Montana State Watershed Lab Montana State University - Bozeman Hydrologic connectivity from...
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Montana State Watershed Lab ntana State University - Bozeman Hydrologic connectivity from hillslope to landscape scales: cations for runoff generation and water qua 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 - RM-4151: Ecology & Management of Northern Rocky Mountain Forests, Tenderfoot Creek Experimental Forest and the USDA, Forest Service, Rocky Mountain Research Station R832449
Montana State Watershed Lab Montana State University - Bozeman Hydrologic connectivity from hillslope to landscape scales: Implications for runoff generation
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
Slide 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
Slide 3
Map area ~ 22 km 2 7 gauged watersheds OBJECTIVES Investigate
hydrologic connectivity over space and time Develop conceptual
model of runoff generationwatershed structure Test ideas in a
developing watershed (Big Sky) applied example Tenderfoot Creek
Experimental Forest
Slide 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
Slide 5
Montana State Watershed Lab Montana State University - Bozeman
0 ha Log 10 40 ha Terrain-based riparian mapping
Topographically-driven redistribution of water
Slide 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)
Slide 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
Slide 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
Slide 9
Date R 2 =0.91 n=24
Slide 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
Slide 11
Montana State Watershed Lab Montana State University - Bozeman
How does upland connectivity relate to streamflow magnitude?
Slide 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 generationwatershed structure
Topographically driven lateral redistribution of water drives
transient upland-stream connectivity and runoff generation Riparian
buffering potential spatially variable Intermediate summary
Slide 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
Slide 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
Slide 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
Slide 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
Slide 17
Montana State Watershed Lab Montana State University - Bozeman
Late summer nitrate Maximum Value 1.31 mg/l Runoff mm/hr Nitrate
mg/l
Slide 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
Slide 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
Slide 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.
Slide 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
Slide 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
Slide 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
Slide 24
Montana State Watershed Lab Montana State University - Bozeman
Extra slides to follow in case there are specific questions
Slide 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.
Slide 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
Slide 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: