Modification and validation of the SWAT model based on multi-plant growth mode, a case study of the Meijiang River Basin, China

Abstract

With the aim of simulating non-point source pollution of the agroforestry system, we established a forest growth model featuring variable density and mixed vegetation types to address the drawbacks of the Soil and Water Assessment Tool (SWAT) in estimating the accumulated biomass, based on the average forest vegetation density and single plant growth pattern. In addition, a dominant vegetation abundance remote sensing inversion model and leaf area index (LAI) and extinction coefficient remote sensing inversion model were set up to obtain relevant parameters of the forest growth model. Moreover, based on radiant energy under intercropping, we used the Keating equation with the intercropping index as the variable to modify the original SWAT single biomass accumulation model. This was done to explore the intercropping growth model as well as the remote sensing inversion method, considering the multiple cropping and intercropping indexes. We selected the Meijiang River basin as the study area, a sub-basin of the Poyang Lake basin in China in a subtropical humid monsoon climate zone and red soil region, to explore the validity of the modified SWAT based on field data. The results show that the modified SWAT outperformed the original model in terms of simulated flow and nutrient load, using variables such as vegetation coverage, different forest components (e.g., coniferous forest, broadleaf forest, and sparse shrubs), and LAI. As for simulated flow, the validity of the modified SWAT was increased by 7.8%, and simulation of the average, maximum, minimum, and total flow rates were closer to the measured values, better reflecting the actual surface water storage. In the simulation of nutrient load, validity was increased by 6.4% (total phosphorus) and 6.1% (total nitrogen), better representing macroscopic and microscopic characteristics of the forest vegetation landscape.