基于不同降水产品的WRF-Hydro模式径流模拟——以漳河流域为例

高玉芳; 吴雨晴; 彭涛; 顾天威

doi:10.16032/j.issn.1004-4965.2020.028

基于不同降水产品的WRF-Hydro模式径流模拟——以漳河流域为例

doi: 10.16032/j.issn.1004-4965.2020.028

1.
南京信息工程大学应用气象学院，江苏南京 210044
2.
中国气象局武汉暴雨研究所/湖北省暴雨监测与预警重点试验室，湖北武汉 430205
3.
南京信息工程大学大气科学学院，江苏南京 210044

基金项目:

国家自然科学基金项目 41675102

国家重点研发计划项目 2017YFC1502102

详细信息

通讯作者:
高玉芳，女，山东省人，副教授，博士，主要从事水文气象方面的研究。E-mail：gaoyf@nuist.edu.cn

中图分类号: P456.7
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- 文章访问数: 216
- HTML全文浏览量: 28
- PDF下载量: 19
- 被引次数: 0
出版历程
- 收稿日期: 2019-09-16
- 修回日期: 2020-04-16
- 刊出日期: 2020-06-01

APPLICATION OF WRF-HYDRO FOR RUNOFF SIMULATION BASED ON DIFFERENT RAINFALL PRODUCTS: TAKING ZHANGHE RIVER BASIN AS AN EXAMPLE

1.
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
Institute of Heavy Rain, CMA/ Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Wuhan 430205, China
3.
School of Atmoshpheric Science, Nanjing University of information Science & Technology, Nanjing210044, China

摘要

摘要: 以漳河流域为研究区域，以CMORPH卫星-地面自动站-雷达三源降水融合数据和ERA5再分析降水资料为WRF-Hydro模式的输入，进行径流模拟，对比分析模拟径流与实测径流的差异，探讨基于两种降水数据的WRF-Hydro模式在漳河流域的径流模拟效果。结果表明：三源降水融合数据的径流模拟效果较优，纳什系数均达到0.7以上，模拟径流与实测径流过程吻合较好；采用三源降水融合数据和ERA5再分析降水资料率定WRF-Hydro模式，以ERA5再分析降水资料为输入，径流模拟结果都不佳；总体而言，三源降水融合数据与WRF-Hydro模式耦合能够较好地模拟漳河流域径流过程。
- WRF-Hydro模式 /
- CMORPH卫星-地面自动站-雷达三源降水融合数据 /
- ERA5再分析资料 /
- 径流模拟
Abstract: Taking Zhanghe River Basin as the study area, the present study used the high-resolution radar-satellite-gauge merged precipitation products and reanalysis precipitation data from ERA5 as input for the WRF-Hydro model for runoff simulation. To explore the accuracy of runoff simulation in Zhanghe River Basin based on the WRF-Hydro model of two precipitation data, we compared and analyzed the difference between simulated runoff and observation runoff. The results show that the three-source merged precipitation products perform better with the Nash efficiency coefficient above 0.7, and the simulated hydrological process curves agree well with the observed hydrological process curves. With the three-source merged precipitation products and the ERA5 reanalysis data calibrated to the WRF-Hydro model, the simulation results are not satisfying with the ERA5 reanalysis data as input. In general, the three-source merged precipitation products combined with the WRF-Hydro model can better simulate the runoff process in the Zhanghe River Basin.
- WRF-Hydro model /
- the high-resolution radar-satellite-gauge merged precipitation products /
- ERA5 reanalysis data /
- runoff simulation

HTML全文

图 1 漳河流域高程及水系分布

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图 2 WRF-Hydro模式运行框架图

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图 3 4场洪水过程对应时期的总降雨量的空间分布图

a、e. 201506；b、f. 201606；c、g. 201607；d、h：201807。a~d.三源降水融合产品，e~h. ERA5再分析降水资料。

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图 4 4场洪水过程对应时期的1 h面雨量的时间序列图

a. 201506；b. 201606；c：201607；d. 201807。

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图 5 情景1下两种降水产品的径流模拟过程

a、b.三源降水融合产品；c、d. ERA5再分析降水资料；a、c. 201606，b、d. 201607。

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图 6 情景2下ERA5再分析降水资料的径流模拟过程

a. 201606；b. 201607。

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表 1 WRF-Hydro模式关键敏感性参数

类别	参数	中文名称	英文名称	默认数值
径流量影响参数	REFKDT	下渗率	infiltration factor	3.0
	RETDEPRT	地表持水深	surface retention depth	1.0
	SLOPE	控制深层排水的系数	coefficient governing deep drainage	系列数
	MannN	曼宁糙率	channel Manning roughness	系列数
水文过程影响参数	OVROUGHRT	地表糙率	surface roughness	1.0
	LKSATFAC	饱和土壤侧向导水率	saturated soil lateral conductivity	系列数
	REFDK	饱和导水率	saturated hydraulic conductivity	2.0×10^-6

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表 2 两种情景下WRF-Hydro模型参数率定结果

情景	REFKDT	MannN	RETDEPRTFAC	OVROUGHRTFAC
情景1	0.53	0.30	1.0	1.0
情景2	0.80	0.25	1.0	1.0

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表 3 两种情景下径流模拟结果的各评价指标值

情景	降水数据	洪水场次	E_R/%	RE_p/%	ΔT/h	R	NSE
情景1	三源降水融合产品	201606	-33.10	-5.61	0	0.91	0.72
	三源降水融合产品	201607	-52.99	-82.06	3	0.68	0.12
	ERA5	201606	33.19	130.61	3	0.62	-2.65
	ERA5	201607	0.68	-31.74	27	0.28	-0.12
情景2	ERA5	201606	-28.03	67.58	3	0.56	-0.99
情景2	ERA5	201607	-6.04	-16.54	24	0.31	-0.35

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