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Changes in the timing of snowmelt and the seasonality of nutrient loading: can models simulate the impacts on freshwater trophic status?
Author(s) -
Pierson Donald C.,
Samal Nihar R.,
Owens Emmet M.,
Schneiderman Elliot M.,
Zion Mark S.
Publication year - 2013
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.9894
Subject(s) - environmental science , snowmelt , nutrient , seasonality , phytoplankton , trophic level , surface runoff , hydrology (agriculture) , water quality , biomass (ecology) , atmospheric sciences , ecology , biology , geotechnical engineering , engineering , geology
The New York City water supply region, located in the Catskill Mountains in upstate New York, has always had a historically variable snow cover, with consequent effects on the magnitude of spring runoff and the relative importance of winter versus spring periods on annual hydrologic and nutrient budgets. Simulations show that under present conditions (1966–2005), on average 38% (12%–70%) of the annual total dissolved phosphorus load occurs during winter (Nov–Feb), while future predictions (2046–2065 and 2081–2100) show winter nutrient loads may account for an average of 46% (18%–73%) of the annual load. It is expected that changes in the importance of winter nutrient loading will lead to some increase in phytoplankton growth under isothermal conditions prior to the onset of thermal stratification, a reduced bloom coinciding with the onset of thermal stratification, and on an annual basis somewhat lower levels of biomass. However, future climate simulations using two different one‐dimensional reservoir water quality models show no strong relationship between changes in algal biomass and the proportion of winter nutrient loading. The lack of a winter response calls into question model assumptions concerning the growth potential of phytoplankton under deeply mixed low light conditions, as well as factors influencing the bioavailability of nutrients input during the winter period. This illustrates the pitfalls of simulating future climate conditions, when the seasonality of model drivers has changed, and processes regulating winter conditions are not strongly represented. Copyright © 2013 John Wiley & Sons, Ltd.