2005 Progress Report: Testing Watershed Classifications Relevant to Bioassessment, Conservation Planning, and Watershed Restoration

EPA Grant Number: R830594
Title: Testing Watershed Classifications Relevant to Bioassessment, Conservation Planning, and Watershed Restoration
Investigators: Hawkins, Charles P. , Baker, Michelle , Cao, Yong , Higgins, Jonathan , Lammert Khoury, Mary , Schmidt, John C. , Stevenson, R. Jan , Tarboton, David G.
Current Investigators: Hawkins, Charles P. , Baker, Michelle , Cao, Yong , Higgins, Jonathan , Lammert Khoury, Mary , Stevenson, R. Jan , Tarboton, David G.
Institution: Utah State University , Michigan State University , Nature Conservancy, The
EPA Project Officer: Goodman, Iris
Project Period: January 1, 2003 through December 31, 2005 (Extended to November 30, 2006)
Project Period Covered by this Report: January 1, 2005 through December 31, 2006
Project Amount: $853,515
RFA: Development of Watershed Classification Systems for Diagnosis of Biological Impairment in Watersheds (2002) RFA Text |  Recipients Lists
Research Category: Water and Watersheds , Water


The objective of our research project is to test the effectiveness of a systematic approach for developing watershed classification schemes useful for environmental assessment and monitoring of aquatic ecosystems. We will identify the specific watershed classification schemes of greatest utility for biological assessment, conservation planning, and the diagnosis of anthropogenic stressors for stream ecosystems in the western United States. To address this objective, we will answer four questions:

  1. How effectively do classifications derived from single types of watershed and reach attributes perform in partitioning naturally occurring biotic variation?
  2. Can sequential application of classifications based on different types of watershed attributes provide insight regarding the stressors affecting aquatic ecosystems?
  3. Can a watershed classification derived from a multivariate analysis of the joint variation in different types of watershed attributes achieve greater effectiveness in partitioning biotic variation among watersheds than classifications based on single factors?
  4. To what degree can we infer aspects of ecosystem function from watershed classifications that predict biotic structure (i.e., composition)?

Progress Summary:

This project year was largely devoted to processing field samples collected to document the response of benthic invertebrates, periphyton, and litter decomposition to stress caused by four types of human-caused watershed alterations: urbanization (Wastach Front, Utah, and Portland, Oregon), hydrologic modification (northern Utah), nutrient alteration associated with agriculture (eastern Montana and western North Dakota), thermal alteration associated with livestock grazing (northern Utah and southern Wyoming), and sediment and channel alteration associated with forest practices (northern Idaho, western Montana). We also continued to work on deriving and testing the watershed classifications that our project addresses. Some of this work involved new collaborations we developed that were related to our ideas (e.g., de Zwart, et al., 2005)

Watershed Topography/Hydrology

Our specific hydrologic objectives were to: (1) develop methods to automatically extract watershed attributes of relevance for watershed classification and prediction of hydrologic flow regime using geographic information system (GIS) and digital terrain analysis methods; (2) define the hydrologic flow regime of importance to biota in terms of quantifiable flow variables and statistics; and (3) predict the hydrologic flow regime for ungauged basins based on watershed attributes.

We have adopted the TauDEM terrain analysis software to delineate and derive watershed attributes for the approximately 800 gauged, reference watersheds and approximately 105 study sites. With the availability of improved Digital Elevation Models (DEM), digital watershed delineation tools like TauDEM (Tarboton and Ames, 2001 http://hydrology.neng.usu.edu/taudem/) and ArcHydro (Maidment, 2002) produce reliable watershed boundaries. They also can be used to compute various DEM-derived watershed attributes like relief, drainage area, and watershed shape. Nevertheless these tools are limited by DEM grid size, do not separately delineate nested watersheds, require outlets to be precisely located on streams and do not calculate all the attributes of interest.

