Post graduate dissertations (Theses) of Water Resources Engineering (WRE) http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/126 2026-04-10T12:04:31Z 2026-04-10T12:04:31Z Asheque Mahmud, Md. http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7241 2026-01-21T04:59:16Z 2025-02-22T00:00:00Z

Forecasting Brahmaputra-Jamuna river flow from satellite data using artificial intelligence Jahan, Dr. Nasreen; Asheque Mahmud, Md.; 0417162049 Bangladesh is a flood-prone country due to its low-lying geography, heavy monsoon rainfall, and frequent cyclones, particularly in the coastal and tidal regions. Severe flooding in recent decades has resulted in many causalities and food scarcity. As a result, reliable and timely flood forecasting and warning are recognized as crucial factors to decrease flood-related damage and human suffering. Unfortunately, the current flood forecasting system provides fairly accurate forecast for shorter lead times (upto 3 days) only (FFWC 2021). Therefore, improving medium to long-range flood forecasting with 5 to 10 day lead times has become essential for better flood preparedness in the country. The aim of this research was to explore the potential of artificial intelligence for medium-range flow forecasting with a 5-day lead time at the Bahadurabad station in the Brahmaputra basin, using data such as precipitation, precipitable water, soil moisture storage, and satellite-derived river water levels. Artificial Neural Network (ANN) and Support Vector Machine (SVM) were utilized for this purpose. This approach presents a promising alternative to traditional streamflow forecasting methods using a hydrologic model, with the results compared against the forecast from the Flood Forecast and Warning Centre (FFWC) of the Bangladesh Water Development Board. For both the ANN and SVM models, 70% of the available data was used for model training, 15% of data was used for model testing, and the rest of the data was used for independent validation. Various input data combinations (called ‘model scenarios’ here) are considered for the ANN and SVM models to simulate discharge. In addition, each data combination was tested using the currently available data, which has a 5-day latency, real-time data, and forecast data, as not all variables are yet available in real-time or forecasts, but are expected to be in the near future. The model that considers all input variables (scenario 01) and the model that uses a combination of water level, precipitation, and soil moisture as inputs (scenario 04) were found as the best models for both ANN and SVM. In this study, three models (Model A, Model B, and Model C) were developed to address data latency issues, considering different data availability scenarios. Model A uses ERA5 data, which currently has a 5-day latency period. Model B assumes the availability of real-time data (used ERA5 data ignoring latency). Model C simulates how discharge forecasts could be improved if reliable climate forecast data were available. The performances of the ANN and SVM methods demonstrated a comparable level of accuracy to the observed flow and, in some cases, surpasses the predictive accuracy of the FFWC model, which forecasts water levels that converted to flow via a rating curve. Here, the SVM methods generally outperformed the ANN methods. Specifically, for the SVM methods of Model A at which scenario A-01 achieved a Root Mean Square Error (RMSE) of 6802.82 m³/s, a coefficient of determination (R²) of 0.87, and a Nash–Sutcliffe Efficiency (NSE) of 0.87, while Model scenario A-04 resulted in a RMSE of 7236.50 m³/s, a R² of 0.85, and a NSE of 0.85. In case of evaluating the RMSE value by comparison in a percentage scale, it was observed that best SVM model scenario C-01 demonstrated an improvement of approximately 58.22% over FFWC Prediction of discharge via a rating curve. This research demonstrates that artificial intelligence, particularly SVM, offers a promising alternative to traditional flood forecasting methods, with improved accuracy in predicting flow at Bahadurabad station in the Brahmaputra basin. Its ability to utilize satellite-derived data enhances flood forecasting and contributes to more reliable predictions, which can significantly improve flood preparedness and risk management in Bangladesh.

