Author
Listed:
- Yao Cui
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Yaolin Liu
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Yanfang Liu
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Dan Liu
(Ningxia Natural Resources Information Center, Yinchuan 750000, China)
- Xiankang Hua
(Xi’an Lvhuan Forestry Technology Service Co., Ltd., Xi’an 710048, China)
- Li Chen
(Ningxia Natural Resources Information Center, Yinchuan 750000, China)
- Qiaoyang Liu
(Ningxia Natural Resources Information Center, Yinchuan 750000, China)
Abstract
Cropland dynamics in ecologically fragile regions are central to balancing food security and ecological integrity in the Yellow River Basin. Ningxia Hui Autonomous Region is used as a case study. An integrated simulation framework is developed by coupling an improved grey prediction model (Improved GM(1,1)) with the CLUMondo spatial model. The analysis addresses four questions: how cropland changed during 2009–2024, which drivers explain cropland suitability and transitions, what spatial resolution is appropriate for implementation, and how cropland patterns differ under alternative development pathways for 2025–2040. Historical cropland change in Ningxia during 2009–2024 is quantified, and spatial patterns for 2025–2040 are projected under three scenarios: business-as-usual (BAU), ecological protection (EP), and rapid urbanization (URE). Cropland change during 2009–2024 shows pronounced phased fluctuations and a stable redistribution pattern described as “southern reduction and northern replenishment, urban decrease and rural increase”. Population growth, economic expansion, and policy regulation jointly drive this spatiotemporal reconfiguration. Land demand forecasting is improved by introducing a metabolism mechanism and residual correction into the grey model, which reduces mid- to long-term divergence. Multi-scale logistic regression tests show the highest AUC at 50 m, with AUC values exceeding 0.8 across land categories, and this resolution is used for model implementation. Model performance is evaluated using AUC, Kappa, and overall accuracy, supporting the applicability of the framework in arid, ecologically fragile regions. Scenario simulations reveal clear divergence in future spatial outcomes. BAU maintains sustained pressure on cropland protection and ecological security. URE increases the risk of encroachment on high-quality cropland in the central–northern irrigated areas due to urban expansion. EP constrains construction land growth and secures strategic ecological spaces, thereby slowing the loss of high-quality cropland while maintaining development capacity. These results provide a transparent basis for scenario-based territorial spatial planning in Ningxia and offer transferable evidence for managing cropland–ecology tradeoffs in arid and semi-arid regions.
Suggested Citation
Yao Cui & Yaolin Liu & Yanfang Liu & Dan Liu & Xiankang Hua & Li Chen & Qiaoyang Liu, 2026.
"Cropland Change Simulation in Arid Regions Based on Coupled Prediction and Spatial Allocation Models: A Case Study of Ningxia,"
Land, MDPI, vol. 15(2), pages 1-25, February.
Handle:
RePEc:gam:jlands:v:15:y:2026:i:2:p:339-:d:1866735
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:15:y:2026:i:2:p:339-:d:1866735. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.