Assessing the Reliability of Multi-Source Gridded Precipitation Products for Use as Inputs to Hydrological and Hydroclimatic Applications: A Case Study of the Helmand River Basin, Afghanistan

Reliable precipitation datasets are essential for basin-scale water resources assessment, climate analysis, flood and drought-related studies, whereas estimation remains challenging in arid to semi-arid, topographically complex, and data-scarce regions. This issue is particularly important in the Helmand River Basin (HRB), Afghanistan, where uncertainty in precipitation input can directly affect hydrological and hydroclimatic assessments. This study evaluated eight multi-source gridded precipitation products against gauge observations from 18 hydro-meteorological stations across the HRB. The evaluation covered daily and monthly timescales, wet and dry season conditions, rainfall-event thresholds, and elevation settings using continuous, categorical, and integrated multi-metric analyses. The results indicate that precipitation product performance in the HRB varies with temporal scale, seasonal regime, and elevation setting. In general, monthly and wet-season evaluations showed better agreement than daily and dry-season evaluations; however, this pattern reflects the combined influence of temporal scale, native product resolution, and spatial extraction method. Among the evaluated datasets, MSWEP and ERA5-Land showed the most balanced overall performance, combining better temporal agreement, lower error, lower bias, and higher rainfall-event detection across stations and elevation classes. CHIRPS also performed well, particularly at monthly and seasonal scales, whereas IMERG and PERSIANN-CDR showed moderate performance. Conversely, CMORPH and GPCC Products were the least reliable because of persistent underestimation in the former and inflated variability and overestimation in the latter. The results further indicate that dataset skill is not spatially uniform, with weaker performance generally associated with high-elevation stations. Overall, this study establishes a basin-specific framework for precipitation dataset selection in the HRB and provides a reproducible basis for selecting fit-for-purpose precipitation inputs for future water resources and hydroclimatic studies in this data-scarce region.