2025-02-22T00:00:00Z Aliur Rahman, Md. http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7055 2025-11-18T06:15:21Z 2024-05-18T00:00:00Z

Distribution of suspended sediment transport between asymmetric bifurcated channels in mobile bed condition Hossain, Dr. K.M. Ahtesham; Aliur Rahman, Md.; 1018162011P; 627.122/ALI/2024 Bifurcations are a fundamental feature in alluvial rivers and estuarine systems, contributing to the complex dynamics of fluvial environments, alongside braiding, anabranching streams, and deltas. Despite extensive research, the distribution of flow and sediments at asymmetric bifurcations remains inadequately understood. To achieve in-depth understanding of flow and suspended sediment dynamics at asymmetric bifurcations, this study has been conducted in the Hydraulics and River Engineering Laboratory at the Department of Water Resources Engineering, BUET. The experimental investigation focuses on varying discharge rates and nose angles in asymmetric bifurcated channels to explore their influence on flow behavior and sediment distribution. In order to achieve the objectives of this study, a total of thirty-six experimental runs have been conducted comprising three distinct nose angles: nose type-1 [θ = (+) 3.5°], nose type-2 [θ = (-) 4.2°], and nose type-3 [θ = (-) 7.3°]. Each nose angle has been tested under three different upstream discharges (40 l/s, 50 l/s, and 60 l/s) with respective rate of sediment feeding. Throughout the experiments, key parameters such as discharge, flow velocity, water depth, bed level changes, and suspended sediment concentration have been measured at specific locations across the channel. Flow visualization has been also observed, particularly near the bifurcation. The results reveal that nose angle plays a vital role in suspended sediment distribution, with turbulence near the nose tip significantly increasing sediment in suspension. As the nose angle changes from positive to negative indicating flow area of nose tip or branch mouth opening narrower to wider of a bifurcated channel, the suspended sediment transport ratio increases for a given upstream flow discharge in that branch. Velocity variation patterns have been observed in relation to nose angle and discharge variation. Bed level changes indicates that erosion intensifies with increasing discharge, and the erosion-deposition pattern varies depending on the nose angles. The relationships among flow patterns, velocity variations, suspended sediment concentration, and bed level changes are examined with consideration of downstream boundary conditions. The bifurcation geometry, especially the branch mouth shape, plays a critical role in sediment dynamics. The nose angle is the significant factor that governs the distribution of sediment and discharge in river bifurcations. Nine nodal point relations of two bifurcated branches have been found for three different nose angles and three upstream discharges. The parameters of the nodal point relations, namely coefficient M and exponent k, reveal a defined pattern corresponding to variations in nose angle. However, these parameters do not demonstrate a significant linear correlation with variations in discharge. The suspended sediment transport ratio of the bifurcated channels is directly proportional to the discharge ratio and inversely proportional to the quasi-offtake bifurcated angle. These results have been compared with the relevant studies and found satisfactory. Nose angle is a vital factor in determining the distribution of suspended sediments between asymmetric bifurcated channels. Therefore, this study provides valuable insights into the interrelationship between suspended sediment transport and nose angle variations under asymmetric conditions, offering a deeper understanding of bifurcation dynamics in the fluvial systems.

2024-05-18T00:00:00Z Faisal Ahmed, Khan http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7048 2025-04-19T09:08:08Z 2023-09-16T00:00:00Z

