遥感蒸散发驱动HYDRUS-RS模型模拟剖面土壤含水率  

Combining remote sensing and HYDRUS-RS model tosimulate large-scale soil moisture dynamics

作　　者：张二东 林人财 刘行刚[2] 魏征[2] 张宝忠[2] 陈鹤[2] ZHANG Erdong;LIN Rencai;LIU Xinggang;WEI Zheng;ZHANG Baozhong;CHEN He(Yongji Branch Center,Inner Mongolia Hetao Irrigation District Water Conservancy Development Center,Bayannur 015000,China;China Institute of Water Resources and Hydropower Research,Beijing 100048,China)

机构地区：[1]内蒙古河套灌区水利发展中心永济分中心,内蒙古巴彦淖尔015000 [2]中国水利水电科学研究院,北京100048

出　　处：《灌溉排水学报》2024年第9期25-32,112,共9页Journal of Irrigation and Drainage

基　　金：国家重点研发计划项目(2022YFD1900500);国家自然科学基金重点项目(52130906);中国水利水电科学研究院流域水循环模拟与调控国家重点实验室自主研究课题(SKL2022TS13)。

摘　　要：【目的】提出一种物理机制明确、具有区域尺度模拟潜力且模拟精度较高的剖面土壤体积含水率(土壤含水率)模拟模型,评估北京大兴区夏玉米生育期不同土层土壤含水率模拟精度。【方法】利用MODIS数据和地表能量平衡系统(SEBS)模型反演大兴区蒸散发(ET),将其拆分为土壤蒸发(E)和植株蒸腾(T),驱动HYDRUS-1D模型中的源汇项,基于地理信息系统(GIS)平台构建HYDRUS-RS模型模拟剖面土壤含水率,并在2018年夏玉米生育期得到验证。【结果】SEBS模型中的R_n模拟效果最好,决定系数(R2)、偏差(Bias)、均方根误差(RMSE)分别为0.81、11W/m2、54.8W/m2;2018年大兴区夏玉米生育期逐日ET主要介于3~6mm/d,土壤含水率监测样点的ET不尽相同,但变化规律相似;在夏玉米生育期,HYDRUS-RS模型模拟的40~60cm土壤含水率精度最高,Bias为0.2%,RMSE为2.1%,R2为0.80。【结论】HYDRUS-RS模型物理机制明确、具有区域尺度模拟潜力,40~60cm土层土壤含水率模拟精度最高。【Objective】HYDRUS is a software widely used to simulate soil water movement,but it requires evapotranspiration which is difficult to obtain at large scales.In this paper,we investigated the feasibility of combining it with remote sensing to simulate spatiotemporal soil water dynamics at large scales.【Method】The experiment was conducted in a summer maize field in Daxing District,Beijing.The evapotranspiration estimated from the MODIS data and the surface energy balance system(SEBS)model was decoupled into soil-surface evaporation and plant transpiration,which were combined with the HYDRUS-1D to simulate spatiotemporal water dynamics in soil profile.Field-scale soil water dynamics was modelled by embedding the HYDRUS-RS model with the geographic information system(GIS)platform.The models were then applied to simulate spatiotemporal changes in soil water in the summer maize field during its growing season in 2018.【Result】The SEBS model was the best in modelling Rn,with the coefficient of determination(R2),bias and root mean square error(RMSE)being 0.81,11 W/m^(2),and 54.8 W/m^(2),respectively.In the experimental area,the estimated daily ET during the growing season of the maize in 2018 varied between 3 and 6 mm/d.This differed slightly from that directly estimated from the soil moistures measured from pre-defined sampling points,but their temporal variation trends were the same.During growing season of the summer maize,soil moisture simulated by the proposed HYDRUS-RS model for the 40-60 cm soil layer was accurate,with the bias,RMSE,and R2 being 0.2%,2.1%and 0.80,respectively.【Conclusion】Combining remote sensing with HYDRUS-1D provides a robust and accurate method for simulating large-scale soil water dynamics in agricultural lands.For the summer maize crop we studied,this integrated approach effectively predicts the changes in soil moisture,particularly in the 40-60 cm root zone.

关 键 词：蒸散发 土壤含水率 地表能量平衡系统模型 大兴区 夏玉米 

分 类 号：S161[农业科学—农业气象学]