Evolution of Japan's flood control planning and policy in response to climate change risks and social changes

Building a sustainable society by strengthening disaster resilience is a common goal in the world. It is crucial to promote cooperation between the general public and the science community by sharing data, information, knowledge, experiences, and ideas. Japan has routinely been beset by catastrophic floods caused mainly by destructive typhoons and critically active seasonal fronts. With the turn of the 21st century, changes in climate and society required additional realignment into the standardized procedures that had evolved over the previous half-century. Japan's new policy, ‘River Basin Disaster Resilience and Sustainability by All,’ takes comprehensive measures, mainly consisting of flood prevention, exposure reduction, and appropriate evacuation, response and recovery, aiming to strengthen disaster resilience and achieve sustainability through concerted efforts among all stakeholders. The policy can play a key role in the achievement of the common global goal.

Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms

Improving the ability of the urban rail transit system to cope with rainstorm disasters is of great significance to ensure the safe travel of residents. In this study, a model of the hierarchical relationship of the influencing factors is constructed from the resilience perspective, in order to research the action mechanisms of the influencing factors of urban rail transit stations susceptible to rainstorm disaster. Firstly, the concept of resilience and the three attributes (resistance, recovery, and adaptability) are interpreted. Based on the relevant literature, 20 influencing factors are discerned from the 3 attributes of the resilience of urban rail transit stations. Subsequently, an interpretative structural model (ISM) is utilised to analyse the hierarchical relationship among the influencing factors. The key influencing factors of station resilience are screened out using social network analysis (SNA). Combined with ISM and SNA for analysis, the result shows that the key influencing factors are: “Flood prevention monitoring capability”; “Water blocking capacity”; “Flood prevention capital investment”; “Personnel cooperation ability”; “Emergency plan for flood prevention”; “Flood prevention training and drill”; “Publicity and education of flood prevention knowledge”; and “Regional economic development level”. Therefore, according to the critical influencing factors and the action path of the resilience influencing factors, station managers can carry out corresponding flood control work, providing a reference for enhancing the resilience of urban rail transit stations.

Dynamic Assessment of Flood Hazard Based on Points-of-Interest Data

In order to better formulate flood prevention and disaster mitigation measures and reduce the impact of urban flood on social development, it is necessary to conduct a scientific and accurate flood hazard assessment. The development of big data technology has brought new opportunities for flood hazard assessment. This study used a coupling model to simulate urban flood, and used the HR method to classify flood hazard. The dynamic change process of two types of Points-of-Interest(POIs) for catering services and living services under different flood hazard degrees were counted. The results showed that (1) In the northern part of the basin, mountainous, impervious ground and the lack of effective drainage channels have combined to cause more serious floods; (2) The flood hazard were mainly low-degree in the study area. Moderate flood hazard mainly occurred in farmland and built-up land. High-degree and extreme-degree flood hazard mainly occurred on both sides of rivers in the northwest of the basin; (3) Affected by the rainfall pattern, the number of POI affected by flood presented the characteristics of “three stages” under four flood hazard degrees; (4) The POIs of the two services was most seriously affected by the flood when the rainfall just stopped; (5) In terms of the proportion of POIs affected by floods, the impact of floods on the two industries is basically the same, but from the perspective of the number of POIs affected by floods, catering services will be more affected; (6) The spatial location of the POIs led to a slight difference in the trend of the number of POIs under high-degree and extreme-degree flood hazard. This study provided a new method for urban flood hazard dynamic assessment, which could help decision makers formulate more targeted flood prevention and disaster mitigation measures

Cascading Models of CNN and GRU with Autoencoder Loss for Precipitation Forecast in Thailand

It is a crucial task to accurately forecast precipitation, especially rainfall in Thailand, since it relates to flood prevention and agricultural planning. In our prior work, we have presented a model based on deep learning approach; however, its performance is still limited due to two main issues. First, there is an imbalance issue, where most rainfall is zero or no rain because Thailand has short rainy season. Second, predicted rainfall is still underestimated since moderate and heavy rainfall cases barely occurs. In this paper, we propose an enhanced deep learning model to forecast rainfall in Thailand. Our model is a cascading of CNN and GRU along with exogenous variables, i.e., temperature, pressure, and humidity. There are two stages in our model. First, CNN is specialized for classifying rain and non-rain events. In this stage, an imbalanced issue is alleviated by applying “focal loss”. Second, GRU is responsible for forecasting rainfall. Its predicted range is lifted using “autoencoder loss”. The experiment was conducted on hourly rainfall dataset between 2012 and 2018 obtained from a public government sector in Thailand. The results show that our enhanced model outperforms ARIMA and CNN-GRU in terms on RMSE of most regions in Thailand.

