Abstract:

Based on daily temperature and precipitation data from 1981 to 2020, a standardized compound dry−hot index (SCDHI) was constructed. Pearson correlation, Spearman rank correlation and quantile regression methods were used in combination with soil moisture data and land cover types to assess temporal variability in SCDHI and its impact on soil moisture. The results showed that: (1) from 1981 to 2020, compound hot−drought events in Ningxia exhibited a phased and fluctuating upward trend, mainly concentrated in July and August, with an overall increase in frequency. (2) SCDHI and soil moisture exhibited a significant overall positive correlation. Among different land cover types, grassland and farmland showed the strongest correlations (r=0.58), followed by forest (r=0.56) and bare land (r=0.51), indicating stronger ecological buffering capacity in forested areas. (3) Quantile regression results revealed that grassland and bare land were most sensitive to SCDHI in the medium to high quantile range (30%−70%), farmland showed a certain degree of buffering effect due to human intervention, while forest showed no significant response. This method effectively reveals asymmetric relationships that cannot be detected by conventional mean−based analyses. In summary, compound hot−dry events have increased in frequency during the growing season in Ningxia, and their impact on soil moisture shows significant variability across land use types and quantile levels. The findings provide scientific support for regional drought monitoring and land management strategies.

Key words: Compound hot and dry events, Soil moisture, Copula function, Quantile regression