Search Results (9)

This observation-based and explainable approach demonstrates the applicability of multi-source remote sensing for flood assessment in data-scarce regions, offering a robust scientific basis for flood management and spatial planning in monsoon-affected areas. Floods are among the most frequent and devastating natural hazards, particularly in developing countries such as Myanmar, where monsoon-driven rainfall and inadequate flood-control infrastructure exacerbate disaster impacts. This study presents a satellite-driven and interpretable framework for high-resolution flood susceptibility and risk assessment by integrating multi-source remote sensing and geospatial data with ensemble machine-learning models—Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM)—implemented on the Google Earth Engine (GEE) platform. Eleven satellite- and GIS-derived predictors were used, including the Digital Elevation Model (DEM), slope, curvature, precipitation frequency, the Normalized Difference Vegetation Index (NDVI), land-use type, and distance to rivers, to develop flood susceptibility models. The Jenks natural breaks method was applied to classify flood susceptibility into five categories across Myanmar. Both models achieved excellent predictive performance, with area under the receiver operating characteristic curve (AUC) values of 0.943 for XGBoost and 0.936 for LightGBM, effectively distinguishing flood-prone from non-prone areas. XGBoost estimated that 26.1% of Myanmar’s territory falls within medium- to high-susceptibility zones, while LightGBM yielded a similar estimate of 25.3%. High-susceptibility regions were concentrated in the Ayeyarwady Delta, Rakhine coastal plains, and the Yangon region. SHapley Additive exPlanations (SHAP) analysis identified precipitation frequency, NDVI, and DEM as dominant factors, highlighting the ability of satellite-observed environmental indicators to capture flood-relevant surface processes. To incorporate exposure, population density and nighttime-light intensity were integrated with the susceptibility results to construct a natural–social flood risk framework. This observation-based and explainable approach demonstrates the applicability of multi-source remote sensing for flood assessment in data-scarce regions, offering a robust scientific basis for flood management and spatial planning in monsoon-affected areas. Full article

Introduction: Extreme precipitation events in the Ayeyarwady River Basin, Myanmar, exhibit pronounced spatiotemporal heterogeneity and non-stationarity, yet their linkages to large-scale climate oscillations remain poorly understood. Objective: This study aimed to characterize distinct rainfall regimes, quantify non-stationary extreme event dynamics, and identify teleconnections with oceanic-atmospheric variability over 66 years (1958–2023). Materials and Methods: A hybrid analytical framework integrating K-means clustering, non-stationary Generalized Pareto Distribution modeling, and wavelet coherence analysis was applied to gridded monthly precipitation data from TerraClimate. Results: Four spatiotemporal rainfall clusters were delineated, exhibiting fundamentally different monsoonal characteristics with mean seasonal peaks ranging from 188 mm to 686 mm. Extreme precipitation behavior demonstrated substantial heterogeneity, with 100-year return periods varying from 501 mm in subdued northern zones to 983 mm in hyper-intense coastal regions. Wavelet coherence analysis revealed regime-specific teleconnections: Cluster 2 exhibited the strongest ENSO influence (0.536 coherence strength, 64-month median duration, 1960 peak), while Cluster 4 demonstrated unique IOD dominance (0.479 strength, 74-month duration) extending beyond annual timescales. Teleconnection effectiveness varied substantially across regimes (0.428–0.536 strength) with significant decadal non-stationarity. Limitations and Perspectives: Basin-wide precipitation averages obscure critical regional variations in extreme event magnitudes and climate forcing mechanisms, necessitating regime-differentiated approaches for flood risk assessment and climate-informed water resources management in Myanmar’s most vital river basin. Full article

