Stream Temperature Pattern and Process in the Trask Watershed Study: Pre Harvest

Transcription

1 Stream Temperature Pattern and Process in the Trask Watershed Study: Pre Harvest Maryanne Reiter, Weyerhaeuser NR Company Sherri Johnson, USFS Pacific Northwest Research Station Peter James, Weyerhaeuser NR Company Presented at the April 2013 Watersheds Research Cooperative Conference, Corvallis, OR Photo by Kelly James All photos by Kelly James

2 Introduction Outline Provide landscape context of climatic variability in the Trask Watershed Study Area Examine temperature variability within the watershed Explore ways to account for variability in the treated watersheds Based on what we learned preharvest, what do we expect postharvest?

3 Introduction Thermal Process Scales Landscape: Latitude, continentality, altitude, orientation and exposure to regional circulation patterns. Watershed: Elevation, aspect, cover (albedo), sun angle and streamflow (volume, depth and timing). Reach: Canopy characteristics, aspect, gradient, stream width, streamflow generation mechanisms (e.g., springs)

4 Landscape Landscape Context of Trask Location, Location, Location

5 Landscape Trask Landscape Context: Sun and Rain DAYMET Ave Ann. Incident Solar Radiation PRISM Ave Annual Precipitation (in) PRISM Climate Group, Oregon State University, created 10 April 2013

6 Landscape Trask Summer Mean Max and Min Temps PRISM Mean July MAX Temp. (C) PRISM Mean July MIN Temp. (C) PRISM Climate Group, Oregon State University, created 10 April 2013

7 Watershed Trask Thermistor Locations

8 Watershed Trask Mean Maximum July Water Temperature Trask Watershed Mean JULY MAX Water Temp (C) 95% CI for the Mean JULY Mean Monthly MAX GUS Gus2 Gus1 Gus4 Gus3 Ph2 Ph1 Ph3 Ph4 POTHOLE RK1 RK3 RK2 ROCK RK4 UM2 UM1 UM3 UPPER MAIN ZTRASK 7

9 Watershed Trask Elevations Elevation is frequently used as a proxy to represent complex environmental gradients including: temperature, atmospheric moisture, winds, precipitation, incoming solar radiation, and air density. All these factors are important drivers of climate and ultimately stream temperature.

10 Watershed Elevation Variability with Climate Mean July Max for a Warm Year (2009) and Cool Year (2011) vs Elevation (m) Mean July 2011 MAX (cool year) Large Med Small Mean July MAX (C) adj. r-square=0.542, p< adj. r-square= 0.263, p=0.004 Mean July 2009 MAX (warm year) Elevation LDEM (m)

11 Watershed Longitudinal Behavior of Stream Temperature Conceptual behavior of stream temperature in the downstream direction Upstream temperature is controlling Upstream temperature + weather is controlling Weather is controlling T e Temperature T 0 Distance downstream Distance downstream is also proxy for changes in elevation and drainage area Modified from Mohseni and Stefan (1999)

12 Watershed Longitudinal Behavior of Trask Temperature Beaver dams Mean July 2011 MAX vs Distance Downstream for Mainstem Sites (m) Mean July 2011 MAX Distance downstream (m)

13 Watershed Aspect Variability

14 Watershed Trask Aspect Example Small Watershed Stream Temperature Aspect Example 2011 Daily Max Temp (C) Variable RK MA X DAY C GUS MAX DA Y C UM MAX DA Y C Jun 1-Jul 1-Aug Month/day 1-Sep 1-Oct There was not a consistent aspect signal in the small watersheds

15 Watershed Geomorphic Variability

16 Watershed Geomorphic Example: Earthflows Geomorph: PH1 and PH Mean Daily Well Stg Change (mm) from June 1 0 PH2 Mean Daily Well Stage Change (mm) Jun Variable PH1 Delta Well Stg from June 1 PH3 Delta Well Stg from June 1 1-Jul 1-Aug Month/day 1-Sep 1-Oct Geomorph: PH1 and PH MAX Daily Temp (C) PH3 Max Daily Temp (C) Variable PH MA X DAY C PH MA X DAY C 1-Jun 1-Jul 1-Aug Month/day 1-Sep 1-Oct

17 Watershed And Then There is Temporal Variability JULY Mean Monthly MAX Through Time Bars are One Standard Error from the Mean 14 Main Sub JULY Mean Monthly MAX (C) Year

