Flood & Hydrogeological Modeling

This study applies hydro-numeric modeling to analyze flood characteristics in an 8 km section of the Old Elbe River using HEC-RAS 1D and BASEMENT 2D. DEM, break lines defining dikes, riverbed, and floodplain, alongside surface roughness variations, were used to refine hydraulic simulations. Mesh discretization was performed to assess 2D floodplain dynamics, while QGIS was employed for pre-processing and visualization. The study evaluates steady-state and subcritical flow regimes, specific discharge, flood extents, velocity distributions, and hydraulic depth variations. Sensitivity analysis was conducted to determine the impact of DEM resolution, mesh size alterations, and land use classifications (LULC) on flood extent and hydraulic parameters. Results show that finer DEM resolutions improve terrain representation, while roughness coefficients significantly affect flood depth, particularly in forested areas. Comparison with historical flood maps highlights discrepancies due to lower discharge values, suggesting the need for calibration and improved modeling approaches. Findings support informed flood risk assessments and sustainable watershed management strategies in dike-protected river systems.

This study employs numerical groundwater modeling to assess hydrological dynamics and water management within the Amsterdam Water Supply Dunes (AWD) in the Netherlands. Using MODFLOW, the analysis incorporates hydrogeological formations, infiltration mechanisms, and abstraction canals to evaluate groundwater flow, recharge, and extraction efficiency in a Managed Aquifer Recharge (MAR) system. The study focuses on simulating steady-state and transient groundwater conditions, examining boundary conditions, hydraulic conductivity, and water balance components using datasets sourced from DINOloket and literature reviews. Scenario analysis assesses the impact of climate change-induced drought and increased water demand on infiltration rates, groundwater availability, and system resilience. Model evaluation and sensitivity analyses validate simulation accuracy, ensuring reliability for water resource management decision-making. Findings highlight the importance of optimizing groundwater abstraction, maintaining artificial recharge stability, and adapting to potential climate-induced stressors to sustain potable water supply for Amsterdam. 

This study evaluates the effects of climate change and urbanization on groundwater recharge within the urban environment of Arusha, focusing on land use and land cover (LULC) transformations over time. Using historical and projected data from 1995, 2020, and 2050, groundwater recharge patterns are assessed under changing urbanization dynamics, household water use, and climate variability. A conceptual water balance model is developed based on precipitation estimates, evapotranspiration rates, impervious surface runoff, soil storage dynamics, and groundwater abstraction rates. Spatial recharge estimates highlight significant reductions in infiltration due to expanded urbanization and increasing impervious surfaces, while climate-driven precipitation variability further exacerbates recharge declines. Groundwater abstraction trends indicate increasing household and municipal water demands, surpassing natural recharge rates in projected scenarios. A comparative analysis of groundwater budget shifts reveals an estimated water table drop of approximately 88 meters by 2050 due to intensified extraction and reduced infiltration. The findings underscore the unsustainable nature of current groundwater use in Arusha and emphasize the need for adaptive strategies, including improved stormwater management, enhanced return flow utilization, and climate resilience measures. This research provides insights into sustainable groundwater resource management and informs policy recommendations for mitigating future water scarcity challenges in urbanizing regions.