The continental margin is a major repository for organic carbon; however, anthropogenic alterations to global sediment and particulate terrestrial organic carbon (TerrOC) fluxes have reduced delivery by rivers and offshore burial in recent decades. Despite the absence of mainstem damming, land use change in the Ayeyarwady and Thanlwin River catchments in Myanmar has accelerated over the last 50 years. As a result, deforestation and landscape erosion have likely altered fluvial fluxes to the Northern Andaman Sea shelf; however, the magnitude and preservation of geochemical signals associated with development are unknown. Utilizing elemental and bulk stable and radioisotope analysis, this study investigates spatial and temporal trends in sediment sources and TerrOC concentrations to identify the potential impacts of recent (<100 years) offshore development. While our results demonstrate an along-shelf trend in provenance and TerrOC concentrations, temporal (downcore) trends are not observed. We attribute this observation to frequent, large-scale seabed resuspension and suggest that extensive mixing on the inner shelf creates a low-pass filter that effectively attenuates such signatures. This is in contrast to other large Asian deltas, where signals of human landscape disturbance are clearly preserved offshore. We predict that planned mainstem damming in Myanmar will result in larger alterations in sediment and TerrOC supply that may become apparent offshore in the near future. Full article

Monitoring morphologically dynamic rivers over large spatial domains at an adequate frequency is essential for informed river management to protect human life, ecosystems, livelihoods, and critical infrastructures. Leveraging the advancements in cloud-based remote sensing data processing through Google Earth Engine (GEE), a web-based, freely accessible seasonal river morphological monitoring system for Ayeyarwady River, Myanmar was developed through a collaborative process to assess changes in river morphology over time and space. The monitoring system uses Landsat satellite data spanning a 31-year long period (1988–2019) to map river planform changes along 3881.4 km of river length including Upper Ayeyarwady, Lower Ayeyarwady, and Chindwin. It is designed to operate on a seasonal timescale by comparing pre-monsoon and post-monsoon channel conditions to provide timely information on erosion and accretion areas for the stakeholders to support planning and management. The morphological monitoring system was validated with 85 reference points capturing the field conditions in 2019 and was found to be reliable for operational use with an overall accuracy of 89%. The average eroded riverbank area was calculated at around 45, 101, and 134 km² for Chindwin, Upper Ayeyarwady, and Lower Ayeyarwady, respectively. The historical channel change assessment aided us to identify and categorize river reaches according to the frequency of changes. Six hotspots of riverbank erosion were identified including near Mandalay city, the confluence of Upper Ayeyarwady and Chindwin, near upstream of Magway city, downstream of Magway city, near Pyay city, and upstream of the Ayeyarwady delta. The web-based monitoring system simplifies the application of freely available remote sensing data over the large spatial domain to assess river planform changes to support stakeholders’ operational planning and prioritizing investments for sustainable Ayeyarwady River management. Full article

Sand mining is one of the major sustainability challenges of the 21st century. Rates of extraction are surpassing sand supply, and ensuing sand starvation is adversely impacting channel-floodplains and deltas. Therefore, quantifying sand mining’s location and extent, through global monitoring and detection, particularly in fluvial systems, is becoming a priority. Sand mining by dredges and barges (extraction of sand and secondarily gravel) in South East Asian rivers, including illegal sand mining, has become rampant, and a monitoring system is not yet in place. Here, we present a high-resolution remote sensing-based mining monitoring system for sand mining in fluvial systems. We used Sentinel-1 mission, a radar component of the Copernicus joint initiative of the European Commission (EC) and the European Space Agency (ESA). The system, tested in the Ayeyarwady, the second largest river in SE Asia, detects sand mining by barges almost in real-time with a satisfactory accuracy level. An additional advantage of the monitoring system is that it does not incur any costs, making it accessible to multiple users, decision-makers, and stakeholders. Full article

