基于SPAC系统的干旱区枸杞蒸腾耗水模拟与分析

Simulation and Analysis of Transpiration Water Consumption of Lycium Barbarum in Arid Area Based on SPAC System

以宁夏干旱区滴灌枸杞为研究对象,利用包裹式茎流计获取枸杞2015年全生育期(4-10月)树干液流实时数据,土壤墒情监测站及自动气象站获取同期枸杞根区土壤含水率及试验区气象数据;利用研究区内国家基准气象站点近10 a(2005年1月-2014年12月)日数据,计算得出枸杞生育期参考腾发量系列。构建干旱区枸杞蒸腾耗水与ET0及其与SPAC系统关键要素的模拟模型,为明晰枸杞耗水规律及其需水诊断提供支撑。结果表明:枸杞生育期树干液流量S与参考作物腾发量ET0呈显著正相关关系(P=0.01),并符合S=0.330 7 ET0-0.201(R2=0.822 1)的线性模型;与枸杞基径r、根区土壤含水率θ、太阳辐射Rs、温度T及饱和水汽压差VPD等参数也呈显著正相关关系(P=0.01),并符合多参数模型S4-10月=1.378 r+0.017θ+0.004 Rs+0.028 T+0.34 VPD-4.579(R2=0.693),模拟值与实测值误差为-5.80%~2.52%,累计平均误差分别为-0.93%(D=3.5 cm)及0.69%(D=2.6 cm),模拟精度较好。

In this study, Lycium barbarum in Ningxia arid area is taken as study object, the real-time data of daily stem sap flow （SSF） in the whole growth period （from April to October） of 2015 was obtained by using the packaged stem sap flow monitoring system, and the soil moisture content in root zone and the meteorological data in experiment zone are obtained through soil moisture monitoring stations and automatic weather stations. By using the meteorological data of Yinchuan meteorological station in recent 10 years （ January of 2005 to December of 2014 ）, the reference evapotranspiration （ETo ） series of Lycium barbarum are obtained, and the simulation model for transpiration water consumption and ETo, and its key elements of the SPAC system is established to provides support for the clarification of the water consumption rules and the water requirement diagnosis of Lycium barbarum. The results showed that ： in the growth period, the sap flow （S） and reference evapotranspiration （ETo ） has positively correlation （P= 0.01 ）, fitting the linear model S= 0.330 7 ET0-0. 201 （R^2 = 0.822 1 ） ; meanwhile, the sap flow and the base diameter （r） , root zone soil water Content （0） , solar radiation （R^2） , Temperature （T） and saturated vapor pressure difference （VPD） also show significant positive correlation （P= 0.01 ） , and are in accordance with the multi parameter model S4-10= 1.378 r＋0.017θ＋0.004 Rs＋0.028 T＋0.34 VPD-4.579（R^2=0.693） ; the error between the simulated values and the measured values is between 5.80% and 2.52%, the cumulative average error is -0.93% （D= 3.5 cm） and 0.69 （D=2.6 cm） , respectively; the simulation precision is good.