The southeastern Tibet region is characterized by rugged terrain and relative isolation, which has significantly constrained the development of agriculture. However, due to the extremely limited archaeological and historical records available, its important role in the history of agricultural development in Tibet has been overlooked. This study focuses on the Linzhi and Changdu regions of southeastern Tibet, integrating limited archival, historical, and documentary data. By reconstructing historical settlement patterns and population data, this study estimates the arable land area during the Tubo, Yuan, Ming, and Qing dynasties. Using a grid-based model, it reconstructs the distribution patterns of arable land during these periods, aiming to provide a reference for the development of agriculture in Tibet. The research findings indicate the following: (1) During historical periods, settlements in southeastern Tibet were primarily distributed in flat, resource-rich alluvial plains at medium to high altitudes. Settlement types exhibited spatial differentiation: Post stations were primarily situated along major transportation routes that connected river valleys, as well as at high mountain passes. Temples tended to occupy moderately steep slopes, while manors were concentrated in low-lying valleys. (2) During the Tubo, Yuan, Ming, and Qing periods, the total arable land area and cultivation rate in southeastern Tibet were generally low, with total arable land areas of 28,085 hm², 29,449 hm², 25,319 hm², and 24,371 hm², respectively, and cultivation rates of 0.12%, 0.13%, 0.11%, and 0.11%, respectively. (3) Farmland was predominantly distributed along the Yarlung Zangbo, Jinsha, Lancang, and Nu Rivers and their broader tributary valleys. Natural constraints resulted in a highly fragmented farmland distribution.

Understanding how the internal structure of precipitation events evolves and responds to antecedent thermal conditions is essential for revealing the mechanisms of extreme precipitation in plateau-margin mountainous regions. Using hourly precipitation and air temperature data from 14 national reference meteorological stations in the Hehuang Valley during the warm seasons (May–September) of 2015–2024, this study constructed an event-based precipitation database and introduced the inter-event maximum temperature (T_{max_inter}) as an indicator of antecedent thermal accumulation. The Theil–Sen slope estimator, Mann–Kendall trend test, K-means clustering, and binary logistic regression were applied to examine changes in precipitation-event structure and their nonlinear response to antecedent high temperature. Results show that warm-season precipitation was characterized by fluctuating frequency but increasing intensity. Precipitation events were classified into three types—uniform, front-peaked, and rear-peaked—with the proportion of uniform events decreasing and the proportions of front-peaked and rear-peaked events increasing. T_{max_inter} was significantly positively associated with extreme precipitation occurrence: for every 1 °C increase in T_{max_inter}, the odds of extreme precipitation increased by 13.4% (OR = 1.134, 95% CI: 1.10–1.17, p < 0.001). These findings provide a reference for extreme precipitation risk identification and disaster prevention in plateau-margin mountainous areas.