Huiping Zhang

Despite widespread recognition that lithological heterogeneity helps shape river networks, a widely applicable topographic diagnostic for whether and where lithological contrasts drive drainage reorganization is still lacking. Here, we introduce a drainage-network metric, the rock proportion–contributing area order (RP-CAO) relationship, and further show that responses diverge with drainage scale: small, low-discharge channels divert around resistant rocks, whereas large, high-discharge rivers largely maintain their course and incise through them. We capture this divergence by tracking rock-type enrichment along the network as a function of contributing area. Across landscape evolution simulations and natural river networks, the enrichment-scale relation forms a robust V-shaped pattern that quantifies these end members. Applied to networks along the eastern Tibetan Plateau, it isolates where lithology most strongly localizes rerouting and divide mobility despite strong spatial variability in tectonic and climatic influences. Requiring only topography and lithological maps, the framework enables comparable tests of drainage reorganization driven by spatially discrete lithological contrasts across mountain belts worldwide.

The initial exhumation of the fold‐and‐thrust belt in the Gangdese retroarc provides key insights into the development of an Andean‐type continental margin in southern Tibet. Here, we present new zircon U‐Pb geochronology, low‐temperature thermochronology and balanced cross section from the Late Cretaceous retroarc and forearc basins to reconstruct the pre‐collisional exhumation history of the Gangdese fold‐and‐thrust belt. Interbedded andesite and tuffite layers from the upper Shexing Formation in the retroarc basin yield weighted mean U‐Pb ages of 85.5 ± 4.4 and 84.6 ± 0.9 Ma, providing refined constraints on the depositional age. Thermochronologic data from the retroarc and forearc basins record Late Cretaceous‐Cenozoic cooling, with inverse thermal modeling indicating the onset of rapid retroarc exhumation at ∼78–70 Ma, shortly after deposition. This timing likely corresponds to the onset of crustal shortening in the Gangdese retroarc, with a minimum estimate of ∼67% as constrained by balanced cross section restoration. This earliest exhumation signal is also recognized in the forearc and north‐central Lhasa terrane, coinciding with a magmatic lull in the Gangdese arc and northward migration of magmatism. Collectively, we interpret that shallow or flat subduction of the Neo‐Tethyan oceanic lithosphere may have provided the primary geodynamic forcing, whereas surface erosion modulated the mechanical state of the orogenic wedge, jointly promoting Late Cretaceous crustal shortening.

Earthquakes are among the most severe natural disasters globally. Since 1949，the number of deaths caused by earthquake disasters in China has accounted for more than 50% of the total deaths from natural disasters. China has suffered from major earthquake catastrophes many times in history. Therefore，strong earthquake risk prediction is of great significance for reducing casualties and economic losses. Currently，strong earthquake risk prediction faces three core challenges：（1） At the scientific level，the mechanism of earthquake generation is unclear，the basic data in the epicenter area is scarce，and the deep observation technology is limited. （2） At the technical level，existing technical means have significant bottlenecks in monitoring，simulation and verification links，and the uncertainty of effectively obtaining parameters such as hazard，exposure and vulnerability is high. （3） At the social level，the contradiction between “probabilistic conclusions” and the “deterministic demand” for disaster prevention is prominent，and it is necessary to transform uncertainty into operable strategies. To address the above challenges，breakthroughs are needed in multiple aspects：（1） In the construction of scientific models，strengthen quantitative and refined three-dimensional seismic structure models，and integrate multiple technologies to identify major earthquake hazard sources. （2） In the field of detection and observation，promote high-precision，high-density observation and multidisciplinary comprehensive research，and achieve observation breakthroughs through technological innovation. （3） In zoning and scenario construction，promote the simulation of multi-scale and wide-frequency strong ground motion. For early warning technology，it is necessary to develop multi-source information fusion to realize real-time perception of disaster situation and emergency response. In the future，strong earthquake risk prediction needs to accelerate the iteration of key technologies，promote efficient collaboration between science and society，and strengthen international cooperation and data sharing. With scientific and technological innovation as the engine，promote the transformation of the four-in-one research paradigm of “earth science + information science + engineering science + management science”，realize the cognitive leap from single-discipline breakthrough to “earth system science”，the technological leap from static risk assessment to real-time dynamic monitoring，and the value leap from disaster response to social resilience construction. Finally，achieve effective identification，dynamic assessment，refined prevention and control，and efficient governance of strong earthquake risks，providing a solid guarantee for sustainable and high-quality social development.

