecology relationships in the ARB at the basin
scale is needed.
Materials and Methods
Hydrologic Data
This study relates basin-wide ecosystem services and related variables to discharge at the
Simmesport gage (USACE gage 03045, river mile 4.9; Figure 3.2), which accounts for all flows
into the ARB from the Red and Mississippi Rivers. One of the ecosystem services examined –
denitrification – relies on stage data collected at the Butte La Rose gage (BLR; USACE gage
03120; river mile 64.8; Figure 3.2). The BLR gage is important for understanding hydrology and
estimates of inundation extent in the ARB (Allen et al. 2008; Alford & Walker 2013), but does
not measure discharge. Linear regression analysis suggests that discharge at Simmesport is
closely related to stage at the BLR gage without any lag adjustment (R2 = 0.96, p<0.001), and
gage height and discharge from both gages show the same trends and long-term cycles (Figure
3.3). The Simmesport and BLR gages are operated by the USACE and collect data at 7 a.m.
26
daily. Data from the gages were analyzed from January 1, 1980 to December 31, 2011; dates
with missing or erroneous values were excluded from the analysis.
Extensive natural and anthropogenic changes in the ARB make identifying a natural flow
regime (Poff et al. 1997) difficult, so Indicators of Hydrologic Alteration (IHA) software
(Richter et al. 1996) was used to calculate 42 biologically-relevant hydrologic parameters for
each year in the hydrology dataset (1980-2011). Monthly low-flow and monthly mean flow data
were combined into seasonal metrics, and variables with missing data were excluded, resulting in
23 hydrologic variables from IHA. In addition, annual mean flow and coefficient of variation
(CV) of daily flows were added for each year. Because the effects of flow on reproduction and
recruitment may not show up in adult population sizes for several years, the lagged mean flow
from one to five years (i.e., mean flow one year prior through five years prior) were also added
based on the time to maturity for the fish species of commercial and recreational importance in
the ARB for a total of 31 hydrologic variables (Table 3.1).
Ecosystem Services Data
Data on 12 ecosystem services and related variables were obtained from public databases,
reports, and papers (Table 3.2). All variables were analyzed on an annual basis due to limitations
on data availability.
Commercial and recreational fisheries production. Production of finfish and shellfish in the
ARB includes several freshwater fishes, crawfish, and blue crabs (which are influenced by river
outflow into the estuary). Data from Alford and Walker (2013) provided annual mean abundance
or biomass estimates for five commercial and recreational fish species and commercial landings
data on three fish groups (Table 3.2) which were used to estimate relationships between annual
hydrologic variables and several metrics of fisheries production.
27
Data on commercial crawfish landings were obtained from the National Oceanic and
Atmospheric Administration (NOAA) National Marine Fisheries Service Commercial Fisheries
Statistics Database (NOAA Fisheries 2013) and the Louisiana Crawfish Promotion and Research
Board (LCPRB; LCPRB 2009). The NOAA database provided data on commercial landings of
wild-caught crawfish in Louisiana from 1949-2011 and the LCPRB (2009) report contained
commercial catch data in Louisiana from 1987-2007 from Louisiana State University (LSU) as
well as the number of licenses issued from 1987-2008. The LSU data were paired with the
license data to control for variation in commercial effort by dividing the total pounds of catch by
the number of licenses issued each year (1987-2007). Although these numbers are for the entire
state of Louisiana, trends in the data are assumed to reflect conditions in the ARB as it accounts
for 83-98% of the wild-caught crawfish harvested in the state each year (LCPRB 2009). The
LCPRB report also contained data on commercial crawfish harvests specifically for the ARB
based on Louisiana Department of Wildlife and Fisheries (LDWF) Trip Ticket data from 20002008 to explore crawfish harvest patterns in addition to the larger statewide dataset. All crawfish
metrics were moderately to highly correlated (R2 = 0.35-0.74) reinforcing the validity of the data,
therefore, only the LSU data corrected for commercial effort (crawfish per license) were used to
reduce the number of variables.
Blue crab (Callinectes sapidus) is an important commercial fishery along the Atlantic and
Gulf coasts of the United States. Landings of blue crab in Louisiana have ranged from over 3
million kg to over 24 million kg since the 1950s and make up 60-80% of Gulf of Mexico
landings (VanderKooy 2013). The Atchafalaya Bay is among the top areas for blue crab in
Louisiana, bringing in landings valued at $400,000 to over $2 million annually since 1999
(Louisiana Department of Wildlife and Fisheries, unpublished data). Crab recruitment and
28
harvest have been closely linked to high river discharge and low salinity, possibly as a result of
physiological or environmental effects such as reduced predation risk and increased food
abundance (Guillory 2000). Commercial landings data were obtained from the LDWF
commercial trip ticket program from 1999-2011.
River transportation. Transportation is another direct provisioning service provided by rivers.
Inland barge transportation in the U.S. can be considerably impacted by both high and low flows
(Lohr 2008; NPR 2012). Inland waterway transportation data were obtained from the USACE
(USACE, personal communication) and the USACE Navigation Data Center (U.S. Army Corps
of Engineers n.d.). Specifically, annual summaries of total lockage events (number of times a
lock was operated) through the Old River lock in the ARB were used as a proxy for river
transportation (Figure 3.2, Table 3.2).
Denitrification model. Respiratory denitrification is the microbial transformation of nitrate
(NO3-) to atmospheric nitrogen and removes agricultural pollutants from freshwater ecosystems
as a supporting ecosystem service. Maximizing denitrification has been identified as a potential
way to decrease the hypoxic zone in the Gulf of Mexico (Mitsch et al. 1999; Mitsch & Gosselink
2007). Values from a model estimating annual basin-wide nitrogen removal via respiratory
denitrification in the ARB (Bennett et al., in press) were used to examine relationships with flow
regime.
Statistical Analyses
Hydrologic variables are often highly multicollinear (Olden & Poff 2003). Principal
components analysis (PCA) was used to reduce the 31 hydrologic variables (Table 3.1) to three
uncorrelated axes using a “broken stick” model to select the number of interpretable axes
(Jackson 1993). The three principal component (PC) axes explained a combined 58.9% of
29
variation in the hydrologic variables (Table 3.1; Appendix B). Analyses were conducted in the R
environment (v. 3.0.0) using the packages ‘stats’ and ‘vegan’ (R Core Team 2012).
The PCA revealed many of the hydrologic variables to be highly correlated (Table 3.1;
Appendix B). Following Olden and Poff (2003), the PCA results were used to select uncorrelated
hydrologic variables. The first three PCs were interpretable based on a broken stick model and
were retained for subsequent analyses. Hydrologic variables with a large loading (positive or
negative) on one of the interpretable PCs that did not load highly on the other two interpretable
PC axes were chosen based on ease of interpretability and applicability to flow management.
‘Rise rate’, with the second highest loading on PC3, was chosen over ‘reversals’ due to
interpretability, although both represent flow variability. For PC1, ‘30-day minimum’ was
chosen over ‘mean flow’ and ‘median flow’ to represent flow magnitude as it is more relevant to
flow management and more meaningful to stakeholders. For PC2, ‘date of maximum’ was
chosen instead of ‘base flow index’ (which had the highest loading), because it is more easily
interpretable and corresponds to a different aspect of flow regime: timing. ‘30-day maximum’
was also chosen from PC2 to represent a different aspect of flow magnitude with relevance to
flow management. The final four variables for subsequent analyses were 30-day minimum, 30day maximum, date of maximum, and rise rate. These final variables had low collinearity, with
Pearson correlation coefficients of |0.06| - |0.42|.
To evaluate flow-ecology relationships, each of the 12 ecosystem services and related
variables were treated as a dependent variable in multiple linear regression models that included
all combinations of the selected hydrologic variables as independent variables. All models were
examined to ensure that assumptions of normality and homogeneity of variance were met based
on normal quantile-quantile plots and predicted-residual plots, respectively. Where assumptions
30
of normality were not met, data were transformed to normalize the data for further analyses. For
each variable, the most optimal model among all significant models (p ≤ 0.05) was selected
using the Aikaike information criterion modified for small sample size (AICc) (Akaike 1974;
Hurvich & Tsai 1989; Burnham & Anderson 2002). AICc is used to select the ‘best’ model
among candidate models by ranking them based on a trade-off between goodness-of-fit and
number of parameters, with fewer-parameter models that explain more variation favored. Models
within +/- 2.00 AICc from the best model were considered equally good models (Burnham &
Anderson 2002). Standardized regression coefficients (variance of independent variables
standardized to 1) were calculated separately to evaluate relative importance of hydrologic
variables. To evaluate relationships among ecosystem service variables, a Pearson correlation
coefficient matrix was created to visualize trade-offs and complementarities through time. All
analyses were performed using the ‘stats’ (for multiple regression and correlation) and
‘AICcmodavg’ (for AICc) packages in the R environment.
Results
Flow-Ecology Relationships
Seven of the 12 ecosystem service-related variables were significantly related to at least
one of the selected hydrologic variables (Figure 3.4), with low to moderate adjusted R2 in
multiple linear regression models (0.19-0.64; Table 3.3). Four variables were related to 30-day
minimum flow: commercial catfish landings (negatively; i.e., increased magnitude of 30-day
minimum flows resulted in a decrease in landings), blue crab landings (negatively), crawfish per
license (positively; i.e., increased magnitude of 30-day minimum flows resulted in an increase in
landings), and lockage events (positively). In all cases, however, the significant models included
other variables that had more or similar influence. In the case of crawfish per license, the model
31
with 30-day minimum was +/- 2.00 AICc values of the most optimal model, which only included
rise rate. This was similarly the case for blue crab, except with 30-day maximum being the best
model. Three variables were significantly negatively related to 30-day maximum: blue crab
landings, Old River lockage events, and denitrification (i.e., increased magnitude of 30-day
maximum flows resulted in lower values). For blue crab landings, the most optimal model
included only 30-day maximum, but models for Old River lockage events and denitrification
included two of the other variables (Table 3.3). Blue catfish biomass and crawfish per license
were positively related to 30-day maximum (i.e., increased magnitude of 30-day maximum flows
resulted in higher landings), but the best model for crawfish per license also included rise rate.
Crawfish per license was negatively related to rise rate, and the best model included only this
variable. Crappie abundance, blue crab landings, Old River lockage events, and denitrification
were positively related to rise rate; however, crappie abundance was only marginally significant
(p=0.05). Finally, two variables were positively related to date of maximum flow (catfish
landings, denitrification; i.e., later Julian dates of maximum flow resulted in higher values) and
two were negatively related to this variable (crappie abundance, Old River lockage events; i.e.,
later Julian dates of maximum flow resulted in lower values). Examining standardized regression
coefficients (Table 3.3), 30-day maximum was most important in models for blue catfish
biomass, blue crab landings, Old River lockage events, and denitrification. Thirty-day minimum
was of similar importance to 30-day maximum and rise rate in one of the best models for blue
crab landings. Rise rate was most important for the crawfish per license model and was of
similar importance as date of maximum flow in the crappie abundance model. Date of maximum
flow was most important for crappie abundance and commercial catfish landings models (Table
3.3).
32
Relationships among Ecosystem Services
The Pearson correlation coefficient matrix (Figure 3.5) allows for visual assessment of
trade-offs and complementarities among ecosystem services and related variables across years.
Positive correlation coefficients among ecosystem service variables that share a response to flow
(same direction of relationship with a hydrologic variable in Figure 3.4, Table 3.3) illustrate
complementary relationships and identify services that should respond similarly to flow
manipulation. Negative correlation coefficients among ecosystem service variables that have
divergent responses to flow (opposite direction of relationship with a hydrologic variable in
Figure 3.4, Table 3.3) identify flow-mediated trade-offs among services.
Two variables exhibited a complementary relationship driven by flow (Figure 3.5). Old
River lock operations and blue crab landings were positively related (r = 0.57, p = 0.04; Figure
3.5) and responded similarly (negatively) to 30-day maximum flow (Figure 3.4, Table 3.3).
