A report from World Bank in 2022 reveals that about 1.81 billion people (23% of the world population) are directly exposed to flood with depths greater than 0.15 meters. In this study, we evaluate the impact of extreme rainfall events on population in urban areas in Taiwan using SOBEK models. The validation results of the SOBEK models are promising with photos collected from social media for historical storm events. To further assess the impact of extreme rainfall events, we used design rainfall with hourly rainfall of 80mm/hr, 90mm/hr, and 100mm/hr derived from Simple Scaling Gaussian Markov (SSGM) method for single rainfall gauge within major urban area. These results are provided for disaster prevention authority to reinforce the flooding management in urban area.

With the growing concern about the failure risk of river embankments in a rapidly changing climate, this study aims to quantify the overtopping probability of river embankment in Kao-Ping River basin in southern Taiwan. A water level simulation model is calibrated and validated with historical typhoon events and the calibrated model is further used to assess overtopping risk in the future under a climate change scenario. A dynamic downscaled projection dataset, provided by Meteorological Research Institute (MRI) has been further downscaled to 5-km grids and bias-corrected with a quantile mapping method, is used to simulate the water level of Kao-Ping River in the future. Our results highlighted that the overtopping risk of Kao-Ping River increased by a factor of 5.7~8.0 by the end of the 21st century.

This study examined the Kaoping River basin, Taiwan, an area severely destroyed by Typhoon Morakot in 2009. Dynamically downscaled data were applied to simulate extreme typhoon precipitation events for facilitating future preparation efforts (2075–2099) under climate change conditions. Models were used to simulate possible impacts in upstream and downstream areas for basinwide disaster loss assessment purposes. The Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability and FLO-2D models were applied to simulate slope-land disaster impacts and sediment volume in the upstream area. The sediment delivery ratio was used to calculate the valid sediment amount delivered downstream and the riverbed uplift altitude. SOBEK was used to build a flood impact model for the Kaoping River basin, and the model was used to simulate potential flooding caused by future extreme typhoon events. The Taiwan Typhoon Loss Assessment System established by the National Science and Technology Center for Disaster Reduction was used to evaluate the potential loss associated with extreme events. The property loss calculation included 32 land-use categories, including agriculture, forestry, fishery, and animal husbandry losses; industrial and commercial service losses; public building losses; and traffic and hydraulic facility losses. One of the Kaoping River basin townships, Daliao District, had the highest flood depth increase ratio (12.6%), and the losses were 1.5 times the original situation. This was much worse than were the losses suffered during Typhoon Morakot. These results also show that sediment delivered from the upstream areas had a significant influence on the downstream areas. This is a critical issue for future flood mitigation under climate change conditions.

This study evaluated the overflow risk of the Tsengwen River under a climate change scenario by using bias-corrected dynamic downscaled data as inputs for a SOBEK model (Deltares, the Netherlands). The results showed that the simulated river flow rate at Yufeng Bridge (upstream), Erxi Bridge (midstream), and XinZong (1) (downstream) stations are at risk of exceeding the management plan’s flow rate for three projection periods (1979–2003, 2015–2039, 2075–2099). After validation with the geomorphic and hydrological data collected in this study, the frequency at which the flow rate exceeded the design flood was 2 in 88 events in the base period (1979–2003), 6 in 82 events in the near future (2015–2039), and 10 in 81 events at the end of the century (2075–2099).

Climate change is a real threat that brings heavier and more frequent extreme weather events. Many researchers have found that climate change will increase the risk of flooding around the world. The SOBEK inundation model and Taiwan Typhoon Loss Assessment System (TLAS) are used in this study to see if embankment and flood storage control measures can mitigate the impact (loss) of extreme events under climate change. Based on the simulation results, three inundation cases are simulated starting about 18 hr after the embankment is breached. When embankment and detention pond measures are not in place (Case A), the average flood depth in the catchment area caused by the TOP event is roughly 1.45 m. When adaptation measures such as [Case B raising embankments (Case B) and] are in place, the flood depth decreased by 39 and 33%, respectively. TLAS was used to evaluate the potential losses associated with the three cases (Case A, B, and C). When we add flood-control measures, the total loss reduced by adaptation measures for future extreme events in the Zhengwen River basin was NT$7 billion. This study provides applicable coping strategies for future extreme precipitation events that will effectively reduce the impact of extreme storm events.

Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS), which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present), 2015 - 2039 (Near-future), and 2075 - 2099 (Future), provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM). Ten extreme rainfall (top ten) events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present) and 0.9 - 2.2 (Future/Present), respectively. Additionally, we evaluated how these future discharges would affect the reservoir's flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam's spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir's flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.

To understand the characteristics of severe floods under global climate change, we created a design hyetograph for a 100-year return period. This incorporates a modified ranking method using the top 10 extreme rainfall events for present, near-future, and far-future periods. The rainfall data sets were projected with a general circulation model with high spatial and temporal resolution and used with a flood model to simulate the higher discharge peaks for the top 10 events of each term in a local watershed. The conventional-like ranking method, in which only a dimensionless shape is considered for the creation of a design hyetograph for a temporal distribution of rainfall, likely results in overestimates of discharge peaks because, even with a lower peak of rainfall intensity and a smaller amount of cumulative rainfall, the distribution shape is the only the factor for the design hyetograph. However, the modified ranking method, which considers amounts of cumulative rainfalls, provides a discharge peak from the design hyetograph less affected by a smaller cumulative rainfall depth for extreme rainfall. Furthermore, the effects of global climate change indicate that future discharge peaks will increase by up to three times of those of Present-term peaks, which may result in difficult flood control for the downstream river reaches.

The microwave/infrared rainfall algorithm MIRA method combines microwave and infrared channels for their respective contributions to the achievement of higher rainfall-correlated and spatial resolution data, in order to acquire appropriate rainfall data for hydrological models. In this study, estimates of rainfall rate using the MIRA method are affected by the time lag between the data acquisition of the microwave and infrared channels. The root-mean-square error RMSE for comparing the rainfall rate retrieved by the MIRA method 5-minute time lag between microwave and infrared data to the ground rainfall rate in Taiwan is 12.23 mm hour−1 with a correlation coefficient of 0.58. In addition, by comparing rainfall estimated by the TMI-2A12 and the MIRA method for three typhoons, the rainfall estimated by the latter method is more significantly correlated with the ground-observed rainfall.

This article proposes an improved multi-run genetic programming (GP) and applies it to estimate the typhoon rainfall over ocean using multi-variable meteorological satellite data. GP is a well-known evolutionary programming and data mining method used to automatically discover the complex relationships among nonlinear systems. The main advantage of GP is to optimize appropriate types of function and their associated coefficients simultaneously. However, the searching efficiency of traditional GP can be decreased by the complex structure of parse tree to represent the multiple input variables. This study processed an improvement to enhance escape ability from local optimums during the optimization procedure. We continuously run GP several times by replacing the terminal nodes at the next run with the best solution at the current run. The current method improves GP, obtaining a highly nonlinear meaningful equation to estimate the rainfall. In the case study, this improved GP (IGP) described above combined with special sensor microwave imager (SSM/I) seven channels was employed. These results are then verified with the data from four offshore rainfall stations located on islands around Taiwan. The results show that the IGP generates sophisticated and accurate multi-variable equation through two runs. The performance of IGP outperforms the traditional multiple linear regression, back-propagated network (BPN) and three empirical equations. Because the extremely high values of precipitation rate are quite few and the number of zero values (no rain) is very large, the underestimations of heavy rainfall are obvious. A simple genetic algorithm was therefore used to search for the optimal threshold value of SSM/I channels, detecting the data of no rain. The IGP with two runs, used to construct an appropriate mathematical function to estimate the precipitation, can obtain more favourable results from estimating extremely high values. Copyright. (C) 2011 John Wiley & Sons, Ltd.

This paper proposes a back-propagated network (BPN) and applies it to predict the rainfall using meteorological satellite data. In the case study, the back-propagated network (BPN) combining with SGji-Dao SM/I microwave frequency channels was employed to establish a suitable method for estimating rainfall at sea surface during typhoon periods. These results are then verified with the data from four rainfall stations located at Peng-Jia-Yu, Don-, Lan-Yu, and Green Island. From the results, the back-propagated network (BPN) outperforms the traditional multiple linear regression and empirical equations with lower estimating errors for predicting the sea-surface rainfall during typhoon periods.

Naltrexone, an opioid receptor antagonist, has been claimed to have anti-inflammatory and immunomodulatory effects both in vitro and in vivo. Thus, the aim of this study was to evaluate the effects of naltrexone on acute hepatitis induced by intraperitoneal (i.p.) administration of lipopolysaccharide (LPS, 20 μg/kg)/D-galactosamine (D-gal, 700 mg/kg) in conscious ICR mice. Results demonstrated that post-treatment with naltrexone (20 mg/kg, i.p.) significantly attenuated the deleterious liver function in mice treated with LPS/D-gal. It was also found that naltrexone significantly inhibited the elevation of plasma tumor necrosis factor-α (TNF-α) caused by LPS/D-gal. The overproduction of nitric oxide (NO) and superoxide anions induced by LPS/D-gal were also significantly reduced by naltrexone. Moreover, infiltration of neutrophils into the liver of mice 12 h after treatment with LPS /D-gal was also decreased by naltrexone. In conclusion, the beneficial effects of naltrexone on LPS/D-gal–induced hepatitis result from its inhibition of pro-inflammatory factors and antioxidant effects. Thus, naltrexone is of therapeutic potential for treating liver injury.

Dextromethorphan (DM), an antitussive agent, has been claimed to have anti-inflammatory and immunomodulatory effects in vitro. Thus, the aim of this study was to evaluate the effects of DM on sepsis induced by intravenous (i.v.) administration of lipopolysaccharide (LPS) in anesthetized Wistar rats and by intraperitoneal administration in conscious ICR mice. Results demonstrated that pretreatment with DM (1, 5 and 10 mg/kg, i.v.) significantly attenuated the deleterious hemodynamic changes (e.g., hypotension and tachycardia) in rats treated with LPS. Meanwhile, DM (5 mg/kg) significantly inhibited the elevation of plasma tumor necrosis factor-α and interleukin-10 levels, as well as values of GOT and GPT (as an index of liver function), and BUN and creatinine (as an index of renal function) caused by LPS. The induction of inducible NO synthase and the overproduction of NO and superoxide anions by LPS were also reduced by DM. Moreover, infiltration of neutrophils into the lungs and liver of rats 6 h after treatment with LPS was also reduced by DM. In conclusion, the beneficial effects of DM on LPS-induced sepsis result from its anti-inflammatory and antioxidant effects. Thus, DM can possibly be used as a prophylactic agent for sepsis in the future.