PreprintArticleVersion 1This version is not peer-reviewed
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
Version 1
: Received: 18 July 2024 / Approved: 18 July 2024 / Online: 18 July 2024 (23:47:58 CEST)
How to cite:
Ma, X.; Liu, S.; Guo, L.; Zhang, J.; Feng, C.; Feng, M.; Li, Y. 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. Preprints2024, 2024071509. https://doi.org/10.20944/preprints202407.1509.v1
Ma, X.; Liu, S.; Guo, L.; Zhang, J.; Feng, C.; Feng, M.; Li, Y. 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. Preprints 2024, 2024071509. https://doi.org/10.20944/preprints202407.1509.v1
Ma, X.; Liu, S.; Guo, L.; Zhang, J.; Feng, C.; Feng, M.; Li, Y. 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. Preprints2024, 2024071509. https://doi.org/10.20944/preprints202407.1509.v1
APA Style
Ma, X., Liu, S., Guo, L., Zhang, J., Feng, C., Feng, M., & Li, Y. (2024). 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. Preprints. https://doi.org/10.20944/preprints202407.1509.v1
Chicago/Turabian Style
Ma, X., Mengyuan Feng and Yilun Li. 2024 "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" Preprints. https://doi.org/10.20944/preprints202407.1509.v1
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 (Scenario1), ecological development priority(Scenario2), and cropland development priority(Scenario3). 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 Scenario1 is highest among different land use scenarios, marginally surpassing ecological development priority by 0.5%; (4) Climate scenarios reveal significant disparities, with SSP126 yielding 67% higher water production 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.
Keywords
PLUS model; InVEST model; water yield; land use/land cover; geodetector
Subject
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
