冬小麦旱情监测中土壤水分估算模型的互补性——以河北省为例

旱灾是影响我国农业最大的气象灾害。频发的冬春旱尤其是春旱恰逢冬小麦生长的关键阶段,对我国的冬小麦生产造成了严重影响,利用遥感技术实现冬小麦旱情监测成为当前农业旱情管理的一个重要发展方向。采用2005年EOS/MOD IS数据产品,对春季不同时段内河北省旱情监测遥感信息模型的互补性进行了研究,得出以下结论:(1)在冬小麦生长的不同时期,ATI模型与TVD I模型之间具有较好的互补性,3月冬小麦旱情遥感监测应选取ATI遥感信息模型;(2)4月~5月表层土壤的RSM-TVD I、RSM-ATI的拟合方程均通过了置信度α=0.001水平的t检验且相关性较好,TVD I和ATI均可以用来估算4月~5月土壤表层土壤水分;(3)4月~5月RSM-TVD I、RSM-ATI的相关性与误差分析结果表明:4月上旬和4月中旬可选择ATI模型或TVD I模型进行冬小麦旱情遥感监测,但以4月上旬选择ATI模型、4月中旬选择TVD I模型为佳,4月下旬~5月下旬TVD I模型是比较合适的冬小麦旱情遥感监测模型。

Complementarity of soil moisture estimation models for drought monitoring of winter wheat: a case study of Hebei

Drought is the major climate disaster affecting agricultural production in China. The drought, frequently occurring in winter/spring, especially in spring, often brings about serious adverse impact on winter wheat production. Using remote sensing technology to monitor drought during the winter wheat growing season is an important development trend in management of agricultural drought. Based on the 2005 EOS/MODIS data available from NASA, a study was conducted on complementarily of remote-sensing-databased drought monitoring models for different periods of spring in Hebei Province. Results show that (1) better complementarily existed between apparent thermal inertia (ATI) model and temperature vegetation drought index (TVDI) model during winter (2) for estimation of relative soil moisture (RSM) in surface soil in April May, both TVDI and ATI can be used for both RSM-TVDI fitted equation and RSM-ATI fitted equation passed the t check (α＝0.001), showing better correlations. TVDI and ATI could be used to estimate surface soil moisture from April to May; and (3) based on correlation analysis and error analysis of equations of RSM-TVDI and RSM-ATI for April and May, ATI model is the best choice for early April, and TVDI model for mid-April. And for the period from late April to late May, the TVDI model is more suitable.