The downstream grain size variation along active river channels has been a long‐standing topic for fluvial geomorphologists. However, identifying the influence and controls on downstream change in bed sediment texture is not straightforward. In this study, we investigated the lithological composition of bedrock and riverbed gravels, rock strength and grain size distribution of fluvial gravels within three active rivers flowing out of the Longmenshan Mountain in the eastern Tibetan Plateau where human disturbances are locally occurring, to examine the spatial pattern of grain size distributions and the controlling factors. The field investigations and geological mapping showed that granite lithology contributed more coarse clasts to the river bed substrate than its areal proportion. Downstream fining trends were detected across the entire river systems of all three rivers, while distinct patterns emerged when comparing upstream and downstream segments from the mountain front. The D₅₀ of granitic gravels in the Yazi River (YZR) and Mianyuan River (MYR) have the same fining rate of about −0.013 km⁻¹, while the sandstone gravels in the YZR and limestone gravels in the MYR have a similar fining rate of −0.010 km⁻¹. In contrast, the granite and plagioamphibolite gravels in the Shiting River (STR) have higher fining rates, with values of −0.022 and −0.029 km⁻¹, respectively. For coarser grain size D₈₄, the granitic gravels in the YZR and MYR have similar fining rates between −0.018 and −0.019 km⁻¹, while sandstone gravels and limestone gravels have lower fining rates between −0.012 and −0.014 km⁻¹. Although the D₈₄ fraction for granite and plagioamphibolite gravels has a higher fining rate of −0.034 and −0.022 km⁻¹ in the STR, the D₅₀ and D₈₄ in STR have the same fining rate (−0.022 km⁻¹) for plagioamphibolite gravels. We interpret our data to indicate that selective deposition is the main control on downstream fining of fluvial gravels, as the mobility of gravel is strongly size‐dependent. In addition, the higher downstream fining rates of both granite and plagioamphibolite gravels in the STR than those in the YZR and MYR also reveal the river channel slope control on the downstream change pattern of fluvial sediments. The significant difference in downstream fining rates between granite and plagioamphibolite gravels in STR indicates that the downstream fining in some reaches would be lithology‐dependent. Although the weathering phenomenon on the surface of granitic gravels in river channels could not explicitly account for its contribution to the downstream fining of granitic gravels, its significance on gravel abrasion deserves further work in future investigations. Our field investigations show that human activities, such as gravel mining and dam construction, had temporal impacts on downstream grain size changes. Our findings highlight that the sediment transport in the Longmenshan Mountain region is strongly influenced by selective deposition, river channel slope and lithology. The new findings provide new insights for understanding the links of grain size patterns to sediment supply, fluvial topography and bedrock lithology in the eastern Tibetan Plateau.

The ongoing India‐Asia convergence during the Cenozoic drove intensively compressional deformation in the northern margins of the Tibetan Plateau, such as Tianshan, which formed the highest mountain peaks and lowest intermontane basins in the Central Asia. Understanding the spatial‐temporal evolution of the Tianshan and its marginal fold‐thrust belts (FTB) are crucial for interpreting intracontinental deformation processes related to the India‐Asia collision. In this work, low‐temperature thermochronology data and growth strata analysis are integrated to constrain chronologically the onset of deformation of the structures in FTB (Belt I, II, and the Huoyanshan Anticline) along the southern front of the Chinese East Tianshan (CETS), and then to underpin the Cenozoic deformational model of the CETS. We propose a three‐stage expansion model to reveal the processes by which the southern thrust belts in the CETS have extended into the Turpan Basin since the Oligocene. Stage 1: thrusting of the South Bogda Fault since ∼30 Ma, which caused the initial uplift of the CETS; Stage 2: deformation expanded southward to the Tarlang River region at ∼20 Ma; Stage 3: the thrust belts propagated southward in a thin‐skinned structural style to the Huoyanshan Anticline in the central part of the Turpan Basin since ∼10 Ma. The progressive propagation of FTB in the southern piedmont of the CETS could have responded to multi‐stage uplift of the Tibetan Plateau during the Cenozoic.