ࡱ> @ |ijbjb LddR_vl  ***$ PN 4 Ko (" (J J J ?4so o o o o o o,)q Isd6o*{"6oJ J 1 ~8J *J oNX X*XXo&fg*dmv Ij ~0jDdmKoKotjssdm Watershed Health Scorecard Technical Report Version date: 9/30/08 gray is writing instructions. green needs to be altered for Napa/Sonoma. yellow or blue is editorial comments by authors. Table of Contents Introduction 1 Methodology 5 Index: Water Supply 8 Index: Water Supply. Indicator: Annual Flow 8 Index: Water Supply, Indicator: Dry Season Flow 11 Index: Water Storage 16 Index: Water Storage, Indicator: Surface Storage 17 Index: Water Storage, Indicator: Groundwater 20 Index: Water Stewardship 24 Index: Stewardship, Indicator: Water Self-Reliance 24 Index: Stewardship, Indicator: Water Use [not written] Index: Stewardship, Indicator: Water Retention [not written] 29 Impervious Area 29 Flashiness [not written] Summary and recommendations for future watershed scorecard efforts 33 Funders and acknowledgements 33 References [subsection in each indicator and index instead?] 34 Introduction [8 or less pages] Purpose of the Watershed Health Scorecard context, need, purpose. Key questions the indicators and indices address. This section still a bit roughintegrate headings into text. What is a Watershed Health Scorecard? The Watershed Health Scorecard describes watershed condition and trends over time. The scorecard, modeled after The Bay Institutes San Francisco Bay Indes (http://www.bay.org/ecological_scorecard.htm.), is a short, easy-to-understand, science-based report card summarizing selected local watershed conditions. The scorecard uses credible data under the guidance of respected scientists to condense technical information into meaningful indexes of condition, and present the results in an information-rich, graphically appealing product under 2 pages long. The strength of this approach lies in the marriage of credibility and accessibility. The conceptual framework and multimetric indicators provide a means to aggregate environmental data into consistent themes and to score ecosystem health, which is increasingly a goal for ecological management worldwide. The scorecards purpose is to provide the information feedback required for adaptive, responsive, transparent watershed management.As water management and watershed management strategies multiply, the scorecard will consistently report on a set of repeatable indicators about basic watershed functions. The Watershed Health Scorecard will be updated as new data become available, funding permitting. Before each update, experts will consider whether any of the existing metrics or indicators, or the scorecards structure, should be modified. Why now? Our community needs tools that focus attention on watershed management, describe current conditions and trends, and provide a common vocabulary for discussing natural resource stewardship in their watersheds. The ever growing stressors on natural resources statewideincluding the impacts on water availability from climate change and development pressuresunderscore the need for communities to become more aware and better informed about the sources of their water, its depletion, and measures to use it more efficiently. These are important and complex issues. The Scorecard offers a tool and an opportunity to engage and inform the public, resource managers, decision makers, and scientists. A key trait of the Watershed Health Scorecard is that each index is constructed to be as meaningful for human needs as for ecosystem needs. This was done 1) to emphasize the fact that ecosystem health underlies and helps create economic and social health, and 2) to broaden the audience for the scorecard. The Watershed Health Scorecard assumes that sustainable, healthy communities and economies depend on healthy, sustainable ecosystems. It implicitly uses the triple bottom line of ecology (environmental health), economy (economic health), and equity (social health). This edition is a pilot. This first 2009 issue of the Watershed Health Scorecard was completed simultaneously for the watersheds of Sonoma Creek and Napa River. It is meant to develop assessment and evaluation methods that are transferable and applicable to other watersheds. This edition of the Watershed Health Scorecard is envisioned as the beginning step for the development of scorecards that report on a spectrum of watershed conditions, from biodiversity to land usean effort that will evolve over time as financial resources become available. The long-term goal of the Watershed Health Scorecard is to build support for watershed protection and restoration through increased awareness of the natural resources that define and sustain our communities. This edition is about water. This first 2009 issue of the Watershed Health Scorecard is focused on answering the question: how is this watershed doing in terms of the availability and sustainability of water to meet local ecosystem and human needs indefinitely? water availability and sustainability for human and ecosystem needs Public concern over the future availability of water for human and ecosystem uses is high in the pilot watersheds. A recent poll in Sonoma County showed that water was by far the environmental issue of greatest concern. Yet most stakeholders, lacking access to useful information about water resource conditions, consider that the situation is incomprehensibly complex and that achieving water sustainability is beyond the control of the community. This project translates the complexity of water dynamics to the public and its decision-makers in simple language, using local data, and comparing conditions to standards developed by scientists and the communities. Relationship to other watershed and natural resource management efforts: This approach supports emerging locally driven and sustained efforts to implement watershed health monitoring programs that are based on the Surface Water Ambient Monitoring Programs monitoring strategy, recently approved by US EPA, Region 9. This project also contributes communication and outreach elements to the Integrated Regional Water Management Plan under development by a consortium of Bay Area drinking water purveyors, wastewater treatment, stormwater management, and natural resource trustee agencies. The project will support upcoming groundwater management planning in the Sonoma Valley basin, and the Critical Coastal Areas plan for the Sonoma Creek watershed. The Sonoma Ecology Center has been collecting traditional watershed data (stream habitat condition, sediment and turbidity levels, water temperature, water quality) for over a decade in Sonoma Valley. Watershed Enhancement Plan. This project builds on many years of successful reporting on the San Francisco Bay by TBI, SFEI, the Association of Bay Area Governments, among others, and takes it up into the watersheds. This has been a rallying cry for some years now. Intended audiences There has never been an easy-to-read report on conditions related to water availability in individual watersheds, as far as the Scorecard project partners can determine. Most reports on environmental conditions are long and technical, or generic and poorly researched. The Watershed Health Scorecard is designed to reach varying audiences, from middle school students to scientists, local landowners, business and farming people, elected and non-elected decision-makers, governmental and non-governmental watershed managers, and general users such as local newspapers. The Scorecard project produced three products, each for a different audience. The scorecard itself (half-page size, 4 pages, graphic, easy to understand) The scorecard report (a summary of the research behind the Scorecard, approximately 20 pages, written for the interested lay reader) The technical report (several pages per indicator, describing data availability, analysis and methodology for scoring, results and their interpretation, as well as acknowledgements, relationship to other related efforts elsewhere. Written for the technical reader.) For natural resource decision makers, the technical report will provide information for planning purposes as well as recommendations for monitoring, regulatory, restoration, and management actions. The scorecard will facilitate state and federal efforts to track the vital signs of the Sonoma Creek watershed. Lastly, the Scorecard contributes to the statewide watershed indicator framework discussions by developing and testing locally appropriate indicators to create multimetric indices that report on ecosystem condition in an easily comprehensible way. The need for accessible information about local water conditions, and measures for evaluating restoration activities, is acute throughout California. The benefits of the Scorecard will be shared through the continuing committed involvement by SEC and the Napa RCD in regional and statewide watershed forums. Beneficiaries include nonprofits and RCDs like the project partners, and also local water utilities and agencies, through participation in forums like the North Bay Watershed Association and the Bay Area Water Forum. Scope and limits of the Scorecard The main limit on the usefulness of the Watershed Health Scorecard is that so much information necessary for wise watershed management is lacking. The Scorecard can only report on data that is available. Comparison with other ecological health indicator efforts San Francisco Bay Index (www.bay.org/ecological_scorecard.htm), Santa Clara Basin Watershed Management Initiative Indicators Workgroup (www.valleywater.org/_wmi/index.shtm), Sacramento River Watershed Program (www.sacriver.org), Great Valley Center (www.greatvalley.org/indicators/index.aspx), Silicon Valley Environmental Index (www.svep.org)). The project builds on The Bay Institutes (TBIs) assessment of conditions in San Francisco Bay, with the publication in 2003 and 2005 of the San Francisco Bay Index. In addition, the San Francisco Estuary Institute (SFEI), TBI, and the Center for Ecosystem Management and Restoration are working to develop San Francisco Bay indicators for the San Francisco Estuary Project, as well as a water-quality indicator system for the San Joaquin River watershed, utilizing many of the indicators and methodologies developed for TBIs Scorecard Project. Further, SFEI, in partnership with the Napa County Resource Conservation District (RCD), is engaged in a range of ecosystem assessment and planning efforts in Napa County that will provide access to important datasets and analyses. Online resources Where to find the data and products online. Methodology [(4 6 pages, including model diagram)] Conceptual framework how the team approached the development of the Scorecard: using the conceptual model of water stocks and flows to ensure nothing was overlooked  choosing indices: Approach considered: surface water and groundwater. Approach considered: supply sufficiency and sponginess Approach taken: supply sufficiency and storage. Our work proceeded on two tracks. One concerned the choice of data that underlie the scorecard, and the other focused on how to design the scorecard and its supporting documentation. First, overall scope discussions at SEC agreed on the handful of main topics that a watershed health scorecard will cover, going beyond the water quantity topic funded by this grant to include topics such as water quality, biodiversity, land use, and climate. Second, discussions between SEC and TBI helped SEC absorb some of the lessons learned from TBIs Bay scorecard experience. Then, the full project team met several times to wrestle with the problem of matching up the kind of information we want to convey with the comparatively limited data that is available. These discussions nailed down some of the following standards: Criteria for indices. The indices should number between 4 and 7, and should: Be relevant to both everyday human concerns and the underlying integrity of the watershed Be important components that will determine future functionality of the watershed Considerations for scorecard design. The final array of products should: Have a product for all types of readers: the scientifically inclined, the lay reader, the elected official with little time, the reader more inclined to graphics than text, the online reader, the student, etc Be a pleasure to look at and easy to read. Appeal equally to those who consider themselves environmentalists, business people, left, right, etc. Make use of the web to lower production costs and make the products widely available. Be designed with an eye toward adding more indices in the future. Be designed to highlight the need for additional data, by including crucially important indicators for which data are currently insufficient. Take the bold step of actually grading or scoring the indicators, by comparing todays conditions against a defensible target that represents a healthy watershed. Teach the reader about the many interacting elements of the watersheds water system. The original intention was to include a graphically appealing diagram of water flows in a watershed. Screening potential indicators Describe in general how indicators were filtered. What criteria were used? Criteria for indicators. An indicator should: Be collected consistently over time in the past Be expected to be collected consistently in the future with reliable funding Be publicly available (not proprietary) Be reliable and accurate Report on something genuinely meaningful and relevant to sustainability and watershed health Screening potential data doing data searches to determine if (1) data were available that could serve as appropriate metrics; (2) data were in a form readily useable without much additional work (e.g., the raw NRCS database on soils would have to be re-worked and was therefore unsuitable). Paths not taken Which of the boxes and arrows in the conceptual model couldnt be parameterized due to lack of information? What can we say about candidate indicators that we thought would make terrific additions to the Scorecard, but for which the data gaps are too significant for now? What might the consequences be of NOT having the ideal indicator(s)? (all we can do is monitor the decline of the system rather than using appropriate indicators to select appropriate management interventions and find out if they result in the desired outcomes.) Why were some indicators unscored? A variety of reasons: no good data, no time to analyze data or determine how to analyze it, data too costly to be collected in future, or not clear how to assign score to data. Team agreed that these indicators are important enough to be mentioned throughout scorecard reports to draw attention to gaps in knowledge. Index: Water Supply Score: ______ Trend: __________ Paragraph: background and description of this resource/element, history of change for this index topic, maps and figures, definitions of key words, limits of what the index reveals and does not reveal, other efforts to measure status and trends of this index topic Index: Water Supply. Indicator: Annual Flow Introduction The purpose of the cumulative flow indicator is to provide context for the time period being scored in terms of whether it is relatively wet or dry. Strictly speaking, this is not an indicator of environmental health. Rather, it should be understood as a key piece of basic information, to be borne in mind in evaluating the other sections of the scorecard. The message to be conveyed is essentially this: how wet is the overall hydrologic picture for the period covered by the scorecard? The importance of this notion cannot be overestimated. In order to evaluate the condition of water quantity in the watershed in light of the sustainability of human activities, we must consider the inputs to the system. If there is less rain, there will naturally be less water in the channels or in storage. The indicator chosen for this task is cumulative flow in the Napa River. By this we mean the total discharge for the entire hydrologic year. We take the hydrologic year to run from October through September, following the convention of the United States Geological Survey (USGS), the agency which has historically collected flow data on the Napa River. The use of total rainfall was considered as an alternate indicator, but rainfall has the disadvantage of being spatially varied, so that to estimate total basin rainfall requires an extended network of rain gages and some means of assigning weights to them to represent the whole. Although there are currently a number of rain gages in the Napa River watershed, few of them have long records. Rainfall would be the ideal way of representing the total hydrologic input into the system (snow not being a factor at this elevation), but in this case it is not the most practical. Cumulative flow is relatively easy to study, over the relatively long period of record on the Napa River. One might ask, of course, whether cumulative flow actually represents input to the watershed. Of course, the answer must be no; rainfall goes to other places besides runoff, and the timing and quantity of runoff are affected by human activities. However, the total of annual discharge does track in a general way how wet the overall hydrologic condition is, and in addition river discharge vividly represents the lions share of the water available for human use. For these reasons, cumulative flow is used in this report as a measure of overall hydrologic condition. For the purpose of determining a wet vs. dry year (or time period) we developed a probability index and ranked cumulative flow for a baseline period of 45 years accordingly. We then distributed the results into quintiles representing very wet, wet, average, dry, very dry water years. Data availability There are two USGS gaging stations on the Napa River, station 11456000 (Napa River near St Helena) and station 11458000 (Napa River near Napa). For each site, multiple decades of daily average flow data are available from the USGS. Both gage sites were considered, and the more downstream site near the City of Napa was chosen as most representative of the watershed as a whole. This dataset is continuous since 1959. Water level is measured continuously and recorded at 15-minute intervals, and a rating curve is maintained to convert the stage record into a discharge record. The data are available for download at the USGS website (http://waterdata.usgs.gov/nwis). The data for this site are generally regarded as of good quality and are the general standard for water resource investigations in the watershed. The likelihood of data collection continuing at this site is good; this is generally considered the primary gage on the Napa River. Analysis, methodology, calculations The approach used was based on the daily average flow record for USGS station 11458000 (Napa River near Napa) for the entire period of record 1959-2007. The daily increments of flow were summed by year, and the annual totals converted to acre-feet for convenience. The annual data are shown in Figure X. This analysis is based on the best available data. In an ideal world, we would have a gage closer to the mouth of the Napa River that would allow us to track the total annual cumulative flow for the entire watershed. Likewise a longer period of record may show us more in the way of long term trends. Figure X showing annual cumulative flow at Oak Knoll Evaluation and scoring To score the indicator, we took advantage of the length of the dataset to create a probability distribution for the period 1960-1999 and compare the current cumulative flow with it. Inspection of the record did not suggest the use of any particular subset of the data to define a baseline condition. In the case of a very long record, with the possibility of significant change in the response of the watershed to rainfall, it would be worthwhile to identify an earlier period as the baseline. In this case, however, essentially the entire dataset was used. The annual values of dry season flow for the entire 40-year period were arranged in ascending order, and exceedance probabilities were assigned to each value. Figure Y shows the resulting probability distribution. Figure Y showing probability distribution of dry season flow ratio In order to score the metric, raw values were converted to probabilities, and scoring breakpoints were defined by dividing the probability range (from 0 to 1) into equal-sized sections. As the figure shows, the entire probability distribution is divided into quintiles. A probability in the lowest quintile, for example, which lies in the interval (0,0.2), is assigned the lowest score (Very Low, for a value of 1). A value in the next quintile is scored as Low (value 2), and so on. To score a particular value, one finds the value on the X-axis and uses the curve to find the corresponding probability on the Y-axis. Please note that, in spite of our use of the word score to describe this evaluation procedure, we are evaluating not environmental health but rather simply noting the magnitude of the cumulative flow. This should be understood as a value-free quantifier of the overall flow picture on a year-by-year basis. In order to give a slightly broader picture of current condition than that afforded by the most recent year only, the current condition was scored on the basis of the average of the years 2004-07. That is, the probability values for each of the four most recent years were averaged and converted into a score for the watershed. The resulting score is 3+ (in the upper part of the normal range). No upward or downward trend is discernible in the data (Figure X). Discussion This indicator tells us how wet the general hydrologic condition is in the period under evaluation. As was discussed in section 3.1.1, this is not an indicator of environmental health, but it is nevertheless fundamental to understanding the hydrologic condition. The message is that, on the basis of cumulative river flow, the hydrologic condition is somewhat wetter than average near the top of the range labeled normal in Figure Y. Water is available, for use by the watershed community. The indicator does not tell us about the prospects for the immediate future. There is some carryover from one hydrologic year to the next hydrologic year 2008 has been dry, for