黄土高原北部草地表层土壤水分状态空间模拟

为探明黄土高原北部草地表层土壤水分空间分布特征及其与环境因素的关系，该文用自回归状态空间模型和经典统计的线性回归模型对该区草地表层土壤含水率的分布状况进行了模拟。结果表明，状态空间方程可以应用于环境因素复杂的黄土高原水蚀风蚀交错区，其拟合效果优于线性回归模型。单因素中基于饱和导水率的模拟效果最佳（R2 = 0.936）；多因素模拟中以饱和导水率+海拔+凋落物模拟效果最佳（R2 = 0.976），可以很好地解释表层土壤水分的变异状况。自回归状态空间模型可用于研究黄土高原北部水蚀风蚀交错区表层土壤水分与其他因素的空间关系。

State-space simulation of soil surface water content in grassland of northern Loess Plateau

In order to understand the spatial distribution of soil surface water content and its relations with environmental factors in grassland of the northern Loess Plateau, the autoregressive state-space models and classical linear regression models were used, to simulate the spatial distribution of soil surface water content in a grassland of the northern Loess Plateau, based on the saturated soil hydraulic conductivity (Ks), soil surface temperature (T), elevation (E) and litter mass (L). The results showed that state-space models could be applied to the wind and water erosion transitional area of the Loess Plateau where landscape factors varied greatly and the state-space models were consistently more effective than linear regression models. Among the mono-variable state-space models, Ks based models showed the best simulation result (R2 = 0.936). Among the multi-variable state-space models, Ks, E and L included model showed the best simulation result (R2 = 0.976), and the combination of such variables based models provided the best approach to explain the spatial variation of soil surface water content. State-space models are recommended for studying spatial relations between soil surface water content and other variables in the wind and water erosion transitional area of the Loess Plateau.