This special issue summarizes the main results of the latter half of a five-year project called SATREPS (Science and Technology Research Partnership for Sustainable Development) supported by Japan International Cooperation Agency (JICA) and Japan Science and Technology Agency (JST). The project title is “Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar” and it is the first SATREPS project adopted in Myanmar. Yangon Technological University (YTU) is a major counterpart organization and both national and local governmental organizations are working together as strategic partners.

In the first half of the project, a database was constructed, composed of important data for assessing urban safety and disaster risk, such as the ground properties, and distribution of buildings, people, and traffic. Using the database, city development model and evaluation models for flood and earthquake risks were developed.

In the latter half of the project, combining these two evaluation models, a system was developed for discussing future damage differences due to different urban plans and countermeasures. Furthermore, regarding flood, near-real-time flood inundation simulation system was developed. Related to earthquake disaster, a support system was developed for implementation of efficient countermeasures for both pre- and post-disaster. For infrastructure maintenance, performance monitoring and maintenance methods were proposed. Finally, in order to continue research activities and promote a continuous utilization of project results, a consortium scheme in which industry, government, and academia can work together has been created.

We hope that our SATREPS project activities can contribute to proper urban development and improvement of disaster management issues not only in Myanmar but also in other Asian countries.

This paper introduces an integrated model that combines the Rainfall Runoff Inundation (RRI) and spatially distributed flood damage estimation models. There are three steps for fulfilling this purpose. The first step is the accomplishment of RRI model for the floodplain region. The second step is a questionnaire survey to analyze the economic damage to affected population and properties caused by the past flooding events; this step aims to estimate the different levels of agricultural damage cost. Finally, the economic flood damage estimation model was developed for the agricultural areas by using the stage-damage function models which were established by the multiple regression analysis of questionnaire survey data. The model results were expressed through spatially distributed flood damage maps for extreme flood events, such as those in 2014, 2015, and 2018. The results were validated by collecting damage cost data from the Department of Agricultural Lands Management and Statistics (DALMS). The final findings included comparative scenarios for reducing damage cost in the most effective and realistic way. The output product was the agricultural damage estimation model. For further research, the model was recommended for application in other study areas with different flood scales.

A massive flood in Myanmar struck the Bago river in July, 2018. In this study, because of the limitation of real-time data availability, the satellite-based precipitation was used for clarifying the characteristics of the flood. The total precipitation during 10 days from July 22, when the flood first began at the western Bago city, was estimated approximately 753 mm and 527 mm at the Bago and Zaungts stations in the Bago river watershed. These values were corresponding to 355% and 294% of average of the 10-day total precipitation at the Bago (1967–2015) and Zaungts (1987–2014) stations. Furthermore, not only the 3-day and weekly peak precipitations but also the annual accumulative precipitations during July 22 and August 16 were estimated larger than the largest recorded precipitations at both stations. Although the Zaungts dam stored approximately 140 million m³ during this period, which was an amount equivalent to 40% of inflow volume during July 22 and 28, the resulting flood widely propagated in the Bago city. Based on the flood survey, the 2018 Bago river flood was classified into 4 areas; the right bank of the Bago river, the eastern town, the northern town, and the downstream from the Zaungts Weir and Bago city. These areas were marked as vulnerable areas in the Bago city. The Bago river watershed has experienced many floods in the past, and floods on the same scale as this flood are expected to occur in the future. Therefore, it is essential to understand the characteristics of the 2018 Bago river flood and develop near real-time monitoring of hydrometeorological situation to be prepared for the next flood disaster.

