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- ItemEnhancing Flood Simulation in Data-Sparse Niger Central Hydrological Area River Basin in Nigeria using Machine Learning-Based Data Fusion.(Springer Nature, 2026-03-12) Ganiyu, Habeeb Oladimeji; Ng, Cia Yik; Othman, Faridah; Wan Jaafar, Wan ZurinaFlooding remains a persistent and devastating natural hazard in Nigeria. Accurate precipitation data are critical for hydrological simulation of floods. However, many river basins in Nigeria lack adequate ground-based meteorological data. This has created a need for alternative rainfall data sources, with satellite-based precipitation products (SPPs) offering promising solutions. However, SPP estimates often exhibit biases and uncertainties, particularly in complex tropical environments. Therefore, enhancing SPP accuracy through data fusion is essential for reliable hydrological modelling. This study enhances flood event simulation in a data-sparse Niger Central Hydrological Area River Basin in Nigeria by employing Extreme Gradient Boosting (XGB), Random Forest (RF), and Long Short-Term Memory (LSTM) models to fuse daily downscaled PERSIANN-CDR with observed rainfall data from 2013 to 2022. The RF-fused PERSIANN-CDR exhibited higher accuracy than the XGB and LSTM models. It improved the downscaled PERSIANN-CDR mean correlation coefficient (R) by 113.48% and reduced the mean MAE, RMSE, and Bias by 29.90%, 26.76%, and 75.71%, respectively. The reliability of the RF-fused PERSIANN-CDR was validated hydrologically using the HEC-HMS model. The simulated flow relative to the observed flow indicated improved NSE and R² values, alongside reduced RSR values during the calibration and validation periods, compared to the individual datasets. The robustness of the RF-fused data improvement was further validated using bootstrapped 95% confidence intervals and paired Wilcoxon tests (p<0.05). This study presents a practical framework that demonstrates the potential of data fusion to enhance satellite precipitation estimates for flood simulations, offering a viable approach for improving flood preparedness in data-sparse regions.
- ItemEffects of Resampled DEM on Watershed Characteristics and Prediction of Sediment Load in Oyun Watershed, Kwara, Nigeria(Journal of Civil Engineering and Urbanism, 2024-09-25) Adeogun Adeniyi Ganiyu; Abdulrasheed. W. Mansur; Abdurasaq. A. MohammedUnderstanding the terrain and its impact on watershed characteristics, streamflow, and sediment loading is crucial for effective water resource management. This study investigates the influence of resampled Digital Elevation Models (DEM) on the prediction of watershed characteristics, streamflow, and sediment loading upstream of Oyun River Watershed, Nigeria. Various DEM resolutions, ranging from 30-meter to 90-meter, were analysed to assess their effects on hydrological predictions. To delineate the watershed, a DEM of 90-meter resolution was sourced from the space Shuttle Radar Topography Mission (SRTM), and the ASTER global DEM data sources. The 90 meter resolution was resampled to four different resolutions which are 75-meter, 60-meter, 45-meter, and 30-meter resolutions. The watershed and streamline were delineated, and the hydrologic simulation was performed using Soil and Water Assessment Tool (SWAT). The research findings revealed that changes in DEM resolution had a negligible impact on streamflow predictions within the Oyun River Watershed. However, a noticeable impact was observed in the prediction of sediment concentration. The 90-meter resolution DEM yielded the lowest predicted sediment concentration, measuring 2.28 mg/l, while the 30-meter resampled DEM produced the highest value at 5.21mg/l. Similarly, the sediment yield (SYLD t/ha) exhibited considerable variation across the different DEM resolutions, with the 90-meter DEM demonstrating the lowest value of approximately 528.90 t/ha, and the 30-meter DEM registering the highest at 2145.57 t/ha. Overall, this research highlights the necessity of careful DEM selection in hydrological modelling to ensure a comprehensive understanding of watershed dynamics, particularly in regions where sediment transport and water quality are of paramount concern.
- ItemInvestigation on Fluoride Concentration in Well Water and Its Health Implications: A Case Study of Gwagwalada, Gwagwalada Area Council, FCT, Abuja(2023-12-12) Habeeb Solihu; Ismaeel Abdulraheem; Solomon Olakunle Bilewu; Adeniyi Ganiyu AdeogunThis study focuses on determining the concentration of fluoride ions in selected hand-dug wells and investigating its health im plications in Gwagwalada Area Council, Federal Capital Ter ritory, Abuja. The necessity for this investigation arose from observed health issues, including dental and skeletal fluorosis among the residents in the area. Fifteen sampling points (well water sources) were chosen in the study area, and a total of for ty-five samples (three per sampling point) were collected. The calorimetric water quality analysis method was employed to an alyze these samples in the laboratory. Additionally, the Inverse Distance Weighting (IDW) interpolation method was used to generate a spatial variation map for fluoride ion concentration using ArcMap. The results indicate a concentration range of 0.122 mg/L to 1.910 mg/L across the study area. When com pared with the recommendations for fluoride ion concentration in the Nigeria Industrial Standard (NIS) for drinking water (0.1 – 1.0 mg/L), approximately 67% of the sampling points (10 out of 15) fall within the recommended values, while 33% fall out side. The areas with higher fluoride ion concentrations include Dupa 1, Dupa 2, Tunga Maje 1, Tunga Maje 2, and Old Ku tunku 2. The study concludes that the observed dental and skel etal fluorosis in these areas can be attributed to the consumption of water with high fluoride concentrations. Consequently, the study recommends increased attention from both local and fed eral authorities to provide potable water for human consump tion in these areas to address the associated health challenges