基于地下水位与土壤含水量的地下水蒸散发估算北大核心CSCD

地下水蒸散发(Groundwater evapotranspiration,ET_(g))是地下水浅埋环境中垂向水文循环的重要组分,是干旱区地下水主要的自然排泄方式(>70%)。准确估算ET_(g)对科学管理干旱区农业与水资源、合理保护和修复地下水依赖型植被意义重大。本文基于地下水位和土壤水分波动方法估算了甘肃临泽县锁龙潭湿地附近的沙枣(Elaeagnus angustifolia)林2017—2018年生长季(4月15日至10月15日)的ET_(g)。结果表明:(1)2017、2018年生长季ET_(g)分别为275、511 mm,在实际蒸散发(ETa)中分别占73%、87%;其中7—8月约占整个生长季ET_(g)的48.2%、48.4%,大致与地下水位变化及植被生长过程同期。(2)ET_(g)及其占总蒸散发的比例与潜在蒸散发、土壤储水量、地下水位正相关(P<0.05),这3个要素对ET_(g)的方差解释率均较高(2017年48%、21%、31%,2018年24%、24%、52%)。(3)数据驱动方法在荒漠绿洲过渡带地下水浅埋环境ET_(g)量化评估中虽然可行,但时间分辨率较低,融合机制模型的数据驱动方法是未来提高ET_(g)估算精度的重要思路。

Groundwater evapotranspiration estimation based on soil moisture and water table measurements

As one of the most important components of the vertical hydrological cycle in shallow groundwater environments and the major groundwater drainage mode naturally （>70%）， the accurate estimation of groundwater evapotranspiration （ET_g） is of great significance for the management of agriculture and water resources， reasonable protection and restoration of groundwater dependent vegetation in arid areas. Based on the water table and soil moisture fluctuation methods， ET_g of Elaeagnus angustifolia. near Suolongtan Wetland in Linze County， Gansu Province during the 2017-2018 growing season （From April 15 to October 15） was estimated. The results showed that： （1） ET_g was 275 mm and 511 mm in 2017 and 2018， accounting for 73% and 87% of actual evapotranspiration （ET_g/ET_a）. Amount during July and August accounted for 48.2% and 48.4% of the total ET_g in the whole growing season， which roughly coincided with the dynamics of groundwater depth and vegetation growth process. （2） ET_g and its proportion in ET_a are positively correlated with potential evapotranspiration， soil water storage and groundwater depth （P<0.05）， the explained variances of the ET_g by the three different factors are 48%， 21%， and 31% in 2017， and 24%， 24%， and 52% in 2018. （3） Data-driven method is feasible in the ET_g quantitative evaluation of shallow groundwater environments in the desert oasis transition zone， but with relatively low temporal resolution， while data-driven method with mechanism modeling maybe a potential idea to improve the accuracy and resolution of ET_g estimation in the study area.