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【Objective】 Drought is the most important abiotic stress affecting crop production in North China. Understanding its characteristics is essential to agricultural management. This paper is to investigate the spatiotemporal variation in drought from 1982 to 2020 and its underlying determinants in Inner Mongolia. 【Method】 The vegetation health index (VHI) measured from 1982 to 2020 was used to analyze the temporal and spatial characteristics of the drought. The cross-wavelet method was used to elucidate the effects of El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO), and sunspots on the drought. 【Result】 Drought in the studied region varied intra-annually, with the most severe droughts occurring in the summer. The main drought period is 8 years and 12 years. The central-northern region in Inner Mongolia experienced more severe droughts than other regions. Drought was more severe in the middle and northeast, while the south had seen a relief in drought. The region had witnessed a total eleven droughts in the studied period, with the most severe droughts occurring from October 1989 to March 1990. The worst and least severe droughts were in the 1980s and 2010s, respectively. Atmospheric circulation and sunspots correlated with the drought, with ENSO having the greatest influence and sunspots having the least impact on drought. 【Conclusion】 From 1982 to 2020, drought in Inner Mongolia had been worsening. ENSO influences drought most. These findings improve our understanding of the reasons behind the droughts and can help improve effective drought management in Inner Mongolia.

【Objective】 Drought is an abiotic stress affecting agricultural production in almost every country across the world. Understanding its spatiotemporal variation is essential to improving water management under climate change. The purpose of this paper to analyze the variation in droughts in the main catchments over the past 60 years (1960—2019) across China. 【Method】 The standardized precipitation evapotranspiration index (SPEI) was used as the drought index; the extreme-point symmetric mode decomposition (ESMD) method was used to decompose the periods and trend of the SPEI time series, from which we calculated the spatiotemporal variation in drought. 【Result】 ①The temporal changes in drought varied with sub-basins from 1960 to 2019, and the most noticeable drought increase occurred in the continental river basins, with the SPEI linear tendency rate being -0.192/10 a. ②The ESMD results showed that the drought had been in increase across China, with the first and second periodic cycles being 2.07 years and 5 years respectively. ③The average occurring frequency of mild drought, moderate drought, severe drought, extreme drought and drought was 13.5%, 10.4%, 5.5%, 2.3% and 31.8%, with their associated average intensity being 0.74, 1.23, 1.67, 1.86 and 1.18, respectively. ④ENSO was closely related to drought, while NAO did not show significant impact on drought. 【Conclusion】 Except for southeastern China, basins in other regions have seen an increase in droughts over the past 60 years.

The spatiotemporal continuity characteristics of drought are the basis for analyzing its spatial migration and evolution, which is significant for mitigation and early warning of drought. The aim of this paper is to identify meteorological and vegetation drought events in China from 1982 to 2022, reveal the dynamic changes of typical drought events, and elucidate the propagation characteristics of meteorological and vegetation drought. The results showed that (1) based on a three-dimensional spatiotemporal clustering algorithm, China experienced 138 meteorological drought events and 76 vegetation drought events; (2) the severity of the meteorological drought event No. M138 (2022.03–2022.11) reached 667.58 × 104 km2·month, and the severity of the vegetation drought event No. V68 (2019.06–2020.04) reached 572.89 × 104 km2·month; (3) a total of 40 meteorological-vegetation drought event pairs had been identified, which was divided into three main types: "single", "simple", and "complexity"; and (4) in the typical drought event pair No. P-34, the area difference was 16.45 × 104 km2, and the severity difference was 3.89 × 104 km2. The research results can provide a new perspective for identifying the dynamic changes and propagation characteristics of drought events from a three-dimensional perspective, which is of great significance for predicting vegetation drought and protecting the ecological environment. [ABSTRACT FROM AUTHOR]

During the dry season, river flow gradually diminishes, and surface water flow dries up. Therefore, the investigation of runoff during the dry season is of great practical significance for rational water allocation and water resource management. Based on hydrological station data from the Xijiang River Basin (XRB) from 1961 to 2020, this study examines the trend and periodic characteristics of dry-season runoff, identifies fluctuation and variability in dry-season runoff, and investigates the main circulation factor combinations influencing dynamic changes in dry-season runoff. The results indicate the following: (1) the characteristics of dry-season runoff variations are basically consistent across sub-basins in the XRB during the study period, with the minimum (21.96 × 108 m3) and maximum (54.67 × 108 m3) average monthly runoff occurring in February and October, respectively; (2) interannual-scale dry-season runoff exhibits periodicity of 3.53 years and 7.5 years; (3) using the Bayesian estimator of abrupt seasonal and trend change algorithm (BEAST), a seasonal abrupt point with a probability of 20.5% occurs in 1983, and the confidence interval for this abrupt point is from 1980 to 1986; (4) based on the cross wavelet approach, solar sunspots are identified as the primary circulation factor contributing to dry-season runoff in the XRB, exhibiting a significant 8–14 years resonance cycle of negative correlation with runoff during the high-energy phase from 1972 to 2006. These findings offer a new perspective on understanding the evolution of dry-season runoff and circulation factor variations, which are crucial for accurate prediction, early warning, and rational allocation of water resources during the dry season. [ABSTRACT FROM AUTHOR]

