Peking University has organized the earliest research group on environmental planning in China. Since 1980s, four categories of models have been proposed, covering environmental evaluation, simulation, optimization, and integrated simulation-optimization models . The group has conducted over 60 case studies across the country at both national and regional scales , among which some are the first ones in China. The proposed models have effectively supported the national-level decision-making on environmental protection and regional sustainable development.
The main technical innovations are highlighted as follows:
(1) Integrated Evaluation and Simulation Model at the Regional and Watershed ScaleWe have proposed an integrated model for evaluation and simulation of regional (watershed) environmental system. It can simulate and forecast the complex “Society-Economy-Environment” system, providing quantitative decision-making supporting. Some uncertainty-based parameter estimation methods, such as Bayesian inference, have been developed for efficient water and air quality modeling. The models have been applied in a wide range of case studies, i.e. Lake Dianchi, Beijing urban area and River Liaohe.
(2) Uncertainty-based Optimization Algorithms
The civil and environmental decision-making processes are plagued with uncertain, vague, and incomplete information. Since 1990s, we have developed a series of uncertainty-based optimization algorithms, including single- and multi-objective ones. Our recent studies proposed a risk explicit Interval linear programming (REILP) algorithm to overcome the limitations of existing interval linear programming approaches. The modeling results showed that REILP can efficiently explore the interval uncertainty space and generate an optimal decision front that directly reflects the tradeoff between decision risks and system return. Therefore it allows decision makers to make effective decision based on the risk-reward information generated by the REILP modeling analysis.
(3) Integrated Simulation-Optimization Modeling Algorithms
The Nonlinearity Interval Mapping Scheme (NIMS) was developed for efficient environmental decision making. The NIMS can not only effectively demonstrate the uncertainty and nonlinearity characteristics of environmental system, but also effectively realize the optimization of planning scheme. Our case studies of waste load allocation analysis in some U.S. and China watersheds demonstrated that the NIMS has a higher computational efficiency than the current algorithms without prejudice to accuracy and can provide feasible ways to solve the large-scale environmental planning issues.