###### Abstract  
This study presents a comparative analysis of flood simulations using rain gauge, ground- and space-borne radar precipitation products. The objectives are to assess the effectiveness of two radar-based data sources, namely the Radar-AWS Rainrates (RAR) and Integrated Multi-satellite Retrievals for GPM (IMERG), in a dam watershed with gauge observations, and explore the modeling feasibility of integrating the half-hourly IMERG satellite precipitation in regions with ungauged or limited observational area. Two types of HEC-HMS models were developed, considering area-averaged and spatially distributed gridded data simulations utilizing eight selected storm events. The findings indicate that the RAR data, although slightly underestimate precipitation compared to the gauge measurements, accurately reproduce hydrographs without requiring parameter adjustments (Nash-Sutcliffe efficiency, ENS, 0.863; coefficient of determination, R\({}^{2}\), 0.873; and percent bias, PBIAS, 7.49%). On the other hand, flood simulations using the IMERG data exhibit lower model efficiency and correlation, suggesting potential limitations in ungauged watersheds. Nevertheless, with available discharge data, the calibrated model using IMERG shows prospects for utilization (ENS 0.776, R\({}^{2}\) 0.787, and PBIAS 7.15%). Overall, this research offers insights into flood simulations using various precipitation products, emphasizing the significance of reliable discharge data for accurate hydrological modeling and the need for further evaluation of the IMERG product. radar; RAR; GPM IMERG; flood simulation; HEC-HMS; ModClark 202315298981152981  
precipitation product is available at 0.1\({}^{\circ}\) latitude/longitude spatial and half-hourly temporal resolutions in three modes: early, late, and final runs based on latency and accuracy, covering the region between 65\({}^{\circ}\) S and 65\({}^{\circ}\) N latitudes. The IMERG is currently accessible from June 2000 to present, with a long-duration archive for scientific research and near real-time applications such as disaster monitoring [7; 9]. The GPM mission has opened new horizons for precipitation observations in ungauged regions through a constellation of satellites and ground systems from partner agencies located in the United States, Japan, Europe, and India, providing the IMERG products on a global scale [5; 7]. The utilization of these products for hydrological modeling and prediction aligns with one of the primary scientific objectives of the GPM mission. However, uncertainties remain regarding the accuracy and suitability of applying these products to ungauged regions. Research efforts to investigate the hydrological utility of these IMERG products have been conducted [10; 11; 12; 13; 14; 15; 16], in addition to the previously performed initial studies on rainfall calibration and validation across various regions worldwide for assessing their applicability. [PERSON] et al. [10], [PERSON] et al. [11], [PERSON] et al. [12], [PERSON] et al. [13], [PERSON] et al. [14], [PERSON] et al. [15], and [PERSON] [16] evaluated the applicability of the IMERG precipitation estimates for hydrologic modeling at the hourly, sub-daily, and daily scales using the CREST [10], GXAJ [11], VIC [12; 13; 14; 15], and SWAT [16] models, respectively. The findings from these studies showed evidence of the significant potential of the IMERG final run products in hydrological modeling. However, they exhibited poor correlation with gauge observations, particularly at the hourly and sub-daily scales. Thus, they can be utilized as the sole available source of precipitation in regions where ground observations are unavailable. Furthermore, prominent studies have utilized the daily IMERG product, focusing on its direct application to hydrologic models: [PERSON] et al. [17] evaluated its streamflow prediction utility using the CREST hydrologic model in the Ganjiang River basin, China. [PERSON] et al. [18] performed MGB-IPH model simulations for obtaining streamflow over the Amazon Basin of Peru and Ecuador.