Mixed Zero-Inflation Method and Probability Distribution in Fitting Daily Rainfall Data

In hydrological processes, rainfall is one of the important components of water supply for human life. We considered how well the statistical distribution simulates rainfall intensity. We propose an asymmetric statistical probability distribution joined by zero-inflated to fit the daily continuous record of rainfall data in Thailand. The candidate statistical probabilities are General Pareto, Exponential, Beta, Gamma, Generalize extreme value, Extreme Value, Normal, Lognormal, Weibull and Rayleigh distribution. The daily data from 123 rain gauges in Thailand collected and removed in a given year, using the null value. The statistical distributions estimated on the statistical coefficient, using the maximum likelihood estimation (MLE) method and resulted in a cumulative density function (CDF). The CDF compared to the CDF of observed data that estimated, using Kaplan-Meier algorithm. The comparisons were evaluated by Goodness of fit (GOF) in 3 null hypothesis tests (Kolmogorov-Smirnov, Anderson-Darling and Chi-Square test). The best fit distribution was identified by minimum residual (R) index and maximum correlation (Cor) index based on difference value between the estimated and observed data. The Weibull distribution matched to the 118 rain gauges while 5 rain gauges were best fitted by the Gamma distribution.In hydrological processes, rainfall is one of the important components of water supply for human life. We considered how well the statistical distribution simulates rainfall intensity. We propose an asymmetric statistical probability distribution joined by zero-inflated to fit the daily continuous record of rainfall data in Thailand. The candidate statistical probabilities are General Pareto, Exponential, Beta, Gamma, Generalize extreme value, Extreme Value, Normal, Lognormal, Weibull and Rayleigh distribution. The daily data from 123 rain gauges in Thailand collected and removed in a given year, using the null value. The statistical distributions estimated on the statistical coefficient, using the maximum likelihood estimation (MLE) method and resulted in a cumulative density function (CDF). The CDF compared to the CDF of observed data that estimated, using Kaplan-Meier algorithm. The comparisons were evaluated by Goodness of fit (GOF) in 3 null hypothesis tests (Kolmogorov-Smirnov, Anderson-Darling and Chi-Square test). The best fit distribution was identified by minimum residual (R) index and maximum correlation (Cor) index based on difference value between the estimated and observed data. The Weibull distribution matched to the 118 rain gauges while 5 rain gauges were best fitted by the Gamma distribution

Probabilistic Tsunami Hazard Analysis of Inundated Buildings Following a Subaqueous Volcanic Explosion Based on the 1716 Tsunami Scenario in Taal Lake, Philippines

A probabilistic hazard analysis of a tsunami generated by a subaqueous volcanic explosion was performed for Taal Lake in the Philippines. The Taal volcano at Taal Lake is an active volcano on Luzon Island in the Philippines, and its eruption would potentially generate tsunamis in the lake. This study aimed to analyze a probabilistic tsunami hazard of inundated buildings for tsunami mitigation in future scenarios. To determine the probabilistic tsunami hazard, different explosion diameters were used to generate tsunamis of different magnitudes in the TUNAMI-N2 model. The initial water level in the tsunami model was estimated based on the explosion energy. The tsunami-induced inundation from the TUNAMI-N2 model was overlaid on the distribution of buildings. The tsunami hazard analysis of inundated buildings was performed by using the maximum inundation depth in each explosion case. These products were used to calculate the probability of the inundated building given the occurrence of a subaqueous explosion. The results from this study can be used for future tsunami mitigation if a tsunami is generated by a subaqueous volcanic explosion

Tsunami Wave Characteristics from the 1674 Ambon Earthquake Event Based on Landslide Scenarios