example, and so the ground may be drier as we begin hydrologic year 2009 than in some recent years, and this will affect runoff. However, the prime driver of hydrology is rainfall, and the indicator has no predictive value. The range of the overall dataset is considerable, from a minimum of 525 ac-ft in 1977 to 423,842 ac-ft in 1983. It is interesting to note that these two values differ by a factor of about 800, while the difference in rainfall between 1977 and 1983 was much less: the rainfall in 1983 was about 5 times the rainfall in 1977, according to the St Helena Star rainfall record (described below in section 3.2.3). In very low rainfall years, most water infiltrates and there is little surface runoff to the river, while in high rainfall years there can be a great deal of runoff. This example of typical hydrologic variation shows how a difference in rainfall is tremendously magnified in cumulative flow, and it argues for the usefulness of this indicator to assessing watershed condition. Data Gaps and Recommendations It would be a useful adjunct to this indicator to have better estimates of total rainfall than we currently have. There are nine rainfall gages operated by the local ALERT system for which data are available going back to 2003. As time passes, these historical data will become increasingly valuable, and it may become possible to make use of them to round out the basic hydrologic picture, alongside the data on cumulative flow in the river. We may also wish to calculate a runoff coefficient in the future, and the more long-term annual rainfall records we have, the better. Index: Water Supply, Indicator: Dry Season Flow Introduction This indicator aims to measure the degree to which flow in the Napa River persists into the summer months. The underlying assumption is that in a more natural, undisturbed watershed flow will persist longer: the response to rainfall input is slower and peaks are lower, whether one is considering individual storms or the rainy season as a whole. In the Napa climate, rainfall is concentrated in the winter and early spring, and the degree to which flow in the river persists into the summer months reflects the continuing capacity of the watershed to soak up rainfall and slowly release it to the river as subsurface flow. We considered several ways of capturing this phenomenon. One idea was to use measurements of the length of dry reaches of tributaries as the indicator. This idea seemed promising for Sonoma Creek, but it was rejected for Napa because no one has made systematic observations of this sort for Napa River tributaries. Another idea was to measure the number of days of zero flow per year, either at a gaging station on the main stem of the river or at a tributary site where such observations are available. In the Napa River watershed, daily flow records going back at least 40 years are available at both the St Helena and Napa gage sites on the Napa River, but no records of comparable length are available at tributary sites. Data for the Napa River gage sites were analyzed and the number of days of zero flow per year compared with rainfall records; but finding that the number of zero flow days did not correlate well with rainfall, we became skeptical about the value of this method. In fact, there is some uncertainty about the point of zero flow, despite the regular efforts of the United States Geological Survey (USGS) field personnel to identify it. On gravel-bedded streams like the Napa River at both gage sites, the level at which actual surface flow ceases is a shifting target. Accordingly, we shifted attention to the total amount of flow recorded during the summer months. This appears to be a more robust approach, and it is the one we have used. Data availability Napa River flow records at both gage sites were considered, and the more downstream site near the City of Napa was chosen as most representative of the watershed as a whole. This dataset is collected by USGS and is continuous since 1959. This dataset was described in section 3.1.2 above. Analysis, methodology, calculations The approach used was based on the daily average flow record for USGS station 11458000 (Napa River near Napa) for the entire period of record 1959-2007. The flow for the months of June through September was summed for each year. Since the amount of this dry season flow is related to rainfall, we accounted for the influence of rainfall by dividing the volume of dry season flow by estimated total rainfall volume. Total rainfall volume was estimated on the basis of annual rainfall totals for St Helena as published in the St Helena Star newspaper. This dataset is available for the period from 1908 to the present. In order to evaluate the appropriateness of this data record for the entire area above the USGS station, we compared annual totals from this record with data since 2002 for the rainfall stations in the locally-maintained ALERT network ( HYPERLINK "http://napa.onerain.com/home.php" http://napa.onerain.com/home.php). The St Helena Star record was scaled down slightly, on the basis of this comparison, to estimate total annual rainfall over the entire drainage area. Finally, we calculated the ratio of dry season flow to total annual rainfall, both expressed as volumes, to use as our indicator. The resulting dataset is illustrated in Figure X. Figure X showing Dry season flow as pct of annual rainfall, by year In an ideal world, it would be preferable to have physically distributed datasets for both dry season flow and rainfall. This would make it possible to observe and evaluate local variations in the overall picture, which would be most useful for land managers. Since such data are not available, the basin-wide methods described above were used. In a future version of the watershed scorecard, we may apply the methods used here to both Napa River gage sites, St Helena as well as Napa. Evaluation and scoring To score the indicator, we took advantage of the length of the dataset to create a probability distribution for the period 1960-1999 and compare the current average dry season flow ratio with it. Since the work on cumulative flow (see Section 3.1 above) did not suggest that a smaller portion of the record would be a more appropriate baseline period, we have used the long period indicated. The annual values of dry season flow for the entire 40-year period were arranged in ascending order, and exceedance probabilities were assigned to each value. Figure Y shows the resulting probability distribution. Figure Y showing probability distribution of dry season flow ratio In order to score the metric, we followed the same procedure as in section 3.1.4 above. Raw values were converted to probabilities, and scoring breakpoints were defined by dividing the probability range (from 0 to 1) into equal-sized sections. As the figure shows, the entire probability distribution is divided into quintiles. A probability in the lowest quintile, for example, which lies in the interval (0,0.2), is assigned the lowest score (Very Low, for a value of 1). A value in the next quintile is scored as Low (value 2), and so on. To score a particular value, one finds the value on the X-axis and uses the curve to find the corresponding probability on the Y-axis. As in the section on cumulative flow, the method employed answers the question how high or low the metric is, compared with the period of record. In this case, in contrast to the earlier section, we make the assumption that higher and lower levels correspond to better and worse environmental health, respectively, for the reason given in section 3.2.1 above. In order to reduce the effect of year-to-year variations, the current condition was scored on the basis of the average of the years 2004-07. That is, the probability values for each of the four most recent years were averaged and converted into a score for the watershed. The resulting score is 3 (Fair). The overall trend in the data is upward; as Figure X shows, there is a distinct tendency for the dry season flow ratio to increase over the period of record. The rise is clearest in the 1980s and 1990s, but the trendline in the figure plainly increases by approximately a factor of two over the period of data. Discussion This indicator suggests that dry season flow has if anything increased slightly during the period of record, a surprising result. Given that there has been some development in the watershed, we expected any trend in the data to be downward. Other than this unexpected trend, the indicator turns out to exhibit considerable variation from year to year, even when the variability in rainfall is taken into account. The current condition scores slightly above average for the entire period, indicating no apparent cause for concern. We explored possible reasons for the upward trend observed in the data. The period of record has seen an increase in vineyard development in the Napa River watershed, replacing other land uses ranging from orchards to cattle grazing. It is possible that the increase in irrigation associated with vineyard development has led to increased agricultural return flows during the summer. One would not expect this to be a large factor, because of the nature of typical vineyard irrigation practices: the virtually universal practice is to use drip irrigation, and applied water volumes are quite low, rarely more than 0.5 ac-ft/ac. However, any water applied to irrigate plants which is not consumed by evapotranspiration will remain in the upper soil layer and slowly make its way to the river, and this is water which would not otherwise have been available in the summer (it is either impounded during the winter, for summertime use, or pumped from groundwater at the time of use). Another possible reason for the observed increase in dry season flow is the increased use of cover crops in vineyards. With strong encouragement from state and county regulatory policies, the use of cover crops in vineyards in this watershed has increased greatly since about 1990. This has had the effect of putting more water into the soil during the summer, but there is little reason to expect farmers to be wasting irrigation water by overwatering what is not even a cash crop. In addition, the timing of this historical development does not match the dry season flow data, which show an increase well before 1990. It should be borne in mind that we are comparing small flows in the application of this indicator. In all years except one (1998), the total summertime discharge is less than 1% of the total estimated rainfall volume, so it is a relatively small portion of the total annual discharge. Although USGS, the agency that collects the data, is committed to making the most accurate measurements possible at all flow levels, it may be that the upper part of the flow rating curve gets more attention, because of its importance in assessing flood risk. Therefore, the result of this indicator should be used with caution. Data Gaps and Recommendations The data necessary to calculate this indicator should be available as long as the USGS maintains the Napa River gaging station referenced