January-February 2009

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Supporting Streams

Introducing three disciplines

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Adam Sukenick taking stream samples

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By Lanse Norris, Adam Sukenick, Bob Bourne

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The different sections of this article are written by three members of the Cobb Country, GA, Stream Monitoring Program. Three previous articles on the program have appeared in past issues of Stormwater: “Municipal In-Stream Monitoring” in the September 2008 issue, “Municipal In-Stream Chemical Monitoring” in the October 2008 issue, and “Municipal In-Stream Macroinvertebrate Sampling” in the November/December 2008 issue.

Introduction
Although I have summarized and then detailed the essential components of Cobb County’s Stream Monitoring Program in the last three issues of Stormwater, I want to conclude by presenting three important disciplines supporting the comprehensive nature of stream monitoring: geomorphology, riparian botany, and geographic information systems (GIS) applications for stream sampling. Robert Bourne, the program’s long-term biologist from 1994 to 1999, addresses fluvial geomorphology and riparian botany. Adam Sukenick and Erin Feichtner have administered the Stream Monitoring Program since 1999, and in this article Adam addresses GIS applications for in-stream monitoring. Whether considering geomorphological impacts of flow-sponsored sediment redeposition, riparian “buffering” of high-sheet-flow and absorption of overabundant plant nutrients, or GIS management of multilayered water-quality program assets and relevant land use features, it is not difficult to understand how geomorphology, riparian botany, and GIS applications directly support and aid in interpreting in-stream chemical and biological assessments.

Cobb County’s Stream Monitoring Program is mandated, firstly, by National Pollutant Discharge Elimination System (NPDES) legislation requiring a “monitoring program for representative data collection for the term of the permit that describes the location of outfalls or field screening points to be sampled (or the location of in-stream stations), why the location is representative, the frequency of sampling, parameters to be sampled, and a description of sampling equipment” (CFR 40 122.26). The program also fulfills biological sampling requirements for the NPDES permits of Cobb County’s Noonday Creek and other expanding wastewater reclamation facilities. Such sampling requirements were also recently added to sampling regimens emphasizing chemical sampling in Phase I communities such as Cobb in the Metropolitan North Georgia Water Planning District.

Anthropogenic-influenced, high-flow scoured bank with threatened tree, which, ironically, is needed for stabilization
The California Stormwater Quality Association (CASQA) also addresses the call for enhanced water-quality assessment in NPDES programs, first defining general program assessment as providing managers “the feedback necessary to determine whether their programs are achieving intended outcomes (complying with permit requirements, increasing public awareness, changing behaviors, etc.), and ultimately whether continued implementation will result in water quality and/or habitat improvement” (CASQA 2008). Further distinguishing between the implementation outcomes of programs like street sweeping, erosion control, and education and the desired result of improved water quality, the document goes on to exhort more limited programs to “evaluate program implementation and water quality, and seek to find the relationship between the two.” The CASQA document concludes with some “Effectiveness Needs and Future Directions,” arguing for “development of cost-effective water quality assessment tools” and lamenting the “lack of readily available and understandable methods”; both deficiencies, it says, contribute to the preponderance of implementation assessment per se over water-quality (improvement) sampling. From California to Georgia, direct, comprehensive water-quality assessment is incumbent upon water resource managers and planners, as NPDES program implementation water-quality impact has been an issue for some time with entities ranging from nongovernmental organizations to Congress and the Office of Management and Budget.

Communities with opportunities to enhance their programs by initiating comprehensive water-quality assessments must become undaunted opportunists in preserving their most critical resource. Alternatively, communities already established in water-quality sampling must not ease into inertia and the easy chair of regulatory adequacy, as there are kinetic, complex, physical, and political pressures characterizing communal life journeys that are far from over. Indeed, environmental professionals and the communities they serve must consider what must be done in the tough terms of what had to be done.
—Lanse Norris

Establish GIS for the Future
Although water-quality analysis has advanced with technology, water-quality technicians have been using the same collection methods for some time. Although we have a better understanding of complex relationships between sampled water quality and biological populations, what has really changed is our capacity to store, analyze, and interpret the data.

Geographic information systems have the capacity to revolutionize what we do with whole, historical data sets. The most commonly recognized component of GIS is the final product, a graphical representation of the data—a map. However, to think of GIS as only a map would be tantamount to thinking of a water-quality study as only a final overall score of “good” or “poor” for a stream.

If you were tasked with the responsibility to conduct a study to determine baseline water-quality conditions, you would likely begin by selecting sampling sites—sites that represent average conditions within the study area. Considerations in choosing sites might include land use, industrial discharges, drainage area, topography, stream accessibility, hydrography, riparian composition, and soil type; the list is really limited only by the time and resources you have to invest in the project. To begin selection, you could find a land use map, determine major land use classes within the study area, and place a sampling site in each class. Next, you could look at industrial discharges to make sure sampling sites are not in a direct waste stream. Certainly, you would also evaluate drainage areas so that various sized watersheds were being sampled, as well as first-, second-, and third-order streams. After preliminary site selection, you would also pull out topographical maps and look at road coverage to see whether the sites selected are accessible.

