The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Estimation of water provision service for monsoon catchments of South China: Applicability of the InVEST model
Abstract
Abstract With recognizing the value of ecosystem services to society, the efforts to manage ecosystem services have increased. One such tool to help manage ecosystem services is the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, a new but powerful ecosystem service model. However, the InVEST model still requires testing in various geographic regions. This study assessed the performance of the InVEST water yield model in a typical East Asian monsoon catchment of South China. A sensitivity analysis shows that precipitation is the most sensitive factor affecting water yield compared with two other important variables: ET0 (reference evapotranspiration) and Z (climate seasonality factor). Especially for some southeast sub-watersheds, a 46% increase in precipitation from 2005 to 2015 resulted in an approximately 138% increase in water yield. The model performed well when the Z parameter was calibrated with available observed data (R2 = 0.92) or inferred from the globally available ω (R2 = 0.92) which is a key parameter that characterizes the land surface properties of catchments. This study will be helpful to other users who employ InVEST model and ecosystem services management in East Asian monsoon catchments.
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Metadata
- Authors
- Yang, D., Liu, W., Tang, L., Chen, L., Li, X., & Xu, X.
- Venue
- Landscape and Urban Planning
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 182
- Pages
- 133-143
- ISSN
- 0169-2046 (ISSN-L)
- OpenAlex
- W2901971143
- Cited by
- 328
- References
- 30
- FWCI
- 7.20
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yang, D., Liu, W., Tang, L., Chen, L., Li, X., & Xu, X. (2019). Estimation of water provision service for monsoon catchments of South China: Applicability of the InVEST model. Landscape and Urban Planning. https://doi.org/10.1016/j.landurbplan.2018.10.011
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