The need for electricity is rapidly increasing, especially in developing countries. There is vast hydropower potential existing globally that has not yet been explored. This could be the only solution to solve future global power shortage. Hydropower is a clean and renewable source of energy because it does not exploit the use of water. However, using the conventional approach to harness hydropower results in several challenges. It is difficult to identify suitable sites and assess site potential during the planning stage of hydropower projects. In this study, run-of-river hydropower potential for the Myitnge River Basin was estimated by intergrating a Geographic Information System (GIS) and Soil & Water Assessement Tool (SWAT) model. A GIS based tool was developed using Python to spot the potential locations of the hydropower plants. The hydrological model (SWAT) was designed in order to obtain the values of monthly discharge for all potential hydropwer sites. The flow duration curves at potential locations were developed and the design discharge for hydropower was identified. Forty-four run-of-river (ROR) type potential hydropower sites were identified by considering only the topographic factors. After simulation with SWAT model, twenty potential sites with a hydropower generation potential of 292 MW were identified. Currently, only one 790 MW Yeywa Hydropower Plant, which is the largest plant in Myanmar, exists in the Myitnge River Basin. The amount of estimated power generated from ROR may increase the existing power system of Myitnge Basin by 36%. This study will assist stakeholders in the energy sector to optimize the available resources to select appropiate sites for small hydropower plants with high power potential.

The Bago River Basin in Myanmar is highly flood-prone. To develop a flood forecasting system, an inundation map of the Bago River Basin is required. This study applied the Rainfall-Runoff-Inundation (RRI) model and SOBEK model to simulate flood discharges and inundation to determine the model most suitable for analysis of the study basin in terms of user friendliness, cost, type of output, and correlation between simulated and observed data. In this study, five flood events were selected to calibrate and validate the models, using discharge data measured at Bago station. The Nash–Sutcliffe efficiency (E_NS) and coefficient of determination (R²) were used to evaluate the performance of the models. The simulated flood inundation area was validated with satellite images. According to the comparison, the SOBEK model is more accurate than the RRI model, and the simulated and observed discharges are closely related. However, when the calculation time and cost are included in the consideration, the RRI model is preferable, as it is faster and freely available. For the Bago River Basin, the RRI model is efficient in predicting the potential flood duration and areas of inundation in near-real time, whereas the SOBEK model is useful for floodplain management. This study shows that the RRI and SOBEK models are applicable to any basin in Myanmar that is similar to the Bago River Basin.

The increasing flood risks in the Bago River due to rapid urbanization and climate change have great implications on the local development and quality of life in the basin. Therefore, the current flood hazard and potential future changes in flooding due to climate change must be assessed. This study investigates the potential flood frequency change in the Bago River and its sensitivity to the bias-correction method used in climate projections from the downscaled Global Climate Model (GCM) output. A pseudo-global warming method using MIROC5 RCP 8.5 was employed to produce 12-km 30-y historical and future climate projections. Empirical quantile mapping (EQM), gamma quantile mapping (GQM), and the multiplicative scaling method (SCM) were used for bias-correcting the rainfall input of the water-energy budget distributed hydrological model (WEB-DHM). The impacts of bias-correction methods used in reproducing the annual maximum series in the frequency analysis are sensitive to the trend of potential future changes in flood discharge frequency estimation. All methods exhibited decreases in the flood peak discharge for 50-yr and 100-yr flood predictions, which may primarily be due to the MIROC5 GCM used. However, the variation in the magnitude of the change is wide. This demonstrates the uncertainty of the frequency analysis for flood magnitude due to the employed bias-correction method. This uncertainty has significant implications on risk quantification conducted using downscaled climate projections. The effect of the uncertainty of the bias-correction method on the annual maximum rainfall time series should be communicated properly when conducting risk and hazard assessment studies.

Flood loss models are essential tools for assessing flood risk. Flood damage assessment provides decision makers with critical information to manage flood hazards. This paper presents a multivariable flood damage assessment based on data from residential building and content damage from the Bago flood event of July 2018. This study aims to identify the influences on building and content losses. We developed a regression-based flood loss estimation model, which incorporates factors such as water depth, flood duration, building material, building age, building condition, number of stories, and floor level. Regression approaches, such as stepwise and best subset regression, were used to create the flood damage model. The selection was based on Akaike’s information criterion (AIC). We found that water depth, flood duration, and building material were the most significant factors determining flood damage in the residential sector.

Understanding of system requirements that satisfy end users’ needs is fundamental of system development, yet challenging when end users are unable to address their needs explicitly. Although a number of scholars have been designing and applying requirement elicitation techniques, there is a research gap in Spatial Decision Support System (SDSS) with Web-based Geographical Information System (Web-GIS) in water resource management for disaster risk reduction. The gap addresses especially design elicitation techniques and their performances 1) to understand data types used for decision making, 2) set timing for sharing the data to accomplish end users’ tasks, and 3) compile the data to be represented so as to facilitate end users’ decision making. This study therefore designed a requirement elicitation technique by advancing User Story Mapping (USM) and validated through a workshop using mock-up system interface with potential end users who are in charge of water resource management in Myanmar’s Bago River Basin. Through the research it could be validated that the user stories-based approach enabled end users to decompose their operation activities into tasks. It also allowed them to link to necessary data with visual image for facilitating their task accomplishments and decision making for water resource management. It was revealed that the benefits of using the designed approach are not only just to summarize necessary data and information for end users’ decision making but also to encourage them to proactively consider data utilization into their operations. For further development of the requirement elicitation to understand end users needs, insights and recommendations for the proposed technique designing and conducting of the workshop were obtained.

Climate change affects both the temperature and precipitation, leading to changes in river runoff. The Bago River basin is one of the most important agricultural regions in the Ayeyarwady Delta of Myanmar, and this paper aims to evaluate the impact of climate change on it. Linear scaling was used as the bias-correction method for ten general circulation models (GCMs) participating in the fifth phase of the Coupled Model Intercomparison Project. Future climate scenarios are predicted for three 27-year periods: the near future (2020–2046), middle future (2047–2073), and far future (2074–2100) with a baseline period of (1981–2005) under two Representative Concentration Pathway (RCP) scenarios: RCP4.5 and RCP8.5 of the IPCC Assessment Report 5 (AR5). The Hydrologic Engineering Center-Hydrologic Modeling System model is used to predict future discharge changes for the Bago River considering future average precipitation for all three future periods. Among the GCMs used to simulate meteorological data in the Ayeyarwady Delta zone, the Model for Interdisciplinary Research on Climate-Earth System is the most suitable. It predicts that average monthly precipitation will fluctuate and that average annual precipitation will increase. Both average monthly and annual temperatures are expected to increase at the end of the 21st century under RCP4.5 and RCP8.5 scenarios. The simulation shows that the Bago River discharge will increase for all three future periods under both scenarios.

Topography represented in the form of Digital Elevation Models (DEMs) has profound applications in hydrological modeling. DEMs can be generated from several sources including satellite products, contours, survey data, and LiDAR, each with their own merits and demerits. Where high resolution, accuracy, and spatial extent are concerned, it is often found that a DEM from one source alone is not able to represent the topography of the target area with full accuracy. Upon comparing different DEMs, it was found that most were able to successfully represent mountainous regions but failed to represent flat deltaic regions. Therefore, in this research with Bago River basin, Myanmar as a study area, a new methodology to combine multiple sources of data with different data types is developed. The inputs are: (a) a 10 m DEM, developed using contour data, point elevation data, and UTM topographic maps; (b) a 5 m Digital Surface Model (DSM) acquired by the Advanced Land Observation Satellite (ALOS); and (c) 168 sets of multiple-point elevation data representing a cross-sectional survey along the Bago River and the Bago-Sittaung canal. The output is a 10 m resolution Enhanced DEM (EnDEM) which is able to preserve the merits of all the input data, i.e., upper mountainous region, lower flat deltaic basin, and the river bathymetry. This paper provides a novel approach to DEM integration and burning of the river cross-section onto the DEM.

Flooding has always been one of the major hazards in Myanmar, accounting for 11% of all disasters. The Bago River Basin is a floodprone area in Myanmar, where, during the last decade, many severe floods occurred during the monsoon season, usually in July and August. Most of these floods are caused by storm rainfall. The 2011 and 2018 floods form part of the historical record of Bago. The main objective of this research paper is to develop a new hydrological model (WEB-DHM) for the Bago River Basin using observed station data to represent floods in the study area. The Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) was used for hydrological modeling as determined for the discharge of floods. The HydroSHEDS digital elevation model is used for the discharge estimation and analysis of the WEB-DHM. The Japanese 55-year Reanalysis JRA-55 data, from the Japan Meteorological Agency (JMA), were used for the preparation of meteorological data for this model. The results of flood discharge from the hydrological modeling and the observed data of the past three years (2014, 2015 and 2016) are provided in this study.