There were more hydrology-related trade-offs than complementary relationships exhibited by
services (Figure 3.5). Crappie abundance and crawfish landings were negatively correlated (r = 0.53, p = 0.03; Figure 3.5) and responded oppositely to rise rate (Figure 3.4, Table 3.3). Blue
crab landings and blue catfish biomass were negatively related (r = -0.75, p <0.01; Figure 3.5)
and exhibited divergent responses to 30-day maximum (Figure 3.4, Table 3.3). Denitrification
was negatively related to crawfish production (r = -0.41; Figure 3.5), although the correlation
was only marginally significant (p = 0.067), and these had divergent responses to 30-day
maximum and rise rate (Figure 3.4, Table 3.3).
In several cases, correlations indicated relationships among ecosystem service variables
that did not have significant responses to hydrologic variables. The two recreational fisheries
production metrics (crappie and bass catch-per-effort) were positively related (r = 0.74, p <0.01)
33
as were blue crab landings and shad abundance (r = 0.64, p = 0.032) and bass catch-per-effort
and catfish landings (r = 0.62; Figure 3.5); however, the latter correlation was only marginally
significant (p=0.055), and there was no evidence for flow relationships based on the multiple
regression, except for marginal relationships for crappie (Figure 3.4, Table 3.3). Blue catfish and
buffalo biomass (r = -0.46, p = 0.055), denitrification and buffalo landings (r = -0.59, p = 0.056),
and shad abundance and commercial shad landings (r = -0.85, p<0.01) were negatively related
(Figure 3.5) but exhibited no significant relationships with hydrologic variables for assessing
flow-mediated trade-offs. These relationships may suggest trade-offs and complementarities that
are not flow mediated or could be a result of data limitations.
Discussion
Ecosystem Services
The ability to control flow, and its status as a “master variable” (Poff et al. 1997), make it
an ideal target for managing ecosystem service provisioning in river systems. The approach
taken here identifies general relationships between ecosystem services and related variables and
flow regime in the ARB that can be further evaluated with finer-scale experiments. The
significant relationships between ecosystem services and hydrologic variables in this study are
not necessarily useful predictively because of model uncertainty and the difficulty in
implementing flow standards based on correlated hydrologic variables, but they do reveal
potential trade-offs and complementarities among ecosystem services in the ARB that are useful
from a management standpoint and deserve more focused study and hypothesis-testing (Figure
3.6). Based on our results, blue catfish abundance is maximized in years with high 30-day
maximum flow, like 2011 in which this variable was greatest (Figure 3.6a). Thirty-day minimum
flow explained more variation than other hydrologic variables in only the blue crab model;
34
however, crawfish landings and river transportation should be higher and catfish and blue crab
landings lower than average in years like 1993 in which 30-day min was highest (Figure 3.6b).
Crawfish landings and crappie abundance are negatively affected in years with high rise rate,
with rapidly rising and falling pulses as in 2002 (Figure 3.6c) while blue crab landings are
higher. Commercial catfish landings and crappie abundance are maximized in years with high
flows later in the year, like 1992 (Figure 3.6d). Such metrics linked to specific annual
hydrographs provide a useful approach to visualizing the context of ecosystem service tradeoffs
and management-relevant hydrologic manipulation (Figure 3.6).
This study found significant relationships between commercial fisheries and hydrology
including catfish, crawfish, and blue crab landings, as well as blue catfish abundance (Table 3.3,
Figure 3.4). These results complement previous work in the ARB (Alford & Walker 2013) but
differ due to the divergent goals and statistical approaches used. Alford and Walker (2013) used
curve-fitting procedures to determine the flood magnitude and duration at which several fisheries
metrics (many also used in our study) were maximized. Relationships among ecosystem services
and between services and environmental metrics are often characterized by non-linear
relationships, thresholds, and feedbacks (Rodríguez et al. 2006; Bennett et al. 2009) that might
make curve-fitting appropriate; however, for our study, the approach was abandoned when it was
clear that single or few points impacted the non-linear fitting of the regression models. The
multiple linear regression models generally had fewer parameters relative to the sample size and
may be less prone to overfitting (Hawkins 2004); that assumptions of linear regression were met
in these models suggests that this approach was warranted. It is impossible to directly compare
results because of the difference in questions, hydrologic variables, and methods; however, our
results do corroborate the presence of significant relationships among multiple fisheries variables
35
and flow regime found by Alford and Walker (2013), including positive relationships between
flow magnitude and both crawfish landings and blue catfish abundance.
Some relationships for fisheries corroborate studies of the Flood Pulse Concept (Junk et
al. 1989) with modifications for temperate rivers (Tockner et al. 2000; Schramm & Eggleton
2006). Blue Catfish are known to extensively use floodplain habitats for food during warm
inundation events (Eggleton & Schramm 2004), and abundance in our models was significantly
related to high flow conditions (higher 30-day maximum; Figure 3.4, Table 3.3). However, other
catfish species may be less strongly linked to floodplain habitats (Schramm & Eggleton 2006)
and total catfish landings were not associated with high-magnitude flow events. Crappie are not
strongly dependent on floodplains (Gutreuter et al. 1999), but spawning and recruitment have
been linked to small flood pulses (Halloran 2010). Concordant with this, crappie abundance
(catch-per-effort) was related to rise rate and flood timing (Figure 3.4, Table 3.3). Blue crab
landings were negatively related to flow magnitude variables 30-day min and 30-day max which
somewhat contradicts previous findings in the Mississippi River (Guillory 2000) and could
suggest stock-specific responses, correlations with other hydrologic variables, or, potentially,
lagged responses.
Several relationships for other ecosystem services are also concordant with current
understanding. Denitrification is substantially affected by cycles of oxic and anoxic conditions in
floodplain soils that are driven by flooding patterns (Reddy & Patrick 1975; Groffman 1994),
and, in this study, modeled denitrification values were related to 30-day maximum (magnitude),
date of maximum (timing), and rise rate (variability) (i.e., responding positively to a later flood
pulse and smaller magnitude but quicker pulsing floods; Figure 3.4, Table 3.3). While the
negative relationship between flow magnitude (30-day min and max) and river transportation
36
(lockages at Old River) appears contradictory to expectations (i.e., greater transportation with
high flows), temporary navigation restrictions occur when rising flood waters and a combination
of a narrow navigation width, the flow and direction of currents, and three bridges that span the
Atchafalaya River in close proximity poses a hazard to navigation and floodway infrastructure.
Model Uncertainty
Many of our findings are consistent with established flow-ecology relationships, but
uncertainty remains due to aggregation to annual time series, small sample size for some
services, economic influences, and correlation of hydrologic variables. Interpreting these
findings is complicated because many factors within a year could be contributing to the
relationships. Further, many hydrologic variables were correlated, and multiple variables
contributed strongly to the hydrologic PC axes, complicating interpretation from a management
standpoint.
The results for crawfish landings corroborate some common generalizations about
hydrologic factors associated with improved crawfish harvest. A recent Louisiana crawfish
management plan states that “maximum production of wild-caught crawfish always corresponds
to so-called flood years in the Lower Mississippi River Valley” (LCPRB 2009, p. 8). This is
supported by the datasets examined in this study, including those uncorrected for commercial
effort, as crawfish landings were positively related to mean and maximum flows; however, they
showed a negative relationship with quickly-rising floods (rise-rate) which was most important
in multiple regression models (Figure 3.4, Table 3.3). According to commercial crawfishermen,
an ideal flood cycle for crawfish production is an early rise in November with mid-winter floods
that maintain floodwaters until July followed by approximately two months of drought (LCPRB
2009). The same crawfishermen identify the ARB’s cypress-tupelo swamps as “hot-spots” for
37
crawfish harvesting, but baldcypress require longer than two months of drought/low flows for
successful regeneration (Conner et al. 1986). If the hydrologic regime were set in accordance
with what crawfishermen perceive is ideal it would compromise the long-term sustainability of
the best crawfish habitat. This highlights the need for better understanding of ecological drivers
by stakeholders and managers alike, and for a more nuanced analysis using consistent or finerscale measurement of ecological responses to flow to evaluate other common assumptions.
While many of the variables in this study are dependent on specific environmental
conditions, the ecosystem service variables used are influenced by market forces. Economic
production should not be conflated with biological production. For example, at the current level
of production the market for wild-caught crawfish is apparently saturated; fishermen could
harvest crawfish daily but buyers limit them to weekends when demand is higher (LCPRB
2009). The limited capacity for economic production of wild-caught crawfish means that the
crawfish data used in this study is impacted by the current market for crawfish and potentially
underestimates the biological production of crawfish in the ARB. The situation may be similar
for the other commercial fisheries variables in our dataset such as blue crab landings.
The Importance of Understanding Relationships among Services
Our approach can serve as a stimulus for developing serious large-scale flow-ecology
experiments, as a framework for improving adaptive management efforts in other watersheds,
and as a useful frame for future data collection and decision-making. As the likelihood of
ecological and socioeconomic impacts increases with increased magnitude of flow alteration
(Poff & Zimmerman 2010), flow regime change in altered systems should be incremental, with
flow targets based on socially relevant components of flow (magnitude, duration,
timing/temperature, frequency, and rate of change), and not wholesale flow regime change. The
38
flow control capabilities in the ARB provide a unique opportunity for large-scale experiments
that can contribute to understanding flow-ecology relationships at larger scales (Richter &
Thomas 2007; Konrad et al. 2011). Despite the federally-mandated flow regime, there appears to
be considerable flexibility in daily and seasonal releases that could allow flow experiments
without significant legal entanglements (Appendix A). Additionally, water management in the
ARB is unique in that ORCC creates a semi-natural flow regime that generally mimics
seasonality of the Lower Mississippi River but limits extreme flow variability (Piazza 2014;
Piazza et al. 2014). This characteristic contrasts with infrastructure such as hydropower dams,
which generally disrupt seasonality, and the difference could be useful in comparing responses to
wholesale flow regime changes (e.g., the Colorado River) versus adding high and low flow
extremes to an otherwise intact seasonal flow pattern.
The move in natural resource management towards adaptive management emphasizes
that stakeholders must be directly involved in environmental decision-making for long-term
sustainability of the process and resources (Berkes 2009). The framework provided here is a first
step towards more effectively integrating stakeholder objectives into scientific flow assessments.
Each ecosystem service in the ARB is used by some set of stakeholders, whether they are beyond
the confines of the ARB levees or more local resource users (e.g., commercial and recreational
fishers). Knowing how these services trade-off or complement each other with a change in flow
regime allows managers to identify areas of direct conflict among resource users and enables
proactive approaches to conflict resolution. For instance, the blue crab and navigation industries
may be natural allies regarding flow management decisions because the ecosystem services they
rely on appear to be complementary (Figures 3.4, 3.5). On the other hand, there may be a need
for conflict mediation between recreational and commercial fisheries because conditions
39
promoting some recreational fish production (e.g., crappie) may reduce landings in some
commercial fisheries (e.g., crawfish). Also, some commercial fisheries such as blue catfish and
blue crab may be in conflict regarding flow management. Efforts to increase crawfish production
may also promote nutrient loading to the Gulf of Mexico through reduced denitrification (Figure
3.4); however the role of denitrification in the ARB may be so limited as to not factor into
decision-making (Bennett et al., in press; Xu 2006).
This analysis identifies individual components of a flow regime that may be ecologically
and socioeconomically significant and relevant to water management decisions. Data limitations
in this study prevent the quantification of flow-mediated changes in ecosystem service related
variables, but the results do provide valuable insights into trade-offs and ecological production
associated with flow regime. An ecosystem service variable that positively correlates with other
variables that share a similar response to flow might be able to serve as a proxy for these
variables. This can effectively reduce data gaps and the dimensions of the management problem
(Figure 3.1). Although the degree of hydrological control capabilities in the ARB is unique, our
approach could be useful in other river basins with varying levels of hydrologic control where
the issue is not the economic value of water-use due to scarcity or over-allocation, but rather an
issue of the socioeconomic impact of water management decisions.
