三峡水库上游流域季节降水预报效果评价

doi:10.11988/ckyyb.20230976

新澳门游戏网站入口院报 ›› 2025, Vol. 42 ›› Issue (1): 28-34.DOI: 10.11988/ckyyb.20230976

三峡水库上游流域季节降水预报效果评价

谢帅¹^,²^,³(), 张森¹^,², 王永强¹^,²(), 刘杨合³

¹ 新澳门游戏网站入口水资源综合利用研究所,武汉 430010
² 新澳门游戏网站入口流域水资源与生态环境科学湖北省重点实验室,武汉 430010
³ 中国长江电力股份有限公司智慧长江与水电科学湖北省重点实验室,湖北宜昌 443000

收稿日期:2023-09-07 修回日期:2024-01-08 出版日期:2025-01-01 发布日期:2025-01-01
通信作者:
王永强(1982-),男,河南郑州人,正高级工程师,博士,研究方向为水文水资源。E-mail:wangyq@mail.crsri.cn
作者简介:
谢帅(1993-),男,河南南阳人,高级工程师,博士,研究方向为水文水资源。E-mail:xieshuai@mail.crsri.cn
基金资助:
国家重点研发计划项目(2022YFC3202302); 湖北省自然科学基金项目(2024AFA011); 湖北省自然科学基金项目(2023AFB039); 湖北省自然科学基金项目(2022CFD027); 武汉市知识创新专项基础研究项目(2022020801010240); 长江水澳门网络游戏网站官网首联合基金项目(U2040212); 水利部重大科技项目(SKS-2022120); 中国长江电力股份有限公司资助项目(Z242302057)

Evaluation of Seasonal Precipitation Forecasting for the Upstream of the Three Gorges Reservoir

XIE Shuai¹^,²^,³(), ZHANG Sen¹^,², WANG Yong-qiang¹^,²(), LIU Yang-he³

¹ Water Resources Department, Changjiang River Scientific Research Institute, Wuhan 430010, China
² Hubei Key Laboratory of Water Resources & Eco-environmental Sciences, Changjiang River Scientific Research Institute, Wuhan 430010, China
³ Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co., Ltd., Yichang 443000, China

Received:2023-09-07 Revised:2024-01-08 Published:2025-01-01 Online:2025-01-01

摘要/Abstract

摘要：

在气候变化条件下,季节降水预报对于中长期的水资源配置和综合利用具有重要的作用。不同的季节降水预报产品各有优劣,为了从中选择最合适的预报产品,基于8种降水预报模型在三峡水库上游流域的1~6个月预见期的预报结果,对比分析了其在不同子流域的确定性预报和集合预报效果,筛选了不同子流域的最优预报模型。结果表明:不同预见期下、不同子流域的最优预报模型均有所差异;整体来看ECCC3、ECMWF、CMCC预测模型的预报效果较好;在整个三峡水库上游流域,预见期为1个月、2~6个月预见期时预报效果表现最好的分别为ECCC3模型、ECMWF模型;在金沙江上游、乌东德上游,ECCC3模型较好,在金沙江下游、乌江、向家坝—寸滩、寸滩—三峡,CMCC模型较好,在岷江,ECMWF模型较好,在沱江,MF模型较好。通过选取各个子流域的最优预报模型,可以组合得到三峡水库上游流域的整体预报结果,相比于单一模型的预报,组合后的预报误差降低9.33%~17.86%。

关键词: 季节降水预报, 确定性预报, 集合预报, 预报效果评价, 三峡水库上游

Abstract:

In the background of climate change, seasonal precipitation forecasting is of great importance for mid-long term allocation and comprehensive utilization of water resources. Given that each forecasting product has its unique advantages and disadvantages, we evaluated and compared the forecasting performance of deterministic and ensemble forecasts of eight models with 1-6 months forecast lead time (FLT) for the upstream of the Three Gorges Reservoir (TGR) to select the optimal model for each sub-basin. Results demonstrate that the optimal model may vary across different sub-basins and FLTs. In general, the ECCC3, ECMWF, CMCC models exhibit superior forecasting performance. Specifically, in the upstream of the TGR, the ECCC3 model performs best when the FLT is 1 month, while the ECMWF model excels for FLTs of 2-6 months. In the upstream of the Jinsha River and the Wudongde Project, the ECCC3 model performs the best. Conversely, in the downstream of the Jinsha River, Wujiang River, Xiangjiaba-Cuntan sub-basin, and Cuntan-Three Gorges sub-basin, the CMCC model outperforms other models. The ECMWF model performs the best for the Minjiang River while the MF model for the Tuojiang River. Based on the forecasting results of the optimal models in different sub-basins, we calculated the forecasting precipitation in the upstream of the TGR. Compared with the forecasting results of single best-performing models, the integration of forecasting result for each sub-basin reduces the root mean squared error by 9.33%-17.86%.