The population of Yangon has increased more than two times in the last 40 years and will reach 9.5 million by 2035. Owing to changes in car import policies, the number of cars in Yangon has increased from 3.6 million to 6.3 million in 5 years. This causes severe traffic congestion, resulting in social, economic, and environmental impacts. Rail transportation is one solution to this problem, but regular maintenance of railway tracks is necessary. In this study, onboard sensor measurement and satellite image analysis are used to monitor rail track conditions for the early detection of damage. The accelerometer in a smartphone is placed against the car body to measure the vertical and lateral acceleration. The smartphone vibrates as the cabin vibrates when the train passes irregular rail track sections. Phased-array-type L-band synthetic aperture radar images are analyzed using the interferometric technique to detect rail track irregularities. Thus, the rail track conditions can be estimated effectively.

After the collapse of Myaungmya Bridge in April 2018, the safety of infrastructure became an urgent task and attracted increased public interest in Republic of the Union of Myanmar. After the incident, monitoring systems were installed in several suspension bridges, of the same structure type as Myaungmya Bridge, recording unwanted bridge movements. The observations indicate that a large deformation occurred, rendering the current bridge condition different from its original design, though the safety of the current condition is unclear. Therefore, in this study, numerical models are simulated utilizing the data from detailed observations made by the monitoring system, to confirm the safety of the bridge. Twantay Bridge was chosen as the bridge analysis target. Linear time history analyses were performed on Twantay Bridge, in which the seismic performance was evaluated by comparing the stresses generated in the main members with the allowable stresses. Moreover, by comparing the analysis results obtained from two models – a design drawing model of the Twantay Bridge, and a model that reproduced the present condition of the bridge – the current bridge performance was confirmed. The information obtained from this analysis is useful in the field of maintenance and will allow Myanmar officials to effectively plan and take corrective action for the requisite maintenance of the damaged bridge.

To ensure the long-term performance of bridges in Myanmar, the Japan International Cooperation Agency (JICA) initiated a capacity development project to enhance the quality control capabilities of engineers in the Myanmar government. Such expertise will be transferred to a group of “core trainers,” who will be responsible for sharing their acquired skills and knowledge with other engineers in Myanmar. The effective transfer of Japanese expertise is thus crucial for realizing the project’s goal of improving the quality of bridges and structures managed by the government of Myanmar. This research aims to explore the perspectives and expectations of the core trainers’ for training transfer after the project using the results of a survey questionnaire and to evaluate the effect of various factors on their expectations for transfer using partial least squares path modeling. It was found that the core trainers had positive expectations regarding the benefits of training transfer as well as generally positive perspectives on the factors affecting such transfer. The results of statistical modeling, however, failed to reveal any significant relationships between the modeled factors and the expectations for training transfer. This may be attributable to the sample size, which is limited by the scope of the capacity development project; a mixed method approach is therefore proposed as a more appropriate method in this context. Nonetheless, the results generally suggest that the work environment is fundamental in facilitating effective training transfer, and further research is necessary.

Yangon is one of the most populated and socio-economically important cities in Myanmar. Unfortunately, it is located in a moderately active-seismic area, and significant damage and loss will be incurred if an earthquake occurs there in the future. The seismogenic Sagaing Fault passes 40 km to the E of Yangon, which has experienced several destructive earthquakes in the past. The urban area studied here, Kyauktada, Pazundaung, and Botahtaung townships, are located mostly on a soft alluvial plain, which is mainly composed of sand, silt, and clay, which are sediments prone to amplify seismic waves. The Yangon Bosai Operation Support System (BOSS), designed to establish a proper disaster management system based on the potential damage that a future earthquake might cause, is under development. BOSS has two components damage prediction and damage response – which are based on predicted damage and current response capability and practices in Myanmar. For damage prediction, major inputs include information on the underlying soils, building construction and associated fragility functions, based on different building types. Microtremor survey is a useful tool for reviewing underlying soil layer information, as this can significantly affect vulnerability assessments and the identification of potential damages. Microtremor surveys and analyses were therefore conducted at 88 sites throughout the studied urban areas to acquire key ground information for BOSS. Our analyses showed that the fundamental frequency of horizontal to vertical spectral ratio (H/V ratio) of microtremors generally ranged 0.6–2.4 Hz, while the peak amplitude was between 1.3 and 4.0. Soil thickness ranged 60–210 m, and the average shear wave velocity over the ground’s upper 30 m, V_s³⁰, was in the range 180–560 ms^-1. All outcomes from this research will become key input parameters for BOSS development in Yangon.

