Jason-2测高卫星对湖泊水位的监测精度评价

doi:10.12082/dqxxkx.2020.190651

地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (3): 494-504.doi: 10.12082/dqxxkx.2020.190651

• “数字地形分析”专栏 • 上一篇下一篇

Jason-2测高卫星对湖泊水位的监测精度评价

何飞^1,², 刘兆飞^1,^*(), 姚治君¹

^1. 中国科学院地理科学与资源研究所,北京 100101
^2. 中国科学院大学,北京 100049

收稿日期:2019-11-04 修回日期:2019-02-13 出版日期:2020-03-25 发布日期:2020-05-18
通讯作者: 刘兆飞 E-mail:zfliu@igsnrr.ac.cn
作者简介:何飞（1994— ）,男,安徽安庆人,硕士生,主要从事水土资源综合评价研究。E-mail: hef.17s@igsnrr.ac.an
基金资助:
中国科学院战略性先导科技专项(XDA23090302);国家自然科学基金项目(41571027)

Evaluation of the Monitoring Accuracy of Lake Water Level by the Jason-2 Altimeter Satellite

HE Fei^1,², LIU Zhaofei^1,^*(), YAO Zhijun¹

^1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
^2. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2019-11-04 Revised:2019-02-13 Online:2020-03-25 Published:2020-05-18
Contact: LIU Zhaofei E-mail:zfliu@igsnrr.ac.cn
Supported by:
Special project of strategic leading science and technology of Chinese Academy of Sciences(XDA23090302);National Natural Science Foundation of China(41571027)

摘要/Abstract

摘要：

湖泊水位是评估湖泊水量变化的重要指标。本文以洪泽湖、高邮湖及洞庭湖为研究对象,利用集中度的概率密度函数方法（CPDF）来提高Jason-2测高数据精度,分析了降水量与各个湖泊水位变化的相关性,并基于实测水位数据对比评价了Jason-2测高卫星原始GDR数据和CPDF方法处理后的卫星数据的精度。结果表明：① Jason-2原始GDR数据点的分布存在疏密之分,大部分数据分布相对集中,且有一定的周期变化,但评价结果显示精度较差,故原始GDR数据不能直接用于湖泊水位监测;② CPDF方法可以极大提高测高卫星的水位数据精度,洪泽湖与高邮湖的均方根误差分别由1.92 m与1.74 m减少到了0.32 m和0.36 m,相关系数由0.28和0.04提高到了0.85和0.72。对于南北宽度较窄且日水位变化较大的湖泊（如洞庭湖）,CPDF方法提高原始GDR结果的精度有限;③ 洞庭湖降水与水位相关性最强,高邮湖次之,而洪泽湖降水与水位成不显著的负相关,是洪泽湖水利工程对于水位的调节导致了这一结果。本研究对于利用测高卫星获得湖泊水位值,进而对湖泊进行动态监控,特别是在填补资料匮乏地区湖泊水位数据方面具有重要意义。

关键词: Jason-2, 卫星测高, 水位, 降水, 洪泽湖, 高邮湖, 洞庭湖, 精度评价

Abstract:

