Long-Term Regional Environmental Risk Assessment and Future Scenario Projection at Ningbo, China Coupling the Impact of Sea Level Rise

Abstract

Regional environmental risk (RER) denotes potential threats to the natural environment, human health and socioeconomic development caused by specific risks. It is valuable to assess long-term RER in coastal areas with the increasing effects of global change. We proposed a new approach to assess coastal RER considering spatial factors using principal component analysis (PCA) and used a future land use simulation (FLUS) model to project future RER scenarios considering the impact of sea level rise (SLR). In our study, the RER status was classified in five levels as highest, high, medium, low and lowest. We evaluated the 30 m × 30 m gridded spatial pattern of the long-term RER at Ningbo of China by assessing its 1975-2015 history and projecting this to 2020-2050. Our results show that RER at Ningbo has increased substantially over the past 40 years and will slowly increase over the next 35 years. Ningbo's city center and district centers are exposed to medium-to-highest RER, while the suburban areas are exposed to lowest-to-medium lower RER. Storm surges will lead to strong RER increases along the Ningbo coast, with the low-lying northern coast being more affected than the mountainous southern coast. RER at Ningbo is affected principally by the combined effects of increased human activity, rapid population growth, rapid industrialization, and unprecedented urbanization. This study provides early warnings to support practical regulation for disaster mitigation and environmental protection.

Spatially-explicit prediction of low-density peri-urban development: comparison between urban and rural scenarios in the Moreton Bay Region in South East Queensland, Australia

“…The systematic sampling method ensures that all cells sampled were evenly distributed in the entire study region; it has been applied in existing CA modelling work to reduce the computational workload (e.g. Feng and Liu, 2013; Feng et al, 2019; Wu, 2002), and the samples were then used to retrieve the CA parameters and build the CA model. The calibration process of the modelling commenced with input of land use data from 1991, nine driving factors and constraints, with each iteration representing 1 year, and stops after 20 iterations to 2011.…”

Production–Living–Ecological Conflict Identification Using a Multiscale Integration Model Based on Spatial Suitability Analysis and Sustainable Development Evaluation: A Case Study of Ningbo, China

“…Regional environmental risk at Ningbo has increased substantially over the past 40 years and will increase over the next several decades with the increasing demands of economic and social development on territorial space resources. The resource bottlenecks and environmental pressure are becoming increasingly prominent, and the contradiction between the supply and demand of land space resources is becoming progressively obvious [19][20][21]. Ningbo has attracted attention from environmentalists, local authorities, and scientists.…”