San Francisquito Creek Watershed Sustainability Analysis: A Novel Approach
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Veronica Chouinard
A Thesis in the Field of Sustainability and Environmental Management
for the Degree of Master of Liberal Arts in Extension Studies
Harvard University
May 2018 Copyright 2018 Veronica Chouinard Abstract
In the western US, most water consumers rely on imports from outside their local watershed. This has implications for both the recipient watershed as well as those which provide the water. The most widely-used metric available to quantify watershed sustainability, the Watershed Sustainability Index (WSI), assumes that water used within the watershed originates there. This research aims to identify and address shortcomings of this metric. Specifically, I adapt the WSI to accommodate watersheds in which imports and exports warrant consideration, I integrate additional sustainability indicators, and I present the results in a treemap. I applied the resulting tool, the Watershed
Sustainability Visualization (WSV), to the local San Francisquito Creek (SFC) watershed to evaluate watershed management effectiveness. I hypothesized that the SFC watershed would perform poorly in a sustainability analysis on hydrological and environmental dimensions, despite the perception that it is healthy and well-managed. Using data available from local agencies and existing databases, I calculated the SFC WSV scores for each indicator. I evaluated the indicators for hydrology and environment and determined that although the quantitative sub-indicator for hydrology supported my hypothesis, the others did not. Furthermore, I hypothesized that, although robust, current management efforts may not adequately address dimensions on which the watershed sustainability analysis indicates a need for improvement. As it turns out, issues are being addressed; however, it remains to be seen whether the outcome will have a favorable or unfavorable impact on sustainability. Acknowledgments
To my research advisor Mark Leighton – I appreciate your guidance: turning my amorphous thoughts into a thesis-worthy proposal and, after I had no luck acquiring a director on my own, pointing out that one of my favorite professors would be a great fit.
To my thesis director Andrew Tirrell – thank you for reminding me to keep a manageable scope for my thesis. I appreciate your encouragement and perspective – they came at the right time and in the right measure.
To my thesis coach Susan Bernhard – I am so lucky to be one of the many, many beneficiaries of your counsel and friendship. You know how, when, and where to nudge.
To Ann Reisenauer and Dick Simpson (and by extension Chaco and Luna) – thank you for being my friends, welcoming me into your beautiful home, and inspiring me to enjoy life, explore the world, and pursue my passions. I will continue to try to repay my debt of gratitude.
Special mention goes to the San Francisquito Creek Joint Powers Authority and the dedicated stakeholders who’ve committed to making improvements to the watershed.
There are several individuals with whom I discussed my research, and I appreciate the perspectives each shared. Their input has contributed to the vibrancy of my understanding of the history and present state of the watershed.
I am grateful for my family, friends, coworkers, and the motley collection of individuals who offered their support to me throughout my thesis process. Thanks for your encouragement!
iv Table of Contents
Acknowledgments...... iv
List of Tables ...... viii
List of Figures ...... ix
Definition of Terms...... x
I. Introduction ...... 1
Research Significance and Objectives ...... 2
Background ...... 3
Water in California ...... 3
Bay Area Water Supply ...... 7
Perception and Social Justice ...... 11
Watershed Sustainability ...... 14
Composite Watershed Sustainability Metrics ...... 16
WSI ...... 18
Opportunities to Improve the WSI ...... 23
Water Footprint ...... 26
Watershed Management and Integrated Water Resource Management ....27
The SFC Watershed ...... 28
Research Question, Hypotheses and Specific Aims ...... 34
II. Methods ...... 36
Application of the WSI to SFC Watershed – Data Acquisition...... 36
v Hydrology ...... 36
Environment ...... 41
Life ...... 43
Policy ...... 45
Application of the WSI to SFC Watershed – Calculation ...... 46
Evaluation of Indicators ...... 47
Inter-basin water transfers...... 47
Social Justice ...... 48
Efficiency ...... 49
Resilience ...... 52
Model Development...... 52
Model Application to the SFC Watershed ...... 53
III. Results ...... 55
SFC WSI ...... 55
SFC WSV...... 56
WSV Model ...... 56
SFC Watershed Sustainability Analysis ...... 57
IV. Discussion ...... 59
Interpretation and Significant Implications of Results ...... 59
Specific Aims ...... 59
Hypotheses ...... 63
Results in Context ...... 64
Opportunities for Methodological Improvement ...... 65
vi General Observations ...... 65
Overlooked assumptions ...... 67
Unintuitive consequences ...... 69
Conclusions ...... 69
Contributions...... 70
Research Limitations ...... 70
Recommendations for Future Research ...... 71
Model improvements ...... 71
Groundwater basin sustainability ...... 72
Appendix 1 Description of WSI Parameters, Levels, and Scores...... 74
Appendix 2 Social Justice and Equity Indicators ...... 77
References ...... 78
Ancillary Appendix 1 Q-values for WQI Calculations...... 85
Ancillary Appendix 2 WSV for Selected Basins (using WSI Results) ...... 90
vii List of Tables
Table 1 Indicators and parameters of the WSI ...... 20
Table 2 Mapping WSI parameter value to score ...... 22
Table 3 Allocation disparity in the SFC watershed ...... 32
Table 5 SFC WSI: parameters values and indicator scores ...... 56
viii List of Figures
Figure 1 San Francisco regional water system ...... 7
Figure 2 Bay Area wholesale suppliers ...... 8
Figure 3 BAWSCA (a) members and (b) supply by source ...... 9
Figure 4 Interconnected dimensions of sustainability ...... 15
Figure 5 WSI parameter score assignment ...... 21
Figure 6 Water infrastructure in California ...... 24
Figure 7 SFC watershed land ownership ...... 29
Figure 8 SFC flood protection projects ...... 30
Figure 9 SFC watershed and alluvial fan ...... 31
Figure 10 SFC watershed satellite map these are beautiful figures ...... 34
Figure 11 Equity indicators ...... 50
Figure 12 SFC WSV ...... 57
ix Definition of Terms
$PCD: Dollars per capita per day
AIMS: Annual Indicator and Measures
Acre-foot: Volume of one acre filled to a depth of one foot, or 435.6 CCF
ACWD: Alameda County Water District
AF: Acre-foot
Basin (see Watershed)
BAWSCA: Bay Area Water Supply and Conservation Agency
BMP: Best management practice
BOD5: Five-day biochemical oxygen demand
CCF: Centum cubic feet
CCWD: Contra Costa Water District
Centum Cubic Feet: 100 cubic feet (which is equivalent to 748 gallons, or 0.0023 AF)
CPUC: California Public Utilities Commission
CWC: Community Water Center
CWS: California Water Service
EBMUD: East Bay Municipal Utilities District e.g.: exempli gratia (literally: “for the sake of example”, commonly interpreted as: “for
example”)
EPI: Environmental Pressure Index
FY: Fiscal Year
GIS: geographic information system; a framework for gathering, managing, and
x analyzing data
GPCD: Gallons per capita per day
GSA: Groundwater Sustainability Agency
HDI: Human Development Index
HELP: Hydrology, Environment, Life, Policy
HELPERS: Hydrology, Environment, Life, Policy, Efficiency, Resilience, Social Justice i.e. id est (literally: “that is”, also commonly interpreted as: “in other words”)
Individual Supply Guarantee: Allocation of water from SFPUC
Intertie: Interconnection permitting passage of water between systems
ISG: Individual Supply Guarantee
IWRM: integrated water resource management
JPA: Joint Powers Authority
MGD: million gallons per day
µS: micro Siemens
MID: Municipal Improvement District
MMWD: Marin Municipal Water District
NB: nota bene (literally: “note well”, commonly interpreted as: “note that”)
NTU/JTU: Nephelometric Turbidity Unit/Jackson Turbidity Unit
O2: oxygen pH: potential of hydrogen, indicates how basic or acidic a solution is
PPIC: Public Policy Institute of California
R-GPCD: residential gallons per capita per day
SCVWD: Santa Clara Valley Water District
xi SFC: San Francisquito Creek
SFPUC: San Francisco Public Utilities Commission
SGMA: Sustainable Groundwater Management Act
UNESCO: United Nations Educational, Scientific, and Cultural Organization
Watershed: an area bound by a divide (generally a ridge) which drains to a stream or
water body
WRM: water resource management
WSI: Watershed Sustainability Index
WSV: Watershed Sustainability Visualization
WQI: Water Quality Index
Zone 7: Zone 7 Water Agency
xii Chapter I
Introduction
Water availability has social, ecological, and economic benefits. On a global scale, sustainability considers how both current and future generations meet their needs.
When applied to watersheds on a local level, sustainability analysis can reveal vulnerabilities and risks that effective watershed management may be able to mitigate.
Appropriate actions taken in response to unsustainable conditions should increase the aggregate benefits to all stakeholders over the long-run.
Society’s relationship with the resources on which it depends reflects its sustainability. In the case of water, western states bear the dual burden of unfavorable circumstances associated with limited resources and the need to reform a long-standing legacy of wasteful practices. Here, the value of my proposed research is explained in terms of the local context, needs, and challenges present in California.
Given the recent and persistent threat of drought in California, water issues have ascended to an unprecedented level of importance. The agricultural sector, which fuels a substantial portion of the state’s economy and produces food for domestic and international consumption, relies upon vast quantities of the west’s limited water resources. The commercial and industrial sectors also compete for water alongside the public which depends on water for domestic use as well as outdoor irrigation. And lastly, the environment, the health of which supports all of the aforementioned activity, warrants its share of the resource that it provides to all of the other stakeholders in the state. Research Significance and Objectives
The intent of this research was three-pronged. Primarily, the results shed light upon, and fill, a gap in the toolkit used to assess watershed sustainability. In addition, this research enables a better understanding of the health of the San Francisquito Creek
(SFC) watershed in terms of sustainability. And ultimately, the results inform watershed management activities intended to improve sustainability.
Many controversial issues involve water rights and how water resources and watersheds are managed. Although it is in society’s long-term interest to sustainably manage the limited water resources available, well-intentioned efforts may fail to have any meaningful impact without effective tools to adequately understand and quantify watershed sustainability. This research will help make the currently available diagnostic tools more robust, allowing us to understand the areas where watersheds are most vulnerable and assess the impact of management efforts aimed at improving conditions.
The current diagnostic toolkit includes an established Watershed Sustainability
Index (WSI) which can help determine a watershed’s health if available water originates and is utilized within the watershed’s boundary (Chaves & Alipaz, 2007); however, it fails to offer a means to assess watershed health and the regional use of water that is not restricted by these conditions. The results of this research help address this need. In addition, this research broadens the lens of the metric to include indicators not previously contemplated.
The implications of this work impact both those interested in understanding watershed ecosystem health as well as those actively involved in managing it. A robust watershed sustainability metric that enables drill-down into the relevant factors facilitates
2 identification of problem areas and evaluation of the effectiveness of management efforts’ ability to improve sustainability.
My objectives were:
• To identify and, to the extent that improvements are clear, address shortcomings
of the current WSI
• To analyze how the current WSI could be adapted to provide a more useful
framework for watersheds, like SFC, in which imports and exports warrant
consideration
• To determine if the refined watershed sustainability metric could be applied to the
SFC watershed (for the purpose of validating and testing it)
• To evaluate watershed management activities’ effectiveness based on knowledge
arising from the refined watershed sustainability metric.
Background
The definition of watershed sustainability as presented in the existing literature serves as the foundation for understanding shortcomings in the current analytical approaches. Moreover, it suggests options for developing a more robust approach to watershed sustainability analysis.
Water in California
California’s relationship with water offers compelling insight into its sustainability challenges. The state boasts a growing population currently at 39 million and slated to surpass 50 million by 2050 (Public Policy Institute of California, 2018).
