ABSTRACT
Climate change and urbanization contribute to the increased frequency of short-duration intense rainstorms. Traditional solutions often involve multiple scenarios for cost-effectiveness comparison, neglecting the rationality of placement conditions. The effective coupling and coordination of the location, number, size, and cost of storage tanks are crucial to addressing this issue. A three-phase approach is proposed to enhance the dynamic link between drainage pipeline and storage tanks in urban high-density built-up areas, integrating Python language, SWMM, the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-III), and the Analytic Hierarchy Process (AHP) methods. In the first stage, each node within the pipeline network is considered as a potential storage tank location. In the second stage, factors such as the length and diameter of the upstream connecting pipeline, as well as the suitability of the storage tank location, are assessed. In the third stage, the length and diameter of the downstream connecting pipeline node are evaluated. The results show that the 90 overflow nodes (overflow time >0.5h) have been cleared using the three-phase approach with a 50a (duration = 3h) return period as the rainfall scenario, which meets the flooding limitations. After the completion of the three-phase method configuration, the total overflow and SS loads were reduced by 96.45% and 49.30%, respectively, compared to the status quo conditions. These two indicators have decreased by 48.16 and 9.05%, respectively, compared to the first phase (the traditional method of only replacing all overflow nodes with storage tanks). The proposed framework enables decision-makers to evaluate the acceptability and reliability of the optimal management plan, taking into account their preferences and uncertainties.
Subject(s)
Floods , Rain , Reproducibility of Results , Computer Simulation , UrbanizationABSTRACT
In order to manage agricultural pathogens, it is crucial to understand the population structure underlying epidemics. Rubber tree powdery mildew, caused by Erysiphe quercicola, is a serious threat to rubber plantations worldwide, especially in subtropical environments including all rubber tree-growing regions in China. However, the population structure of the pathogen is uncertain. In this study, 16 polymorphic microsatellite markers were used to genotype powdery mildew samples from the main rubber tree-growing regions including Yunnan (YN), Hainan (HN), western Guangdong (WG), and eastern Guangdong (EG). YN had higher genotypic diversity (Simpson's indices), genotypic evenness, Nei's gene diversity, allelic richness, and private allelic richness than the other regions. Cluster analysis, discriminant analysis of principal components, pairwise divergence, and shared multilocus genotype analyses all showed that YN differed significantly from the other regions. The genetic differentiation was small among the other three regions (HN, WG, and EG). Analysis of molecular variance indicated that the variability among regions accounted for 22.37% of the total variability. Genetic differentiation was significantly positively correlated (Rxy = 0.772, P = 0.001) with geographic distance. Linkage equilibrium analysis suggested possible occurrence of sexual recombination although asexual reproduction predominates in E. quercicola. The results suggested that although significant genetic differentiation of E. quercicola occurred between YN and the other regions, pathogen populations from the other three regions lacked genetic differentiation.
