베이지안 네트워크와 코플라 함수의 결합을 통한 가뭄전이 발생확률의 정량적 분석

초록

Meteorological drought originates from a precipitation deficiency and propagates to agricultural and hydrological droughts through the hydrological cycle. Comparing with the meteorological drought, agricultural and hydrological droughts have more direct impacts on human society. Thus, understanding how meteorological drought evolves to agricultural and hydrological droughts is necessary for efficient drought preparedness and response. In this study, meteorological and hydrological droughts were defined based on the observed precipitation and the synthesized streamflow by the land surface model. The Bayesian network model was applied for probabilistic analysis of the propagation relationship between meteorological and hydrological droughts. The copula function was used to estimate the joint probability in the Bayesian network. The results indicated that the propagation probabilities from the moderate and extreme meteorological droughts were ranged from 0.41 to 0.63 and from 0.83 to 0.98, respectively. In addition, the propagation probabilities were highest in autumn (0.71 ~ 0.89) and lowest in winter (0.41 ~ 0.62). The propagation probability increases as the meteorological drought evolved from summer to autumn, and the severe hydrological drought could be prevented by appropriate mitigation during that time.

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