## 4 Discussions
Through the integration and removal of fine patches, a total of 551 HRUs including forest land, cultivated land, grassland, water land, bare land, and construction land were delineated (Figure 7). The HRU can fully reflect the characteristics and laws of land distribution in the KAPZs, and provide a data carrier for the following correlation analysis and regression analysis. According to the MHRU, the spatial autocorrelation analysis of the groundwater depth in the agricultural-pastoral ecotone was carried out. The spatial autocorrelation can effectively reflect the spatially high and low concentration characteristics of groundwater depth. The results (Figure 8) show that the groundwater burial depth shows an obvious step-like distribution, and the east shows a high-value aggregation. The wide distribution of cultivated land and bare land leads to a significant drop in groundwater level compared to the west; therefore, in the spatial autocorrelation analysis, forest land, bare land, and cultivated land have a strong correlation with groundwater depth. [PERSON] demonstrated the correlation between cultivated land and groundwater level through linear regression and the groundwater level in areas where the proportion of cultivated land increased [73]. [PERSON] et al. used the unsaturated zone model to simulate the high correlation between the bare ground and groundwater level [74]. From the qualitative research of groundwater depth to quantitative research, the driving force of groundwater depth change is to represent NDVI, NDDI, and NRI of three types of land and establish ground-weighted regression with groundwater depth. Based on the fitting coefficient R\({}^{2}\) greater than 0.8, the forest land and groundwater burial depth showed a negative correlation trend, and the bare land and groundwater burial depth showed a positive correlation trend; therefore, the study of groundwater burial depth can predict large-scale groundwater burial depths and changes based on geographically weighted regression models through NDVI and NDDI. Cultivated land in mountainous and plain areas presents distinctly different distribution rules. Due to the proximity of forest land and rivers within the range of cultivated land in mountainous areas, there is a negative correlation with groundwater depth. The cultivated land in the eastern part of the study area has a positive correlation with groundwater burial depth due to its proximity to bare land. Using the geographically weighted regression model, the quantitative relationship between ground-type band index and groundwater depth is perfectly established, and the band index can be used to predict the convergence and recharge of groundwater depth in unknown areas. [PERSON] also studied the relationship between groundwater depth and land cover in Iran's Hammirza Plain based on geographically weighted regression, indicating that land types have a huge impact on groundwater depth, but the study did not deal with different land cover types separately [75]. This article highlights the geographically weighted regression analysis of the forest land, bare land, and cultivated land with the greatest impact on groundwater depth; however, this study is limited to the groundwater depth of the KAPZs. There may be certain errors in high-altitude areas, densely-vegetated areas, and hilly mountain areas. Because of the uniqueness of KAPZs, we found it to be an interesting and relevant research area. The groundwater burial depth in the KAPZs is an indicator that is hard to detect in the underground soil layer, and plays an important role as a buffer carrier and maintains the water cycle in ECZ [45; 46; 76]. The spatial-temporal differentiation of groundwater depth in KAPZs has obvious characteristics. The types of land cover with obvious hierarchical distribution in the key agricultural and pastoral belts have a decisive influence on the groundwater depth. Based on this, the research on the driving analysis of the ground cover type on groundwater burial depth in KAPZs was studied.