1. Montana State Watershed Lab Montana State University - Bozeman Hydrologic connectivity from hillslope to landscape scales: Implications for runoff generation and water quality Brian McGlynn – Montana State University (MSU) Kelsey Jencso, PhD student (MSU) Kristin Gardner, PhD student (MSU) Collaborators Mike Gooseff – Penn State Ken Bencala – USGS, NRP – Menlo Park Steve Wondzell – USFS, Olympia Ward McCaughey – USFS RMS Jan Seibert – Stockholm University, Sweden EAR-0337650 - McGlynn EAR-0337781 - Gooseff RM-4151: Ecology & Management of Northern Rocky Mountain Forests, Tenderfoot Creek Experimental Forest and the USDA, Forest Service, Rocky Mountain Research Station R832449

2. Montana State Watershed Lab Montana State University - Bozeman Does spatial location of change influence watershed response to perturbation? Big Sky, Montana an outdoor laboratory Requires : 1)understanding of hydrologic connectivity across landscape 2)relationships between pattern of change and landscape structure Residences (septic systems) increasing by 100s per year

3. Map area ~ 22 km 2 7 gauged watersheds OBJECTIVES Investigate hydrologic connectivity over space and time Develop conceptual model of runoff generation–watershed structure Test ideas in a developing watershed (Big Sky) – applied example Tenderfoot Creek Experimental Forest

4. Hydrologic instrumentation  24 transects of nested wells and piezometers (140 recording GW wells)  7 flumes with real time specific conductance (SC), temperature, and stage recorders  ALSM 1m topography data  9 water content probe nests across riparian hillslope transitions  >8 rain gauges  4 snowmelt lysimeters  2 SNOTEL sites  2 H 2 O/CO 2 eddy-covariance towers w/ full energy budget instrumentation.  600 m 2 plot w/ intense water content (64 TDR probes) soil and snow temperature (80)  Frequent stream and GW sampling with a focus on solutes, 18 O, D, and DOC Little Belt Mountains, Montana ~850 mm precipitation with ~550 mm ET ~75% as snow 0 degrees C average temperature Soil depths 1-2 meters Elevation range ~500m from 2300m base Highly instrumented USFS nested catchments with a focus on water and carbon research from the plot to multiple watershed scales

5. Montana State Watershed Lab Montana State University - Bozeman 0 ha Log 10 40 ha Terrain-based riparian mapping Topographically-driven redistribution of water

6. Montana State Watershed Lab Montana State University - Bozeman Combining upland drainage and local riparian area along the stream network Hilllsope area accumulation Hillslope area accumulation Upland area accumulation pattern 0 ha Area accumulation 40 ha > area accumulation > water accumulation > increase in streamflow stream Low riparian buffer potential High riparian buffer potential Low to High riparian buffer potential Buffering potential f (riparian area : hillslope area)

7. Montana State Watershed Lab Montana State University - Bozeman Lateral inflows vary along the channel network Riparian buffering potential varies along the channel network Riparian buffering potential frequency Buffering potential

8. Hillslope-riparian-stream hydrologic connectivity South hillslope South riparian 10/64/0710/7 Kelsey Jencso NO CONNECTIVITY North hillslope North riparian Water table elevation m Connectivity

9. Date R 2 =0.91 n=24

10. Montana State Watershed Lab Montana State University - Bozeman Examining watersheds in 4 th dimension (temporal connectivity) Max bar height = 100% Of the year Each side of the stream separated

11. Montana State Watershed Lab Montana State University - Bozeman How does upland connectivity relate to streamflow magnitude?

12. Montana State Watershed Lab Montana State University - Bozeman Obj. 1: Investigate hydrologic connectivity over space and time Obj 2: Develop conceptual model of runoff generation–watershed structure  Topographically driven lateral redistribution of water drives transient upland-stream connectivity and runoff generation  Riparian buffering potential spatially variable Intermediate summary

13. Principles to apply to analysis of landuse change in the Big Sky watershed Hydrologic connectivity Riparian buffering potential  Suggests location of change in watershed could be significant

14. Montana State Watershed Lab Montana State University - Bozeman Does spatial location of change influence watershed response to perturbation? Big Sky, Montana - an outdoor laboratory Resort Residences (septic systems) increasing by 100s per year Sampling locations

