气候变化领域集成服务门户(CCPortal): Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data

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DOI	10.1007/s11629-021-6727-1
	Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data
	Yang Fan; Lu Hui; Yang Kun; Huang Guang-wei; Li Yi-shan; Wang Wei; Lu Ping; Tian Fu-qiang; Huang Yu-gang
通讯作者	Lu, H (通讯作者)
发表日期	2021
ISSN	1672-6316
EISSN	1993-0321
起始页码	2982
结束页码	3002
卷号	18 期号:11
英文摘要	The Nu-Salween River (NSR), the longest free-flow river in Southeast Asia, plays an irreplaceable role in social development and ecological protection. The lower NSR region is particularly valuable as it is inhabited by approximately 6.7 million people. The basin has limited hydraulic conservancy infrastructure and insufficient ability to cope with climate change risks. Studying the hydrological characteristics and changes in the basin provides the scientific basis for rational protection and development of the basin. However, owing to the limitation of observation data, previous studies have focused on the local area and neglected the study of the lower reaches, which is not enough to reflect the spatial characteristics of the entire basin. In this study, the ECMWF 5th generation reanalysis data (ERA5) and Multi-Source Weighted-Ensemble Precipitation (MSWEP) were applied to develop a geomorphology-based hydrological model (GBHM) for reconstructing hydrological datasets (i.e. GBHM-ERA5 and GBHM-MSWEP). The reconstructed datasets covering the complete basin were verified against the gauge observation and compared with other commonly used streamflow products, including Global Flood Awareness System v2.1, GloFAS-Reanalysis dataset v3.0, and linear optimal runoff aggregate (LORA). The comparison results revealed that GBHM-ERA5 is significantly better than the other four datasets and provides a good reproduction of the hydrological characteristics and trends of the NSR. Detailed analysis of GBHM-ERA5 revealed that: (1) A multi-year mean surface runoff represented 39% of precipitation over the basin during 1980-2018, which had low surface runoff in the upstream, while areas around the Three Parallel Rivers Area and the estuary had abundant surface runoff. (2) The surface runoff and discharge coefficient of variations in spring were larger than those in other seasons, and the inter-annual variation in the downstream was smaller than that in the upstream and midstream regions. (3) More than 70% of the basin areas showed a decreasing trend in the surface runoff, except for parts of Nagqu, south of Shan State in Myanmar, and Thailand, where surface runoff has an increasing trend. (4) The downstream discharge has dropped significantly at a rate of approximately 680 million cubic metres per year, and the decline rate is greater than that of upstream and midstream, especially in summer. This study provides a data basis for subsequent studies in the NSR basin and further elucidates the impact of climate change on the basin, which is beneficial to river planning and promotes international cooperation on the water- and eco-security of the basin.
关键词	FLOW REGIMES SIMULATION MANAGEMENT SATELLITE UPSTREAM PRODUCTS RAINFALL RUNOFF SYSTEM
英文关键词	Nu-Salween River; Distributed hydrologic model; ERA5; Surface runoff; Discharge; Climate Change
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
WOS记录号	WOS:000710381900007
来源期刊	JOURNAL OF MOUNTAIN SCIENCE
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/260439
推荐引用方式 GB/T 7714	Yang Fan,Lu Hui,Yang Kun,et al. Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data[J]. 中国科学院青藏高原研究所,2021,18(11).
APA	Yang Fan.,Lu Hui.,Yang Kun.,Huang Guang-wei.,Li Yi-shan.,...&Huang Yu-gang.(2021).Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data.JOURNAL OF MOUNTAIN SCIENCE,18(11).
MLA	Yang Fan,et al."Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data".JOURNAL OF MOUNTAIN SCIENCE 18.11(2021).