基于地面遥感信息与气温的夏玉米土壤水分估算方法

土壤水分是土壤-植被-大气连续体的一个重要组分,是决定陆地生态系统水分状况的关键因子,也是作物的水分供应库.为了估算站点尺度不同深度的土壤水分,基于下垫面能量平衡方程和水分亏缺指数,提出了基于地面遥感信息(归一化植被指数和下垫面温度)和气温估算土壤相对湿度方法.利用2014年中国气象局固城生态与农业气象试验站夏玉米水分控制试验资料验证的结果表明: 该方法可以有效估算不同深度的土壤相对湿度,陆地生态系统的潜在干旱程度即实际蒸散与潜在蒸散之比与不同深度土壤湿度呈显著的线性关系.其中,0～10 cm土层的土壤水分估算精度最高,决定系数达0.90;0～20 cm到0～50 cm土层土壤水分估算的平均相对误差均在15%以内,相对均方根误差均在20%以内.研究结果可为作物的干旱监测与灌溉管理提供参考.

Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R²=0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.