Myanmar is a thriving country in Southeast Asia and is facing future earthquake risks caused by the Sagaing Fault. Under these circumstances, Yangon must implement earthquake risk reduction measures in future development. Applying the building collapse risk evaluation method proposed by the Tokyo Metropolitan Government, and analyzing current and future urban conditions of Yangon City based on available datasets, this study aimed to (1) evaluate present urban vulnerability focusing on building collapse risk, (2) clarify its future expansion tendency based on residential area development conditions from 2004 to 2018, and (3) estimate future building collapse risk in terms of future urban expansion limitation with urban function and building vulnerability in order to obtain useful information on earthquake risk reduction for future development in Yangon. Mainly, this research clarified as follows: (1) The inventory provided by YCDC (Yangon City Development Committee) showed that wooden buildings and RC accounted for 93.8% of all buildings in Yangon. (2) In order to understand the present urban vulnerability of Yangon based on the Tokyo Metropolitan Government’s method, 567 objective wards were categorized into five ranks according to the building collapse risk value. It indicated that building collapse risk in the Dawpon and Tharkayta Townships, located on the west side of Pazundaung Creek, were the highest. Some newly developed outskirts areas, such as Hlaingtharyar or Dala, also appeared as vulnerable with Ranks 4 and 5. (3) Yangon’s urban development conditions from 2004 to 2018 were visually clarified. Then, the relationships between the number of buildings, residential district area, and population according to townships were analyzed to estimate future development. (4) Finally, two types of urban development scenarios were set: Scenario A based on urban expansion limitation and urban function, and Scenario B based on building vulnerability. Then, the future building collapse risk trend from 2014 until 2040 was estimated. It was found that the Sub-center System would deter future urban sprawl in the future more than the Super CBD Single-core System, and the number of damaged buildings can be reduced by 43.5% at most in Dagon Seikkan.

In Yangon and the suburbs of Myanmar, timber-framed buildings are the popular choice of construction for residential purposes. Nearly 8% of the total population in Yangon live in the slums and slum-like areas where the dwellings are predominantly made of non-durable materials. Wood, jungle wood, and bamboo are used as the framework and corrugated galvanized iron sheets as walling and sheathing material. The seismic-resistance capacity of timber buildings in slum areas has never been approved based on experimental evidence. Therefore, this study aims to conduct a seismic fragility analysis for poorly built timber buildings by providing a suitable method through numerical and experimental approaches. Pull-over loading tests were conducted on selected buildings to assess their loading-displacement capacity. Further, numerical modeling was done using the Wallstat simulation tool, which is based on the discrete element method. The pushover curve was validated with the curve from the pull-over load test. Once the numerical model was confirmed, dynamic analysis was conducted for different peak ground acceleration (PGA) (g) values until the complete numerical collapse of the building. Three building configurations with three ranges of variable material properties were considered in this study. A primary damage state started at the low PGA value of 0.05 g, and it can be confirmed that the timber buildings that were studied, are vulnerable to earthquakes. The results based on qualitative analysis were accumulated to obtain the damage state matrix, which was then used to obtain the fragility curves.

Rapid growth in private vehicle ownership and usage is one of the key problems in the development of a sustainable transportation system for Yangon City. Car ownership depends on the land use patterns and socioeconomic characteristics of a city. Socioeconomic factors, including age, gender, income, house type, and family size also affect the choice of transportation mode and destination in the short and long terms, while the choice of housing location is affected in the long term. In this study, aggregate level land use data and disaggregate level individual and household data are used to determine the effects of land use and socioeconomic factors on household decisions to own zero, one, and two or more cars. This research models car ownership by the estimating multinomial logit model using SPSS (Statistical Packages for Social Sciences). The result suggests that income level, house type of a household, and the housing location have influence on car ownership in Yangon City. The car ownership level will be higher if the household number in the central business district (CBD), inner ring area, and outer ring area is increased. Increase in low income and normal income households will reduce the probability of car ownership in the suburban area.

