Rao Mukund Palat, Cook Edward R, Cook Benjamin I, Palmer Jonathan G, Uriart Maria, Devineni Naresh, Lall Upmanu, D'Arrigo Rosanne D, Woodhouse Connie A, Ahmed Moinuddin, Zafar Muhammad Usama, Khan Nasrullah, Khan Adam, Wahab Muhammad
Tree Ring Laboratory, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY 10964, USA.
Department of Earth and Environmental Science, Columbia University, New York, NY 10027, USA.
Water Resour Res. 2018 Aug;54(8):5687-5701. doi: 10.1029/2018WR023080. Epub 2018 Aug 3.
Our understanding of the full range of natural variability in streamflow, including how modern flow compares to the past, is poorly understood for the Upper Indus Basin (UIB) because of short instrumental gauge records. To help address this challenge, we use Hierarchical Bayesian Regression (HBR) with partial pooling to develop six centuries long (1394-2008 C.E.) streamflow reconstructions at three UIB gauges (Doyian, Gilgit, and Kachora), concurrently demonstrating that HBR can be used to reconstruct short records with interspersed missing data. At one gauge (Partab Bridge), with a longer instrumental record (47 years), we develop reconstructions using both Bayesian Regression (BR) and the more conventionally used Principal Components Regression (PCR). The reconstructions produced by PCR and BR at Partab Bridge are nearly identical and yield comparable reconstruction skill statistics, highlighting that the resulting tree-ring reconstruction of streamflow is not dependent on the choice of statistical method. Reconstructions at all four reconstructions indicate flow levels in the 1990s were higher than mean flow for the past six centuries. While streamflow appears most sensitive to accumulated winter (January-March) precipitation and summer (MJJAS) temperature, with warm summers contributing to high flow through increased melt of snow and glaciers, shifts in winter precipitation and summer temperatures cannot explain the anomalously high flow during the 1990s. Regardless, the sensitivity of streamflow to summer temperatures suggests that projected warming may increase streamflow in coming decades, though long-term water risk will additionally depend on changes in snowfall and glacial mass balance.
由于仪器测量记录时间较短，我们对印度河上游流域（UIB）径流的全范围自然变异性，包括现代径流与过去相比的情况，了解甚少。为了应对这一挑战，我们使用带有部分合并的分层贝叶斯回归（HBR），在UIB的三个测量点（多伊安、吉尔吉特和卡乔拉）开发了长达六个世纪（公元1394 - 2008年）的径流重建，同时证明HBR可用于重建夹杂缺失数据的短记录。在一个测量点（帕尔塔布桥），有更长的仪器记录（47年），我们使用贝叶斯回归（BR）和更常用的主成分回归（PCR）进行重建。PCR和BR在帕尔塔布桥产生的重建结果几乎相同，并且产生了可比的重建技能统计数据，突出表明由此产生的径流树轮重建不依赖于统计方法的选择。所有四个重建结果都表明，20世纪90年代的流量水平高于过去六个世纪的平均流量。虽然径流似乎对冬季（1月至3月）累积降水量和夏季（6 - 9月）温度最为敏感，温暖的夏季通过增加冰雪融化导致高流量，但冬季降水量和夏季温度的变化无法解释20世纪90年代异常高的流量。无论如何，径流对夏季温度的敏感性表明，预计的变暖可能会在未来几十年增加径流量，尽管长期水风险还将额外取决于降雪和冰川质量平衡的变化。
