Access to clean water is critical to our happiness and well-being as a society. Clean water is required for drinking, bathing, watering crops, and supporting recreation and wildlife. Yet, numerous man-made factors are degrading the health of our streams and rivers, resulting in impaired water quality and a lower quality of life. According to the U.S. Environmental Protection Agency, these factors include increased amounts of:
• Point and non-point source pollution;
• Municipal wastewater and storm water runoff;
• Agricultural runoff of sediment, fertilizers and pesticides;
• Channelization, construction and land development;
• Water withdrawls, barriers, and habitat modification;
• Removal of riparian vegetation, and streambank destabilization.
These factors lead to economic inefficiencies, including higher water treatment and delivery costs, more water use restrictions, enhanced drought and flood risk mitigation efforts, and costs associated with avoidable water-related disasters. These factors also degrade entire ecosystems and the overall environment through the loss of instream habitat and increased numbers of Threatened and Endangered Species.
Improving water quality in a stream or river is complex. Most often, many different issues combine to impair water quality and stream health and such conditions can vary widely throughout a stream system. High quality and detailed data are fundamental to understanding the current conditions and issues in any river or stream corridor. Such data is critical to applying an integrated planning and management framework for prioritizing and implementing remediation plans. The new High Definition Stream Survey (HDSS) method is a much faster and more cost effective way of collecting this data. HDSS involves collecting continuous visual and numerous other data points over long (many mile) waterway segments. The results of an HDSS effort are highly valuable for stream channel assessments, water quality and quantity studies, habitat assessments, community outreach and overall integrated watershed planning (Figure 1).
In contrast to the continuous coverage of long stream segments provided by the HDSS approach, traditional stream sampling surveys are based on point samples or descriptions of short sections of streams or rivers. These traditional methods collect information on a small percentage of total aquatic habitats and then extrapolate the findings between sampling sites to fill in the gaps. It is not uncommon for a few-hundred-meter survey site to be considered representative of 20 or more miles of adjacent stream. Extrapolation of data is a major source of error and will completely miss problems if the problem areas fall outside of a sample location. The HDSS method avoids the problems of data extrapolation by collecting a continuous survey of the entire river segment allowing the location, extent, and intensity of problem areas to be accurately identified (Figure 2).
Figure 2. An example of good and bad streambank conditions. These two sites are located about 1 mile apart on the Big Canoe Creek, AL. These images highlight the variability of conditions throughout a stream and the difficulty of choosing a sampling location that accurately reflects stream conditions as a whole.
The heart of the HDSS method is the ability to gather a wide range of stream corridor data at a consistent spatial resolution (Figure 3). This means that documentation of stream corridor conditions is rapidly and consistently applied to very long stream segments which results in continuous measurements. Traditional survey methods focus on collecting highly detailed measurements at one location, but ignore information for miles in either direction. The HDSS method not only delivers a more complete data set than traditional surveys but is also much more efficient, as fewer people are needed to capture data more quickly along longer portions of a stream. The HDSS methodology can capture data in wadeable and non-wadeable streams, providing more consistent and broadly applicable results while still collecting the data at a greater speed.
Figure 3. HDSS gathers information from the front, both sides, and down while recording time and location every second. This rapid approach provides consistent spatial resolution data for long stream segments and is far more efficient and effective than traditional transect approaches.
The HDSS method is an outgrowth of research efforts developed at the University of Tennessee. The rapid, multi-attribute, geo-referenced techniques have been tested and used for delineation of streambank erosion potential (Connell 2012), development of sediment TMDLs (Hensley 2014), mapping of aquatic habitats (Candlish 2010, McConkey 2010, Connell and Parham 2015), comparing thalweg and cross-sectional transect approaches (Swinson 2012), and prioritizing restoration areas (Connell and Parham 2014). The method has been used successfully on numerous streams and rivers including Big South Fork River, TN (McConkey 2010), Obed River, TN (Candlish 2010), Beaver Creek and the New River, TN (Connell 2012), Paint Rock Creek, AL (Connell and Parham 2014), Bear Creek, AL (Connell and Parham 2014), Turkey Creek, AL (Connell and Parham 2015), Manoa, Palolo, Makiki, Waiawa and Iao Streams, HI (Parham 2015) and many others.
The HDSS method follows a standardized process that promotes rapid, systematic collection and processing of large amounts of river condition information (Figure 4). The specifics of the data collected can be customized to meet a project’s requirements, but following the basic HDSS process ensures a successful project.
Figure 4. Standard HDSS project flow chart. Systematic data collection and processing supports high quality project results.
High Definition Stream Surveys (HDSS) provide many advantages over traditional transect-based stream surveys. Some of these advantages include:
Better Data: HDSS provides continuous, geo-referenced data regarding river corridor conditions. This eliminates the need to extrapolate conditions from transects and spot data collections.
Faster Data Collection: Automated and continuous data collection using HDSS has proven to be much faster and more accurate than traditional transect survey methods. This allows much larger areas to be sampled over the time budgeted for field work.
Much Higher Value for the Cost: The HDSS method provides a broader array of data than traditional transect surveys. Using HDSS, multiple miles of continuous stream data (i.e., both stream banks, stream bottom, water quality and water quantity, habitat, and geomorphology) can often be collected in the same amount of time that a traditional transect method would take to cover several hundred meters of point data.
