River water, vital for water supply, irrigation, and the ecosystem, constantly threatens nearby settlements through flooding and contamination. Excessive precipitation exceeding the riverbed's capacity leads to flash floods in the lowlands or flood plains and water logging for a season or permanently. Precipitation, along with other factors such as land use and the soil profile, is considered the primary catalyst for the hydrological cycle. Accurately estimating runoff volume from rainfall is crucial for reservoir water storage and flood risk assessment. For a few decades, various hydrological models incorporating geographic information systems (GISs) have been utilized for different regional river basins to predict surface runoff patterns. Such models simulate runoff patterns based on time interval rainfall data. HEC-HMS, a rainfall-runoff simulation software package, addresses water availability, flood forecasting, urban drainage, and hydrological impact studies. Creating a data-driven model using this software requires fewer parameters that can easily be calibrated and validated. Knowledge of hydrological behavior and basin parameter factors is pivotal for developing this type of physical model. The literature review clearly showed that globally utilizing this software for regional stream flow forecasting was fairly compelling. Unfortunately, few studies have been performed on the Bangladesh region, where floods are the central natural calamity for socioeconomic loss every year.
The Halda River basin in Bangladesh, known for its extensive agricultural importance (Haque et al. 2020), experiences substantial discharge during monsoons, which can cause floods in nearby areas and Chittagong City (Raihan et al. 2022). Severe land degradation adds to the basin's challenges. To address flooding and water scarcity in lean periods, a study aimed to estimate the basin's runoff by creating a tailored rainfall-runoff model using the HEC-HMS. This model aims to determine the performance of simulating the Halda River hydrology toward enhancing flood risk management.