# Evaluation of Algal Control Measures in Eutrophic Reservoir Based on Aquatic Ecosystem Models
## 2 Materials and Methods
### Model Setup and Simulation Scenarios
#### 2.5.2 Model Verification and Validation  
The hydrodynamic verification results are shown in Figure 4, while the water quality and biomass indicators' verification results are illustrated in Figure 5. Simultaneously, the model's effectiveness was evaluated and analyzed using the statistical indicators Root Mean Square Error (RMSE) and Nash-Sutcliffe efficiency coefficient (NSE) [46], as shown in Table 2. Due to the strong correlation between chlorophyll and biomass [47; 48], this study uses chlorophyll concentration to represent the biomass indicator.  
Generally speaking, an NSE greater than 0.6 is considered acceptable, and a smaller MRE is preferred. Based on the indicator results (Table 2), the NSEs for TN, TP, NH\({}_{3}\), and flow rate are relatively low, indicating poor performance. However, the NSEs for water level, CHL, TEM, and DO are higher, indicating better performance. The performance of the RMSE is acceptable, with the chlorophyll indicator slightly higher compared to other indicators.  
Overall, the water level simulation results are in good agreement, and the flow velocity simulation demonstrates moderate effectiveness, showcasing the reservoir flow velocity's order of magnitude. The simulated water quality indicators are basically consistent with the measured values, especially the important parameters such as CHL and TEM, effectively reflecting the annual variations in the water quality of Shanzai Reservoir.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Statistical** & **Water Level** & **Flow Velocity** & **Tem** & **DO** & **TN** & **NH\({}_{3}\) (mg/L)** & **TP** & **CHL (mg/L)** \\
**Indicators** & **(m)** & **(m/s)** & **(\({}^{\circ}\)C)** & **(mg/L)** & **(mg/L)** & **NH\({}_{3}\) (mg/L)** & **TP** & **(mg/L)** \\ \hline RMSE & 1.12 & 0.001 & 1.24 & 1.55 & 0.13 & 0.52 & 0.005 & 7.18 \\ NSE & 0.98 & 0.01 & 0.96 & 0.65 & 0.08 & 0.16 & 0.32 & 0.71 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Model statistical indicators.  
Figure 4: Verification of hydrodynamic simulation results.  
Figure 5: Water quality simulation results’ verification.  
Concerning CHL simulation and measurement results, the simulation effectively reflects the inter-annual variations, showing a normal distribution curve with the highest concentration occurring from June to August. The simulation results exceed the measured values in August and September, likely due to the gradual decrease in solar radiation after July in the northern hemisphere, leading to a rapid decline in reservoir temperature. The model's monthly average TEM simulation is 1-2 \({}^{\circ}\)C higher than the actual temperatures due to the reservoir's vertical stratification buffer effect [49]. Moreover, the model utilizes a single-value function curve to express the algae growth rate at the most suitable temperature, while a stepped growth curve where algae maintain a stable growth efficiency within an optimal temperature range may exist in reality [50]. Addressing this discrepancy is a potential direction for further exploration and model improvement.