Our study required that we have the capability to handle large regions and delineate a large number of watersheds quickly with minimal manual editing to adjust the surveyed outlets to correspond exactly to DEM-delineated streams. We also wanted to automate the extraction of specific attributes in which we were interested. Therefore, we developed a Windows-based application named “Multi-Watershed Delineation Tool” (Figure 1) to delineate multiple watersheds. This tool uses functionalities of TauDEM and ArcObjects (http://www.esri.com/arcobjectsonline/) to quickly delineate a large number of watersheds. This tool is also capable of computing DEM-derived watershed and channel network attributes such as watershed area; minimum, maximum, mean, and the standard deviation of elevations; stream order and stream length; slope of each stream segment; and contributing area at upstream and downstream ends of each stream segment.

Figure 1. The Multi-Watershed Delineation Tool


The reclassification of state geology coverages to provide a simplified classification that describes the nutrient and substrate producing potential of watersheds is now about 75 percent complete. We have been able to test the developing classification through our continued collaboration with state agencies in the western United States. The new classification was particularly successful in refining predictions of the invertebrate biota expected at streams within Wyoming, a state with particularly heterogeneous geology. These predictions, in turn, have allowed the Wyoming Department of Environmental Quality to more accurately assess biological impairment (and the likely reasons causing it). This work has been complicated by the fact that the Ph.D. student working on this task, John Olson, is a member of the National Guard, and has had to devote part of his time to the increased activity of the Guard. He may be assigned to Afghanistan for a year or more, and we are working with John to minimize the adverse impacts of this assignment on grant products.

Thermal Regimes

We have developed simple predictive models of stream temperature (monthly and annual mean, minimum, and maximum temperatures plus annual range) from long-term records collected at U.S. Geological Survey gauging stations. These models use latitude, elevation, and watershed area as predictors and are reasonably accurate. We are in the process of refining the models by including additional watershed attributes derived from GIS including hydrologic regime and estimates of solar radiation striking the watershed and its stream channels.

Channel Geomorphology

This work was largely completed during the last project period, and we are mainly waiting for the other classifications to be completed before applying the channel classifications to tests of our hypotheses.

Future Activities:

Because of the ambitious nature of this project, we have not had time to complete all tasks, but expect to do so in the next year with the approval of the 1-year, no-cost extension. Our primary work during this time period will focus on the three areas described below.

Extending the List of Watershed Attributes

Part of our work is evaluating the use of different watershed variables for predicting flows at ungauged basins and classifying streams. We will be developing methods to add more watershed variables to our existing watershed delineation tool. The watershed attributes that are intended to be added are:

  • Watershed shape factors: The shape of the watershed influences the time of concentration and shape of storm hydrographs and thereby plays a role in high flow statistics.
  • Drainage density: Drainage density influences the watershed response to a rainfall event. A watershed with high drainage density usually results in a quick runoff removal resulting in larger peak flows and hydrographs with shorter duration. TauDEM incorporates an objective method for determining drainage density based on stream network geomorphology that will be further evaluated.
  • Hypsometric curve indices: The hypsometric curve quantifies the distribution of watershed area with elevation. Hypsometric curves can be used to compare watersheds and give information about the hydraulic and hydrologic behavior of the watershed.
  • Parameters associated with geomorphology power laws including: (1) the power law probability distribution of drainage area related to flow aggregation; and (Rodriguez-Iturbe et al., 1992); and (2) the slope-drainage area function representing a dynamic equilibrium in landscape evolution (Flint, 1974; Tarboton, et al., 1992). Willgoose and Perera (2001) suggested that (1) and (2) combine to form a geomorphic basis for the wetness index distribution that is fundamental to the runoff generation when the saturation-from-below mechanism is dominant. In the power law relationships of (1) and (2), the exponents vary within a small range for different watersheds. The coefficients, however, vary between watersheds depending on the attributes such as geology and relief, dictated by tectonics and climate. These coefficients will be computed for the watersheds of interest to evaluate their effectiveness in predicting flow regimes at ungauged watersheds.

This research will advance our understanding of the relationship between flow regime variables and watershed attributes in the western United States and the relationships between watershed attributes, flow, and stream ecosystems.

Completing Other Watershed Classifications

The remaining challenges are to complete the classification of watershed geology and complete collaboration with The Nature Conservancy on testing how well the watershed/reach classifications we have derived aid in identifying areas of distinct biological potential. As mentioned previously, this task will be complicated if our Ph.D. student who serves in the National Guard is assigned to Afghanistan. At a minimum, we expect to have all western States classified prior to his anticipated January deployment. We also have hired additional undergraduate students to aid him in this task.

