Improvement And Numerical Analysis Of NOAH-MP Land Surface Model

In recent years,the impact of human activities on the terrestrial-atmospheric system has intensified,and the study of food production is currently a hot topic related to human survival.The growth and development of crops are inseparable from the effects of soil moisture and tem-perature.In the Noah-Multiparameterization Land Surface Model(Noah-MP),the difference scheme of the soil water and heat transport equations after discretization is not accurate,and the simulation results of crop-related variables with farmland as the underlying surface are poor.In order to more accurately simulate the growth and development of crops,improve the soil the discrete difference scheme of water and heat transport equations and the introduction of field management(irrigation)are very necessary.In this paper,Fengqiu County,Henan Province(114.3325°E,35.0625°N)was selected as the research site,and the reanalysis data of 2014 The Goal of The Global Land Data As-similation System(GLDAS)was used as the driving data to conduct the single-point numerical simulation test,and the model was evaluated and simulated using Moderate-Resolution Imaging Spectrometer(MODIS)Leaf Area Index(LAI)product(MCD15A3)as the observation data.We first improved the finite difference scheme of the soil water and heat transport equations in the non-uniform space through the correction method of the truncation error remainder and perform error analysis.Then dynamic maize field management(irrigation)was introduced into Noah-MP land surface model by using the method of controlling irrigation duration and fre-quency according to the threshold of soil moisture.The experimental results show that the im-proved differential scheme of the soil water and heat transport module improves the simulation of LAI.The improvement of the mode difference scheme and the addition of field management(irrigation)have expanded the application of the Noah-MP crop model in agricultural research,providing theoretical guidance for the implementation of field operations and the improvement of grain yield.