## 3 Results
### The Responses of the Agroecosystem to the VMFDI
#### 3.3.2 The Response of the Crop Growth Status to the VMFDI  
Correlations between the monthly VMFDI and the crop growth status indicators were analyzed (Figure 10). In the agroecosystem, crop greenness (NDVI) was significantly positively correlated with the VMFDI (r = 0.66, \(p<\) 0.05), indicating that reduced crop greenness occurred in response to regional dryness. The GPP, WUE, and LAI of crops were also significantly positively correlated with the VMFDI, with the correlation coefficients of 0.54 (\(p<\) 0.05), 0.20 (\(p<\) 0.05), and 0.59 (\(p<\) 0.05), respectively (Figure 10a). These findings suggest that crop productivity, water use efficiency, and yield decline as regional dryness increases. In maize and wheat planting systems, the NDVI, GPP, and LAI had strong positive correlations with the VMFDI (correlation coefficients \(>\) 0.62, \(p<\) 0.05, and \(>\)0.70, \(p<\) 0.05, respectively) (Figure 10b,c). This indicates that increasing drought intensity leads to decreased crop greenness, GPP, and yields. Notably, WUE was negatively correlated with the VMFDI in maize and wheat planting systems, primarily due to the inconsistent rates of change in GPP and ET, as well as crop resistance to drought. Although both GPP and ET decreased with increasing drought, crop drought resistance helped mitigate the reduction in carbon sequestration, particularly in maize (C\({}_{4}\) plants), which is more effective than C\({}_{3}\) plants in fixing CO\({}_{2}\) under the conditions of high light levels, temperature, and drought. As a result, the WUE of crops, especially maize, increases as drought intensifies. Figure 9: A time series of monthly VMFDI, VPD, SM, SIF, and VMFDI anomalies in the agroecosystem of the Yellow River Basin from 2003 to 2020. In figure (**a**)., r represents the correlation between variables and ***** represents the level of significance (\(p<\) 0.05). The box diagram represents the value distribution of each variable. In figure (**b**), VMFDI_anomalies\({}_{ij}\) is the difference between the VMFDI value in month i of year j and the multiyear mean value in month i. The red bars represent the values below zero. Furthermore, the results indicate that the decreasing VMFDI resulted in a higher VPD and LST but a lower SIF, PRE, and ET (Figures 6a and 11a). These relationships suggest that as drought conditions intensify, atmospheric conditions such as VPD and LST increase, which further exacerbate the drying effects on vegetation. Conversely, the reduction in SIF, PRE, and ET under drought conditions highlights the limitations on photosynthetic activity and water availability in the ecosystem. In terms of the underlying driving forces of drought in the Yellow River Basin, atmospheric circulation is also one nuclear factor causing drought seasonality and annual movement, the anomalies of which generally lead to spatiotemporal variations in precipitation. The Yellow River Basin is located in a transitional climate zone between arid, semiarid, and sub-humid regions, which makes it particularly susceptible to variations in atmospheric circulation. The basin is influenced by both the East Asian monsoon and the mid-latitude westerly belt, making precipitation patterns highly sensitive to shifts in monsoonal activity [68]. Additionally, circulation factors--the Arctic Oscillation (AO), El Nifio-Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO)--significantly impact drought patterns in the Yellow River Basin [66; 69; 70]. For instance, the AO affects the transport of warm and wet water vapor through activities such as the Siberian high, westerlies, and Rossby waves, thereby affecting winter precipitation in the basin [69]. A positive phase of the winter AO has been shown to be associated with a decrease in winter precipitation in northern East Asia [71]. The variation in land--sea thermal differences during ENSO led to the East Asian monsoon transition and further affected precipitation in the basin.