The importance of year-to-year variation in meteorological and runoff forcing for water quality of a temperate, dimictic lake

摘要

Natural stochasticity can pose challenges in managing the quality of theenvironment, or hinder understanding of the system structure. It isproblematic because unfavourable stochastic events cancel management effortsand because a favourable stochastic event may overestimate perceived success.This paper presents a variance-based modelling method that can be used toquantify the extent to which natural stochasticity can affect the targetenvironment. We use a case study of a eutrophication assessment of aNorwegian lake, ?rungen, using a lake model, MyLake, in order to presentthe method, and to investigate how this method could assist in answering scientific andmanagement questions. Here we contrasted two effects of nutrient loading inrunoff (partially controllable by policies) and meteorology (purely naturalstochastic events), illustrated in the case study, in order to achieve theseason-by-season quantification of mutually confounding factors of stochasticevents. The results indicate that, for example, variation in runoff volumewas most prevalent during autumn and winter, while variation in phosphorusinflow was most extensive from late winter to early spring. Thermal-relatedproperties in the lake were well predicted by the model, and showed that thetime of thermocline formation varied among years by more than 1 month, frommid-April to mid-May, whereas loading was the most important factor forphytoplankton biomass and water transparency. Mild winters and greater inputsof suspended matter and phosphorus were followed by increased phytoplanktonbiomass and light attenuation. These findings also suggest that futurechanges in the global climate may have important implications for local watermanagement decision-making. The present method of disentangling mutuallyconfounding factors is not limited to lake water quality studies and may alsoprovide utility in other types of aquatic system modelling.