# Evaluating CHIRPS and ERA5 for Long-Term Runoff Modelling with SWAT in Alpine Headwaters
## 5 Conclusions  
This study evaluated the performance of two gridded precipitation products (GPPs), CHIRPS and ERA5, as alternative inputs to the SWAT hydrological model in three pilot catchments in the inner Austrian Alps. The objective was to assess the suitability of GPPs for long-term runoff simulations, through a combination of point-to-point comparisons of precipitation amounts and trends and comparisons between simulated and observed runoff and runoff trends. The key conclusions are as follows:  
* Both gridded precipitation products (GPPs) effectively replicate the observed precipitation patterns and reproduce the observed runoff regime. CHIRPS generally outperforms ERA5, showing lower _RMAE_ in annual (25% CHIRPS, 37% ERA5) and monthly (40% CHIRPS, 44% ERA5) precipitation estimates. This translates into improved runoff performance, with CHIRP achieving lower _RMAE_ in annual (12% CHIRPS, 20% ERA5) and monthly (20% CHIRPS, 26% ERA5) runoff. Despite its higher bias in precipitation and runoff, ERA5 demonstrates a higher correlation and a more consistent performance in precipitation amounts and trends across elevation bands and pilot catchments. This consistency likely stems from ERA5's reanalysis framework, but it is limited by coarser resolution. The comparable performance of CHIRPS and ERA5 aligns with findings from earlier studies in the Alps [51, 58, 94]. * The evaluation of GPP precipitation trend performance has received limited research attention. Trend analysis shows that both GPPs generally follow observed precipitation trends and are capable of reproducing observed long-term runoff trends. Their performance in capturing precipitation trends is comparable to that for precipitation amounts. While precipitation trends are generally overestimated, CHIRPS shows lower precipitation trend bias at annual, seasonal, and monthly scales. This cascaded GPP performance, from precipitation amounts to precipitation trends, has been reported previously, including similar precipitation trend performance between CHIRPS and ERA-Interim (_Error_TP_ = 1.87% y\({}^{-1}\) CHIRPS, 1.97% y\({}^{-1}\) ERA-Interim) [80]. * CHIRPS's lower \(RMAE\) in annual precipitation corresponds to a lower annual runoff error than ERA5, while ERA5's higher cold season precipitation results in elevated runoff \(RMAE\) relative to CHIRPS. Similarly, spatial patterns of precipitation trend errors are reflected in the corresponding runoff trend errors in the respective catchments. Seasonal precipitation trend error is likewise mirrored by seasonal runoff trend error. These consistent cascade of errors from precipitation and precipitation trends to runoff and runoff trends highlight the substantial impact of precipitation performance on hydrological model outputs in the pilot area. * Some systematic overestimations of precipitation and precipitation trends are evident. Both products overestimate precipitation at lower elevations and during cold season. These biases likely stem from challenges in capturing winter precipitation from non-convective systems and snow-covered surfaces, particularly in complex alpine terrain. Additionally, both GPPs tend to overestimate precipitation trends during the warm season. * The spatial resolution of GPPs substantially influences hydrological model performance in mountainous areas, independent of GPP performance in representing precipitation amounts and trends. CHIRPS's finer spatial resolution (0.05\({}^{\circ}\)), gauge correction, and enhanced ability to capture orographically induced precipitation make it more suitable for complex mountainous terrain. CHIRPS's more reliable runoff trend estimates and fewer missed trend significance counts at the monthly scale strengthen its advantage for long-term hydrological simulations in multiple mountainous catchments, particularly smaller ones. In contrast, ERA5's coarser grid may limit its ability to accurately resolve orographic precipitation patterns in smaller catchments.