Abstract
Abundant shallow underground brackish water resources could help in alleviating the shortage of fresh water resources and the crisis concerning agricultural water resources in the North China Plain. Improper brackish water irrigation will increase soil salinity and decrease the final yield due to salt stress affecting the crops. Therefore, it is urgent to develop a practical and low-cost method to monitor the soil salinity of brackish irrigation systems. Remotely sensed spectral vegetation indices (SVIs) of crops are promising proxies for indicating the salinity of the surface soil layer. However, there is still a challenge concerning quantitatively correlating SVIs with the salinity of deeper soil layers, in which crop roots are mainly distributed. In this study, a field experiment was conducted to investigate the relationship between SVIs and salinity measurements at four soil depths within six winter wheat plots irrigated using three salinity levels at the Yucheng Comprehensive Experimental Station of the Chinese Academy of Sciences during 2017–2019. The hyperspectral reflectance was measured during the grain-filling stage of winter wheat, since it is more sensitive to soil salinity during this period. The SVIs derived from the observed hyperspectral data of winter wheat were compared with the salinity at four soil depths. The results showed that the optimized SVIs, involving soil salt-sensitive blue, red-edge, and near-infrared wavebands, performed better when retrieving the soil salinity (R2 ≥ 0.58, root mean square error (RMSE) ≤ 0.62 g/L), especially at the 30-cm depth (R2 = 0.81, RMSE = 0.36 g/L). For practical applications, linear or quadratic models based on the screened SVIs in the form of normalized differential vegetation indices (NDVIs) could be used to retrieve soil salinity (R2 ≥ 0.63, RMSE ≤ 0.62 g/L) at all soil depths and then diagnose salt stress in winter wheat. This could provide a practical technique for evaluating regional brackish water irrigation systems.
Highlights
The shortage of fresh water is severe in the North China Plain, where 64.7% of the total water use is accounted for by agriculture [1]
The results showed that the spectral vegetation indices (SVIs) in the forms of an normalized differential vegetation indices (NDVIs), ratio vegetation index (RVI), Difference vegetation index (DVI), and modified simple ratio (MSR) were sensitive to soil salinity at depths of 10 and 20 cm, whereas the above SVIs as well as those in the forms of an enhanced vegetation index (EVI), modified rednormalized differential vegetation index (mNDVI), and Plant senescence reflectance index (PSRI) were sensitive to soil salinity at depths of 30 and 40 cm
The results showed that the indices with the combination of blue and red/nearinfrared performed well in retrieving the soil salinity at different depths (Tables 3 and 4)
Summary
The shortage of fresh water is severe in the North China Plain, where 64.7% of the total water use is accounted for by agriculture [1]. Improper brackish water irrigation could increase the soil salinity and cause crop physiological stresses [3,7,8,9,10,11,12,13,14]. To fully understand the degree of salinity stress on crops caused by brackish water irrigation, it is necessary to measure the soil salinity at different depths accurately. Traditional methods for monitoring soil salinity usually require the manual analysis of field soil samples in a laboratory or the installation of in-situ sensors to automatically measure the soil salinity. Neither of these are suitable for regional applications because of their high costs. Most of them focused on the soil salinity at a target depth, whereas a quantitative investigation concerning SVIs and the soil salinity along the vertical profile has not yet been reported
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