# Evaluating CHIRPS and ERA5 for Long-Term Runoff Modelling with SWAT in Alpine Headwaters
## 2 Materials and Methods
### Evaluation Using Hydrological Model
Following common evaluation practices for monthly time step ([PERSON] et al. [122]), _NSE_ greater than 0.75 indi \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameter** & **Description** & \multicolumn{2}{c}{**Calibration**} & \multicolumn{2}{c}{**Calibration**} \\  & & **Range** & & & \\ \hline V\_TLAPS.sub & \multicolumn{2}{c}{Temperature lapse rate} & \multicolumn{1}{c}{–8—2} & & \\  & (°C/km) & & & & \\ V\_PLAPS.sub & \multicolumn{2}{c}{Precipitation lapse rate} & & & & \\ V\_STMP.bsn & \multicolumn{2}{c}{(mm/100 m)} & 0–100 & & & \\ V\_STMP.bsn & Snowfall temperature (°C) & & & & \\ V\_SMTMPEnsn & Snowf temperature (°C) & & & & \\ V\_SMTMPEnsn & Snowf temperature (°C) & & & & \\ V\_SMFMC.bsn & \multicolumn{2}{c}{Marginal snowmelt factor–21 st} & 5–10 & & & \\ V\_SMFN.bsn & \multicolumn{2}{c}{Minimal snowmelt factor–21 st} & 0–5 & & & \\ V\_SMFN.bsn & \multicolumn{2}{c}{Snow temperature lag factor (°)} & 0–1 & & & \\ \hline  & & **b1 Sill** & & **b2 Dava** & & **b3 Isel** \\ \hline  & & **Calibration** & & & \\  & **range** & **Fitted value** & **cailibration** & **range** & **Fitted value** \\ \hline R\_CN2.mg & \begin{tabular}{c} Soil conservation services (SCS) \\ runoff curve number \\ Threshold depth of water in \\ shallow aquifer for return \\ flow (mm) \\ \end{tabular} & 0–0.2–0.2 & 0.081 & \(-\)0.2–0.2 & \(-\)0.143 & \(-\)0.2–0.2 & \(-\)0.066 \\ R\_ESO.hru & \begin{tabular}{c} Soil evaporation \\ compensation coefficient \\ Delay time for aquifer \\ recharge (days) \\ \end{tabular} & 0–0.25–0.25 & 0.103 & \(-\)0.25–0.25 & 0.151 & \(-\)0.25–0.25 & 0.019 \\ A\_SISUB8N.hru & \begin{tabular}{c} Average slope length (m) \\ \end{tabular} & \(-\)9–115 & 13.44 & \(-\)9–115 & 90.324 & \(-\)9–115 & 2.53 \\ R\_GW_REVAP.gw & \begin{tabular}{c} Groundwater \\ \"reap\" coefficient \\ Threshold depth of water in the \\ shallow aquifer for \"reap\" or \\ Percolation to occur (mm H20) \\ \end{tabular} & 0–0.2–0 & \(-\)0.109 & \(-\)0.2–0.2 & \(-\)0.058 & 0–0.2 & 0.067 \\ V\_ALPHA\_B.gw & \begin{tabular}{c} Beavelhon alpha factor (1/days) \\ Available water capacity of the \\ soil layer (mm H20/mm soil) \\ \end{tabular} & 0–1 & 0.427 & 0–1 & 0.147 & 0–1 & 0.177 \\ V\_RCHG.DP.gw & \
\begin{tabular}{c} Available water capacity of the \\ soil layer (mm H20/mm soil) \\ \end{tabular} & \(-\)0.05–0.05 & 0.034 & \(-\)0.05–0.05 & \(-\)0.047 \\ V\_RCHG.DP.gw &
Note: the “V\_.-° term means replacing the value of the parameter, “R\_.-° means relative change to the parameter, where parameter gets changed by percentage (value given in the calibration range), while “A\_.-° means absolute change, where the provided calibration range values get added or subtracted from the default parameter value.  
\end{table} 
Table 8: Adopted ranges of model parameters. cates very good model skill, values between 0.65 and 0.75 represent good skill, and values between 0.50 and 0.65 satisfactory skill, while _NSE_ below 0.5 is considered unsatisfactory skill. The _NSE_ determines the relative magnitude of the residual variance [122; 123], and previous studies have reported monthly _NSE_ > 0.75 as good model performance [87]. The model skill for the calibration and validation periods (Table 9) shows good performance for catchments b1 and b3 (_NSE_ = 0.90 and 0.93 for the calibration period, _NSE_ = 0.84 and 0.89 for the validation at the outlets). The simulated hydrographs (Figure 4) show that the observed runoff regime for catchments b1 and b3 is well reproduced during both the calibration and validation periods. The model has slightly lower performance in the upstream river sections. The model has worse performance in catchment b2 (_NSE_ = 0.67 for the calibration period and 0.50 for the validation at the outlet). The observed hydrograph in catchment b2 does not show snowmelt-induced high spring discharges as in the other two catchments (Figure 4).