The Huai River Basin (HRB) is an important grain and industrial production area in eastern China with frequent droughts. Under the background of current climate change, the hydrological and meteorological characteristics of the basin may be changed, which may lead to the changes of regional drought characteristics. It should be paid more attention on the drought research under climate change and the difference between different drought indices. Coupled Model Intercomparison Project phase 5 (CMIP5) as an important tool for climate change research has been used in the study and the study chosen three global circulation models (GCMs)—such as CNRM-CM5 (CNR), HadGEM2-ES (Had), and MIROC5 (MIR)—to gather an ensemble model (EnM) for providing the future climate information. The Standardized Precipitation Index (SPI) and Humidity Index (HI) were used to evaluate and compare the drought situations in the past and the future periods with two representative concentration path scenarios (RCP4.5 & RCP8.5). Some sequence statistics methods, such as Mann–Kendall test and run theory, were carried out to analyze the trend and the changes of extreme drought frequency and characteristics values. The research showed that the simulation accuracy of the EnM would better. SPI and HI take different factors into count and thus lead to differences in describing drought trend, extreme drought frequency, and characteristic values, such as drought severity, drought duration, mean drought severity, and max drought intensity. The research showed that both SPI and HI showed the same wetting or drying trend in the same timescales (except winter) as in the historical data. However, the future annual and seasonal drought trend reflected by SPI shows a wetting trend while HI shows a drying trend. Both in the past and the future, extreme drought frequency and characteristic values reflected by HI are higher than SPI. The drought trend is greater, and the extreme drought frequency and characteristics tend to be strengthened under RCP8.5. Low precipitation and high potential evapotranspiration (PET), especially the PET caused by temperature rise, are the main influencing factors of drought in the future. Therefore, the influence of the PET should not be ignored in drought analysis and we should strengthen the comparative study of different drought indices in future drought analysis under climate change.

Huai River Basin (HRB) is an important food and industrial production area and a frequently drought-affected basin in eastern China. It is necessary to consider the future drought development for reducing the impact of drought disasters. Three global circulation models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5), such as CNRM-CM5 (CNR), HadGEM2-ES (Had) and MIROC5 (MIR), were used to assessment the future drought conditions under two Representative Concentration Pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. The standardized precipitation evapotranspiration index (SPEI), statistical method, Mann-Kendall test, and run theory were carried out to study the variations of drought tendency, frequency, and characteristics and their responses to climate change. The research showed that the three CMIP5 models differ in describing the future seasonal and annual variations of precipitation and temperature in the basin and thus lead to the differences in describing drought trends, frequency, and drought characteristics, such as drought severity, drought duration, and drought intensity. However, the drought trend, frequency, and characteristics in the future are more serious than the history. The drought frequency and characteristics tend to be strengthened under the scenario of high concentration of RCP8.5, and the drought trend is larger than that of low concentration of RCP4.5. The lower precipitation and the higher temperature are the main factors affecting the occurrence of drought. All three CMIP5 models show that precipitation would increase in the future, but it could not offset the evapotranspiration loss caused by significant temperature rise. The serious risk of drought in the future is still higher. Considering the uncertainty of climate models for simulation and prediction, attention should be paid to distinguish the effects of different models in the future drought assessment.

This study used the “Daily meteorological dataset of basic meteorological elements of China National Surface Weather Station (V3.0)” and applied the absolute threshold method and standardized precipitation evapotranspiration index to identify heatwave events and drought events. This study analyzed the spatiotemporal evolution patterns of three types of summer disaster events, namely, heatwave events, drought events, and compound drought and heatwave events, in Jiangsu Province from 1960 to 2018. Additionally, it investigated and verified the concurrent historical data of the identified years with the most severe occurrence of compound drought and heatwave events and calculated the monthly drought centers and summer accumulations of the standardized precipitation evapotranspiration index (SPEI-3). The results indicate that over the 59 years analyzed, the number of days with a threshold of 35 °C, which were considered hot days, was 503.2, accounting for 9.27% of the total summer days in Jiangsu Province. Both the number of hot days and the frequency of heatwave events showed a clear increasing trend from the northeastern coastal areas to the southwestern regions of Jiangsu Province. The total frequency of drought events at different stations in Jiangsu Province from 1960 to 2018 fell within the range of 50–64. The fitted slope of the frequency of compound drought and heatwave events in Jiangsu Province was −0.021 for the period 1960 to 1989, and 0.079 for the period 1990 to 2018, indicating a higher frequency compared with the preceding 30 years. This trend aligned with the rise in heatwave events experienced in Jiangsu Province in recent years. The frequency and duration of compound drought and heatwave events in Jiangsu Province exhibited an increasing spatial pattern from the southwestern parts to the northeastern parts. This study’s verification established that the identification of compound drought and heatwave events was relatively accurate.

The temperature sensitivity ( Q ₁₀ ) of soil respiration ( Rs ) is one of the major determinants of carbon emissions from Rs . Identifying the controlling factors of Q ₁₀ can contribute to quantifying the response of Rs to climate change and assessing potential carbon emission risks. The Tibetan Plateau (TP), known as the Earth's third pole, plays a pivotal role in the global climate and carbon cycle system. However, the controlling factors of Q ₁₀ and its responses to future climate change in this region are not well understood. Here, we introduce a method for calculating Q ₁₀ from cumulative carbon emission data on Rs , which allows substantially expanding the available data set. Building on this, we integrate various statistical analyses with explainable machine learning techniques to examine the controlling factors regulating Q ₁₀ on the TP. Our analyses consistently show that precipitation and soil potential of Hydrogen are the two most important factors regulating Q ₁₀ . Precipitation is the dominant factor regulating Q ₁₀ across nearly 70% of the plateau, while pH's dominance is about 30%, highlighting the primary role of precipitation as a regulator of Q ₁₀ on the TP. Future precipitation increases (wetting) on the TP are predicted to markedly boost the warming‐induced increase in Rs , with this effect being particularly pronounced in arid areas. Our findings clearly demonstrate that under future warming and wetting on the TP, the compound effects of precipitation and temperature would enhance Rs , consequently accelerating the soil organic carbon release.