Land and Water Resources

Remote sensing retrieval of soil moisture and estimation of vegetation water requirements in the north and south mountains of Lanzhou City

  • ZHANG Hua ,
  • YA Haiting ,
  • XU Cungang
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  • College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, Gansu, China

Received date: 2023-08-28

  Revised date: 2023-12-14

  Online published: 2024-04-26

Abstract

To understand the dynamic change characteristics of soil moisture in the arid region of Northwest China, the relationship between vegetation water requirement and soil moisture was explored. The perpendicular drought index (PDI) was determined on the basis of Sentinel-2 L2A and Landsat 8 OLI remote sensing data in combination with 111 soil surface measurements in the 0-10 cm layer. The PDI, modified PDI (MPDI), and vegetation-adjusted PDI (VAPDI) were used to construct a soil moisture inversion model, and four quantitative indicators—determination coefficient (R2), mean absolute error (MAE), mean relative error (MRE), and root mean square error (RMSE)—were used to assess the accuracy of the inversion model. The optimal soil moisture inversion model was selected and used in combination with the soil moisture limiting coefficient. Spatial data of the vegetation area of forest land, grassland, and cultivated land in the study area in 2019 and reference crop evapotranspiration data during the growing season at each station were collected, and a model of the ecological water requirement of vegetation was constructed to explore the spatiotemporal changes in soil moisture and vegetation water requirement in the study area. The results showed that (1) PDI, MPDI, and VAPDI determined using the two data sources showed a linear negative correlation with the measured data to varying degrees, and the coefficient of determination R2 was 0.37, 0.64, and 0.59, respectively. The model evaluation indicators suggested that the soil moisture regression model of MPDI had the highest fitting coefficient of determination. The spatial distribution patterns of soil moisture obtained from the two remote sensing data were consistent. (2) The high-resolution Sentinel-2 L2A soil moisture inversion was more precise, and the overall soil moisture showed a fluctuating growth trend. The multitime average of soil moisture was 23.27%; it showed a trend of initial decrease, followed by an increase and subsequent decrease, with an overall growth rate of 74.07%. (3) The average vegetation water requirement and soil moisture content of the northern and southern mountains of Lanzhou City from April to October showed a trend of fluctuation and decline. The maximum vegetation water requirement between April and October was 3.98×107 m3—observed in July—and the minimum water requirement was 0.97×107 m3—observed in October. With the implementation of the environmental greening project, the northern and southern mountains of Lanzhou City have gradually formed a community structure of multispecies combination from only drought-tolerant herbs and low shrubs. In general, this study provides a reference for the rational use of soil water resources and restoration of vegetation in the two mountains of Lanzhou.

Cite this article

ZHANG Hua , YA Haiting , XU Cungang . Remote sensing retrieval of soil moisture and estimation of vegetation water requirements in the north and south mountains of Lanzhou City[J]. Arid Zone Research, 2024 , 41(4) : 566 -580 . DOI: 10.13866/j.azr.2024.04.04

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