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Watershed Experiments

Watershed Experiments. Lab 3. Watersheds. Several different designs Single watershed (data for modeling) Nested (evaluate accumulated effects) Paired (cause and effect) Watershed studies were important for detection of environmental problems such as acid rain and climate change.

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Watershed Experiments

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  1. Watershed Experiments Lab 3

  2. Watersheds • Several different designs • Single watershed (data for modeling) • Nested (evaluate accumulated effects) • Paired (cause and effect) • Watershed studies were important for detection of environmental problems such as acid rain and climate change. • Very Expensive and difficult to do process research • Look at long-term trends, cumulative-impacts, and develop models with data. • Most of our knowledge on the impact of land use on watershed scale processes are from paired watersheds. Processes include: • Runoff volume (water yield) • Peak Flows (flooding) • Sediment Yield • Other water quality parameters (N, P, K, etc.)

  3. Watersheds • Nested Design • Can Evaluate: • Scale effects • Hillslope to channel • Spatial processes • Cumulative impacts Walnut Gulch Experiment Watershed

  4. Paired Watershed • Watersheds should be similar (geology, soils, terrain, vegetation, etc.) • Need to develop a relationship between watersheds before treatment (i.e pre-treatment) • You need to collect data for years before the treatment is implemented. • This is an experiment in an uncontrolled environment. • Potential disturbance can disrupt the experiment.

  5. H.J. Andrews Experimental ForestOregon, USA

  6. Paired Watersheds • Multi-factorial experiment is where more then one factor varies over time. • To understand the relationship between response and treatment we must take measures over different levels of all the factors. In our case we are looking at response over a series (i.e. years) of environment conditions (e.g. climate). • Develop relationships for two time periods, pre-treatment and post-treatment. Test to see if they are statistically difference.

  7. Statistical Test • We will develop two regression model for pre- and post-treatment time periods where: • SFF-pre = a1 + b1 * SFD-pre • SFF-post = a2 + b2 * SFD-post • SF = Annual Streamflow (inches) • F = Watershed F • D = Watershed D • We will test to see in the equation coefficients are equal where the HO: a1=a2 and b1=b2. • If one of the tests is rejected the equations are not equal which indicates we may have a treatment effect. • Watershed D is the Control watershed and Watershed F is the Treated watershed. Watershed F was treated with herbicides to kill deep-rooted shrubs and was converted to grass.

  8. Statistical Tests b1≠ b2 a1 ≠ a2 Post Post Watershed F Pre Pre Watershed D Watershed D

  9. Water Yield Increase • If there is a treatment effect that the Increase in water yield can be computed as: • WYI = SFf-post – [a1+b1*SFd-post]

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