雅鲁藏布江流域多源降水产品评估及其在水文模拟中的应用

doi:10.18306/dlkxjz.2020.07.006

Abstract

Abstract:

The gauge-based precipitation data from the National Climate Center, China Meteorological Administ-ration (CMA), Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record (PERSIANN-CDR), Global Precipitation Measurement (GPM), Global Land Data Assimilation System (GLDAS), High Asia Refined analysis (HAR) are compared with each other and evaluated by the precipitation data from 16 national meteorological stations during 1980-2016 in the Yarlung Zangbo River and its sub-basins. The potential utilities of these multiple precipitation datasets are then systematically evaluated as inputs for the variable infiltration capacity (VIC) macroscale land surface hydrologic model. The results show that: 1) PERSIANN-CDR and GLDAS contain the largest precipitation estimates among the six datasets with mean annual precipitation of 770-790 mm, followed by the HAR and GPM (650-660 mm), while CMA and APHRODITE contain the lowest precipitation estimates with mean annual precipitation of 460-500 mm. All the products can detect the large-scale monsoon-dominated precipitation regime in the Yarlung Zangbo River and its sub-basins with 70%-90% of annual total precipitation occurring in June-September except the GPM. 2) The general spatial pattern of the annual mean precipitation fields is roughly in agreement among the six datasets, with a decreasing trend from the southeast to the northwest in the Yarlung Zangbo River Basin except the PERSIANN-CDR and GLDAS. 3) Relative to the data from the national meteorological stations, APHRODITE, GPM, and HAR generally underestimate precipitation by 10%-30%, while PERSIANN-CDR and GLDAS overestimate precipitation from stations in upstream sub-basins by 28%-60% and underestimate precipitation from stations in downstream sub-basins by 11%-21%. 4) The six precipitation datasets cannot satisfy the needs of hydrological simulation in term of accuracy or period in the basin. 5) HAR precipitation data—output of regional climate model—show more reasonable amount and seasonal pattern among the six datasets in the upper Brahmaputra according to the inverse evaluation by VIC hydrological model.

Key words: precipitation estimate, hydrological simulation, the Yarlung Zangbo River, Tibetan Plateau

SUN He, SU Fengge. Evaluation of multiple precipitation datasets and their potential utilities in hydrologic modeling over the Yarlung Zangbo River Basin[J].PROGRESS IN GEOGRAPHY, 2020, 39(7): 1126-1139.

Figures/Tables 11

Fig.1

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Tab.2

Fig.2

Tab.3

Fig.3

Fig.4

Tab.4

Fig.5

Tab.5

Fig.6

References 38

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	拉孜	拉孜—奴各沙	日喀则	拉萨	奴各沙—羊村	羊村—奴下	奴下—巴昔卡
水文观测站	拉孜站	奴各沙站	日喀则站	拉萨站	羊村站	奴下站	—
经度位置/(°E)	29.05	29.32	29.25	29.63	29.28	29.47	28.10
纬度位置/(°N)	87.38	89.71	88.88	91.15	91.88	94.57	95.53
流域面积/km²	50553	45327	11064	26235	26599	41770	51507
流域平均海拔/m	5370	4983	5353	5272	4767	4937	3711
研究时段	1980—2000年	1980—2000年	1980—2000年	1980—2000年	1980—2000年	1980—2000年	—
实测径流/(m³/s)	172.18	202.15	55.16	300.02	163.87	920.31	—
对总径流贡献/%	9.17	11.09	3.76	15.98	8.99	51.01	—
冰川面积/km²	835.40	145.90	129.50	266.50	458.14	1104.36	5351.76
冰川占比/%	1.60	0.41	1.21	0.98	1.71	2.81	10.21
积雪覆盖比例/%	15.58	7.12	6.98	23.08	10.21	24.25	31.97

降水数据	研究时段	时空分辨率	数据类别	来源
CMA	1980—2016年	1/12°、逐日	站点插值数据	国家气象局
APHRODITE	1979—2007年	0.25°、逐日	基于站点数据	Yatagai等^[21]
PERSIANN-CDR	1983—2016年	0.25°、6 h	遥感卫星数据	Ashouri等^{[22 ]}
GPM	2015—2016年	0.10°、逐日	遥感卫星数据	Huffman等^[23]
GLDAS	1980—2016年	0.25°、3 h	再分析数据	Rodell等^[24]
HAR	2001—2013年	10 km、逐日	区域气候模式输出	Maussion等^[19]

子流域	站点	APHRODITE		GPM		PERSIANN-CDR		GLDAS		HAR
子流域	站点	相关系数	相对误差/%	相关系数	相对误差/%	相关系数	相对误差/%	相关系数	相对误差/%	相关系数	相对误差/%
拉孜	拉孜	0.57	9.00	0.88	-2.03	0.57	59.51	0.38	59.01	0.60	-42.27
拉孜—奴各沙	南木林	0.99	-6.60	0.93	-89.04	0.46	28.61	0.32	39.96	0.65	-8.74
日喀则	日喀则	0.99	-0.11	0.87	-24.50	0.57	34.47	0.54	48.66	0.26	-54.61
日喀则	江孜	0.98	4.65	0.98	9.99	0.68	58.07	0.46	69.62	0.63	-4.40
拉萨	拉萨	0.99	-7.71	-0.14	-34.29	0.17	37.23	0.47	34.43	0.21	-139.09
	当雄	0.93	-0.77	0.89	-20.13	0.42	23.28	0.62	15.83	0.25	35.88
	墨竹工卡	0.99	-26.08	0.85	-70.72	0.45	23.54	0.36	20.12	0.12	-52.48
奴各沙—羊村	泽当	0.99	3.44	0.88	-10.57	0.39	57.02	0.54	46.46	0.19	-13.82
	尼木	0.94	-0.39	0.89	-51.80	0.87	45.24	0.65	55.20	0.20	-32.65
	浪卡子	0.99	1.08	0.93	6.61	0.67	47.97	0.45	59.91	0.20	39.57
	贡嘎	0.88	-13.44	0.89	-33.30	0.45	42.21	0.47	50.70	0.15	18.15
羊村—奴下	加查	0.99	7.74	0.91	-42.40	0.49	52.73	0.15	31.54	-0.20	-55.70
	米林	0.99	-6.60	0.70	11.38	0.79	28.07	0.38	27.32	0.35	-120.23
	林芝	0.98	-3.58	0.98	-9.63	0.64	29.81	0.41	8.91	0.09	-49.92
奴下—巴昔卡	嘉黎	0.99	6.26	0.08	-34.49	0.38	29.59	0.26	-19.39	0.03	18.09
奴下—巴昔卡	波密	0.99	-8.63	0.94	-50.42	0.67	-11.15	0.43	-20.95	0.09	-11.07

子流域	CMA		APHRODITE		GLDAS		PERSIANN-CDR
子流域	纳什系数	相对误差/%	纳什系数	相对误差/%	纳什系数	相对误差/%	纳什系数	相对误差/%
拉孜	0.40	-29.9	0.60	-28.6	-19.90	301.9	-51.60	383.6
拉孜—奴各沙	0.80	-29.5	0.35	-49.2	-0.70	170.7	-1.40	130.8
日喀则	0.50	-41.7	0.20	-56.3	-12.70	264.8	-3.30	159.2
拉萨	0.60	-41.6	0.50	-48.2	0.70	-35.8	0.50	34.7
奴各沙—羊村	0.20	-54.9	-0.10	-70.3	-0.20	89.1	0.60	81.4
羊村—奴下	-0.20	-69.6	-0.40	-76.4	0.10	-53.9	0.80	5.8

Evaluation of multiple precipitation datasets and their potential utilities in hydrologic modeling over the Yarlung Zangbo River Basin

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降水产品	年均	春季	夏季	秋季	冬季	降水产品	年均	春季	夏季	秋季	冬季
拉孜						奴各沙—羊村
CMA	325	50	177	60	37	CMA	385	35	282	66	2
APHRODITE	254	33	152	44	25	APHRODITE	360	35	256	65	4
PERSIANN-CDR	739	81	503	105	49	PERSIANN-CDR	803	118	527	140	17
GPM	308	59	140	40	68	GPM	284	35	187	53	9
HAR	466	50	287	68	61	HAR	495	70	318	96	12
GLDAS	721	127	422	115	57	GLDAS	792	82	578	130	2
拉孜—奴各沙						羊村—奴下
CMA	379	26	288	58	7	CMA	559	97	343	110	9
APHRODITE	314	22	237	51	4	APHRODITE	537	94	329	103	11
PERSIANN-CDR	814	104	541	143	27	PERSIANN-CDR	1025	193	609	190	33
GPM	258	26	181	45	6	GPM	528	110	291	111	15
HAR	545	59	369	101	15	HAR	719	135	396	161	28
GLDAS	789	89	551	129	19	GLDAS	729	106	490	127	6
日喀则						奴下—巴昔卡
CMA	343	27	261	53	2	CMA	705	177	350	158	20
APHRODITE	328	28	242	55	3	APHRODITE	981	225	520	204	32
PERSIANN-CDR	657	96	433	111	16	PERSIANN-CDR	883	204	465	177	36
GPM	331	54	214	56	8	GPM	1011	263	498	218	32
HAR	328	40	207	71	10	HAR	1430	328	657	337	108
GLDAS	937	104	666	160	7	GLDAS	828	156	496	157	18
拉萨						雅鲁藏布江
CMA	506	62	342	95	8	CMA	465	73	288	89	15
APHRODITE	504	66	330	99	10	APHRODITE	500	84	305	96	16
PERSIANN-CDR	765	122	484	140	19	PERSIANN-CDR	773	118	449	183	24
GPM	414	70	246	85	13	GPM	660	135	400	105	19
HAR	566	50	287	68	61	HAR	650	106	368	133	39
GLDAS	566	55	411	97	3	GLDAS	786	123	509	131	24