Search Results (12)

Asian Mega-Deltas (AMDs) are important food baskets and contribute significantly to global food security. However, these areas are extremely susceptible to the consequences of climate change, such as rising temperatures, sea-level rise, water deficits/surpluses and saltwater intrusion. This study focused on maize crop suitability mapping and yield assessment in two major AMDs: the Ganges Delta, spanning parts of northeast India and Bangladesh, and the Mekong Delta across Vietnam and Cambodia. We investigated the historical climate reanalysis AgERA datasets and climate projections from the Coupled Model Intercomparison Phase 6 (CMIP6) for the periods 2040–2070 and 2070–2100 using PyAEZ-based modeling to estimate maize yields for periods in the near (2050s) and far future (2100s). Province-level yield estimates were validated against statistics reported by the governments of the respective countries. Model performance varied across regions, with R² values ranging from 0.07 to 0.94, MAE from 0.67 t·ha⁻¹ (14.2%) to 1.56 t·ha⁻¹ (20.7%) and RMSE from 0.62 t·ha⁻¹ (14.6%) to 1.74 t·ha⁻¹ (23.1%) in the Ganges Delta, and R² values from 0.23 to 0.85, MAE from 0.37 t·ha⁻¹ (12.8%) to 2.7 t·ha⁻¹ (27.2%) and RMSE from 0.45 t·ha⁻¹ (15.9%) to 1.76 t·ha⁻¹ (30.9%) in the Mekong Delta. The model performed comparatively better in the Indian region of the Ganges Delta than in the Bangladeshi region, where some yield underestimation was observed not accurately capturing the increasing upward trend in reported yields over time. Similarly, yields were underestimated in some provinces of the Mekong Delta since 2008. This may be attributed to improved management practices and the model’s inability to fully capture high-input management systems. There are also limitations related to the downscaling of CMIP6 data; the yield estimated using the downscaled CMIP6 data has small variability under rainfed and irrigated conditions. Despite these limitations, the modeling approach effectively identified vulnerable regions for maize production under future climate scenarios. Additionally, maize crop suitability zones were delineated, providing critical insights for planning and policy design to support climate adaptation in these vulnerable regions. Full article

Mapping spatial data is essential for the monitoring of flooded areas, prognosis of hazards and prevention of flood risks. The Ganges River Delta, Bangladesh, is the world’s largest river delta and is prone to floods that impact social–natural systems through losses of lives and damage to infrastructure and landscapes. Millions of people living in this region are vulnerable to repetitive floods due to exposure, high susceptibility and low resilience. Cumulative effects of the monsoon climate, repetitive rainfall, tropical cyclones and the hydrogeologic setting of the Ganges River Delta increase probability of floods. While engineering methods of flood mitigation include practical solutions (technical construction of dams, bridges and hydraulic drains), regulation of traffic and land planning support systems, geoinformation methods rely on the modelling of remote sensing (RS) data to evaluate the dynamics of flood hazards. Geoinformation is indispensable for mapping catchments of flooded areas and visualization of affected regions in real-time flood monitoring, in addition to implementing and developing emergency plans and vulnerability assessment through warning systems supported by RS data. In this regard, this study used RS data to monitor the southern segment of the Ganges River Delta. Multispectral Landsat 8-9 OLI/TIRS satellite images were evaluated in flood (March) and post-flood (November) periods for analysis of flood extent and landscape changes. Deep Learning (DL) algorithms of GRASS GIS and modules of qualitative and quantitative analysis were used as advanced methods of satellite image processing. The results constitute a series of maps based on the classified images for the monitoring of floods in the Ganges River Delta. Full article

