Study region The Greater Mekong Region, comprising Myanmar, Thailand, Laos, Cambodia, and Vietnam, covering an area of nearly 2 million km2. Study focus Groundwater resources have become increasingly crucial to support the region's rapid development. Advancements in hydrogeological knowledge have led to a better understanding of groundwater availability and water quality at both national and sub-national levels. However, very little attention has been given to integrating groundwater knowledge at the regional scale, leading to major data gaps between national studies and global hydrogeological knowledge. This study aims to address these major data and knowledge gaps by conducting a comprehensive hydrogeological review of 179 documents focused on the Greater Mekong Region in Southeast Asia. New hydrogeological insights for the region The review provides the first synthesised overview of the hydrogeology of the Greater Mekong Region. The results are new regional hydrogeological maps of aquifer distribution and groundwater threats from arsenic pollution, high salinity, and over-abstraction. The maps serve as the basis for a unified transboundary framework and an overview of the most significant groundwater challenges. The review also shows that, beyond transboundary aquifers, there are similarities among major aquifer systems and significant differences in the management and development of water resources across borders. Hence, regional cooperation and exchange of lessons learnt in similar hydrogeological settings would be highly beneficial for sustainable groundwater development across the region.

Droughts have been reported to cause socio-economic disruption in the Vietnamese Mekong Delta (VMD), threatening the region's sustainable development. However, it is difficult to monitor droughts in the VMD due to the lack of ground-based rainfall stations. Alternatively, remote-sensing technologies that provide regular temporal and spatial data are analysed. We verify the correlation between the Tropical Rainfall Measurement Mission (TRMM) 3B42 product and rainfall data collected from meteorological (gauged) stations in the VMD. Next, we assess the reliability of TRMM for monitoring meteorological drought and quantifying the drought characteristics based on the standardised precipitation index (SPI) at a wide range of time scales (1-12 months) during the period 1998-2018. TRMM shows a good match to station data at the monthly scale, as evidenced through biases < 5% and RMSE < 80 mm at selected sites. The driest episode was from 2014 to 2016, with a widespread drought area, most severely (with SPI < -1.5) in the northern part (Dong Thap, Tien Giang and parts of adjacent provinces). We also show that drought severity follows an increasing trend during 1998-2018, as indicated through Mann-Kendall tests on SPI time series, potentially due to changes in regional climate variability.

Vietnam faces heightened vulnerability to severe climate change impacts, notably sea level rise, flooding, and landslides. In recent years, the northwest mountainous regions have experienced recurrent and widespread landslides during the rainy season (May to October), resulting in significant economic losses. This study focuses on the Lao Cai province, employing various data mining techniques—Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Random Forest (RF)—to spatially predict landslide hazards. Initially, a comprehensive landslide inventory map was constructed from diverse sources, pinpointing past landslide occurrences. Subsequently, multiple factors influencing landslides were considered, including slope angle, slope aspect, profile curvature, wetness index, lithology, Normalized Difference Vegetation Index (NDVI), soil type, soil moisture, road density, house density, and rainfall. Utilizing these factors, landslide susceptibility indexes were computed through the respective models. Validation, using landslide locations not utilized in the training phase, revealed that models employing Random Forest (RF) exhibited the highest prediction capability. The trained model was then applied to generate real-time forecasts of landslide susceptibility maps for up to 16 days, using bias-corrected Global Forecast System (GFS) precipitation data. This WebGIS operational prediction system enhances preparedness and awareness, facilitating improved mitigation strategies to mitigate the impact of landslides.