This study focuses on understanding the historical tsunami events in Eastern Indonesia, specifically the Banda Sea region, by extracting information from the limited and challenging-to-interpret historical records. The oldest detailed account of a tsunami in Indonesia dates back to 1674, documented in the book Waerachtigh Verhael Van de Schlickelijcke Aerdbebinge by Rumphius. The study aims to comprehend the primary source of the tsunami and analyze its characteristics to facilitate future tsunami risk reduction. The methodology includes collecting topography and bathymetry data, conducting landslide scenario analysis, employing a two-layer wave propagation model, and performing spectral analysis. The study utilizes comprehensive datasets, investigates potential landslide scenarios, simulates tsunami propagation, and analyzes frequency characteristics using the fast Fourier transform. The 1674 event yielded a runup height of approximately 50–100 m, whereas this study underestimated the actual runup. To illustrate the tsunami wave along the bay’s coastline, a Hovmöller diagram was employed. By analyzing the Hovmöller diagram, the power spectral density was computed, revealing five prominent period bands: 6.96, 5.16, 4.1, 3.75, and 3.36 min. The integration of these components provides a rigorous approach to understanding tsunami dynamics and enhancing risk assessment and mitigation in the study area

Systematic Evaluation of Different Infrastructure Systems for Tsunami Defense in Sendai City

The aim of this study is to assess the performances of different infrastructures as structural tsunami countermeasures in Sendai City, based on the lessons from the 11 March 2011, Great East Japan Tsunami, which is an example of a worst-case scenario. The tsunami source model Ver. 1.2 proposed by Tohoku University uses 10 subfaults, determined based on the tsunami height and the run-up heights measured for all tsunami affected areas. The TUNAMI-N2 model is used to simulate 24 cases of tsunami defense in Sendai City based on a combination of 5 scenarios of structural measures, namely, a seawall (existing and new seawall), a greenbelt, an elevated road and a highway. The results of a 2D tsunami numerical analysis show a significant difference in the tsunami inundations in the areas protected by several combinations of structures. The elevated road provides the highest performance of the single schemes, whereas the highest performance of the 2-layer schemes is the combination of an existing seawall and an elevated road. For the 3-layer scenarios, the highest performance is achieved by the grouping of an existing seawall, a new seawall, and an elevated road. The combination of an existing seawall, a new seawall, a greenbelt and an elevated road is the highest performing 4-layer scenario. The Sendai City plan, with a 5-layer scenario, reduces the tsunami inundation area by 20 sq. km with existing structural conditions. We found that the combination of an existing seawall, a greenbelt, an elevated road and a highway (a 4-layer scheme) is the optimum case to protect the city against a tsunami similar to the 2011 Great East Japan Tsunami. The proposed approach can be a guideline for future tsunami protection and the evaluation of countermeasure schemes

Mechanisms of Flood-Induced Levee Breaching in Marumori Town during the 2019 Hagibis Typhoon

Typhoon Hagibis, which occurred at the beginning of October 2019, was one of the largest and most powerful tropical cyclones and was considered to be the most devastating typhoon to hit Japan in recorded history. Extreme heavy rainfall caused massive impacts to Japan in general and to Marumori Town, Miyagi Prefecture in particular. In the present study, the detailed flood characteristics at Marumori Town were investigated by using field observation and numerical simulations. The obtained data immediately after the flood has clearly shown that most levee breaches were caused by the water overflow on the river embankment at the constriction areas such as the tributaries’ junction and the intersection of the river embankment. Numerical simulations were performed to investigate the mechanism of levee breaching in Marumori Town. According to the simulation results, the flooding water from the upstream levee breach locations flowed into the paddy field area and caused the levee to breach at the river embankment interaction in the downstream area. A new levee breach criterion in terms of overflow depth and its duration on the river embankment was proposed. In addition, a sensitivity analysis was also performed to understand the effect of the backwater and phase lag of water level rise between the mainstream and tributaries. Although there have been many studies on flood disasters, the typhoon’s flood-induced disasters on the river and coastal infrastructures have still remained a big challenge. The present study outcomes provide useful information not only to understand how the river embankment of tributaries is vulnerable to water level rise, but also to support the river authorities to prepare better mitigation plans for future flood disasters