At present, high-resolution drought indices are scarce, and this problem has restricted the development of refined drought analysis to some extent. This study explored the possibility of calculating the standardized precipitation index (SPI) with short-term precipitation sequences in China, based on data from 2416 precipitation observation stations covering the time period from 1961 to 2019. The result shows that it is feasible for short-sequence stations to calculate SPI index, based on the spatial interpolation of the precipitation distribution parameters of the long-sequence station. Error analysis denoted that the SPI error was small in east China and large in west China, and the SPI was more accurate when the observation stations were denser. The SPI error of short-sequence sites was mostly less than 0.2 in most areas of eastern China and the consistency rate for the drought categories was larger than 80%, which was lower than the error using the 30-year precipitation samples. Further analysis showed that the estimation error of the distribution parameters $\beta$ and $q$ was the most important cause of SPI error. Two drought monitoring examples show that the SPI of more than 50,000 short-sequence sites can correctly express the spatial distribution of dry and wet and have refined spatial structure characteristics.

In this study, the standardized precipitation index (SPI) data in Hunan Province from 1961 to 2020 is adopted. Based on the critical slowing down theory, the moving t-test is firstly used to determine the time of drought-flood state transition in the Dongting Lake basin. Afterwards, by means of the variance and autocorrelation coefficient that characterize the phenomenon of critical slowing down, the early-warning signals indicating the drought-flood state in the Dongting Lake basin are explored. The results show that an obvious drought-to-flood (flood-to-drought) event occurred around 1993 (2003) in the Dongting Lake basin in recent 60 years. The critical slowing down phenomena of the increases in the variance and autocorrelation coefficient, which are detected 5–10 years in advance, can be considered as early-warning signals indicating the drought-flood state transition. Through the studies on the drought-flood state and related early-warning signals for the Dongting Lake basin, the reliabilities of the variance and autocorrelation coefficient-based early-warning signals for abrupt changes are demonstrated. It is expected that the wide application of this method could provide important scientific and technological support for disaster prevention and mitigation in the Dongting Lake basin, and even in the middle and lower reaches of the Yangtze River.

Estimating the probability and consequences of drought disasters is an important task in drought risk assessment, which contributes to the development of mitigation strategies. Based on rainfall data from 2481 stations and the drought-affected arable land of each province from 1961 to 2021, a probabilistic analysis model of drought duration, drought severity and the proportion of affected farmland area (PAFA) was constructed by a three-dimensional copula function. The results show that the distribution functions of drought duration, drought severity and the PAFA are well given based on the principle of maximum entropy and can pass the Kolmogorov–Smirnov (K-S) distribution test with a significance level of 0.05. Among the three Archimedean copulas, Frank’s method has a relatively better accuracy, suggesting that it captures the dependencies between drought characteristics better and is more suitable for constructing joint distribution functions. The value of PAFA in Gansu, Inner Mongolia, Shanxi and Liaoning is about 0.3, which is higher than other provinces. Drought duration and drought severity levels of 3 to 4 are the main causes of a PAFA greater than 0.3, which can be used as an early warning line for drought risk. At the same level of PAFA, the drought in the southern region lasted longer and was more intense.

In recent years, the dry-wet transition (DWT), which often leads to regional floods and droughts, has become increasingly frequent in the Poyang Lake basin and the Dongting Lake basin (hereinafter referred to as the two-lake region). This study aims to investigate the early warning signals (EWSs) for DWT events. Firstly, based on the standardized precipitation index (SPI) at 161 meteorological stations in the two-lake region from 1961 to 2020, the two-lake region is divided into four sub-regions by the Rotational Empirical Orthogonal Function (REOF) analysis method. Then, the occurrence time of the DWT events in each sub-region is determined by the moving t-test (MTT) technique. Finally, by using two indicators (variance and the auto-correlation coefficient) to describe the critical slowing down (CSD) phenomenon, the EWSs denoting the DWT events in all sub-regions are investigated. The results reveal that there was a significant dry-to-wet (wet-to-dry) event around 1993 (2003) in the two-lake region during the last 60 years. The phenomenon of CSD, where the auto-correlation coefficient and variance increases are found in all sub-regions around 10 years before the DWT, suggests that it can be taken as an EWS for the DWT events. This study confirms the effectiveness of applying the slowing down theory in investigating the EWSs for abrupt changes in the two-lake region, aiming to provide a theoretical basis for effective prevention and mitigation against disasters in this region. Moreover, it is expected to be well-applied to the middle and lower reaches of the Yangtze River.

This study aims to quantify the relationship between the duration and occurrence frequency of droughts in China, particularly focusing on different drought intensities. By analyzing daily meteorological drought composite index (MCI) data from 1897 meteorological stations across China spanning from 1961 to 2020, the study reveals a significant double-logarithmic relationship between drought duration and occurrence frequency. The results show that shorter drought durations are associated with higher occurrence frequencies, while longer durations correspond to lower frequencies. This relationship is characterized by one parameter (k or b), which can independently describe the nonlinear association between drought duration and frequency. Spatially, the values of the parameter exhibit a gradient from northwest to southeast, with higher values in arid and semi-arid regions and lower values in humid and semi-humid regions. Notably, the parameter k aligns well with precipitation isolines, effectively distinguishing arid, semi-arid, and humid regions. Additionally, droughts in arid and semi-arid regions tend to last longer (often exceeding 60 days), while those in humid and semi-humid regions are shorter but more frequent. These findings provide critical insights for optimizing water resource management, agricultural planning, and disaster mitigation strategies, enhancing societal resilience to drought impacts.

This study aims to quantify the relationship between the duration and occurrence frequency of droughts in China, particularly focusing on different drought intensities. By analyzing daily meteorological drought composite index (MCI) data from 1897 meteorological stations across China spanning from 1961 to 2020, the study reveals a significant double-logarithmic relationship between drought duration and occurrence frequency. The results show that shorter drought durations are associated with higher occurrence frequencies, while longer durations correspond to lower frequencies. This relationship is characterized by one parameter (k or b), which can independently describe the nonlinear association between drought duration and frequency. Spatially, the values of the parameter exhibit a gradient from northwest to southeast, with higher values in arid and semi-arid regions and lower values in humid and semi-humid regions. Notably, the parameter k aligns well with precipitation isolines, effectively distinguishing arid, semi-arid, and humid regions. Additionally, droughts in arid and semi-arid regions tend to last longer (often exceeding 60 days), while those in humid and semi-humid regions are shorter but more frequent. These findings provide critical insights for optimizing water resource management, agricultural planning, and disaster mitigation strategies, enhancing societal resilience to drought impacts.