## 3 Results
### Correlation Between Reservoir Properties, Climate, and Land Use Change  
As shown in Figure 7a, precipitation-related variables (Y-P2 and Y-P4) are significantly correlated with five of the seven regional cooperation frameworks (RCFs)--AREA, CAP, DIS, and DOR--out of the 12 indices. In particular, the correlation between Y-P2 and Y-P4 with YEAR passes the significance test at the \(p<0.05\) level, while Y-P3 also shows a significant correlation with YEAR at the \(p<0.01\) level. Additionally, Y-P2 and Y-P4 were significantly correlated with four RCFs (AREA, CAP, DIS, and DOR). A comparison of the correlation strengths between the S-P and W-P (1-4) indicators for different regions and RCFs reveals that reservoir attributes have a more pronounced impact on precipitation during the summer months than in winter. Specifically, YEAR, CAP, and DIS exert a stronger influence on precipitation, while DEP shows a weaker correlation with precipitation.  
In the case of the temperature variable, its correlation pattern with precipitation differs, showing significant correlations with six RCFs (excluding DEP), with a greater number of significant tests compared to that for precipitation (Figure 7b). Notably, S-T1 shows no significant correlation with any of the RCFs. From the perspective of RCFs, it is important to note that CAP and DEP exhibit weaker correlations with the overall temperature index, while YEAR, FSL, AREA, CAP, and DIS have a stronger influence on temperature, particularly YEAR and AREA. Among the reservoir attributes, YEAR has a more significant effect on both temperature and precipitation. However, when considering the effect of FSL on the post-reservoir precipitation series (LAAV), its impact on precipitation is more pronounced than that on temperature, especially on -T4. Compared to other RCFs, CAP and DIS have a stronger influence on precipitation, with a lesser effect on temperature. In contrast, some RCFs (e.g., AREA, CATCH) have a greater impact on temperature than on precipitation.  
Figure 8 illustrates the correlation between basic reservoir attributes and land use changes. The correlation coefficients reveal notable relationships between different land use types and reservoir attributes. Specifically, impervious surfaces show a strong negative correlation with FSL (\(-0.638\)), while barren areas are more positively correlated with the reservoir attribute AREA (0.332). Water demonstrates a strong negative correlation with several reservoir attributes (YEAR, FSL, and CAP), indicating that changes in water may  
Figure 7: Reservoir attributes and climate correlation analysis map: (**a**) correlation between basic reservoir properties and precipitation; (**b**) correlation between basic reservoir properties and temperature (Note—strong positive correlation (0.7 to 1) *; moderate positive correlation (0.3 to 0.7) *; weak correlation (0 to 0.3)).  
significantly impact water body utilization. Grassland shows weaker correlations with reservoir attributes such as CAP and DIS, though a relationship remains. The correlations between shrubland, forest, and cropland with other reservoir attributes are more complex, showing both positive and negative correlations. This reflects the diverse and multifaceted nature of how basic reservoir attributes influence changes in these land use types. Through these correlation analyses, a deeper understanding of how reservoir attributes affect land use changes can be achieved.