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A Coarse-Grained Parallel Genetic Algorithm (CGPGA) is utilized to search for near-optimal solutions for land use allocation optimization problems in the context of multiple objectives and constraints. Plans are obtained based on the trade-off among three spatial objectives including ecological benefit, accessibility and compatibility. The Multi-objective Optimization of Land Use model integrates these objectives with the fitness function assessed by reference point method (goal programming). The CGPGA, as the first coupling in land use allocation optimization problems, is tested through the experiments with one processor, two processors and four processors to pursue near-optimal land use allocation scenarios and the comparison to these experiments based on Generic Genetic Algorithm (GGA), which clearly shows the robustness of the model we proposed as well as its better performance. Furthermore, the successful convergent (near-convergent) case study utilizing the CGPGA in Tongzhou Newtown, Beijing, China evinces the capability and potential of CGPGA in solving land use allocation optimization problems with better efficiency and effectiveness than GGA. [ABSTRACT FROM AUTHOR]

In this research, an integrated simulation-optimization modeling approach (ISOMA) was developed for supporting agricultural N2O emission mitigation at the watershed scale. This approach can successfully combine soil N2O emission simulation and the consequential mitigation management within a general modeling framework. Also, uncertainties associated with the key soil parameter can be effectively reflected and addressed through adoption of Monte Carlo analysis for the simulation results. The Monte Carlo simulated results were then used to generate fuzzy membership functions that can be consequentially used for emission mitigation management, reflecting the combined uncertainties for N2O emission simulation and mitigation management. The developed ISOMA was then applied to a reservoir watershed in Miyun county of Beijing municipality. In the studying watershed, the simulation model was calibrated and verified. Then, N2O emission from multiple agricultural land-use patterns were predicted. The amounts of N2O emission of four land use patterns (i.e., cash tree, orchard, cropland, and natural forest) were (536.9, 590.8, 653.1), (237.7, 254.4, 275.9), (79.5, 100.7, 105.1), (33.0, 47.3, 61.1) kg CO2 eq ha−1 year−1, respectively. Two scenarios (i.e., G1 and G2) were set up according to development priorities of local economy and society. Meanwhile, multiple credibility levels were considered according to the risk of N2O emission. The land use patterns could be adjusted according to solutions of ISOMA. The developed methods could help regional manager choose various production patterns with cost-effective agriculture N2O emission management schemes in the Miyun reservoir watershed. The manager also can obtain deeply insights into the tradeoffs between agricultural benefits and system reliabilities. [ABSTRACT FROM AUTHOR]