Inversion of Soil Moisture and Shallow Groundwater Depth Based on SVM in Arid Oasis-Desert Ecotone

被引：0
|
作者：
Zhang J. [1 ,2 ]
Ding J. [1 ,2 ]
Tan J. [2 ,3 ]
机构：
[1] College of Resource and Environment Sciences, Xinjiang University, Urumqi
[2] Key Laboratory of Wisdom City and Environmental Modeling, Xinjiang University, Urumqi
[3] School of Computer Science and Engineering, Xinjiang University of Finance and Economics, Urumqi
来源：
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | 2019年 / 50卷 / 03期
关键词：
Groundwater depth; Sentinel-1A; Soil moisture content; Support vector machine; T[!sub]s[!/sub]-VI feature space;
D O I：
10.6041/j.issn.1000-1298.2019.03.024
中图分类号：
学科分类号：
摘要：
In order to further study the interaction between shallow groundwater, vegetation and soil of arid and semi-arid regions, the database of the Sentinel-1A, Landsat images, soil moisture and the groundwater depth were utilized to quantitatively analyze the information of soil moisture and groundwater depth in the study area by the model of support vector machine (SVM) regression algorithm. Furthermore, the comparison of optical remote sensing and microwave remote sensing collaborative inversion in soil moisture and groundwater depth was also analyzed. By the survey of soil moisture and groundwater depth in the study area, the results indicated that the highest accuracy in SVM model was the correlation between soil water content in 0~10 cm and groundwater depth. The accuracy of temperature vegetation drought index (TVDI) was improved, through the C calibration model. It was feasible to invert the groundwater depth by SVM model with different parameters. For single factor modeling, the model constructed by TVDIMSAVI had the highest accuracy and the R2 of modeling set was 0.74, the value of RMSE was 4.66%, and the R2 of verification set was 0.70, the value of RMSE was 4.65%, compared with only single factor (σsoil0 or TVDI), σsoil0 and TVDIMSAVI combination work with the highest model accuracy, R2 was 0.86, and RMSE was 4.16%, the R2 of verification set was 0.92, and RMSE was 2.73%. The results of the optimal model parameters were used to retrieve the soil moisture and groundwater with good accurate. The average relative error of groundwater was 8.23%, which was better than the previous results of the study area of 18.06%. © 2019, Chinese Society of Agricultural Machinery. All right reserved.
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页码：221 / 230
页数：9
相关论文
共 40 条
  • [1] Liu D., Li S., Fu Q., Et al., Comprehensive evaluation method of groundwater quality based on BP network optimized by krill herd algorithm, Transactions of the Chinese Society for Agricultural Machinery, 49, 9, pp. 275-284, (2018)
  • [2] Cheng G.D., Li X., Zhao W.Z., Et al., Integrated study of the water-ecosystem-economy in the Heihe River basin, National Science Review, 1, 3, pp. 413-428, (2014)
  • [3] White C.J., Tanton T.W., Rycroft D.W., The impact of climate change on the water resources of the Amu Darya basin in central Asia, Water Resour Manage, 28, 15, pp. 5267-5281, (2014)
  • [4] Liu G., Yang J., He L., Et al., Fuzzy comprehensive evaluation based assessment of soil alkaline desertification in typical arid area of Xinjiang, Transactions of the CSAE, 27, 3, pp. 1-5, (2011)
  • [5] Zhao W., Zhou H., Liu H., Advances in moisture migration in vadose zone of dryland and recharge effects on groundwater dynamics, Advances in Earth Science, 32, 9, pp. 908-918, (2017)
  • [6] Mettemicht G.I., Zinck J.A., Remote sensing of soil salinity: potentials and constraints, Remote Sensing of Environment, 85, 1, pp. 1-20, (2003)
  • [7] Danierhan S., Abudu S., Guan D.H., Coupled GSI-SVAT model with groundwater surface water interaction in the riparian zone of Tarim River, Journal of Hydrologic Engineering, 18, 10, pp. 1211-1218, (2013)
  • [8] Salwa F.E., An overview of integrated remote sensing and GIS for groundwater mapping in Egypt, Ain Shams Engineering Journal, 6, 1, pp. 1-15, (2015)
  • [9] Liu M., Jiang Y., Xu X., Et al., Long-term groundwater dynamics affected by intense agricultural activities in oasis areas of arid inland river basins, Northwest China, Agricultural Water Management, 203, pp. 37-52, (2018)
  • [10] Suman P., Satiprasad S., Pulak M., Et al., Impacts of urbanization on land use/cover changes and its probable implications on local climate and groundwater level, Journal of Urban Management, 7, 2, pp. 70-84, (2018)
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