Coupled and collaborative optimization model of impervious surfaces and drainage systems from the flooding mitigation perspective for urban renewal.

Urban pluvial flooding mitigation is a significant challenge in city development. Many mature methods have been used to reduce the risk of flood. The optimal design of impervious surfaces (ODIS) is an adaptive solution to urban flooding from the perspective of urban renewal planning. However, existing ODIS models are limited because they do not consider the drainage systems. To address this issue, this study proposes an elastic and controllable optimization model based on assumptions about rainstorm and drainage capacity, nondominated sorting genetic algorithm-II (NSGA-II), multivariate linear programming (MLP) and soil conservation service curve number model (SCS-CN) in a case study of the old town of Guangzhou city, China. The model not only coupled the drainage systems, but also collaboratively optimized the impervious surfaces and the drainage systems. The results show that the proposed model achieved an optimized efficiency of 5.70 %, which is more than a tenfold improvement compared to existing ODIS models. The study emphasizes that the optimization of the drainage system should be the focus and the optimization of impervious surfaces should be supplementary, and different flood risk areas require different optimization strategies. Furthermore, transforming impervious surfaces into a "high-low-high" spatial distribution of impervious surface densities is the optimal design solution for impervious surfaces. In general, this study offers a novel perspective and approach to urban flooding mitigation, enabling comprehensive control of flooding from a global perspective.

Vegetation dynamics and their relationships with climatic factors in the "Golden Triangle" region.

The "Golden Triangle" is located on the border between Myanmar, Laos, and Thailand, and slash-and-burn cultivation is an ancient and typical land type in this region. With the development of the "The Belt and Road" strategy of China and the climate change, the vegetation information is bound to change intensively under the combined influence of alternative plantation projects and economic policies. Here we used MOD13Q1-normalized differential vegetation index (NDVI) and meteorological data to analyze the variation of vegetation coverage and its correlation with climatic factors (temperature and precipitation) during the period of 2000-2018 by using trend analysis, stability analysis, and partial correlation analysis. The results showed that the overall vegetation coverage of this region exerted the trend of improvement and became more stable over time. Spatially, the agglomeration degree became weaker as time goes during 2000-2018. The precipitation was more closely correlated with NDVI than temperature, indicating that precipitation could be the main limiting factor influencing vegetation change in this area. The correlation between NDVI and climatic factors exhibited differences among different seasons, with NDVI being less correlated with temperature and precipitation in spring and summer and more correlated with them in autumn and winter. Investigating the long-term vegetation coverage of this region and analyzing the trend of climate change is beneficial to understand the development trend of the ecological environment and resource potential in this region. Simultaneously, it can provide a favorable ecological evaluation for The Belt and Road strategy and provide important scientific suggestions and guidance for the sustainable development of ecosystems and human society under the drastic environmental changes.