## 3 Results
### Influencing Factors of Evaportranspiration Change  
The state of the substratum vegetation is an important factor influencing the actual evapotranspiration process, temperature and precipitation changes affect the regional hydrothermal distribution, and the actual evapotranspiration changes are in turn closely related to the hydrothermal variation pattern [43]. Therefore, to investigate the causes of evapotranspiration changes in the Yiluo River Basin, normalized difference vegetation index (NDVI), precipitation (P) and mean temperature (T) were selected for correlation analysis of actual evapotranspiration in the Yiluo River Basin. The correlation analysis of ETa with the influencing factors was carried out based on month-by-month data, and the monthly values were averaged over the entire basin. The scatter distributions of correlations between ETa and NDVI, P, and T by Pearson correlation analysis are shown in Figure 5a,c,e, respectively. ETa was positively correlated with NDVI, P, and T, with correlation coefficients of 0.87, 0.66, and 0.93, respectively (all passed the 0.01 significance test), indicating that temperature may be the dominant factor affecting ET variation. The spatial distribution of the correlation coefficient between ETa and NDVI, P, and T is shown in Figure 5b,d,f, and the proportion of the watershed area in the areas showing significant positive correlation reached 99%. From the spatial distribution of the correlation coefficient between ETa and NDVI, P, and T, the areas with negative correlation and low correlation coefficient were mainly distributed around towns, reservoirs, and rivers in the downstream area. In general, ETa has a positive correlation with NDVI, precipitation, and temperature in the Yiluo River Basin. The correlation coefficient between ETa and NDVI was \(-\)0.09 to 0.91, with an average value of 0.74; the correlation coefficient with precipitation was \(-\)0.26 to 0.75, with an average value of 0.63; and the correlation coefficient with air temperature was \(-\)0.002 to 0.94, with an average of 0.87. From the correlation analysis results, ETa showed the best correlation with temperature, followed by NDVI and then precipitation. Figure 4: ETa change within a year: (**a**) monthly change; (**b**) seasonal change. Figure 5: Correlation between ET and NDVI, precipitation and temperature: (**a**) scatter distribution of correlation between ET and NDVI; (**b**) spatial distribution of correlation coefficient between ET and NDVI; (**c**) scatter distribution of correlation between ET and p (**d**) spatial distribution of correlation coefficient between ET and p; (**e**) scatter distribution of correlation between ET and T; (**f**) spatial distribution of correlation coefficient between ET and T.  
The interannual and intra-annual changes in NDVI, precipitation, and temperature are shown in Figure 6. From the intra-annual variation in evapotranspiration (Figure 6d), the monthly variation in actual evapotranspiration was consistent with the growth pattern of vegetation and the monthly variation in precipitation and temperature. From January, the temperature increased monthly, precipitation was gradually abundant, vegetation entered the budding stage in spring and the growth peak in summer, and the actual evapotranspiration increased accordingly, reaching the annual maximum in July. After August, the temperature decreased monthly, precipitation decreased, vegetation started to leaf out in autumn and entered dormancy in winter, and actual evapotranspiration decreased accordingly. From 2001 to 2020, NDVI and temperature showed an increasing trend, the growth rate of NDVI was 0.0046/a, and the growth rate of temperature was 0.024 \({}^{\circ}\)C/a; the precipitation showed a decreasing trend, and the decrease rate of precipitation was 6.01 mm/a. It can be seen from the previous section that the change in actual evapotranspiration showed a decreasing trend, the same as that of precipitation, and opposite to that of NDVI and temperature.