4.6 Article

Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP-PLUS-InVEST Model and an Applied Case Study in Hangzhou, East China

Journal

LAND
Volume 11, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/land11122213

Keywords

carbon storage; land-use; land-cover change; multiobjective programming; PLUS model; InVEST model; multiple scenario simulation

Funding

  1. National Natural Science Foundation of China [51878593]
  2. Center for Balance Architecture, Zhejiang University [KH-20212946]

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The study found that from 2000 to 2020, artificial surfaces grew significantly, while cultivated land significantly decreased, leading to an overall decrease in carbon storage with local aggregation and sporadic distribution. By 2030, the areas of artificial surfaces, water bodies, and shrubland will continue to increase, while cultivated land and grassland will continue to decrease. The balanced development scenario can effectively achieve ecological protection and economic development objectives, while carbon storage is expected to continue declining with the ecological protection scenario having the highest carbon storage.
Land-use/land-cover change (LUCC) is an important factor affecting carbon storage. It is of great practical significance to quantify the relationship between LUCC and carbon storage for regional ecological protection and sustainable socio-economic development. In this study, we proposed an integrated framework based on multiobjective programming (MOP), the patch-level land-use simulation (PLUS) model, and the integrated valuation of ecosystem service and trade-offs (InVEST) model. First, we used the InVEST model to explore the spatial and temporal evolution characteristics of carbon storage in Hangzhou from 2000 to 2020 using land-cover data. Second, we constructed four scenarios of natural development (ND), economic development (ED), ecological protection (EP), and balanced development (BD) using the Markov chain model and MOP, and then simulated the spatial distribution of land cover in 2030 with the PLUS model. Third, the InVEST model was used to predict carbon storage in 2030. Finally, we conducted a spatial correlation of Hangzhou's carbon storage and delineated carbon storage zoning in Hangzhou. The results showed that: (1) The artificial surfaces grew significantly, while the cultivated land decreased significantly from 2000 to 2020. The overall trend was a decrease in carbon storage, and the changing areas of carbon storage were characterized by local aggregation and sporadic distribution. (2) The areas of artificial surfaces, water bodies, and shrubland will continue to increase up to 2030, while the areas of cultivated land and grassland will continue to decrease. The BD scenario can effectively achieve the multiple objectives of ecological protection and economic development. (3) The carbon storage will continue to decline up to 2030, and the EP scenario will have the highest carbon storage, which will effectively mitigate the carbon storage loss. (4) The spatial distribution of carbon storage in Hangzhou was inextricably linked to the land cover, which was characterized by a high-high concentration and a low-low concentration. The results of the study can provide decision support for the sustainable development of Hangzhou and other cities in the Yangtze River Delta region.

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