above. Given the importance of this gaging station for multiple purposes, it seems likely to be maintained. Future reporting on this topic will be improved, though, if additional data sources can be made available. Observations on summertime flow in tributaries of the Napa River, which typically go dry at some point, would provide a useful independent perspective on the phenomenon in question. These might take the form of observations of the date surface flow ends at various key points in the channel network, or the length of dry reaches on selected tributaries might be measured. Such observations can be carried out satisfactorily by volunteers, under appropriate supervision. Index: Water Storage Score: ______ Trend: __________ As we mentioned under Section 2 above, an important part of the water picture is storage in the watershed. Water is stored in two principal places: on the surface and underground. This Water Storage index aims to measure the degree to which storage in these places is adequate to the demands placed on it whether it is being preserved or depleted. In the Napa River watershed, there is a significant amount of surface storage, including 5 municipal reservoirs and a considerable number of farm ponds. Most surface storage facilities in Napa have been created since 1950. By far the largest reservoir is Lake Hennessey, a well-known feature of the landscape owned and maintained by the City of Napa. Groundwater storage is not so obvious, but it may be even more important, especially because it is not readily restored when once depleted. In our climate, both surface and groundwater storage tend to be at their highest in the spring, near the end of the rainy season, and at their lowest in late fall, before the rains resume. Two key terms we use are drawdown and recharge. By drawdown we mean the reduction in storage in a surface reservoir between the spring and late fall. This quantity is a volume, usually measured in acre-feet. An acre-foot is the volume of water it would take to cover an acre of land to a uniform depth of one foot. To quantify our groundwater storage indicator, we define recharge as the increase in level between the fall of one year and the spring of the next, measured in feet. This metric does not literally indicate the change in volume of groundwater storage, which would be difficult to measure with any confidence. Notice that in contrast to drawdown, this term measures the recovery of the resource rather than its consumption. Water supply planning is important to Napa local government, and the capacity of surface and groundwater storage to meet present and future needs has been studied often, most recently in the 2050 Napa Valley Water Resources Study (West, Yost & Associates 2005). That report projects supply and demand through the year 2050 for both the incorporated and unincorporated areas of the Napa Valley, taking into account all sources. It also provides a summary of previous studies on the topic. The water storage index is a composite of two separate indicators, reflecting surface water and groundwater respectively. Each indicator compares the experience of the recent past with a longer period for which we have data. The ability of the indicators to account for hydrologic variation (how wet or dry the recent past has been) is limited: we will further discuss this and other limitations of the indicators in the following sections. TABLE 4-X, capacities of municipal reservoirs here or under section 4.1 MAP showing locations of municipal reservoirs here or under section 4.1 MAP showing locations of DWR monitoring wells and associated GW basins here or under section 4.2 Index: Water Storage, Indicator: Surface Storage Introduction The purpose of the surface storage indicator is to compare the amount of surface water used with the amount available. Broadly put, the question is this: are we living within our means? In an ideal world, we would have a very long hydrologic record, not subject to climate change, and we would have precise measurements of withdrawals for use to compare with what we expect each reservoir to yield; and we would have this information for all reservoirs, large and small. Lacking such complete information, we have simplified the picture considerably in order to quantify this indicator. We compare the drawdown, or the difference in reservoir volume between the springtime maximum and the fall minimum in a calendar year, with the average-year yield that is, the amount of water that flows into the reservoir in an average year. We do this for all the reservoirs for which we have multiple years of data, which are the three largest municipal reservoirs: Hennessey and Milliken (operated by the City of Napa) and Bell Canyon (operated by the City of St Helena). We necessarily take these three to be representative of the whole. Estimates of the average-year yield for each of the three reservoirs are taken from the 2050 Napa Valley Study. They are based on a relatively short hydrologic record and, to the best of our knowledge, make no attempt to allow for climate change. Alternate methods considered included comparing drawdown with reservoir capacity, rather than yield. We also experimented with different mathematical formulations; see section 4.1.3 below. Data availability We contacted all the Napa Valley municipalities that operate surface water reservoirs, in search of data on annual drawdown. In addition, we contacted the Napa County Farm Bureau about farm ponds. Generally speaking, no multi-year information on annual drawdown is available for any other reservoirs in the watershed. On the basis of our conversation with the Farm Bureau, we believe that there is very little carryover from one year to the next in the case of farm ponds, in any case. The City of Napa Water Division retains information on annual maximum and minimum storage values for Hennessey and Milliken reservoirs, but this information was not available for the present study for years before 1990. For the Bell Canyon reservoir maintained by the City of St Helena, similar information was available from consulting engineers employed by the City for years going back to 1987. Given the increasing ease and sophistication of electronic data storage, we anticipate that more extensive multi-year information will be available in the future. Analysis, methodology, calculations The chosen method defines annual drawdown as the metric, to be evaluated by comparison to the expected yield for the reservoir. Annual drawdown is a rough measure of use, chosen because it made full use of available data to provide a gauge of the amount used from the reservoir each year. There are several drawbacks to this method. Drawdown includes evaporation from storage; it ignores the runoff which enters the reservoir either in late spring or early fall; and it includes only part of the amount withdrawn for use during the year. Nevertheless, we believe that it is roughly proportional to total withdrawals for use. We experimented with other mathematical formulations of the metric, in an attempt to make a larger mathematical value correspond to a more healthy condition, but these efforts were rejected because they made the metric more complicated and harder to explain. We also considered defining a set of three random variables for each reservoir one each for the annual values of spring storage, fall storage, and replenishment over the winter in a manner similar to that used for the groundwater storage indicator in section 4.2 below. However, the spring storage data showed too little variation to be meaningful; except during dry periods, the reservoirs have generally been full in the spring. The annual winter replenishment of the reservoirs was disappointing as well, because the data were distorted by the fact that these reservoirs typically fill and begin to spill sometime during the winter, except during dry periods. These considerations led us to reject this method of calculating the metric. As an alternate method of evaluation, we considered comparing drawdown with reservoir capacity, but this method was rejected because capacity is not related to the amount of water that becomes available in a typical year; it may be considerably larger or smaller than the average-year yield, depending on the particular reservoir. Use of the average-year yield turns out to have an additional advantage, in that it simplifies the problem of scoring the indicator: see section 4.1.4 below. Annual data were available for both Napa reservoirs for the years 1990-91 and 1994-2007. For Bell Canyon, data were available for the entire period from 1987 to 2007, with some uncertainty about the minimum value for 2005. The two Napa reservoirs were combined into one metric, because they contribute to the same municipal supply, while Bell Canyon was treated as a separate metric. FIGURE showing annual drawdowns, with flatline showing expected yield? Evaluation and scoring For each of the two reservoir metrics, we compared the annual drawdown with the average-year yield. The average-year yields (60% exceedance values) for the reservoirs are tabulated in the 2050 Napa Valley Study, along with several other relevant exceedance values. In order to obtain additional breakpoints for scoring, we made use of a range of exceedance values from 50% (wetter than average year) to 100% (single critically dry year). The volumes associated with each breakpoint are shown in Table 4-X, along with the associated score. In the table, a given ecological health score is applied if a drawdown value does not exceed the corresponding yield threshold. Table 4-X: Scoring Breakpoints for Surface Storage Drawdown Ecological HealthScoreExceedance Value, %DescriptionYield, ac-ftHennessey/ MillikenBell CynExcellent5100Single critically-dry year 5,400 530Good4 85Multiple dry years11,1201035Fair3 60Average year18,2001800Poor2 50Wet Year20,2002050Very Poor1Yield values from 2050 Napa Valley Study, Technical Memorandum No. 4, Table 4, p. 9, with Hennessey and Milliken combined into a single value. For both metrics and throughout the period of data, the annual drawdown varies widely but is almost always in the range Fair (score 3) to Good (score 4). In 1990, a year in which demand was reduced by drought conditions, the Napa drawdown was reduced below 5,400 ac-ft and would be scored as Excellent. No long-term trend is evident in either dataset. In order to reduce the effect of year-to-year variations, the current condition was scored on the basis of the average of the years 2004-07. That is, the drawdowns for the four most recent years were averaged and the resulting average was scored, separately for the Napa reservoirs and Bell Canyon. Then, in order to obtain a combined score for the watershed as a whole, the scores for the two reservoir metrics were combined by weighting them as follows: Napa 70%, Bell Canyon 30%. The resulting combined score is 3.49, almost midway between Fair and Good, on the basis of individual scores of 3.7 (Napa) and 3.0 (Bell Canyon). Discussion The indicator shows that the drawdown of water from reservoirs in the Napa River watershed is normally less