Key words: seasonal precipitation forecasting, deterministic forecasts, ensemble forecasts, evaluation of forecasting results, upstream of the Three Gorges Reservoir

中图分类号:

TV213.9水利资源综合利用

谢帅, 张森, 王永强, 刘杨合. 三峡水库上游流域季节降水预报效果评价[J]. 新澳门游戏网站入口院报, 2025, 42(1): 28-34.

XIE Shuai, ZHANG Sen, WANG Yong-qiang, LIU Yang-he. Evaluation of Seasonal Precipitation Forecasting for the Upstream of the Three Gorges Reservoir[J]. Journal of Changjiang River Scientific Research Institute, 2025, 42(1): 28-34.

图/表 10

图1 研究区域

Fig.1 The upstream basin of the Three Gorges Reservoir

表1 季节降水预报数据概况

Table 1 Overview of the seasonal precipitation forecasting data

机构	预报系统名称	预报时段及时空精度	预报期集合预报成员数	回报年限	回报期集合预报成员数
ECMWF	SEAS5	至2022年12月的未来6个月内逐月预报结果,均为1°×1°网格数据	51	1993—2016	25
UKMO	GloSea6		62	1993—2016	28
MF	System 8		51	1993—2018	25
CMCC	SPS3.5		50	1993—2016	40
DWD	GCFS2.1		50	1993—2019	30
NCEP	CFSv2		120	1993—2016	28
ECCC2	CanCM4i		10	1993—2020	10
ECCC3	GEM5- NEMO		10	1993—2020	10

图2 ECCC3模型在不同流域的预报效果评估指标

Fig.2 Criteria of forecasting performance of ECCC3 model for different basins

图3 ECMWF模型在不同流域的预报效果评估指标

Fig.3 Criteria of forecasting performance of ECMWF model for different basins

图4 各模型在三峡水库上游的预报效果对比

Fig.4 Comparison of forecasting performance among different models for the upstream of TGR

图5 各模型在乌东德上游的预报效果对比

Fig.5 Comparison of forecasting performance among different models for the upstream of Wudongde Hydropower Station

图6 预见期1个月时各模型的预报效果对比

Fig.6 Comparison of forecasting performance among different models with 1-month FLT

图7 不同预报模型在各月份的预报效果对比

Fig.7 Comparison of forecasting performance among different models in different months

表2 最优预报模型

Table 2 Optimal forecasting models for various sub-basins with different FLTs

区域	不同预见期时最优模型
区域	1个月	2个月	3个月	4个月	5个月	6个月
金沙江上游	ECCC3	ECCC3	ECCC3	ECCC3	ECCC3	ECCC3
金沙江中游	ECCC3	ECMWF	ECMWF	ECMWF	ECMWF	ECMWF
金沙江下游	CMCC	CMCC	CMCC	CMCC	CMCC	CMCC
向家坝— 寸滩	CMCC	CMCC	CMCC	CMCC	CMCC	CMCC
寸滩—三峡	CMCC	CMCC	CMCC	CMCC	CMCC	CMCC
雅砻江	ECMWF	ECMWF	ECMWF	ECCC3	ECCC3	ECCC3
岷江	ECMWF	ECMWF	ECMWF	ECMWF	ECMWF	ECMWF
沱江	MF	MF	MF	MF	MF	MF
嘉陵江	ECCC3	MF	MF	MF	ECMWF	ECMWF
乌江	CMCC	CMCC	CMCC	CMCC	CMCC	CMCC
乌东德上游	ECCC3	ECCC3	ECCC3	ECCC3	ECCC3	ECCC3
三峡水库上游	ECCC3	ECMWF	ECMWF	ECMWF	ECMWF	ECMWF

表3 各子流域最优模型组合和单一最优模型的三峡水库上游预报效果对比

Table 3 Comparison of forecasting performance between the integration of best-performing models for different sub-basins and the single best-performing model

预见期/月	单一最优模型的 RMSE/mm	各子流域最优模型组合后的RMSE/mm	相对变化/%
1	31.98	26.27	-17.86
2	32.12	27.18	-15.36
3	30.91	26.69	-13.66
4	30.41	26.24	-13.73
5	30.01	26.81	-10.66
6	29.66	26.89	-9.33

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三峡水库上游流域季节降水预报效果评价

Evaluation of Seasonal Precipitation Forecasting for the Upstream of the Three Gorges Reservoir

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