40
Table 3.1. Hydrologic variables used in analyses and their loadings on the three interpretable
principal component axes. The percent of variation explained by each axis is in parentheses.
Hydrologic
Variable
Mean flow
Mean 1yr lag
Mean 2yr lag
Mean 3yr lag
Mean 4yr lag
Mean 5yr lag
CV
Median flow
1-day minimum
3-day minimum
7-day minimum
30-day minimum
90-day minimum
1-day maximum
3-day maximum
7-day maximum
30-day maximum
90-day maximum
Base Flow Index
Date of minimum
Date of maximum
Low pulse count
High pulse count
Rise rate
Fall rate
Reversals
Winter low flow
Winter mean flow
Spring mean flow
Summer mean flow
Fall mean flow
Description
Average daily flows
Average daily flow 1 year prior
Average daily flow 2 years prior
Average daily flow 3 year prior
Average daily flow 4 year prior
Average daily flow 5 year prior
Coefficient of variation in daily flow
Median of daily flows
Annual minimum 1-day means
Annual minimum 3-day means
Annual minimum 7-day means
Annual minimum 30-day means
Annual minimum 90-day means
Annual maximum 1-day means
Annual maximum 3-day means
Annual maximum 7-day means
Annual maximum 30-day means
Annual maximum 90-day means
7-day minimum flow divided by mean annual
flow
Julian date of minimum flow
Julian date of maximum flow
Number of occurrences of flow pulses below
th
25 percentile of daily flows
Number of occurrences of flow pulses above
75th percentile of daily flows
Mean of all positive differences between
consecutive daily flows
Mean of all negative differences between
consecutive daily flows
Number of negative and positive changes in
flow from one day to the next
Average of monthly mean low flows Dec-Feb
Average of monthly mean flows Dec-Feb
Average of monthly mean flows Mar-May
Average of monthly mean flows Jun-Aug
Average of monthly mean flows Sept-Nov
41
PC1
Loading
(29.9%)
-0.307
PC2
Loading
(21.0%)
-0.128
-0.106
0.158
PC3
Loading
(7.9%)
0.125
-0.129
-0.113
0.338
-0.277
-0.256
-0.254
-0.258
-0.265
-0.253
-0.212
-0.212
-0.211
-0.22
-0.227
-0.198
-0.203
-0.202
-0.19
-0.206
0.283
0.285
0.287
0.273
0.257
-0.326
-0.117
-0.194
0.14
0.132
-0.165
-0.172
-0.146
-0.123
-0.264
-0.134
0.236
-0.323
-0.234
-0.358
0.172
0.299
0.12
-0.191
-0.176
-0.113
-0.428
0.218
0.281
0.129
-0.149
-0.107
-0.208
0.109
Table 3.2. Summary and description of ecosystem service variables used in this study.
Variable
Abbrev.
Service Type
Measured
Blue Catfish
(Ictalurus
furcatus)
WPEa
Largemouth
Bass
(Micropterus
salmoides)
CPEa
BlueCat
Provisioning;
commercial
fisheries
LMB
Cultural,
provisioning;
recreational
fisheries
Crappie
(Pomoxis
species) CPEa
Crappie
Cultural,
provisioning;
recreational
fisheries
Total buffalo
(Ictiobus
species)
biomassa
Buffalo
Provisioning;
commercial
fisheries
Shad
CPE
Provisioning;
commercial
fisheries
Comm
Buffalo
Provisioning;
commercial
fisheries
Commerical
catfish
landingsa
Comm
Cat
Provisioning;
commercial
fisheries
Commerical
Gizzard Shad
landingsa
Comm
Shad
Provisioning;
commercial
fisheries
Crawfish/
License
Crawfish
Provisioning;
commercial
fisheries
Blue Crab
(Callinectes
sapidus)
landings
BlueCrab
Provisioning;
commercial
fisheries
Old River
Lockages
Lockages
Modeled
Potential
Denitrification
Denitr
Provisioning;
transportation/i
ndustry
Supporting;
nutrient
cycling/water
purification
Gizzard Shad
(Dorosoma
cepedianum)
CPEa
Commerical
buffalo
landingsa
a
Description
Weight-per-effort
(kg/ gill net-hour) of
Blue Catfish
(Ictalurus furcatus)
Catch-per-effort
(individuals/
electrofishing-hour)
for Largemouth Bass
(Micropterus
salmoides) > 200
mm total length (TL)
Catch-per-effort
(individuals per
electrofishing-hour)
for crappie (Pomoxis
spp.) >150 mm TL
Biomass (kg/ gill net
summed by year) of
all buffalo (Ictiobus)
species
Catch-per-effort
(individuals/ gill nethour) of Gizzard
Shad (Dorosoma
cepedianum)
Total commercial
landings (kg) of
buffalo from dealers
in the ARB
Total commercial
landings (kg) of
catfish (Ictalurus
spp.) from dealers in
the ARB
Total commercial
landings (kg) of
Gizzard Shad from
dealers in the ARB
Total commercial
crawfish landings
(lbs) divided by total
licenses issued
Total commercial
blue crab landings
(kg)
Number of lockage
events at Old River
Lock
kg nitrogen removed
via denitrification
Collection
Method
N
(yrs, #missing)
Gill net
18
(1992 – 2009, 0)
Alford &
Walker
2011
Electrofishing
22
(1984 – 2009, 4)
Alford &
Walker
2011
Electrofishing
22
(1984 – 2009, 4)
Alford &
Walker
2011
Gill net
20
(1990 – 2009, 0)
Alford &
Walker
2011
Gill net
18
(1992 – 2009, 0)
Alford &
Walker
2011
LDWF
Commercial
Trip Ticket
Program
reporting
LDWF
Commercial
Trip Ticket
Program
reporting
LDWF
Commercial
Trip Ticket
Program
reporting
Commercial
reporting
11
(1999 – 2009, 0)
Alford &
Walker
2011
11
(1999 – 2009, 0)
Alford &
Walker
2011
11
(1999 – 2009, 0)
Alford &
Walker
2011
21
(1987 – 2008, 1)
LDWF
Commercial
Trip Ticket
Program
reporting
12
(1999-2011, 0)
LSU/LDWF
data
(LCPRB
2009)
Louisiana
Department
of Wildlife
and
Fisheries
Daily records
27
(1980 – 2011, 0)
Model results
49
(1980 – 2011, 0)
Detailed summary and descriptions, including sampling methodology, in Alford and Walker (2011)
42
Source
USACE
Navigation
Data Center
Bennett et
al. (in press)
Table 3.3. Significant (p<0.05) multiple regression models relating ecosystem service variables
to selected flow metrics. Bold models indicate the optimal model based on AICc. Standardized
regression coefficients indicate the relative importance of flow metrics in the model. One model
with p=0.05 for crappie CPE is also shown
Significant Models (p ≤ 0.05)
AICc
2
R
p
30dmin
Blue Catfish WPE
30dmax
Crappie CPE
Riserate + Datemax
Catfish Landings
30dmin + Datemax
30dmin + Riserate + Datemax
30dmax + 30dmin + Datemax
Crawfish/License
Full
30dmin + 30dmax + Riserate
Riserate
30dmin + Riserate
30dmax + Riserate
Riserate + Datemax
30dmin + Riserate + Datemax
30dmax + Riserate + Datemax
Blue Crab Landings
Full
30dmin + 30dmax + Riserate
30dmin + 30dmax
30dmax
30dmin + Riserate
30dmax + Riserate
30dmax + Datemax
30dmin + Riserate + Datemax
30dmax + Riserate + Datemax
30dmin + 30dmax + Datemax
Old River Lockages
Full
30dmin + 30dmax + Riserate
30dmin + 30dmax
30dmax
30dmax + Riserate
30dmax + Datemax
30dmax + Riserate + Datemax
30dmax + 30dmin + Datemax
Potential Denitrification
Full
30dmin + 30dmax + Riserate
30dmin + 30dmax
30dmax
Riserate
Datemax
30dmin + Datemax
30dmax + Riserate
30dmax + Datemax
Riserate + Datemax
30dmin + Riserate + Datemax
30dmax + Riserate + Datemax
30dmax + 30dmin + Datemax
Std Regression Coefficients
30dmax
Riserate
Datemx
12.44
0.21
0.03
77.35
0.19
0.05
-12.33
-5.13
-6.05
0.61
0.56
0.60
0.009
0.03
0.02
-1.06
-1.05
-1.24
0.21
66.89
63.83
59.46
61.50
60.69
61.70
64.75
62.90
0.29
0.30
0.30
0.30
0.33
0.29
0.27
0.33
0.05
0.03
0.006
0.015
0.01
0.02
0.04
0.02
-0.01
0.11
0.26
0.20
392.58
385.68
387.25
384.60
387.27
386.56
388.92
391.56
391.17
390.34
0.61
0.64
0.43
0.41
0.43
0.46
0.36
0.43
0.45
0.48
0.019
0.007
0.02
0.01
0.02
0.02
0.04
0.046
0.04
0.03
-0.47
-0.50
-0.28
486.30
489.44
487.53
485.18
487.08
482.08
483.29
484.77
0.29
0.17
0.18
0.20
0.19
0.31
0.32
0.28
0.01
0.04
0.02
0.006
0.02
0.002
0.003
0.006
-0.02
-0.23
-0.20
604.58
609.82
615.13
613.44
616.80
613.67
615.55
607.34
607.74
610.63
611.74
601.73
610.56
0.50
0.37
0.22
0.22
0.14
0.22
0.21
0.39
0.38
0.32
0.33
0.51
0.36
<0.001
0.001
0.01
0.004
0.02
0.004
0.01
<0.001
<0.001
0.001
0.002
<0.0001
0.001
-0.05
0.10
0.16
43
0.51
0.18
0.24
0.13
0.23
-0.60
-0.49
-0.57
-0.68
-0.73
-0.69
-0.68
-0.90
-0.59
0.06
-0.68
-0.48
0.36
-0.39
-0.07
1.22
1.25
1.35
-0.59
-0.56
-0.58
-0.58
-0.55
-0.61
-0.60
-0.59
0.20
0.44
0.49
0.16
0.16
0.10
0.19
0.56
0.30
0.45
0.42
-0.64
-0.43
-0.45
-0.51
-0.51
-0.53
-0.54
-0.55
0.28
0.23
-0.56
-0.67
-0.60
-0.53
0.30
0.31
0.02
0.32
-0.22
0.40
-0.25
0.21
0.18
-0.36
-0.39
-0.38
0.35
0.13
0.43
0.50
-0.23
-0.63
-0.48
-0.29
0.02
-0.45
-0.49
0.33
0.11
0.19
0.38
0.37
0.43
0.50
0.37
0.36
Figure 3.1. Simplified example of an n-dimensional decision space (i.e., production possibilities
frontier; see Bekele et al 2013) for water management where n is the number of socioeconomic
and environmental objectives that must be considered. The star represents the current state of the
system. Black arrows represent water management decisions that are Pareto improvements
because there are no reductions in economic output or environmental quality. Grey arrows
illustrate water management decisions that produce trade-offs but may move the system to a
more desirable state.
44
Figure 3.2. The Atchafalaya River Basin in central Louisiana with relevant features shown.