Reviewable Results: The HDSS system captures and synchronizes a high definition video of a stream ecosystem with sonar, water quality and other data, and then maps everything to a stream using a geo-referencing process. Users can revisit the results at any time in the future and see what conditions looked like at any point or section of the stream as of the collection date. HDSS data collection is automated, simultaneous, continuous and frequently validated during the collection process. In contrast, traditional survey methods require the repetition of discrete and highly manual data collection steps over multiple sites which increases the likelihood of inconsistent measurements, recording errors, missing or invalid data. Missing a collection step or problems with data validation usually requires additional field work to obtain the information, which can compromise the quality of the overall data set due to differences in stream conditions. Moreover, traditional survey methods do not provide extensive visual representations of a waterway due to limited survey stretches.
Wider Application: HDSS is not a single answer survey. The results can be used to support a wide range of river management applications. In the past, different surveys were often conducted in the same waterway to answer different questions. For example, water quality samples collected at multiple locations in a river system would not provide information about instream habitat or the condition of infrastructure along the river. Inefficient data collection practices boost cost and make integrated management much more difficult. The data collected in a single HDSS survey can support many different types of assessments: streambank erosion susceptibility, habitat, corridor, infrastructure, water quality, water quantity, impact, and others. Thus, HDSS enables collaboration and better water management much more efficiently.
Powerful Visualizations: The HDSS approach provides a powerful, integrated dashboard visualization of your waterway. No longer are survey results explained in confusing charts and statistics that often represent a single metric dissociated from the rest of the survey results. HDSS results show instream conditions in high-definition video, superimposed with other survey data or results, if needed. HDSS is a virtual solution that puts decision-makers “in the field” so they can actually visualize problem areas and gain a better understanding of their relative magnitude and impact.
Increased Collaboration: HDSS promotes collaboration and partnerships by collecting data useful to many organizations with a single survey. Collaboration on data collection across multiple organizations avoids the unnecessary cost of soliciting and managing multiple and often redundant surveys whose results often do not support integrated management.
Integrated Watershed Management: Stream and river systems are influenced by the land and upstream conditions. As a result, managing for a single aspect of the stream is costly and inefficient. The HDSS approach can better align multiple management objectives by collecting core data relevant to all concerns and more specific or customized data for more targeted concerns, all in one survey.
Easy to Integrate with GIS: All HDSS data are continuously geo-referenced: data are synchronized by time and mapped to the particular point in a waterway where it was collected. HDSS data easily integrates into modern Geographic Information Systems (GIS) to allow other spatial data to overlay the HDSS survey results.
Excellent Time-Series Comparisons: The HDSS method collects continuous data along much longer sections of a waterway, which makes it very simple to compare changes in a particular area or multiple different areas over time. In traditional surveys, change observations would be limited to the transect locations.
In small wadeable streams, the majority of the work is accomplished using the backpack-mounted HDSS system (Figure 1). When using the HDSS Backpack system, the surveyor follows the thalweg of the stream. The backpack-mounted HDSS system enables continuous GPS tracking, high-definition video of the stream and surrounding areas with image stabilization, underwater video in areas of appropriate depth, and water quality samples. Water quality measurements can be collected at user defined intervals (typically every 50 to 100m) and at any sites of interest, such as incoming tributaries or outfall pipes.
The HDSS Kayak system is used in floatable streams and small rivers (Figure 2). In addition to data captured by the HDSS Backpack system (GPS tracking, water quality, and high definition video of surrounding areas), the HDSS Kayak system also captures underwater habitat, biota, substrate and channel condition data using underwater video and side-scan sonar. Sonar will accurately capture data in areas too deep or too turbid for video. The GPS data is combined with the depth and water quality data to create data-rich stream maps.
Figure 1. Dr. Jim Parham surveying Brook Trout habitat in the Cherokee National Forest using the HDSS Backpack system.
Figure 2. Example of survey equipment on the kayak HDSS system.
The HDSS method produces a continuous flow of standard stream corridor variables pertaining to both shoreline and instream parameters, as shown in the tables below. While the standard variables are highly useful, additional variables can be added or substituted based on their availability and unique project requirements. Trutta can assist in selecting the variables that will provide the widest applicability of the final data while effectively answering project-specific questions.
The following variables are commonly collected using the HDSS method:
Visual data provided by the HDSS video (e.g., stream bank condition or substrate) are classified based on recognized scientific standards systems by highly trained classification experts using proprietary HDSS Video Coder software (Figure 1).
Figure 1. Proprietary HDSS Video Coder software enables custom classification schemes to be applied to the video and links the attribute score to the exact stream location.
Numerous classification variables can be developed from the video or side-scan imagery, including habitat types (Figure 2), left and right bank condition (Figure 3), substrate type, percent embeddedness, and bottom type, to name a few. HDSS video also makes it possible to identify discrete objects such as man-made structures, large woody debris, or tributary junctions.
A key strength of the HDSS approach is the ability to gather a wide range of stream corridor information at a consistent spatial resolution. This means that your classification system is rapidly and consistently applied to very long stream segments, rather than producing highly detailed measurements at one location, but no stream information for miles in either direction. By using HDSS Video Coder software we can create custom classification systems that differentiate the important features within a particular system, depending on your needs. More information enables better analysis and better decisions.
Figure 2. An example of Habitat Type Classification using images from the HDSS Backpack system.
Figure 3. An example of Bank Stability Classification using images from the HDSS Kayak System.