Author
Listed:
- Yuhao Jin
(College of Water Conservancy and Civil Engineering, South China Agricultural University, Guangzhou 510642, China)
- Jiajun Guo
(College of Water Conservancy and Civil Engineering, South China Agricultural University, Guangzhou 510642, China)
- Hengkang Zhu
(School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)
Abstract
Water ecosystem services (WESs) are intrinsically associated with the livelihood of urban residents and are frequently disrupted by human activities. Land use and landscape patterns are key driving factors of alterations in WESs. However, existing research primarily quantifies single-factor influences and often overlooks the interactions between these factors. This study addresses this gap by employing a multi-model coupling approach, integrating the Patch-generating Land Use Simulation (PLUS), Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and Geographical Detector (GD) models alongside various indicators to analyse the evolution of land use, landscape patterns and WESs in the Greater Bay Area from 2000 to 2020, and to simulate spatio-temporal change patterns in different scenarios from 2030 to 2050. Additionally, this study examines the multi-factorial interactions between land use, landscape patterns, and WESs. The results indicate that (1) urbanisation steadily increased, leading to intensified landscape fragmentation, and water yield (WY) and total phosphorus (TP) consistently increased, while total nitrogen (TN) in water gradually decreased; (2) urban areas exerted the most significant impact on WY in the Greater Bay Area while Patch density (PD) had a stronger influence on WY, and Shannon’s diversity index (SHDI) had the most pronounced effect on TN and TP; (3) the interaction between any two land-use types or landscape indices exerted a greater impact on WESs compared with the impact of individual factors alone. The interaction between urban areas and cropland substantially influenced WY ( q ¯ = 0.634) and most strongly affected TN and TP in water ( q ¯ = 0.74 and 0.73, respectively). SHDI and PD had the most significant impact on WY in the economic development scenario ( q ¯ = 0.19) and exhibited the greatest influence on the TN and TP levels in the ecological priority scenario ( q ¯ = 0.12 and 0.15, respectively). Our findings can provide theoretical and technical support for the integrated scientific planning of regional water ecosystems and the development of comprehensive land use policies in the future.
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