Source: Atchafalaya Basin Program NRIAS, ESRI Basemap
45
Figure 3.3. Mean monthly discharge of the Atchafalaya River at Simmesport, LA (bars, left
axis), and mean monthly stage of the Atchafalaya River at Butte La Rose, LA (points, right axis),
1980-2011
46
Figure 3.4. Simple example hydrograph summarizing multiple regression and model selection
results. Signs (+/-) indicate flow-ecology relationships based on significant multiple regression
models (positive and negative, respectively). Bold variable text indicates the flow metric was the
most important in the model as judged from standardized regression coefficients
47
48
Figure 3.5. Correlation matrix for ecosystem service variables. Pearson correlation coefficients (>|0.10| ) above diagonal and p-values
below diagonal (p < 0.07 shown;NS=nonsignificant). Shaded boxes show significant and marginally significant relationships between
ecosystem service variables. Solid bold and dashed outlined boxes show significant relationships (complementary and trade-off,
respectively) driven by hydrologic variables. Bold variables indicate their significant relationship with one or more hydrologic
variables. Note that not all significant relationships between ecosystem service variables were found to be significantly related to
hydrologic variables. See Table 3.2 for variable codes
49
Figure 3.6. Example daily hydrographs showing years in which important hydrologic variables were greatest. a) Highest 30- day
maximum in 2011 b) Highest 30-day minimum in 1993. c) Highest rise rate in 2002. d) Highest (latest) date of maximum flow in
1992
CHAPTER 4
TOWARDS DYNAMIC FLOW REGIME MANAGEMENT FOR ECOSYSTEM
RESTORATION IN THE ATCHAFALAYA RIVER BASIN, LOUISIANA
Introduction
Natural resource management in the 21st century is confronted with increasingly rapid
biotic and abiotic changes (Millennium Ecosystem Assessment 2005; IPCC 2007) that can result
in the creation of hybrid ecosystems. Hybrid ecosystems are created when human activities and
associated indirect effects result in new combinations of species and/or abiotic conditions that
can alter the structure and function of an ecosystem, yet still retain some original characteristics
(Chapin III & Starfield 1997; Williams et al. 2007; Lindenmayer et al. 2008; Seastedt et al. 2008;
Hobbs et al. 2009).
Many managed river systems can be considered coupled human-natural systems where
the preexisting, presumably natural, ecosystem has been transformed by human intervention into
a hybrid ecosystem. This occurs because human activities have reduced the natural variability of
river processes, such as channel migration, channel-floodplain interactions, and flow magnitude
to the extent that many major rivers now function outside of their historic range of flow
variability (Postel & Richter 2003). This transformation caused both lateral and longitudinal
habitat fragmentation threatening important ecological functions and biodiversity and facilitating
the establishment of non-native species (Ward & Stanford 1995; Power et al. 1996; Bunn &
Arthington 2002; Poff et al. 2007), thus challenging the ability to achieve ecosystem goals.
Increasing demand for water resources (Vörösmarty et al. 2000) and the uncertain effects of
climate change on specific river systems (Margaret A. Palmer et al. 2008) will further challenge
50
current river management approaches and require new strategies to maximize natural capital and
provide important ecosystem services (Acreman et al. 2014). The success of such strategies
depends on recognizing fundamental changes that have occurred in a river system and
identifying management strategies that address those changes to restore processes that benefit
both ecological and socioeconomic needs (Holling 2001; Arthington et al. 2010).
The natural flow regime paradigm states that the natural variability in the timing,
quantity, quality, rate of change, and frequency of flows in a river are fundamental to sustaining
riverine ecosystems and associated biodiversity (Poff et al. 1997). Restoring a natural flow
regime is often a preferred approach to river restoration and, if practicable, is likely the best
option for ecological restoration and river health. However, in systems where it is not achievable
(e.g., systems within the historic range of variability but altered to provide specific societal
benefits that are still in demand), an environmental flow strategy based on the natural flow
regime can be prescribed (see: Landres et al 1999; Keane et al 2009).
Environmental flows attempt to restore particular characteristics of the natural flow
regime to help support biodiversity, ecological function, and desired ecosystem services when
management options are limited by social demands (Acreman & Dunbar 2004; Arthington
2012). In some river systems, a return to natural conditions is not possible or desirable but the
river still retains ecological value. In cases where restoration goals are the maintenance and
prevention of further ecosystem degradation, a holistic approach can be used where knowledge
of the fluvial processes that structured existing ecosystems is paired with the current, altered
flow regime to form an environmental flow prescription (Arthington & Pusey 2003; Poff et al.
2003; Richter et al. 2003; Tharme 2003; Acreman et al. 2014).
51
In this paper, we propose an environmental flow prescription for the highly regulated and
significantly altered Atchafalaya River Basin (ARB), Louisiana (Figure 4.1). We examine the
physical and hydrologic changes in the ARB that make it a hybrid ecosystem and propose an
environmental flow prescription that functions within the current federal flow mandate to restore,
to the extent possible, the basin-wide flow conditions necessary to sustain important habitat and
complement existing restoration goals.
Study System
The ARB is the largest contiguous wetland in North America (Ford & Nyman 2011) and
the keystone of a flood mitigation effort that protects large areas of Louisiana from inundation
including substantial port infrastructure on the Lower Mississippi River and the city of New
Orleans. Its development into a federal floodway, and the resulting water management model,
has altered the physical landscape threatening ecologically important and socially desirable
habitat and creating a hybrid ecosystem (Piazza 2014).
In 1928, the ARB was designated a principal floodway of the Mississippi River and
Tributaries Flood Control Project to be maintained and operated by the U.S. Army Corps of
Engineers (USACE). To ensure its flood carrying capacity the ARB has been significantly
modified: basin area has been reduced to 26% of its historic size by flood protection levees
(Lambou 1990; Sabo et al. 1999); 22 natural distributaries were cut-off from the main channel;
new channels for freshwater distribution were constructed; and the main channel of the
Atchafalaya River was leveed for the first 85 km of its length to contain its flow (Reuss 2004).
Also, bank stabilization and river engineering caused a rapid disconnection of swamp habitats
from the Atchafalaya River and its distributaries (Piazza 2014).
52
The increased capacity of the main channel and a more efficient flow path to the Gulf of
Mexico contributed to the Atchafalaya River capturing an increasing proportion of Mississippi
River flow. To prevent total capture of the Mississippi River by the Atchafalaya River, the Old
River Control Complex (ORCC) was completed in 1963 to regulate flow from the Mississippi
River into the ARB. The authorizing legislation for ORCC requires that the annual flow
distribution between the Mississippi, Red, and Atchafalaya Rivers be in proportions that
occurred in 1950, when 70% of total flow discharged down the Mississippi and 30% discharged
through the ARB. Because the Red River flows directly into the ARB, the ORCC regulates flow
only from the Mississippi River. Flow through ORCC, z, can be conceptualized with the
equation:
z = 0.3 (x+y) – x
(Eq. 1)
where x is the flow in the Red River and y is the flow in the Mississippi River. The result is 6093% of the flow in the Atchafalaya River comes from the Mississippi River (Mossa 1996),
maintaining a seasonal flow regime that mimics the Mississippi River and results in seasonal
inundation of floodplain forests and riverine wetlands (Piazza et al. 2014). With the exception of
flood events, the USACE meets this 70/30 flow distribution on a daily basis allowing for a
±7.5% operational margin (Water in the Basin Committee 2002; Piazza 2014).
Despite extensive engineering works, the ARB maintains large expanses of floodplain
inundation, supports large areas of remote wild lands, high levels of biodiversity, important
habitat (Reuss 2004; Ford & Nyman 2011; Piazza 2014), and provides market and non-market
ecosystem services valued in the billions of dollars annually (Cardoch & Day Jr 2001;
Atchafalaya Basin Program 2014). Especially important are the baldcypress (Taxodium
53
distichum) – water tupelo (Nyssa aquatica) swamp forests, which are not only ecologically
critically important but also an integral part of the economy and culture of the region.
These swamp forests make up 43% (106,227 ha) of the Lower Atchafalaya Floodway
(Figure 4.2; Faulkner et al. 2009) and support rapid nutrient removal (Chambers et al., 2005;
Rivera-Monroy et al., 2010) and carbon storage (Watt & Golladay 1999). They also provide
critical habitat for many species (Gooding et al. 2004; Crook 2008; Ernst & Lovich 2009),
especially for juvenile crawfish, which represent a direct intermediate link in the food web
between detritus material and recreationally and commercially important fish species in the ARB
(van Beek et al. 1979; Lambou 1990; Bryan et al. 1998). When flooded, cypress-tupelo swamps
are “hot-spots” for commercial crawfishing, the dominant commercial fishery in the ARB,
producing crawfish yields more than 100 times greater than other swamp habitats (Huner & Barr
1991; Chambers et al. 2005).
Cypress-tupelo swamp productivity and reproduction is determined by the timing,
frequency, duration, and spatial distribution of floodplain inundation events, making water stage
rather than discharge, most relevant to forest health. Baldcypress depend on specific hydrological
cycles for regeneration (Conner et al. 1986; Kozlowski 1997; Keim et al. 2006) but can survive
and grow in nearly permanent inundation, commonly living 400-600 years, with trees found to
exceed 1600 years in age (Stahle et al. 1988; Wilhite & Toliver 1990; Keeland & Young 1997).
Both species can regenerate in damp and frequently inundated soils but seeds will not germinate
under water; total submergence for 4-5 weeks will kill seedlings (Conner & Buford 1998).
Due to water management problems, cypress-tupelo swamps in the ARB are at risk.
Faulkner et al. (2009) estimate that only 5.8% of cypress-tupelo forests in the ARB can
regenerate naturally as a result of hydrologic changes, making them a primary focus of
54
restoration efforts (Atchafalaya Basin Program 2014). Current restoration projects in the ARB
involve water management in cypress-tupelo swamp forests but only address the spatial
distribution of water within Water Management Units – distinct hydrologic sub-units of the ARB
(USACE, 2000). These projects, which aim, among other things, to prevent flood-induced stress
and mortality in cypress-tupelo swamps are local in scope and constrained by the flow regime at
ORCS that ultimately determines the timing, frequency, and duration of flood events. The daily
flow mandate may limit large-scale restoration alternatives, potentially threatening further loss
and degradation of cypress-tupelo forests in the ARB (Chambers et al. 2005). Therefore, we
investigate whether the current flow mandate befits restoration needs and propose an
environmental flow prescription, based on current scientific understanding of flow-ecology
relationships in cypress-tupelo swamp forests, as a potential way to sustain existing cypresstupelo forest habitat, and associated ecosystem functions and services, through large-scale flow
management in the ARB.
Data and Methods
Specific-gage Analysis
We investigated the stage-discharge relationship along the Atchafalaya River using daily
hydrologic data acquired from the USACE (2013) for the period of record for the Simmesport
(USGS #07381490) and Butte LaRose (BLR; USGS #07381515) gages in the ARB (Table 4.1).
Simmesport accounts for all flow into the ARB from the Red and Mississippi Rivers and
provides discharge data recorded daily at 14:00 Greenwich Mean Time (GMT). There are no
other substantial inflows into the ARB. BLR provides stage data recorded daily at 14:00 GMT, is
tied to flooding conditions throughout the Lower Atchafalaya Floodway (Allen et al. 2008), and
is a benchmark for current restoration efforts. First, we employed specific-gauge analysis
55
(Biedenharn & Watson 1997; Blench 1969) to these hydrologic data to track changes in stage
over time for a fixed discharge. We then used the changes in the stage-discharge relationship to
determine the analysis period for this study.
Analysis of the Current Flow Regime
We conducted a one-period analysis of the flow regime of the ARB from 1988-2012
using Indicators of Hydrologic Alteration (IHA) software (Richter et al. 1996; Richter et al.
1997; Mathews & Richter 2007). IHA calculates characteristics of hydrologic regimes and
identifies ecologically-relevant hydrologic parameters of specific rivers, detailing the magnitude,
timing, frequency, rate of change, and duration of flow events. Given the primacy of the floodcontrol mission for water management in the ARB, IHA identified key aspects of the current
flow regime (environmental flow components) necessary to maintain desired geomorphic and
hydraulic characteristics of the floodway (Mathews & Richter 2007). These environmental flow
components are based on flow exceedance probability: low flows represent base flows; extreme
low flows represent the 10th percentile of all low flows; high flows are greater than low flows up
to a two-year flow event; small flood events are 2-10 year flow events; and large floods are equal
to or greater than the 10-year flood event. Paired with an understanding of the altered system and
current channel-floodplain interaction thresholds, IHA provided a hydrological basis for
individual components of the environmental flow prescription.