3 The state’s economy also recently surpassed France as the sixth largest in the world
(World Bank, 2016). With the third largest land area in the United States, California spans diverse landscapes and climates, the most dominant of which is the Mediterranean
Climate in the Central Valley. Although less predictable in the age of climate change, water availability represents one of the greatest concerns for numerous stakeholders both within and outside the state. An abundance of water results in devastating floods while water scarcity resulting from drought or overuse compromises everyone’s ability to meet their needs. These diametrically opposed situations are further compounded by climate change which intensifies the amplitude and frequency of drought and flood, and in doing so exposes the social, environmental, and economic vulnerabilities of the state.
Arguably, California has the most extensive water infrastructure in the world (Austin,
2015). In most parts of the state, precipitation is limited to the winter season (November through April). However, multiple systems consisting of pipes, tunnels, canals, reservoirs, dams, pumping stations, power plants, fish hatcheries, and siphons work in concert to meet societal needs for water. As expected, infrastructure projects are accompanied by high, capital costs as well as high, ongoing expenses for operation and maintenance of their facilities. Although late in coming, environmental considerations are now being weighed in decisions concerning hydrologic alterations.
Understanding the state’s non-local water supply and systems is informed by its history. In many ways, Western development was fueled by water availability. In the arid west, reliable water typically resulted from generous promises and costly infrastructure projects effectively transforming arid regions into desirable economic centers in which water was readily available. Water rights mimicked property and
4 mining rights and the power of those that held them ensured that they would perpetuate despite their incoherence (Cantú, 2015). The West’s insatiable thirst for water became problematic once its inhabitants realized that an unlimited water supply was not guaranteed.
Although different, supply and demand issues pose similar challenges for water and energy. Sources of freshwater supply naturally fall into two broad categories: groundwater and surface water. However, it’s worth noting that technological innovation and need have fostered the development of other supply alternatives, including water treatment plants ranging from desalination (used in wealthy coastal areas that otherwise lack adequate freshwater supply) to recycling and purification. The products of the treatment processes may be tailored to specific uses based on certain requirements (e.g. standards for drinking water vs. industrial or agricultural), allowing for different grades of water. Although water treatment often renders water supply from different sources incompatible, all drinking water is generally lumped into the same category: potable.
Unlike the highly perishable commodity of electricity, water exhibits non- perishable characteristics. This important distinction allows for storage and conveyance over great distances, but does not guarantee its efficiency. Water readily evaporates, seeps into the ground, and poses logistical challenges due to its density. Its conveyance involves expensive infrastructure and significant energy. According to a 2005 California
Energy Commission report, transportation and treatment of water, treatment and disposal of wastewater, and the energy used to heat and consume water account for nearly 20 percent of the total electricity usage in the state (California Energy Commission).
5 Like energy, water conservation and efficient use of water resources can delay the need to tap into new sources of supply. The limited sources of supply are rapidly being exploited and exhausted. To complicate matters, contaminants threaten water quality, necessitating treatment to meet increasingly more stringent standards.
Knowing that developed water has a cost and is limited in supply, its use matters.
How much developed water is put to “beneficial use”? What is “beneficial use”? How much consumption is one-time use? How much developed water returns to the watershed? As viable water supply options become scarcer, water managers may begin to more carefully contemplate questions like these. Would they consider a tax on certain types of consumption? Or might they, like Australia, consider the implementation of water markets that differentiate between water grades driven by end-use (such as recycled water for irrigation)?
Groundwater extraction has costs both in the electricity to pump as well as diminished capacity when overdrafting results in land subsidence permanently reducing aquifer storage capacity. Water providers throughout California increasingly find themselves evaluating the possibility of practices like groundwater recharge, desalination, recycling (purification of wastewater effluent), and water banking.
Inasmuch as the country depends on food grown in California, the state itself depends on water from external sources. Furthermore, the majority of Californians counts on water supplied from outside its local watershed. For example, San Francisco and many communities of the Bay Area depend on an aqueduct that conveys water 167 miles from Yosemite National Park to the San Francisco Bay Area. In California, local water is the exception, not the rule, even outside urban centers.
6 Bay Area Water Supply
The regional water supply system operated by the San Francisco Public Utilities
Commission (SFPUC) collects water (~85%) from the snow-fed Tuolumne River in the
Sierra and wheels it to residential, commercial, and wholesale customers in the Bay Area
(SFPUC, 2017). The infrastructure used to convey the water is collectively referred to as the San Francisco Regional Water System (Figure 1). Despite its utility, the impounding of water behind the O’Shaughnessy Dam (and many others) is also not without controversy as groups call for the removal of dams to restore rivers.
Figure 1. San Francisco regional water system. 85% of SFPUC’s water is impounded at Hetch Hetchy Reservoir. Large pipes convey the water from the reservoirs to customers in the Bay Area (SFPUC, 2017).
The Bay Area Water Supply and Conservation Agency (BAWSCA) coordinates the water agencies that rely on both local supplies as well as those that are imported via the San Francisco Regional Water System (BAWSCA, n.d.). The BAWSCA members
7 on the peninsula primarily rely on water imports from one of two agencies: the SFPUC and the Santa Clara Valley Water District (SCVWD); although some agencies are able to receive supply from both wholesalers through interties (Figure 2).
Figure 2. Bay Area wholesale suppliers. Two wholesale suppliers serve the San Francisco Peninsula: SFPUC and SCVWD (Brown and Caldwell, 2017).
Agencies that rely on a diverse supply portfolio are less vulnerable to uncertainties associated with supply availability. In addition to imported supply,
BAWSCA members may also rely on groundwater, surface water, or recycled water
8 supplies (Figure 3). However, some member agencies rely exclusively on imported water from a single wholesale supplier.
Water agencies need resilient supply portfolios that can respond to changes in demand as well as disruptions in sources. Absent a diverse supply portfolio with
Figure 3. BAWSCA (a) members and (b) supply by source (Gonzalez & Ajami, 2015). Legend 1 Alameda County Water District 13 Mid-Peninsula Water District 2 City of Brisbane 14 City of Millbrae 3 City of Burlingame 15 City of Milpitas 4a CWS – Bear Gulch 16 City of Mountain View 4b CWS – Mid-Peninsula 17 North Coast County Water District 4c CWS – South San Francisco 18 City of Palo Alto 5 Coastside County Water District 19 Purissima Hills Water District 6 City of Daly City 20 City of Redwood City 7 City of East Palo Alto 21 City of San Bruno 8 Estero Municipal Improvement District 22 San Jose Municipal Water System – North 9 Guadalupe Valley MID 23 City of Santa Clara 10 City of Hayward 24 Stanford University 11 Town of Hillsborough 25 City of Sunnyvale 12 City of Menlo Park 26 Westborough Water District
9 contingencies for source disruptions, water agencies’ risk profile becomes unacceptable.
The water crisis in Cape Town, South Africa provides a sad example of the dangers of dependence on a single source of supply.
Various stakeholders have become increasingly vocal about water management.
Environmentalists focus on impacts to the ecosystem, homeowners call upon their elected officials to address flood risks, and developers continue to demand more resources to supply new housing stock. As a result of this, various attempts at regulation have taken shape to remediate the situation.
Today, joint power authorities that focus on watershed management proliferate.
Since waterways often divide community and jurisdictional boundaries, the need for new regional governmental agencies continues to grow, with their boundaries coincident with that of their respective watersheds. And although initially motivated by concerns about liability associated with waterways, joint power authorities are increasingly seeing waterways as important assets. The joint power authorities and watershed managers focus on ecosystem, social and recreational needs, as well as emergency response plans.
In short, these agents are responsible for ensuring watershed sustainability. They devote considerable resources to projects but do not always have visibility into the overall impact of those actions on the watershed’s overall health. In order to determine the effectiveness of their actions or to justify future activities, it seems logical that they should know that they will achieve meaningful and desirable results with high positive impact.
10 Perception and Social Justice
Reisner’s classic book, Cadillac Desert, published in 1987, offered a stark picture of water in the West. In the 30 years since its publication, despite its advances,
California seems to have perfected the art of trading one problem for another in its attempts to engineer a solution to one problem and, in turn, create another.
“I’ll believe there’s a drought in California when the golf course greens are brown” (D. Erskine, personal communication, 2015). In the height of the most recent drought, a long-time California resident told me that he didn’t believe there was a drought. Apparently the dwindling capacity of reservoirs and the subsidence resulting from overdrafting of the aquifers in the Central Valley was not concerning to him. But, he had a good point. How could it be that, despite the worst drought in the state’s history,
California still had lush green golf courses in the desert?
Moreover, how could a community with a lush green golf course be situated beside another community that had (and continues) to rely on water trucks because its wells have gone dry? This stark contrast would be completely absurd were it not reality for the residents of East Porterville.
It didn’t help matters that homes in the directly adjacent, slightly wealthier town of Porterville had running water from the town’s municipal water system. Perhaps the most glaring example of this could be found on the city boundary: locals would take showers at Igelsia Emmanuel in East Porterville, while directly across the street, in
Porterville, was a patchy but green golf course (Lurie, 2015).
A veneer of abundance belies the tenuous relationship between Californians and their water. Although many Californians have adopted water conservation as a way of
11 life, others remain blissfully ignorant of the water challenges that the state faces. To a certain extent, “Brown is the new Green,” and many Californians have learned to recognize waste in the culture of “convenience.” Incentives have been put in place, educational campaigns have been successful, alignment between government agencies, and a healthy dose of social pressure seems to have given many the nudge they need to make behavioral changes. However, it took until 2014 for the state to pass legislation to manage groundwater. Until then, California was the only western state without laws to preserve and protect its groundwater resources.
According to the Community Water Center, more than one million Californians have unreliable access to safe and affordable drinking water (2016). Here, “safe water” is defined as that which is available in the quantity to meet human needs and of the quality to maintain health. Marginalized communities (predominantly low-income and Latino) are disproportionately affected.
The right to water is uncontested; however, water service does have a cost. There is a school of thought that water should be “free.” However, as previously explained, the cost of the infrastructure and maintenance to provide water service is quite expensive, consequently tap water is not free.
Although water may be relatively cheap for some, others devote a significant portion of their income (5-10%) in order to pay for safe drinking water. Since most household taps and fixtures don’t measure water flow or indicate how much water use costs, most customers rely on a water bill that comes a month or more in arrears – making it hard to course-correct. Furthermore, many members of disadvantaged communities often find themselves in shared living situations where the number of occupants is high
12 relative to the average household size. One negative consequence of inclined block rate structures that promote conservation is that they result in higher water charges for low- income, high-occupancy living situations. Also, for those living in communities with small water systems that are not adequately maintained, residents may also be forced to purchase bottled water to get safe water. Bottled water costs about 300-2000 times more than most pay for their water service (Boesler, 2013).
Urban water pricing lacks transparency, is unintuitive, and downright complicated. Rates may or may not provide signals to consumers. This is due in part by the reality that prices are not driven by markets nor constraints. Rates for public agencies are governed by Proposition 218 which stipulates that one group of customers cannot subsidize another, by dictating that the fee for a service must be proportional to its cost.
As such many public agencies are reluctant to impose a rate design that might otherwise incentivize water conservation. Meanwhile, the CPUC which approves rates for regulated water utilities, has recently mandated that water companies provide conservation incentives to its customers through a decision in its Balanced Rates proceeding (CPUC, 2016).
