基于特征水体的旱情预报和等级评估方法

Drought forecasting and severity assessment method based on characteristic waterbodies

  • 摘要: 为提升干旱发生早期识别与发展过程的评估能力,本文提出“特征水体”概念,并将其划分为对干旱响应敏感的小微水体与具有显著季节性变化的中大型水体,探索其在旱情早期预报与过程评估中的应用。针对小微水体,基于水体状态转移关系构建归一化小微水体状态转移指数(NSWSTI),用于旱情早期预报;针对中大型水体,提出遥感干湿基准值(RSDWI),结合标准化水体面积异常指数(SAAI)及多源水文气象因子,构建综合干旱评估指标。以2022年鄱阳湖、洞庭湖和洪泽湖流域干旱事件为例开展分析。结果表明:NSWSTI在洞庭湖和鄱阳湖流域相对于实测水位变化提前约半个月响应,在洪泽湖流域相对于库容变化也表现出一定领先性;综合干旱指数能够较好反映典型流域干旱事件的发展过程及空间差异。

     

    Abstract: To enhance the capability for early identification and evaluation of drought occurrence and development process, the research proposes the concept of “Characteristic Waterbodies” and classifies them into small waterbodies sensitive to drought and medium-to-large waterbodies with significant seasonal variations, exploring their application in early prediction and process assessment. For small waterbodies, a normalized small waterbody size transition index (NSWSTI) was developed based on water body size transition relationship for early drought forecasting; For medium-to-large waterbodies, a remote sensing dry-wet index (RSDWI) was proposed and combined with standardized area anomaly index (SAAI) and multi-source hydro meteorological factors to construct a comprehensive drought index. The drought events in the Poyang Lake, Dongting Lake, and Hongze Lake basins in 2022 was selected as case studies for analysis. The results show that NSWSTI respond approximately half a month earlier than observed water-level changes in the Dongting Lake and Poyang Lake basins, and also demonstrate a certain lead time relative to storage-capacity changes in the Hongze Lake basin. The comprehensive drought index can effectively reflect the development process and spatial differences of typical basin-scale drought events.

     

/

返回文章
返回