## 4 Results and Discussions
### Geographical Exploration of Spatial Differentiation of Water Conservation in Yunnan Province  
#### 4.4.1 Construction of an Impact Factor Index System  
Prior research has established a connection between spatial variations in water source conservation and factors stemming from both the natural environment (including climate, terrain, and ecology) and socio-economic elements (encompassing economic conditions, social development, transportation infrastructure, and land use) [14; 35; 41]. Drawing on these existing studies, we have devised an index system that comprises influencing factors responsible for the spatial differentiation of water conservation function. This system, encompassing dimensions from both the natural environment and social economy, is presented in Table 3 for reference. ArcGIS is used for spatial processing; the grid data of 100 m \(\times\) 100 m are resampled. In order to explore the difference of influencing factors of water conservation function in different climate years, the representative year 2000 of wetter climate, 2010 of normal climate and 2018 of drier climate are selected here for driving factor analysis. \begin{table}
\begin{tabular}{c c c c} \hline
**Tier 1 Indicators** & **Secondary Indicators** & **Tertiary Indicators** & **Specific Indicators** \\ \hline \multirow{4}{*}{Natural Environment} & Climate factors & \(X_{1}\) & Average annual precipitation \\  & \(X_{2}\) & Actual evaporation amount \\  & Terrain factor & \(X_{3}\) & DEM \\  & Ecological factors & \(X_{4}\) & NPP \\  & \(X_{5}\) & NDVI \\ \hline \multirow{4}{*}{Socio-economic} & Economic level & \(X_{6}\) & GDP \\  & Social Development & \(X_{7}\) & Population density \\ \cline{1-1}  & Traffic Location & \(X_{8}\) & Distance from town \\ \cline{1-1}  & Land Use & \(X_{9}\) & Land Use Change \\ \hline \end{tabular}
\end{table} 
Table 3: Index system of influencing factors of spatial differentiation of water conservation function in Yunnan Province. Figure 6: Local spatial autocorrelation of water conservation function in Yunnan Province. 4.4.2 Detection of Spatial Differentiation Factors of Water Conservation Function in Yunnan Province  
As displayed in Table 4, the results of single-factor static year analysis of water conservation function in Yunnan Province highlight that precipitation and Net Primary Productivity (NPP) stand out as the most influential factors in explaining spatial heterogeneity. Specifically, across the years 2000, 2010, and 2018, these two factors exhibited an average correlation exceeding 50%, indicating their central role as core influencing factors [42]. Precipitation, in particular, consistently demonstrated an explanatory power surpassing 75% throughout the years. Factors such as Normalized Difference Vegetation Index (NDVI), elevation, and evapotranspiration maintained explanatory powers above 30%, signifying their secondary yet substantial impact. NDVI, closely linked to vegetation types, exerts an influence on soil characteristics, and previous research underscores the vital role of soil properties in water conservation [40; 43]. Categorized by factor types, climate and ecological factors emerged as the primary contributors to explanatory power. Among socio-economic factors, land use changes exert a more pronounced influence on the spatial differentiation of water source conservation than other variables. This is primarily attributed to regions characterized by dense urban construction, high population density, and extensive impervious surfaces, all of which are susceptible to surface runoff. Table 5 shows the influencing factors of spatial differentiation of water conservation in the three dynamic periods of 2000-2010, 2010-2018 and 2000 to 2018 after excluding the factors that have no significant change between years in ArcGIS spatial processing. Except for NPP and GDP, the explanatory power of other factors increased significantly from 2010 to 2018.