The Sangu River basin significantly contributes to national economy significantly; however, exposures to water-related hazards are frequent. As it is expected that water-related disasters will increase manifold in the future due to global warming, the Government of Bangladesh has formulated the Bangladesh Delta Plan 2100 (BDP-2100) to enhanced climate resilience. Accordingly, this study assessed the hydro-meteorological characteristics of the Sangu River basin under the changing climate. This study scientifically selected five General Circulation Models (GCMs) to include the model climate sensitivity and statistically bias-corrected their outputs. The Water and Energy Budget-based Rainfall-Runoff-Inundation (WEB-RRI) model was used to simulate the hydrological responses of the basin. The analysis of five GCMs under the Representative Concentration Pathway (RCP8.5) revealed that all selected GCMs estimate a 2–13% increase in annual rainfall and a 3–12% increase in annual discharge in the near-future (2025–2050), whereas four GCMs project an 11–52% increase in annual rainfall and a 7–59% increase in annual discharge in the far-future (2075–2100). The projected more frequent and intense increased extreme rainfall and flood occurrences in the future indicate an increase in flood disaster risk, whereas increased meteorological and hydrological drought in the future reflects a scarcity of water during dry periods. The number of projected affected people shows an increasing trend due to the increased inundation in the future. However, an increasing trend of transpiration indicates agricultural productivity will increase in the future. Policymakers can utilize this evidence-based information to implement BDP-2100 and to reduce the disaster risks in the basin. Full article

The sustainability index (SI) is a relatively new concept for measuring the performance of water resource systems over long time periods. The purpose of its definition is to provide an indication of the integral behavior of the system with regard to possible undesired consequences if a misbalance in available and required waters occurs. Therefore, the tidal river management (TRM) approach has been implemented for the past three decades (from 1990 to 2020) within the polder system in Southwest Bangladesh to achieve water sustainability. TRM plan and watershed management plan (WMP) have commonalities as both are aimed at ensuring the sustainable use of watershed resources with the management of land, water, and the wider ecosystem of the watershed in an integrated way. The TRM plan focuses mostly on coastal regions, whereas the WMP focuses on both coastal and non-coastal regions. According to this, the aim of this study was to explore the application of the sustainability index of tidal river management (SITRM) in measuring the sustainability of tidal river management in the coastal area of the Lower Ganges–Brahmaputra–Meghna (GBM) delta. In order to quantify the sustainability of tidal river management, this research first provided the components and indicators of SITRM for the coastal region. The study follows a 5-point Likert scale for opinion survey of key informants and comprises households’ survey of farmers. In addition, it includes Landsat satellite images from Earth Explorer of the United States Geological Survey (USGS) and direct field observation to collect information regarding the indicators of SITRM. The study measures the index value of SITRM for identifying the water sustainability of Beel East Khukshia-TRM. The index value was 71.8 out of 100, showing good tidal river management for the Hari–Teka–Bhadra catchment. To achieve water sustainability and aid stakeholders and water managers in decision making, it may be possible to include the SITRM framework in tidal river management projects. In addition, the SITRM is more capable of facing drainage congestion, waterlogging, and climate change issues than watershed sustainability index (WSI), Canadian water sustainability index (CWSI), West Java water sustainability index (WJWSI), and water poverty index (WPI). Therefore, water professionals and policymakers can apply SITRM to assess the resilience of specific TRM schemes for greater sustainability in different coastal regions of the world. Full article

A comprehensive understanding of the dynamic characteristics of geomorphological, ecological, and human systems is essential to explaining complex charland (mid-channel island) processes and crafting and implementing policy measures. This work demonstrates that the characteristics and outcomes of riparian hazards are determined by the interactive dynamics between hydrogeology and human conditions, which constitutes a novel contribution to the literature in this research area. We further contend that such dynamic social-ecological systems demand a flexible, adaptive management and planning approach. The present research has three key interdisciplinary objectives: (i) to analyze the salient features and characteristics of the geomorphological and riparian systems of the Bengal Delta; (ii) to analyze the evolutionary discourse of the legal systems concerning eroded (diluvion) and accreted (alluvion) land in Bangladesh; and (iii) to assess the characteristics of the coping and adaptation strategies employed by charland inhabitants. The findings of this research reveal that delta-building processes, which are characterized by dynamic shifts in the river channels, along with the erosion and accretion of charlands have made Bangladesh’s land and water systems very dynamic and unstable. The destabilization of these systems increases the inhabitants’ vulnerability to riparian hazards, which consistently results in the displacement of settlers and, consequently, a serious deterioration in their socioeconomic status. At present, Bangladesh does not have an effective institutional framework and structure for resettlement planning; therefore, the formulation of a comprehensive national resettlement policy with adequate flexibility to adapt to changing scenarios is urgently needed. Full article

