Extreme daily loads: role in annual phosphorus input to a north temperate lake
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Changes in fertilizer use, manure management or precipitation may alter the frequency of episodes of high nutrient runoff and thereby affect annual nutrient loads and total nutrient concentrations of lakes. We developed an empirical, stochastic model for daily P loads and used the model to project annual P loads and summer total P concentrations in Lake Mendota, Wisconsin, USA. Daily P loads (8,250 daily observations) were fit closely by a three-part gamma distribution composed of days with low, intermediate, and high P loads. High P load days happen when heavy rains or snowmelt occur on soil with abundant P, often as a result of manure or inorganic fertilizer application. In Lake Mendota, on average 29 days per year accounted for 74 % of the annual load. Simulations showed that median annual P loads increased linearly with the frequency of high P load days. However, the upper quantiles of the annual P load distribution increased more steeply than the median. Increases in the number of high P load days per year also increased summer concentrations of P in the lake. Thus increases in the frequency of high P load days due to larger precipitation events or increased application of fertilizers and manure may worsen widespread problems caused by P pollution of lakes in this agricultural watershed.
KeywordsDaily load extremes Lake Phosphorus load Water quality
This research was supported by NSF through the Water Sustainability and Climate program (Grant #DEB-1038759) and the North Temperate Lakes LTER site, and by the Wisconsin Department of Natural Resources.
- Carpenter SR, Lathrop RC, Nowak P, Bennett EM, Reed T, Soranno PA (2006) The ongoing experiment: restoration of Lake Mendota and its watershed. In: Magnuson JJ, Kratz TK, Benson BJ (eds) Long-term dynamics of lakes in the landscape. Oxford University Press, LondonGoogle Scholar
- Caspers H (1984) OECD: Eutrophication of Waters. Monitoring, Assessment and Control—154 pp. Paris: Organisation for Economic Co-Operation and Development 1982. (Publié en français sous le titre » Eutrophication des Eaux. Méthodes de Surveillance, d’Evaluation et de Lutte «). Internationale Revue der gesamten Hydrobiologie und Hydrographie 69(2):200. doi: 10.1002/iroh.19840690206
- Eghball B, Gilley JE, Baltensperger DD, Blumenthal JM (2002) Long-term manure and fertilizer application effects on phosphorus and nitrogen in runoff. Trans Am Soc Agric Biol Eng 45:687–694Google Scholar
- Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. Trans Am Soc Agric Biol Eng 50:1211–1250Google Scholar
- Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian data analysis. Chapman and Hall, New YorkGoogle Scholar
- Jennings E, Jones S, Arvola L, Staehr PA, Gaiser E, Jones ID, Weathers KC, Weyhenmeyer GA, Chiu C-Y, De Eyto E (2012) Effects of weather-related episodic events in lakes: an analysis based on high-frequency data. Freshw Biol 57(3):589–601. doi: 10.1111/j.1365-2427.2011.02729.x CrossRefGoogle Scholar
- Lathrop RC, Carpenter SR (1992) Phytoplankton and their relationship to nutrients. In: Kitchell JF (ed) Food web management: a case study of Lake Mendota, Wisconsin. Springer, New York, pp 99–128Google Scholar
- Peterson TC, Zhang X, Brunet-India M, Vazquez-Aguirre JL (2008) Changes in North American extremes derived from daily weather data. J Geophys Res-Atmospheres 113 (D7). doi: 10.1029/2007jd009453
- Pitt R, Voorhees J (2002) SLAMM, the source loading and management model. In: Field R, Sullivan D (eds) Wet-weather flow in the Urban Watershed: technology and mangement. CRC Press, Boca Raton, pp 103–139Google Scholar
- R Development Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar