基于多源遥感数据的玛纳斯河流域冰川物质平衡变化

doi:10.11821/dlxb202001008

地理学报 ›› 2020, Vol. 75 ›› Issue (1): 98-112.doi: 10.11821/dlxb202001008

基于多源遥感数据的玛纳斯河流域冰川物质平衡变化

赵贵宁¹, 张正勇¹(), 刘琳¹, 徐丽萍¹, 王璞玉², 李丽¹, 宁珊¹

^1. 石河子大学,石河子 832000
^2. 中国科学院西北生态环境资源研究院冰冻圈科学国家重点实验室,兰州 730000

收稿日期:2018-12-27 修回日期:2019-11-09 出版日期:2020-01-25 发布日期:2020-03-25
通讯作者: 张正勇 E-mail:zyz0815@163.com
作者简介:赵贵宁(1992-), 男, 硕士生, 主要从事冰川变化对气候响应研究。E-mail: 13345492733@163.com
基金资助:
国家自然科学基金项目(41761108);国家自然科学基金项目(31760151);国家自然科学基金项目(41641003)

Changes of glacier mass balance in Manas river basin based on multi-source remote sensing data

ZHAO Guining¹, ZHANG Zhengyong¹(), LIU Lin¹, XU Liping¹, WANG Puyu², LI Li¹, NING Shan¹

^1. Shihezi University, Shihezi 832000, Xinjiang, China
^2. State Key Laboratory of Cryospheric Science,Northwest Institute of Eco-Environment and Resources, CAS, Lanzhou 730000, China

Received:2018-12-27 Revised:2019-11-09 Online:2020-01-25 Published:2020-03-25
Contact: ZHANG Zhengyong E-mail:zyz0815@163.com
Supported by:
National Natural Science Foundation of China(41761108);National Natural Science Foundation of China(31760151);National Natural Science Foundation of China(41641003)

摘要/Abstract

摘要：

冰川物质平衡变化是连接气候和水资源的重要纽带,对河川径流有重要的调节功能。本文采用MOD11C3和TRMM 3B43等多源遥感数据驱动度日模型,模拟了2000—2016年玛纳斯河（简称玛河）流域冰川物质平衡过程,并分析了冰川融水对径流的补给规律。结果表明： ① 通过构建气温及降水反演模型能有效校正气象遥感原数据的精度,且经降尺度后能较精细刻画冰川区气候变化特征。冰川区年均气温和降水量分别为-7.57 ℃和410.71 mm,海拔4200 m处为气候变化剧烈地带,气温直减率以其为界上下分别为-0.03 ℃/100 m和-0.57 ℃/100 m,降水梯度分别为-2.66 mm/100 m和4.8 mm/100 m,海拔大于4700 m后降水又以5.17 mm/100 m递增。② 研究期内流域冰川持续呈负平衡状态,累积物质平衡达-9811.19 mm w.e.,年均物质平衡介于-464.85~-632.19 mm w.e.之间。垂向物质平衡在消融区和积累区分别以244.83 mm w.e./100 m、18.77 mm w.e./100 m递增。2000—2002年、2008—2010年冰川消融减缓,2002—2008年、2010—2016年消融加剧,其中2005—2009年期间冰川亏损最为强烈。③ 年内河川径流对冰川物质平衡变化响应强烈,尤以7月、8月物质平衡亏损最为严重占全年总量的75.4%,使得同期河川径流量占全年径流总量的55.1%。年际冰川融水补给率波动于19%~31%之间,可能是不同年份降水和积雪融水补给率差异较大所致。玛河与天山北坡其他河流冰川融水贡献率非常接近,也进一步证实了本研究物质平衡估算结果的可靠性。本研究可为其他流域冰川物质平衡研究提供借鉴和参考。

关键词: 多源遥感数据, 度日模型, 物质平衡, 冰川融水, 玛纳斯河流域

Abstract:

The glacier mass balance (GMB) is an important link between climate and water resources, which has remarkable regulation functions for river runoff. The research, using MOD11C3, TRMM 3B43 and other multi-source remote sensing data to drive the degree-day model, simulates the GMB processes and analyzes the recharge of glacial meltwater to runoff in the Manas River Basin (MRB) during 2000-2016. The results show that: (1) By constructing the temperature and precipitation inversion model, the accuracy of the meteorological remote sensing data can be effectively corrected, and the characteristics of climate change in the glacial region can be well described after downscaling. The annual average temperature and precipitation in the glacier area were -7.57 ℃ and 410.71 mm, respectively. The place at an altitude of 4200 m is a severe climate change zone. Above 4200 m, the temperature drop rates and precipitation gradients were -0.03 ℃/100 m and -2.66 mm/100 m, respectively; while below 4200 m, they were -0.57 ℃/100 m and 4.8 mm/100 m, respectively. Besides, at a higher altitude of 4700 m, the precipitation increased by 5.17 mm/100 m. (2) During the study period, the glaciers in the basin continued to be in a negative state, with a cumulative GMB of -9811.19 mm w.e. and an average annual GMB between -464.85 mm w.e. and -632.19 mm w.e. The vertical GMB increased by 244.83 w.e./100 m and 18.77 w.e./100 m in the ablation zone and the accumulation zone, respectively. From 2000 to 2002 and 2008 to 2010, the melting of glaciers slowed down, and the ablation was intensified from 2002 to 2008 and from 2010 to 2016. Strikingly, the loss of glaciers was most serious during the period 2005-2009. (3) The river runoff responded strongly to the change of GMB within the year, especially in July and August, namely, the GMB loss accounted for 75.4% of the total amount of the whole year, and the river runoff accounted for 55.1% of the annual total. The inter-annual glacial meltwater recharge rate fluctuated between 19% and 31%, which may be due to the differences of precipitation and snow melt water recharge rates in different years. The contribution rate of glacial meltwater of the MRB is close to that of other river basins on the northern slope of the Tianshan Mountains, which can further confirm the reliability of the GMB estimation results. Above all, the research can provide reference for the study of GMB in other river basins.

Key words: multi-source remote sensing data, degree-day model, glacier mass balance (GMB), glacial meltwater, Manas river basin (MRB)

赵贵宁, 张正勇, 刘琳, 徐丽萍, 王璞玉, 李丽, 宁珊. 基于多源遥感数据的玛纳斯河流域冰川物质平衡变化[J]. 地理学报, 2020, 75(1): 98-112.

ZHAO Guining, ZHANG Zhengyong, LIU Lin, XU Liping, WANG Puyu, LI Li, NING Shan. Changes of glacier mass balance in Manas river basin based on multi-source remote sensing data[J]. Acta Geographica Sinica, 2020, 75(1): 98-112.

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数据类型	时间	分辨率	数据来源
DEM	-	30 m×30 m	地理空间数据云(http://www.gscloud.cn/)
NDVI	2000—2016年	250 m×250 m	地理空间数据云(http://www.gscloud.cn/)
MOD11C3		0.05°×0.05°	美国国家航空航天局(https://www.nasa.gov/)
TRMM 3B43		0.25°×0.25°	美国国家航空航天局(https://www.nasa.gov/)
气温		逐月	国家气象信息中心(http://data.cma.cn/)
降水			国家气象信息中心(http://data.cma.cn/)
径流量			肯斯瓦特水文站
冰川面积	2009年	-	寒区旱区科学数据中心(http://westdc.westgis.ac.cn/)
积雪密度	2014年	-	文献[20]

月份	回归因子系数								精度验证
月份	λ	a	b	c	d	e	f	g	RMSE	R²
1	5.41	1.12	-0.64	-0.0020	0.210	0.0110	3.89	1.57	3.06	0.89
2	56.48	-0.47	-0.41	-0.0040	0.260	0.0101	8.97	1.38	1.78	0.94
3	121.38	-2.05	-0.26	-0.0070	0.220	0.0130	15.43	1.22	2.88	0.95
4	143.06	-2.54	-0.11	-0.0120	0.170	0.0060	6.88	0.84	1.82	0.94
5	140.79	-2.31	-0.05	-0.0100	0.170	0.0043	-1.61	0.76	1.16	0.95
6	127.95	-1.80	-0.04	-0.0130	0.136	0.0080	-4.57	0.63	1.16	0.96
7	108.19	-1.36	-0.04	-0.0130	0.120	0.0120	-5.25	0.66	1.42	0.96
8	109.65	-1.40	-0.05	-0.0130	0.120	0.0110	-5.25	0.63	1.16	0.94
9	111.77	-1.70	-0.04	-0.0090	0.160	0.0101	-3.00	0.72	1.30	0.92
10	81.19	-1.35	-0.10	-0.0058	0.208	0.0058	6.03	1.06	1.15	0.89
11	48.80	-0.57	-0.25	-0.0034	0.240	0.0110	9.49	1.18	1.27	0.90
12	51.62	0.26	-0.71	-0.0030	0.280	0.0120	-14.49	0.62	1.52	0.90

