Academic literature on the topic 'SALMO-OO'

Object - oriented ecosystem modelling was introduced in the early of 1990s ( Silvert, 1992 ). From that time on, ecosystem models using object - oriented programming ( OOP ) has earned significant achievements with increasing upgraded information technology. The common purposes of ecosystem modellers are to build a model with flexible structure, which allow continuous modifications on the model content. In last decade, ecosystem modellers have put a large number of efforts to practice the OOP approaches in order to implement a true object - oriented ecosystem model. However, these previous work have not fully take advantage of object - orientation because of misusing more or less this technique. This paper explains the shortcoming of these previous endeavours therewith points out a practical solution that using the methodology of object - oriented software engineering and some relative novel information techniques. A case study SALMO - OO will be presented in this paper to prove Silvert ' s assumption that OOP play an important role on ecosystem modelling approaches. Moreover, the results of SALMO - OO convince that object - oriented ecosystem modelling can be achieved by using object - oriented software engineering associating with a true object - oriented programming language ( Java in this case ).
Thesis (M.Sc.)--School of Earth and Environmental Sciences, 2006.

Object - oriented ecosystem modelling was introduced in the early of 1990s ( Silvert, 1992 ). From that time on, ecosystem models using object - oriented programming ( OOP ) has earned significant achievements with increasing upgraded information technology. The common purposes of ecosystem modellers are to build a model with flexible structure, which allow continuous modifications on the model content. In last decade, ecosystem modellers have put a large number of efforts to practice the OOP approaches in order to implement a true object - oriented ecosystem model. However, these previous work have not fully take advantage of object - orientation because of misusing more or less this technique. This paper explains the shortcoming of these previous endeavours therewith points out a practical solution that using the methodology of object - oriented software engineering and some relative novel information techniques. A case study SALMO - OO will be presented in this paper to prove Silvert ' s assumption that OOP play an important role on ecosystem modelling approaches. Moreover, the results of SALMO - OO convince that object - oriented ecosystem modelling can be achieved by using object - oriented software engineering associating with a true object - oriented programming language ( Java in this case ).
Thesis (M.Sc.)--School of Earth and Environmental Sciences, 2006.

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 (Benndorf and Recknagel, 1982; 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 study 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 three phytoplankton growth and three grazing process models have been implemented in SALMO-OO, with the aim to increase the generality and flexibility of SALMO-OO for simulations of lakes with different trophic states and mixing conditions. The initial focus was on phytoplankton models that were of the form of ordinary differential equations (ODEs) that displayed a similar model rationale to the original SALMO model. Three phytoplankton growth and three grazing models implemented in the full object-oriented version of the model (SALMO-OO) as a simulation library of alternative process models. Combinations of different growth and grazing functions were tested within the simulation library to find generic model structures for lakes with different trophic state and mixing conditions. The validation of the SALMO-OO simulation library was based on comparison between the simulation library experiments and the results produced by the original SALMO-OO growth and grazing functions for phytoplankton biomass, zooplankton biomass, phosphate concentration and algal functional groups abundances. Root-mean square error (RMSE) and r2 values are given as a quantitative measure of fit between the measured data and the model outputs for each state variable. The results demonstrate the ability of the SALMO-OO model to simulate a variety of trophic and mixing conditions for freshwater lakes using a generic approach, and the ability of the simulation library to improve the validation results for each lake simulated. Generic model structures were found for different categories of lakes based on trophic state (eu-/hyper-, meso- and oligotrophic) and mixing conditions (dimictic and warm monomictic). A key factor that has determined a particular generic model structure has been the realistic simulation of phytoplankton functional groups dynamics. By providing the simulation library as an additional validation toolbox this has improved the overall model performance to give more accurate and realistic results for phytoplankton dynamics. As a result, the SALMO-OO model is a more comprehensive decision support tool for lake and reservoir management, which can be used to support the ranking of management scenarios and to base decisions on understanding and expert knowledge. Future research for the SALMO-OO simulation library includes the integration of a multiple parameter optimisation option based on evolutionary algorithms. 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.
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Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Sciences, 2007

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 (Benndorf and Recknagel, 1982; 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 study 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 three phytoplankton growth and three grazing process models have been implemented in SALMO-OO, with the aim to increase the generality and flexibility of SALMO-OO for simulations of lakes with different trophic states and mixing conditions. The initial focus was on phytoplankton models that were of the form of ordinary differential equations (ODEs) that displayed a similar model rationale to the original SALMO model. Three phytoplankton growth and three grazing models implemented in the full object-oriented version of the model (SALMO-OO) as a simulation library of alternative process models. Combinations of different growth and grazing functions were tested within the simulation library to find generic model structures for lakes with different trophic state and mixing conditions. The validation of the SALMO-OO simulation library was based on comparison between the simulation library experiments and the results produced by the original SALMO-OO growth and grazing functions for phytoplankton biomass, zooplankton biomass, phosphate concentration and algal functional groups abundances. Root-mean square error (RMSE) and r2 values are given as a quantitative measure of fit between the measured data and the model outputs for each state variable. The results demonstrate the ability of the SALMO-OO model to simulate a variety of trophic and mixing conditions for freshwater lakes using a generic approach, and the ability of the simulation library to improve the validation results for each lake simulated. Generic model structures were found for different categories of lakes based on trophic state (eu-/hyper-, meso- and oligotrophic) and mixing conditions (dimictic and warm monomictic). A key factor that has determined a particular generic model structure has been the realistic simulation of phytoplankton functional groups dynamics. By providing the simulation library as an additional validation toolbox this has improved the overall model performance to give more accurate and realistic results for phytoplankton dynamics. As a result, the SALMO-OO model is a more comprehensive decision support tool for lake and reservoir management, which can be used to support the ranking of management scenarios and to base decisions on understanding and expert knowledge. Future research for the SALMO-OO simulation library includes the integration of a multiple parameter optimisation option based on evolutionary algorithms. 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.
Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Sciences, 2007

