L. Shawn Matott

A benchmarking framework for simulation-based optimization of environmental models

Simulation models assist with designing and managing environmental systems. Linking such models with optimization algorithms yields an approach for identifying least-cost solutions while satisfying system constraints. However, selecting the best optimization algorithm for a given problem is non-trivial and the community would benefit from benchmark problems for comparing various alternatives. To this end, we?propose a set of six guidelines for developing effective benchmark problems for simulation-based optimization.The proposed guidelines were used to investigate problems involving sorptive landfill liners for containing and treating hazardous waste. Two solution approaches were applied to these types of problems for the first time - a pre-emptive (i.e. terminating simulations early when appropriate) particle swarm optimizer (PSO), and a hybrid discrete variant of the dynamically dimensioned search algorithm (HD-DDS). Model pre-emption yielded computational savings of up to 70% relative to non-pre-emptive counterparts. Furthermore, HD-DDS often identified globally optimal designs while incurring minimal computational expense, relative to alternative algorithms. Results also highlight the usefulness of organizing decision variables in terms of cost values rather than grouping by material type.

Calibrating Environment Canada's MESH Modelling System over the Great Lakes Basin

Abstract This paper reports on recent progress towards improved predictions of a land surface-hydrological modelling system, Modélisation Environmentale–Surface et Hydrologie (MESH), via its calibration over the Laurentian Great Lakes Basin. Accordingly, a “global” calibration strategy is utilized in which parameters for all land class types are calibrated simultaneously to a number of sub-basins and then validated in time and space. Model performance was evaluated based on four performance metrics, including the Nash-Sutcliffe (NS) coefficient and simulated compared with observed hydrographs. Results from two calibration approaches indicate that in the model validation mode, the global strategy generates better results than an alternative calibration strategy, referred to as the “individual” strategy, in which parameters are calibrated individually to a single sub-basin with a dominant land type and then validated in a different sub-basin with the same dominant land type. The global calibration strategy was relatively successful despite the large number of calibration parameters (51) and relatively small number of model evaluations (1000) used in the automatic calibration procedure. The NS values for spatial validation range from 0.10 to 0.72 with a median of 0.41 for the 15 sub-basins considered. Results also confirm that a careful model calibration and validation is needed before any application of the model.

Modelling Concentrations of Pharmaceuticals and Personal Care Products in a Canadian Watershed

The concentrations of several pharmaceuticals and personal care products (PPCPs) were simulated in the Grand River watershed using the PhATE (Pharmaceutical Assessment and Transport Evaluation) model. PPCPs that were previously measured in the Grand River watershed were selected as the target compounds for this study. The application of the PhATE model was adapted to account for Canadian climatic conditions and its seasonal variability. In this regard, seasonal hydrological parameters (i.e., stream flow and velocity) were estimated based on historical data. Chemical loss parameters, including in-stream decay, human loss, and removal efficiency of treatment plants, were initially extracted from the literature and then calibrated to the site data. In general, the adapted PhATE model reasonably simulated pharmaceuticals with continuous use by humans such as ibuprofen, naproxen, carbamazepine, and gemfibrozil. Validation, which was performed only for ibuprofen, naproxen, and carbamazepine suggests that the calibrated model is able to reliably simulate concentrations. The model is the most accurate in validation when simulating carbamazepine which is the most persistent substance tested in this study, and as such, variations in its concentration primarily follow variation in stream flow.

Parameterizing sorption isotherms using a hybrid global-local fitting procedure

Predictive modeling of the transport and remediation of groundwater contaminants requires an accurate description of the sorption process, which is usually provided by fitting an isotherm model to site-specific laboratory data. Commonly used calibration procedures, listed in order of increasing sophistication, include: trial-and-error, linearization, non-linear regression, global search, and hybrid global-local search. Given the considerable variability in fitting procedures applied in published isotherm studies, we investigated the importance of algorithm selection through a series of numerical experiments involving 13 previously published sorption datasets. These datasets, considered representative of state-of-the-art for isotherm experiments, had been previously analyzed using trial-and-error, linearization, or non-linear regression methods. The isotherm expressions were re-fit using a 3-stage hybrid global-local search procedure (i.e. global search using particle swarm optimization followed by Powells derivative free local search method and Gauss-Marquardt-Levenberg non-linear regression). The re-fitted expressions were then compared to previously published fits in terms of the optimized weighted sum of squared residuals (WSSR) fitness function, the final estimated parameters, and the influence on contaminant transport predictions - where easily computed concentration-dependent contaminant retardation factors served as a surrogate measure of likely transport behavior. Results suggest that many of the previously published calibrated isotherm parameter sets were local minima. In some cases, the updated hybrid global-local search yielded order-of-magnitude reductions in the fitness function. In particular, of the candidate isotherms, the Polanyi-type models were most likely to benefit from the use of the hybrid fitting procedure. In some cases, improvements in fitness function were associated with slight (<10%) changes in parameter values, but in other cases significant (>50%) changes in parameter values were noted. Despite these differences, the influence of isotherm misspecification on contaminant transport predictions was quite variable and difficult to predict from inspection of the isotherms.