AMSR-E土壤水分产品评价及在干旱监测中的应用

doi:10.13866/j.azr.2021.03.07

Abstract

Abstract:

Soil moisture plays an important role in surface energy exchange and climate change. Drought is a common natural disaster and soil moisture is the most intuitive index to reflect drought, therefore the use of microwave remote sensing to monitor surface soil moisture has obvious advantages. Microwave soil moisture products also play an important role in drought monitoring, but because of the difference of underlying surface and the accuracy of inversion algorithm, the application of soil moisture products is limited. Thus this study evaluated the accuracy of widely used AMSR-E (Advanced Microwave Scanning Radiometer for EOS) soil moisture products in china and their role in drought monitoring. The results showed that AMSR-E can better reflect the soil moisture at different depths, most of the sites have a very significant correlation, but the correlation of 20 cm is lower than 10 cm, and the high correlation coefficient area is significantly reduced; The correlation at bare soil between AMSR-E and agricultural meteorological station is significantly higher than that of farmland. For most crop regions, there are obvious relationships of soil moisture between agricultural meteorological station and AMSR-E. For 10 cm depth, the best correlation was observed under the planting sorghum with a coefficient of 0.579, while for 20 cm depth, the best correlation was under cotton with a coefficient of 0.528. The correlation of spring, summer and autumn was higher, but the correlation in winter was slightly lower. In the case of planting crops, the correlations of soil moisture between station and AMSR-E are better in Northeast, South and Northwest China, while in the case of white land those in Northwest, Southwest and Central China are higher; AMSR-E has a wider range of soil moisture values than the agricultural test station, but the peak values of AMSR-E are different in different regions, and the distribution and fluctuation of the two kinds of soil moisture in North China are relatively consistent; AMSR-E can basically reflect the trend of soil moisture difference caused by drought in the north and rainy in the south; For most stations and most crop types, if the correlation of 10 cm between agricultural meteorological station and AMSR-E is good, that of 20 cm soil moisture will also have this performance. Secondly, there is a good correlation between AMSR-E soil moisture anomaly percentage extracted by AMSR-E and precipitation anomaly percentage, especially in the northwest and most areas of northern China. AMSR-E soil moisture products can better reflect the fluctuation of precipitation and the occurrence of drought.

Key words: AMSR-E soil moisture, soil moisture, precipitation anomaly index, crop types

WANG Jing,FANG Feng,HUANG Pengcheng,YUE Ping,LI Jiangping,WANG Dawei. Evaluation of Advanced Microwave Scanning Radiometer for EOS(AMSR-E) soil moisture products over China and its application in drought monitoring[J].Arid Zone Research, 2021, 38(3): 650-664.

Figures/Tables 15

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References 31

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	一季稻	元麦	麻类	冬小麦	向日葵	夏玉米	大豆	大麦	套玉米	宿根蔗	马铃薯
样本量	1401	3	103	26945	54	6577	3690	21	798	628	2085
相关系数	0.193^**	-0.167	0.456^**	0.224^**	-0.248	0.295^**	0.247^**	0.209	0.249^**	-0.138^**	0.492^**
	新植蔗	早稻	春小麦	春玉米	晚稻	普通棉	棉花	油菜	烟草	牧草	高粱
样本量	229	407	4722	11683	361	5523	116	2395	166	4414	312
相关系数	0.086	0.200^**	0.191^**	0.328^**	0.334^**	0.363^**	0.559^**	0.302^**	0.315^**	0.523^**	0.579^**
	甘蔗	甘薯	甜菜	白地	芝麻	花生	莜麦	谷子	长绒棉	青稞	其他作物
样本量	25	848	334	37808	38	759	57	760	5	523	4470
相关系数	0.322	0.300^**	-0.161^**	0.444^**	0.299	0.171^**	0.305^**	0.391^**	-0.352	0.235^**	0.260^**