Despite its energy benefits, hydropower dam development often causes ecological damages and social disruption, including downstream livelihood impacts, and biodiversity loss. Current methods for analyzing changes in downstream inundation extent due to dam operation typically rely on historical ground or satellite observations, or on coupled hydrological‐hydrodynamic modeling. However, while the former fails to isolate hydropower impacts from climate variations, the latter suffers from extensive input data requirements and high computational burden. This study proposes a novel hybrid framework integrating satellite data‐driven Forecasting Inundation Extents using REOF (Rotated Empirical Orthogonal Function) analysis (FIER), and the process‐based Hydrological Predictions for the Environment (HYPE) model incorporating the Integrated Reservoir Operation Scheme (IROS). The framework enables the isolated assessment of long‐term hydropower impacts on downstream inundation dynamics with computational efficiency and reduced ground data requirements, making it suitable for poorly gauged regions. Applying FIER‐HYPE‐IROS to the Lower Mekong River basin (LMB), a region significantly affected by dam proliferation impacting fisheries and agriculture, we found that dam operations decreased decadal‐average wet season water levels by up to 5% and increased dry season levels by up to 11%. Wet season inundation occurrence decreased by 11 days and the inundated area by 6%, while dry season inundation occurrence extended by 6 days and the surface water area increased by 40%. Although the current framework does not explicitly assess the downstream hydrological modifications, it offers a cost‐effective alternative for evaluating upstream alterations on inundation dynamics, such as dam operations, particularly in poorly gauged regions.

The evolution of delta and riverbank erosion within the river basin can significantly impact the environment, ecosystems, and lives of those residing along rivers. The Vietnamese Mekong Delta (VMD), counted among the world’s largest deltas, has undergone significant morphological alterations via natural processes and human activities. This research aims to examine these morphological alterations and their impacts on local economic and social conditions in the VMD. This study utilized satellite data from 1988 to 2020, coupled with population density and land use/land cover (LULC) maps from 2002, 2008, and 2015. The findings reveal that the VMD experienced widespread erosion over the past three decades, covering an area of 66.8 km2 and affecting 48% of the riverbank length (682 km). In contrast to riverbanks, islets showed an accretion trend with an additional area of 13.3 km2, resulting in a decrease in river width over the years. Riverbank and islet erosion has had a profound impact on the LULC, population, and economy of the provinces along the VMD. From 2002 to 2020, eight different land use types were affected, with agricultural land being the most severely eroded, constituting over 86% of the total lost land area (3235.47 ha). The consequences of land loss due to erosion affected 31,273 people and resulted in substantial economic damages estimated at VND 19,409.90 billion (USD 799.50 million) across nine provinces along the VMD. Notably, even though built-up land represented a relatively small portion of the affected area (6.58%), it accounted for the majority of the economic damage at 70.6% (USD 564.45 million). This study underscores the crucial role of satellite imagery and GIS in monitoring long-term morphological changes and assessing their primary impacts. Such analysis is essential for formulating effective plans and strategies for the sustainable management of river environments.

This study proposes a sustainability assessment framework for managing the water resources of the Vietnamese portion of the Srepok River Basin (VSRB). A sustainability hierarchy was developed using five, ten, seven and five sustainability indicators to characterize economic, environmental, social and management dimensions of the basin's water resources. Reliable weights for each of these sustainability components were assigned using fuzzy analytical hierarchy process evaluations of judgements obtained from five highly experienced experts. The sustainability levels were ranked in increasing order of Management > Economic > Environment > Social, allowing a composite sustainability index to be assessed. By taking into account economic, environmental, social and management perspectives, the assessment provides a comprehensive understanding of the sustainability of water resources in the VSRB.

Water extraction solutions in the high mountainous areas of Northern Vietnam commonly include rainwater harvesting, dug wells, drilled wells, groundwater springs, and hanging lakes. However, many water supply systems operate inefficiently and lack flexibility. This study established 10 criteria for selecting groundwater exploitation technology, divided into three groups: water resources, economic and technical, social, and environmental criteria. These criteria aim to identify appropriate water extraction technologies suitable for high mountainous and water-scarce regions, ensuring the long-term and efficient operation of water supply systems. The Geographic Information System (GIS) approach was utilized, integrating the criteria using the Analytical Hierarchy Process (AHP) method to select suitable water extraction technologies. The research results indicate that the evaluation criteria for determining suitable areas for implementing sustainable water extraction technologies, and the weights assigned to these criteria, ensure a consistent ratio (CR) <10 % according to the hierarchical analysis method. This article presents the results of identifying areas suitable for implementing groundwater extraction technologies using drilled wells, based on seven criteria within three groups: water resources, economic and technical, and social criteria. The GIS approach has been employed, and the criteria have been integrated using the AHP to select and determine the areas suitable for implementing groundwater extraction technologies using drilled wells.

Human interventions activities around the world, particularly reservoir operation, have dramatically altered hydrological and sediment regimes in most of the major river basins. In the Mekong River, specifically the Upper Srepok River Basin (USRB) which is a main tributary of the river basin connected to the Mekong Delta's rice bowl and the Tonle Sap Lake's top inland fisheries, there are increasing concerns about the impacts of cascade reservoir operations on downstream streamflow and sediment budgets. Previous studies estimating impacts either relied solely on observed data or did not verify simulations of regulated streamflow. Using a process‐based hydrological model calibrated and validated for both natural and regulated streamflow in the USRB, it was found that the monthly hydrological changes were up to ±20% compared to pre‐dam periods at the most downstream station bordering between Vietnam and Cambodia (i.e., Ban Don station). The basin also experienced a slight decrease (less than 2%) in annual streamflow. Additionally, average and peak suspended sediment concentration decreased significantly in both of the annual and seasonal periods. At the Ban Don station, sediment loads were reduced 140 thousand tons/year (i.e., 15%) compared to pre‐dam period. Most of the changes in streamflow and sediment budgets in the basin were driven by the Buon Tua Srah reservoir, which had the highest degree of regulation in the basin. Therefore, integrated and transboundary water and sediment management, particularly at Buon Tua Srah reservoir, needs to be developed for the sustainability of the river basin.

Lack of sufficient and reliable gauged hydrological data over the Red River basin (RRB)—one of the largest river basins in the world, has been a challenge to water resource planning and management in Vietnam. To address this critical issue, this study mainly aimed to apply the VIC hydrological model to simulate surface runoff at the basin scale over the RRB during the period 2005–2014. The surface runoff coefficient estimated from the VIC model output was analyzed in relation to precipitation pattern and watershed factors in three regions (the Northeast, Northwest, and Red River Delta (RRD) region) of the RRB to investigate key factors influencing the spatial and temporal variations of surface runoff coefficients. The results showed that the spatiotemporal variation of surface runoff coefficient was strongly impacted by precipitation pattern, which was indicated by the increased surface runoff coefficients associated with both the increased precipitation amount and precipitation intensity for all regions in the RRB, most obviously in the wet season. In addition, the combined effects of various watershed factors (terrain elevation, land use and land cover, soil type, and soil moisture) in different regions of the RRB also largely contributed to the spatiotemporal variation of surface runoff coefficient. The highest surface runoff coefficients were found in the uppermost areas of the Northeast and Northwest regions and the middle areas of the Northwest region where the high terrain elevations over 1500 m and the dominance of savanna, shrubland, and deciduous broadleaf forest were identified as the key factors contributing to the variation of surface runoff coefficients. These findings could provide a better understanding on the spatial and temporal variations of surface runoff over the RRB toward supporting governmental agencies in making policies and decisions for soil and water resources conservation.

Mass urbanisation and intensive agricultural development across river deltas have driven ecosystem degradation, impacting deltaic socio-ecological systems and reducing their resilience to climate change. Assessments of the drivers of these changes have so far been focused on human activity on the subaerial delta plains. However, the fragile nature of deltaic ecosystems and the need for biodiversity conservation on a global scale require more accurate quantification of the footprint of anthropogenic activity across delta waterways. To address this need, we investigated the potential of deep learning and high spatiotemporal resolution satellite imagery to identify river vessels, using the Vietnamese Mekong Delta (VMD) as a focus area. We trained the Faster R-CNN Resnet101 model to detect two classes of objects: (i) vessels and (ii) clusters of vessels, and achieved high detection accuracies for both classes (f-score = 0.84-0.85). The model was subsequently applied to available PlanetScope imagery across 2018-2021; the resultant detections were used to generate monthly, seasonal and annual products mapping the riverine activity, termed here the Human Waterway Footprint (HWF), with which we showed how waterborne activity has increased in the VMD (from approx. 1650 active vessels in 2018 to 2070 in 2021 - a 25 % increase). Whilst HWF values correlated well with population density estimates (R2 = 0.59-0.61, p < 0.001), many riverine activity hotspots were located away from population centres and varied spatially across the investigated period, highlighting that more detailed information is needed to fully evaluate the extent, and type, of human footprint on waterways. High spatiotemporal resolution satellite imagery in combination with deep learning methods offers great promise for such monitoring, which can subsequently enable local and regional assessment of environmental impacts of anthropogenic activities on delta ecosystems around the globe.

Vietnam is gifted with a dense network of rivers and abundant water resources. However, the gift along with the limited irrigation system of the country seems putting more pressure on the sustainable management of water resources in river basins. In order to develop a framework for assessing environmental sustainability for water resources in the Srepok River basin in Vietnam (VSRB), this study applied the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) since this approach has been powerful and appropriate for sustainability assessment studies. The ten core environmental sustainability indicators were developed based on the current issues existing in the VSRB.

Access to a reliable and safe domestic water supply is a serious challenge for many developing countries worldwide. In the capital of Vietnam, Hanoi, the municipal government is facing a number of difficulties in providing sufficient water in a sustainable manner due to the increasing urban population and the serious pollution of both surface and groundwater resources, but this is also due to a lack of resources to invest in the supply system. This study aimed to investigate water users’ willingness to pay for the improvement of Hanoi’s domestic water supply system. A contingent valuation process based on a survey of 402 respondents was used to explore citizens’ willingness to pay (WTP) for the improvement of their urban water supply. The results show that Hanoi’s urban communities (more than 90%) were generally satisfied with the quantity of their water supply, but tended to be dissatisfied with its quality, with 80% of the respondents using advanced water purifiers before drinking and cooking. Respondents were also concerned about the overall reliability of the service, with 40% of respondents indicating that they received no check and maintenance service. A WTP regression model was developed based on the survey findings. The average WTP is 281,000 dong/household/month (approximately 12.2 USD at the exchange rate of 1 USD to about 23,000 VND), equivalent to 1.4% of the average household income at the end of 2019, indicating the level of affordability of monthly water payments among Hanoi citizens.

Inland lakes have been increasingly impacted by climate change and human activities, leading to unprecedented environmental consequences. Among many rapidly changing lakes is the Tonlé Sap Lake (TSL) in Cambodia-Southeast Asia's largest inland lake-which is under growing threats from altered flows and inundation dynamics due to compounding effects of climate change and dam construction in the Mekong River basin (MRB). While previous studies have examined the potential causes of recent changes in open water areas, a mechanistic quantification of the lake's shifting hydrologic balance and inundation dynamics due to natural climate variability and dam operations is lacking. Here, using a hydrological-hydrodynamic modeling system that includes the major dams in the MRB, we show that while climate variability has been a key driver of inter-decadal variabilities in the lake's water balance, the operation of Mekong dams has exerted a growing influence-especially after 2010-on the Mekong flood pulse, Tonlé Sap River's flow reversal, and the TSL's inundation dynamics. The dam-induced dampening of the Mekong's peak discharge increased from 1-2% during 1979-2009 to ~7% in the 2010s, causing comparable alterations in the peak of inflow from the Mekong into TSL. More crucially, during the 2010s, the dams caused a reduction in annual inflow volume into TSL by 10-25% and shortened the annual inundation duration by up to 15 days in the lake's periphery. Further, seasonally inundated areas decreased (increased) most substantially by ~245 km2 or ~3% (~270 km2 or ~6%) in August (April) during the 2010s. These results demonstrate that Mekong dams have already caused substantial alterations in the hydrologic balance and inundation dynamics of the TSL. Our findings offer critical insights relevant for improved transboundary water management and decision making in light of growing concerns about the adverse impacts of large dams in the MRB.

