Multi-Criteria Decision-Support System for Sustainable Management of the Aral Sea Basin under Uncertainty

— The Aral Sea Desiccated Basin faces one of Central Asia’s most severe ecological and socio-economic crises, driven by decades of unsustainable water use and climate change. Developing sustainable management strategies for this region remains complex due to uncertain, incomplete, and often conflicting environmental data. This study presents a hybrid Multi-Criteria Decision-Support System (MCDSS) that integrates Intuitionistic Fuzzy Sets (IFS) with Multi-Criteria Decision-Making (MCDM) techniques to address uncertainty and hesitation in environmental decisions. By incorporating membership, non-membership, and hesitation degrees, the proposed model enables a more realistic evaluation of management alternatives compared to traditional deterministic or fuzzy methods. To further enhance analytical capacity, a Large Multimodal Model (LMM) is introduced to process and fuse satellite imagery, numerical indicators, and expert textual inputs. The LMM supports cross-modal reasoning and improves the interpretation of soil salinity, vegetation degradation, and water resource distribution. A case study on water allocation and land rehabilitation in the Aral Sea Basin demonstrates that the LMM-enhanced IFS–MCDM framework improves decision robustness, adaptability, and transparency. The results suggest that the proposed system can effectively support data-driven, sustainable management strategies for ecologically vulnerable regions under uncertainty.