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.

In the context of global warming, extreme precipitation on the Qinghai-Tibet Plateau has intensified significantly. Understanding the internal structure of precipitation events and their response to rising temperatures is crucial for elucidating these intensification mechanisms. Focusing on the Hehuang Valley, this study constructed an event-scale dataset using hourly observations from 15 meteorological stations (2015–2024), introducing “Inter-event Maximum Temperature” as a key thermal driver. By integrating clustering, trend tests, and logistic regression, we analyzed the spatiotemporal evolution of precipitation extremes. Results indicate that: (1) regional precipitation exhibits a pattern of fluctuating frequency but increasing intensity; (2) the proportion of uniform precipitation has decreased while non-uniform types, especially rear-peak events, have increased significantly; (3) spatial heterogeneity is strongly influenced by topography, with extreme precipitation concentrated on windward slopes and in valley contractions;(4) Inter-event maximum temperature exerts a significant non-linear positive effect, where a 1°C increase raises the odds ratio for extreme precipitation occurrence by approximately 13.4%. These results confirm that antecedent thermal accumulation enhances extremes by increasing atmospheric water-holding capacity and convective instability. While decadal-scale uncertainties remain due to the limited 10-year data span, these findings provide a scientific basis for disaster prevention and water resource management in high-altitude basins.

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.

Anthropogenic land use constitutes a key driver of land cover change, exerting profound impacts on terrestrial carbon/water cycles and ecosystems across global to regional scales. Consequently, long-term land cover datasets serve as fundamental data infrastructure for ecological effect assessment and paleoclimate modeling. Considering the dominant role of historical anthropogenic disturbances in vegetation change across the Hehuang Valley, we developed a 1 km × 1 km potential vegetation prior to land reclamation map through integrating remotely sensed land-use patterns with Random Forest-modeled vegetation predictions. Then, we derived changes in forest and grassland areas and their spatial patterns over the past two millennia by subtracting the spatially explicit cropland cover for six agricultural expansion stages. Finally, we compared our results with representative historical LUCC datasets. The main conclusions are as follows: (1) The potential vegetation of the Hehuang Valley was predominantly grassland, with forest occurring as a patchy and linear mosaic. Grassland and forest covered approximately 2.6 × 10⁴ km² and 0.7 × 10⁴ km², respectively. (2) Over the past two millennia, during the Han (202 BCE–220 CE), Tang (618–907 CE), Song (960–1279 CE), Ming (1368–1644 CE), and Qing (1644–1912 CE) dynasties, as well as the Republic of China period (1912–1949 CE), cropland reclamation reduced forest and grassland cover by 6% and 18%, respectively. Forest area decreased by 23.58–100.03 km², while grassland area decreased by 310.72–1513.05 km² across these periods. Grassland reduction was concentrated in valleys, whereas forest reduction was spatially scattered but locally intensive. These findings highlight the need to promote sustainable cropland development through technological innovation, improved management, and agricultural specialization rather than ecosystem conversion. (3) Compared with the HYDE 3.2 dataset and a national-scale reconstruction dataset, our framework better reflects the regional characteristics of the Hehuang Valley and provides a more detailed reconstruction of long-term forest and grassland changes.