Estimation and Prediction of Water Conservation Capacity Based on PLUS–InVEST Model: A Case Study of Baicheng City, China

As an important ecosystem service, water conservation is influenced by land use related to human activities. In this study, we first evaluated spatial and temporal changes in water conservation in Baicheng City, western Jilin Province, from 2000 to 2020. Then, we identified three different scenarios: the natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). We coupled the Patch-generating Land Use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models to predict the distribution of land use types and water conservation in Baicheng City under these scenarios for 2030. The results showed the following: (1) The average water conservation in Baicheng City from 2000 to 2020 was 7.08 mm. (2) Areas with higher water conservation were distributed in the northwest and northeast, while lower water conservation areas were distributed in the central and southwest of Baicheng City. (3) The simulation results of the future pattern of land use show an increasing water conservation trend in all three scenarios. Compared with the other two scenarios, the ecological protection scenario is the most suitable option for the current development planning of Baicheng City. Under the ecological protection scenario (EPS), ecological land is strictly protected, the area of agricultural land increases to some extent, and the overall structure of changes in land use becomes more rational. This study provides a reference for land resource allocation and ecosystem conservation.

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Publication Details

Journal
Land
Published
2025-10-04
DOI
https://doi.org/10.3390/land14101993
Primary Topic
Water Resources and Sustainability
Type
article
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Estimation and Prediction of Water Conservation Capacity Based on PLUS–InVEST Model: A Case Study of Baicheng City, China

Ran Duan, Yanfeng Wu, Xiaoyu Li
Land
Water Resources and Sustainability
article

Estimation and Prediction of Water Conservation Capacity Based on PLUS–InVEST Model: A Case Study of Baicheng City, China

Ran Duan, Yanfeng Wu, Xiaoyu Li
article en

Abstract

As an important ecosystem service, water conservation is influenced by land use related to human activities. In this study, we first evaluated spatial and temporal changes in water conservation in Baicheng City, western Jilin Province, from 2000 to 2020. Then, we identified three different scenarios: the natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). We coupled the Patch-generating Land Use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models to predict the distribution of land use types and water conservation in Baicheng City under these scenarios for 2030. The results showed the following: (1) The average water conservation in Baicheng City from 2000 to 2020 was 7.08 mm. (2) Areas with higher water conservation were distributed in the northwest and northeast, while lower water conservation areas were distributed in the central and southwest of Baicheng City. (3) The simulation results of the future pattern of land use show an increasing water conservation trend in all three scenarios. Compared with the other two scenarios, the ecological protection scenario is the most suitable option for the current development planning of Baicheng City. Under the ecological protection scenario (EPS), ecological land is strictly protected, the area of agricultural land increases to some extent, and the overall structure of changes in land use becomes more rational. This study provides a reference for land resource allocation and ecosystem conservation.

LandVol. 14(10)
Chinese Academy of Sciences (CN), Northeast Institute of Geography and Agroecology (CN)
Openalex Percentile: Top 74%
Water Resources and Sustainability
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Estimation and Prediction of Water Conservation Capacity Based on PLUS–InVEST Model: A Case Study of Baicheng City, China — Ran Duan, Yanfeng Wu, et al. · Land (2025) | TGRS Research Map | TGRS