Optimizing Spatial Pattern of Water Conservation Services Using Multi-Scenario Land Use/Cover Simulation and Bayesian Network in China’s Saihanba Region

Chong Liu, Liren Xu, Fuqing Kang, Zhaoxuan Ge, Jing Zhang, Jinglei Liao, Xuanrui Huang and Zhidong Zhang ()
Additional contact information
Chong Liu: College of Forestry, Hebei Agricultural University, Baoding 071000, China
Liren Xu: National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
Fuqing Kang: Zhangjiakou Academy of Forestry Sciences, Zhangjiakou 075000, China
Zhaoxuan Ge: College of Forestry, Hebei Agricultural University, Baoding 071000, China
Jing Zhang: College of Forestry, Hebei Agricultural University, Baoding 071000, China
Jinglei Liao: College of Forestry, Hebei Agricultural University, Baoding 071000, China
Xuanrui Huang: College of Forestry, Hebei Agricultural University, Baoding 071000, China
Zhidong Zhang: College of Forestry, Hebei Agricultural University, Baoding 071000, China

Land, 2025, vol. 14, issue 8, 1-21

Abstract: Optimizing the spatial pattern of water conservation services (WCSs) is essential for enhancing regional water retention and promoting sustainable water resource management. The Saihanba region, a critical ecological barrier in northern China, has experienced severe degradation due to historical over-logging, leading to weakened WCS functions. This study used remote sensing techniques to interpret land use/land cover change (LULC) and combined it with meteorological and basic ecological data to assess changes in WCS capacity in the Saihanba region, China, under multiple 2035 scenarios using CA-Markov and Bayesian network models. The Bayesian belief network identified priority areas for spatial optimization. Results showed the following: (1) The spatial distribution patterns of WCSs showed a strong dependence on land-use types, with both forest and grassland areas demonstrating superior water conservation capacity compared to other land cover categories; (2) although total WCS capacity varied across scenarios, spatial distribution remained consistent—high-value zones were mainly in the south and central-east, while lower values occurred in the west; and (3) WCS areas were categorized into key optimization, ecological protection, and general management zones. Notably, the Sandaohekou Forest Farm and the western Qiancengban Forest Farm emerged as critical areas requiring urgent optimization. These findings offer practical guidance for spatial planning, ecological protection, and water resource governance, supporting long-term WCS sustainability in the region. The study also contributes to cleaner production strategies by aligning ecosystem service management with sustainable development goals.

Keywords: water conservation services; land-use changes; CA-Markov model; Bayesian network model; scenario simulation; Saihanba region; remote sensing (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/14/8/1679/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/8/1679/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:14:y:2025:i:8:p:1679-:d:1728868

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().