Climate Change Alternate Energy and Water Resources Institute, National Agricultural Research Centre (NARC), Pakistan Agricultural Research Council, Islamabad, Pakistan; Earth System Science, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands.
Earth System Science, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands.
Sci Total Environ. 2016 Apr 1;548-549:289-306. doi: 10.1016/j.scitotenv.2016.01.001. Epub 2016 Jan 21.
Scarcity of in-situ observations coupled with high orographic influences has prevented a comprehensive assessment of precipitation distribution in the high-altitude catchments of Indus basin. Available data are generally fragmented and scattered with different organizations and mostly cover the valleys. Here, we combine most of the available station data with the indirect precipitation estimates at the accumulation zones of major glaciers to analyse altitudinal dependency of precipitation in the high-altitude Indus basin. The available observations signified the importance of orography in each sub-hydrological basin but could not infer an accurate distribution of precipitation with altitude. We used Kriging with External Drift (KED) interpolation scheme with elevation as a predictor to appraise spatiotemporal distribution of mean monthly, seasonal and annual precipitation for the period of 1998-2012. The KED-based annual precipitation estimates are verified by the corresponding basin-wide observed specific runoffs, which show good agreement. In contrast to earlier studies, our estimates reveal substantially higher precipitation in most of the sub-basins indicating two distinct rainfall maxima; 1st along southern and lower most slopes of Chenab, Jhelum, Indus main and Swat basins, and 2nd around north-west corner of Shyok basin in the central Karakoram. The study demonstrated that the selected gridded precipitation products covering this region are prone to significant errors. In terms of quantitative estimates, ERA-Interim is relatively close to the observations followed by WFDEI and TRMM, while APHRODITE gives highly underestimated precipitation estimates in the study area. Basin-wide seasonal and annual correction factors introduced for each gridded dataset can be useful for lumped hydrological modelling studies, while the estimated precipitation distribution can serve as a basis for bias correction of any gridded precipitation products for the study area.
由于原地观测的稀缺性以及高地形的影响,使得人们无法全面评估印度河流域高海拔集水区的降水分布。现有的数据通常是零散的,分布在不同的组织中,而且大部分都覆盖在山谷中。在这里,我们将大部分可用的站数据与主要冰川积累区的间接降水估计相结合,以分析印度河流域高海拔地区降水的海拔依赖性。现有的观测结果表明地形在每个次水文盆地中的重要性,但无法推断出与海拔相关的降水准确分布。我们使用了带有海拔作为预测因子的外部漂移克里金(KED)插值方案,来评估 1998-2012 年期间的逐月、季节性和年平均降水的时空分布。基于 KED 的年降水估计值与相应的全流域观测到的特定径流量进行了验证,结果显示吻合度较好。与早期的研究相比,我们的估计值显示在大多数次流域中降水明显更高,表明有两个明显的降雨高峰;第一个在 Chenab、Jhelum、Indus 主河和 Swat 流域的南部和最下部以及南部和最下部的斜坡上,第二个在喀喇昆仑山脉中部的 Shyok 流域的西北角。研究表明,覆盖该地区的选定网格化降水产品容易出现显著误差。在定量估计方面,ERA-Interim 与观测值较为接近,其次是 WFDEI 和 TRMM,而 APHRODITE 在研究区域内给出的降水估计值则明显过低。为每个网格化数据集引入的流域范围的季节性和年度修正因子对于集中式水文模型研究可能是有用的,而估计的降水分布可以作为对研究区域内任何网格化降水产品进行偏差修正的基础。