18 Watershed What Can We Learn From Temporal Variability? Mean July 2009 MAX (warm year) Trask Mean July MAX Warm Year (2009) vs a Cool Year (2011) Mean July 2009 MAX = Mean July 2011 MAX Mean July 2011 MAX (cool year) S R-Sq 90.2% R-Sq(adj) 89.8% We used mean July maximum stream temperature data from a cool year (2011) to predict warm year temperatures (2009). Residuals Resdiuals from Regression Predicting Warm Yr Temps with Cool Yr Temps Warmer than predicted Cooler than predicted GUS-1 GUS-2 GUS-3 GUS-4 GUS-MOUTH PH-1 PH-2 PH-3 PH-4 POTHOLE-CE RK-1 RK-2 RK-3 RK-4 ROCK UM-1 UM-2 UM-3 Upper Main Then took the residuals (this graph only shows the study sites) to see which stream are warmer than would have been predicted (e.g., Gus mouth, UM3) and those that are cooler (Pothole CE, PH2 and PH4). Red are downstream sites and yellow are small watersheds

19 Reach July Mean MAX Temp and Channel Metrics Mean July 2011 MAX Water Temp vs Slopes Subshed slope Subshed stream slope JULY 2011 MMAX WT m above Thermistor Slope Thermistor reach slope

20 Reach Small Watershed Stream Flow and Temperature Small Watershed Summer Flow (l/s) and Stream Temperature (C) Mean Monthly Max Water Temperature (C) Small Watershed Summer Flow (m/s) (l/s) June 2011 Mean Max Aug 2011 Mean Max Sept 2011 Mean Max Mean JULY 2010 MAX Mean SEPT 2010 MAX We did not find a strong connection between streamflow and stream temperature when we examined individual small streams. This may be due to the fact that the flows are extremely low with some streams barely flowing.

21 Treatment Effects Harvest Treatments Clearcut harvest with buffer Clearcut harvest with leave tree retention Clearcut harvest with no leave trees Thinning with buffer

22 Treatment Effects What do we Expect to Change? Timber harvest can effect the microclimate of a site by removing the canopy. Harvest can reduce shade which can increase radiative heat flux into the water and also indirectly increase air temperature above the water. Removing trees also reduces wind sheltering which can cause increased wind speeds and increased convective and evaporative cooling. For those sites that show response prior to harvest to air temperature and wind, we would expect them to show more of a response following harvest.

23 Treatment Effects Predicting Effects: Climatic Sensitivity PH1 and PH2 Mean Monthly MAX Water Temp and NWS Mean Max Air Temp (C) Examples of small watershed responses to wind speed (sheltering) and air temperature (proxy for shading). We would expect sites such as PH1 to be more sensitive to changes in shading and sheltering since it was sensitive prior to harvest. PH2 appears less thermally sensitive. PH1 and PH2 Mean Monthly MAX Temps (C) PH1 and PH2 Mean Monthly MAX Temps (C) PH1 and PH2 Mean Monthly MAX Water Temp and NWS Mean Max Wind Speed (m/s) Variable PH1 Mean Max PH2 Mean Max No. Climate Station Mean Monthly Air Temp (C) Variable PH1 Mean Max PH2 Mean Max No. Climate Station mean monthly max wind speed (m/sec)

24 Analysis Accounting for Variability 13 UM3 Mean Monthly MAX temp (C) vs UM1 and RK UM3 Mean Max Reference Mean Monthly MAX WT (C) Variable UM1 Mean Max RK3 Mean Max UM3 example.. proximity does not confer process Reference Watersheds Treatment Watersheds Variable GUS2 GUS3 GUS4 PH1 PH2 PH4 UM2 UM3 GUS PH RK RK RK RK UM Red number is correlation to reference subbasin in cluster, black bold number is where correlation of other reference sites are higher than the cluster site

25 Summary Trask Temperature Patterns The Trask Watershed Study summer stream temperatures, especially in the small streams, are highly variable. This variability can only partially be explained by watershed parameters such as elevation and aspect due to complex environmental parameters that govern local temperature sensitivity. Even though temperature varies throughout the Trask there are ways to account for the variability. In attempting to understand the drivers of pre harvest thermal patterns, we can, at least conceptually, anticipate the response of small streams to harvest.

26 Summary (cont.) Link to the Biology Since there are a multitude of temperature metrics, how we analyze the data will ultimately depend on the objectives. Riparian vegetation Light Leaf litter, Detrital matter Birds Temperature Invertebrates Geomorphology Hydrology Nutrient availability Turbidity, Sus. sediment Primary producers (algae, diatoms) Amphibians Fish