Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning.

ABSTRACT: Cotton is widely used in textile, decoration, and industry, but it is also threatened by soil salinization. Drip irrigation plays an important role in improving water and fertilization utilization efficiency and ensuring crop production in arid areas. Accurate prediction of soil salinity and crop evapotranspiration under drip irrigation is essential to guide water management practices in arid and saline areas. However, traditional hydrological models such as Hydrus require more variety of input parameters and user expertise, which limits its application in practice, and machine learning (ML) provides a potential alternative. Based on a global dataset collected from 134 pieces of literature, we proposed a method to comprehensively simulate soil salinity, evapotranspiration (ET) and cotton y

SUBMITTER: Jiang Z 

PROVIDER: S-EPMC10282761 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature