Application of the Simple Biosphere Model 2 (SiB2) with Irrigation Module to a Typical Low-Hilly Red Soil Farmland and the Sensitivity Analysis of Modeled Energy Fluxes in Southern China

Zhihao Jing,Rangjian Qiu,Hanggoro Wido,Fangmin Zhang,Yuanshu Jing

doi:10.3390/w11061128

Abstract

Land surface processes are an important part of the Earth’s mass and energy cycles. The application of a land surface process model for farmland in the low-hilly red soil region of southern China continues to draw research attention. Conventional model does not perform well in the simulation of irrigated farmland, because the influence of land surface water is not considered. In this study, an off-line version of the Simple Biosphere model 2 (SiB2) was locally parameterized in a typical farmland of the low-hilly red soil region using field observations and remote sensing data. The performance of SiB2 was then evaluated through comparison to Bowen-ratio direct measurements in a second growing period of rice in 2015 (late rice from 23 July to 31 October). The results show that SiB2 underestimated latent heat flux (LE) by 16.0% and overestimated sensible heat flux (H) by 16.7%, but net radiation flux (Rn) and soil heat flux were reasonably simulated. The single factor sensitivity analysis of Rn, H, and LE modeled in SiB2 indicated that downward shortwave radiation (DSR) and downward longwave radiation (DLR) had a significant effect on Rn simulation. In driving data, DSR, DLR and wind speed (u) were the main factors that could cause a distinct change in sensible heat flux. An irrigation module was added to the original SiB2 model to simulate the influence of irrigated paddy fields according to the sensitivity analysis results of the parameters (C1, bulk boundary-layer resistance coefficient; C2, ground to canopy air-space resistance coefficient; and Ws, volumetric water content at soil surface layer). The results indicate that application of the parameterized SiB2 with irrigation module could be better in southern Chinese farmland.

Highlights

Land is the basis of human survival, and accounts for only 29.2% of the surface area of the Earth.Land surface processes impact the climate primarily through the exchange of energy, momentum, and matter, such as CO2 or H2 O, between the surface and the atmosphere, and across the atmospheric boundary layer [1,2,3,4]
Through sensitivity analysis of the driving meteorological factors, we found that the modeled energy flux had higher sensitivity to downward short-wave radiation (DSR), downward long-wave radiation (DLR) and wind speed (u), of which average sensitivity could exceed 0.5 (Table 6)
Modeling land surface processes plays an important role in understanding the interaction between the land surface and the atmosphere [31,32,33,34]

Summary

Introduction

Land surface processes impact the climate primarily through the exchange of energy, momentum, and matter, such as CO2 or H2 O, between the surface and the atmosphere, and across the atmospheric boundary layer [1,2,3,4]. Climate simulations are especially sensitive to diurnal variations in a surface partitioning of available energy (Rn -G0 ) into sensible (H) and latent (LE) heat fluxes [5,6]. As the focus of land–atmosphere exchange research, can directly affect land surface temperature, water transport, vegetation growth and ecosystem productivity [9]. Sensible heat and latent heat flux measurements can be obtained through direct or indirect methods, such as Bowen ratio-energy balance method, the eddy covariance method, and the scintillometer method [10,11,12]

Objectives

Methods

Results

Conclusion