The currently used hydrological forecast system in China is mainly focused on flood, and the flood forecasting frameworks are typically based on point discharge measurements and predictions at discrete locations, hence they can't provide spatio-temporal information of various hydrological elements, such as surface runoff, soil moisture, ground water table, and flood inundation extents over large scales and at high spatial resolutions. The use of distributed hydrological model has recently appeared to be the most suitable option to bridge this gap. An open source GIS-based distributed hydrological forecast system was established recently, and the watershed delineation and hydrological modelling were integrated together seamlessly. The time and human consuming work of processing the spatial data in building distributed hydrological model could be reduced significantly, and the spatial distribution of hydrological information could be quickly simulated and predicted using this system. The system was applied successfully to forecast the flood caused by super strong typhoon “Mangkhut” which attacked the south China in 2018.

Super Typhoon Mangkhut hit Hong Kong on September 16, 2018, necessitating the issuance of the highest tropical cyclone warning signal, No. 10 Hurricane Signal. Packing ferocious winds and record-breaking storm surge, Mangkhut brought the most serious and widespread destruction to the territory in the recent three decades. A series of post event information search, field visits and damage surveys has been conducted by the Hong Kong Observatory (HKO) and the findings on the damages and impacts caused by Mangkhut in different parts of the territory are documented in this paper. Moreover, by analyzing the economic loss data reported by various government departments, public utilities and organizations in Hong Kong and the statistics on insurance claims from the Hong Kong Federation of Insurers (HKFI), the estimated direct economic loss due to Mangkhut in Hong Kong is about HK$ 4.60 billion, which is about 3.8 times to that of Super Typhoon Hato in 2017. On the contrary, in the Guangdong-Hong Kong-Macao Greater Bay Area, the estimated direct economic loss due to Hato is significantly higher than that of Mangkhut. This could be attributed to the early and effective warnings for Mangkhut, increased public awareness and typhoon
preparedness for Mangkhut in 2018 since the fierce attack of Hato in 2017, and infrastructure enhancement of the major impact areas.

India follows a strategy of having Multi-Purpose Cyclone Shelters along the coastline for tropical cyclone risk mitigation. These shelters are meant to provide refuge to vulnerable populations at the time of a cyclonic storm and otherwise to be used as school, community centres etc. This paper aims to examine the exact role which these Multi-Purpose Cyclone Shelters seek to perform; as a safe shelter for people living in a tropical cyclone threatened region or meant for those who fail to evacuate due to various reasons. Based on qualitative method and field work conducted after four cyclones which made landfall on India's east coast during 2013e19, this study argues that lack of clarity over its role has led to an emphasis on increasing number of Multi-Purpose Cyclone Shelters proportionate to the population size without due examination of its safety and sustainability aspects.

The characteristics of raindrop size distribution during Typhoon Meranti, determined using disdrometer (LPA10) data collected from 14 to Sep. 15, 2016 in Fujian Province, China, were associated with different parts of the storm. From the front side of the rain band to the central region and then to the rear side or to the residual clouds of Typhoon Meranti, the top of the radar echo, reflectivity, raindrop number concentration and spectrum width all increased when Meranti moved close and then decreased as it moved away. Moreover, precipitation was produced from the stratiform to the oceanic convective and then to the oceanic convective-stratiform mixed clouds or to the stratiform.