Environmental Flow Prescription
We defined an environmental flow prescription as the future modeled flows required to
achieve basin-wide flow conditions necessary to sustain cypress-tupelo forests in the ARB. We
based the flow prescription on the Sustainability Boundary Approach (Richter 2010), which sets
limits or a range of acceptable flows for water infrastructure operations to sustain social benefits
56
and meet environmental goals in freshwater systems. In this approach, boundaries (flow targets)
are understood to be flexible to accommodate changing social values and new scientific
understanding of flow-ecology relationships and serve as a basis for consideration of
management alternatives (Richter 2010). Next, we used the USACE Regime Prescription Tool
(HEC-RPT; http://www.hec.usace.army.mil/software/hec-rpt/) to develop the environmental
flow prescription for the ARB and assess performance of the current flow regime in relation to
future modeled flows. HEC-RPT was adapted from the Building Block Methodology (King et al.
2008) and the Holistic Approach (Arthington et al. 1992) for defining environmental flows
(Richter et al. 2006).
Flow prescriptions in HEC-RPT are constructed using three types of flow components.
Low flows are the foundation of the time series and are defined for each day in a calendar or
water year. Pulse flows and flood flows deviate from low flow and are defined by timing,
duration, magnitude, and duration of peak flow. Flow prescriptions have one series of low flows
but can have multiple pulses and floods. HEC-RPT also tracks differences in flow volume
between the imported hydrological record and the environmental flow prescription, especially
useful in the ARB where flow is based on a percentage of latitudinal flow.
The modeled environmental flow components were defined based on a review of
published literature and reports specific to the ARB that detail important flow regime
characteristics (flow targets) for cypress-tupelo forests and associated biogeochemistry and
aquatic wildlife (Table 4.2). Similar to Rood et al. (2003), flow targets were based on optimum
stage heights necessary for healthy cypress-tupelo swamps. Here, flow targets were determined
using the average discharge of all flow events (at Simmesport) that produced desired stage at
BLR during the study period.
57
We used flow targets from the literature and IHA analysis of the current flow regime to
model flood and dry season flows to serve as a baseline, from which modeled flood pulses and
extreme low flows deviate. To account for inter-annual variations in flow, we defined each
calendar year as either wet (top 25%), average (middle 50%), or dry (bottom 25%) based on
mean annual flow (Luce & Holden 2009). To account for intra-annual variations in flow, we set
minimum flows for the flood season -- January 5 to April 15 -- for all years, and defined the
flood season as extending to May 15 for average years and to June 1 in wet years. Setting
minimum flood-season flows ensures that hydrologic conditions prevent the establishment of
bottomland hardwoods and allow cypress-tupelo to remain the dominant forest type (van Beek et
al. 1979). Minimum flood-season flows also provide access to important habitat for crawfish and
other fishes and allow commercial and recreational fishermen to access favored areas (Water in
the Basin Committee 2002; Louisiana Crawfish Promotion & Research Board 2009; Alford &
Walker 2013). We also set maximum flows for the dry season, which we defined as: June 15October 31 for dry years, June 15-October 15 for average years, and July 1-October 15 for wet
years. Maximum-allowed dry season flows: 1) ensure a majority of cypress-tupelo swamps drain
to maximize diversity of chemical habitat characteristics; 2) allow accumulated organic debris to
oxidize; 3) mitigate aquatic invasive species; and 4) support cypress-tupelo forest productivity
and regeneration (Bryan et al. 1998; Faulkner et al. 2009; Keim et al. 2006; Sabo et al. 1999).
Next, we used HEC-RPT to model a small flood and a high-flow pulse during wet and
average years, respectively, and used IHA results as a guide for magnitude, rise and fall rates,
and duration. The time window for this spring pulse is March 15-May 31 to ensure that most
annual flooding occurs while temperatures are below the median as part of a strategy to
maximize habitat diversity and reduce hypoxia (Sabo et al. 1999). The magnitude of this flood
58
pulse ensures there is good overbank flow to flush hypoxic water and replenish sediment and
nutrients in cypress-tupelo swamps (Sabo et al. 1999; Water in the Basin Committee 2002;
Alford & Walker 2013). In dry years, intended to coincide with natural climatic droughts, we
modeled a flow reduction to maximize natural cypress-tupelo regeneration potential (Bryan et al.
1998; Faulkner et al. 2009). Again, rise and fall rates of flow were held within the current range
of change rates based on IHA results. These environmental flows were then modeled over the
entire study period.
Because our aim was to make this prescription useful to mangers, we produced annual,
seasonal, quarterly, and monthly modeled flow volumes. These modeled flow volumes were then
used to evaluate the deviation of the flow prescription from current flows to assess the feasibility
of implementing the flow prescription and meeting the 70/30 flow mandate over time intervals
that are more useful for ecosystem management and restoration goals.
Results
Specific-gage Analysis
Specific-gage analysis revealed 1988-2012 as an acceptable study period because, after a
phase of rapid adjustment, stage at BLR was relatively stable during this time (Figure 4.3). A
strong (R2=0.98) relationship between discharge at Simmesport and stage at BLR without any
lag adjustment (Figure 4.4) supported use of flow targets based on desired stage at BLR.
Compared to the pre-ORCS time period, 1930-1962, mean monthly discharge at Simmesport
showed an increase of 12-92% for the study period (Table 4.3). Compared to early stage records
at BLR, 1959-1974, mean monthly stage has decreased 24-43% for the study period (Table 4.3).
Analysis of Current Flow Regime
59
IHA analysis revealed mean annual flow (stage at BLR) for the study period (1988-2012)
as 6450 m3s-1 (2.8 m at BLR) with median dates for maximum and minimum flows March 28th
and October 22nd, respectively. Six wet years (1991, 1993, 1998, 2008, 2009, 2011) had a mean
annual flow of 8000 m3s-1 (3.5 m at BLR), and median dates for maximum and minimum flows
were May 17th and October 24th, respectively. Thirteen average years (1989, 1990, 1992, 19941997, 1999, 2001-2004, 2010) had a mean annual flow of 6600 m3s-1 (3.0 m at BLR), and
median dates for maximum and minimum flows were April 15th and October 12th, respectively.
Six dry years (1988, 2000, 2005-2007, 2012) had a mean annual flow of 4600 m3s-1 (1.9 m at
BLR), and median dates for maximum and minimum flows were February 7th and August 31st,
respectively (Figure 4.5).
IHA also identified values for five environmental flow components for the study period
(Table 4.4), ranging from 935 m3s-1 (0.2 m at BLR) for extreme low flows to almost 20,000 m3s-1
(6.8 m at BLR) for large floods. Interestingly, IHA classified both established backswamp
inundation (6200 m3s-1; 2.8 m at BLR) and overbank flooding (8090 m3s-1; 3.7 m at BLR)
thresholds in the lower ARB floodway (Hupp et al. 2008) as low flows based on exceedance
probability. Additionally, the threshold for widespread, levee-to-levee flooding (17,300 m3s-1;
stages above 6.1 m at BLR; Alford & Walker 2013) was classified as a small flood, based on
exceedance probability.
Small floods typically had the longest duration, and most extreme low-flow events were
relatively short in duration (Table 4.5). High-flow pulses had a median duration of 22 days and a
minimum threshold of 8920 m3s-1 and small floods a median duration of 67 days and a minimum
peak flow of 13,590 m3s-1. The median date for high flows was March 8 and for small floods
60
April 24. Rise and fall rates ranged from approximately 310 m3 s-1 to -370 m3 s-1 for both highflow pulses and small flood events (Table 4.5).
Environmental Flow Prescription
Flow recommendations from the literature were paired with IHA analysis to produce a
flow prescription for dry, average, and wet years that falls within the current range of variability
(Figure 4.6; Table 4.6). The mean annual flows for the modeled wet, average, and dry years were
7120 m3 s-1, 6220 m3 s-1, and 4920 m3 s-1, respectively.
Annual
Overall, the environmental flow prescription met the +/-7.5% operational margin of the
70/30 flow mandate in only seven years. Over the study period, modeled annual flows ranged
from 76-121% of current flows. Annually, the environmental flow prescription required 90% of
current flows for wet years, 95% of current flows for average years, and 106% of current flows
for dry years. Current flow for all wet years (6/6) and a majority of average years (8/13) showed
higher mean annual flow than modeled, and most dry years (4/6) showed lower mean annual
flows than modeled (Table 4.7).
Seasonal
When flow volumes for flood and dry seasons were calculated separately, a different
picture emerged (Table 4.8). Current flows fluctuated around the minimum flow target in the
flood season and the maximum flow target in the dry season. When modeled minimum flows for
the flood season were <100% of current flows, the flow prescription was met and a 70/30 flow
distribution was possible for the season. Likewise, when prescribed maximum flows for the dry
season were > 100% of current flows, the flow prescription was met and the 70/30 flow
distribution was possible for the season. Both conditions were met in only three years (1988,
61
1991, 1994). An additional three years (1999, 2002, 2012) were within the +/-7.5% operational
margin.
Looking at flood and dry seasons separately, eight years (32%) met the operational
margin during the flood season (Table 4.8). Seven years (28%) met the minimum requirements
of the flow prescription for flood season, meaning the flow prescription was possible within the
70/30 flow mandate. For the dry season, the operational margin was met during four years
(16%). Another three years (12%) met the maximum flow requirements of the flow prescription
for the dry season, meaning less actual flow occurred that season than the maximum prescribed
and therefore the 70/30 flow mandate was achievable.
Quarterly
Quarterly (calendar year) flow volume calculations revealed further variations in actual
and prescribed flows (Table 4.9). Only four years (16%; 1991, 1994, 1997, 2002) met the flow
mandate and the flow prescription in all four quarters. During January-March, 18 years (72%)
were within the operational margin of the 70/30 flow mandate or met the requirements of the
flow prescription. April-June, which was counted as part of the flood season (minimum required
flows), had 15 years (60%) within the operational margin of the 70/30 flow mandate or met the
requirements of the flow prescription.
The dry season quarter of July-September showed only eight years (32%) within the
operational margin or able to meet the maximum required flows of the flow prescription. Further,
years that did not meet the flow prescription had 10-56% more flow than prescribed. OctoberDecember begins during the prescribed dry season but ends during the transition period before
the flood season. Treated as a dry season period, 19 years (76%) met the 70/30 mandate within
the operational margin or were able to meet the requirements of the flow prescription.
62
Monthly
Monthly flow volumes provided a more detailed look at differences between the flow
prescription and current flows. The flow mandate and flow prescription were met an average of
three months per year for dry years, six months for average years, and five months for wet years
(Table 4.10). Only one year (1997) met the flow mandate and prescription for each month during
the flood season (January-May) and two years (1988, 2002) met the flow mandate and
prescription for the dry season (July-October). During the flood season, the flow mandate and
prescription were met most often in January and February (68% of years), March (56%), and
May (60%). April showed values that met both criteria in only 20% of years. During the dry
season the flow mandate and prescription were met most often in September and October (76%),
followed by August (48%). July met the flow mandate and prescription only twice (8%). During
the transition period in the flow prescription, current flows were evaluated only for adherence to
the flow mandate. The mandate was met in only 12% of years during June and November and
16% of years during December.
Discussion
Nearly a century of significant anthropogenic alterations in the ARB have created a
hybrid ecosystem that challenges the current water management model. Although there has been
an increase in mean monthly discharge over the period of record there has been a decrease in
stage height at an important location in the ARB. This change in stage-discharge relationship has
ecological implications as it affects the timing, duration, and magnitude of floodplain inundation
events. Results from our specific-gage analysis, however, suggest this stage-discharge
relationship has been in equilibrium for the past 25 years, exhibiting a temporal response pattern
similar to the rate law in fluvial geomorphology proposed by Graf (1977). Despite these
63
hydrologic changes, the one-period IHA analysis showed that flow-ecology recommendations
for the ARB’s cypress-tupelo swamp forests are within the current range of flow variability. This
finding suggests environmental flows can be complementary with the desired hydraulic and
geomorphic characteristics of the flood control mission.
