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    2025年中—尼吉隆口岸冰湖溃决灾害遥感复盘分析

    Remote sensing analysis of the 2025 glacial lake outburst flood event at the China-Nepal Gyirong Port

    • 摘要: 2025年7月8日,中尼边境东林藏布流域发生冰湖溃决并引发跨境泥石流灾害。由于事源地位于边境高寒地区,实测资料稀缺,为复盘灾害过程,综合利用多源遥感影像与GF-7地形数据,揭示了溃决冰湖前期快速扩张至0.6 km²的过程,提取了冰湖水位—面积—库容关系,估算其总蓄水量为800万~850万m3,溃决下泄水量为500万~600万m3,并基于遥感识别的溃口参数推算泄流洪峰流量为1 100~1 400 m3/s,与下游水文站实测洪峰流量高度吻合。然而,受潜在的冰川内部蓄水空间及下游河道固态物质冲刷等因素影响,遥感估算的冰湖泄流水量与下游河道监测洪量存在差异。本研究显示了遥感技术在高寒偏远地区冰湖动态监测与危险性评估中的不可替代价值,也凸显了冰湖溃决灾害链的复杂机理,以及对未来构建穿透式探测与天空地一体化监测网络的迫切需求。

       

      Abstract: On July 8, 2025, a glacial lake outburst flood (GLOF) occurred in the Donglin Zangbo Basin along the China-Nepal border, triggering a cross-border debris flow. Due to the scarcity of in-situ measurements in this remote high-altitude region, in order to review the disaster process, multiple remote sensing images and Gaofen-7 (GF-7) topographic data were comprehensively used to reveal the rapid expansion of the glacial lake to 0.6 km2 in the early stage of the outburst flood. The water level area storage capacity relationship of the glacial lake was extracted, and the total water storage capacity was estimated to be 8.0~8.5 million m3, with a total water discharge of 5.0~6.0 million m3 from the outburst flood. Based on remotely identified breach parameters, the peak discharge was calculated to be 1 100~1 400 m3/s, which aligns well with the hydrograph measured at a downstream gauging station. However, a discrepancy was observed between the remotely sensed outburst volume and the monitored flood volume downstream. This disparity suggests the potential involvement of internal water storage within the glacier and the entrainment of substantial solid materials from the channel. This study underscores the indispensable value of remote sensing for monitoring glacial lake dynamics and assessing GLOF risks in inaccessible high-mountain regions. It also highlights the complex mechanisms of GLOF-induced disaster chains and emphasizes the urgent need for developing integrated ground-penetrating and space-air-ground collaborative monitoring networks.

       

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