Scenario simulation of ecological risk based on land use/cover change under SSP-RCP scenarios : A case study of Xinjiang

Author:

Zhang Yue1,Zhang Kun2,Lv Jing1

Affiliation:

1. Nanjing Normal University

2. China University of Mining and Technology

Abstract

Abstract Taking Xinjiang as the research area, this paper constructed an ecological risk model based on data of Land use/cover Quality Index (LQI), Climate Quality Index (CQI), and Soil Quality Index (SQI) to simulate the ecological risk of Xinjiang and predict it under different scenarios (Shared Socioeconomic Pathways SSPs) at 2100. There are five conclusions drawn:(1) the land use/land cover have changed no obvious from 2020 to 2100. Grassland and farmlands have change the most. Unused land was stable, while forest and water areas have declined significantly. (2) In 2100, after reviewing different scenarios in Xinjiang, it can be seen that the LULCC risk level is dominated by the medium-quality risk level. The areas with medium-quality risk level account for about 70% of the total area of Xinjiang. (3) In 2100, the high-quality climatic and ecological risk areas of different SSPs in Xinjiang are mainly distributed in mountains, desert, and other regions. The medium-quality climatic and ecological risk areas are mainly distributed in the central and eastern regions of Xinjiang. (4) Under different scenarios in 2100, the spatial distribution of ecological risk levels in Xinjiang is mainly dominated by areas with low and medium ecological risk levels, accounting for nearly 70% of the total area. (5) From 2020 to 2100, the ecological risk levels of different scenarios show a decreasing trend in sequence. Typically, from 2020 to SSP370 (2100), most areas change from being at a previous medium ecological risk level to being at a relatively high/high ecological risk level. Under the SSP585 scenario, a large area of areas has changed from the original low ecological risk level to the current high ecological risk level. Only a small area of areas is showing an opposite area change.

Publisher

Research Square Platform LLC

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