The results from modeling the environmental flow prescription over different time
periods shed light on the ability to meet the federal flow mandate while implementing
environmental flows and raised some important logistical issues. We found limited success in
meeting the flow mandate with an annual accounting of flow volume. Further, when examining
flow volumes on a seasonal basis, three of the years that met the flow mandate in the annual
accounting – 1995, 2003, and 2011 – were contrary to the intentions of the flow prescription –
low flows in the flood season and high flows in the dry season. The annual and seasonal
accounting of flow volume also raises the logistical issue of accurately predicting how wet the
coming year or season will be. The general inability to predict annual or seasonal flows with
high levels of certainty, and the lack of success found in this study, eliminates them as a feasible
option for environmental flow implementation in the ARB.
We found greater success in meeting both the flow mandate and the flow prescription
with quarterly and monthly accounting of flow volumes. A majority of months and quarters had
greater than 50% success rates with late dry-season months and first-quarter success rates greater
than 70%. The lack of success for the dry-season quarter (July-September) could pose a
significant water management issue in meeting the flow mandate. Overall, deviations from a
daily 70/30 implementation would likely be necessary during the dry season, but many years
would likely meet the flood-season flow requirements with minimal deviation from a daily 70/30
implementation, thereby greatly simplifying flow control management.
64
Given that the flow mandate is an annual target, from a decision-making perspective, a
monthly approach to environmental flows in the ARB appears to have real potential for
implementation. The ARB’s location at the outlet of a large river basin enables 28-day forecasts
for the Lower Mississippi River based on water currently in the watershed and rainfall expected
in the next 24 hours (NOAA 2015). This ability to forecast can reduce decision-making
uncertainty in meeting both the flow mandate and environmental flow targets. The 22-day highflow pulse modeled for average water years can be implemented within forecasted future flows,
though the small flood and extreme low flow modeled for wet and dry years, respectively, would
require a higher level of confidence in expected future flows. Further, a monthly approach can
provide the management flexibility needed to mitigate environmentally and socioeconomically
damaging flow events. Since 1996 there have been seven 2-3% increases in flow through ORCS
for 7-16 days during the flood season to increase crawfish production, improve water quality,
and protect aquatic resources (Kozak et al. 2015). These reactionary measures are essentially a
stop-gap approach to ecosystem management, are not without cost, and will not serve the region
in the future when precipitation and drought events are expected to be more variable (IPCC
2007).
Before any environmental flows can be implemented in the ARB there is a need for
hydraulic modeling to better refine the estimation of inundation extent and patterns and drying of
swamp land. Current estimates are based on historic Landsat imagery and only appropriate for
use at the basin scale or within specific Water Management Units (Allen et al. 2008). Improved
hydraulic modeling and improved validation using remotely-sense imagery would further
understanding of site-specific inundation patterns (Jung et al. 2012) and flow-ecology
relationships facilitating refinement of the environmental flow prescription.
65
Downstream considerations on both the Atchafalaya and Mississippi Rivers are needed
before any significant changes to flow distribution at ORCS can take place. The Atchafalaya and
Wax Lake Deltas (Figure 4.1) are currently the only prograding deltas on the Louisiana coast and
play a role in long-term coastal restoration efforts. The impact to sediment delivery and
dynamics that could occur with a change in flow distribution at ORCS is also important to the
Birds Foot Delta of the Mississippi River, where efforts to reverse coastal erosion and land-loss
are ongoing. Such considerations complicate straightforward implementation of an
environmental flow prescription in the ARB but could be included in monitoring and adaptive
management protocols to assess and limit negative impacts.
Conclusions
The need for increased flexibility in water management for restoration efforts in the ARB
is apparent. The environmental flow prescription presented here connects ecosystem science with
water management in the ARB while accommodating the federal flow mandate, provided the
implementation of the current flow mandate is loosened to longer time scales. An environmental
flow prescription would provide the necessary structure for implementing future water
management initiatives, and perhaps most importantly, it would provide the opportunity to
complement current, small-scale restoration projects with basin-wide flow management.
Prescribing environmental flows for river systems like the ARB can be challenging,
because institutional barriers make it difficult to change how rivers are managed (Wondolleck &
Yaffee 2000). This makes approaches to setting environmental flows within an established
decision space attractive. Because water demands are expected to increase in the future, a
broader implication of this work is that it may be in the best interest of water managers in waterwealthy regions to establish the environment as a legitimate user of water now before the need
66
for environmental flows becomes a more contentious issue. Such a precedent can go a long way
toward sustaining local livelihoods dependent on natural and hybrid ecosystems and represents a
concerted effort to consider the environment in future water management decisions.
67
Table 4.1. U.S. Geological Survey real-time stream gages used in this study.
Gage Name
USGS ID
USACE ID
Simmesport
Butte LaRose
7381490
7381515
03045
03120
Latitude
Longitude
30.9825000
30.2813888
-91.7983333
-91.6866666
68
River Mile
4.9
64.8
Period of Record
1930-present
1959-present
Table 4.2. Environmental flow targets from scientific literature and reports for the Atchafalaya
River Basin used to create the environmental flow prescription.
Source
Purpose
Recommendation
van Beek et al.
1979
Habitat diversity
Bryan et al. 1998
Ideal watering and
dewatering cycle
Sabo et al. 1999
Hypoxia reduction,
aquatic and forest
productivity
Water in the
Basin Committee
2002
Water quantity and
quality;
socioeconomics
Water begins to flow into backswamp areas at 2.7 m, good overbank
flow at 5.2 m. Introduce additional flow January-April if water
temperatures are below 20°C, avoid additional flow May-December
Keim et al. 2006
Cypress-tupelo
forest productivity
and regeneration
Low-water events, ≈0.6 m at Butte LaRose, required to maximize
cypress-tupelo regeneration potential. Widespread artificial planting
possible at ≈1.6 m at Butte LaRose
Hupp et al. 2008
Sedimentation and
inundation patterns
Study sites in Lower Atchafalaya Floodway experienced flooding in
backswamp areas at 2.8 m at Butte LaRose and banks were
overtopped around 3.7 m
Faulkner et al.
2009
Cypress tupelo
natural regeneration
potential
Prolonged extreme low-flows (0.5 m at Butte LaRose) maximize
natural and artificial regeneration potential of cypress-tupelo forests
Louisiana
Crawfish
Promotion &
Research Board
2009
Socioeconomics,
crawfish harvest
and production
Water begins to flow into backswamp areas at 2.7 m at Butte
LaRose, good overbank flow at 5.2 m. Crawfish benefit from 2 month
summer drought and floodwaters in mid-winter
Fisheries
production
3.6 m flood stage at Butte LaRose beneficial for fisheries production,
6.1 m flushes hypoxic water and sediment in some areas, deposits
sediments and nutrients in others. Fisheries production optimized
with approximate stage of 4.0 m for 4-5 months during winter-spring
months
Alford & Walker
2013
Minimum of 7 months of flooding for areas to be dominated by
cypress-tupelo
In Lower Atchafalaya Floodway: 2.7 m at Butte LaRose by early
January, increase to 4.3 m by mid-April, reduce water levels to 1.5 m
by mid-June. Prolonged dry periods should coincide with natural
climatic drought cycles
Annual flood pulse should occur when temperatures are below the
median. Low water levels should occur during high temperatures,
prolonged low water levels beneficial to aquatic and forest
productivity
69
Table 4.3. Historic (1930-1962, 1959-1974) and study-period (1988-2012) mean monthly
discharge and mean monthly stage trends at the Simmesport and Butte LaRose gages in the
Atchafalaya River Basin. The years 1930-1962 span the beginning of the period of record at the
Simmesport gage to the establishment of the current flow policy in 1963. The years 1959-1974
span the first 15 years of the period of record for the Butte LaRose gage.
Month
January
February
March
April
May
June
July
August
September
October
November
December
3 -1
Discharge at Simmesport, LA (m s )
1930-1962
1988-2012
% Change
4610
7210
56
6260
8050
29
7600
9220
21
8330
9310
12
7750
9320
20
5960
7990
34
4370
5770
32
2660
4010
51
1890
3260
72
1920
3450
80
2170
4050
87
3070
5880
92
70
Stage at Butte LaRose, LA (m)
1959-1974 1988-2012 % Change
4.2
3.1
-26
4.6
3.5
-24
5.4
4
-26
6
4
-33
5.7
3.9
-32
4.6
3.5
-24
3.3
2.5
-24
2.4
1.6
-33
2
1.3
-35
2.3
1.3
-43
2.4
1.6
-33
3.5
2.4
-31
Table 4.4. Ranges of discharge and stage values (1988-2012) corresponding to the
environmental flow components defined by one-period IHA analysis for the ARB. Note the
overlap in discharge and stage ranges exhibited by the high-flow pulse, small flood, and large
flood components caused by the return interval of a flow event of that duration and magnitude
(see Mathews and Richter 2007).
3 -1
Discharge (m s )
Extreme low flow
Stage (m)
935 - 2520
0.2 - 0.9
2550 - 8920
0.9 - 3.9
High Flow pulse
8950 - 13600
4.1 - 5.5
Small flood
8950 - 17700
4.1 - 6.2
Large flood
9010 - 19600
4.1 - 6.8
Low flow
71
Table 4.5. Results of IHA percentile analysis of current flows showing range of discharges, associated stages at Butte LaRose (in
parentheses), and variability of the different environmental flow components.
IHA Percentile Data
72
EFC Flow Parameters
Extreme low peak
Extreme low duration
Extreme low timing
Extreme low freq.
High flow peak
High flow duration
High flow timing
High flow frequency
High flow rise rate
High flow fall rate
Small Flood peak
Small Flood duration
Small Flood timing
Small Flood freq.
Small Flood rise rate
Small Flood fall rate
Large flood peak
Large flood duration
Large flood timing
Large flood freq.
Large flood rise rate
Large flood fall rate
10%
3 -1
1900 m s (0.7 m)
1 day
September 1
-1
0 year
3 -1
9340 m s (4.2 m)
8.15 days
December 6
-1
0 year
3 -1 -1
90 m s d
3 -1 -1
-370 m s d
3 -1
13630 m s (5.5 m)
34.6 days
February 5
-1
0 year
3 -1 -1
60 m s d
3 -1 -1
-350 m s d
3 -1
18040 m s (6.2 m)
66 days
March 29
-1
0 year
3 -1 -1
180 m s d
3 -1 -1
330 m s d
25%
3 -1
2160 m s (0.7 m)
1 day
September 29
-1
1 year
3 -1
9990 m s (4.5 m)
11.38 days
January 28
-1
1 year
3 -1 -1
130 m s d
3 -1 -1
-250 m s d
3 -1
13900 m s (5.6 m)
45 days
March 12
-1
0 year
3 -1 -1
140 m s d
3 -1 -1
-290 m s d
3 -1
18040 m s (6.2 m)
66 days
March 29
-1
0 year
3 -1 -1
180 m s d
3 -1 -1
330 m s d
50%
3 -1
2340 m s (0.9 m)
2.5 days
October 24
-1
3 year
3 -1
10430 m s (4.6 m)
22.25 days
March 9
-1
2 year
3 -1 -1
170 m s d
3 -1 -1
-190 m s d
3 -1
14720 m s (5.7 m)
67 days
April 25
-1
0 year
3 -1 -1
190 m s d
3 -1 -1
-270 m s d
3 -1
18820 m s (6.3 m)
86 days
April 26
-1
0 year
3 -1 -1
250 m s d
3 -1 -1
250 m s d
75%
3 -1
2400 m s (0.9 m)
7 days
November 24
-1
5.5 year
3 -1
11390 m s (4.9 m)
28 days
April 24
-1
3 year
3 -1 -1
240 m s d
3 -1 -1
-150 m s d
3 -1
15520 m s (5.8 m)
96 days
May 28
-1
1 year
3 -1 -1
260 m s d
3 -1 -1
-180 m s d
3 -1
19600 m s (6.8 m)
106 days
May 24
-1
0 year
3 -1 -1
320 m s d
3 -1 -1
170 m s d
90%
3 -1
2480 m s (0.9 m)
33.7 days
December 24
-1
7.4 year
3 -1
12470 m s (5.2 m)
47.45 days
June 19
-1
4.4 year
3 -1 -1
320 m s d
3 -1 -1
-110 m s d
3 -1
17310 m s (6.1 m)
110 days
June 17
-1
1 year
3 -1 -1
320 m s d
3 -1 -1
-120 m s d
3 -1
19600 m s (6.8 m)
106 days
May 24
-1
0 year
3 -1 -1
320 m s d
3 -1 -1
170 m s d
Table 4.6. The environmental flow prescription for the Atchafalaya River Basin, Louisiana.