The use of public buses constitutes the primary daily transportation mode for commuters inside the city of Yangon. The efficiency of the public bus transportation service is important to the local government in terms of public safety and energy saving. The main objective of this study is to understand the current public bus transportation problems in Yangon and to propose a new improved method for the allocation of bus stops. In this study, an on-board survey was conducted to collect bus-passenger counts. Moreover, a check-point survey was carried out to determine the passenger volume at each bus stop and to decide whether the bus stop should be relocated. Finally, a geographic information systems (GIS) model was developed to determine the optimized bus-stop locations based on the passenger volume and on various public-facility locations (such as offices and shopping centers). This study aims to support the Yangon Bus Service (YBS), a major bus transportation service in Yangon city – Myanmar, to optimize its bus network.

Rapid urbanization and modernization are increasing worldwide, including in Myanmar. Mobile call detail records (CDRs) provide new opportunities for measuring transport demands and problems in transportation planning. This research aims to analyze trip distributions and transit behaviors of mobile phone users based on their call activities. Origin-Destination (O-D) pairs were computed for the entire city, and the trip distributions help understand human mobility. It was found that zone-to-zone flow has the highest flow in commercial and industrial areas. Moreover, the logical assumptions were specified to extract the transit behaviors of users. The results indicate the degree of mode-to-mode transfer behaviors of users. Among the four categories of transit usage, only rail users do not transfer to other modes, having the lowest proportion, with other mode-to-other mode transfers having the highest proportion. The results were validated with the Person Trip Survey for Comprehensive Urban Transport Plan of the Greater Yangon. This study contributes significantly to the expansion of current and potential future transit systems, which can provide a new and improved transport system for Yangon City to meet its demands. This information is helpful in conducting disaster management and emergency preparedness in terms of trip distributions of human mobility patterns changing over space and time and the transit behaviors of the transferring mode in daily trips.

This study aims to present the traffic conditions of one of the most congested areas in Yangon as well as the route choice behaviors of the road users in that area. It analyzes drivers’ route choice behaviors and traffic congestion according to road segments. Manual traffic counting and roadside interview methods were used in this survey. The data gathered were used in finding routes alternative to the U Htaung Bo road, which is extremely congested almost all the time. With regard to the report, it will be helpful to identify the scale of the problem that is caused by traffic congestion and to increase awareness of this issue, including amongst the government, policy makers, traffic engineers, and road users.

The current urbanization and motorization have caused a gradual negative impact on the existing transport infrastructure in Yangon City. Currently, the road network throughout Yangon operates at or above its desired capacity during the peak periods. At present, there are over 62,886 registered taxis operating in Yangon City. These taxis provide two different services to passengers: non-metered taxi (traditionally hailed on the street) service and metered taxi (on demand) service. Private cars and taxis constitute 70% of the modes of transport in Yangon City; this may lead to traffic congestion. However, there is lack of relevant data and taxi trip pattern information on how taxi service is related to traffic congestion. Therefore, studies on taxi surveying using Global Positioning Systems (GPS) need to be conducted, and investigations on the effect of taxi services on traffic congestion from these GPS data need to be performed. This study explores the comparison between hourly and daily trips’ frequencies as well as spatial and temporal variations of taxi trips between the two services. Field survey data collected through the GPS and Geographic Information System (GIS) were used to estimate the different taxi travel times that can be applied in predicting the occupied and vacant times in the study area. The specific objective of this research is to examine vacant taxi movement and stationary time (parking time and congestion time) of the two services to quantify the impact of taxi travel time on traffic congestion in Yangon. Moreover, by knowing how the two services vary in terms of operation, the main solution for reducing the congestion in Yangon City can be established. Further, the taxi stationary duration information is useful for knowing the taxi trip hotspot points in each township in Yangon. This may lead to support in defining proposed taxi stands in Yangon City.