than the yield for an average year and is frequently less than the yield for a period of multiple dry years. This fact is true generally for the period of data and specifically for the period 2004-07. This means that, in a general way, the demands being made on these reservoirs can be sustained except in periods of drought. The annual drawdown, used here as a metric, is only a rough indicator, as we wrote in section 4.1.3 above. However, there is no sign of a chronic problem. There is always the possibility of drought. This indicator tells us nothing about the likelihood of wet or dry years in the near or distant future, and any future drought will mean water shortages. In addition, there are several future trends that can be reasonably anticipated, which may affect the adequacy of surface water storage in the Napa watershed. They include increased demand as population increases, the loss of reservoir capacity over time, and climate change. Data Gaps and Recommendations There are two other municipal reservoirs in the Napa River watershed for which multi-year data are not available, Rector Reservoir (which serves the Veterans Home and the Town of Yountville) and Kimball Reservoir (which serves the City of Calistoga). It would be desirable to obtain data for these reservoirs as well. Of course, we hope that as the years pass longer and longer datasets will be available. We encourage the responsible government agencies to retain annual reservoir data for the long term. Data availability Analysis, methodology, calculations Evaluation and scoring Discussion Index: Water Storage, Indicator: Groundwater Introduction The purpose of this indicator is to track groundwater storage, which we do by comparing groundwater levels the changing level of the water table over time. We considered the possibility of measuring groundwater use more directly, instead of relying on the condition of the water table. Detailed pumping records are not generally available for private wells, but it would be possible to collect statistics on the number of wells, their depth, etc. and one might estimate from them the amounts withdrawn. However, this method of defining the indicator was not used, because of the increased effort required and the uncertainty that the results would justify it. In an ideal world, of course, tracking withdrawal trends would be desirable, because of its clear focus on human management. The intent is to get an idea of the extent to which the resource is being depleted or enhanced. In a more perfect world, we would track groundwater levels on the basis of a dense physical array of well sites, with a long term record for each, and we would be able to identify rising or falling trends with some precision. We would also have a good idea of the storage in the aquifers underlying our watershed. However, the groundwater data available are somewhat sparse, and we are forced to make do with fairly large-scale spatial averages of groundwater level. Data availability The California State Department of Water Resources (DWR) maintains a database of groundwater information (http://www.water.ca.gov/iwris/). The database was searched for well sites in the Napa River watershed with continuous records since 1980; we included all sites having at least one spring and one fall measurement each year. Groundwater levels are generally at their highest in the spring and at their lowest in the fall. Typically measurements were made in April and October, but there is some variability in timing. For this study, measurements made at other times in the spring or fall were treated as if made in April or October respectively. The measurements were made by a variety of individuals over a period of many years and may be subject to some variation in observation method, but it is likely that the data will continue to be available in future years. Of course, it is possible that some of the sites used for this study may be discontinued and others added. Analysis, methodology, calculations Depth-to-groundwater data were available for a total of 24 sites in the Napa River watershed for years 1980 through 2007. We grouped these sites by associated groundwater basin, reflecting the notion that water levels within a groundwater basin are tied to each other in a way that levels in adjacent basins are not. The Napa River watershed is generally subdivided into three groundwater basins: the Main basin, the Milliken/Sarco/Tulucay (MST) basin and the Carneros basin. Grouping our data by basin gave us 17 sites in the Main basin, 7 in the MST basin and none in Carneros. Besides considering the spring and fall annual data series, we also looked at recharge, or the increase in level from one fall to the following spring. This made it possible to focus on the annual replenishment of the resource, perhaps the most important part of the picture. For all 3 data series and for each basin, we calculated an average value for each year. We reasoned that the use of average values would make for a simpler subsequent analysis and that, in any case, the data are too sparse to represent local effects well. We tried two methods of calculating averages: weighting all sites equally and weighting each site in proportion to the total basin surface area which is closer to that site than to any other. The latter is essentially the Thiessen polygon method, as is used for weighting rain gages in a hydrologic model. We found the differences in results between the two methods to be minimal and determined to use the simple average, with all sites weighted equallyl, for our analysis. The spring and fall data for the MST basin are illustrated in Figure X. FIGURE X showing typical annual spring & fall series of groundwater level data for MST basin Evaluation and scoring The three metrics (spring level, fall level, and recharge) were scored by comparing current values with a baseline period. To identify an appropriate baseline period, we first looked at the history of vineyard development in Napa County, since the principal use of groundwater in the Napa River watershed is for vineyard irrigation. Using the annual Napa County crop reports, we plotted the annual totals of vineyard acres in the County since 1960 (http://www.co.napa.ca.us/BUSINESS/Apps/CropReports/). The period for which we have groundwater data (1980-2007) shows fairly steady growth in vineyard acreage through 1999, with a distinct spike after that, so we selected the period 1980-1999 as the baseline. For each of the three metrics and for each basin, the baseline period values were arranged in order of decreasing depth, and exceedance probabilities were assigned to each value (ref Chris Farrars writeup?). Figure Y shows the probability distributions for the Main basin. FIGURE Y showing probability distribution of groundwater level data for Main basin, including recharge (2 plots, 1 for spring & fall levels and 1 for recharge) In order to score the three metrics, raw values were converted to probabilities, and scoring breakpoints were defined by dividing the probability range (from 0 to 1) into equal-sized sections. As the figures show, the entire probability distribution is divided into quintiles. A probability in the lowest quintile, for example, which lies in the interval (0,0.2), is assigned the lowest score (Very Low, for a value of 1). A value in the next quintile is scored as Low (value 2), and so on. To score a particular value, one finds the value on the X-axis and uses the curve to find the corresponding probability on the Y-axis. We make the assumption that higher and lower levels correspond to better and worse environmental health, respectively. In order to reduce the effect of year-to-year variations, the current condition was scored on the basis of the average of the years 2004-07. That is, the probability values for each of the four most recent years were averaged, separately for each basin and for each metric (for a total of 6 current values). These current values were all converted into scores, and the result was averaged to produce an individual score for each basin and a combined score for the watershed as a whole. The two basins were weighted equally in the final combined score. The resulting combined score is 2.67 (or 3 minus, barely Fair), and the individual basin scores are 2.1 (Poor) for MST and 3.2 (fair) for the Main basin. Overall trends for spring and fall levels in the entire 1980-2007 dataset are different for the two basins. For MST, the trendlines of average level for fall and spring each show a drop of over 20 ft since 1980. In the Main basin, the fall trendline is downward, though not quite as steep as for MST, while the spring trendline is roughly level. Short-term trends (within the last four years) are slightly up in both basins. Discussion The downward trends observed for both spring and fall in the MST basin have a strong effect on the current values, despite a good rate of recharge in the last few years, and are the main explanation for the poor score given to this basin. In the Main basin, by contrast, although the groundwater level is being drawn down further than in past years, the wintertime recharge has been adequate to restore the resource to previous levels. The combination of strong recharge with more consistent springtime levels is the reason for the higher score assigned to this basin. The message of the indicator is that the annual use of the groundwater resource is increasing, as measured by the fall data series for both basins. Since the groundwater resource is necessarily limited, increasing our demands on it must at some point become unsustainable, so this message should sound a note of caution for water users. In the Main basin, spring levels appear to be rebounding to previous levels, which is some comfort: so far, the recharge capacity of the basin is adequate to the challenge. In the MST basin, on the other hand, the resource is not rebounding well in the spring, so that the current pattern does not seem sustainable. The state of the groundwater resource in the MST basin has received considerable attention from Napa County and other public agencies in recent years, and a recent detailed study by USGS has focused on that issue as well. Our indicator appears to support the concerns which have been expressed (Farrar and Metzger, 2003). It is important to note that this indicator, particularly with regard to the MST basin, is based on a relatively small number of wells (7), which cannot be regarded as truly representative. For the same reason, it would be inappropriate to draw conclusions about specific localities in the MST basin from the locations of the 7 wells. These caveats apply to the Main basin as well, which has 17 wells but is considerably larger than MST. Data Gaps and Recommendations The data for this indicator are sparse, and the strength of the indicator would be greatly improved by increasing the number of monitoring wells. However, it would take a long time to reap the benefit of such an increase, because the nature of the indicator requires a record of at least several decades. In any case, we strongly recommend that as many as possible of