Drought is a complex and recurrent natural disaster that can have devastating impacts on economies, societies, and ecosystems around the world. In light of climate change, the frequency, duration, and severity of drought events worldwide have increased, and extreme drought events have caused more severe and irreversible damage to terrestrial ecosystems. Therefore, estimating the resilience of different vegetation to drought events and vegetation's response to damage is crucial to ensuring ecological security and guiding ecological restoration. Based on meteorological and remote-sensing datasets from 1982 to 2022, the spatial distribution characteristics and temporal variability of vegetation were identified in the Yellow River Basin (YRB), the dynamic changes and recurrence periods of typical drought events were clarified, and the driving effects of different drought types on vegetation were revealed. The results indicated that (1) during the research period, the standardized vegetation water-deficit index (SVWI) showed a downward trend in the YRB, with a 99.52% probability of abrupt seasonal changes in the SVWI occurring in January 2003; (2) the characteristic values of the grid trend Zs were −1.46 and 0.20 in winter and summer, respectively, indicating a significant downward trend in the winter SVWI; (3) the drought with the highest severity (6.48) occurred from September 1998 to February 1999, with a recurrence period of 8.54 years; and (4) the growth of vegetation was closely related to drought, and as the duration of drought increased, the sensitivity of vegetation to drought events gradually weakened. The research results provide a new perspective for identifying vegetation's dynamic changes and responses to drought, which is of great significance in revealing the adaptability and potential influencing factors of vegetation in relation to climate. [ABSTRACT FROM AUTHOR]

The dynamic variations of agricultural drought can reflect the water shortage situation of the agricultural system, and there is a progressive relationship in the response of agricultural drought to meteorological drought on a spatiotemporal scale. In this study, the vegetation health index and the standardized precipitation evapotranspiration index were adopted as agricultural and meteorological drought indicators, respectively. Additionally, using the three‐dimensional spatiotemporal clustering technology, the dynamic evolutions of typical drought events were clarified, and the spatiotemporal response characteristics of agricultural drought to meteorological drought were revealed. The results indicated that: (a) there were 81 agricultural drought events in the North China Plain (NCP) during 1982–2020, with a largest drought severity (12.82 × 104 month km2), a 6‐month duration, and a 23.24 × 104 km2 affected area occurring in the No. 4 event; (b) from the 1980s to the 2010s, the agricultural drought gradually decreased and large‐scale droughts mainly concentrated in the border areas of Hebei, Shandong, and Henan; and (c) a total of 13 drought event pairs were successfully matched in the NCP, including 7 pairs of "one‐to‐one," 4 pairs of "one‐to‐many," 1 pair of "many‐to‐one," and 1 pair of "many‐to‐many." The spatiotemporal responses of agricultural drought were elucidated in a three‐dimensional perspective, which can propose a new approach for establishing drought propagation model, predicting future agricultural drought conditions, improving ecological environment quality, and can also be applied for the investigation of other drought types. Plain Language Summary: There is a certain delay effect and time lag between agricultural drought and meteorological drought, thus, it is crucial to investigate the dynamic variation of agricultural drought and its response to meteorological drought to understand the impact of climate change on vegetation, which has important scientific significance and application value for improving ecological environment quality and restoring ecosystem functions. However, the dynamic variation of agricultural drought and its response to meteorological drought are still unclear from a three‐dimensional perspective. Based on the Center for Satellite Applications and Research and Famine Early Warning Systems Network Land Data Assimilation System data set, the vegetation health index and the standardized precipitation evapotranspiration index were adopted as agricultural and meteorological drought indicators, respectively. Additionally, using the three‐dimensional spatiotemporal clustering technology, the temporal variations and spatial patterns of drought were explored, the dynamic evolutions of typical drought events were clarified, and the spatiotemporal response characteristics of agricultural drought to meteorological drought were revealed from a three‐dimensional perspective. This study sheds new viewpoints into the identification of agricultural drought variation and its relationships with meteorological drought, which can also be applied in other areas. Key Points: There were 81 agricultural drought events in the North China Plain during 1982–2020The drought gradually decreased from the 1980s to the 2010sA total of 13 drought event pairs were successfully matched [ABSTRACT FROM AUTHOR]

