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The Yellow River flows through multiple provinces in China, shaping the North China Plain, the largest alluvial plain in China. As the control node of basin ecological environment, the confluence of Weihe River and Yellow River is deemed as the gateway to North China Plain. In this study, a numerical simulation of the Weihe River–Yellow River confluence is conducted using a 2D hydrodynamic model and a coupled transport model for dissolved oxygen–biochemical oxygen demand. The results show that: (i) The typical flow field with multiple backflow areas is formed at the stagnant area where main stream and tributary converge and abrupt channel change area in different hydrological periods. The spur dike here mainly affects the velocity of the Weihe River outlet. (ii) There is an obvious concentration transition mixing zone downstream of the confluence, and the width of the mixing zone gradually linear increases with the direction of water flow. (iii) The self‐purification ability of the confluence is strongest in dry period, weaker in level period, and weakest in wet period. Water bodies have stronger self‐purification capacity on riverbanks than in the middle, and it is stronger in the upper reaches of Weihe River compared to Yellow River. Lower reaches also have a stronger self‐purification capacity than upper reaches. The study results can serve as a scientific reference for protecting the ecological environment of the Yellow River. [ABSTRACT FROM AUTHOR]

Bangladesh is one of the most densely populated countries in the world. There are 57 trans‐frontier rivers in the country, the widest being the Brahmaputra River. The river's channels have frequently changed course, but the relationship between such river migrations and human settlement patterns has remained unstudied. In this paper, optically stimulated luminescence and radiocarbon dating techniques were applied to sedimentary and organic materials in the oldest urban center (Wari‐Bateshwar) in Bangladesh. The results showed that the landscape around the urban center was dominated by floodplain and peatland facies between 7.9–7.6 and 4.7–1.6 ka, respectively. Humans occupied this area at ~3.2 ka, and manufactured delicate semi‐precious gemstone beads between ~2.4 and 1.8 ka. The urban center might be the same as an important city of the Gangaridai described in historical records. Due to fluvial migration at ~1.8 ka, the area surrounding the urban center was covered by fluvial sand. Humans might have been forced to abandon the urban center, leading to the bead processing technology in Bangladesh being lost forever. [ABSTRACT FROM AUTHOR]

Vast palaeolakes once occupied the Qinghai‐Tibetan Plateau (TP). Analyses of the sedimentary records of these lakes could potentially provide an extensive dating archive. Many previously constructed age‐depth models simulating lacustrine cores have been principally based on radiocarbon (14C) dating. However, such dating could have been hampered by the so‐called ‘lake reservoir effect’ (LRE) and the reworking of lakebed sediments, resulting in inaccurate 14C age‐depth models and limiting interpretations of existing lacustrine palaeoclimatic records. Lake Linggo Co is located on the central TP, in one of the coldest and most arid regions of Tibet. We dated a 9.87‐m‐long lacustrine core extracted from the lakebed at a water depth of ~60 m using a combination of 210Pb, 14C and optically stimulated luminescence (OSL) techniques. Some 14C ages showed significant age reversals; all the 14C ages were much older than the 210Pb and OSL ages for the same depths. This could possibly be attributed to the presence of old, inherited carbon, causing the inherited 14C age to appear unstable during the deposition period. The 210Pb and OSL ages were roughly concordant, and were also consistent with the stratigraphical succession. We therefore suggest that 14C dating may, on its own, be inadequate for accurate dating of lacustrine sediment sites on the TP, and that the OSL method should also be applied in order to evaluate the reliability of any 14C ages. With this approach, we constructed an age‐depth model, revealing sedimentation rates of 1.7, 0.8, 6.8 and 0.6 mm a−1 between 0–1.9, 1.9–4.2, 4.2–4.4 and 4.4–9.4 ka, respectively. [ABSTRACT FROM AUTHOR]