4.5 Article

Inexpensive spot sampling provides unexpectedly effective indicators of watershed nitrogen status

Journal

ECOSPHERE
Volume 11, Issue 8, Pages -

Publisher

WILEY
DOI: 10.1002/ecs2.3224

Keywords

bootstrapped regression; composite sampling; nitrogen management; nitrogen pollution; stream sampling; synoptic sample; water quality; watershed assessment

Categories

Funding

  1. NSF [BSR-89-05219, DEB-92-06811, DEB-93-17968]
  2. NOAA [NA66RG0129]
  3. Governor's Research Council of Maryland
  4. Government of Charles County Maryland
  5. Smithsonian Institution Environmental Sciences Program

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Stream water quality data are essential for understanding watershed processes and managing water pollution, but the effort and expense of stream monitoring limit how many watersheds can be studied. For 59 small watersheds in the Chesapeake Bay drainage, we compared water quality measurements from inexpensive spot sampling to data from costly automated monitoring that used 1-3 yr of continuous flow measurement and weekly, temporally composited water sampling. Mean nitrogen (N) levels ranged from 0.01 to 16 mg N/L among streams. There were important temporal variations in N concentrations at each site, but the differences among sites were much greater. Spot samples were very effective at accurately and precisely placing average stream N levels within the N gradient among streams draining N-enriched watersheds. Among watersheds, nitrate (NO3) and total N concentrations from spot samples were very strongly correlated with means from weekly composite sampling (R-2 > 97%). We confirmed this result for independent data for 85 larger watersheds in the Chesapeake Bay Non-tidal Network. NO(3)concentration from a single March spot sample was highly correlated (R-2 > 92%) with flow-weighted average total N concentration synthesized from five years of monitoring. Spot sampling effectively quantifies average N status across N-enriched watersheds because most N moves as dissolved NO(3)in subsurface flow and that flux is much less variable than the episodic surface transport of particulate materials. For questions answered by quantifying average N levels, spot sampling can assess more watersheds at much lower cost than automated sampling, so it should be more widely used to support cost-effective N research and management. For materials that are mainly bound to particulates, such as phosphorus, spot sampling is much less effective.

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