Abstract
In recent years, global climate change has altered precipitation patterns, causing uneven spatial and temporal distribution of precipitation that gradually induces precipitation polarization phenomena. Taiwan is located in the subtropical climate zone, with distinct wet and dry seasons, which makes the polarization phenomenon more obvious; this has also led to a large difference between river flows during the wet and dry seasons, which is significantly influenced by precipitation, resulting in hydrological drought. Therefore, to effectively address the growing issue of water shortages, it is necessary to explore and assess the drought characteristics of river systems. In this study, the drought characteristics of northern Taiwan were studied using the streamflow drought index (SDI) and Markov chains. Analysis results showed that the year 2002 was a turning point for drought severity in both the Lanyang River and Yilan River basins; the severity of rain events in the Lanyang River basin increased after 2002, and the severity of drought events in the Yilan River basin exhibited a gradual upward trend. In the study of drought severity, analysis results from periods of three months (November to January) and six months (November to April) have shown significant drought characteristics. In addition, analysis of drought occurrence probabilities using the method of Markov chains has shown that the occurrence probabilities of drought events are higher in the Lanyang River basin than in the Yilan River basin; particularly for extreme events, the occurrence probability of an extreme drought event is 20.6% during the dry season (November to April) in the Lanyang River basin, and 3.4% in the Yilan River basin. This study shows that for analysis of drought/wet occurrence probabilities, the results obtained for the drought frequency and occurrence probability using short-term data with the method of Markov chains can be used to predict the long-term occurrence probability of drought/wet events.
Highlights
Climate change is the biggest threat to human society in the 21st century
The streamflow drought index (SDI) method was used to analyze the severities of drought and wet events in the
The method of Markov chains was used to analyze the transition frequency of SDI values at different time durations, which enables the prediction of occurrence probability of an event severity
Summary
Climate change is the biggest threat to human society in the 21st century. A report of the Intergovernmental Panel on Climate Change (IPCC) has pointed out, based on temperature observations over the past 133 years, that from 1880 to 2012, the global mean surface temperature has increased by 0.85 °C, along with significant regional differences. In order to understand the process of hydrological drought and its impact, many variables need to be analyzed in detail, including the time of occurrence, severity, duration, and spatial distribution using different methods [2,7,8,9,10,11,12,13,14]. Among the drought monitoring methods, Nalbantis (2008) proposed the method of SDI, which analyzes drought characteristics based on cumulative streamflow volumes. Advantages of this method include simplicity and high effectiveness. The drought occurrence probabilities were calculated using the Markov chain method
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