Investigating the influence of human activities and climate change on streamflow and sediment load is of great significance for understanding the hydrological cycle, addressing climate change, and ensuring sustainable water resource management. Based on observed data of precipitation, streamflow, and sediment load from 1990 to 2021 in the Xiliugou Basin, trend and abrupt change analyses of streamflow and sediment load were conducted using the coefficient of variation and Bayesian change point detection method. The effects of climate change and human activities on streamflow and sediment load were further examined through the double mass curve method, with a focus on the impact of land use changes on streamflow and sediment load dynamics. The results indicated that: (1) During the study period, there was a consistent decreasing trend in streamflow, sediment load, and precipitation, with respective rates of −77.76 × 104 m3/year, −55.97 × 104 Mt/year, and −0.84 mm/year. The distribution of annual streamflow and sediment load in the basin was uneven, with 61.05% of precipitation occurring during the wet season and the peak sediment discharge month being July, accounting for 58.90% of the total annual sediment load. (2) The variations in streamflow and sediment load in the Xiliugou Basin exhibited distinct stage characteristics, with abrupt changes occurring around 1997. Both streamflow and sediment load showed significant fluctuations from the reference period to the changing period, decreasing by 45.54% and 82.85%, respectively. (3) A positive correlation between precipitation and streamflow was observed in the Xiliugou Basin, with correlation coefficients (R) of 0.62 and 0.49, indicating a stimulating effect of precipitation on streamflow and sediment load. Human activities significantly reduced sediment load in the Xiliugou Basin from 1998 to 2021, contributing to a reduction of 115.08%. (4) An increase in cropland, water, and barren areas would lead to higher streamflow and sediment load, while an increase in grassland, forest, and impervious areas would decrease both streamflow and sediment load. [ABSTRACT FROM AUTHOR]

Drought refers to a meteorological disaster that results in insufficient soil moisture due to a long-term lack of rainfall and disrupts the moisture balance of crops. Yinshanbeilu in Inner Mongolia is an arid and semi-arid region, and the onset of drought and its subsequent transmission is a key challenge in water resource management. This study takes Yinshanbeilu as the study area, analyses the changing characteristics of multi-timescale drought from 1971 to 2020 based on the Standardised Precipitation Index (SPI), and analyses the stochasticity and stability of the drought by using a cloud model. Finally, the cross-wavelet transform method and Pearson's test are used to explore the correlation between atmospheric circulation factors, PRE and PET, and drought. The results indicate that (1) on the annual scale, the frequency of drought in Yinshanbeilu mainly ranges from 22% to 28%, with a high frequency of light droughts, a low frequency of severe droughts, a high frequency of droughts in the east and west, and a low frequency of droughts in the north and south; on the seasonal scale, the frequency of droughts in winter is the highest, with a rate of 34.6%, and the lowest frequency of droughts is in autumn, with a rate of 28.3%. (2) There is a decreasing trend in Entropy (En) and Hyper-Entropy (He), and an increasing trend in Expectation (Ex) for the inter-annual SPI-12 cloud model. Spatially, Ex and He are negatively correlated, while En and He are positively correlated. The inter-annual variation in cloud eigenvalues is greater than the inter-site variation, so the cloud model better reflects the spatial stochasticity and stability of regional inter-annual SPI. For the seasonal-scale SPI-3 cloud model, Ex is smaller in all seasons, En is also smaller, and He is larger. (3) Sunspot, PRE (precipitation), and PET (Potential Evapotranspiration) are all positively correlated with SPI and have the highest correlation. This study reveals the characteristics and causes of variations of drought in Yinshanbeilu, which can be applied to future research areas related to regional drought risk management. [ABSTRACT FROM AUTHOR]

The growing concern surrounding climate change has gradually drawn attention to the influence of climate factors on drought occurrence. In order to effectively prevent the occurrence of drought and reasonably utilize water resources, the vegetation health index (VHI) was used to characterize drought in North China Plain (NCP) in this study. Furthermore, six climate factors: air temperature (AT), precipitation (P), evapotranspiration (ET), specific humidity (SH), soil moisture (SM), and soil temperature (ST) were selected. The pole symmetric mode decomposition (PSMD) and improved gridded trend test (IGT) were used to analyze the spatial–temporal characteristics of drought and climate factors in NCP from 1982 to 2020. By calculating the cumulative climatic factors of 0 months, 1 month, 2 months, and 3 months, the correlation between drought and the climatic factors with different cumulative scales was analyzed. The results showed that: (1) from 1982 to 2020, the drought in NCP showed a downward trend and the climate factors showed an upward trend; (2) with the increase in AT, P, ET, SH, SM, and ST, VHI showed an upward trend, and SM showed the strongest correlation with VHI; (3) the optimal cumulative lag time (CLT) for AT, P, ET, SH, SM, and ST were 1.67 months, 1.48 months, 1.95 months, 1.69 months, 0.89 months, and 1.81 months, respectively; and (4) AT was the main driving factor of drought in NCP. This study contributes to the early warning and prediction of drought events, providing a scientific basis for water management authorities in drought management and decision making, and mitigating the negative impacts of drought on socio-economic aspects. [ABSTRACT FROM AUTHOR]