The process of soil wind erosion is affected by vegetation coverage. From a functional perspective, vegetation can be categorized as photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV).  

The NPV represents dormant and dead vegetation, crop residues, and litter, which are the main components of surface vegetation during the non-growing season. It also helps to reduce wind erosion during this time.  

However, the normalized difference vegetation index (NDVI) can generally reflect the fractional cover of PV, but it may not accurately reflect the fractional cover of NPV, leading to potential errors in estimating NPV’s fractional coverage.  

A research team from the Northwest Institute of Eco-Environment and Resources of the Chinese Academy of Sciences (CAS) collected hyperspectral data on NPV to estimate fractional coverage in the Mu Us Sandy Land (MUSL) using Landsat 8-OLI images from 2014 to 2017. 

The study was published in Geoderma on Apr. 17. 

Researchers conducted short-term observations of wind erosion to estimate the fractional cover of NPV and calibrate the simulated results, reducing uncertainties in wind erosion simulations.  

It was found that the mean values of NPV fractional coverage in the MUSL from 2014 to 2017 were approximately 2.71 times higher than those estimated by NDVI data.  

After coupling NPV into the revised wind erosion equation (RWEQ) model, the simulation accuracy of this model obviously increased, as validated by observation data.  

Without considering NPV, the wind erosion modulus is overestimated. The wind erosion modulus was overestimated from 2014 to 2017 at rates of 130.48 t/km²/a, 91.79 t/km²/a, 85.51 t/km²/a, and 93.76 t/km²/a respectively. The corresponding overestimation rates in wind erosion for those years were 26.52 %, 16.9 %, 21.47 % and 31.33 % respectively.  

This study integrated NPV into the RWEQ model to enhance the simulation accuracy of this model and provide a new perspective for future development of wind erosion models. 

Contact:  

DU Heqiang  

E-mail: dilikexue119@163.com