基于SPEI指数的金沙江流域气象干旱时空特征分析

Spatial-temporal Characteristics of Meteorological Drought in Jinsha River Based on SPEI Index

金沙江流域水能资源丰富,是长江经济带重要的水源地,分析其干旱时空演变规律特征,对水资源管理规划及下游的农业生产具有重要的指导意义。基于金沙江流域28个气象站1960-2020年逐月降水和气温资料,计算了年尺度和季尺度的标准化降水蒸散指数(Standardized Precipitation Evapotranspiration Index,SPEI),定量分析了季尺度和年尺度不同等级气象干旱发生频率的年代变化规律及空间分布特征,并采用云模型分析了年尺度气象干旱时空分布的随机性与稳定性。结果表明,年尺度上,金沙江流域主要以轻旱和中旱为主,呈现轻旱高频和重旱低频的特点,且整体趋于干旱化;季尺度上,四个季节干旱频率均在30%左右,主要以春季和夏季干旱为主;空间分布上,丽江一带干旱发生频率较高。云模型分析结果表明,年尺度上,SPEI指数时间分布的离散程度较空间分布的大,不均匀性更加不稳定;时间分布上站点间干旱程度差异随年际变化增大,且不均匀性趋于不稳定;空间分布上,随着熵值的增大,超熵值减小,期望越低的站点相对多年平均干旱程度波动越大,其干旱程度的不均匀性越稳定。

Jinsha River is rich in water energy resources and is an important water source in the Yangtze River Economic Belt. The analysis of temporal and spatial evolution characteristics of drought in Jinsha River has an important guiding significance for water resources management planning and agricultural production in the lower reaches. Based on the monthly precipitation and temperature data of 28 meteorological stations in the Jinsha River from 1960 to 2020, the standardized precipitation evapotranspiration index(Standardized precipitation evapotranspiration index) at annual and seasonal scales is calculated, and the temporal variation and spatial distribution characteristics of drought frequency at different levels at seasonal and annual scales are quantitatively analyzed. The randomness and stability of spatial and temporal distribution of annual meteorological drought are analyzed by the cloud model. The results show that on the annual scale, the Jinsha River is mainly characterized by light droughts and moderate droughts, with high frequency of light droughts and low frequency of severe droughts. On the seasonal scale, the drought frequency of the four seasons is about 30%, mainly in spring and summer. In terms of spatial distribution, the occurrence frequency of drought is high in Lijiang Area.The results of cloud model analysis show that the temporal distribution of SPEI index is more discrete than the spatial distribution, and the heterogeneity is more unstable. In terms of time distribution, the difference of drought degree between stations increases with the interannual variation, and the unevenness tends to be unstable. In terms of spatial distribution, the hyperentropy value decreases with the increase in entropy value, and the site with lower expectation fluctuates more with respect to the annual average drought degree, and its drought degree unevenness is more stable.