15. Montana State Watershed Lab Montana State University - Bozeman Weekly nitrate time series from 4 of 9 watersheds Residences Area km 2 NF = 1 SF = 151 MF = 1690 WF = 1880 NF = 21 SF = 118 MF = 85 WF = 207

16. Montana State Watershed Lab Montana State University - Bozeman Winter nitrate Maximum Value 2.17 mg/l Yellowstone Club – no access - Runoff mm/hr Nitrate mg/l

17. Montana State Watershed Lab Montana State University - Bozeman Late summer nitrate Maximum Value 1.31 mg/l Runoff mm/hr Nitrate mg/l

18. Montana State Watershed Lab Montana State University - Bozeman Stream nitrogen sources  15 N of dissolved N Septic Atmospheric Deposition Geologic sources Natural range Septic impacted Human-derived nitrogen can be tracked with stable isotope analysis Stream samples across Big Sky watershed

19. Flow connected Not flow connected Spatial structure of stream N Synoptic sampling variograms October SeptemberJune March February August SUGGESTS N immobilization in the growing season, leads to complex spatial patterns and a lack of spatial correlation Distinct Seasonality in Spatial Dependence No spatial correlation

20. Montana State Watershed Lab Montana State University - Bozeman Spatial Linear Models Generalized Least Squares Estimation: Potential explanatory variables for stream nitrogen  # septics in subwatershed  # septics weighted by connectivity potential  geology (% shales)  stream order  % forest  riparian buffer potential (riparian area/hillslope area)  elevation  slope  roads  bare rock and talus  aspect  watershed area  and more… Methods: Cressie et al., 2006; Ver Hoef et al., 2006; Peterson et al., 2007.

21. Montana State Watershed Lab Montana State University - Bozeman Seasonal Influences on Streamwater Nitrate Dormant Season # Septics Geology Growing Season Septic connectivity Riparian buffer pot. Geology N loading N processing potential R 2 = 0.9R 2 = 0.45 -0.53

22. Montana State Watershed Lab Montana State University - Bozeman Spatial Data Analysis Conclusions  Seasonality in variograms suggest N immobilization in uplands, riparian areas and stream network break down spatial patterns during growing season.  Spatial linear models indicate seasonality in the influences on streamwater NO 3 - N loading variables significant during dormant season Hydrologic connectivity and riparian buffer potential are significant during growing season Summer Winter

23. Montana State Watershed Lab Montana State University - Bozeman Take home message  Transient connectivity drives runoff generation (source areas change through time)  Watershed structure strong control on runoff generation and riparian buffering potential  Spatial location of change matters and intersection of change pattern and watershed hydrology influences response to perturbation *Gardner, K.K. and B.L. McGlynn. In revision. Spatio-Temporal Controls of Stream Water Nitrogen Export in a Rapidly Developing Watershed in the Northern Rockies. Water Resources Research. *Jencso, K. J., B. L. McGlynn, M. N. Gooseff, S. M. Wondzell, and K. E. Bencala. In revision. Hydrologic Connectivity Between Landscapes and Streams: Transferring Reach and Plot Scale Understanding to the Catchment Scale, Water Resources Research. EAR-0337650 - McGlynn EAR-0337781 - Gooseff R832449

24. Montana State Watershed Lab Montana State University - Bozeman Extra slides to follow in case there are specific questions

25. Montana State Watershed Lab Montana State University - Bozeman Spatial Linear Models 1) Flow Connected vs Flow Unconnected Site B and C are flow-connected Site A and C are flow-connected Site A and B are not flow connected 2) Downstream Flow Distance (DFD) BC = 20 AC = 18 AB = 19 A C B 10 9 [Cressie et al., 2006; Ver Hoef et al., 2006; Peterson et al., 2007.

26. Montana State Watershed Lab Montana State University - Bozeman Spatial Linear Models 3) Proportional Influence of upstream site on downstream site ABC A100 B010 C0.20.81 FROM SITE TO SITE A C B WatershedArea A10 B40 C50

27. Montana State Watershed Lab Montana State University - Bozeman Spatial Linear Models Covariance matrix (  ) is a function of downstream distance (DFD),flow connectedness, and proportional influence.  = parameter estimates X = known explanatory variables z = known dependant variable (NO 3 - ) Generalized Least Squares Estimation: