Hydrological modeling in the data-scarce regions is challenging. Recent advances in remote sensing make producing climate data easier and provided alternatives to the conventional climate data sources, particularly for hydro-climatological studies in the data-scarce regions. However, rigorous evaluations are warranted to evaluate the reliability and effectiveness of gridded climate products. This study evaluated the CFSR and CHIRPS products against the observed climate for hydrologic prediction at two streamflow gauging stations. The Soil and Water Assessment Tool (SWAT) is used to simulate hydrological processes in the watersheds. Model sensitivity analysis and calibration were conducted using the Sequential Uncertainty Fitting-2 (SUFI-2) algorithm in the SWAT-Calibration Uncertainty and Prediction (SWAT-CUP). Streamflow simulation performance was evaluated using several statistical, hydrological performances and prediction uncertainty of p-factor and r-factor within the SUFI-2 framework. Simulation of the model using the observed and gridded climate products provided satisfactory model performance in terms of the goodness of fit criteria and uncertainty prediction. Results show that CHIRPS rainfall combined with CFSR and observed temperatures demonstrates slightly better statistics and hydrological performance than observed, but shows substantial difference than CFSR. The simulations with CHIRPS and observed yielded minor differences in the water balance component estimates where the CFSR simulation gave lower average annual rainfall, resulting in lower water balance components. Quantifying the various water balance component in the watershed helps to tackle the water management issues. Overall, the CHIRPS rainfall combined with CFSR temperature can serve as a better alternative climate input for hydrological applications in the study region

数据稀缺地区的水文建模具有挑战性。遥感方面的最新进展使生成气候数据变得更加容易，并为传统气候数据源提供了替代方案，特别是对于数据稀缺地区的水文气候研究。然而，需要进行严格的评估来评估网格化气候产品的可靠性和有效性。本研究根据观测到的气候评估了 CFSR 和 CHIRPS 产品，用于在两个流量测量站进行水文预测。土壤和水评估工具 (SWAT) 用于模拟流域中的水文过程。使用 SWAT-Calibration Uncertainty and Prediction (SWAT-CUP) 中的 Sequential Uncertainty Fitting-2 (SUFI-2) 算法进行模型灵敏度分析和校准。使用 SUFI-2 框架内 p 因子和 r 因子的几个统计、水文性能和预测不确定性来评估流模拟性能。使用观测和网格化的气候产品模拟模型在拟合优度和不确定性预测方面提供了令人满意的模型性能。结果表明，CHIRPS 降雨与 CFSR 和观测温度相结合的统计数据和水文性能略好于观测值，但与 CFSR 相比存在显着差异。使用 CHIRPS 和观察到的模拟在水平衡分量估计中产生了微小差异，其中 CFSR 模拟给出的年平均降雨量较低，导致水平衡分量较低。量化流域中的各种水平衡成分有助于解决水管理问题。总体而言，CHIRPS 降雨与 CFSR 温度相结合可以作为研究区域水文应用的更好的替代气候输入