Development of water allocation mechanism for water stressed and abundance area under changing environmental condition Khan, Dr. Md. Sabbir Mostafa; Faisal Ahmed, Khan; 1014164001; 628.16068095492/FAI/2023 Water is one of the most used (and abused) natural resources on the earth. Water resources are particularly vital for the Agriculture sector. Irrigation has been a determining factor in sustaining the self-sufficiency of Bangladesh in food grain production. In addition to the agriculture sector, domestic and industrial sectors have also been important consumptive water users. Water is a limited resource spatially and temporally. Therefore, this resource should be allocated among different sectors and users in an equitable and efficient way. This aspect of allocation of water is stated explicitly in SDG 6 on water and its sub-goals. Water management in Bangladesh and elsewhere is becoming more challenging due to growing demand and increasing conflict among users. The decision support tool, Water Evaluation and Planning System (WEAP) developed by Stockholm Environmental Institute (SEI) is increasingly being applied in managing water resources systems in diverse environments across the world. This study employed this toll for Gazipur and Manikganj districts, where the former area is water abundant and the latter is water stressed. Being the adjacent areas to the capital Dhaka, these districts are considered as commercially and industrially important area in Bangladesh. Water resources of this area is distributed unevenly over space and time (between and within years) making it a scarce resource in most places and situations. These districts are used to compare in respect of water resources availability, demands, unmet demands and managements. For water allocation, water demands of the different sectors for the base year 2016 and 2020 have been estimated. Water demands have been projected for the year 2030 and 2050. Water demand of domestic sector has been estimated for base year 2016, 2020 and for future years 2030 and 2050. Water demand of agricultural sector has been divided into crop water demand and livestock water demand. Crop sector water demand has been assessed using meteorological data by using FAO CROP WAT 8.0 software. Major crops like Boro and Wheat are considered for determining irrigation water requirements. Irrigation water requirements have been assessed for the year 2016, 2020 and projected for the year 2030 and 2050. Questionnaire survey has been conducted to find out water requirements of different type of industries and commercial units. Water demands of cattle, buffaloes, goat, fowl and duck have been determined separately. For surface water resources, river discharges have been simulated using seasonal autoregressive integrated moving average (SARIMA) model. For groundwater, output of groundwater study conducted by Bangladesh Agricultural Development Corporation (BADC) has been used. Upstream and downstream water quality of major rivers have been compared. Surface and groundwater quality have been compared with national and international standards. Using hydrological Tennant method, Environmental flow of all relevant rivers have been estimated. GIS shape file, all sectoral demands, surface water, groundwater data have been incorporated in the WEAP model for water allocation and simulated. Finally, five scenarios have been developed. First scenario has been considered water consumption by demanding sectors without any management in 2016, 2020, 2030 and 2050. Second scenario described regular growth of water demand by all sectors with effective water management. Third scenario described the regular growth of water demand by all sectors with effective water management but no growth of water demand in the industrial sector. Domestic demand site management 11.5 percent and increasing irrigation efficiencies up to 2 percent in 2030 and up to 4 percent in 2050 have been considered as management in water demanding sectors. No unmet water demand has been found in Manikganj in the first three scenarios. But unmet water demand was found for Gazipur. For Gazipur, another two scenarios have been formulated to elucidate water scarcity. Forth scenario has been formulated to replace intensively irrigated boro rice with low water demanding vegetables. Water management have been selected as like the third scenario. But still unmet water demand prevailed. So, the fifth scenario has been formulated to introduce with industrial water reuse increased up to 35 percent in 2030 and 55 percent in 2050. Scenario IV and V have been the modified situation of scenario III. So, finally, five scenarios have been formulated for the allocation of water in the study area. In the current trend without water management, water demand in Gazipur will increase up to 4.37 billion cubic meters (bcm) in 2030 and 7.52 bcm in 2050. Scenario I has been introduced with regular growth of water demand with no management and regulation. The unmet demand was projected to increase to 1.82 bcm in 2030 and 6.42 bcm in 2050. For scenario II, total water demand in Gazipur was projected as 1.82, 2.80, 4.37, and 7.52 bcm for 2016, 2020, 2030, and 2050 respectively. No unmet demand was found in 2016. But unmet demands were found 0.18, 1.42, and 5.71 bcm for 2020, 2030 and 2050, respectively. Scenario III for water scarce district Gazipur resulted in, total water demand 1.82, 2.80, 2.81, and 2.83 bcm for 2016, 2020, 2030, and 2050, respectively. No unmet demand was found in 2016. But the unmet demands were found 0.179, 0.207, and 0.264 bcm for 2020, 2030 and 2050 respectively. After considering three scenarios, unmet demands were found in the water scarce Gazipur district. Boro rice was found to be an intensively irrigated crop in the study area. The scenario IV has been developed to change the cropping pattern in the low flow dry season. This scenario replaced the boro rice from the cropping pattern and introduced vegetables in the dry season. Water demand in scenario IV for Gazipur resulted in 1.37, 2.36, 2.42, and 2.50 bcm for 2016, 2020, 2030, and 2050, respectively. The unmet demands were found to be 0.16, 0.11, and 0.936 bcm for 2020 and 2030 accordingly. Finally, scenario V for Gazipur has been formulated with higher water reuse in the industrial sector. There was no unmet water demand in the Gazipur district. For Manikganj, minimum water demand has been found at 481.20 million cubic meters (mcm) for scenario III in 2050, maximum water demand at 534.80 mcm for scenario I in 2020, which are the reasons for the decreasing trend of crop land. There was no unmet water demand for Manikganj for all scenarios. Industrial waste water reuse has been found as a good guideline for lowering water demands. District level restriction on new industries has been found successful for lowering water demands. Vegetable cultivation instead of rice cultivation has been found effective in lowering irrigation water demands. Finally, district specific water uses guidelines or micro level water policy have been found to be very useful in improving water scarcity.