	春季	夏季	秋季	冬季
样本量	12193	9032	13800	2783
相关系数	0.462^**	0.431^**	0.440^**	0.305^**

	一季稻	元麦	麻类	冬小麦	向日葵	夏玉米	大豆	大麦	套玉米	宿根蔗	马铃薯
样本量	1374	3	103	26715	54	6538	3690	18	787	627	2054
相关系数	0.151^**	-0.305	0.384^**	0.245^**	-0.338^*	0.298^**	0.233^**	0.042	0.261^**	-0.185^**	0.502^**
	新植蔗	早稻	春小麦	春玉米	晚稻	普通棉	棉花	油菜	烟草	牧草	高粱
样本量	228	332	4690	11643	364	5476	114	2386	165	4399	309
相关系数	0.066	0.170^**	0.147^**	0.314^**	0.129^*	0.332^**	0.528^**	0.287^**	0.384^**	0.513^**	0.513^**
	甘蔗	甘薯	甜菜	白地	芝麻	花生	莜麦	谷子	长绒棉	青稞	其他作物
样本量	25	844	334	37560	38	765	57	761	5	522	4434
相关系数	0.462^**	0.280^**	0.107	0.433^**	0.204	0.145^**	0.251	0.374^**	-0.348	0.153^**	0.234^**

		东北	华北	华东	华南	华中	西北	西南
多种作物类型	样本量	15755	36325	10512	12347	2860	28781	11982
多种作物类型	相关系数	0.289^**	0.207^**	0.065^**	0.289^**	0.128^**	0.280^**	0.180^**
白地	样本量	7319	14609	1805	766	2862	8082	2365
白地	相关系数	0.307^**	0.255^**	0.317^**	0.163^**	0.337^**	0.449^**	0.354^**

		全国	东北	华北	华东	华中	华南	西南	西北
多种作物类型	相关系数	0.863^**	0.838^**	0.849^**	0.899^**	0.930^**	0.692^**	0.732^**	0.924^**
多种作物类型	样本数	629	80	180	64	70	23	75	134
白地	相关系数	0.738^**	0.863^**	0.606^**	0.906^**	0.910^**	0.828^**	0.377^*	0.849^**
白地	样本数	476	75	153	43	45	16	35	106

Evaluation of Advanced Microwave Scanning Radiometer for EOS(AMSR-E) soil moisture products over China and its application in drought monitoring

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References 31

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	一季稻	其他作物	冬小麦	向日葵	夏玉米	大豆	套玉米	宿根蔗	新植蔗	早稻
相关系数	0.768^**	0.668^**	0.716^**	0.356	0.884^**	0.727^**	0.939^**	0.928^*	0.991^**	0.046
样本数	46	66	248	4	128	65	16	5	4	15
	春小麦	春玉米	晚稻	普通棉	棉花	油菜	烟草	牧草	甘蔗	甘薯
相关系数	0.891^**	0.917^**	0.694^**	0.974^**	0.949^**	0.736^**	0.149	0.919^**	0.989^**	-0.005
样本数	70	164	30	64	29	56	6	44	5	18
	甜菜	芝麻	花生	谷子	青稞	马铃薯	高粱	麻类
相关系数	-0.919	0.997^**	0.961^**	0.897^**	0.972^**	0.870^**	0.966^**	0.760
样本数	4	3	25	14	7	41	11	6

站点	同AMSR-E土壤水分相关性		同农试站观测土壤水分相关性			站点	同AMSR-E土壤水分相关性		同农试站观测土壤水分相关性
站点	相关系数	样本量	相关系数	样本量	地表作物类型	站点	相关系数	样本量	相关系数	样本量	地表作物类型
敦煌	0.002	241	0.266	16	白地、普通棉	岷县	-0.058	260	0.811^**	33	马铃薯、其他作物、白地
永昌	-0.034	204	0.614^*	16	白地、大麦	文县北	-0.006	302	0.609^**	52	冬小麦、夏玉米、白地
凉州东	0.077	216	0.614^**	25	白地、春小麦、套玉米	武山	0.149^*	269	0.870^**	19	冬小麦、白地
景泰	0.071	251	0.929^**	20	白地	成县东	0.229^**	325	0.665^**	39	冬小麦、春玉米、白地
会宁	0.167^**	243	0.745^**	19	白地、春小麦	两当	0.250^**	328
崆峒	0.079	259	0.450^**	33	冬小麦、春玉米、白地	敦煌东	0.223^*	85
泾川	0.090	265	0.751^**	29	冬小麦、高粱、白地	安定西	0.184^**	258
宁县	-0.039	256	0.948^**	17	冬小麦、白地	秦安	0.148^*	258
玛曲	-0.131	211	0.775^**	20	白地、牧草	张家川	0.084	278
合作	-0.141^*	217	0.751^**	31	牧草、青稞	成县西	0.242^**	328

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