Process-based simulation library SALMO-OO for lake ecosystems

Over the past three decades numerous lake ecosystem models incorporating algal population dynamics have been developed and published. However, most of these models have been constructed, calibrated and validated ad hoc to suit one specific lake application. Even though many models, including SALMO (Recknagel and Benndorf, 1982), were designed and validated as being generic for a range of lake properties they were always rigid in their process equations and parameter values. This paper discusses the concept, implementation and testing of SALMO-OO towards a more generic simulation library for lakes by taking advantage of object-oriented design and Java programming. A library of four process models for phytoplankton growth have been implemented in SALMO-OO, with one growth model from the library presented here as a case study to demonstrate its increased generality and flexibility for simulations of lakes with different trophic states. The initial focus was on phytoplankton models that were of the form of ordinary differential equations (ODEs). The phytoplankton growth models were selected from the literature where different combinations of growth equations and classical growth-limiting functions regarding nutrients, light and water temperature were applied. Those models that displayed a similar model rationale to the original SALMO were implemented in the full object-oriented version of the model (SALMO-OO). Combinations of different growth functions were tested within the simulation library. The validation of SALMO-OO was based on comparisons of calculated and measured algal biomass data of two lakes with meso- and hypereutrophic conditions. The results show that the SALMO-OO model can effectively simulate eutrophic systems very well, and improvements made to parameter values produced significantly improved results, compared to the original SALMO model. The SALMO-OO model does struggle to describe mesotrophic conditions, however the application of a growth model from the simulation library greatly improved this result. Another area of concern with the original model was that the algal functional groups simulated did not fully reflect the typical seasonality observed in eutrophic or mesotrophic systems. Significant improvements were made to the original SALMO model by adopting the more realistic parameter values from the algal growth model of Hongping and Jianyi (2002) whilst retaining the same structure. Experiments with the new parameter values from this growth model improved simulation results of SALMO-OO for the algal groups: blue-green algae, green algae and diatoms. Five parameter values were adopted from Hongping and Jianyi (2002), the most notable were the maximum growth rate (PHOTXMAX), half-saturation constant for P uptake (KP) and the preference factor (PF) values for zooplankton grazing. The original SALMO model was developed as a generic model and the new SALMO-OO model aims to strengthen this attribute. By improving the original model through the simulation library, SALMO-OO gained more flexibility for the simulation of a broad range of lakes with different trophic states, which demonstrates its generality. In addition to the algal growth models, a simulation library for algal grazing is currently being tested. This will further strengthen the flexibility and generality of SALMO-OO. Also a multiple parameter optimisation based on evolutionary algorithms will be integrated in SALMO-OO. This will calibrate parameter values within their range of variance to improve the accuracy of simulation results. It is concluded that the object-oriented implementation of ODE based ecosystem models significantly improves its knowledge base, functionality and accuracy