Under intensifying climate change and anthropogenic pressures, extreme low-flow events increasingly jeopardize water security in the Yellow River water supply region. This study develops the Inter-basin Multi-source Water Joint Allocation and Interconnected Routes Regulation System (IMWA-IRRS) to optimize spatiotemporal allocation of multi-source water and simulate topological relationships in complex water networks. The model integrates system dynamics simulation with multi-objective optimization, validated through multi-criteria calibration using three performance indicators: correlation coefficient (R), Nash-Sutcliffe Efficiency (E_ns), and percent bias (PBIAS). Application results demonstrated exceptional predictive performance in the study area: Monthly runoff simulations at four hydrological stations yielded R > 0.98 and E_ns > 0.98 between simulated and observed data during both calibration and validation periods, with |PBIAS| < 10%; human-impacted runoff simulations at four hydrological stations achieved R > 0.8 between simulated and observed values, accompanied by PBIAS within ±10%; sectoral water consumption across the Yellow River Basin exhibited PBIAS < 5%, while source-specific water supply simulations maintained PBIAS generally within 10%. Comparative analysis revealed the IMWA-IRRS model achieves simulation performance comparable to the WEAP model for natural runoff, human-impacted runoff, water consumption, and water supply dynamics in the Yellow River Basin. The 2035 water allocation scheme for Yellow River water supply region projects total water supply of 59.691 billion m³ with an unmet water demand of 3.462 billion m³ under 75% low-flow conditions and 58.746 billion m³ with 4.407 billion m³ unmet demand under 95% low-flow conditions. Limited coverage of the South-to-North Water Diversion Project’s Middle and Eastern Routes constrains water supply security, necessitating future expansion of their service areas to leverage inter-route complementarity while implementing demand-side management strategies. Collectively, the IMWA-IRRS model provides a robust decision-support tool for refined water resources management in complex inter-basin diversion systems.

In large irrigated agricultural regions under intensive human management, irrigation profoundly influences agricultural drought dynamics. High-frequency irrigation markedly alters natural farmland soil moisture, causing traditional drought indices to distort the actual severity of human-modified agricultural drought and leading to substantial monitoring deviations. In this work, an improved agricultural drought index based on the Crop Moisture Index (CMI) was developed to accurately characterize drought conditions, using the Haihe River Basin as a case study. The CMI’s water balance equation was revised by incorporating an auto-irrigation threshold method with crop coefficients and water stress coefficients. Furthermore, the improved CMI explicitly models irrigation by defining auto-irrigation thresholds based on the critical growth stages of the main crops. The performance of the original and improved CMI was evaluated by comparing their simulated soil moisture and drought detection accuracy against benchmark data derived from measurements across yearly, monthly, and weekly scales. The spatial evolution of a major 2002 drought in North China was also reconstructed to assess the indices’ performance. The results showed that: (1) The revised soil water balance equation achieved significantly lower relative errors than the original equation across all time scales; (2) The improved CMI consistently demonstrated higher drought identification accuracy rates than the original CMI; (3) Drought patterns monitored by the improved CMI showed superior alignment with actual conditions, confirming that it has enhanced applicability for agricultural drought assessment and demonstrates clear advantages for drought assessment in large-scale irrigated agriculture. This work provides crucial insights into the driving mechanisms of agricultural drought under intense human interventions and offers valuable guidance for drought risk management in major agricultural zones.