Considering how rate design impacts the most vulnerable members of the population reveals other embedded iniquities of water costs as well as more social justice issues. Income determines both where and how you can afford to live in the Bay Area, just as it does in many places throughout the country and the world. And although location may determine an individual’s water rates, living arrangement may dictate how much an individual’s (or his/her family’s) water costs. It is not uncommon for 10-40 people to be hot-bunking in a modest sized house in East Palo Alto. Although these
13 individuals may have less expensive water rates than residents of nearby Woodside, they may pay a larger fraction of their income because (a) their income is about a tenth of their hillside neighbors and (b) their water usage may be charged in a higher tier rate. These unintuitive findings often elude common metrics and sustainability analysis.
Watershed Sustainability
When it comes to freshwater supply, water and watershed sustainability are inextricably linked: the sustainability of one depends on that of the other. As a general definition, sustainability is the capability of present and future generations to meet their needs. The definition applies on a global scale and to species other than our own (Fulton and Shilling, 2015).
Although an exhaustive discussion might take into consideration the complementary ground-water watersheds, I will focus on surface-water watersheds and the hydrologically connected water within the superficial watershed boundary (Winter,
Harvey, Franke, & Alley, 1998).
Beyond the formal definition of sustainability, it’s useful to frame sustainability in more tangible pieces. Here I will discuss eight dimensions (Figure 4). The first and most straightforward dimension is hydrology. Simply put: reliable water relates, in part, to hydrological aspects including accessibility, quantity and quality. The second dimension of water sustainability is related to resiliency or ability to adapt. Assuming that conditions are constant leads to a false sense of security and inadequate preparation for a future wrought by climate change. Moreover, absence of alternative options indicates vulnerabilities. The third dimension of water sustainability is the environment or
14 ecosystem. And the fourth is economic considerations, including everything from the cost and price of water to the way in which it may be subsidized.
Beyond these four core components are softer and less-intuitive, overlapping dimensions of watershed sustainability: education, regulation, equity (or social justice), and efficiency. Watershed sustainability should be analyzed across all of its dimensions
– they are integral, albeit often taken piecemeal.
Social Justice Economy
Resiliency
Education
Efficiency
Policy
Environment
Hydrology
Figure 4. Interconnected dimensions of sustainability. Dimensions of sustainability interact with one another. For example, social justice may impact resiliency, policy, education, and economy and be influenced by policy, hydrology, and education (by author).
15 Composite Watershed Sustainability Metrics
Ideally an analysis of watershed sustainability should parallel the three main pillars of sustainability: social, environmental, and economic. However, coverage of these pillars is paramount to alignment with them. Instead, the desirable and undesirable characteristics of composite watershed sustainability metrics need to be evaluated in order to inform the evaluation of those that are currently available.
There are numerous watershed assessment tools based on indicators. Previous reviews have explored the selection of indicators, weighting of indicators, robustness of analysis, and interpretation of the final metric, for the purpose of aiding others who wish to customize existing indices for their applications or for developing new metrics
(Juwana, Muttil, & Perera, 2012). This work facilitated my own evaluation of metrics and informed the development of a sustainability tool that considers inter-basin water transfers.
First the appropriate unit of analysis (i.e. the spatial boundaries concerned with the unit and scale) was evaluated. The watershed is a natural choice as it establishes natural boundaries that are in concert with hydrology. Furthermore, the basin boundary may also delineate the management area, that is, where actions are taken that impact the watershed. Note that there may be limits to the scale at which a given analysis may be applied, but that aggregating sub-basin (or micro watershed) results may provide regional specificity within a given watershed. By extension, temporal factors that enable the metric to quantify sustainability during a specific interval were considered. It is also worth noting the value of metrics that incorporate perspective – beyond just a snap shot – these metrics provide an indicator of the extent to which a situation is changing over time
16 or as a result of something else. For example: pressure, state, response parameters are used for each indicator. Parameters can be thought of as factors of an indicator. Pressure may measure variation in the indicator values over the history of measurement. State can measure the value of the indicator during a specified time. Response, in contrast to pressure, may measure changes in the indicator value during a specified period of interest.
In my search for a metric, I also acknowledged the desire to quantify sustainability, both in order to objectively benchmark the metric, but also for comparison within a given watershed or among different watersheds.
The methods used to develop the composite watershed metric were equally important. Data availability, straightforward calculations, and understandable results were prime considerations.
The strength of conclusions that can be drawn from simple metrics may be limited. For example, imagine trying to use height measurement as an indicator of someone’s health? Wouldn’t there be additional data you’d want? Here I tried to find the sweet spot – telltale data that could be leveraged to draw powerful conclusions.
Similarly, I recognized the need to balance the ability to get data or perform calculations with simplicity.
Although informative, an approach using sophisticated math, such as finite element analysis, would involve numerous assumptions and would likely put off otherwise interested practitioners from attempting the analysis, if not for its complexity, but also for its steep learning curve, and somewhat esoteric, if not inaccessible partial differential equations. I personally would like to avoid too many Greek symbols and
17 having to explain Eigen values in my metric.
Also, I’d like to think of the audience to whom results are communicated.
Knowing that local stakeholders are laypeople, information: data and results should be accessible, understandable, and easy to communicate. This applies to decision-makers as well.
Most composite watershed sustainability metrics do not provide basin-specific insight. The two noteworthy exceptions are the Watershed Sustainability Index (WSI) and a metric that aims to evaluate the sustainability of river basins subjected to an inter- basin water transfer project. However, the method employed in the latter assumes a one- to-one relationship between recipient and source watersheds (Kefayati, Bahram, Azadeh,
& Babazadeh, 2018). Thus, my model will build upon the simple, yet robust, WSI foundation.
WSI
Motivated by the desire to assess the efficacy of basin-specific watershed management efforts, I wanted to have a basin-specific indicator that integrates the aforementioned sustainability dimensions. Although numerous, the current indicators tend to focus on only a subset of the sustainability dimensions, and with one noteworthy exception, fail to offer basin-specific insight (Brown & Matlock, 2011).
The WSI assesses watershed sustainability with respect to watershed management efforts and most-effectively incorporates several of the sustainability dimensions previously discussed. The WSI has been applied to numerous watersheds around the world (Catano et al., 2011; Chaves, 2011; Cortés et al., 2012; Firdaus, Nakagoshi, &
Idris, 2014; Kretschmer, Wendt, Oyarzun, & Chaves, 2011; Maynard, Nascimento, Cruz,
18 & Gomes, 2017; Oliveira de Castro, Santos Loureiro, Vieira Santos, Silva, & Bonino
Rauen, 2017; Senent-Aparicio, Pérez-Sánchez, García-Aróstegui, Bielsa-Artero, &
Domingo-Pinillos, 2015). The basis for its development was a pre-existing UNESCO framework, HELP. HELP, the brainchild of UNESCO’s International Hydrology
Program, includes hydrology, environment, life, and policy. As shown in Table 1, the
WSI looks at each of these four variables across three parameters (Chaves & Alipaz,
2007). A given indicator is the average of its parameter values and the WSI is the average of the indicator values.
Parameter values are grouped into defined levels and assigned a score. Defined patterns (e.g. E-I-1) are shown in Figure 5 and mapped to their respective parameters in
Table 2. Notable features include: (A) nine distinct patterns; (B) values may be divided into even or uneven intervals, denoted by the letter E or U, respectively; (C) the score either increases or decreases with the value, denoted by the letter I or D, respectively; (D) in some instances, values are numeric, in others they are categorical; (D) parameter score may take one of five values (e.g. 0.00, 0.25, 0.50. 0.75, 1.00).
In the case of the quantitative hydrological indicator, it is assumed that the per capita water availability is based upon water originating from within the basin. It should be noted that this particular assumption is not valid for most urban watersheds, nor for those watersheds, located in places with water constraints, that may rely on imported water supplies.
In addition to providing a beachhead for my research effort, the WSI’s authors also recommend the use of the Habitat Conservation Trust Fund’s guidelines for selection of indicators. The bulleted guidelines that follow, set forth criteria intended to make the
19 Table 1. Indicators and parameters of the WSI. Parameters* Pressure State Response Indicators Hydrology Variation in the Basin per Improvement in basin per capita capita water water-use water availability efficiency in the availability in (long-term period analyzed the period average)
Variation in the Basin BOD5 Improvement in basin (long-term sewage biochemical average) treatment/disposal oxygen demand in the period (BOD5) in the analyzed period analyzed Environment Basin Percent of Evolution in basin Environment basin area with conservation Pressure Index natural [percent of (EPI, for rural vegetation protected areas, and urban) in the best management period analyzed practices] in the period analyzed Life Variation in the Basin Human Evolution in the basin per capita Development basin Human income in the Index Development period analyzed (weighted by Index in the county period analyzed population) Policy Variation in the Basin Evolution in the basin Human institutional basin’s Integrated Development capacity in Water Resource Index - Integrated Management Education in the Water expenditures in period analyzed Resource the period Management analyzed
20 Key: Parameter Score Value 0.00 0.25 0.50 0.75 1.00
(E-I-1)
-20 -10 0 10
(E-I-2)
-10 0 10 20
(E-I-3)
Very Poor Poor Medium Good Excellent
(E-I-4)
1,700 3,400 5,100 6,800
(U-I-1)
5 10 15 20 25 30 35 40
(U-I-2)
0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90
(E-D-1)
-10 0 10 20
(U-D-1)
0 5 10 15 20
(U-D-2)
1 2 3 4 5 6 7 8 9 10
Figure 5. WSI parameter score assignment. The values of the corresponding parameter, shown in the graphic map to one of five parameter scores which are in turn used to calculate the WSI (by author).
21 Table 2. Mapping WSI parameter value to score. Parameters
Pressure State Response
Hydrology (quantitative) E-I-1 E-I-4 E-I-3 (qualitative) E-D-1 U-D-2 E-I-3
Environment U-D-1 U-I-1 E-I-2
Life E-I-1 U-I-2 E-I-2
Policy E-I-1 E-I-3 E-I-2
resultant metric useful.
• Available: the indicator data should be available and easily accessible. They
should be collected throughout the watershed, published on a routine basis, and
made available to the public.
• Understandable: indicators should be easily understood by a diverse range of
nontechnical audiences.
• Credible: indicators should be supported by valid, reliable information, and
interpreted in a scientifically defensible manner.
• Relevant: indicators should reflect changes in management and in activities in the
watershed. They should be able to measure changes over time.
• Integrative: indicators should demonstrate connections among the environmental,
social and economic aspects of sustainability. (Chaves & Alipaz, 2007, p. 885)
The creators of the WSI intended that it would serve as a universal index capable of being applied to any basin for which the data is available. And although conceptually flexible, allowing for weighting the indicators differently depending on consensus, the
22 WSI does not adequately register enough dimensions to allow for the analysis of watersheds in which water imports or exports warrant consideration. Its application is generally limited to evaluation of basins in the countries for which data may be scarce, but could be incredibly useful if refined to be able to take into consideration characteristics of basins in the western United States, in particular, California.
If I were to conceptualize an analytical watershed boundary around all of the watersheds that are interconnected via interties, I’d see that many large swaths of the state of California would fall into a single boundary, due in large part to water transfers made possible by state, federal, and local engineering projects (Figure 6). The San
Francisco Peninsula is no exception. However, it is worth noting that an all-inclusive watershed boundary poses an analytical challenge which beyond being untenable would lead to generalized conclusions that are overly broad given the specific issues of the constituent local watersheds. In the interest of reaching meaningful conclusions that are relevant to local stakeholders I aim to retain watershed specificity.
Opportunities to Improve the WSI
For all its strengths, the WSI also has its shortcomings. With the motivation to improve the metric, I consider a few weaknesses. First, in its methodology, the WSI does not discuss what to do if data are unavailable, missing, or cannot be calculated. There is no guidance provided – it is unclear whether a particular indicator should be either dropped from the calculation or assigned an arbitrary value. As a practical matter, at the very least, you’d need to adjust the weighting if a value were unavailable. However, there is limited transparency in the results if weighting is altered from the default recommendations.
