Soil moisture is one of the restricting factors in the humid karst areas, which feature strong spatial heterogeneity. However, current research about the effects of vegetation restoration on soil moisture content have mainly focused on plot scale and slope scale, while these effects still remain unclear at regional scale in this area. Taking Southwest China as a case study and based on the land parameter data record (LPDR) and enhanced vegetation index (EVI) data set during 2002–2018, this study analyzed the spatiotemporal variation characteristics of vegetation and soil moisture content, and evaluated the effects of vegetation restoration on regional soil moisture content dynamics in paired years with similar precipitation conditions. The results showed that the EVI generally increased at a rate of 0.035/10a during 2002–2018, while the soil moisture was dominated by a drying trend at a variation rate of −0.0006 (cm³/cm³)/10a. The increasing trend of EVI accounted for 90.90% across the study area, whereas the decreasing trend of soil moisture accounted for 51.66%, and the increasing trend of soil moisture accounted for 48.34%. In addition, the decreasing trend of soil moisture coupled with an increasing trend of EVI distributed in most of the study area, especially in the homogenous limestone area. Our results demonstrate that there were remarkable vegetation restoration efforts in a series of ecological restoration projects, which resulted in a drying trend of the regional soil moisture content in the humid karst areas. The results suggest that it is necessary to consider reasonable vegetation planting density and suitable revegetation types to balance the relationship between vegetation water consumption and soil moisture supplementation in vegetation restoration practice in the humid karst areas.

For different vegetation types, soil moisture content shows varying characteristics in different seasons and under different precipitation conditions. However, these characteristics have not been extensively analyzed in karst regions of southwest China. In this study, the soil moisture content of four plots of bare land, grassland, shrubland, and forestland was monitored, and the soil moisture content and corresponding meteorological data for each plot were analyzed. The results indicate that the average soil moisture content in grassland was the highest with weak temporal variation and that in bare, shrub, and forest lands soil moisture content was low with moderate temporal variation. The average soil moisture content in bare, grass, and forest lands was higher in the rainy season than in the dry season, whereas in shrubland, the soil moisture content was higher in the dry season than in the rainy season. Increase in soil moisture content during each precipitation event correlated with the rainfall amount. With increasing rainfall amount, soil moisture content in forest and shrub lands increased more than in bare and grass lands. The peak soil moisture time in each vegetation type plot varied and the peak soil moisture time was related to soil moisture content before a rainfall event. Temperature showed a strong negative correlation with soil moisture content for all vegetation cover types in both the dry and rainy season. Wind speed also showed a strong negative correlation with soil moisture content for all vegetation types during the dry season. Relative humidity had a strong positive correlation with soil moisture content in bare, shrub, and forest lands during the dry season as well as in the four vegetation types during the rainy season. These results demonstrate the variations in soil water characteristics across different vegetation types in karst regions of southwest China.

The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Run (IMERGF) product has now been upgraded to Version 4 (V4), which has been available since March 2017. Therefore, it is desirable to evaluate the characteristic differences between the V4 and the previous V3 products. A comprehensive performance evaluation of the errors of the successive V3 and V4 IMERGF products is performed with a comparison of the China daily Precipitation Analysis Products (CPAP) from March 2014 to February 2015. The version 6 Global Satellite Mapping of Precipitation (GSMaP) research product (which is another Global Precipitation Measurement (GPM) based precipitation product) is also used as a comparison in this study. Overall, the IMERGF-V4 product does not exhibit the anticipated improvement for China compared to the IMERGF-V3 product. An analysis of the metrics of annual daily average precipitation over China for the IMERGF-V3 and IMERGF-V4 products indicates a decrease of the relative bias (RB) from 3.70% to −7.18%, a decrease of the correlation coefficient (CC) from 0.91 to 0.89, an increase of the fractional standard error (FSE) from 0.49 to 0.56, and an increase of the root-mean-square error (RMSE) from 0.63 mm to 0.72 mm. Compared to the IMERGF-V3 product, the IMERGF-V4 product exhibits a significant underestimation of precipitation in the Qinghai-Tibetan plateau with a much lower RB of −60.91% (−58.19%, −65.30%, and −63.74%) based on the annual (summer, autumn, and winter) daily average precipitation and an even worse performance during winter (−72.33% of RB). In comparison, the GSMaP product outperforms the IMERGF-V3 and IMERGF-V4 products and has the smallest RMSE (0.47 mm/day), highest CC (0.95), lowest FSE (0.37), and best performance of the RB (−2.39%) in terms of annual daily precipitation over China. However, the GSMaP product underestimates the precipitation more than the IMERGF-V3 product for the arid XJ region.