基于WRF-Hydro模式的沂河流域水文气象模拟参数优化研究

doi:10.3969/j.issn.1673-503X.2023.02.003

摘要/Abstract

摘要：

为优化适用于沂河流域WRF-Hydro模式水文气象预报模拟的参数方案, 利用中国区域地面气象要素驱动数据与沂河流域内气象站点实测降雨数据驱动WRF-Hydro模式, 采用分布率定法对模式几项主要的水文参数进行参数率定分析, 选取相似暴雨引发的洪水过程对率定结果进行参数拟合验证。结果表明: WRF-Hydro模式的入渗系数和地表粗糙度对产流量影响具有非线性特征; 河道曼宁糙率同时对产流量和汇流速度均有较明显的影响, 曼宁糙率系数越小, 汇流速度越快, 产流量越大, 峰现时间越早。入渗系数和河道曼宁糙率在所有率定参数中最敏感, 尤其在非饱和土壤条件下。当入渗系数和河道曼宁糙率乘子分别为1.5和0.7、地表持水深度和地表粗糙度取模式默认值1.0时, 径流过程模拟效果最优。

关键词: 淮河流域, WRF-Hydro模式, 径流模拟, 参数率定

Abstract:

In order to optimize the parameter scheme suitable for WRF-Hydro hydro-meteorological forecast and simulation in the Yihe River Basin, the distribution calibration method was adopted to analyze several main hydrological parameters of WRF-Hydro model, which was driven by the China meteorological forcing dataset (CMFD) and precipitation data observed by the meteorological stations in the Yihe River basin.The flooding process caused by similar rainstorms was selected to carry out parameter fitting verification of the calibration results.The results show that the infiltration coefficient and surface roughness of the WRF-Hydro model have nonlinear characteristics on the yield flow.MannN roughness of the river has an obvious influence on both production flow and confluence velocity.The smaller the MannN roughness coefficient is, the faster the confluence speed is, the larger the production flow is and the earlier the peak occurrence time is.The infiltration coefficient and manning roughness are the most sensitive among all the measured parameters, especially in unsaturated soil.When the infiltration coefficient and MannN roughness multiplier are 1.5 and 0.7 respectively, and the default value of surface water holding depth and surface roughness is 1.0, the simulation effect of the runoff process is optimal.

Key words: Huaihe River Basin, WRF-Hydro model, Runoff simulation, Parameter calibration

中图分类号:

P456.7/P338

刘俊杰, 高金兰, 刘蕾, 邵月红, 吴必文, 程智. 基于WRF-Hydro模式的沂河流域水文气象模拟参数优化研究[J]. 气象与环境学报, 2023, 39(2): 20-27.

Jun-jie LIU, Jin-lan GAO, Lei LIU, Yue-hong SHAO, Bi-wen WU, Zhi CHENG. Optimization of hydro-meteorological simulation parameters in Yihe River Basin based on WRF-Hydro model[J]. Journal of Meteorology and Environment, 2023, 39(2): 20-27.

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参考文献 19

1	张浩, 马晓群, 彭妮, 等. 淮河流域冬小麦涝渍灾害损失评估研究[J]. 气象与环境学报, 2015, 31 (6): 123- 129.
2	黄勇, 翟菁, 邱学兴. 淮河流域一次强对流性天气过程的遥感资料分析[J]. 气象与环境学报, 2013, 29 (2): 19- 26.
3	Senatore A , Mendicino G , Gochis D J , et al. Fully coupled atmosphere-hydrology simulations for the central Mediterranean: Impact of enhanced hydrological parameterization for short and long time scales[J]. Journal of Advances in Modeling Earth Systems, 2015, 7 (4): 1693- 1715. doi: 10.1002/2015MS000510
4	Kerandi N , Arnault J , Laux P , et al. Joint atmospheric-terrestrial water balances for East Africa: a WRF-Hydro case study for the upper Tana River basin[J]. Theoretical and Applied Climatology, 2017, 131, 1337- 1355.
5	Arnault J , Wagner S , Rummler T , et al. Role of runoff-Infiltration partitioning and resolved overland flow on land-atmosphere feedbacks: A case study with the WRF-Hydro coupled modeling system for West Africa[J]. Journal of Hydrometeorology, 2016, 17 (5): 1489- 1516. doi: 10.1175/JHM-D-15-0089.1
6	刘昱辰, 刘佳, 李传哲, 等. WRF-Hydro模式在水文模拟与预报应用中的研究进展[J]. 水电能源科学, 2019, 37 (11): 1- 5.
7	Naabil E , Lamptey B L , Arnault J , et al. Water resources management using the WRF-Hydro modelling system: Case-study of the Tono dam in West Africa[J]. Journal of Hydrology: Regional Studies, 2017, 12, 196- 209. doi: 10.1016/j.ejrh.2017.05.010
8	孙明坤, 李致家, 刘志雨, 等. WRF-Hydro模式与新安江模型在陈河流域的应用对比[J]. 湖泊科学, 2020, 32 (3): 850- 864.
9	高玉芳, 吴雨晴, 彭涛, 等. 基于不同降水产品的WRF-Hydro模式径流模拟——以漳河流域为例[J]. 热带气象学报, 2020, 36 (3): 299- 306.
10	许娈, 董美莹, 陈锋. 基于逐时降水站点资料空间插值方法对比研究[J]. 气象与环境学报, 2017, 33 (1): 34- 43.
11	Ryu Y , Lim Y J , Ji H S , et al. Applying a coupled hydrometeorological simulation system to flash flood forecasting over the Korean Peninsula[J]. Asia-Pacific Journal of Atmospheric Sciences, 2017, 53, 421- 430.
12	Yucel I , Onen A , Yilmaz K K , et al. Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall[J]. Journal of Hydrology, 2015, 523, 49- 66.
13	王洁, 郭鹏, 何晓凤, 等. 基于测风塔观测资料的近地层风速平面订正[J]. 气象与环境学报, 2020, 36 (6): 115- 121.
14	王芃, 谈建国, 束炯, 等. 基于数据窗口标准差的边界层高度反演方法——以上海市为例[J]. 气象与环境学报, 2021, 37 (2): 107- 112.
15	田静, 苏红波, 孙晓敏, 等. GDAS数据和NOAH陆面模式在中国应用的精度检验[J]. 地理科学进展, 2011, 30 (11): 1422- 1430.
16	Chen F , Dudhia J . Coupling an advanced land surface-hydrology model with the Penn state-NCAR MM5 modeling system.Part I: Model implementation and sensitivity[J]. Monthly Weather Review, 2001, 129 (4): 569- 585.
17	Wood E F , Lettenmaier b D P , Xu L A , et al. The project for intercomparison of land-surface parameterization schemes (PILPS) phase 2(c) Red-Arkansas River basin experiment: : 1.Experiment description and summary intercomparisons[J]. Global and Planetary Change, 1998, 19 (1/2/3/4): 115- 135.
18	Liu Y C , Liu J , Li C Z , et al. Parameter sensitivity analysis of the WRF-Hydro modeling system for streamflow simulation: a case study in semi-humid and semi-arid catchments of Northern China[J]. Asia-Pacific Journal of Atmospheric Sciences, 2021, 57, 451- 466.
19	Lahmers T M , Gupta H , Castro C L , et al. Enhancing the structure of the WRF-Hydro hydrologic model for semi-arid environments[J]. Journal of Hydrometeorology, 2019, 20 (4): 691- 714.

参数项	参数值
驱动数据时间间隔	3 h
模型输出数据间隔	1 h
陆面模式	NoahMP
汇流网格计算步长	6 s
汇流网格距	100 m
陆面模式网格距	1000 m
土层厚度	10 cm, 30 cm, 60 cm, 100 cm
次表面径流	开启(DHSVM)
坡面流	开启(D8法)
河道汇流	开启(扩散波)
概念水箱模型	关闭

过程序号	开始时间	结束时间	平均累积雨量/mm	时间C_v值	空间C_v值
过程1	2003年6月22日08时	2003年6月24日08时	98.70	0.50	0.08
过程2	2005年6月25日20时	2005年6月28日20时	69.30	0.75	0.25

参数项	参数试验值	RSR	NSE
REFKDT	0.5	2.04	-3.25
	1.0	0.74	0.44
	1.5	0.68	0.53
	2.0	0.78	0.37
	2.5	0.86	0.24
	3.0	0.92	0.14

参数项	参数试验值	RSR	NSE
OVROUGHRTFAC(REFKDT=1.5，RETDEPRTFAC=1.0)	0.0	0.41	0.83
	0.1	1.27	-0.65
	0.3	0.78	0.37
	0.6	0.51	0.74
	0.9	0.42	0.82
	1.0	0.41	0.83

参数项	参数试验值	RSR	NSE
MannN(REFKDT=1.5、RETDEPRTFAC=1.0、OVROUGHRTFAC=1.0)	0.5	1.06	-0.15
	0.7	0.45	0.80
	0.8	0.41	0.83
	1.0	0.68	0.53
	1.2	0.94	0.10
	1.5	1.13	-0.31