can the pamolare 1-layer model predict eutrophication in hypertrophic lakes? a case study: the zaribar lake, iran

eutrophication is known as the most common problem in water bodies, caused by high concentrations of different nutrients leading to unbalanced growth of aquatic plants, among other symptoms. hence, the possibility of eutrophication prediction can be beneficial to the sustainable management of these natural resources and create an opportunity to control their trophic conditions over time. a software package applied for generating these predictions is pamolare with its different models (layers). the 1-layer model of this method was selected to investigate the trophic condition of hypertrophic zaribar lake. prior to 1012, water samples were collected from six stations over a seven-year period. during the last year of this period, sediment samples were also collected. the concentrations of n and p were measured in the samples. the initial results showed that the zaribar lake is a hypertrophic water body. applying the pamolare 1-layer model showed that this model was not powerful enough to predict the trophic changes in this hypertrophic water body and suggested that other models should be examined and modified for use in these ecosystems. alternatively, it is necessary to improve the software for the prediction of eutrophication in hypertrophic water bodies.