# Projections of Climate Change Impact on Stream Temperature: A National-Scale Assessment for Poland
## 4 Discussion  
### Modelling of Climate Change Impact on Stream Temperature  
The modelling of stream temperature under climate change exhibits a wide range of spatial scales, each tailored to specific research objectives and contextual intricacies [49]. Most commonly, studies have focused on the watershed scale, where the integration of climate, land use, and hydrological factors within a distinct drainage area allows for a holistic understanding of stream temperature dynamics [22, 28, 50, 51]. Some investigations extend their purview to a regional scale, encompassing multiple watersheds to capture larger climate patterns and diverse landscapes [52]. Although less common, certain studies adopt a national or global perspective to assess large-scale patterns, relying on coarse-resolution climate models. For instance, [PERSON] et al. [53] explored the influence of anticipated global temperature rise on the temperatures of freshwater resources on a global-continental scale across various climatic zones using a simple regression model based on the relationship between stream water temperature and air temperature. They asserted that the forecasts for future alterations in stream temperature, based on the ECHAM5 A2 and B1 scenarios, suggest a potential increase ranging from 1 \({}^{\circ}\)C to 5 \({}^{\circ}\)C by the 2050s, aligning with the outcomes of the current investigation for the territory of Poland. To date, there has been no national-scale assessment of the influence of climate change on stream temperature covering the entire territory of Poland. Earlier studies, such as those conducted by [PERSON] et al. [29], focused on individual sub-catchments and utilized EURO-CORDEX projections under RCP8.5, employing intricate stream temperature models. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Temperature** & **Season** & **RCP** & **ACT** & **NF** & **FF** & \
\begin{tabular}{c} **FF-ACT Absolute** \\ **Change** \\ \end{tabular} &
\begin{tabular}{c} **NF-ACT Absolute** \\ **Change** \\ \end{tabular} \\ \hline
20 th percentile & summer & 4.5 & 13.2 & 13.7 & 14.2 & 1.0 & 0.6 \\
20 th percentile & summer & 8.5 & 13.2 & 14.2 & 15.8 & 2.6 & 1.0 \\
80 th percentile & summer & 4.5 & 19.0 & 19.4 & 19.9 & 0.9 & 0.4 \\
80 th percentile & summer & 8.5 & 19.0 & 19.8 & 21.4 & 2.4 & 0.9 \\
20 th percentile & winter & 4.5 & 3.9 & 4.5 & 5.6 & 1.7 & 0.7 \\
20 th percentile & winter & 8.5 & 3.9 & 5.2 & 7.0 & 3.1 & 1.3 \\
80 th percentile & winter & 4.5 & 10.0 & 10.4 & 10.9 & 1.0 & 0.5 \\
80 th percentile & winter & 8.5 & 10.0 & 10.8 & 12.5 & 2.5 & 0.9 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Changes in temperature characteristics for Representative Concentration Pathways (RCPs) 4.5 and 8.5 at baseline (ACT), in the near future (NF), and in the far future (FF). According to their findings, the anticipated rise in stream temperatures across these specific sub-catchments is projected to be approximately 1-2 \({}^{\circ}\)C for the period of 2021-2050 and 2-3 \({}^{\circ}\)C for 2071-2100, aligning with the outcomes of the current investigation. Despite relying on a simplified stream temperature model, this study can be regarded as the first macro-scale analysis, offering valuable insights into the predicted alterations in stream temperature and their potential repercussions for freshwater ecosystems in Poland. Generally, in the assessment of climate change impact on stream temperatures, an increase in the spatial scale of analysis often prompts a careful consideration of methodological choices, including the complexity of modelling approaches [41]. As the analysis expands to encompass larger geographic areas, there is a pragmatic need to streamline methodologies to enhance computational efficiency and facilitate broader insights. This may involve opting for modelling frameworks that strike a balance between accuracy and computational feasibility. While high-resolution detailed models might be suitable for smaller scales, the computational demands become prohibitive when applied over extensive regions [40].