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1. 昆明理工大学国土资源工程学院,昆明,650093
2. 智慧矿山地理空间信息集成创新重点实验室,昆明,650093
3. 云南省高校自然资源空间信息集成与应用科技创新团队,昆明,650211
Published:2024
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LIU Fengru, ZHAO Junsan, LIN Yilin, et al. Temporal and Spatial Evolution and Driving Force Analysis of Water Conservation [JP] Function in Yunnan Province Based on Climate and Land Use Change[J]. 2024, 38(5): 212-224.
LIU Fengru, ZHAO Junsan, LIN Yilin, et al. Temporal and Spatial Evolution and Driving Force Analysis of Water Conservation [JP] Function in Yunnan Province Based on Climate and Land Use Change[J]. 2024, 38(5): 212-224. DOI: 10.13870/j.cnki.stbcxb.2024.05.033.
[目的] 探讨水源涵养功能是应对未来气候变化的重要途径
现有研究主要侧重于历史和现状的水源涵养功能评估
缺乏对未来水源涵养功能的认识
限制了对区域可持续发展和动态管理的指导价值。[方法] 以云南省为例
结合系统动力学模型、斑块级土地利用变化模拟模型(PLUS模型)和InVEST模型
构建了未来气候和土地利用变化影响下水源涵养评价框架。该框架可在未来气候变化和不同经济发展的背景下预测土地利用变化和评估水源涵养。基于3种共享社会经济路径和典型浓度路径(SSP1-1.9、SSP2-4.5、SSP5-8.5)的耦合情景对云南省水源涵养进行评价
并利用最优参数地理探测器识别云南省水源涵养时空变化的主要驱动因子。[结果] (1)2000—2030年
耕地、未利用地面积整体减少
水域和建设用地面积逐渐增加
林地和草地呈波浪线变化;不同情景的土地利用变化趋势大致相同
表现为草地>建设用地>耕地>未利用地>水域>林地。(2)2000—2020年水源涵养量总体上呈现逐渐减少趋势
减少2.27×109 m3;受不同气候和土地利用模式的影响
不同情景下的水源涵养量有所差异
其中SSP2-4.5情景下的水源涵养量最高
为9.338×109 m3;空间上呈“西南高东北低”的分布格局。(3)地理探测结果表明
年平均降水量、土壤类型、DEM是影响水源涵养时空分布差异的主要驱动因素
且降水量与其他因素交互显著增强。[结论] 研究根据云南省水源涵养时空分异提出不同建议
为云南省生态系统服务研究和可持续发展路线规划提供科学参考。
[Objective] Exploring the water-holding function is an important way to cope with future climate change. Existing research mainly focuses on the assessment of historical and current water-holding function
and lacks the understanding of the future water-holding function
which limits the value of guiding the sustainable development and dynamic management of the region. [Methods] Taking Yunnan Province as an example
this paper combined the system dynamics model
patch-level land use change simulation model (PLUS model)
and InVEST model to build a water conservation evaluation framework under the impact of future climate and land use change. The framework can predict land use change and assess water conservation in the context of future climate change and different economic developments. Water conservation in Yunnan Province was evaluated based on the coupling scenarios of three shared socioeconomic paths and typical concentration paths (SSP1-1.9
SSP2-4.5
SSP5-8.5). The main driving factors of temporal and spatial changes in water conservation in Yunnan Province were identified by using the optimal parameter geodetector. [Results] (1) From 2000 to 2030
the total area of cultivated land and unused land decreased
the area of water area and construction land increased gradually
and the forest land and grassland changed in a wavy line; The trend of land use change in different scenarios is roughly the same
namely: grassland > construction land > cultivated land > unused land > water area > forest land. (2) From 2000 to 2020
water conservation showed a gradually decreasing trend
decreasing by 2.27×109m3; Under the influence of different climate and land use models
the water conservation under different scenarios is different
and the water conservation under the SSP2-4.5 scenario is the highest
which is 9.338×109m3. The spatial distribution pattern is "high in the southwest and low in the northeast". (3) The results of geographical detection show that the average annual precipitation
soil type
and DEM are the main driving factors affecting the spatiotemporal distribution difference of water conservation
and the interaction between precipitation and other factors is significantly enhanced. [Conclusion] According to the temporal and spatial differences in water conservation in Yunnan Province
different suggestions were put forward in this study to provide scientific reference for ecosystem service research and sustainable development route planning in Yunnan Province.
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