## 3 Results and Discussion
### Optimal Allocation of Irrigation Water Diversion (Model I)
#### 3.2.2 Optimization Results of Crop Planting Structure (Model I)  
Figure 8 illustrates the total planting area of crops across different periods. For the current years, the total planting area of crops increased from 16.5 thousand hectares before optimization to 17.4 thousand hectares after optimization, representing an increase of 0.9 thousand hectares. For the future year, the total planting area of crops is projected to be 18.1 thousand hectares in the short term and 18.4 thousand hectares in the long term, which are 0.7 and 1.0 thousand hectares more than the current years, respectively. Due to constraints on the total amount of irrigation water available, the total planting area of crops in each period does not reach the total arable land area in the irrigation region (20.01 thousand hectares). The potential increase in crop planting area for the current years, short-term years, and long-term years are 2.6, 1.9, and 1.6 thousand hectares, respectively. Despite the shortage of irrigation water resources, efficient use of return flow can lead to an expansion in crop planting area.  
Table 10 presents the results of crop planting structure optimization for different periods. In the current years, the proportion of the planting area for each crop significantly changes compared to the pre-optimization state. Specifically, the planting proportions of spring wheat, corn, and flax, which have low water productivity, decrease by 10.4%, 11.2%, and 3.2%, respectively. Conversely, the planting proportions of potato, melon, goji berry, and forest fruit, which have high water productivity, increase by 6.6%, 0.9%, 8.0%, and 9.3%, respectively. The future year optimization results indicate that only the planting proportion of flax will increase. In the short-term future, the planting proportion of flax  
Figure 8: Total planting area in different periods.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Crop Type**} & \multicolumn{2}{c}{**Current**} & \multirow{2}{*}{**Short-Term**} & \multirow{2}{*}{**Long-Term**} \\ \cline{2-2} \cline{5-5}  & **Before Optimization** & & & \\ \hline Spring wheat & [2.26, 2.95] & [1.29, 1.68] & [1.30, 1.69] & [1.30, 1.70] \\ Corn & [3.34, 4.87] & [2.2, 3.22] & [2.24, 3.25] & [2.26, 3.27] \\ Flax & [2.27, 2.55] & [0.84, 0.94] & [2.82, 3.16] & [3.64, 4.08] \\ Potato & [2.79, 3.87] & [6.60, 9.18] & [6.63, 9.2] & [6.63, 9.21] \\ Melon & [2.34, 3.28] & [2.87, 4.03] & [2.87, 4.03] & [2.88, 4.03] \\ Goji berry & [8.34, 10.24] & [15.06, 18.5] & [15.08, 18.52] & [15.09, 18.53] \\ Forest fruits & [20.04, 26.98] & [30.81, 41.48] & [30.86, 41.54] & [30.88, 41.55] \\ \hline \hline \end{tabular}
\end{table}
Table 9: Results of net profit (million USD) optimization for various crops during different periods (Model I).  
will rise by 3.8%, and in the long-term future, it will increase by 5.4% compared to the current optimized planting proportion. This suggests that the increase in distributable irrigation water due to future climate change will be allocated to expanding flax planting areas, thereby increasing its planting proportion.