基于水资源分区的黄河流域极端降水时空变化特征

探究和预估气候变化下黄河流域极端降水的变化特征,是科学认知黄河水情以及支撑流域防洪减灾工作的基础。本文基于全国水资源二级分区,综合采用“中国区域地面气象要素驱动数据集”和跨部门影响模型相互比较项目（ISIMIP）的降水数据,利用Mann-Kendall趋势检验、Sen’s斜率估计等方法分析了黄河流域及其8个二级水资源分区的6个极端降水指标在历史期（1979—2018年）和未来期（2021—2100年）的时空变化特性。研究表明：①空间上,历史期与未来不同情景下黄河流域极端降水指标值在整体上均呈现由西北至东南逐渐增大的变化特征,在河口镇至龙门（Ⅳ）、龙门至三门峡（Ⅴ）等分区内部还出现了极端降水高值中心,这些区域高值中心与历史洪水爆发区具有较好的空间对应关系;②时间上（历史期）,多数水资源分区的极端降水指标主要呈上升趋势,且小时尺度极端降水增强是所有分区的统一特征;作为黄河干流洪水主要来源区的兰州以上（Ⅰ和Ⅱ）、河口镇至龙门（Ⅳ）、花园口以下（Ⅶ）分区的所有极端降水指标呈上升趋势;③时间上（未来期）,在不同辐射强迫情景下,未来各水资源分区的极端降水指标值都呈增加趋势,且增加幅度和空间覆盖范围会随着辐射强迫的增大而增大,这将加剧黄河分区防洪形势,其中河口镇以上3个分区（Ⅰ、Ⅱ、Ⅲ）和龙门至三门峡（Ⅴ）分区的极端降水增强幅度最为明显,是未来防洪重点区。本文结果可为黄河流域未来极端降水灾害风险评估、区域防洪风险分析及应对、雨洪水资源管理等提供参考。

Spatiotemporal variations of extreme precipitation in the Yellow River Basin based on water resources regionalization

Investigating the change characteristics of extreme precipitation in the Yellow River Basin (YRB) is essential for understanding the hydrologic regime and reducing flood losses. In this study, based on the national secondary water resources regionalization, the spatiotemporal variations of the six extreme precipitation indicators of the YRB and its eight subregions were analyzed for the historical period (1979-2018) and the future period (2021-2100) using the Mann-Kendall test and Sen’s slope estimator. The precipitation data for the two periods were obtained from the China Meteorological Forcing Dataset and the Inter-Sectoral Impact Model Intercomparison Project, respectively. The results show that: (1) Values of the six extreme precipitation indicators increase from northwest to southeast in the YRB during the two periods from a spatial perspective. The areas with high indicator values appear in the Hekou-Longmen subregion and the Longmen-Sanmenxia subregion, which correspond to sites with frequent floods. (2) From a temporal perspective, the hourly-scale indicator values increase in all subregions, and values of the rest five indicators increase in most subregions during the historical period. As significant flood source areas, the four subregions (above Longyangxia, Longyangxia-Lanzhou, Hekou-Longmen, and below Huayuankou) all experience an increase in values of the six indicators. (3) Values of the six indicators of all subregions increase in the three future emission scenarios, with larger increments in higher greenhouse gas emission scenarios. The increasing trends of all the indicators would prevent effective flood prevention. The three subregions above Hekou and the Longmen-Sanmenxia subregion with significant growing trends are critical areas for future flood prevention. The results could provide a valuable reference for future risk assessment of extreme precipitation, regional flood risk analysis and prevention, and water resources management in the YRB.