月份	回归因子系数								精度验证
月份	λ	a	b	c	d	e	f	g	RMSE	R²
1	19.27	-1.15	0.34	-0.0021	0.049	0.0036	-1.86	1.15	3.69	0.74
2	42.42	-2.33	0.68	-0.0030	0.136	-0.0020	-38.85	1.18	9.31	0.76
3	-60.87	1.32	0.04	-0.0018	-0.006	0.0105	4.37	1.03	6.75	0.81
4	158.81	-4.82	0.65	-0.0113	0.108	0.0011	-29.90	1.64	10.33	0.85
5	63.84	-2.64	0.66	-0.0053	0.065	-0.0054	-24.15	1.31	13.20	0.85
6	-149.02	2.60	0.44	0.0095	-0.014	-0.0289	-19.10	1.01	14.41	0.88
7	-174.73	2.97	0.47	0.0145	0.106	-0.0261	-11.22	0.97	14.33	0.83
8	-83.76	1.29	0.26	0.0113	0.072	-0.0201	-11.61	1.11	19.69	0.84
9	-25.69	1.09	-0.27	0.0001	-0.027	0.0172	-20.52	1.51	8.43	0.82
10	38.29	0.60	-0.72	-0.0034	0.038	0.0143	-8.00	0.91	8.42	0.85
11	60.39	-1.92	0.28	-0.0047	0.035	-0.0002	-5.51	1.12	9.08	0.78
12	-4.97	-0.06	0.10	-0.0024	0.001	0.0007	-6.95	0.93	4.29	0.71

年份	零物质平衡线高度(m)	物质平衡(mm w.e.)	冰川融水(10⁸ m³)	纯冰消融(10⁸ m³)	纯冰消融比率	河川径流(10⁸ m³)	冰川融水比率
2000	4538	-545.86	3.29	2.72	0.83	16.29	0.20
2001	4550	-566.88	2.99	2.60	0.87	14.43	0.21
2002	4530	-551.41	3.51	2.82	0.80	18.74	0.19
2003	4558	-584.20	3.22	2.72	0.85	11.05	0.29
2004	4560	-620.49	3.47	2.90	0.83	12.28	0.28
2005	4532	-575.59	3.37	2.71	0.81	13.39	0.25
2006	4588	-632.19	3.63	2.99	0.82	13.18	0.28
2007	4537	-602.90	3.68	2.81	0.76	15.47	0.24
2008	4569	-624.72	3.27	2.82	0.86	13.77	0.24
2009	4507	-464.85	2.91	2.56	0.88	11.00	0.26
2010	4533	-527.05	3.36	2.84	0.85	16.62	0.20
2011	4560	-602.95	3.65	2.90	0.79	11.74	0.31
2012	4555	-597.01	3.46	2.79	0.81	12.54	0.28
2013	4553	-587.42	3.41	2.79	0.82	13.37	0.25
2014	4556	-563.95	3.21	2.75	0.86	10.65	0.30
2015	4573	-605.61	4.01	3.20	0.80	18.35	0.22
2016	4528	-558.11	3.48	2.82	0.81	15.45	0.23
均值	4549	-577.13	3.41	2.81	0.83	14.02	0.25

区域	拟合方程	相关性
消融区	y₁ = 2.4483x-10729	R² = 0.927
积累区	y₂ = 0.1877x-788.3	R² = 0.073
冰川区(整体)	y₃ = 1.7909x-2522.5(线性)	R² = 0.873
冰川区(整体)	y₄= -0.0014x²+13.75x-32691(非线性)	R² = 0.993

基于多源遥感数据的玛纳斯河流域冰川物质平衡变化

Changes of glacier mass balance in Manas river basin based on multi-source remote sensing data

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