the existing monitoring wells be retained in the state database. Their value will only increase as the records become longer. It is particularly unfortunate that no monitoring wells in the Carneros basin were found to have records going back far enough to be useful for this investigation, since groundwater levels are a major concern of landowners there; the Carneros Creek Stewardship group has instituted a private well monitoring program out of concern that water levels may be dropping, at least in some locations. Index: Stewardship Score: ______ Trend: __________ Paragraph: background and description of this resource/element, history of change for this index topic, maps and figures, definitions of key words, limits of what the index reveals and does not reveal, other efforts to measure status and trends of this index topic Websters Ninth Collegiate Dictionary defines stewardship as the individuals responsibility to manage his life and property with proper regard to the rights of others. Transferred to a mix of private and public properties, including watershed resources owned by all (e.g., certain allocations of flow in streams, the air we breathe, aquifers, etc.), stewardship assumes a meaning of taking care of and sustainably managing resources without compromising the ability of future generations to meet their own needs. For this project, we selected three indicators to form a Stewardship Index: Water self-reliance Water use Water retention Additional indicators may be developed in the future to expand this index. Stewardship indicators are a means by which management of water resources can be evaluated and tracked over time, with the intent to develop a line of evidence capable of linking environmental conditions to management and stewardship activities. If environmental condition indicators tell us that we are moving away from certain benchmarks or desired conditions, and certain stewardship indicators are exhibiting no change over time, watershed managers may use this information to re-prioritize activities or increase the level at which appropriate management practices are being implemented. In essence, stewardship indicators serve to measure and track management responses to undesirable conditions and therefore facilitate learning. 5.1.1 Introduction Water self-reliance can be used as an expression of the extent to which any given watersheds social, cultural, and economic needs are currently met within its own available water resources, rather than those imported from other watersheds or extracted from aquifers faster than they can be replenished. This indicator allows residents and government agencies to evaluate trends in active management steps designed to increase reliance on local water sources and mimic certain watershed functions that have been lost after large-scale landscape and hydrologic modifications took place. Through conversion of vegetation cover to intensive land uses that rapidly channel runoff from hill slopes and impervious areas, such as roads, roofs, and parking lots, a significant amount of rainfall is now no longer absorbed and slowly released throughout the long dry season but is rapidly routed to San Pablo Bay, where it is no longer available for stream flow augmentation, groundwater recharge, or other beneficial uses. 5.1.2 Data availability Five major datasets were considered for this indicator: Number of zoning or other land use provisions restricting development in groundwater recharge areas (less groundwater recharge capacity results in lower self-reliance on local water sources) Number of policies and ordinances encouraging and facilitating grey water re-use (grey-water recycling diminishes the need for water imports and increases reliance on local water sources) Number of building code provisions encouraging runoff harvesting and storage features for all land use designations (runoff remaining for longer periods in a watershed increases the options for use before it leaves the watershed and drains into San Pablo Bay) Number of state and local policies in place representing barriers to greater self-reliance (e.g., California Water Code provisions preventing storage for deferred use under riparian water rights; local ordinances preventing water harvesting features from commercial properties; building codes requiring connections of roof down-spouts to storm drains, etc.) Percent of treated effluent recycled Most of the metrics associated with this indicator are regularly collected, although not readily available in useable form. Data sets associated with state and local policies, ordinances, and codes have not been systematically compiled and will require considerable effort to analyze. One of the key recommendations from this Score Card effort is that information management systems covering watershed management measures and management practices need to be developed and applied in parallel with databases for environmental conditions and stressors. Data are generally collected and maintained by city and county land use departments, the Association of Bay Area Governments, and non-governmental organizations, such as the Local Government Commission. However, no consistent and standardized classification system exists at this point that organizes policies, guidelines, ordinances, and codes in a hierarchical fashion that would indicate if land use planning goals and objectives have been translated into tangible action items at the implementation level. An example of a hierarchical arrangement of stewardship data and information comes from the Napa River watershed: The updated County General Plan (at the highest level in the hierarchy) states: The County shall maintain or enhance infiltration and recharge of groundwater aquifers by requiring all discretionary projects be designed (at minimum) to maintain a sites predevelopment groundwater recharge potential, to the maximum extent feasible, by minimizing impervious surfaces and promoting recharge (e.g., via the use of water retention/detention structures, use of permeable paving materials, bio-swales, water gardens, cisterns, and other best management practices). At the next level in the hierarchy, the Action Items in the General Plan directs resources to be made available to: Identify, map, and disseminate information on groundwater recharge areas, and provide educational materials and resource information on ways of reducing and limiting the development of non-pervious surfaces in those areas. No steps have yet been taken, however, to enable project applicants and review staff to clearly identify if a proposed project is located in a designated groundwater recharge areas and to insure that project designs meet the goals spelled out in the General Plan and its associated Action Item. In addition to the groundwater recharge protection data, those associated with grey water re-use, water harvesting, and policy barriers to increases in water self-reliance will also require the development of a transparent system of data classification to insure that watersheds are comparable, and that calculations do not rely on subjective observer judgment. Analysis, methodology, calculations The first metric the number of zoning provisions restricting development in groundwater recharge areas can be calculated based on the number of land use jurisdictions in both watersheds. The Sonoma Creek and Napa River watershed differ in the number of local jurisdictions with land and water use authority. The Napa River watershed contains five incorporated cities, with land use in the unincorporated areas administered by the County. The Sonoma Creek watershed has only two land use jurisdictions the City of Sonoma and the County of Sonoma. Therefore, the maximum number of land use jurisdictions that could theoretically adopt specific zoning restrictions intended to protect groundwater recharge areas is six in the Napa River watershed and two in the Sonoma Creek watershed. The recently updated General Plan for Napa County contains a specific goal that addresses protection of groundwater recharge areas. No equivalent provisions exist for any of the other five land use jurisdictions in the Napa River watershed. The General Plan for Sonoma County, similar to Napa County, contains a groundwater recharge protection objective, but the City of Sonomas General Plan does not. However, General Plan goals by themselves do not necessarily result in development restrictions, unless they are accompanied by specific zoning or code provisions. Therefore, analysis needs to include, as outlined in the previous section, to what extent groundwater protection goals are enshrined in clear guidance to both developers and project design review and implementation oversight staff. In addition to the number of land use jurisdictions per watershed with the authority to restrict development in groundwater recharge areas, the calculation for the indicator score may need to include some kind of point system for (a) applicable municipal or county codes; and (b) compliance and implementation outcomes. The second metric number of ordinances encouraging and facilitating grey water re-use also resides under the jurisdictions of cities and counties, with oversight by the California Department of Public Health. Of the eight land use jurisdictions in the Sonoma Creek and Napa River watersheds, none facilitates grey water re-use. A similar need exists for the grey-water re-use dataset as for the other four policy-related data: In addition to counting the presence or absence of ordinances or codes that enhance water self-reliance, a transparent method of assigning points based on implementation friendliness and implementation outcomes needs to be developed. This is not a trivial task and requires in-depth analysis and the development of a classification system for assigning points that is outside the scope of this current Score Card project. The third dataset required for the Water Self-Reliance Indicator - number of building code provisions encouraging runoff harvesting and storage features for all land use designations also has the number of land use jurisdictions as a foundation. While County General Plans may explicitly mention the facilitation of runoff harvesting features as goals or objectives, none of the eight land use jurisdictions in the Napa River and Sonoma Creek watersheds have provisions in their building codes that encourage, let alone require, water harvesting. The fourth metric - number of state and local policies in place representing barriers to greater self-reliance requires considerable analysis first. Policy barrier interpretation is often in the eye of the beholder. However, it may be possible to develop unambiguous criteria for what could be considered a clear barrier to greater self-reliance and keep track of barrier removal over time. The last data set is much simpler to analyze and calculate, since reporting requirements for recycled water amounts are fairly straight-forward. Each city in the Napa River watershed manages its own water supply, and sewage treatment facilities are servicing all sewered areas, which more or less overlap with city