Analysis of meteorological drought periods based on the Standardized Precipitation Evapotranspiration Index (SPEI) using the Power Law Process approach

In recent decades, abnormal rainfall and temperature patterns have significantly impacted the environment and human life, particularly in East Nusa Tenggara. The region is known for its low rainfall and high temperatures, making it vulnerable to drought events, which have their own complexities due to being random and changing over time. This study aimed to analyze the trend of short-term meteorological drought intensity in Timor Island, East Nusa Tenggara. The analysis was carried out by utilizing the standardized precipitation evapotranspiration index (SPEI) for a 1-month period to characterize drought in intensity, duration, and severity. A power law process approach was used to model the intensity of the event, which is inversely proportional to the magnitude of the drought event. Intensity parameters of the power law process were estimated using the maximum likelihood estimation (MLE) method to predict an increase in the intensity of drought events in the future. The probability of drought was calculated using the non-homogeneous Poisson process. The analysis showed that “extremely dry” events in Timor Island are less frequent than “very dry” and “dry” events. The power law process model’s estimated intensity parameter showed a beta value greater than 1, indicating an increase in future drought events. In the next 12 months, two months of drought are expected in each region of Timor Island, East Nusa Tenggara, with the following probabilities for each region: 0.264 for Kupang City, 0.25 for Kupang, 0.265 for South Central Timor, 0.269 for North Central Timor, 0.265 for Malaka, and 0.266 for Belu. This research provides important insights into drought dynamics in vulnerable regions such as East Nusa Tenggara and its potential impact on future mitigation and adaptation planning.
Keywords: meteorological; meteorological drought; power law process; non-homogeneous Poisson process; standardized precipitation evapotranspiration index