Protecting Existing Urban Green Space versus Cultivating More Green Infrastructures: Strategies Choices to Alleviate Urban Waterlogging Risks in Shenzhen

For urban waterlogging alleviation, green infrastructures have been widely concerned. How to carry out scientific green infrastructure planning becomes an important issue in flood control and disaster relief. Based on historical media records of urban waterlogging from 2017 to 2020 and combined with variables about topography, land cover and socioeconomics, we used the Radial Basis Function Neural Network (RBFNN) to conduct urban waterlogging susceptibility assessment and simulate the risk of waterlogging in different scenarios of green land configuration in Shenzhen. The results showed that: (1) high proportions of impervious surface and population could increase the risks in Luohu and Futian districts, followed by Nanshan and Baoan districts, while high proportions of green space could effectively reduce the risks in southeastern Shenzhen; (2) urban waterlogging in Luohu and Futian districts can be alleviated by strengthening green infrastructure construction while Longgang and Longhua districts should make comprehensive use of other flood prevention methods; (3) turning existing urban green space into impervious surfaces would increase the risks of waterlogging, which is more evident in places with high proportions of green space such as Dapeng and Yantian districts. The effectiveness of green infrastructures varies in different spatial locations. Therefore, more attention should be paid to protecting existing green spaces than cultivating more green infrastructures in urban waterlogging alleviation.

Experimental Optimization of Self-Priming Pump Based on the Full Factor Test

Self-priming pump as the core equipment for flood fighting and emergency rescue plays an important role in flood prevention and other fields. More importantly, the geometric parameters of the self-priming nozzle directly determine the performance of the self-priming pump. In the previous analysis，only small amount of experiment was conducted to optimize the geometry parameters of self-priming nozzle, and the interaction between the parameters was not considered. In this paper, the full factor test method is employed to explore the main and interaction effect of the nozzle geometric parameters on the self-priming performance, and the order of response to self-priming time is obtained. Meanwhile, a novel self-priming performance model was established, the self-priming time of different geometric parameters self-priming nozzles can be effectively predicted, and the test analysis cycle and production costs were greatly reduced. Finally, the self-priming test under different self-priming height with optimal self-priming nozzle was conducted, the variation regulation between self-priming time and self-priming height was obtained. Therefore, this research could effectively provide the design reference of self-priming nozzles optimization.

Harmonizing Erosion Control and Flood Prevention with Restoration of Biodiversity through Ecological Engineering Used for Co-Benefits Nature-Based Solutions

Reconciling erosion control and flood prevention with restoration of diversity is an important challenge for our societies today. However, examples of applications remain rare because practitioners and engineers are searching for more integrated solutions for this kind of situation. New considerations should, therefore, refocus attention on developing innovative actions by raising the question of how best to accommodate the two components. Moreover, little attention has been paid to erosion processes and their control for decreasing floods, although this can largely contribute to this purpose. Merging security with ecology, turning to co-benefits nature-based solutions at the catchment scale, based on the use of local ecological engineering, especially soil and water bioengineering combined with civil engineering, can provide adapted practices for harmonizing flood prevention and erosion control with restoration of biodiversity at the water catchment scale. This kind of approach should be accompanied by proposals for coherent and adapted governance for application of co-benefits nature-based solutions at the catchment and territory scales.

Infiltration wells utilizing watershed conservation for flood prevention

Rainfall is a determining factor in analyzing planned floods. This research was conducted by collecting secondary data and the field data concerning the soil’s ability to infiltrate the volume of rainfall. Data processing is carried out by statistical analysis to estimate the average rainfall, intensity value, estimated discharge plan, volume of runoff and estimated infiltration rate. These parameters are important related to the infiltration well dimensions planning and the conserving water area. From the research results, it is shown that infiltration rate and optimal dimensions of infiltration wells very dependent on rainfall discharge and runoff volume in each region. Artificial infiltration is an alternative solution for maintaining groundwater balance and overcoming water problems. With groundwater infiltration, groundwater infiltration can maintain a relatively stable groundwater depth. Infiltration rate in RT 06 Cawang are 54,03 cm/hour lower than in Kelurahan 11 Cawang East Jakarta are 54,12 cm/hour, with perimeter area of wells DSP = 1,5 m2, Depth of well (HSP) = -1,89 m2 and coverage area of well (ASP) = 1,77 m2.

Flow velocity behavior programming on open channel bends

Flow velocity on open channel bends generally experiences additional velocity which is called secondary velocity. This paper aims to analyse and calculate the velocity that occurs in an open channel bend in general. The calculation that the writer uses is the calculation with fortran programming, in a case study of a river that bends, where the variables that must be present are given. The results of calculations and measurements of Secondary Speeds that occur at channel bends in this Open Channel will be very useful for river channel improvement or flood prevention in river channels, especially on existing bends. The conclusion is that at the bend of an open channel or river, there will be an increase in flow velocity in the transverse direction. This additional velocity is caused by the additional secondary velocity, namely the transverse velocity.