boundaries. The five publicly owned sewage treatment facilities in the Napa River watershed have a current cumulative recycling potential of approximately 18,000 acre feet per year (2050 Napa Valley Water Resources Study, (http://www.napawatersheds.org/Content/10210/Water_Use__Supply.html). Each facility keeps track of how much of its treated wastewater is reused, and a percentage of recycled water can be calculated for each reporting period. A little less than 50% of water for municipal and industrial uses in the Napa River watershed is imported, while most residential water users in the unincorporated areas of the watershed obtain their drinking water from private wells or surface water diversions via riparian rights (the exception are customers of the Howell Mountain Mutual Water Company - a small water purveyor that services about 1,500 residents in the unincorporated town of Angwin). Agricultural water users also rely exclusively on local water sources. Most unincorporated areas are recycling their wastewater on-site via private sewage disposal systems. The percentage of the Napa River watershed population that relies on private wells or riparian rights comprises less than 18% of the total. Approximately the same percentage of the population recycles a large proportion of this water via private sewage disposal systems. The Napa Sanitation District, the largest in the watershed, generates on average approximately 10,000 acre feet per year of tertiary-treated effluent, of which about 22% is recycled, mostly for irrigation supply to golf courses, parks, school grounds, and commercial purposes (David Martin, NSD, personal communication). The watershed-wide water recycling percentage of treated effluent can be calculated by averaging the percent effluent recycled from all five publicly owned treatment works. More nuanced data may be added to the calculations to differentiate water recycling directed at high water users, such as golf courses and turf production vs. groundwater replenishment and aquifer restoration that could lead to higher-value uses. The sewered areas in the Sonoma Creek watershed are serviced by x sewage treatment facilities with a cumulative daily treatment average of xx million gallons, or a current recycling potential of XXX acre feet per year. Private sewage disposal systems recycle their wastewater on site, comprising approximately x% of the Sonoma Creek watershed. Water purveyors service approximately x% of the population residing in the Sonoma Creek watershed, with the Sonoma County Water Agency servicing x% of the watershed population. Similar to its neighboring watershed, the service boundaries of water purveyors and publicly owned sewage treatment works tend to overlap considerably [confirm]. X% of the watershed population obtains their drinking water from private wells or surface water diversions via riparian rights. While approximately X% of water for municipal and industrial uses is imported, unlike the Napa River watershed, a significant number of households recycles this imported water on-site via private sewage disposal systems.[confirm] Imported water may therefore contribute considerably more to the amount that is recycled and stays in the watershed longer than in the Napa River watershed. Evaluation and scoring We are not scoring the METRICS. We are scoring the indicator. The datasets associated with the Water Self-Reliance Indicator, once fully compiled and analyzed can be compared to benchmarks associated with desired condition. For the four policy-related datasets, the number of policies, guidelines, and codes could be converted into a point system that includes compliance and implementation and then compared against the ideal points that could theoretically be achieved. Similarly, for the recycled water use data, a 100% reuse goal could be converted into points that can then be added to the overall score for all five elements of the Water Self-Reliance Indicator. Because not all of the data needed to score this indicator nor a consistent analysis and data classification system have yet been developed, we did not attempt to score this indicator at this time. Discussion This indicator tells us much about the level of governance and stewardship that is in place to promote water self-reliance and minimize the transfer of impacts in other watersheds that might otherwise experience resource extraction at the expense of their own watershed health. The more self-reliant a watershed is, the greater the likelihood that it can respond adequately to changing climate conditions or natural disturbances. Data Gaps and Recommendations The analysis of state and local policies related to water self-reliance will require considerable time and resources due to the dispersed nature of the data and the lack of an appropriate and standardized classification system that would allow us to assign points or scores in a transparent and objective manner. Index: Water Supply, Indicator: Impervious Area (Sonoma Creek) Introduction Kat: Lisa can fill in to speak to the whole retention indicator. Ill just focus on the impervious metric. Data availability Two major datasets were considered for the percent impervious area (IA) indicator: the National Land Cover Database (NLCD) which covers the entire United States, and a dataset based on General Plan land use data developed by the Information Center for the Environment at UC Davis. The reliability of NLCD (as a federally funded and widely-used dataset) and the shorter time needed to calculate impervious area made it the best choice for this project. NLCD was developed through a partnership called Multi-Resolution Land Characteristics Consortium (MRLC), a group of several federal agencies (USGS, EPA, USFS, NOAA, NASA, BLM, NPS, NRCS and USFWS). Percent imperviousness was calculated using Landsat imagery and orthophotographs to calibrate an algorithm that produces % imperviousness per pixel. This particular dataset is ideal because it applies a consistent methodology to all 50 United States and Puerto Rico, so that data for imperviousness can be compared across many watersheds and regions. Even though the two watersheds in this project are right next door to each other, land use data varies by county, and so NLCD was the best way to assure consistent data. There are a few caveats about the NLCD that stem from it being a widely applied dataset across a large area. First, the dataset is by now over 7 years old. A large amount of development has occurred in both watersheds, and it is difficult to project the % change in IA since the NLCD was developed in order to get a better idea of current imperviousness. Second, the data is based on an algorithm that was calibrated using a sample of photographs, and there may be errors due to how certain structures or landscapes appear in a photograph and how much impervious area is actually present. A detailed description of the methodology and dataset is explained in Homer et al 2004 and at  HYPERLINK "http://www.mrlc.gov" http://www.mrlc.gov. The first version of NLCD was developed in 1992, and updated for 2001. Given this timeline, and the natural increase in development throughout the country it is likely that this dataset will see a third version within the next 5 or so years so that there is a new version every 10 years. However, there is no information from MRLC at this time that indicates the future updating of this dataset. Analysis, methodology, calculations One of the chosen metrics for this indicator is percent IA. It was calculated using the NLCD, and a series of steps in the computer program, ArcGIS. The NLCD was loaded into a map document, along with watershed boundary shapefiles for both Sonoma Creek and the Napa River. A mask for the watershed boundaries was applied, with the extent for the impervious layer set as the same for the watershed. Then raster calculator was used to calculate the percent IA in each watershed. This method was used to calculate percent IA for 20 Bay Area watersheds by Circuit Rider Productions for a project looking at steelhead habitat. Since there was no need to duplicate this effort, we used their results from calculating IA. There are a range of methodologies for estimating or calculating IA including using satellites, ground surveys, global positioning system technology, aerial interpretation, or a combination of methodologies. This method was already applied by another organization and was easily accessible for this project. In addition, as mentioned above, the 2001 NLCD is nationwide, meaning that this method can be used in other watersheds in California or across the country for comparison. Other methods are more time consuming and though they may be slightly more up-to-date or detailed due to changes in resolution, it was not within the scope or budget of this project to pursue those methodologies. In an ideal world higher resolution photographs taken from a plane would be analyzed and impervious areas delineated for both watersheds to have more exact area calculations. Using this alternative method, statistics on impervious area could be obtained for individual subwatersheds or even smaller scales to allow for more site-specific planning of development and riparian area management. In an even more ideal world, the metric would be effective impervious area instead of total impervious area. Effective impervious area (EIA) may be considerably different because it only includes the impervious surfaces that are directly connected to streams and other water bodies. There are several possible means of connection, including a storm drain system, or agricultural areas with extensive engineered hill slope drainage or plastic covering for crops, which direct runoff directly into ditches and streams. EIA excludes those areas that direct runoff into some sort of treatment area because it is less likely that those areas contribute a significant amount of pollution to receiving waters (Booth and Jackson 1997; Walsh 2004). It can be argued that EIA is the more accurate indicator of stream health (Brabec et al 2002). The argument against TIA comes from the fact that watersheds with a comparable percentage of TIA can have a wide range of biological conditions, due in part to the varying percentages of impervious areas that directly feed runoff into streams without some kind of pretreatment. This is particularly relevant in watersheds with little urban development (Walsh 2004; Booth et al 2002). Walsh conducted a study in 16 watersheds near Melbourne, Australia to test this theory (2004). His results showed that the amount of storm water connections, or degree of drainage connectivity, was a better predictor of macroinvertebrate taxa richness and composition that simply TIA. He also suggested that in order to restore stream health and improve degraded watersheds in an urban setting, local governments should focus first on reducing the amount of direct connections between streams and the storm water system and then later address habitat restoration. Even if riparian buffers and other natural filters for runoff are implemented, their potential for filtration might not be fully