Coasts and coastlines in many parts of the world are highly dynamic in nature, where large changes in the shoreline position can occur due to natural and anthropogenic influences. The prediction of future shoreline positions is of great importance in the better planning and management of coastal areas. With an aim to assess the different methods of prediction, this study investigates the performance of future shoreline position predictions by quantifying how prediction performance varies depending on the time depths of input historical shoreline data and the time horizons of predicted shorelines. Multi-temporal Landsat imagery, from 1988 to 2021, was used to quantify the rates of shoreline movement for different time period. Predictions using the simple extrapolation of the end point rate (EPR), linear regression rate (LRR), weighted linear regression rate (WLR), and the Kalman filter method were used to predict future shoreline positions. Root mean square error (RMSE) was used to assess prediction accuracies. For time depth, our results revealed that the higher the number of shorelines used in calculating and predicting shoreline change rates the better predictive performance was yielded. For the time horizon, prediction accuracies were substantially higher for the immediate future years (138 m/year) compared to the more distant future (152 m/year). Our results also demonstrated that the forecast performance varied temporally and spatially by time period and region. Though the study area is located in coastal Bangladesh, this study has the potential for forecasting applications to other deltas and vulnerable shorelines globally. Full article

This paper presents a review of water research, development, and management in Bangladesh, with examples drawn from the past and present. A bibliometric analysis is adopted here to analyze the water-related publication data of Bangladesh. Water-quality-related research is the dominating research field in Bangladesh as compared to water-quantity (floods and droughts)-related ones. The most productive author was found to be Ahmed KM for water-related publication in Bangladesh. The arsenic contamination in Bangladesh has received the highest attention (13 out of the top 15 highly cited papers are related to arsenic contamination). Climate-change-related topics have been showing an increasing trend in research publications over the last 5 years. Bangladesh Delta Plan 2100, prepared recently, is a visionary master plan that is expected to shape water management in Bangladesh in the coming decades to adapt to climate change. A set of recommendations is made here to achieve sustainable water management in Bangladesh. Full article

Bangladesh is in the floodplains of the Ganges, Brahmaputra, and Meghna River delta, crisscrossed by an intricate web of rivers. Although the country is highly prone to flooding, the use of state-of-the-art deep learning models in predicting river water levels to aid flood forecasting is underexplored. Deep learning and attention-based models have shown high potential for accurately forecasting floods over space and time. The present study aims to develop a long short-term memory (LSTM) network and its attention-based architectures to predict flood water levels in the rivers of Bangladesh. The models developed in this study incorporated gauge-based water level data over 7 days for flood prediction at Dhaka and Sylhet stations. This study developed five models: artificial neural network (ANN), LSTM, spatial attention LSTM (SALSTM), temporal attention LSTM (TALSTM), and spatiotemporal attention LSTM (STALSTM). The multiple imputation by chained equations (MICE) method was applied to address missing data in the time series analysis. The results showed that the use of both spatial and temporal attention together increases the predictive performance of the LSTM model, which outperforms other attention-based LSTM models. The STALSTM-based flood forecasting system, developed in this study, could inform flood management plans to accurately predict floods in Bangladesh and elsewhere. Full article

Population displacement by extreme weather events have long plagued Bangladesh, a low-lying disaster-prone river delta. The country experiences yearly displacement of approximately one million people and losses of about 1% of its gross domestic product due to cyclones, floods, and riverbank erosion. This study examines how the Bangladesh government has managed climate-induced displacement with a particular focus on socioeconomic development policies. We analyzed the country’s 1984 Land Reform Ordinance, the 2009 climate change strategy and action plan, the 1997 agricultural Khasland settlement policy, perspective plan for 2010–2021, poverty reduction strategy paper, and five-year plans to understand governance changes for displaced communities. We found that, overall, the central government implemented four main strategies. In the first strategy, Bangladesh resettled displaced people in cluster villages on public lands. Then, it provided life skills training (e.g., leadership, disaster preparedness, income generation) to rehabilitate the residents. The third strategy was to align resettlement efforts with local-level climate change adaptation and poverty reduction activities. Here, the central government and its seventeen departments collaborated with local councils to support resettled households under the social safety program. The fourth strategy was to diversify financial resources by obtaining more fund from donors and establishing its own financial mechanism. However, we also found that the decision-making and implementation process remained top-down without need assessment and community participation. This paper intends to offer insights on how similar challenged countries and regions may respond to climate displacement in the future. Full article