Instead of using a drawer full of maps and countless hours of field reconnaissance, you could employ GIS. GIS can be useful in site selection by first defining the study area, then adding as many site-influencing “layers” as you have available. Think of each map in the above scenario as a layer on a GIS. Layers can be turned on and off to look at multiple images (or combination of images) at once. By using the hydrography, riparian, and soil layers simultaneously, you could, for example, determine that sites are likely situated in wetlands without having to go to the field and spar with aggressive wetland insects. To optimize time and efficiency, criteria for site selection are predetermined, and GIS is used to choose potential sites. Later, after sites are field-verified, you can create a whole new layer to geographically display your sites.

With site selection finalized, you must now consider which chemical parameters, for example, to analyze and how to manage data. Consider that every visual map is really only a graphical representation of some data set. Management of data is the second, less appreciated, component of a GIS. A road map is merely a list of road names geographically referenced and displayed. Water-quality data, like road names, can also be managed and later displayed using GIS. A database of results from water-quality analysis can be stored and used to “map” results of a water-quality study. Each site sampled for a study will be geographically referenced with a name, location, and dataset. Later, GIS can be used to visually display information contained within that dataset. For example, fecal coliform data stored within GIS can be queried and used to create a display that graphically displays each site that fails to meet the state standard. Beyond that, with proper planning, chemical and land use data can be cross referenced and used to display geographic relationships, such as displaying all sampled sites located downstream of agricultural land use areas that fail to meet state water-quality standards for fecal coliform. Even further, by analyzing several years of data, you may be able to determine trends in the data, such as when fecal coliform thresholds were exceeded and the rate at which they’re increasing.

With enough data entered into the system, the data relationships you can infer are quite comprehensive. If a water-quality study includes data from outside sources (such as industrial monitoring, sanitary, and storm sewer discharge data), as well as collected water chemistry, GIS may be useful in detecting sources of “hits,” or unusual results, found during routine sampling. Essentially, field investigation or reported problem inquiries often begin at your computer. For example, if lab analysis produces a metals result well above typical baseline levels, you can use GIS to first display topography and delineate the area draining to the point at which the sample was collected. Then, using land use coverage, the next step could involve highlighting all industrial land use (the area with the highest potential to produce metals contamination). Next, locate known industrial discharges within this selected area and query industrial monitoring data to determine which industry is likely to produce waste with metal identification and concentration close to the sample collected downstream. If this doesn’t immediately narrow your search or identify the source, it may mean that there is a new industry or previously unmonitored industry you are not aware is discharging.

Using GIS to expose complex relationships illustrates the third and final component of a GIS—its ability to analyze data and model or create unrealized or derived datasets. GIS has the ability to manage countless datasets, and its usefulness as an analytical tool is limited only by the stored data. The example applications above illustrate how chemical, land use, and industrial monitoring data can be used to detect trends and locate sources of pollution, but consider GIS coverage of nonpoint-source information. Biological and habitat data, for instance, are key elements of any water-quality program and are very susceptible to change and influence from external inputs. Storage of biological datasets gives a user the ability to graphically present sites with the best biological diversity or illustrate locations where rare or endangered fish were collected. However, by cross-referencing databases, we may discover relationships previously unknown. More obvious relationships between biological and chemical results have been explored, but using GIS might quickly identify subtle thresholds or parameters that limit diversity. For instance, by geographically mapping all sites where sensitive species, such as stoneflies, exist and analyzing concomitant water chemistry results versus water chemistry results where stoneflies are not found might demonstrate the possibility of a biological limiting factor like pH or low dissolved oxygen (DO). With enough chemical and biological sampling information, different existing datasets may be cross referenced, and they may already hold enough information to conclude that below a certain pH or DO level stonefly populations will vanish. With thresholds for stoneflies established, one can now filter the entire dataset to look for downward trends in pH or DO. If results are found to be approaching stonefly tolerance levels, the identified sites can be prioritized for additional study or protection.

Good natural buffer with integrated, stabilizing vegetation
GIS has broader applications that cover projects from implementation to assessment. From the initial question to the final answer, GIS streamlines each step. New components of compliance permits, for example, can be organized, managed, and evaluated using GIS. After identifying a problem—perhaps spill containment time—GIS can be used for initial analysis of the problem.

In this case, one would identify all streams and likely points of entry, such as storm drains or industrial discharges, then collect input flow data through field work or from local monitoring stations (such as USGS gages) to determine baseline flow rates at several points within each watershed. With these data, one can employ GIS to test spill scenarios and response times. With flow-rate data, and using spatial analysis to derive spill travel distance, one could determine the dispersion time of a spill from its point of entry to locations downstream, and, by adding traffic datasets for the same area, one could also determine response times to locations throughout the region. With the problem and response times now identified, one could focus on slow response times and implement strategies to expedite containment. Using GIS, one could create datasets to identify areas where current response plans are not adequate. The user could also map areas where the fastest response time is most critical. Next Page >

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