utilized as long as storm water systems bypass these areas. Further, the offsite causes of habitat degradation would still be in place without first reducing drainage connectivity. However, given the variable distribution within a watershed, and varying recognition of impacts, precision may not always be important. Many applications do not require the use of IA as a precise indicator, but instead apply it more broadly as a screening device used to make a rough estimate of where in a watershed pollutant loads or other impacts could be high, where effects of hydromodification might be more pronounced, or where to prioritize the implementation of management measures in order to identify current and predict future impacts so they can be mitigated or prevented, To make coarse calculations, it is not necessary to have a precise means of measurement. Though results could have changed slightly with higher resolution photo-interpretation, the relative impervious area between watersheds would most likely remain the sameNapa has slightly more imperviousness than Sonoma Creek, but both are on the very low end of the scale and at the same order of magnitude. Evaluation and scoring The Center for Watershed Protection (CWP) in Ellicot City, MD has popularized the idea that watersheds consisting of more than 10% impervious area, tend to exhibit impaired stream health. Further, after an approximate threshold of 25%, the system may be non-supporting to aquatic life (Schueler 2000). This rule has been confirmed by about 50 other studies, but there are also many exceptions to this rule. CWP discloses that this threshold has not been tested in California or other semi-arid regions of the country and that it only applies to 1st-3rd order streams (CWP 2003), as the impacts of imperviousness for higher order streams will be more cumulative. Two studies in the West (Austin, TX, and the Rocky Mountain) revealed that the 10% IA threshold rule does not necessarily apply (Maxted 2000; Maxted and Scoggins 2004). In both case studies, streams appeared to be more resistant to urbanization than eastern watersheds. In other studies based in southern California, streams have been more sensitive than the CWP threshold, with physical degradation of stream channels [detected] when basin impervious cover is between 3% and 5%. However, biological effects are probably occurring at even lower levels (Stein and Zaleski 2005). Some studies have concluded that any amount of IA, under existing management practices, will negatively affect aquatic systems (Booth et al 2002). Based on the above literature review and the fact that IA is really used when comparing watersheds, it is not really possible at this time to score this metric. Short term trends are difficult to predict but over the long term it is inevitable that more development will occur in both watersheds, lending to an increase in IA throughout both watersheds. However, the amount of EIA, which is directly connected to stream channels, may decrease over time. With the growing popularity of low impact development (LID) design and techniques implemented for stormwater control and provisions showing up in building codes, it is possible that more runoff will be treated onsite before heading straight into stream channels. Pervious pavement, filter strips, and other similar designs allow for the more natural percolation of water into the ground so that large flows do not inundate stream channels, erode banks, and further exacerbate hydromodification that is occurring in both watersheds. Discussion The most valuable thing that this metric tells us is that the Napa River, with a slightly higher percentage of IA (6.09%) than Sonoma Creek (3.63%), is at a slightly higher risk for hydromodification and the negative impacts that such action brings to river systems. Because the scope of this scorecard does not include analyses of macroinvertebrate taxa richness, or other biological indicators of riparian health, it is difficult to determine whether the ecological health of either system is at great risk for degradation and at what scale the problem has reached. However other studies, such as those related to the Sediment, Nutrients, and Pathogens TMDLs for both watersheds, indicate that there are major problems common across both watersheds that are caused by increasing development (urban, suburban, and agricultural) and are affecting water quality. There are concerns about the utility of using percent IA as an indicator of stream health in semi-arid regions such as California. Coleman et al (2005) examined the response of southern California streams to increasing IA and the accompanying hydromodification. They found two key aspects of a watershed affected this response: 1) the size of the watershed, and 2) the seasonality of a stream channel. Most watersheds in the study had at least some channels with ephemeral or intermittent flow, since they are very common in semi-arid climates, even in larger watersheds that have more contributing runoff. They found that ephemeral channels are more sensitive to change in total IA, and exhibit signs of degradation at 2-3% IA, in contrast to perennial channels in humid regions in the literature, which start to degrade at 7-10%. In addition to climate, there are two other major considerations when evaluating a watersheds response to increasing IA. First the effects of hydromodification are much more pronounced in small storms than in larger storms. This is due in part to the common state of artificially increased drainage connectivity in a watershed. In urban settings, increased connections come from a variety of sources, including storm drain systems, swales and ditches along roads, concrete channels, and other conveyance infrastructure for flood control or water supply. In agricultural or other rural areas, tile drains placed in fields to reduce soil saturation can increase conveyance of runoff and increase the connection between small ephemeral streams, to major channels. In undeveloped areas where increased connectivity is rarely the case, runoff from small storms would naturally infiltrate into the ground or form small ponds that would eventually evaporate or infiltrate. However increased connections throughout the watershed, created to accommodate increasing impervious areas, funnel runoff through the various infrastructures into larger channels instead of allowing for natural infiltration. Increased runoff volume leads to increased velocity that invariably results in severely altered channel geometry. In large storms, connections between tributary streams and main channels are made whether the landscape is developed or not, due to natural topography and infiltration capacity of the soils being exceeded over larger areas for longer periods of time. The accumulation of effects over many small storms often surpasses the damage done by one, large storm. Another major consideration when evaluating the effects of hydromodification is spatial location of the impervious areas in a watershed relative to other land uses and the outlet of the basin. If a large percentage of the watersheds IA is located in the upper reaches of the watershed, the impacts to aquatic biology will accumulate throughout and, overall, be more pronounced. If the IA is concentrated farther down or even at the mouth of a watershed, such as in an estuary, the effects will be more localized and perhaps less severe. In this scenario, the upland reaches should remain relatively unaffected, assuming they are less developed. Most watersheds, however, have impervious areas unevenly distributed throughout the landscape, mostly in the form of roads and houses, with perhaps a few urban centers. In this case the effect of IA cannot be easily determined except on a case-by-case basis. Data Gaps and Recommendations recommendations for future reporting on this indicator, both in the real world and in the ideal world? Summary and recommendations for future watershed scorecard efforts [2-3 pages] Not just about content and technical lessons learned, but also about this Scorecard teams experience of the projects process, and recommendations for future Scorecard editions in these watersheds or Scorecard projects in other watersheds [pull text from annual report] Im not sure were ready to write this section yet. Maybe we should wait until closer to the end of the project. --Caitlin Funders and acknowledgements [under 3 pages] Authorship This report was written by (in alphabetical order): From Sonoma Ecology Center: Caitlin Cornwall, Deanne DiPietro, Becca Lawton, Lisa Micheli, Alex Young. From Napa County Resource Conservation District: Frances Knapczyk, Robert Zlomke. From The Bay Institute: Peter Vorster. From San Francisco Estuary Institute: Rainer Hoenicke, Kat Ridolfi. Technical sections 3 5 were authored by: Water Supply index: Lisa Micheli Cumulative flow indicator: Alex Young: Dry season flow indicator: Robert Zlomke Impervious area indicator: Kat Ridolfi Water Storage index: Robert Zlomke Surface storage indifcator: Alex Young Groundwater indicator: Robert Zlomke Water stewardship index: Rainer Hoenicke Water self-reliance indicator: Rainer Hoenicke Water use indicator??: Peter Vorster Water retention indicator??: Lisa Micheli Funders We are grateful for the vote of confidence shown in this project and this team by our funders. Major funding for the 2009 Watershed Health Scorecard came from the CALFED Watershed Program (agreement # 4600004706), administered by the Department of Conservation. Secondary funding sources included the State Water Resources Control Board (2005 - 2006 Consolidated Grants - Proposition 50 Coastal Non Point Source Pollution Control, Agreement No. 06-346-552-0); [Who Else?] Acknowledgments We thank Leigh Sharp, district manager at Napa County RCD, for helping obtain funding for the project. We thank Tina Swanson, executive directjor at The Bay Institute, for expert advise on the complex process of bringing a scorecard project to completion. We thank Chris Farrar at US Geological Survey for being the groundwater advisor on our technical team. [who else?] References [I think we should instead have a references subsection for each indicator and indexCaitlin] Cited for groundwater indicator: U.S. Geological Survey (USGS). (2006). Geohydrological Characterization, Water-Chemistry, and Ground-Water Flow Simulation Model of the Sonoma Valley Area, Sonoma County, California, with a section on basement rock configuration interpreted from gravity data by Victoria E. Langenheim. Farrar, C.D., Metzger, L.F., Nishikawa, Tracy, Koczot, K.M., and Reichard, E.G U.S. Geological Survey Scientific Investigations Report 2006-5092, 167 p.  Hydromodification from changes in impervious area are most recognizable in watersheds smaller than about 20 square miles, and management of IA is most critical in watersheds less than 2.5 square miles (p. 54). While these finding do not apply to the either Sonoma Creek or the Napa River watershed as a whole, they could have implications for applying management measures at the sub-watershed level. 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