There are increasing concerns for the ecological health of rivers, and their ability to provide important ecosystem services. Frameworks describing the character and condition of rivers have been developed in many parts of the world but rarely include river ecosystem services. South East Asia is a region with some of the world’s great rivers—Mekong, Salween and Ayeyarwady—running through six different countries, but data on river ecological character and condition is patchy and inconsistent. Development pressures on these rivers has never been higher, and ecosystem services may be lost before being described and valued. The development of a framework of ecological importance is envisaged, which maps out the relative contributions of river reaches to a wide range of ecosystem services. This could be a tool for river basin planning and water resource management, baseline information for impact assessment of infrastructure (for example, hydropower and irrigation), and for protecting ecologically important areas. We asked a diverse group of 109 river basin planners, and water and natural resource management professionals in the region whether a framework of ecological importance would support their activities, and which river ecosystem services are most important to be assessed. Our findings allow prioritisation of river ecosystem services to be assessed and mapped according to importance in different river reaches and sub-basins within the region. The locations of ranked threats and pressures on the river systems allow indication of river health and integrity in these sub-basins. We consider the feasibility of measuring ecosystem services and pressures through the identification of appropriate indicators, methods, and availability of global, regional, and national data. Full article

We reflect on methodologies to support integrated river basin planning for the Ayeyarwady Basin in Myanmar, and the Kamala Basin in Nepal, to which we contributed from 2017 to 2019. The principles of Integrated Water Resources Management have been promoted across states and regions with markedly different biophysical and political economic conditions. IWRM-based river basin planning is complex, resource intensive, and aspirational. It deserves scrutiny to improve process and outcome legitimacy. We focus on the value of co-production and deliberation in IWRM. Among our findings: (i) multi-stakeholder participation can be complicated by competition between actors for resources and legitimacy; (ii) despite such challenges, multi-stakeholder deliberative approaches can empower actors and can be an effective means for co-producing knowledge; (iii) tensions between (rational choice and co-productive) models of decision complicate participatory deliberative planning. Our experience suggests that a commitment to co-productive decision-making fosters socially legitimate IWRM outcomes. Full article

Newly developed mobile phone applications in combination with citizen science are used in different fields of research, such as public health monitoring, environmental monitoring, precipitation monitoring, noise pollution measurement and mapping, earth observation. In this paper, we present a low-cost water quality mobile phone measurement technique combined with sensor and test strips, and reported the weekly-collected data of three years of the Ayeyarwady River system by volunteers at seven locations and compared these results with the measurements collected by the lab technicians. We assessed the quality of the collected data and their reliability based on several indicators, such as data accuracy, consistency, and completeness. In this study, six local governmental staffs and one middle school teacher collected baseline water quality data with high temporal and spatial resolution. The quality of the data collected by volunteers was comparable to the data of the experienced lab technicians for sensor-based measurement of electrical conductivity and transparency. However, the lower accuracy (higher uncertainty range) of the indicator strips made them less useful in the Ayeyarwady with its relatively small water quality variations. We showed that participatory water quality monitoring in Myanmar can be a serious alternative for a more classical water sampling and lab analysis-based monitoring network, particularly as it results in much higher spatial and temporal resolution of water quality information against the very modest investment and running costs. This approach can help solving the invisible water crisis of unknown water quality (changes) in river and lake systems all over the world. Full article

The Ayeyarwady River in Myanmar is one of the largest rivers in Southeast Asia. It is predominantly fed by monsoonal precipitation and, to a lower extent, by meltwater from glaciers located in the Himalaya mountains. Information about the glaciers in its headwater region and glacier changes is scarce. Glaciers, in general, are highly important for the hydrological system and are contributing to river flow, therefore playing a key role in water availability, especially in catchments with (semi-) arid downstream areas as is in parts of Myanmar. This study investigated 130 glaciers in the Ayeyarwady headwaters by analyzing satellite images from Landsat missions between 1976 and 2015. The results of the glacier area and volume change analyses indicate that the glaciers are experiencing unprecedented losses. Over the 39 years, the glaciers lost up to 54.3 ± 7.64% of their area and 60.09 ± 1.56% of their mass and volume. The highest losses occurred in the period 2002–2015, which corresponds to increasing global and local warming. This development will probably have a strong influence on the glaciers’ storage function and will affect the local river runoff in the headwater region. Full article