Many deltas worldwide have increasingly faced extreme drought and salinity intrusion, which have adversely affected millions of coastal inhabitants in terms of lives and property. The Vietnamese Mekong Delta (VMD) is considered one of the world's most vulnerable regions to drought and saline water intrusion, especially in the context of climate change. This study aims to assess livelihood vulnerability and adaptation of the coastal people of the VMD under the impacts of drought and saltwater intrusion. A multi-disciplinary approach was applied, including desktop literature reviews, field surveys, interviews, and focus group discussions with 120 farmers and 30 local officials in two representative hamlets of Soc Trang, a coastal province of the VMD. A vulnerability assessment tool in combination with a sustainable livelihood framework was used to evaluate livelihood vulnerability using the five capital resources to indicate the largest effects of drought and salinity intrusion on the migration of local young people to large cities for adaptation. Livelihood Vulnerability Indexes revealed higher vulnerability in terms of the five capitals of coastal communities living in Nam Chanh hamlet compared to Soc Leo. Results of interviews with officials indicated an optimized mechanism between social organizations and local communities before, at the time, and after being impacted by the drought and salinity intrusion. Our findings contribute evidence-based knowledge to decision-makers to enable coastal communities in the VMD and other deltas worldwide to effectively adapt to the impacts of drought and salinity intrusion.

The climate change and global warning have been appeared as an emerging issue in recent decades. In which, the drought problem has been influenced on economics and life condition in Vietnam. In order to solve this problem, in this paper, we have designed and deployed a long range and energy efficient drought monitoring based on IoT (Internet of Things) for real time applications. After being tested in the real condition, the proposed system has proved its high dependability and effectiveness. The system is promising to become a potential candidate to solve the drought problem in Vietnam.

Droughts can become disasters if the lack of water impacts vulnerable households. Yet, in many cases drought management relies on maps with relatively simple indicators based on hydro-meteorological data or measurements of other physical variables that are assumed to correlate with households' drought exposure and vulnerability. This study contributes to more comprehensive drought risk assessments by combining a hydrological hazard indicator with socio-economic indicators for exposure and vulnerability derived from a household survey in a drought risk map for 13 communes in central Vietnam. We find that local and individual circumstances matter in drought risk assessment and that incorporating household survey information is key to understanding drought risks.

This study evaluates eight Satellite-derived Precipitation Estimate (SPE) datasets, which include uncorrected SPE and gauge-corrected SPE products from Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TMPA), Global Precipitation Measurement (GPM), Climate Hazards group Infrared Precipitation (CHIRP), and Precipitation Estimation form Remotely Sensed Information using Artificial Neural Networks (PERSIANN). These datasets are utilized with six representative river basins, corresponding to six sub-climate zones in Vietnam, during the period 2002-2017. The evaluations were carried out in two parts: 1) inter-comparison of the SPE products with rain gauges, for the six basins; 2) comparison of streamflow simulations, using the Soil and Water Assessment Tool (SWAT) forced by precipitation from rain gauge and SPE products. The results indicated that the gauge-corrected SPE datasets exhibited slightly better over the uncorrected datasets in comparison with rain gauges, but showed much higher performances as inputs in hydrological simulations. The GPM Integrated Multi-satellitE Retrievals for GPM (IMERG) Final run version 06B (GPM IMERGF-V6) exhibited the best overall performances among SPE products, in comparison with the rain gauges for the simulation of streamflow. This study is the first of its kind to validate GPM IMERG products in Vietnam, indicating the strong capability of the new IMERG retrieval algorithms. The CHIRP with stations (CHIRPS) dataset demonstrates a relatively low bias, could benefit long-term water resources planning for droughts. In monthly streamflow simulations, the SPE-driven simulations outperformed rain gauge-driven simulations in a larger basin (North West Region), which has low rain-gauge density. The results of this study could be a guide to determine the suitability of different SPE products for hydrological simulations.