Shown here are the individual flow targets of the prescription, including minimum flood season
flows, maximum dry season flows, high-flow pulses, small floods, and flow reductions.
Flow Component
Low flows
Early January minimum
flow
Mid-April minimum flow
May 15 minimum flow
(Average years only)
June 1 minimum flow
(wet years only)
Dry season max. flow
(Dry and average years)
Dry season max. flow
(Wet years)
Pulse flow/drawdowns
Stage at
BLR (m)
Timing/Duration
Approximate
Discharge at
Simmesport
3 -1
(m s )
IHA
January 5
2.7
6340
Low flow
April 15
4.3
9850
High flow
May 15
4.3
9850
High flow
June 1
4.3
9850
High flow
June 15-October 15
1.5
4020
Low flow
July 1-October 15
1.5
4020
Low flow
Average year spring high
flow
22 days between March
15 and May 15
5.2
12300
High flow
pulse
Wet year small flood
67 days between March
15 and May 31
6.1
17300
Small flood
July 1 - October 31
0.7
1930
Extreme low
flow
Dry year drawdown
73
Table 4.7. Annual breakdown of flow prescription volumes relative to actual flows. The percent
deviation in flow is the deviation of the prescribed flow from actual flow. Shaded cells represent
annual flow volumes that meet the current +/-7.5% operational margin.
Year
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Classification
Dry
Average
Average
Wet
Average
Wet
Average
Average
Average
Average
Wet
Average
Dry
Average
Average
Average
Average
Dry
Dry
Dry
Wet
Wet
Average
Wet
Dry
Percent
Deviation
9
-11
-17
-9
9
-24
-8
0
-9
-15
-2
3
21
3
-4
4
-12
-8
17
-11
-8
-9
-12
-4
16
74
Table 4.8. Seasonal breakdown of flow prescription flow volumes relative to actual flows. The
percent deviation in flow is the deviation of the prescribed flow from actual flow. Dark grey cells
represent seasonal flow volumes that meet the current +/-7.5% operational margin. Light grey
shaded cells represent seasons that met the flow prescription and were able to meet the 70/30
flow mandate. Flood season: dry years = January 5 to April 15; average years = January 15 to
May 15; wet years = January 15 to June 1. Dry season: dry years = June 15 to October 31;
average years = June 15 to October 15; wet years = July 1 to October 15.
Year
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Classification
Dry
Average
Average
Wet
Average
Wet
Average
Average
Average
Average
Wet
Average
Dry
Average
Average
Average
Average
Dry
Dry
Dry
Wet
Wet
Average
Wet
Dry
Percent deviation
Flood Season
Dry Season
-6
-12
-9
-13
28
-8
-16
25
27
-25
-1
-7
82
10
1
27
13
-17
60
4
-4
23
-5
13
2
29
-29
-30
26
-15
-51
9
-32
-27
-17
-18
-1
-43
0
6
-15
-31
-31
-26
-48
-35
-19
-29
-19
1
75
Table 4.9. Quarterly breakdown of flow prescription volumes relative to actual flows. The
percent deviation in flow is the deviation of the prescribed flow from actual flow. Dark grey cells
represent quarterly flow volumes that meet the current +/-7.5% operational margin. Light grey
shaded cells represent quarters that met the flow prescription and were able to meet the 70/30
flow mandate.
Year
Classification
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Dry
Average
Average
Wet
Average
Wet
Average
Average
Average
Average
Wet
Average
Dry
Average
Average
Average
Average
Dry
Dry
Dry
Wet
Wet
Average
Wet
Dry
Jan-March
-13
-23
-16
-34
11
-20
-16
14
28
-29
-17
-18
100
-3
5
5
-1
-23
57
1
-2
17
-12
35
-2
Percent deviation
April-June July-Sept
39
27
-8
-25
-22
-19
5
21
98
-15
-4
-51
-42
9
2
-22
-2
-13
-9
-6
14
-23
29
2
18
-49
11
12
-31
27
40
-10
-2
-23
14
-34
36
-19
-1
-56
-11
-37
6
-16
-12
-29
-13
-23
38
0
76
Oct-Dec
12
39
15
-5
-8
-34
16
49
-26
54
12
16
12
-4
13
16
-31
38
-26
1
36
-44
36
-7
46
Table 4.10. Monthly breakdown of flow prescription volumes relative to actual flows. The
percent deviation in flow is the deviation of the prescribed flow from actual flow. Dark grey cells
represent monthly flow volumes that meet the current +/-7.5% operational margin. Light grey
shaded cells represent monthly flow volumes that met the flow prescription and were able to
meet the 70/30 flow mandate. June, November, and December are transition period months and
not subject to maximum or minimum flows for the flow prescription, therefore they were only
evaluated for adherence to the flow mandate.
Year
Classification
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Dry
Average
Average
Wet
Average
Wet
Average
Average
Average
Average
Wet
Average
Dry
Average
Average
Average
Average
Dry
Dry
Dry
Wet
Wet
Average
Wet
Dry
Jan
-32
-23
30
-54
-11
-35
13
17
50
-12
-26
4
145
36
2
3
-5
-41
90
-27
15
-6
-22
-14
-11
Feb
-16
-10
-27
-24
47
-7
-21
16
3
-21
-12
-40
207
7
-12
55
-5
-32
29
10
7
35
-33
109
-12
March
16
-32
-27
-15
11
-14
-27
9
38
-42
-14
-7
41
-25
29
-16
4
13
65
29
-14
27
6
-9
17
April
13
-2
8
30
59
10
-9
70
39
-24
31
29
31
29
-11
82
55
17
80
21
-11
60
12
43
36
Percent Deviation
May June July Aug
70
80
30
25
24
-44
-53
13
-14
-65
-42
-7
4
-24
-12
42
63
-5
-16
-32
-4
-23
-51
-59
-27
-10
-15
16
-2
-65
-47
-15
-1
-60
-31
-16
-2
-49
-38
14
10
-4
-51
-16
-8
-32
-35
17
45
-25
-68
-38
45
-42
-15
19
-18
-52
2
40
6
-47
-25
-6
20
-50
-48
4
31
-13
-46
-15
17
5
-30
-10
-9
-21
-67
-47
0
-28
-53
-20
6
-37
-29
-16
-2
-44
-44
-29
-22
-45
-46
-13
41
37
-9
7
77
Sept
25
1
3
60
15
-39
43
36
22
45
47
87
-13
49
49
7
-2
-35
-15
-46
-28
3
2
9
3
Oct
10
4
12
86
26
-42
44
46
4
53
9
3
-14
26
6
34
0
-18
-48
-20
2
-46
10
39
-6
Nov
15
38
33
8
17
-18
28
35
-20
58
8
156
4
52
14
39
-23
31
-41
0
77
-54
63
37
36
Dec
11
85
5
-35
-23
-37
-5
65
-41
51
19
99
32
-35
17
-6
-47
93
5
14
43
-32
39
-38
93
Figure 4.1. The Atchafalaya River Basin (ARB), Louisiana. Also shown are the location of the
basin-wide flood control levees, major floodways within the ARB and the US Geological Survey
gages used in this study.
78
Figure 4.2. The spatial extent of cypress-tupelo swamp forests in the Lower Atchafalaya
Floodway, mapped following the Cowardin et al. (1979) National Wetlands Inventory
classification system.
79
Water Surface Elevation (m NAVD 1988)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
1959
1969
1979
1989
1999
2009
Figure 4.3. Specific-stage at Butte LaRose with a discharge of 3100 m3s-1 (~ 80 % flow
exceedance probability) at Simmesport, 1959-2012.
80
Water Surface Elevation (m NAVD 1988)
8.0
7.0
6.0
5.0
4.0
y = -1E-08x2 + 0.0006x - 0.6788
R² = 0.9829
3.0
2.0
1.0
0.0
0
2500
5000
7500
10000
12500
15000
17500
20000
Discharge at Simmesport (m 3 s-1)
Figure 4.4. Relationship of discharge at Simmesport and stage at Butte LaRose, 1988-2012.
81
Figure 4.5. Hydrograph showing mean daily flows and corresponding water surface elevation
(stage at BLR) for wet, average, and dry years during the study period (1988-2012). These flows
and stages resulted from the current flow regime, based on the basin-wide flow mandate.
82
Figure 4.6. The environmental flow prescription for the Atchafalaya River Basin, Louisiana.
Shown here are low flows, flood pulses, small floods, and dry-year flow. Established thresholds
for backswamp inundation and overbank flooding are also shown along with the upper bound of
extreme low flow events.
83
CHAPTER 5
SUMMARY
The many essential resources that rivers naturally provide to humans has resulted in their
status as coupled natural and human systems. While these benefits have contributed to quality of
life and helped shape society, society has also changed rivers to the extent that many major rivers
now function outside of their historic range of flow variability (Postel & Richter 2003). Human
alterations such as land-use change and channel modification have degraded large river systems
and, as a result, the ecosystem services that modern society depends on are impaired. The
restoration of ecosystem services and ecological function in these degraded systems is occurring
globally as a primary management goal (Palmer et al. 2005; Arthington et al. 2010). To be
successful, river management and restoration efforts require a strong understanding of the
relationship between the ecological needs of the aquatic system and socioeconomic demands
placed upon it.
I developed three separate projects focused on this relationship between the ecological
needs and the socioeconomic demands as they pertain to the management and restoration of the
Atchafalaya River Basin in Louisiana. The first project provides a critical analysis of the current
structure and process of restoration planning in the ARB and proposes a modified decisionmaking process to address the challenges associated with incorporating local stakeholders and
scientific methods into restoration decisions. The second project focused on the relationship
between flow regime in the ARB and the production of locally important ecosystem services and
related variables. The third project considers the potential for implementing environmental flows
while maintaining the primary water management objective of flood mitigation.
84
A proposed process for applying a structured decision making framework to restoration
planning in the Atchafalaya river basin, Louisiana, USA
This project was developed to 1) characterize how the current restoration planning
process contributes to stakeholder conflicts with managers in the ARB and to 2) propose a
decision-making process that addresses this issue while retaining the scientific integrity of the
restoration process. Based on meetings with restoration planners in the ARB and documented
stakeholder accounts identifying the perceived source of their conflict, it was apparent the public
hearings were an ineffective form of stakeholder involvement. They contribute to a perceived
back-end inclusion of stakeholder ideas and create a disconnect between project proposal and the
developed project. The proposed process for applying a structured decision-making framework
to restoration planning in the ARB seeks to address this issue by allowing for the inclusion of the
basin’s stakeholders throughout the planning process while maintaining the strong scientific
foundation through which restoration projects are currently developed.
Stakeholder participation is a necessary component of adaptive management, one that
helps build social capital and facilitates the establishment of the institutional diversity required to
restore environmental quality in complex, coupled natural and human systems. Over the longterm, the scientific foundation of the structured decision-making process can help reduce
uncertainty in decision-making, and, as part of a participatory process, it facilitates collaborative
learning by all stakeholders.
This proposal contributed to understanding the relationship between the ARB’s
stakeholders and the current restoration planning process. When presented to the Louisiana
Department of Natural Resources Atchafalaya Basin Program it achieved buy-in and a stated
desire to implement; however, implementation was derailed by a state emergency. The
85
opportunity to implement this proposal still exists with the planned update to the Atchafalaya
River Basin State Master Plan. If implemented, an empirical assessment of the effectiveness of
the structured decision-making process in meeting its stated objectives (e.g., reducing conflict,
promoting joint inquiry and learning, facilitating long-term commitment to conservation) would
contribute to the environmental decision-making literature.