2023-09-16T00:00:00Z Abdullah, Faruque http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7042 2025-04-19T04:45:30Z 2024-10-23T00:00:00Z

Monitoring water level, discharge and shoreline of Jamuna river using multi-satellite data Jahan, Dr. Nasreen; Abdullah, Faruque; 1018162012; 627.1220954924/FAR/2024 In a river-centric deltaic country like Bangladesh, an optimal and efficient management of water resources is a challenging task. This is further exacerbated by the lacking coverage and availability of the observation data, such as water level, discharge, and bathymetry. Traditional in-situ observation platforms are costly to install and maintain, and the data is often publicly inaccessible. This does not meet water resources management requirements, where timely and reliable information with high spatial and temporal coverage is preferable. Therefore, this study aims to address these challenges by designing a multi-satellite monitoring system that provides comprehensive, timely, and accessible data on key water resources components i.e. water level, discharge, shoreline, and floodplain bathymetry—thereby enhancing spatial and temporal coverage to meet the critical needs of water resource management in Bangladesh. The multi-satellite monitoring framework developed in this study integrates altimetry data from Sentinel-3A, Sentinel-3B, Jason-2/3, Synthetic Aperture Radar (SAR) data from Sentinel-1 and spectral data from Sentinel-2. A comprehensive, automated, near-real-time monitoring system is developed that can monitor water levels, discharge, shorelines, and floodplain digital elevation models (DEMs) and implemented over the Jamuna River. By leveraging the multi-satellite technique, the observation period of water level and discharge has been significantly improved from an average of 10 days with single satellites to 3.90 days and a continuous record has been developed for 2008 to 2022. Using SAR and multi-spectral imageries from Sentinel-1 and Sentinel-2 respectively, an automated shoreline extraction technique is applied to monitor the river shoreline and morphology in quasi near real-time. Such continuous monitoring provides an annual floodplain DEM, as well as a yearly assessment of river erosion-accretion. The dataset generated in this study has been validated based on in-situ observations at BWDB stations i.e. Bahadurabad (SW46.9L) and Kazipur (SW49A) showing good performances in monitoring water level and discharges. Multi-satellite water level monitoring shows an RMSE, MAE, average percent error and correlation coefficient values of 0.53 m, 0.36 m, 2.31% and 0.98 respectively while discharge estimations exhibited RMSE, MAE, average percent error and correlation coefficient of 4,738 m³/s, 2,997 m³/s, 23.69% and 0.95 respectively at Bahadurabad station. Analysis of the DEM reveals that the floodplains along the Jamuna river have been substantially changed over the last ten years, and the global bathymetry product does not reflect the current river topography (particularly the Chars). In addition, the erosion zone identified in the process matches well with secondary newspaper-based field conditions. By leveraging the improved temporal frequency provided by the multi-satellite data, the water level and discharge datasets developed in this study were able to effectively capture flood events. Additionally, continuous monitoring of the shoreline and floodplain using high-resolution satellite imagery provided highly detailed information on flood extents, enabling precise mapping and comprehensive assessment of the affected areas. This study concludes that multi-satellite remote sensing technique presented here can not only be a reliable operational tool for water resources management agencies in Bangladesh, but also can provide valuable and publicly accessible dataset to the broad water resource research community. Such up-to-date and accessible dataset should be useful for further advancing research on floods, morphological evolution, as well as for more informed decision-making.

2024-10-23T00:00:00Z