23 Figure 6. Water infrastructure in California. Many large watersheds are hydrologically interconnected both with and outside the state of California (Silverman, 2015).
With respect to quantity, there is no distinction between economic and physical water scarcity. This is an issue for underprivileged consumers. With respect to
24 hydrological indicators, taking annual data masks hydrological variability. Depending on whether or not water can be impounded in a reservoir, this may mask stresses on a watershed.
Also assumptions about historical patterns persisting into the future may not be valid. Impounding water in a storage reservoir to hedge against seasonal variation in precipitation may not be sustainable if a new norm comes into play. California may be entering an age in which the infrastructure, designed and constructed 50 or more years ago, was conceptualized with certain assumptions that may no longer be valid. For example, the assumption that precipitation falls as snow and slowly melts to fill surface reservoirs during the spring may not be valid going forward.
In addition, data sources may influence results. Most indices rely on secondary data. Relying on readily available data, may not be specific to the exact area of interest, and different sources often provide wildly different values.
With respect to basins and sub-basins, it may also be invalid to suggest that sub- basins can be aggregated to a larger basin up to 2,500 square kilometers for the WSI.
Furthermore, diluting information with an average (weighted or otherwise) masks important details behind a single numerical index that may be counterproductive. And a single numerical index may undermine the intrinsic value of the indicators by muting the variation, specifically, any outliers.
Also, the index does not use non-collinear factors. Many of the indicators share similar values (be it between the pressure, state, and response parameters or between the indicators themselves).
25 Weighting and evaluation of some factors is subjective. The methodology suggests that unless there’s a strong reason to change these weightings, they should be equal. However, it’s worth noting that, this discretionary decision may have perverse consequences. Depending on the situation, manipulation of the weighting may alter the outcome in such a way that it appears either more bleak, or more favorable.
Lastly, limiting scores to five values seems unnecessary. It limits the combination of possible outcomes. As a corollary, most WSI values fall within a small range.
Approximately 95% of results indicate intermediate sustainability. Undifferentiable results make it difficult to use the information. Decision makers may find it difficult to determine what to act upon and how to measure the effectiveness of their actions.
Water Footprint
Water footprint, like the concept of carbon footprint, is an accounting system; in essence it tracks the amount of water to produce, supply, and deliver goods and services to a specific location, person, or group. Unlike the WSI, the water footprint is, to a certain extent, watershed agnostic.
Water footprint accounting does not necessarily require the imposition of boundaries – geopolitical, or those of a watershed. However, by that same token, the absence of watershed-specific information dilutes the applicability of the analysis to specific watersheds.
A water footprint provides an accounting of all of the water necessary to support a given lifestyle – both direct and indirect uses: as an example, water to drink or the water involved to grow food or transport goods from where they were produced to where they
26 are consumed. Although water footprint is dependent on habits and, to a large extent, location, it is not typically examined at the watershed level.
Conceptually, water footprint draws the distinction between consumptive use of water – that is, that which makes use unavailable for other uses – and nonconsumptive use. This accounting convention then looks at three types of water, which have been associated with the colors blue, green, and grey, as follows:
• Blue water: includes surface and groundwater that are developed and managed for
human use;
• Green water: includes the water that exists in the environment that is not
developed for human use;
• Grey water: (N.B. not graywater): indicates the level and degree of contamination
resulting from processes that humans engineer – it is the equivalent volume of
water necessary to dilute that contamination to a level that is no longer harmful
(Fulton & Shilling, 2015).
In combination, these three dimensions of the water footprint help shed light on a different approach to analyzing water sustainability.
Watershed Management and Integrated Water Resource Management
Watershed management primarily refers to the actions taken within a watershed to sustainably distribute its resources. This may include policy, projects, and programs aimed at improving the features that impact communities (human, flora, and fauna) within the watershed’s boundaries. Similarly, Integrated Water Resource Management
(IWRM) focuses on sustainability; however, it is not bound by watershed limits and it
27 focuses on developing and managing water, land, and resources in a way that equitably addresses both economic and social welfare without degrading the ecosystem.
Both watershed management as well as IWRM may be assessed qualitatively or quantitatively with respect to their respective over-arching goals. Moreover, both should have tangible outcomes which can be deemed successful or unsuccessful, necessary or unnecessary, and effective or ineffective. And given the financial cost of undertaking either watershed management or IWRM activities, it behooves the public to understand which outcomes deliver meaningful results relative to the investment.
The SFC Watershed
The area of interest, the San Francisquito Creek (SFC) watershed, is situated on the San Francisco peninsula, snuggled up against the eastern slope of the Santa Cruz
Mountains, sprawling 45 square miles down to the San Francisco Bay (Herman,
Torregrosa, Kapla, & Hoong, 2007). Significant portions of the watershed are owned by the city or county, federal government, Midpeninsula Regional Open Space District,
Peninsula Open Space Trust, Jasper Ridge Biological Preserve, California Water Service and private parties (Figure 7).
The area includes Searsville Lake, Felt Lake, Lagunita Lake, and Bear Gulch
Reservoir (each of which is formed by a dam) as well as various natural habitats, and five communities from two counties, Palo Alto and Menlo Park in Santa Clara County, and
East Palo Alto, Portola Valley, and Woodside in in San Mateo County. Long-term precipitation is approximately 15 inches to 40 inches annually at lower and upper reaches of watershed, respectively (Metzger, 2002).
28 Figure 7. SFC watershed land ownership. Large swaths of SFC watershed are owned by various public and private entities (Cohen, 2002).
Although conservation and management of the watershed officially falls under the auspice of the Santa Clara Valley Water District, the SFC Joint Powers Authority
(SFCJPA) actually oversees the area and serves the communities (Materman et al., 2017).
The SFCJPA’s current work include three major projects to “reduce a proven flood threat, enhance ecosystems and recreational opportunities, and connect communities (San
Francisquito Creek Joint Powers Authority, 2018).” Two projects (Figure 8) are related to the infrastructure around the creek. The first focuses on the portion of the creek upstream of Highway 101, while the second targets the portion of the creek that runs from Highway 101 to the San Francisco Bay. SFCJPA’s third project is its Strategy to
Advance Flood Protection, Ecosystems and Recreation along the Bay (known as the
29 SAFER Bay Project), which evaluates infrastructure alternatives to protect Bayshore communities from extreme tides with sea level rise, and enhance shoreline ecosystem and access.
Figure 8. SFC flood protection projects (San Francisquito Creek Joint Powers Authority, n.d.).
SFC watershed comprises several subwatersheds and is transected by the San
Andreas Fault. Historically, throttled where hills meet the flatlands (point A, Figure 9), the SFC deposited sediment in an alluvial fan. Over time the course of the SFC became deeper. During floods, the SFC would overflow its banks depositing sediments that
30 Figure 9. SFC watershed and alluvial fan. Historical depiction of watershed and alluvial fan. Before the creek channel deepened, the creek would overflow leaving alluvial deposits downstream of point A (Sowers, 2005).
formed levees. As a result of construction of a dam which impounds water and sediment at Searsville Lake, the SFC carries limited material to deposit downstream (point B).
31 Records indicate that a levee passing point C (Figure 9) was a former course of the SFC.
Today, the SFC runs through a channel that was engineering in the 1930s. (Oakland
Museum of California, n.d.)
Although allocations vary by water system (Table 3), the majority of SFC watershed’s residents receive water service supplied by an aqueduct that runs nearly 200 miles from the Hetch Hetchy Reservoir located in Yosemite National Park (California
Water Service, 2016; City of East Palo Alto, 2016; City of Palo Alto Utilities, 2016;
Menlo Park Municipal Water District, 2016; San Francisco Public Utilities Commission,
2016).
Table 3. Allocation disparity in the SFC watershed. Communities of SFC Watershed Served by California Water East Palo Palo Menlo Service Company Alto Alto Park Woodside Portola Valley Population (thousands) 194* 25 67 15 ISG (MGD) 35.68* 1.96 17.08 4.46 Use (MGD) 29.05* 1.57 9.68 2.63 Fixed Charge ($/mo) 20.29** 13.73 16.77 20.08 Variable Rate ($/CCF) 6.73** 3.82 6.73 5.53 Usage (GPCD) 155** 64 153 158 Income ($PCA) 125,559 99,621 18,527 75,257 77,766 * data for Bayshore district and Bear Gulch districts of California Water Service ** data for Bear Gulch district, which serves Woodside and Portola Valley (by author).
32 There are several native species of ecological interest within the SFC watershed, including steelhead trout. The SFC is famous for hosting one of the last remaining wild populations of steelhead trout in the San Francisco Bay.
Similarly, there is a diverse population and robust economy within the watershed boundary; however, intertwined within the excessive affluence of the watershed lies the economically disadvantaged community of East Palo Alto, bringing to mind the inequalities and iniquities of the poor in resource allocation. Forest and low-density residential neighborhoods typify the upper part of this basin, whereas high-density housing and commercial businesses are more common in the lower reaches, as seen in
Figure 10 (Bicknell & Fusco, 2016). Wealth is also concentrated at the higher elevations and all but absent where the creek pours in to the Bay. It should be noted that along with
Stanford University, some of Silicon Valley’s most successful commercial businesses were started in the SFC watershed.
The Joint Powers Authority (JPA) allows the SFC communities to work toward their mutual interests as part of the same organization. The SFCJPA plans, designs, and executes projects that reduce the threat of flood, enhance the ecosystem, augment recreation, and connect communities. Because the SFC watershed is part of the Lower
Peninsula watershed which is part of the Santa Clara Valley, the Santa Clara Valley
Water District (SCVWD) is a member agency of the SFCJPA.
The SFC watershed provides a good case study for critique and validation of the refined watershed sustainability metric owing to the watershed’s water imports, extant
JPA, as well as its socioeconomic diversity.
33 Figure 10. SFC watershed satellite map these are beautiful figures. Contrast between upper watershed which is typified by natural vegetation and limited development while lower watershed has been highly developed (US Geological Society, 2001).
Research Question, Hypotheses and Specific Aims
My primary research question was: How may the WSI be adapted to provide a more useful framework for watersheds in which imports and exports warrant consideration?
My hypotheses were:
• The WSI could be refined and better address watershed sustainability in settings
where imports and exports warrant consideration.
• The SFC watershed would perform poorly in a sustainability analysis, specifically
in one which employs the refined watershed sustainability metric, in hydrological
34 and environmental dimensions, despite the perception that the watershed is
healthy and well-managed.
• Current management efforts do not adequately address the dimensions on which
the watershed sustainability analysis indicates deficiencies.
Specific Aims
To examine these hypotheses and address my research question, I:
1. Applied the WSI to the SFC watershed; identified what limits the WSI from being
applied to watersheds with inter-basin water transfers.
2. Identified and evaluated indicators that reflected and could quantify watershed
sustainability.
3. Used selected indicators to formulate a new model; applied it to the SFC
watershed.
4. Analyzed the results: identified current watershed management practices within
SFC watershed and evaluated their efficacy.
35 Chapter II
Methods
The approach used to investigate the aforementioned inquiries included data collection, calculations, evaluation of indicators, model development, and analysis, as described below.
Application of the WSI to SFC Watershed – Data Acquisition
In order to establish a baseline, I calculated the WSI for the SFC watershed. The metric used three parameters for each of five indicators as previously described in Table
1. Based on the historical record, I was able to determine that my long-term averages would be based upon available data from 1932-1941 and from 1951-2016. I also selected the study period to be 10 years from 2007-2016, based on availability of data. All values were converted into WSI scores according to the methodology described by Chaves and
Alipaz, with exceptions noted (2007).
