Based on the MODIS satellite image data and field survey from 2010 to 2019, we accomplished the remotely-sensed monitoring of soil moisture in the main stream of Tarim River from a macroscopic perspective with the support of geographic information technology. Results revealed that the reflectance of MODIS band 7 was negatively correlated with soil moisture. Soil moisture in the upper, middle and lower reaches of the main stream of Tarim River varied greatly in space and time during the year. By comparing different river reaches in the same time period, we found that the soil moisture in the upper reaches of Tarim River was higher than that in the middle reaches and that in the lower reaches in sequence. Meanwhile, by comparing different time periods of the same reach, we discovered that the increment of soil moisture in the upper reaches was larger than that in the middle reaches and lower reaches in sequence. Moisture of soil (0-10 cm) in the main stream of Tarim River varied markedly among seasons. In 2019, the maximum soil moisture (6.29%) occurred in June, while the lowest (around 4.16%) in February. In the past decade, each February and lower reaches witnessed the biggest changes in soil moisture data, with the CV both exceeding 15%.
Key words
soil moisture /
dynamic change /
remotely sensed monitoring /
MODIS /
Tarim River basin
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] 杨 涛,宫辉力,李小娟,等. 土壤水分遥感监测研究进展[J]. 生态学报,2010,30(22):6264-6277.
[2] 张 穗,谭德宝,王宝忠,等.TM遥感影像监测裸露土壤含水率的方法研究[J].raybet体育在线
院报,2008,24(1):34-35,64.
[3] URSO G D,MINACAPILLI M.A Semi-empirical Approach for Surface Soil Water Content Estimation from Radar Data without a-Priori Information on Surface Roughness[J].Journal of Hydrology,2006,321(1/2/3/4):297-310.
[4] CASHION J,LAKSHMI V,BOSCH D,et al. Microwave Remote Sensing of Soil Moisture: Evaluation of the Trmm Microwave Imager (TMI) Satellite for the Little River Watershed Tifton, Georgia[J]. Journal of Hydrology, 2005, 307(1/2/3/4): 252-253.
[5] 张仁华. 以作物光谱与热红外信息为基础的复合估产模式[J]. 科学通报,1989(17):1331-1334.
[6] 杨鹤松,王鹏新,孙 威. 条件植被温度指数在华北平原干旱监测中的应用[J]. 北京师范大学学报(自然科学版),2007(3):314-318.
[7] 邢文渊. 基于MODIS影像数据反演干旱区土壤湿度方法研究[D]. 乌鲁木齐:新疆大学,2006.
[8] 魏 珍. 基于Landsat ETM遥感数据的大柳塔煤炭开发区土壤水分信息提取[D]. 西安:长安大学,2010.
[9] 杨东旭. 吉林中部土壤湿度遥感研究与应用[D]. 长春:吉林大学,2013.
[10] 霍艾迪. 基于MODIS数据的沙漠化遥感监测技术研究[D]. 杨凌:西北农林科技大学,2008.
[11] 韦 红,霍艾迪,管文轲,等. 运用中分辨率成像光谱数据对塔里木河流域植被覆盖度动态变化分析[J]. 东北林业大学学报,2019,47(7):62-67.
[12] 钟家骅,管文轲,易 秀,等. 荒漠化地区土壤理化性质及其对胡杨林生长的影响[J]. 水土保持研究,2018,25(4):134-138.
[13] 杜伟宏,管文轲,霍艾迪,等. 塔里木河干流胡杨林下土壤的水盐特征研究[J]. 西南林业大学学报(自然科学),2019,39(5):92-99.
[14] 魏光辉,张洛晨,姜振盈. 塔里木河干流1957—2010年径流变化及特征分析[J].人民珠江,2018,39(6):89-92.
[15] 黄友昕,胡茂胜,沈永林,等. MODIS干旱指数结合RBFNN反演冬小麦返青期土壤湿度[J]. 农业工程学报,2019,35(12):81-88.
[16] 王俊霞,潘耀忠,朱秀芳,等. 壤水分反演特征变量研究综述[J]. 土壤学报,2019,56(1):23-35.
[17] 李 薇. 基于MODIS的沙漠化地区地下水位遥感监测模型研究[D]. 西安:长安大学,2010.
PDF(2735 KB)
