# Evaluating CHIRPS and ERA5 for Long-Term Runoff Modelling with SWAT in Alpine Headwaters
###### Abstract
Changes in land cover and land use (LC/LU) in mountains are influenced by climate change and are mainly related to snowmelt [18; 19], glacier retreat [20; 21; 22] and the greening of scree slopes [23; 24]. In the 1980s, significant LC/LU changes were observed in the Alps [19], which were caused by increased and earlier snowmelt and a shorter duration of snow cover in the winter months [19]. Similar changes have been observed in glaciated areas over the last 15 years [21; 22]. In the Alps, the greening of previously glaciated areas and scree slopes is occurring at an intermediate rate in most catchments [23] (56% of the area in the French Alps [24]). Recent climate and LC/LU changes have significantly influenced runoff generation in mountainous regions [19; 25; 26; 27; 28]. In the Alps, runoff shows a clear positive trend in winter and spring [12], likely driven not only by a weak positive precipitation trend [12; 13; 15; 29] but more substantially by increased snow and glacier melt and a shift from snow to rain in winter and spring precipitation events [12; 13; 14; 29; 30]. Earlier and intensified snowmelt contributes to higher spring runoff [25; 31]. However, this also results in reduced baseflow and lower summer peak flows, intensifying summer water scarcity when combined with declining precipitation and rising evapotranspiration [25; 26]. These shifts increase summer water demand [27; 32], as dramatically illustrated by the 2022/2023 European drought, during which reservoir levels dropped below historical minima and record salt intrusion occurred in the Italian Po Delta [33]. This highlights the urgent need to better understand the long-term impacts of environmental changes in the Alpine runoff regime. Gridded \(P\) and \(T\) products are widely used as alternative inputs in hydrological models to assess the impact of environmental changes on runoff [12; 34; 35; 36; 37], to support flow and flood forecasting [38; 31; 39] and to support a range of water-related research in river basins. Advances in remote sensing and communication technologies have enabled the development of diverse gridded datasets derived from various sources, including gauges, radar, satellite, reanalysis, or their combinations. These products can be grouped according to the number of input data sources: (a) gauge-only products (GPCC-daily [40], CPC Unified-daily [41], E-OBS [42], SAFRAN [43], SPARTACUS [44]), (b) satellite-only products (CMORPH [45], PERSIANN [46], TRMM [47], SM2 RAIN [48]), (c) gauge-corrected satellite products (CMORPH-CRT [49]) or gauge-corrected reanalysis products (ERA-Interim and ERA5 [50], PGF [51], CFSR [52]), and (d) products with a combination of the gauge, satellite and reanalysis inputs (CHIRPS v2.0 [53], MSWEP 2.2 [54]). A summary of publicly available gridded datasets (Table 1) shows that most products offer global coverage (except for some observation-based products, i.e., E-OBS, SAFRAN, SPARTACUS) and typically feature spatial resolution around 0.25\({}^{\circ}\) with daily or sub-daily temporal resolution. Publicly available gridded climate products offer sufficient temporal and spatial resolution to support hydrological modelling in poorly gauged regions. However, it is important to evaluate their respective advantages and limitations [54; 55; 56], particularly in topographically complex areas influenced by convective precipitation and snowfall [57; 58]. The performance of gridded products is usually  
applications [86; 87; 88; 89; 90; 91; 92] and for simulating climate and land use change impacts [1; 93]. The details of these studies are summarized in Table 2.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & **Variable** & **Authors(s)** & **Study Area** & **Assessment** \\ \hline \multirow{9}{*}{CFSR} & \(p\_T\) & [PERSON] et al. [62] & Catskill Mountains, (USA); Blue Nile & m (SWAT) \\  & \(p\_T\) & [PERSON] \& [PERSON] [63] & & (Ethiopia) & m (SWAT) \\  & \(p\_T\) & [PERSON] \& [PERSON] [79] & Lake Tanana, Ethiopia & \(\alpha\)+m (SWAT) \\  & \(p\_T\) & [PERSON] et al.