## 3 Results and Discussion  
First, it is essential to present and discuss the calibration and validation of the SWAT we used to simulate the river flow as well as the nitrate load in the river basin. Figure 6 displays results of the calibration and validation of the outflow and nitrate concentration in the target downstream areas. According to Tables 1 and 2, the model is reliable for further applications. Figure 5: Hierarchical framework of FTOPSIS in the present study [31]. Figure 6: Calibration and validation of outflow and nitrate concentration produced using SWAT. Figure 7 displays the nitrate concentration simulated using the validated model for different crops per hectare in the simulation period. Currently, all targeted agricultural areas in this study are rice fields, but we tried to optimize the area with combinations wheat and rice to minimize environmental impacts. Crops 1 to 4 are two varieties of wheat and two varieties of rice that have been recommended by the Department of Agriculture for the study area. We selected these crops for the optimization system. In fact, the farmers are familiar with the cultivation of these crops. Thus, the proposed optimal cultivation pattern might be useable in practice. Figure 8 displays the optimal nitrate concentration as the output of the optimization model. It seems that the performance of the different algorithms differed regarding the mitigation of the impact of the nitrate concentration on the downstream aquatic habitats in the catchment. However, the performance of some algorithms, such as SFLA and SCE, was similar. The performance of IWO was not as robust as that of other algorithms. The optimum threshold in the optimization model was 50 mg/L, which provides a suitable habitat for aquatic species. This threshold was selected based on the expert opinions of regional ecologists who were familiar with the biological characteristics of the native fishes in the local habitats. Seemingly, IWO was not able to optimize the nitrate concentration in the simulated period. In fact, the optimal nitrate concentration produced by IWO was much higher than that produced by other algorithms. In fact, the performance of this algorithm was poor in terms of the optimization of the nitrate concentration. Conversely, DE was very robust in terms of optimizing the nitrate concentration. In fact, in most time steps, the nitrate concentration was very low, so DE produced crop pattern that creates the most suitable habitats for fishes. However, selecting the best optimization performance was not only based on the performance of the system in terms of nitrate concentration. Other factors should be considered in evaluation of the results of the optimization model. The optimization system should have robust performance in terms of agricultural considerations as well. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **Period** & **NSE** & **RSR** & **PBIAS** \\ \hline \multirow{2}{*}{River flow} & Calibration & 0.93 & 0.26 & \(-0.88\) \\ \cline{2-5}  & Validation & 0.91 & 0.31 & 2.76 \\ \hline \multirow{2}{*}{Nitrate} & Calibration & 0.80 & 0.45 & 5.05 \\ \cline{2-5}  & Validation & 0.83 & 0.41 & 6.91 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Evaluation indices of SWAT in the case study. Figure 7: Nitrate concentration Simulated using SWAT for different crops. Figure 9 displays the optimal cultivation pattern proposed by the optimization model. The performance of the algorithms differed in terms of cultivated area for each crop as well. For example, IWO optimized the cultivation pattern by allocating more area to each crop. In contrast, DE allocated a very small area for some crops. Moreover, Figure 10 displays total area produced using the different algorithms. The total area produced using the IWO method is larger than that produced using the other algorithms. Conversely, the total area produced with DE is smaller than that produced with other algorithms. In fact, it seems that these two algorithms were not able to apply the penalty functions efficiently.