# Evaluating CHIRPS and ERA5 for Long-Term Runoff Modelling with SWAT in Alpine Headwaters
## 3 Results
### Performance Evaluation Using Hydrological Model  
The runoff regime has a strong seasonal character. Higher runoff in late spring and early summer is driven by snowmelt and early summer storms, while lower runoffs occur in the winter months (January, February, March) (Figure 5a). The specific annual runoff is higher in catchments b1 Sill and b3 Isel (929 and 1050 mm) than in catchment b2 Drava (648 mm), which is mainly due to the higher warm seasonal runoff (Table 12). The interannual variations in runoff are particularly evident at the high-elevation stations (b1_KRO, b3_BRU), where summer runoff is more than six-times higher than the winter runoff. The SWAT model simulations with the inputs from the two precipitation products in the period 1991-2018 were compared with the observed runoff at nine hydrological stations in the three catchments. Due to a poorer model performance and the lower estimation of precipitation amounts and trends by the GPPs in catchment b2 Drava, the GPP assessment is primarily based on the model results in catchments b1 Sill and b3 Isel. The SWAT model forced with measured precipitation (MEAS) underestimates annual runoff at the catchment outlets (\(PB\_Q_{annual}=-13\%\) in b1, \(-15\%\) in b3). Since both GPPs  
\begin{table}
\begin{tabular}{c c|c c c|c c c|c c c|c c c} \hline \hline \multirow{2}{*}{**Matrix**} & \multirow{2}{*}{**Product**} & \multirow{2}{*}{_mean a_} & \multirow{2}{*}{**Annual**} & \multicolumn{2}{c|}{**mean**} & \multirow{2}{*}{**Warm**} & \multicolumn{2}{c|}{\multirow{2}{*}{\(\epsilon\)}} & \multirow{2}{*}{**Cold**} & \multicolumn{2}{c}{**mean**} & \multirow{2}{*}{**Monthly**} \\  & & & & & & & & & & & & & & \\ \hline \multirow{3}{*}{(mm)} & **outlets** & & b1\_NN & b3\_LIE & & b1\_NN & b3\_LIE & & b1\_NN & b3\_LIE & & & b1\_NN & b3\_LIE \\ \hline \multirow{3}{*}{\(Q\)} & OBS & 950 & 929 & 1050 & 784 & 698 & 870 & 207 & 228 & 175 & 82 & 77 & 87 \\  & CHIRPS & 877 & 824 & 930 & 734 & 650 & 817 & 143 & 173 & 113 & 73 & 68 & 78 \\  & ERA5 & 1069 & 1185 & 952 & 831 & 830 & 831 & 238 & 356 & 121 & 89 & 98 & 80 \\  & MEAS & 854 & 811 & 896 & 702 & 635 & 769 & 152 & 176 & 128 & 71 & 67 & 75 \\ \hline \multirow{3}{*}{\(PB\)} & CHIRPS & \(-11\%\) & \(-11\%\) & \(-11\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) \\  & ERA5 & 9\% & 28\% & \(-\%\) & \(-\%\) & \(7\%\) & \(19\%\) & \(-\%\) & \(13\%\) & \(56\%\) & \(-\%\) & \(-\%\) & \(10\%\) & \(28\%\) & \(-\%\) \\  & MEAS & \(-16\%\) & \(-13\%\) & \(-15\%\) & \(-10\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) & \(-\%\) \\ \hline \multirow{3}{*}{\(MAE\)} & CHIRPS & 123 & **105** & 141 & 78 & **56** & 100 & 58 & **55** & 61 & 77 & **14** & 19 \\  & ERA5 & 186 & 261 & **112** & 106 & 135 & **78** & 92 & 130 & **54** & 21 & 25 & **17** \\  & MEAS & 136 & 118 & 154 & 84 & 66 & 102 & 51 & 52 & 49 & 15 & 13 & 16 \\ \hline \multirow{3}{*}{\(RMSE\)} & CHIRPS & 12\% & **11\%** & 13\% & 10\% & **8\%** & 11\% & 37\% & **24\%** & 35\% & 20\% & **19\%** & 21\% \\  & ERA5 & 19\% & 28\% & **11\%** & 14\% & 19\% & **9\%** & 44\% & 57\% & 31\% & 26\% & 33\% & 20\% \\  & MEAS & 14\% & 13\% & 15\% & 11\% & 10\% & 12\% & 25\% & 23\% & 28\% & 18\% & 17\% & 19\% \\ \hline \multirow{3}{*}{\(NSE\)} & CHIRPS & & & & & & & & & & & & & & & \\  & MEAS & & & & & & & & & & & & & & & & \\ \hline \multirow{3}{*}{ \begin{tabular}{c} **Monthly** \\ \end{tabular} \begin{tabular}{c} **all stations** \\ \end{tabular}