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| DOI | 10.5194/hess-28-1873-2024 |
| Variation and attribution of probable maximum precipitation of China using a high-resolution dataset in a changing climate | |
| 发表日期 | 2024 |
| ISSN | 1027-5606 |
| EISSN | 1607-7938 |
| 起始页码 | 28 |
| 结束页码 | 8 |
| 卷号 | 28期号:8 |
| 英文摘要 | Accurate assessment of the probable maximum precipitation (PMP) is crucial in assessing the resilience of high-risk water infrastructures, water resource management, and hydrological hazard mitigation. Conventionally, PMP is estimated based on a static climate assumption and is constrained by the insufficient spatial resolution of ground observations, thus neglecting the spatial heterogeneity and temporal variability of climate systems. Such assumptions are critical, especially for China, which is highly vulnerable to global warming in similar to 100 000 existing reservoirs. Here, we use the finest-spatiotemporal-resolution (1 d and 1 km) precipitation dataset from an ensemble of machine learning algorithms to present the spatial distribution of 1 d PMP based on the improved Hershfield method. Current reservoir design values, a quasi-global satellite-based PMP database, and in situ precipitation are used to benchmark against our results. The 35-year running trend from 1961-1995 to 1980-2014 is quantified and partitioned, followed by future projections using the Coupled Model Inter-comparison Project Phase 6 simulations under two scenarios. We find that the national PMP generally decreases from southeast to northwest and is typically dominated by the high variability of precipitation extremes in northern China and high intensity in southern China. Though consistent with previous project design values, our PMP calculations present underestimations by comparing them with satellite and in situ results due to differences in spatial scales and computation methods. Interannual variability, instead of the intensification of precipitation extremes, dominates the PMP running trends on a national scale. Climate change, mainly attributed to land-atmosphere coupling effects, leads to a widespread increase ( > 20 %) in PMP across the country under the SSP126 scenario, which is projected to be higher along with the intensification of CO 2 emissions. Our observation- and modeling-based results can provide valuable implications for water managers under a changing climate. |
| 语种 | 英语 |
| WOS研究方向 | Geology ; Water Resources |
| WOS类目 | Geosciences, Multidisciplinary ; Water Resources |
| WOS记录号 | WOS:001208289100001 |
| 来源期刊 | HYDROLOGY AND EARTH SYSTEM SCIENCES
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/303003 |
| 作者单位 | Wuhan University; Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Roorkee; University of Oslo |
| 推荐引用方式 GB/T 7714 | . Variation and attribution of probable maximum precipitation of China using a high-resolution dataset in a changing climate[J],2024,28(8). |
| APA | (2024).Variation and attribution of probable maximum precipitation of China using a high-resolution dataset in a changing climate.HYDROLOGY AND EARTH SYSTEM SCIENCES,28(8). |
| MLA | "Variation and attribution of probable maximum precipitation of China using a high-resolution dataset in a changing climate".HYDROLOGY AND EARTH SYSTEM SCIENCES 28.8(2024). |
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