Testing Hypotheses and Completion of Research Products

We anticipate spending 70 percent of the upcoming year completing analyses and preparing manuscripts for publication.

Journal Articles on this Report : 7 Displayed | Download in RIS Format

Other project views: All 39 publications 15 publications in selected types All 13 journal articles
Type Citation Project Document Sources
Journal Article Cao Y, Hawkins CP, Storey AW. A method for measuring the comparability of different sampling methods used in biological surveys: implications for data integration and synthesis. Freshwater Biology 2005;50(6):1105-1115. R830594 (2005)
R830594 (Final)
  • Abstract: Wiley-Abstract
  • Journal Article Cao Y, Hawkins CP. Simulating biological impairment to evaluate the accuracy of ecological indicators. Journal of Applied Ecology 2005;42(5):954-965. R830594 (2005)
    R830594 (Final)
  • Full-text: Wiley-Full Text HTML
  • Abstract: Wiley-Abstract
  • Other: Wiley- Full Text PDF
  • Journal Article de Zwart D, Dyer SD, Posthuma L, Hawkins CP. Predictive models attribute effects on fish assemblages to toxicity and habitat alteration. Ecological Applications 2006;16(4):1295-1310. R830594 (2005)
    R830594 (Final)
  • Abstract from PubMed
  • Abstract: ESA-Abstract
  • Journal Article Ostermiller JD, Hawkins CP. Effects of sampling error on bioassessments of stream ecosystems: application to RIVPACS-type models. Journal of the North American Benthological Society 2004;23(2):363-382. R830594 (2004)
    R830594 (2005)
    R830594 (Final)
  • Abstract: BioOne-Abstract
  • Journal Article Stoddard JL, Larsen DP, Hawkins CP, Johnson RK, Norris RH. Setting expectations for the ecological condition of streams: the concept of reference condition. Ecological Applications 2006;16(4):1267-1276. R830594 (2005)
  • Abstract from PubMed
  • Abstract: ESA
  • Journal Article Van Sickle J, Hawkins CP, Larsen DP, Herlihy AT. A null model for the expected macroinvertebrate assemblage in streams. Journal of the North American Benthological Society 2005;24(1):178-191. R830594 (2005)
    R830594 (Final)
  • Abstract: BioOne-Abstract
  • Journal Article Van Sickle J, Huff DD, Hawkins CP. Selecting discriminant function models for predicting the expected richness of aquatic macroinvertebrates. Freshwater Biology 2006;51(2):359-372. R830594 (2005)
    R830594 (Final)
  • Full-text: ResearchGate - Abstract & Full Text PDF
  • Abstract: Wiley-Abstract
  • Supplemental Keywords:

    EPA regions, CA, California, OR, Oregon, WA, Washington, ID, Idaho, NV, Nevada, AZ, Arizona, NM, New Mexico, CO, Colorado, WY, Wyoming, MT, Montana, UT, Utah, watershed classification, indicators, bioassessment, restoration, conservation, diagnostics, modeling, anthropogenic stressors, multivariate analysis, aquatic ecosystems, digital elevation model,, RFA, Scientific Discipline, INTERNATIONAL COOPERATION, Water, ECOSYSTEMS, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, Water & Watershed, Aquatic Ecosystem, Monitoring/Modeling, Water Quality Monitoring, Environmental Monitoring, Terrestrial Ecosystems, Ecological Risk Assessment, Biology, Watersheds, anthropogenic processes, anthropogenic stress, bioassessment, biodiversity, watershed management, ecosystem monitoring, conservation, biota diversity, diagnostic indicators, ecosystem indicators, aquatic ecosystems, water quality, bioindicators, watershed sustainablility, biological indicators, ecosystem stress, watershed assessment, conservation planning, aquatic biota, restoration planning, watershed restoration, ecosystem response

    Relevant Websites:

    http://www.cnr.usu.edu/wmc Exit
    http://hydrology.neng.usu.edu/taudem/ Exit

    Progress and Final Reports:

    Original Abstract
    2003 Progress Report
    2004 Progress Report
    Final Report