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The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

Located in the hinterland of the Eurasian continent, the inland areas of northwestern China have an arid climate and are confronted with continuing challenges in water resources quantity and quality. Reclaimed water plays an important role in maintaining the sustainable use of urban water resources, especially in arid regions. In this paper, a system dynamics urban reclaimed water model (SDURWM) considering the status of arid regions in northwestern China was constructed. The supply and demand balance index (RWB) and the utilization efficiency index (RWUE) of reclaimed water were proposed as evaluation indicators. The potential of reclaimed water utilization (2016–2025) in three typical cities with similar natural environments and population sizes but with large economic differences were estimated by the SD model. Then the relevant values of reclaimed water quota, supply and resident awareness were adjusted within the range of 10%–20%. The predicted results from intervention demonstrate that the RWB of three cities will be closer or maintain to the ideal value, and that the RWUE will increase by about 0.1, compared with the non-intervention results. This indicates that a minor change of the targeted policies can invigorate the capacity of reclaimed water use in droughty cities. This paper provides some effective solutions for the government's planning of developing the potential of reclaimed water. • Established a SD model for urban reclaimed water utilization in arid areas. • Proposed RWB and RWUE for evaluating the comprehensive utilization potential of reclaimed water. • Explored targeted measures to improve the utilization of reclaimed water in typical arid cities of northwest China. [ABSTRACT FROM AUTHOR]