Recent studies have shown that the geothermal systems in Tibet are rich in rare metal elements such as lithium (Li), boron (B), rubidium (Rb), and cesium (Cs). However, the understanding of the origin of Cs-rich geyserite formed by hot springs remains unclear. In this study, a detailed petrological, elemental geochemical, and strontium–neodymium (Sr–Nd) isotopic investigation on Cs-rich geyserite in the Chabu region revealed that opal was the main mineral component of Chabu geyserite; here, some samples were rich in terrigenous clastic material, and well-developed diatom fossils were also present. Chabu geyserite had high contents of SiO₂ (78.95%–94.72%) and Al₂O₃ (3.02%–8.14%) and low contents of Fe₂O₃ (0.21%–1.94%), TiO₂ (0.01%–0.20%), MnO (0.01%–0.15%); additionally, the Fe/Ti ratio, the Al/(Al + Fe) ratio, and the Al/(Al + Fe + Mn) ratio showed large variations. These results indicated different degrees of participation by the terrigenous materials, hydrothermal deposition, and biogenic processes. Chabu geyserite was depleted in transition metal elements (e.g., Sc, V, and Cr) and high field strength elements (e.g., Nb, Zr, and Hf), relatively enriched in large-ion lithophile elements (e.g., Li, Rb, Sr, and Ba), and strongly enriched in Cs, (by up to 100 times the Cs content in the upper crust); in addition, it had low V/Y (1.30–2.00) and U/Th ratios. Chabu geyserite exhibited a right-dipping rare earth element (REE) distribution pattern and had significant negative Eu anomalies (0.26–0.72) and no or weak positive Ce anomalies (0.97–1.36). These results further indicated the influence of terrigenous clastic materials and nonhydrothermal sedimentation factors. The Sr–Nd isotopic composition of Chabu geyserite was significantly different from that of the mantle, with relatively high ⁸⁷Sr/⁸⁶Sr ratios (0.7070–0.7076) and low ¹⁴³Nd/¹⁴⁴Nd ratios (0.512223–0.512314). These ratios were similar to those of the crust. Combined with previous studies, the results from this study indicated that Chabu geyserite was a Cs-rich geyserite and was formed in an intracontinental post-collisional orogenic environment, mainly from crustal material, with the participation of biological and hydrothermal processes.

The Qinghai–Xizang Plateau and its surrounding regions have experienced intense tectonic activity, resulting in complex geostress environments that cause frequent and distinctive rockburst disasters in plateau tunnel engineering. In this study, numerical simulations were conducted to investigate the distribution characteristics and patterns of tunnel rockbursts in high-altitude regions, using geostress orientation, lateral pressure coefficient, and tunnel depth as the primary independent variables. Secondary development of FLAC3D 7.00.126 was carried out using FISH language to enable the recording and visualization of tangential stress, the Russense rockburst criterion, and elastic strain energy. Based on this, the influence mechanisms of these key geostress parameters on the location, extent, and intensity of rockbursts within tunnel cross sections were analyzed. Results indicate that geostress orientation predominantly affects the location of rockbursts, with the surrounding rock in the direction of the minimum principal stress on the tunnel cross section being particularly prone to rockburst risks. The lateral pressure coefficient primarily influences the rockburst intensity and pit range within local stress concentration zones, with higher values leading to greater rockburst intensity. Notably, when structural stress is sufficiently large, rockbursts may occur even in tunnels with shallow burial depths. Tunnel depth determines the magnitude of geostress, mainly affecting the overall risk and potential extent of rockbursts within the cross section, with greater depths leading to higher rockburst intensities and a wider affected area.

Xizang is characterized by high altitude, low air pressure, strong atmospheric transparency, and complex terrain, while sparse ground stations coexist with continuously available remotely sensed data, and systematic studies on SSR bias correction and meteorological influences under plateau conditions remain limited. This study focuses on a short-term spring case at one urban observation site in Lhasa, using observations collected from 4 to 30 April 2025 to investigate the bias correction of remotely sensed surface solar radiation (SSR) and the influence of meteorological factors. Ground observations and Himawari-8 remotely sensed data were first spatially and temporally matched and preprocessed. Spearman correlation analysis was then used to select key input variables. Support vector regression, random forest, XGBoost, and multiple linear regression models were subsequently developed, followed by a Stacking ensemble model for bias correction. Finally, local sensitivity analysis was conducted to examine the local response of the correction model to selected meteorological variables at a representative baseline point. The results showed that the correlation coefficient between remotely sensed SSR and ground-observed SSR was 0.88 ($p<0.001$). The Stacking ensemble model achieved the best performance, with a test set $R^2$ of 0.8796, an MAE of 118.54 W/m², and an RMSE of 152.41 W/m². Local sensitivity analysis showed that a +10 hPa perturbation in air pressure increased the model output by 173.45 W/m², while a +10 °C perturbation in air temperature increased the output by 23.76 W/m². This study provides a reference for improving the accuracy of remotely sensed SSR and for solar resource assessment in plateau regions.