Hydrological Extremes and Responses to Climate Change in the Kelantan River Basin, Malaysia, Based on the CMIP6 HighResMIP Experiments
Hydrological Extremes and Responses to Climate Change in the Kelantan River Basin, Malaysia, Based on the CMIP6 HighResMIP Experiments
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DOI：
10.3390/w13111472
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发表时间：
2021-05
期刊：
影响因子：
3.4
通讯作者：
M. Tan;Ju Liang;N. Samat;N. Chan;J. Haywood;K. Hodges
中科院分区：
文献类型：
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作者：
M. Tan;Ju Liang;N. Samat;N. Chan;J. Haywood;K. Hodges
这项研究介绍了一个水文气候极端评估框架，该框架将来自耦合模式对比项目第六阶段(CMIP6)HighResMIP的最新气候模拟与土壤和水评估(SWAT)模式相结合，并研究了不同气候模式分辨率的影响。根据水文变化指标(IHA)计算了66个水文和环境流量指标，以评估马来西亚基兰丹河流域(KRB)未来的极端流量，该流域特别容易发生洪水。结果表明，到2021-2050年期间，年降水量、径流量、最高气温和最低气温预计将比1985-2014年基准线分别增加6.9%、9.9%、0.8℃和0.9℃。月降水量和径流量预计将增加，特别是西南季风(6-9月)和东北季风初期(12月)。预计1、3、7、30和90天的最小流量增加7.2%~8.2%，最大流量增加10.4%~28.4%。最后，未来水文气候极值的变化在高分辨率和低分辨率模式之间往往有很大不同，例如，高分辨率模式预计11月-12月-1月的月平均流量增加11.8%，而低分辨率模式为3.2%。
This study introduces a hydro-climatic extremes assessment framework that combines the latest climate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP with the Soil and Water Assessment (SWAT) model, and examines the influence of the different climate model resolutions. Sixty-six hydrological and environmental flow indicators from the Indicators of Hydrologic Alteration (IHA) were computed to assess future extreme flows in the Kelantan River Basin (KRB), Malaysia, which is particularly vulnerable to flooding. Results show that the annual precipitation, streamflow, maximum and minimum temperatures are projected to increase by 6.9%, 9.9%, 0.8 °C and 0.9 °C, respectively, by the 2021–2050 period relative to the 1985–2014 baseline. Monthly precipitation and streamflow are projected to increase especially for the Southwest Monsoon (June–September) and the early phase of the Northeast Monsoon (December) periods. The magnitudes of the 1-, 3-, 7-, 30- and 90-day minima flows are projected to increase by 7.2% to 8.2% and the maxima flows by 10.4% to 28.4%, respectively. Lastly, changes in future hydro-climatic extremes are frequently quite different between the high-resolution and low-resolution models, e.g., the high-resolution models projected an increase of 11.8% in mean monthly flow in November-December-January compared to 3.2% for the low-resolution models.