As one of the important characteristics of lakes, lake water level is an important indicator for evaluating the change of lake water storage capacity. As a new remote sensing monitoring technology, satellite altimetry technology has played an increasingly important role in monitoring the dynamic changes of lake waters, and has become an effective means for lake research, water resources investigation and wetland protection. This study took Hongze Lake, Gaoyou Lake and Dongting Lake as examples, using the Centralized Probability Density Function method (CPDF) to improve the accuracy of Jason-2 altimetry data, as well as analyze the correlation of precipitation and water level of each lake. Besides, based on the measured water level data we compared the accuracy of the original GDR data of the Jason-2 altimeter satellite and the satellite data processed by the CPDF method. Results show that: (1) The distribution of Jason-2 original GDR data points is sparse, most of the data are relatively concentrated, and there are certain periodic changes, but the evaluation results show poor accuracy, so the original GDR data cannot be directly used for lake water level monitoring. (2) CPDF method can greatly improve the accuracy of the water level data of the altimeter satellite. The evaluation results of Hongze Lake and Gaoyou Lake show that the RMSE decreased from 1.92m and 1.74m to 0.32 m and 0.36m, and the correlation coefficient increased from 0.28 and 0.04 to 0.85 and 0.72, indicating that Jason-2 altimetry data processed by the CPDF method can achieve higher accuracy in lake water level monitoring. However, it is worth noting that for the lake, which is with narrow north-south widths and large changes in daily water levels (such as Dongting Lake), the accuracy of the raw GDR improved by the CPDF method would be limited. (3) The precipitation of Dongting Lake had the strongest correlation with the water level, followed by Gaoyou Lake,the water level changes of Gaoyou Lake and Dongting Lake lag behind the precipitation by about 1 month and 1-2 months respectively. However, the precipitation of Hongze Lake was not significantly negatively correlated with the water level, which is partly due to the adjustment of water level by the Hongze Lake water conservancy project. This study is of great significance for obtaining lake water level values using altimetry satellites, and then for dynamic monitoring of lakes, especially in filling lake water level data in data-poor areas.

Key words: Jason-2, satellite altimetry, water level, precipitation, Hongze Lake, Gaoyou Lake, Dongting Lake, evaluation of accuracy

何飞, 刘兆飞, 姚治君. Jason-2测高卫星对湖泊水位的监测精度评价[J]. 地球信息科学学报, 2020, 22(3): 494-504.DOI:10.12082/dqxxkx.2020.190651

HE Fei, LIU Zhaofei, YAO Zhijun. Evaluation of the Monitoring Accuracy of Lake Water Level by the Jason-2 Altimeter Satellite[J]. Journal of Geo-information Science, 2020, 22(3): 494-504.DOI:10.12082/dqxxkx.2020.190651

图/表 10

图1

图2

表1

最佳Bin宽度计算公式"

估算器	计算公式	公式编号	参考文献
E1	$R 1 + lo g 2 N$	（3）	[30]
E2	$R 1.87 (N - 1) 0.4$	（4）	[31]
E3	$R 1 + lo g 2 γ 2 + lo g 2 N$	（5）	[32]
E4	$3.49 σ N - 13$	（6）	[33]

表1

图3

表2

图4

图5

图6

图7

表3

参考文献 34

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湖泊名称		洪泽湖	高邮湖	洞庭湖
原始GDR平均值/m		11.39	5.58	29.01
原始GDR标准差/m		2.47	2.62	1.23
实测数据平均值/m		12.80	6.09	26.80
实测数据标准差/m		0.47	0.25	1.42
CPDF平均值/m		12.70	5.95	28.99
CPDF标准差/m		0.52	0.34	1.15
均值差/m	CPDF	0.38	0.25	0.85
均值差/m	原始GDR	1.15	1.04	0.79
均方根误差/m	CPDF	0.32	0.36	1.27
均方根误差/m	原始GDR	1.92	1.74	1.3
相关系数	CPDF	0.85	0.72	0.95
相关系数	原始GDR	0.28	0.04	0.96
湖泊面积/km²		879.10	612.30	153.00

Jason-2测高卫星对湖泊水位的监测精度评价

Evaluation of the Monitoring Accuracy of Lake Water Level by the Jason-2 Altimeter Satellite

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摘要/Abstract

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图/表 10

参考文献 34

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	洪泽湖		高邮湖		洞庭湖
滞后月数	相关系数	显著性^*	相关系数	显著性^*	相关系数	显著性^*
0	-0.31	显著	0.24	显著	0.56	显著
1	0.08	不显著	0.43	显著	0.64	显著
2	0.22	不显著	0.18	显著	0.64	显著
3	0.16	不显著	0.16	不显著	0.33	显著

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