Evolution and Analysis of Water Yield under the Change of Land Use and Climate Change Based on the PLUS-InVEST Model: A Case Study of the Yellow River Basin in Henan Province

IF 3 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Water Pub Date : 2024-09-09 DOI:10.3390/w16172551
Xiaoyu Ma, Shasha Liu, Lin Guo, Junzheng Zhang, Chen Feng, Mengyuan Feng, Yilun Li
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Abstract

Understanding the interrelationships between land use, climate change, and regional water yield is critical for effective water resource management and ecosystem protection. However, comprehensive insights into how water yield evolves under different land use scenarios and climate change remain elusive. This study employs the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models, Patch-generating Land Use Simulation (PLUS) model, and Geodetector within a unified framework to evaluate the dynamics of land use, water yield, and their relationships with various factors (meteorological, social, economic, etc.). To forecast the land use/cover change (LUCC) pattern of the Yellow River Basin by 2030, three scenarios were considered: economic development priority (Scenario 1), ecological development priority (Scenario 2), and cropland development priority (Scenario 3). Climate change scenarios were constructed using CMIP6 data, representing low-stress (SSP119), medium-stress (SSP245), and high-stress (SSP585) conditions. The results show the following: (1) from 2000 to 2020, cropland was predominant in the Yellow River Basin, Henan Province, with significant land conversion to impervious land (construction land) and forest land; (2) water yield changes during this period were primarily influenced by meteorological factors, with land use changes having negligible impact; (3) by 2030, the water yield of Scenario 1 is highest among different land use scenarios, marginally surpassing Scenario 2 by 1.60 × 108 m3; (4) climate scenarios reveal significant disparities, with SSP126 yielding 54.95 × 108 m3 higher water yield than SSP245, driven predominantly by precipitation; (5) Geodetector analysis identifies precipitation as the most influential single factor, with significant interactions among meteorological and socio-economic factors. These findings offer valuable insights for policymakers and researchers in formulating land use and water resource management strategies.
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基于 PLUS-InVEST 模型的土地利用变化和气候变化下的产水量演变与分析:河南省黄河流域案例研究
了解土地利用、气候变化和区域产水量之间的相互关系对于有效的水资源管理和生态系统保护至关重要。然而,对于水资源产量在不同土地利用方案和气候变化情况下如何演变的全面见解仍然难以捉摸。本研究在一个统一的框架内采用生态系统服务和权衡综合评估(InVEST)模型、斑块生成土地利用模拟(PLUS)模型和 Geodetector,以评估土地利用、产水量的动态及其与各种因素(气象、社会、经济等)的关系。为了预测黄河流域到 2030 年的土地利用/植被变化(LUCC)模式,考虑了三种情景:经济优先发展(情景 1)、生态优先发展(情景 2)和耕地优先发展(情景 3)。利用 CMIP6 数据构建了气候变化情景,分别代表低压力(SSP119)、中压力(SSP245)和高压力(SSP585)条件。结果显示如下(1) 2000-2020 年,河南省黄河流域以耕地为主,大量土地向不透水土地(建设用地)和林地转化;(2) 这一时期的产水量变化主要受气象因素影响,土地利用变化的影响可以忽略不计;(3) 到 2030 年,在不同土地利用方案中,方案 1 的产水量最高,略微超过方案 2 1.60 × 108 立方米;(4) 气候情景显示出显著差异,SSP126 的产水量比 SSP245 高 54.95 × 108 立方米,主要受降水驱动;(5) Geodetector 分析认为降水是影响最大的单一因素,气象和社会经济因素之间存在显著的相互作用。这些发现为决策者和研究人员制定土地利用和水资源管理战略提供了宝贵的见解。
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来源期刊
Water
Water WATER RESOURCES-
CiteScore
5.80
自引率
14.70%
发文量
3491
审稿时长
19.85 days
期刊介绍: Water (ISSN 2073-4441) is an international and cross-disciplinary scholarly journal covering all aspects of water including water science and technology, and the hydrology, ecology and management of water resources. It publishes regular research papers, critical reviews and short communications, and there is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles. Computed data or files regarding the full details of the experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.
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