My original contribution to knowledge is the successful application of two modelling paradigms 1) SALMO-PLUS process based model and 2) HEA data driven model to tropical lakes of different morphometry and trophic status. The application of SALMO-PLUS to tropical lakes involves utilising the SALMO-OO model structure for optimisation. This was followed by multi objective parameter optimisation on selected parameters to seek the optimum parameter values that can model the algal dynamics and state variables fluctuations in the tropical lakes to an acceptable magnitude and peaks. SALMO-PLUS is another version SALMO-OO with capability to run optimisation by means of particle swarm optimisation (PSO) method. SALMO-OO has been used as a research tool over a number of lakes with different trophic states and mixing conditions to simulate algal succession and respond to ecosystem dynamic. SALMO-OO is driven by process-based differential equations and works by utilizing a library of three phytoplankton growth and three grazing process models. Evolutionary algorithms (EA) are bio-inspired adaptive methods which mimic processes of biological evolution, natural selection and genetic variation such as cross-over and mutation to develop solutions to complex computational problems (Recknagel et al, 2006). HEA is designed for rule discovery in water quality timeseries (Cao et al., 2006b) and is capable of forecasting potential algal population dynamics and outbreaks in water bodies. The SALMO-PLUS model was applied for simulating the state variables of selected lakes (Lake Kenyir, Lake Penang, Saidenbach Reservoir, Roodeplaat Dam and South Para Reservoir). Measured data from the year 2005 and 1992 were used for Lake Penang and Lake Kenyir respectively. The HEA was applied for predicting the Chl-a and algal biovolume abundance on tropical lakes (Lake Putrajaya, Lake Penang and Lake Kenyir) in Malaysia. This study discusses the application of SALMO-PLUS and HEA towards tropical lakes eutrophication management. The results of application of SALMO-PLUS on tropical lakes are presented, simulating response of the phytoplankton community to fluctuation in nutrient loading, light availability and hydrological aspect in the water bodies. Results of applying HEA on tropical lakes are also interpreted in the context of empirical and causal knowledge on Chl-a and algal biovolumes dynamics under tropical lake water quality conditions by means of rule-based model. Results for both Lake Kenyir and Penang showed that SALMO-PLUS were able to predict annual average trends not only for chlorophyll-a but also other state variables and algal functional groups. Simulated state variables namely Chl-a, N and P showed good agreement with field observations data for both lakes. Despite the fact that this is the first time SALMO-PLUS been used for tropical lakes and the limited data availability from this region, the simulated values of biological and nutrient state variables match reasonably with measured data. Outcomes from SALMO-PLUS simulation show consistent compliance with algal community assembly obtained from other researchers. The HEA achieved reasonable accuracy in predicting timing and magnitudes of algal blooms up to 7-days-ahead. The HEA proved to be most efficient in modelling and predicting seasonal dynamics of chlorophyll-a and algal biovolumes. A sensitivity analysis conducted for Lake Penang revealed that algal abundance is not only driven by physical and chemicals characteristics of the water body but also by impact of inorganic substances in the water that contributes to high level of chemical oxygen demand in the water as well. In addition, this study has successfully implemented a new process model from Law et al. (2009) consisting algal growth, algal grazing, zooplankton growth and zooplankton mortality functions into the SALMO-OO simulation library. Combination of this new process models were tested on dataset from Lake Kenyir, Lake Penang, Saidenbach Reservoir and Roodeplaat Dam within the simulation library to discover the optimal model structures for respective water bodies. Even though the new process model was not selected in complete totality as the optimal model structure for any of the test lakes, the addition has added another alternative for water body simulation in SALMO-OO process library. Based on these forecasting results, both SALMO-PLUS and HEA have showed potential for utilisation in early warning and strategic control of algal blooms in tropical freshwater lakes. The generic nature of HEA forecast model was also observed when tested for forecasting algal biovolume for merged data of similar lake ecosystem category. Results from merged Lake Kenyir and Lake Penang data showed reasonable accuracy in predicting the timing and magnitudes of algal blooms up to 7-days-ahead. Addition of the new process model from Law et al. (2009) into the SALMO-PLUS simulation library has also expanded the alternative for lake category simulation to give a more comprehensive decision support tool for lake and reservoir management. This study has also affirmed the generality and flexibility of SALMO-PLUS for usage in tropical lakes modelling. SALMO-PLUS was observed to be capable of simulating simultaneous seasonal fluctuations in algal growth and nutrients (phosphate and nitrate) making it valuable for forecasting the impacts of various simulated scenarios for various lake management regimes.
Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Sciences, 2012