Using flow-ecology relationships to evaluate ecosystem service trade-offs and
complementarities in the nation’s largest river swamp
This study was developed to assess the impact of various components of flow regime on
twelve ecosystem services and related variables in the ARB. Several of the relationships found
for the fisheries data and potential denitrification correspond to those established in the literature.
While these results cannot be used predictively, they do shed light on important assumptions and
the nuances of flow management in a complex aquatic system. For example, the best years for
commercial crawfishermen are supposedly flood years, but in our results the strongest
relationship between a hydrologic variable and crawfish catch-per-effort was flow variability, not
flow magnitude. Further, navigation had a negative correlation with flow magnitude, the
opposite of what would be expected. While this result makes sense given the navigation hazards
specific to the Atchafalaya River at high water, it does reveal a potential conflict of interest
between navigation interests and environmental interests that desire high flushing flows to
benefit water and habitat quality in backswamp areas of the basin. Overall, these results give
insight into potential conflicts among stakeholder groups, can reduce the dimensions of
management decisions, and provide initial hypotheses for experimental flow modifications.
There is an acknowledged need for a new approach to flow management in the ARB. The
hydrologic variables used in this study were selected specifically for their relevance to flow
86
management; however, the uncertainty inherent in this approach must be noted. Much of the
fisheries data is affected by market forces, especially for crawfish. Further research incorporating
market forces is necessary for a more complete understanding of the potential socioeconomic
impacts of water management decisions. Another area of further research is incorporating more
non-market ecosystem services. Supporting and regulating services are underrepresented or
absent from this study. Although the issue of double-counting ecosystem service benefits is not
an issue with this approach, a paucity of data sources and the difficulty of accurately quantifying
these benefits will require further consideration.
Towards dynamic flow regime management for ecosystem restoration in the Atchafalaya
River Basin, Louisiana
This study was developed to determine if ecosystem restoration goals in the ARB could
be better served within the current flow mandate. The flow mandate is an annual target but is
currently implemented on a daily basis limiting water management and restoration alternatives.
The primary target of restoration in the ARB is the baldcypress-water tupelo forests that are
threatened by hydrologic changes in the basin. A historical hydrological analysis showed that,
while mean monthly discharges have increased over time, mean monthly stage heights in the
ARB have decreased, but have been relatively stable for the past 30 years. A one-period IHA
analysis of the current flow regime (1988-2012) provided detailed statistics on the current range
of flow variability. A literature review of the hydrologic needs of baldcypress-water tupelo
forests showed that their hydrologic needs are within the current range of flow variability and
thus an environmental flow prescription based on them has the potential to be complementary
with the current flow mandate. A flow prescription based on the hydrologic needs of
87
baldcypress-water tupelo forests was modeled to evaluate its deviation from current flows and to
assess the feasibility of implementing the flow prescription and meeting the flow mandate over
time intervals that are more useful for ecosystem management and restoration goals.
We found that lengthening the implementation of the current flow mandate to monthly or
quarterly time scales has high potential for success in meeting both the flow mandate and
important flow-ecology relationships. An area of further research interest is how this
environmental flow prescription would affect current restoration efforts. Current efforts address
the spatial distribution of water in Water Management Units – distinct hydrological units within
the ARB. A change to flow regime would potentially affect the timing, duration, and magnitude
of flow events in these areas; however, this will require hydraulic modeling to improve the
estimation of inundation extent and patterns at finer scales.
88
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APPENDICES
Appendix A. Proposed changes in flow distribution through the Old River Control Complex
due to requests from the Governor’s Office (from the August 2002 “Water in the Basin” report
and subsequent documentation):
Date
May-June 1983
May 1991
Requested Diversion
Held Red River
Landing gage to 60.4’
equal to 31.6% at the
crest
Distribution of flow
through the Old River
Complex was reduced
to 28.5% - 29.0%
1993
Requested that the
Mississippi River
Commission reduce
flows into the
Atchafalaya Basin
April 1996
March 2003
Flow increased to
32%
Flow increased to
32%
Flow increased to
32%
Increase requested to
32%
Increase to 32%
April 8, 2004
Requested Increase
March 26, 2007
Requested increase
May 1, 2012
Requested Increase
April 8, 2013
Requested Increase
March 2000
Feb. – March 2001
May 8, 2002
Reason
To prevent the
evacuation of the state
penitentiary at Angola
Duration
16 Days
Allowed for rapid
receding of flood
waters in the Red,
Black, and Ouachita
Rivers
Minimize the
probability of a fish
kill following
extensive fish
restocking after
Hurricane Andrew
Increase crawfish
production
Increase crawfish
production
Increase Crawfish
production
Increase crawfish
production
Water quality /
Aquatic Resources
Water Quality /
Aquatic Resources
Increase crawfish
production
Increase crawfish
Production
Economic / Ecologic
Impact
21 Days
Denied
14 Days
16 Days
Approved 6 Days +
Approved 2% for 2
weeks
Approved 2% for 1
week
Approved 2% for 2
weeks
Denied
Denied
Approved 3% for 2
weeks
SCR 107 2001 Regular Session filed with the secretary of state 6/7/2001
Requests US Corp of Engineers to increase the flow of water into the Atchafalaya Basin to
maintain a minimum stage of twelve feet National Geodetic Vertical Datum (NGVD) at the
Butte La Rose gauge throughout the spring.
102
HCR 168 2001 Regular Session
Urges and requests the U.S. Army Corps of Engineers to increase the water flow rate from the
Mississippi River into the Atchafalaya River through the Old River Control structure in
Simmesport.
SCR 62 2002 Regular Session
Requests the executive assistant of Coastal and Marine Activities, office of the governor, and the
director of the Atchafalaya Basin Program to jointly conduct an evaluation, and to make
recommendations, as to how to improve the water quality in the Atchafalaya Basin. Report due
to the House and Senate Natural Resources Committees by 9/30/2002.
It does not reference HCR 62, but a report was submitted August 12, 2002 titled, “Louisiana
Department of Natural Resources, Atchafalaya Basin Program, Water in the Basin Committee,
Recommendations to the Governor”. The report states that a “Water in the Basin” committee
was one of 18 committees formed after the adoption of the Atchafalaya State Master Plan in
1998. The report used stage information from 1980-1999, where available and responses to
surveys to arrive at its recommendations.
HCR 252 2003 Regular Session (not passed)
Memorializes the U.S. Army Corp of Engineers to examine water level and water quality issues
in the Atchafalaya Basin and to report its findings prior to the 2004 R.S.
HCR 117 2012 Regular Session
Urges the governor to request that the U.S. Army Corps of Engineers increase the water flow
at the Old River Control structure from the Mississippi River into the Atchafalaya Basin.
Source:
Water in the Basin Committee. 2002. Water in the Basin Committee Recommendations to the
Governor. Atchafalaya Basin Program, Louisiana Department of Natural Resources,
Baton Rouge, LA.
103
Appendix B. Biplots of principal component analysis results showing loading of hydrologic
variables on PC1, PC2, and PC3. PC1 explained 29.9%, PC2 21.0%, and PC3 7.9% of the
variation in the hydrologic data. Red arrows and labels indicate the direction of association of the
hydrologic variables. Black numbers indicate years of the hydrologic data (in order 1-49 from
1980-2011). The first figure shows PC1 (x axis) plotted against PC2 (y axis). The second figure
shows PC2 (x axis) plotted against PC3 (y axis). The third figure shows the screeplot for the
PCA
-4
-2
0
SPQcfs_CV
4
2
18
12
SPQcfs_mean_4yrlag
32
29
2620
5
9
-4
-0.2
-2
0
0.0
SPQcfs_meanX1000
Date.min
SPQcfs_mean_1yrlag
Hi.pulse..
SPQcfs_mean_5yrlag
15
1Lo.pulse..
WinterLow
8
23
SPQcfs_medX1000
10
19 6
Fall.rate
16
11
22
24
SummerMean
Rise.rate
28
Reversals
SpringMean 31
2
SPQcfs_mean_3yrlag
WinterMean
3
30
SPQcfs_mean_2yrlag
17
27 21
7
X30.day.min
25
Date.max
X1.day.min
X7.day.min
X3.day.min FallMean
X90.day.min
14
13
-0.4
Comp.2
4
X7.day.max
X3.day.max
X1.day.max
X30.day.max
X90.day.max
0.2
0.4
4
2
Base.flow
-0.4
-0.2
0.0
Comp.1
104
0.2
0.4
-2
0
2
4
6
0.4
6
-4
2
7
4
4
5
2
23
-0.2
0.0
Comp.2
105
0.2
0.4
0
12
9
11
SPQcfs_medX1000
SpringMean
SPQcfs_mean_3yrlag
FallMean
17
SPQcfs_mean_2yrlag
SPQcfs_meanX1000
SPQcfs_mean_1yrlag
14X90.day.min
X90.day.max
19 15
X30.day.max
10
X7.day.max
32
28
X3.day.max
X1.day.max
Hi.pulse..
SummerMean
SPQcfs_CV
25
30
SPQcfs_mean_5yrlag
X30.day.min
SPQcfs_mean_4yrlag
27
22 Date.min
X7.day.min
20
1
X1.day.min
X3.day.min
31
26 18
Base.flow
Lo.pulse..
21
Rise.rate
29
Reversals
24 16
-2
0.0
-0.2
Comp.3
13
6
WinterMean Fall.rate
8
Date.max
WinterLow
-4
0.2
3
4
2
0
Variances
6
8
flow.pca3
Comp.1
Comp.3
Comp.5
106
Comp.7
Comp.9
VITA
Graduate School
Southern Illinois University
Justin P. Kozak
[email protected]
University of Illinois – Urbana Champaign
Bachelor of Arts, Geography, May 2007
Southern Illinois University Carbondale
Master of Science, Geography and Environmental Resources, August 2009
Awards:
NSF IGERT Fellowship, Southern Illinois University Carbondale, 2011 – 2013, 2014 – 2015
Master’s Fellowship, Southern Illinois University Carbondale, 2007 - 2008
Roepke Scholarship, University of Illinois Department of Geography, 2007
George Huff Award, University of Illinois Alumni Association, 2006
Big Ten Conference Scholar-Athlete Award, 2004-2005
Dissertation Title: Restoration and water management in the Atchafalaya River Basin, Louisiana
Major Professors: Christopher Lant and Jonathan Remo
Publications:
Bennett, Micah G. and Justin P. Kozak. In press. Spatial and temporal patterns in fish community
structure and abundance in the largest U.S. river swamp, the Atchafalaya River floodplain,
Louisiana. Ecology of Freshwater Fish.
Bennett, Micah G., Anne Hayden-Lesmeister, Justin P. Kozak, Kelley A. Fritz, and Aaron
Nickolotsky. In press. An estimate of basin-wide denitrification based on floodplain
inundation in the Atchafalaya River Basin, Louisiana. River Research and Applications.
Kozak, Justin P., Micah G. Bennett, Anne Hayden-Lesmeister, Kelley A. Fritz, and Aaron
Nickolotsky. 2015. Using flow-ecology relationships to evaluate ecosystem service trade-offs
and complementarities in the nation’s largest river swamp. Environmental Management
55(6):1327-1342.
Kozak, Justin P. and Bryan P. Piazza. 2015. A proposed process for applying a structured decision
making framework to restoration planning in the Atchafalaya River Basin, Louisiana,
USA. Restoration Ecology 23(1): 46-52.
Kozak, Justin P., Christopher Lant, Sabina Shaikh, and Guangxing Wang. 2011. The geography of
ecosystem service value: The case of the Des Plaines and Cache River wetlands, Illinois.
Applied Geography 31(1): 303 – 311.
Reports:
Bennett, Micah G., Kelley A. Fritz, Anne Hayden-Lesmeister, Justin P. Kozak, and Aaron
Nickolotsky. 2013. NSF IGERT report - Multi-use management in the Atchafalaya River
Basin: Research at the confluence of public policy and ecosystem science. Final Report in
fulfillment of NSF-IGERT program requirements: Southern Illinois University, Carbondale,
IL.
107