Synergistic Dynamic Optimization of Dry-Wet Edges in NDVI-LST/EVI-LST Feature Spaces and Surface Soil Moisture Monitoring Based on TVDI Crop Growth Periods in the Hetao Irrigation District

Precise spatiotemporal monitoring of soil moisture is fundamental to the efficient regulation and sustainable utilization of agricultural water resources in arid and semi-arid irrigation districts. This study focuses on the Yichang Irrigation District within the Hetao Irrigation Area to elucidate the spatiotemporal dynamics of surface soil moisture during the crop growing season. Multi-year Landsat 8/9 remote sensing imagery (2022–2024) was integrated with the Temperature Vegetation Dryness Index (TVDI) framework to construct two feature spaces, namely Normalized Difference Vegetation Index–Land Surface Temperature (NDVI–LST) and Enhanced Vegetation Index–Land Surface Temperature (EVI–LST). A dual-index complementary inversion strategy was applied for soil moisture estimation, and the outputs were validated against Soil Moisture Active Passive (SMAP) soil moisture products and MOD16 evapotranspiration products. Results indicated that the dry edges of the feature spaces derived from both vegetation indices exhibited double-inflection-point characteristics, with optimal fitting intervals located between the inflection points. The inflection point positions shifted dynamically with variations in crop coverage. During bare-soil and low-vegetation-coverage periods (May, June, and September), the minimum thresholds for low NDVI and EVI values were 0.07 and 0.06, respectively, whereas during high-vegetation-coverage periods in July and August, the minimum thresholds for both indices increased to 0.15. NDVI demonstrated superior performance during May, June, and September, whereas EVI exhibited greater advantages during active crop growth periods in July–August. The optimized model achieved robust inversion accuracy, with a validation R2 of 0.81 for the measured soil moisture in the 0–20 cm layer on 12 May 2024. The inversion results exhibited strong correlations with the SMAP soil moisture products (R2 = 0.663 during low crop coverage; R2 = 0.625 during high crop coverage) and MOD16 evapotranspiration data (R = 0.751). The spatiotemporal patterns of soil moisture were distinctly discerned. Following spring irrigation in May, abundant moisture in certain areas resulted in bimodal distribution patterns in the inversion results. June exhibited the lowest soil moisture content across the study area, with arid zones making up 36.67% of the total area. From July to August, concentrated precipitation coupled with summer irrigation reduced the proportion of extremely arid zones to below 0.98%.