## 4 Results and Discussion
### Results of the Rainfall-Runoff Simulation Model  
To assess the performance of the campus drainage system and surface runoff under various rainfall return periods, we selected outlet point D as the study focus (see Figure 3) to estimate the system's load. The runoff volume at this main outlet reflects the runoff of the entire connected study area. Table 6 presents the runoff volumes from the rainfall-runoff simulation model, while Figure 5 illustrates the relationship between the rainfall intensity and the runoff volume at outlet point D across different return periods.  
As shown in Table 6 and Figure 5, the peak runoff volume at the outlet lagged behind the peak rainfall intensity for the same return period, indicating a delay, as surface runoff generation requires time. With increasing return periods, the lag between the peak runoff volume and the rainfall intensity gradually shortened. The study area's rainfall intensity shows a positive correlation with the outlet runoff volume per unit time, and the runoff duration extended with increased rainfall. After reaching peak rainfall, as the rainfall intensity diminished to zero, the outlet runoff volume did not immediately decrease. A portion of rainwater remained stored, preventing immediate relief of pressure in the  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Return** & **Infiltration** & **Surface Runoff** & **Peak Flow** & \begin{tabular}{c} **Time of Maximum** \\ **Rainfall Intensity** \\ **\(T_{\text{0}}\) (min)** \\ \end{tabular} & \begin{tabular}{c} **Time of Peak** \\ **Flow \(T_{s}\) (min)** \\ \end{tabular} & \
\begin{tabular}{c} **Interval Time** \\ **Flow \(T_{s}\) (min)** \\ \end{tabular} &
\begin{tabular}{c} **Runoff** \\ **Coefficient \(\psi\)** \\ \end{tabular} \\ \hline
1 & 5.59 & 25.31 & 1.10 & 48 & 66 & 18 & 0.74 \\
2 & 5.65 & 41.20 & 2.16 & 48 & 62 & 14 & 0.81 \\
5 & 5.70 & 62.34 & 3.84 & 54 & 64 & 10 & 0.86 \\
10 & 5.81 & 92.11 & 4.84 & 60 & 69 & 9 & 0.89 \\
20 & 5.83 & 107.11 & 5.45 & 60 & 67 & 7 & 0.91 \\
50 & 5.85 & 126.97 & 6.31 & 60 & 66 & 6 & 0.92 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Results of runoff volume at outlet point D under different return periods.  
Figure 4: Process of rainfall events under different return periods (y means year).  
drainage pipes. Consequently, a significant amount of water continued to accumulate in the pipeline until the rainfall event concluded.  
The ability of the campus surface to absorb rainwater has been significantly reduced due to outdated construction, aging drainage infrastructure, low permeability of the building roofs and roadways, insufficient water storage capacity in green spaces, and a high proportion of impermeable surfaces. As a result, the campus struggles to cope with the extreme rainstorm events typical of Wuhan. Rainwater is primarily discharged into the municipal drainage system via surface runoff, which increases the load on the stormwater infrastructure. This often leads to ponding and waterlogging during heavy rainfall, severely disrupting the daily activities of teachers and students. Furthermore, the existing drainage system lacks provisions for retaining and reusing rainwater, resulting in unnecessary water wastage.