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Temporal and Spatial Variability of Groundwater Nitrate in the Southern Willamette Valley, Oregon. Glenn Mutti & Roy Haggerty Oregon State University Department of Geosciences. Introduction. Overview of previous spatial and temporal studies Sampling Network Results and Implications

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temporal and spatial variability of groundwater nitrate in the southern willamette valley oregon

Temporal and Spatial Variability of Groundwater Nitrate in the Southern Willamette Valley, Oregon

Glenn Mutti & Roy Haggerty

Oregon State University

Department of Geosciences

introduction
Introduction
  • Overview of previous spatial and temporal studies
  • Sampling Network
  • Results and Implications
  • Modeling Nitrogen Dynamics
  • Conclusions
hypothesis
Hypothesis
  • Seasonal precipitation should impact shallow groundwater nitrate concentrations
  • Why should it matter?
    • Distinguish seasonal trends vs. actual trends in monitoring data
    • Determine optimal sampling periods
monitoring network
Monitoring Network
  • 19 wells sampled monthly for 15 months
    • 15 residential wells
    • 4 monitoring wells
  • Well log extant
  • Well Depth ≤ 50 ft
  • Screening Interval ≤ 15 ft
  • Pass Coliform bacteria test
was there seasonal variability
Was there Seasonal Variability?
  • Yes, precipitation influences nitrate values
  • However, seasonal wetting patterns are critical!
wetting up period necessary to have no 3 response
Wetting Up Period Necessary to have NO3- Response
  • Used water levels to indicate when recharge occurred
  • Soil needs to wet up before recharge, then groundwater nitrate values respond to precipitation
sample distributions based on geology and soil

n = 6

n = 6

n = 7

n = 9

n = 10

Sample Distributions Based on Geology and Soil

Qal = Holocene Floodplain and Alluvial Deposits

Qs = Pleistocene Alluvium and Flood Deposits

FSL= Fine Sandy Loam

SCL= Silty Clay Loam

SL= Silt Loam

n = 6

n = 6

n = 6

modeling goals
Modeling Goals
  • Calibrate SWAT so that reasonable outputs are obtained and validated
  • Examine different land management options and their impact on leached nitrate
  • Examine future scenarios and the impacts of nitrate Best Management Practices
non gis model inputs
Non-GIS Model Inputs
  • Climate Data
  • River flows originating from non-modeled areas
  • Land Management Practices
closing points
Closing Points
  • Relationship between NO3- and precipitation may be biased by data set: needs further analysis
  • Data uncertainties have yet to be analyzed
  • Small sample size could limit the significance of results
conclusions
Conclusions
  • Nitrate concentrations in the Southern Willamette Valley are dynamically linked to precipitation during recharge months
  • The recharge month with the highest annual precipitation is likely to have the highest annual groundwater NO3-concentration (but also the highest variability!!)
  • Wells drilled in different geologic formations or soil classes are likely to exhibit different seasonal variabilities
acknowledgements
Acknowledgements:
  • Funding provided by: USGS Small Grants Program, Award No. 01HQGR0145
  • SWAT Development: USDA ARS and Blackland Research Center, Texas A&M University