The four primary indicators measured include: hydrology, environment, life, and policy.
Hydrology
The hydrological indicator is bifurcated into quantitative and qualitative aspects, denoted H1 and H2, respectively.
The quantitative hydrological indicator utilized USGS data in conjunction with historical population estimates and GIS data to calculate the pressure and state
36 parameters. The pressure parameter measures the variation in the basin per capita water availability during the study period, relative to the long-term average, H1:P, and can be expressed as:
− : = Where QPCA is the annual volumetric flow rate divided by the respective population and the subscript “lt” designates “long-term average” while the subscript “sp” designates
“study period”.
The discharge data used to calculate the volumetric flow for the QPClt was determined using available discharge data from the USGS Station 11164500 at Stanford
University. Ideally, the measurement would capture all available water. However, this may not be possible in watersheds with withdrawals or in which water is impounded in reservoirs.
According to SFCJPA’s Watershed Analysis and Sediment Reduction Plan, this station provides the best long-term record of flow on the creek. It captures 37.5 mi2 of the watershed.
The population was estimated using GIS. The watershed boundary was mapped in ESRI’s ArcGIS software and the population determined using 2010 US Census population data. To determine the QPClt, the average volumetric flow rate was determined and then divided by an interpolated population. I took the watershed population estimated using GIS as my starting point. I then determined the Bay Area
Population Growth since 1930 using data from San Mateo and Santa Clara Counties to determine a proxy for the watershed population in 1930 (that is, the percentage of the
2010 Bay Area population that resides within the watershed was applied to the 1930
37 data). I then used that 1930 watershed population proxy to interpolate the watershed population for each year where volumetric flow data was available.
The state parameter of the hydrological indicator, H1:S, is the long-term average basin per capita water availability.
This is the same value used in the calculation : = of the hydrological pressure parameter.
The response parameter of the hydrological indicator, H1:R, evaluates the improvement in water-use efficiency in the basin in the period studied. Recent drought data suggested that the population within the watershed was able to reduce its water consumption by more than 25% (with a statewide average reduction slightly above 20%) according to the California State Water Resources Control Board (2017). Given that suppliers serving this area reduced their consumption between 21.7% and 38.8%, and that each of them met their state-mandated conservation target by year end of 2016 (Table 4), it seems appropriate to assign a value of “Excellent.”
The qualitative hydrological indicator, as defined by the WSI, utilizes five-day biochemical oxygen demand (BOD5) measurements for the pressure and response parameters values. The motivation behind using BOD5 relates to the perceived availability of data as well as its correlation to other important water quality parameters
(Chaves & Alipaz, 2007). However, as noted by Hallock (2002), the Water Quality
Index (WQI) can be used to combine multiple constituents, aggregate over time, and provide a single score to indicate health relative to expectations. The WQI integrates data about temperature, pH, fecal coliform bacteria, dissolved oxygen, nutrients, and sediments. It seems appropriate to replace the exclusive use of BOD5 with a more
38 Table 4. Water-use efficiency for SFC water suppliers. Applicable State-mandated cumulative savings Conservation Standard achieved by Total 3/1/16 6/1/16 Supplier as Estimated Population Supplier Name (previous) (current) compared to 2013 R-GPCD Served
California Water Service - Bear Gulch 36% 2% 28% 72.8 69,852
City of East Palo Alto 8% 8% 23% 41.6 29,143
City of Palo Alto 24% 0% 22% 70.9 64,403
City of Menlo Park 16% 0% 39% 48.3 16,066 June 2015 through November 2016 Cumulative Savings and Compliance data (Metropolitan Transportation Commission and the Association of Bay Area Governments, n.d.).
flexible metric. Therefore, I proposed that an adapted WQI be used in place of BOD5 to measure the hydrological pressure and state parameters for the qualitative indicator.
Available data for any of the constituents (i.e. BOD, dissolved oxygen, fecal coliform, nitrates, pH, temperature, total dissolved solids, total phosphate, turbidity) were converted to an index score ranging from 0 to 1 (instead of 1 to 100). The index scores for each water quality constituent were then be aggregated into a single score by averaging the values, provided they are for approximately the same duration, e.g. one month. The individual constituent indices were then assigned relative weighting in order to yield the adapted WQI.
= Where ri is the relative weighting for constituent i of n constituents for which data is available, given by the formula:
= ∑ 39 Thus, the pressure parameter for the qualitative hydrological indicator, H2:P, becomes the variation in the basin WQI in the period studied, relative to the long-term average and may be written:
− : = . As before, subscripts denote the reference period, “long-term” or “study period”.
Similarly, the state parameter for the qualitative hydrological indicator, H2:S, is simply the corresponding, long-term average value of the WQI for the basin.
Although intermittent, water quality = data was . available from Grassroots Ecology for various stations along SFC between 2013 and 2015. Grass Roots Ecology is a volunteer-run non-profit organization that focuses on local ecosystem restoration. As part of their mission they focus on water quality monitoring. They have been collecting samples in five watersheds in Silicon Valley – including that of the SFC. Data for the
San Francisquito Creek is spotty, but viable for the monitoring stations located on SFC at the Piers Lane Bridge (Station 1), on Los Trancos Creek at the Piers Lane Bridge (Station
2), and where SFC crosses East Bayshore Road (Station 5). Grassroots Ecology data typically includes depth (cm), temperature (°C), conductivity (µS), dissolved oxygen (O2,
% and mg/L), pH, and Turbidity (NTU/JTU).
Due to the limited data available, I elected to redefine the most recent month’s data as the “study period” for the pressure parameter of the hydrological quality indicator and truncate the “long-term” to the years for which data was available 2013-2015 for both the pressure and state parameters of the hydrological quality indicator.
40 For each of the available constituents of interest (temperature, dissolved oxygen, pH, and turbidity), I determined index values and then aggregated the values (for the various months as well as for stations 2 and 5). I determined the relative weighting for each constituent and then calculated the respective WQI value. Since the WQI value scale coincides with the WSI scale, the score for H2:S was the value.
The response parameter for the water quality component of the hydrology indicator, H2R, measures improvement in wastewater treatment within the basin during the period studied. The assessment was a subjective one; however, given (a) the existing adequate infrastructure and (b) recent infrastructure improvements, including the relocation of a sewer main in East Palo Alto (SFCJPA, 2018), it seems appropriate assign a value of “Good”. In addition, as is evident from Palo Alto’s long-range facilities planning, there is a commitment to improvement (City of Palo Alto, 2017).
Environment
The indicator for the environment is also represented by three parameters: EP, ES, and ER, corresponding to pressure, state, and response, respectively.
The Environmental Pressure Index (EPI) is used for EP, and can be written:
, % % where = the frame= of reference is the study period.
For the SFC watershed, only 15% of the land use is dedicated to rangeland or agricultural use (Bicknell & Fusco, 2016). The San Andreas Fault zone is where one is likely to find agricultural activity (also, it appears that a significant portion of the designated special conservation areas are located within Stanford’s agriculture leaseholds
41 (Santa Clara County, 2001). According to 1995 data from Association of Bay Area
Government, 4,100 acres of the SFC watershed were dedicated to rangeland and another
490 acres represented agricultural land use. It appears that changes to rangeland and agricultural land use have been de minimis. As such, the significant term in the equation becomes the population growth. The population data derived for the hydrological indicators was reused for this calculation.
The state parameter of the environmental indicator is the fraction of the watershed basin under natural vegetation. For consistency, it is assumed that this percentage be roughly representative of the study period. According to the Santa Clara Valley Urban
Runoff Pollution Prevention Program, 44.7% of the watershed is forested, which for the purpose of this exercise was considered natural vegetation (n.d.).
The final parameter for the environmental indicator, response, looks at the evolution in basin conservation areas during the period studied. This includes both protected areas as well as best management practices (BMPs).
Although not expecting to find large swaths of land being converted to conservation easements, given the amount of land currently under protection, I was able to find several noteworthy examples of best management practices being implemented within the watershed. SFC hosts the most viable remaining native steelhead population in the South Bay. In 2013, a Bonde weir was removed from the SFC restoring the streambed to a more natural course. The concrete barrier had impeded steelhead trout en route to their spawning grounds (Kinney, 2013). Open space preserves continue to protect land in the upper reaches of the watershed and the SFC retains a natural channel
(a rarity in the Bay Area, where most streams are confined to concrete channels).
42 However, proponents of the removal of Searsville Dam, continue to rally for the restoration of 20 miles of habitat for the endangered steelhead trout. Given the complex medley, it appears that the outcome during the study period was neutral or slightly positive. (also, I wouldn’t know how to quantify it otherwise given no increase in conservation land area).
Life
Life is the penultimate WSI indicator and focuses primarily on economics, specifically income. The pressure parameter, LP, reflects the variation in the Human
Development Index-Income (HDI-Income) between the study period and the preceding time period. Since HDI data has only recently become available for California, and the
HDI-Income metric spans a two-year period, I deemed it appropriate to use 2011, the midpoint of my study period (2007-2016) as my reference point. Conveniently, 2011 fell into the 2010-2012 reporting window. The preceding reporting period was 2006-2008.
The pressure parameter for the life indicator, LP, can be written:
− − − = Where the subscripts “sp” and “pp” refer to −“study period” and preceding period”, respectively. I made use of Measure of America’s California Human Development
Report titled “A Portrait of California (2014-2015)” to obtain the American HDI-Income values for San Mateo County and Santa Clara County (Lewis & Burd-Sharps, 2014).
Absent a good indicator of the relative weighting of population between the two states, and given that the values were similar, I averaged them to determine the American HDI-
Income for the basin.
43 It is worth noting that the American HDI-Income is different from the HDI-
Income. Measure of America Report uses established goal posts to determine and
American HDI-Income. The goal posts are the selected maximum and minimum values and the American HDI-Income is given by the following formula:
log( ) − log(min ) − = 10 The values of American HDI-Incomelog(max range from 0 to 10. ) − log(min )
The state parameter for the life indicator, LS, is the basin HDI. Again, I relied on
2010-2012 data from Measure of America’s report. The American HDI is the simple average of the health, education, and income indices and the values theoretically range from 0 to 10. However, given that the scale for the HDI is 0 to 1, it seemed appropriate to evaluate the score based on the national HDI value. Since the average American HDI value is ~5 relative to the HDI value of 0.92, it seems reasonable to assume that the
American HDI value of 7.07 would earn a score equal to or greater than .92. Therefore
I’ve determined the score to be 1.
The response parameter for the life indicator, LR, is the evolution in the basin HDI during the study period.
− = I applied the methodology from LP to calculate L R, with one noteworthy exception, use of the HDI, in place of the HDI-Income. Again, making use of data from Measure of
America, I substituted the American HDI in place of the HDI.
44 Policy
The last indicator, policy, also has pressure, state, and response parameters: PP, PS, and
PR, respectively. The pressure parameter measures the variation in HDI-Education during the study period, compared to the previous period.
− − − = As with the parameters for the life indicator, − American HDI-Education was used in place of the international HDI-Education. The American HDI-Education is based on the
Educational Attainment Index and the Enrollment Index. These two indices are calculated using the same formula:
− min = 10 The actual value for the Educationmax Attainment − Indexmin is the sum of (a) the fraction of the population (25 years or older) that has at least a high school diploma; (b) the fraction of the population that has at least a bachelor’s degree; and (c) the fraction of the population that has a graduate or professional degree.
The actual value for the Enrollment Index is the combined gross enrollment ratio.
The combined gross enrollment ratio is sum of the enrollment ratios for primary, secondary and tertiary education. The enrollment ratio is the number of students enrolled in a given level of education, as a percentage of the population of the corresponding age group for that level of education (United Nations Development Programme, n.d.). The
American HDI-Education is the weighted average of the Education Attainemnt Index and the Enrollment Index, as follows:
2 1 − = . + 3 3 45 The state parameter of the policy indicator is the institutional capacity in IWRM.
Given the existence and activity of the SFCJPA, the SCVWD, local governments, and federal agencies, it seems that SFC watershed has excellent institutional capacity.
The response parameter of the policy indicator is the evolution in the watershed’s
WRM expenditure during the study period. As a proxy for WRM expenditure, I looked at the SFCJPA’s operating expenses. They have increased by approximately 66% from
FY 06-07 to FY 16-17. In addition, there appears to be an upward trend in spend on
WRM within the SFC watershed, including feasibility studies as well as the aforementioned tree major infrastructure projects.
Application of the WSI to SFC Watershed – Calculation
Once all of the values for the parameters are determined, calculation of the WSI is relatively straightforward. Parameter values are mapped to aforementioned scores and the overall indicator, I is the average of the parameter scores, such that:
+ + = Where IP, IS, and IR, are the respective pressure,3 state, and response parameter scores.
The overall hydrology indicator, H, is the average of the quantitative and qualitative components of the hydrological indicator:
+ = The WSI can then be calculated as the average 2of the indicators:
+ + + = 4
46 Evaluation of Indicators
The WSI covers several of the dimensions of sustainability previously identified, including: hydrology, environment, economy, education, and policy. However, it lacks the ability to account for water transfers (imports and exports). Moreover, the WSI fails to address the dimensions of social justice, resiliency, and efficiency adequately.
Building upon the work done by Chaves and Alipaz (2007), I proposed some upgrades, including: optional, supplemental indicators and adjustments (beyond the aforementioned refinements) to address these shortcomings.
Inter-basin water transfers
To account for inter-basin water transfers, I recommended and applied a three- pronged approach that considers hydrology, economics, and efficiency.
The hydrological aspect is relatively straightforward, an adjustment to account for the addition (imports) or removal (exports) was be applied to the state parameter for the hydrological quantitative sub-indicator. For the SFC watershed, transfers received from the SFPUC system may be estimated at a high level by approximating the pro rata supply delivered to the watershed population and then annualizing it.
For example:
( . ) ( . ) = ℎ ′ Imports would be added to (and exports would be subtracted ( . ) from) the numerator in the state parameter and scores would be applied as normal. To account for the economic burden or benefit associated with the water transfer, I recommend the addition of an efficiency parameter. This parameter would also measure the productivity, or waste,
47 associated with the transfer by looking at energy and water loss. This new indicator will be presented in more detail later in the methods.
Social Justice
Given that sustainability is concerned with how present and future generations meet their needs, it seems appropriate to look at where disparity may exist and focus on the most marginalized members of the community. Some members of a given community may not be able to enjoy its benefits as a result of their race, income, or where they live (Cooley et al., 2016). Social justice and equity indicators are limited and data is often not available at a granular level (Lampmann, 2013). The ideal approach would be to use community-level indicators, such as those identified in Determinants of
Equity: Identifying Indicators to Establish a Baseline of Equity in King County (Beatty &
Foster, 2015).
There is a need for more communities to look at equity and social justice – and although metrics are not well-established, viable indicators exist. In King County, 14 determinants were identified and mapped back to 21 key equity indicators, shown in
Figure 11. These top tier indicators were selected from a total of 67 community-level indicators (Beatty & Foster, 2015). And although the scope of this investigation does not include the effort required to quantify these equity indicators for the SFC watershed, this approach should be recognized as the preferable methodological approach. Unlike the existing indicators, for which data is readily available, I would begin with the inclusion of a single parameter for state, SS.
The calculation of the parameter would involve three steps:
48 1. Calculate the index value for each of the community-level indicators (for which
there is data available) for people of color, limited English proficiency, low-
income, and disadvantaged neighborhoods. (Measures for indicators are provided
in Appendix 2)
− min − = 2. Average the community-level indicators to determinemax the value − formin SS .
3. Transfer the value directly to the score for SS.
Efficiency
The introduction of inter-basin water transfers is the primary motivator for the inclusion of an efficiency indicator; however, the breadth and depth of its utility is readily apparent. Like the social justice indicator, my initial recommendation is to only include a state parameter, Efficiency has three primary dimensions in this context: water,
S energy, and economics.ℰ . Water loss sub-indicator, is simply a measure of the
1:S, efficiency of the water transfer. How much water isℰ unaccounted for as a result of its transfer? For a system without inter-basin transfers, this would simply be the unaccounted for water as a percentage of water produced. However, for watersheds with inter-basin transfers the transmission losses or water loss due to evaporation (in reservoirs or canals) may also need to be taken into account. Therefore,
where the estimated waterℰ loss : = percent1 − can be calculated by dividing % the sum of the estimated system water losses and the pro rata water losses associated with the water transfer by the estimated total water system production for the watershed. For watersheds
49 Figure 11. Equity indicators. King County’s top 21 equity indictors relate to 14 determinants (Beatty & Foster, 2015).
with multiple systems, each system may be approximated by proration.
50 The energy efficiency sub-indicator, , looks at the amount of electricity
2:S required to operate water systems within the ℰwatershed. This includes urban supply
(including pumping), irrigation, and treatment (such as desalination). For watersheds with inter-basin transfers, this also includes the pro rata energy consumption associated with the infrastructure to wheel the water.
The energy requirement for sourcing, conveyance, and treatment of water is huge.
Pumps are largest consumer of electricity. Options such as desalination are also highly energy-intensive.
As a general note, the efficiency of supply may be related to where the watershed is. Southern California conveyance is less efficient (a 2000 ft climb up the Tehatchapi
Mountains is not a trivial lift). Energy use depends upon distance, elevation, and quantity
(CPUC, 2016). These factors may be driven by hydrology, precipitation, demand, and pump efficiency, too.
The electricity energy associated with water use within the watershed can be determined by estimating A, the electricity usage to operate the local water systems
(again, prorated for watersheds in which systems serve customers beyond the confines of the boundary); B, the prorated electricity usage associated with the inter-basin transfer; and C, the total electricity use within the watershed. The sub-indicator, would then
2:S be calculated as follows, ℰ ,
− ℰ : = The third efficiency sub-indicator, , +is a proxy for economic efficiency, and
3:S can also be thought of as an indicator of vulnerability.ℰ Since the cost to build, maintain, and improve infrastructure dominates water system expenses, the economic efficiency of
51 a watershed will be reflected in cost avoidance outside the basin boundary. Simply put, the sub-indicator is calculated as the sum of all local developed water supply divided by the total developed water supply (which includes local and non-local supply).
ℰ : =
Resilience
To a certain extent, the aforementioned parameters may allude to risk, vulnerability, and the speed of recovery, or resilience. However, in lieu of using indicators, it seems appropriate to suggest an alternate approach to quantifying watershed resiliency. By using a time series, one can track the degree to which a given indicator is changing as well as the speed at which it changes.
Like sustainability, resiliency has numerous dimensions. Repeating this exercise at intervals will provide insight specific for each of the indicators mentioned. The resultant time series becomes the metric for resilience.
Model Development
In addition to my previous recommendations, I also am suggesting the following refinements to the WSI methodology originally outlined by Chaves and Alipaz:
• Utilize a treemap to present data relevant to the watershed sustainability analysis,
rather than using a single numerical representation.
• For state parameters, utilize data from the study period to better characterize
current conditions.
52 • Adjust the weighting for the pressure, state, and response parameters to 30%,
50%, and 20%, respectively.
• Provide guidance that specifies the “study period” to be a 1-2 year timeframe.
• Recommend repeating the sustainability assessment at 5-year intervals.
• Utilize all of the indicators and parameters for which data is available.
• Update this metric as other data becomes available.
Furthermore, I have renamed this new tool, the Watershed Sustainability Visualization
(WSV). It is readily available on the web at https://sites.google.com/view/wsv- model/home.
Model Application to the SFC Watershed
The final part of the methodology will focus on the application of the WSV to the
SFC watershed. Specifically, I noted that the activities within the management plan contribute to watershed sustainability. To the extent possible, these activities have been quantified in the WSV.
I evaluated the effectiveness of the watershed management activities through the following procedures:
1. Identified which dimensions of sustainability are most problematic for the SFC
watershed (based on the indicators with the poorest performance in the WSV) in
order to determine which watershed management activities and efforts are most
relevant and likely to enhance sustainability.
2. Determined what watershed management activities could improve deficient
indicators.
53 3. Analyzed how watershed management plan improvements would affect watershed
sustainability.
54 Chapter III
Results
I was able to apply the WSI to the SFC watershed using existing data. I determined that, although problematic, it was possible to account for inter-basin water transfers in a sustainability metric.
In order to develop a new model, I identified and evaluated indicators that were, or could be, used to quantify watershed sustainability. I then used selected indicators to formulate the WSV model. The new model accounts for inter-basin water transfers, includes additional dimensions of sustainability, improves on the WSI’s methodology, and reveals more insight into each dimension of sustainability.
I applied the WSV to the SFC watershed using available data and analyzed the results. This allowed me to identify opportunities for improvement and evaluate the efficacy of prescriptive watershed management activities.
SFC WSI
Information available in existing data was sufficient to apply the WSI to the SFC watershed (with the refinements explained in Methods). The WSI for the SFC was 0.71 which corresponds to good sustainability overall (Table 5). The policy indicator and quantitative hydrological sub-indicator had the best (0.92) and worst (0.42) results respectively.
55 Table 5. SFC WSI: parameters values and indicator scores.
Sub- Pressure State Response Indicator Indicator Sub- indicator Result indicator Level Score Level Score Level Score Result
Quantity -68.0% 0.00 3040 0.25 Excellent 1.00 0.42 Hydrology 0.58 Quality -4.0% 0.75 0.76 0.76 Good 0.75 0.75
Environment 5.3% 0.50 44.7% 1.00 0.0% 0.50 0.67
Life -6.1% 0.50 7.07 1.00 1.1% 0.50 0.67
Policy 4.0% 0.75 Excellent 1.00 65.7% 1.00 0.92
WSI Result 0.71
SFC WSV
Again, existing data were used to apply the WSV to the SFC watershed.
However, data was not readily available for several of the sub-indicators. The resulting treemap is shown in Figure 12. The area of each block represents relative weight of indicators and parameters while color indicates performance, where red is low and green is high.
WSV Model
The primary outcome of this research is a novel approach to watershed sustainability analysis. The WSV is both a model as well as an actual tool for watershed sustainability practitioners to use. It is readily available on the web at: https://sites.google.com/view/wsv-model/home.
56 Figure 12. SFC WSV. Red indicates poor sustainability, specifically with the pressure parameter of the quantitative sub-indicator. Green indicates excellent sustainability in the state parameters for environment, life and policy as well as the response parameters for the quantity sub-indicator and policy indicator (by author).
The site provides access to WSV information, as well as the tool itself, and examples including: a data entry portal, calculation worksheets (with formulas to perform the calculations based on the data), and the resulting treemap chart. Users can easily copy the spreadsheet template file and apply the WSV to a watershed of their own choice.
Results can be analyzed and communicated to watershed managers and stakeholders to readily identify where the watershed is performing well or to identify areas for improvement.
SFC Watershed Sustainability Analysis
The WSV allowed me to easily identity which dimensions of sustainability are most problematic for the SFC watershed (based on the indicators with the poorest
57 performance in the WSV) in order to determine which watershed management activities and efforts are most relevant and likely to enhance sustainability.
There is little evidence to suggest that current efforts do not enhance the sustainability of the SFC watershed. However, it is also worth noting that the poorest performing indicators may not be improving as a result of current watershed management activities. As is evidenced by the red areas in the WSV treemap, there is evidence of water stress in the watershed. The per capita water availability in the SFC watershed is concerning, even when taking inter-basin transfers into account.
58 Chapter IV
Discussion
The WSV model provides a novel way to analyze and expand upon data that had previously been masked by reduction to a single numerical index. Here, I revisit my hypotheses, interpret the outcome of my investigation, note what additional work has been identified, and summarize the key takeaways of this project.
Interpretation and Significant Implications of Results
Beyond fulfilling the specific intentions of this research, I was able to leverage my results to draw some conclusions on my hypotheses.
Specific Aims
With respect to my intention of applying the WSI to the SFC watershed, it was immediately apparent that the metric did not adequately account for the hydrological gains. Furthermore, the WSI metric does not have a way to account for drawbacks associated with inter-basin transfers (such as inefficiencies associated with energy and water loss). Because the WSI metric itself comprises several estimates, devising a few rudimentary modifications seemed like a reasonable way to improve it.
While applying the WSI to the SFC watershed, it became apparent that indicators or parameters that seemed straightforward and reasonable could be tweaked to integrate and provide more relevant information, as in the case of the inclusion of additional water
59 quality details or the move to use current data for the state parameter of the qualitative sub-indicator for hydrology, respectively.
Starting with a functional definition of watershed sustainability, I easily identified several dimensions that I felt warranted consideration. The WSI indicators covered (at least, in part) the dimensions of hydrology, environment, economy, education, and policy. The remaining dimensions: efficiency, resilience, and social justice consumed my attention.
I recognized that the resilience dimension would best be addressed by replicating the exercise at regular intervals and comparing the results. This exogenous dimension relates more to the use of the tool, as opposed to the tool itself.
While simultaneously thinking about how to account for the non-hydrological dimension of inter-basin water transfers, it became apparent that I’d need a separate indicator for the efficiency dimension to look at constrained resources: water, energy, and capital. By parsing out each constraint as a sub-indicator, I drilled down into what drives inefficiencies. Although conceptualized with the intention of providing additional accounting for watersheds with inter-basin water transfers, it has been designed to accommodate those without transfers, too.
The social justice and equity dimension of sustainability challenged me.
Established metrics that measure progress are plentiful, and data for them is readily accessible. However, when it comes to social justice and equity, which are concerned with how society provides and cares for each member, metrics are scarce. It’s imperative that data and metrics be accessible, digestible, and informative (Lampmann, 2013).
60 Rather than defer to established norms (as an example, international indices like
HDI), I sought out community-level indicators. The use of local metrics provides a holistic picture of the most marginalized members of the community and make it easy to focus attention where disparities exist. King County, driven by goals to encourage active engagement, is pioneering work to create an actionable database of equity indicators. It is my intention to highlight and promote that this work be replicated elsewhere, as these conversations need to be a meaningful part of the dialogue in every community.
In order to integrate King County’s Tier 1 indicators into my analysis, I have proposed an indexing methodology and recommended that values be calculated for the attributes that most often cause members of the community not to enjoy the same benefits: race (people of color), where they live (disadvantaged neighborhoods), income
(low-income), and language barrier (limited English proficiency).
To improve the WSI, I looked at ways to combine the data. Attempts to avoid multicollinearity steered me away from trying to utilize a single numerical representation.
Instead I recognized that the indicators, sub-indicators, and parameters for my analysis had a hierarchical relationship. Rather than mask the vibrancy of individual results by repeatedly averaging factors at a given level, I converted the data into a visual representation. The treemap was a natural choice given the embedded hierarchy (Figure
12). I chose an intuitive color scheme that is frequently employed in spectral data, where bright red indicates unfavorable results and bright green indicates favorable results. A gray color represents results the midrange and shades vary between these three colors depending on where the value falls within the range, in this case 0.00-1.00.
61 The treemap makes the relative weighting of metrics readily apparent. The size of the box of a treemap corresponds with the relative weighting, that is, the area is proportional to the weighting. The effect of the treemap is to draw your attention toward the outlying values, either good or bad and toward those which are most heavily weighted.
In addition, using dynamic software, the user is able to drill down into indicators and sub-indicators to see higher levels of detail. Rather than hide this information, the tool enables it to become more prominent with each drill down.
In order to ensure consistent results, I created a template for the WSV model. I then, entered the data acquired from my earlier exercise (of applying the WSI to the SFC watershed) and readily saw where the strengths and deficiencies were in the watershed’s sustainability profile.
Deficiencies were prominent in the hydrological indicator, specifically related to the water available per capita and the decrease in water available per capita. The station used for the data on stream flow is located at the junction of the San Francisquito Creek and its tributary Los Trancos Creek. As previously mentioned, this station has historically been used to measure stream flows. However, it remains downstream of the largest reservoir, Searsville Lake. It is unclear how much water is being withdrawn at the reservoir. Ongoing, heated, discussions have been underway debating the future of the
Searsville Dam. With respect to watershed sustainability, I question whether or not the removal of the dam improves the hydrological sustainability of the watershed, since current withdrawals are typically used for fire protection or irrigation (which would recharge the groundwater, but has not been the case since 2013 when the most recent
62 drought began). That said, allowing the water to run downstream would enable fish passage. Steelhead trout would gain access to an estimated 20 miles of spawning habitat.
Beyond the environmental and political actors debating the future of the dam are some pragmatists wondering what would happen to the 2.7 million cubic yards of sediment currently trapped behind the 65-foot dam. In my estimation, this hotly contested issue falls into the broad camp of watershed management. Admittedly, the WSV would not change significantly as a result of the removal of the dam due to (a) a 90% reduction in the volume of the reservoir behind the dam (that is, minimal water is being impounded and it’s not being extracted) and (b) the hydrology quantity indicators are relative to the population. As the trend indicates, population within the watershed will continue to increase.
Hypotheses
As a result of this investigation, I was able to revisit my hypotheses and determine which had been supported or refuted.
My experience indicates that I was accurate to assume that the WSI could be refined such that it could address watershed sustainability in settings where imports and exports warrant consideration.
I was both correct and incorrect in my hypothesis that the SFC watershed would perform poorly in a sustainability analysis. I had conjectured that both hydrological and environmental indicators would indicate deficiencies, despite the perception that the watershed is healthy and well-managed.
As previously indicated the sub-indicator for quantitative hydrology was unfavorable; however, the qualitative sub-indicator (for both the WSI and WSV) had
63 reasonably good results. It’s worth noting that the response parameter result is highly debatable. I doubt that others would reach the same conclusion I did absent quantitative data. This is a general shortcoming of the WSI methodology: that qualitative assessment of indicators is highly subjective and likely inconsistent. That said, there is significant evidence to suggest water stress within this watershed, absent the inclusion of groundwater supply.
My final hypothesis assumed that current management efforts do not adequately address the dimensions on which the watershed sustainability analysis indicates deficiencies. Given the complexities related to the dam removal, I am hesitant to draw a definitive conclusion. I would instead offer the following: the concerning issues are being addressed, and it remains to be seen whether the outcome will have a favorable or unfavorable impact on sustainability.
Results in Context
Judging by the references in the literature and the proliferation of its use, the WSI appears to be a popular metric. I was initially perplexed by the widespread use of this metric. However, it appears that basin-specific metrics and the selection of readily available indicators has made it very accessible.
There are many organization and investigators around the world that have applied the WSI to various watersheds. Most of the watersheds are in the developed world. It is my hope that the WSV may see widespread use as well, specifically in the water-scarce regions of the western US.
As a simple comparison, I’ve selected several of the watersheds for which the
WSI data was available and applied the base WSV to them. The resultant treemap charts
64 can be found in Ancillary Appendix 2. The visualization avoids both the confusion with having a single number with limited context and the numerical glare of being inundated with nearly 50 values in a table.
Visualizing the WSI data enhances the analysis. It readily shows the outliers
(rather than masking them in an average). It also makes the relative weighting completely transparent and it offers the ability to aggregate watershed data (i.e. from sub- watersheds). If data is not available and no suitable proxy is available the WSI breaks down; however, the visualization can still show results absent values (within reason).
The visualization is flexible, values can be reweighted or left as blank placeholders to indicate data was not available. Even absent the additional improvements incorporated in the WSV, the visualization of WSI data is a powerful improvement.
Opportunities for Methodological Improvement
In an attempt to identify and address shortcomings with the WSI, I have inadvertently created many opportunities for improvement with the WSV. I note that most of these flaws were unintentional and that as a practical matter, most discretionary decisions in modeling have both pros and cons.
General Observations
Like its predecessor, my own methodology has weaknesses. The continuation of the use of qualitative levels on parameters was a poor choice. Despite my frustration with the subjectivity for the parameters that used qualitative assessment (or those that inadequately described how a quantitative metric be determined), I deferred to the status
65 quo. This decision was equal measures personal deference to precedent and absence of a better solution.
In developing the WSV, I tried to strike a balance between reasonable estimates that could be readily understood from which powerful insight may be derived and intuitively obvious data from which conclusions are limited. Although I am interested in leveraging technology, I recognize that GIS has a steep learning curve and may be foreign to many. I also recognize that, although robust, equations may be intimidating for the layperson water manager.
Another holdover from the WSI methodology that I carried forward was the scores for several parameters and indicators. Limiting scores to five quantities (0.00,
0.25, 0.50, 0.75, or 1.00) mutes the richness of the data. In the WSI, the effect (combined with the application of average on top of average) is convergence of all results around the same number. With the WSV, the effect is discrete bands of color. A continuum of values, and colors, would more accurately reflect the underlying measure’s values.
My final mythological regret is the propagation of gratuitous averages. For simplicity, I averaged water quality data from various stations to a single value for a given constituent. However, it might be more valuable to retain the granular station- specific data to target appropriate locations. In a similar vein, I did not scrutinize the question of weighting values or subdividing the visual to correspond to different area
(e.g. upper, middle, and lower parts of the watershed). However, it may be appropriate to provide a greater degree of transparency with increased visualization, rather than simply employing the use of averages (e.g. water quality data).
66 Overlooked assumptions. Although not immediately apparent, the original and my own methodology have embedded assumptions about discretionary variables that warrant explanation where limited, or none has been provided.
Timeframes have been poorly defined throughout the methods. In retrospect, results are sensitive to how the duration of study period has been defined, and how “long- term” has been defined. For values that change over time, the duration during which data are sampled affects the result. The ambiguity of “long-term” may be counter-productive in that a long historical record may unnecessarily emphasize periods of time that are far removed from the current time. My modeling methods do not recommend when or how to appropriately weight time series data. As a corollary to this, the method is lax on the issue of consistency between time frames for different data. Although a weakness in some respects, this is a necessary evil, given the meta-analysis being done and the frequency of updates from available sources (e.g. population data from the census).
It’s also worth noting that no firm requirements are established for sampling frequency for water quality data. This is both a weakness and a strength in the methodology in that it (a) compromises the models ability to generate results that can be reproduced (given user discretion) while (b) affording a degree of flexibility to the analyst to make appropriate decisions based on the availability of information.
The concept of location is not given the rigor it deserves, given its centrality as the model’s unit of analysis. Where is the watershed? The approximate area may be generally agreed upon, but basin boundaries are not necessarily static and it is difficult to ascertain the border of alluvial fans.
67 Watershed boundaries seem somewhat inconsistent. In the case of the SFC watershed, I found a lack of consensus on the watershed boundary from different sources, such as the USGS and the SFCJPA. It is clear that the alluvial fan has changed with the course of development over time, but each source that I consulted seemed to show different watershed limits in the lower part of the basin for the present time. I was forced to make a reasonable attempt at a consensus boundary.
Because the watershed defines the analytical unit for this model, location matters.
That said, my methodology remains unclear on how boundaries that change over time should be addressed, and how to determine authority or primacy on this type of information. The boundary definition impacts the results. In disputed areas, for example, lower basin where population density is highest, these type of discrepancies can shift population estimates wildly. Although not ideal, at a minimum, it is important to maintain a consistent boundary throughout any modeling iteration.
Furthermore, there is a lack of guidance with respect to water quality data collection – in most watersheds, results will vary based upon numerous factors, not the least of which is sampling location. Assuming that viable data from multiple locations are available, my methodology lacks recommendations for weighting different stations (it simply assumes averaging the data).
Although I hoped to be able to validate data used in this study, I should have made recommendations for keystone variables that warrant a higher degree of scrutiny and corroboration.
In a similar vein, I recognize that the efficiency factor sub-indicators are driven by estimated values: i.e., watershed population is used to prorate the water losses and energy
68 usage associated with the inter-basin water transfer. And, the equivalent values for energy use, and water supply with the basin are hastily covered. However, to a data analyst, the determination of the basin-specific values is a both an art and a science. Data for water production and usage would come from local water agencies or companies whose service areas do not necessarily overlap with the watershed area. Not all watersheds coincide nicely with the areas associated with data used in the calculations suggested by the model. My methods are silent on this matter, leaving the analysts the freedom to employ their best judgment.
Unintuitive consequences. The WSV highlights the incongruence between cause and effect. The WSI and WSV imply that higher index values and more green, respectively, can be equated with improved sustainability. However, like other indices, these tools should be regarded as directional indicators. They indicate areas of deficiency that warrant attention, or highlight successes that should be perpetuated. A theoretical index value of 1.00 or a verdant green treemap does not guarantee anything. This may be an unintuitive outcome given the motivation for quantifying sustainability in the first place.
I look at these type of metrics as useful tools that can help water managers reflect upon their efforts relative to the direction that sets them up for success in the future.
Conclusions
The development of the WSI and WSV represent milestones in watershed sustainability analysis. Here I discuss the contributions of my work, research limitations, and my recommendations for future research.
69 Contributions
Data without action are plentiful. Data that predicate action are the foundation of sustainability and environmental management. It is my hope that the WSV and future improvements to it will inspire active citizenship and community engagement that will drive watershed management activities that promote sustainability.
The results of this research shed light upon, and fill, a gap in the toolkit we use to assess watershed sustainability. In addition, this research helps us better understand the health of the SFC watershed in terms of sustainability. Ultimately, the results better inform watershed management activities intended to analyze, improve, and promote sustainability.
Research Limitations
Given the limited resources available for this research project, the scope was narrowly defined to focus on a few specific topics related to the WSI. As a result of which, analysis was limited to existing data that was readily available on the web and I had to make and explain lots of assumptions. I tried my best to validate information that
I found with the tools at my disposal (for example, estimation of the number of inhabitants within the SFC watershed boundary using GIS and 2010 census data).
Unfortunately, these limitations also prevented me from being able to examine the newest indicators proposed in a truly meaningful way. Given the decision to abide by the guidelines I established for criteria to be used in the watershed sustainability analysis or to incorporate important indicators that may not yet have readily available data, I opted for the challenge that I believe will unlock valuable insight into frequently ignored social
70 justice issues associated with water and sustainability. I have no doubt that a better- equipped team with more resources would be able to make progress where I was unable.
Recommendations for Future Research
My recommendations for future research fall into two broad camps: model improvements and groundwater basin sustainability.
Model improvements. In addition to the recommendations incorporated into the WSV, there are ample opportunities to further refine the WSV.
One key opportunity for future research would be in the inclusion and integration of the role of reservoirs that impound stream capacity. A deeper look into how dams affect watershed sustainability would be useful – specifically, how could the metric account for the presence of a dam or reservoir. There is a time component associated with impounding water, but there are also supply issues related to the diversion of water from downstream beneficiaries, including the environment.
Similarly, the WSV does not adequately discriminate between various forms of water use. It would be helpful to differentiate between sustainable consumption and actual consumption of water; however, further research would be needed to determine what “sustainable consumption” is. My initial assumption would be that this could be incorporated into the environmental indicator. As a corollary, the efficiency indicator could also incorporate a measure for urban use in excess of what is defensible (i.e. for a residential customer: a standard indoor daily allowance per person plus an outdoor allowance based on the permeable area of the household lot relative to recorded weather conditions). The level of granularity of this data is quite high and has been subject to
71 criticism – understanding whether the level of effort required is worth it would be helpful, too. At the very least it would be helpful to look more closely at discretionary water use, possibly targeting the largest water wasters.
The area that I would most like to see developed in the WSV would be the inclusion of an indicator (or sub-indicator) to capture affordability. Affordability appears in various manifestations. Consider the following situations: (a) economic component of inter-basin transfer – is it affordable for the lowest income residents to finance massive infrastructure to convey water, not to mention the ongoing costs associated with water;
(b) water rate subsidization – users who conserve water may effectively be subsidizing those that waste water because the capital cost of infrastructure to deliver larger volumes of water is significantly greater than the marginal cost of an additional unit of water (it would be important to take fire flows into account when analyzing); (c) water rate equity
– who pays the most for water if you look at water bill as a fraction of household income or water bill unitary rates per person (a large household size hit with conservation rates may end up paying substantially more for its water); (d) death spiral – this was the term used to describe the Flint system, when population declines, the remaining water system customers may be unable to afford the maintenance of their system (this is reality in several desert communities in California that once thrived).
Groundwater basin sustainability. By design, the WSV does not take into account groundwater. It would be helpful to incorporate an adjustment so that watersheds that rely on groundwater can be analyzed using this tool. It is unclear to me how to adjust the metrics, perhaps they need to be bifurcated. Nevertheless, it is a worthy topic to
72 investigate with future research. Furthermore, it should be noted that simple inclusion of a parameter to account for groundwater in the hydrological indicator would not address groundwater basin sustainability. It may be that a separate metric would need to be developed to analyze groundwater basin sustainability in a manner analogous to how the
WSV analyzes the superficial watersheds.
On a related note, the interplay between surface and groundwater watersheds would be a valuable information to understand. Although this model assumes a surface watershed boundary for analysis, it is unlikely that this is a valid assumption for other watershed. What is the right unit for analysis? How does the interplay between surface runoff and groundwater recharge impact sustainability? In the SFC watershed, it is estimated that ~9% of surface water recharges the groundwater supply. How does one analyze this interaction appropriately?
Furthermore, it is my understanding that over drafting in the Central Valley is leading to irreversible land subsidence permanently reducing the storage capacity of the aquifer. Although Groundwater Sustainability Agencies (GSAs) have proliferated in
California as a result of the Sustainable Groundwater Management Act (SGMA), it is unclear whether the simplistic visual of a two dimensional map of groundwater basin boundaries belies the complexity of groundwater hydrology. Assumptions about these basins will determine how much and to whom extraction rights are allocated.
73 Appendix 1
Description of WSI Parameters, Levels, and Scores
(Chaves & Alipaz, 2007)
74 (Chaves & Alipaz, 2007)
75 (Chaves & Alipaz, 2007)
76 Appendix 2
Social Justice and Equity Indicators
Indicator Measure Kindergarten Readiness Percent of students who demonstrate the skills of a kindergartener in the domains of social emotional, physical, language, cognitive, literacy, and math at the beginning of kindergarten. Third Grade Reading Proficiency Percent of students proficient in third-grade reading on the Measurement of Student Progress (MSP) test by race, LEP, and income On-time High School Graduation Rate Adjusted four-year cohort graduation rates (percent of students who graducate in four years) by race, LEP and income Incarceration Rate Adult incarceration rate per 100,000. Data captures adults booked into local county jail systems, includes Department of Correction violators, but not including persons booked in municipal jail. Unemployment Rate Percent of the civilian population age 16 and over without a job, were available to start a job and actively looking for work during the last four weeks. Median Household Income Household income includes income of the head of household as well as all other household members over 15 years old. The median household income divides the income distribution into two equal groups with half of all households above this number and half below. Food Security The financial relationship between income and food. The USDA defines low to very low food security from the reduction in the quality and variety of diet all the way to multiple indications of disrupted eating patterns and reduced food intake within the last 12 months. Retail Food Environment Index Ratio of fast food restaurants and convenience stores divided by the number of supermarkets, small grocers and produce vendors Home Ownership Rates The percent of people that own a home. Foreclosure Risk Score Composite score comprised of risk factors that include: subprime lending, mortgage delinquencies, foreclosures and vacancies. Cost-Burdened Owners Renters and mortgage-holders that pay more than 30 percent of income for housing Perceived Neighborhood Safety Measure reflects how often within the last 12-months people experienced feeling worried about the threats to safety, including: ◦ Children’s safety in their neighborhood ◦ Children’s safety in school ◦ Their own physical safety in their neighborhood ◦ Their physical safety at home ◦ Being robbed or having their house broken into ◦ Being physically attacked by someone they don’t know Social Cohesion A measure of mutual trust among neighbors and informal social control for example, the likelihood that a neighbor would intervene if children were skipping school or spray-painting graffiti. Park Access Travel distance to a park (score may take mileage or time into account). Open Green Space Less developed parks, greenbelts, open space, undeveloped areas, natural areas, ecological land, and developed parks Tree and Forest Canopy Normalized difference vegetation index (NDVI) Pollution by Region Air release of all reportable toxic chemicals & carcinogenic chemicals by region
Proximity to Metro Transit Percent of housing units per census tract that are located within a quarter mile of a transit stop or a two mile drive to a park-and-ride Transit Cost Burden (auto ownership costs + auto use costs + public transit costs)/ representative income Uninsured Adults Number of adults 18 and over with no health insurance Life Expectancy Number of years a person can expect to live if the current death rates stay the same for his/her life
(Beatty & Foster, 2015)
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84 Ancillary Appendix 1
Q-values for WQI Calculations
Hallock notes that the Water Quality Index (WQI) can be used to combine multiple constituents, aggregate over time, and provide a single score to indicate health relative to expectations (2002). The WQI integrates data about temperature, pH, fecal coliform bacteria, dissolved oxygen, nutrients, and sediments. Values shown in tables below (Riverwatchers, n.d.) are derived from the charts (Pathfinder Science Network,
2006) that follow.
85 86 87 88 89 Ancillary Appendix 2
WSV for Selected Basins (using WSI Results)
Watershed Sustainability Visualization for basins to which the WSI had previously been applied. WSI data has been converted to the WSV treemap format.
Japaratuba River Watershed: WSI = 0.67
(Maynard, Nascimento, Cruz, & Gomes, 2017)
90 Elqui River Watershed: WSI = 0.61
(Cortés et al, 2012)
Panama Canal Watershed: WSI = 0.76
(Chaves, 2011)
91 Tacuarembo River Basin: WSI = 0.64
(Chaves, 2012)
Revntazon River Basin: WSI = 0.74
(Catano, 2011)
92 Iguacu River Basin in Curitaba: WSI = 0.69
(Oliveira de Castro, Santos Loureiro, Vieira Santos, Silva, & Bonino Rauen, 2017)
Campo de Cartagena Basin: WSI = 0.55
(Senent-Aparicio, Pérez-Sánchez, García-Aróstegui, Bielsa-Artero, & Domingo- Pinillos, 2015)
93 Batang Merao Basin: WSI = 0.59
(Firdaus, Nakagoshi, & Idris, 2014)
94