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<p>The effective functioning of ecosystem water conservation is fundamental to regional ecosystem stability, making its quantitative assessment essential for ecosystem management and ecological civilisation construction. However, existing quantitative assessment models exhibit varying degrees of regional applicability and uncertainty. Integrating multiple models within the same watershed can help reduce model-specific bias and enhance the robustness and reliability of assessment outcomes, thereby enabling more refined ecological and environmental governance. From the perspective of hydrological model selection, this study focuses on the Liupan Mountain region and quantitatively evaluates regional water conservation capacity from 2003 to 2022 using the SWAT model, the InVEST model, and a regional water balance approach. Moreover, the key climatic and environmental drivers underlying the spatiotemporal variation in water conservation capacity are systematically examined. The results indicate that: (1) both the SWAT and InVEST models reveal a significant increasing trend in water conservation capacity over the study period, with the SWAT model displaying more stable interannual variability; (2) both models consistently identify pronounced spatial heterogeneity, with water conservation capacity increasing from north to south and from west to east; (3) simulated water conservation capacity from both models shows a significant positive correlation with precipitation; and (4) the SWAT model demonstrates greater temporal stability and higher sensitivity to climatic variability, making it well suited for hydrological process analysis and long-term water resource planning, whereas the InVEST model, owing to its lower parameter requirements and higher computational efficiency, is more appropriate for large-scale spatial pattern assessment and evaluations of ecological protection effectiveness. Overall, the contrasts between the two models highlight their complementary strengths across different application contexts.</p>

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Divergence or Convergence? A Comparison of InVEST and SWAT in Simulating Water Conservation Patterns and Drivers

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Li Ma,
  • Jianling Yang,
  • Yingjuan Han,
  • Zhenhua Di,
  • Xueyi Zhang,
  • Yazhen Wu,
  • Liping Ma,
  • Xuemei Yang

摘要

The effective functioning of ecosystem water conservation is fundamental to regional ecosystem stability, making its quantitative assessment essential for ecosystem management and ecological civilisation construction. However, existing quantitative assessment models exhibit varying degrees of regional applicability and uncertainty. Integrating multiple models within the same watershed can help reduce model-specific bias and enhance the robustness and reliability of assessment outcomes, thereby enabling more refined ecological and environmental governance. From the perspective of hydrological model selection, this study focuses on the Liupan Mountain region and quantitatively evaluates regional water conservation capacity from 2003 to 2022 using the SWAT model, the InVEST model, and a regional water balance approach. Moreover, the key climatic and environmental drivers underlying the spatiotemporal variation in water conservation capacity are systematically examined. The results indicate that: (1) both the SWAT and InVEST models reveal a significant increasing trend in water conservation capacity over the study period, with the SWAT model displaying more stable interannual variability; (2) both models consistently identify pronounced spatial heterogeneity, with water conservation capacity increasing from north to south and from west to east; (3) simulated water conservation capacity from both models shows a significant positive correlation with precipitation; and (4) the SWAT model demonstrates greater temporal stability and higher sensitivity to climatic variability, making it well suited for hydrological process analysis and long-term water resource planning, whereas the InVEST model, owing to its lower parameter requirements and higher computational efficiency, is more appropriate for large-scale spatial pattern assessment and evaluations of ecological protection effectiveness. Overall, the contrasts between the two models highlight their complementary strengths across different application contexts.