Cropland Change Simulation in Arid Regions Based on Coupled Prediction and Spatial Allocation Models: A Case Study of Ningxia

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.

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Publication Details

Journal
Land
Published
2026-02-17
DOI
https://doi.org/10.3390/land15020339
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00

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article

Cropland Change Simulation in Arid Regions Based on Coupled Prediction and Spatial Allocation Models: A Case Study of Ningxia

Xiankang Hua, Q Liu, D Liu, Yuyu Liu et al.
Land
Land Use and Ecosystem Services
article

Cropland Change Simulation in Arid Regions Based on Coupled Prediction and Spatial Allocation Models: A Case Study of Ningxia

Xiankang Hua, Q Liu, D Liu, Yuyu Liu, Li Chen, Yao Cui
article en

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.

LandVol. 15(2)
Ningxia University (CN), Wuhan University (CN), Institute of Forestry (RS), Ningxia Seismological Bureau (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 66%
Land Use and Ecosystem Services
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