# Evaluating CHIRPS and ERA5 for Long-Term Runoff Modelling with SWAT in Alpine Headwaters
###### Abstract
[59] & Swiss and Italian Alps, French & o \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & North America & o+m (HMETS, GR4) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [54] & Global & o+m (HBV) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & USA & m (GR4), HMETS) \\ \hline \multirow{9}{*}{EMORPH-CRT} & \(p\) & [PERSON] et al. [80] & Global & o+m (HBV) \\ \cline{1-1}  & \(p\) & [PERSON] et al. [58] & Austria & o \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [58] & Austria & o \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & North America & o+m (GR4), HMETS) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [54] & Global & o+m (HBV) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & USA & m (GR4), HMETS) \\ \hline \multirow{9}{*}{CMORPH-RAW} & \(p\) & [PERSON] et al. [80] & Global & o+m (HBV) \\ \cline{1-1}  & \(p\) & [PERSON] et al. [58] & Austria & o \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & Upper Adige basin, Italy & o+m (ICHYMOD) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & Upper Adige basin, Italy & o+m (GR4) \\ \hline \multirow{9}{*}{EMORPH-RAW} & \(p\) & [PERSON] et al. [59] & Swiss and Italian Alps, French & o \\ \cline{1-1}  & \(p\),T & [PERSON] et al. [78] & Cevernes, etc. & o+m (HYPAMOD) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [80] & North America & o+m (HYPAMOD) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [54] & Global & o+m (HBV) \\ \cline{1-1} \cline{2-3}  & \(p\) & [PERSON] et al. [8] & USA & m (GR4), HMA review of the published results highlights that the optimal choice of gridded climate product for hydrological modelling is area-specific, particularly in complex mountainous regions like the Alps. In continental Europe, numerous studies have compared gridded products to gauge data [48; 51; 56; 58; 59; 60; 61; 69; 80; 96], and several have evaluated climate products in the European Alps using hydrological models such as ICHYMOD, HBV and GR4J models [65; 67; 80; 85]. However, only a few have evaluated products within the SWAT model framework in an Alpine environment [64; 66]. In the Upper Adige basin (Italy), CHIRPS-V2.0 and TRMM \(P\) products, combined with measured \(T\) inputs, were evaluated using SWAT [64] and showed satisfactory model performance, suggesting CHIRPS is a favorable option for Alpine regions [64]. Similarly, the CFSR \(P\) and \(T\) products and SAFRAN \(P\) product were evaluated using SWAT in the Garonne basin (France) [66]. A broader comparison involving CHIRPS-V2.0 and CFSR \(P\) products across multiple climatic regions, including Spain, also supported CHIRPS as a more suitable input for SWAT, largely due to its finer spatial resolution (0.05\({}^{\circ}\)), which more effectively captures precipitation spatial heterogeneity [75]. ERA5 has been evaluated in Alpine regions against gauge data in Austria [58], in the Alto Adige region using the ICHYMOD model [85] and as an input to HBV-3 in Switzerland, where it showed strong calibration performance [31]. It also demonstrated comparable performance to CHIRPS for model calibration in Africa [8] but produced mixed performance when compared to gauge data in Austria [58]. In our study, CHIRPS-V2.0 and ERA5 were used with the CFSR \(T\) dataset, which has previously showed acceptable performance in SWAT applications in the French Alps [66] and in Spain [75]. We considered including additional GPPs such as MSWEP-2.2 due to its demonstrated high performance across various regions, including Europe [80]. The same study also noted that while CHIRPS outperformed other GPPs in some other areas, no single dataset consistently yielded the best performance across all regions. Given that MSWEP-2.2 is a