Understanding the interactions between shallow saline groundwater and surface water is crucial for managing water logging in deltaic islands. Water logging conditions result in the accumulation of salt in the root zone of crops and detrimentally affect agriculture in the economically and socially backward deltaic region of West Bengal and Bangladesh. In this paper, we undertook a modeling study of surface water–groundwater interactions in the Gosaba Island of Sundarbans region of the Ganges delta using MODFLOW followed by comprehensive parameter sensitivity analysis. Further, scenario analyses (i.e., no-drain, single drain, three drains) were undertaken to evaluate the effectiveness of drainage infrastructure to reduce saline water logging conditions. The evaluation indicated that installation of three drains can remove water at a rate of up to −123.3 m³day⁻¹ and lower the water table up to 0.4 m. The single drain management scenario could divert water at the rate of −77.9 m³day⁻¹ during post monsoon season, lowering the shallow saline groundwater table up to 0.1 m. This preliminary modeling study shows encouraging results to consider drainage management as to solve the increasing challenge of water logging and salinity management in the deltaic region. The insights will be useful for farmers and policymakers in the region for planning various sustainable saline groundwater management. Building drainage infrastructure could potentially be part of initiatives like the national employment guarantee scheme in India. In the future, this model can be coupled with solute transport models for understanding the current status and future expansion of salinity in the study area. Further modeling and optimization analysis can help identify the optimal depth and spacing of drains. Full article

Impacts of climate change adaptation strategies need to be evaluated using principled methods spanning sectors and longer time frames. We propose machine-learning approaches to study the long-term impacts of flood protection in Bangladesh. Available data include socio-economic survey and events data (death, migration, etc.) from 1983–2014. These multidecadal data, rare in their extent and quality, provide a basis for using machine-learning approaches even though the data were not collected or designed to assess the impact of the flood control investments. We test whether the embankment has affected the welfare of people over time, benefiting those living inside more than those living outside. Machine-learning approaches enable learning patterns in data to help discriminate between two groups: here households living inside vs. outside. They also help identify the most informative indicators of discrimination and provide robust metrics to evaluate the quality of the model. Overall, we find no significant difference between inside/outside populations based on welfare, migration, or mortality indicators. However, we note a significant difference in inward/outward movement with respect to the embankment. While certain data gaps and spatial heterogeneity in sampled populations suggest caution in any conclusive interpretation of the flood protection infrastructure, we do not see higher benefits accruing to those living with higher levels of protection. This has implications for Bangladesh’s planning for future and more extreme climate futures, including the national Delta Plan, and global investments in climate resilient infrastructure to create positive social impacts. Full article

Coastal people, especially those living within deltaic areas, encounter major climatic concerns which affect their livelihoods. To cope with this problem, different types of planned adaptation strategies have been implemented guided by laws, policies and programs. However, these guiding documents sometimes fall short of addressing the needs of climate-affected people, especially in natural resource-dependent societies in Asia and Africa. Based on this premise, this paper sought to evaluate the effectiveness of existing policy documents which affect the lives of people living in one large delta (Ganges-Brahmaputra-Meghna in Bangladesh), two medium-sized deltas (Indian Bengal delta—part of the Ganges-Brahmaputra-Meghna and Mahanadi in India), and a small-sized delta (Volta in Ghana). The study followed a mixed methods research design, which included desktop analyses of policies, laws and programs, a questionnaire survey conducted among individuals who played various roles in the policy and legal development processes at national and local levels and focus group discussions at the community level in the three countries. National laws, policies and programs were assessed in the context of climate change adaptation through three lenses: human rights, natural resource management and disaster response. Findings of this paper reveal that the existing documents have some strengths to promote adaptation, although they have some major limitations that cause concerns among the delta communities. Full article