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In recent years, the delicate balance between economic development and ecological environment protection in ecologically fragile arid areas has gradually become apparent. Although previous research has mainly focused on changes in ecological service value caused by land use, a comprehensive understanding of ecology–economy harmony and ecological compensation remains elusive. To address this, we employed a coupled deep learning model (convolutional neural network-gated recurrent unit) to simulate the ecological service value of the Wuwei arid oasis over the next 10 years. The ecology–economy harmony index was used to determine the priority range of ecological compensation, while the GeoDetector analyzed the potential impact of driving factors on ecological service value from 2000 to 2030. The results show the following: (1) The coupled model, which extracts spatial features in the neighborhood of historical data using a convolutional neural network and adaptively learns time features using the gated recurrent unit, achieved an overall accuracy of 0.9377, outperforming three other models (gated recurrent unit, convolutional neural network, and convolutional neural network—long short-term memory); (2) Ecological service value in the arid oasis area illustrated an overall increasing trend from 2000 to 2030, but urban expansion still caused a decrease in ecological service value; (3) Historical ecology–economy harmony was mainly characterized by low conflict and potential crisis, while future ecology–economy harmony will be characterized by potential crisis and high coordination. Minqin and Tianzhu in the north and south have relatively high coordination between ecological environment and economic development, while Liangzhou and Guluang in the west and east exhibited relatively low coordination, indicating a greater urgency for ecological compensation; (4) Geomorphic, soil, and digital elevation model emerged as the most influential natural factor affecting the spatial differentiation of ecological service value in the arid oasis area. This study is of great significance for balancing economic development and ecological protection and promoting sustainable development in arid areas.

With the expansion of the social economy and adjustment of environmental policies, particularly with the onset of development policies for the western region, ecosystems in the arid areas of Northwest China have undergone profound changes. This study collected soil, topographical, climate, and nighttime light data to develop a set of ecological vulnerability assessment indexes based on the background ecological characteristics of the arid areas of Northwest China. The spatiotemporal evolution of ecological carrying capacity was analyzed by our team using Spatial Principal Component Analysis (SPCA) in 2000, 2007, 2012, and 2018 to construct an ecological security pattern. The results revealed that the ecological carrying capacities of the arid areas in the northwest were primarily weak, albeit decreasing, while those areas with strong carrying capacities were increasing. In terms of spatial distribution, the ecological carrying capacities of the Hexi, Northern Xinjiang, and Western Inner Mongolia regions were on the rise, while those of the Southern Xinjiang region were declining. The Minimum Cumulative Resistance (MCR) model was used to extract 51 road-type, river-type, and green corridors with a total length of 7285.43 km. A total of 71 nodes representing important patches, wet rivers, and ecologically fragile areas were extracted. According to the calculated results, the arid region of the northwest was divided into 16 ecological security patterns, which were optimized according to changes in their ecological carrying capacities.

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