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Droughts, depending on their nature, have had devastating consequences, including crop destruction, famine and millions of deaths, particularly in countries like India that heavily rely on rainfall for agriculture. The present study aims to quantify the linkage between meteorological, agricultural and hydrological drought at a high spatial resolution across India. These connections were established by developing various drought propagation metrics followed by subsequent correlation analysis, lag analysis and clustering. Standard Precipitation Index (SPI), Deviation in NDVI (Dev‐NDVI) and GRACE Drought Severity Index (GRACE‐DSI) were used to represent meteorological, agricultural and hydrological droughts. Run theory with thresholds of −1, −0.5 and −0.05 were used to delineate the drought events for meteorological, hydrological and agricultural droughts, respectively. Furthermore, multivariate K‐means clustering based on factors such as drought duration, latitude, longitude, severity, propagation and recovery speeds was done to create spatial clusters having similar drought characteristics. Correlation analysis showed the highest average correlations at a lag of around 7–8 months between meteorological and hydrological drought, a lag of 1–2 months in case of meteorological and agricultural drought and a lag of 3–4 months between agricultural and hydrological drought. The analysis of drought duration indicated that, on average, meteorological drought in India lasted for 2.34 months, while agricultural drought lasted for 3 months, reflecting a 26.5% increase, whereas hydrological drought lasted for 5.22 months, indicating a notable 123% increase. This increase in average drought duration as it propagates from meteorological to agricultural to hydrological drought can be attributed to the lengthening property of drought propagation. Clustering analysis reveals presence of five homogeneous drought clusters. Additionally, cluster analysis reveals that for meteorological and agricultural droughts arid regions showed the highest severity whereas for hydrological droughts north Indian states including Punjab and Haryana showed the highest severity. [ABSTRACT FROM AUTHOR]

Recent climate change has accelerated the global hydrological cycle, substantially affecting drought metrics such as drought duration and drought propagation; however, knowledge of drought patterns in these metrics remains limited. Here, we aimed to address the evolution and influencing factors of major drought metrics under past and future climate scenarios within the Yellow River Basin (YRB) based on Coupled Model Intercomparison Project Phase 6 (CMIP6). Accordingly, we investigated the changes in drought duration for meteorological drought and agricultural drought across the YRB and identified the variability in drought propagation time from meteorological drought to agricultural drought by using a standardized precipitation/soil moisture index and run theory. Meteorological and agricultural drought duration, and propagation time, increased from 1850 to 2014, decreased significantly from 2015 to 2100 with change trends of −0.0027, −0.0197, and −0.002 month/year, respectively. Drought duration had a negative sensitivity to humidification, and agricultural drought was more sensitive than meteorological drought. Propagation time exhibited a greater sensitivity to meteorological humidification than agricultural humidification. The results also suggest that precipitation, evapotranspiration, and soil moisture are the main drivers of drought metric changes, with air temperature and crop cover exhibiting a strong indirect effect on drought metrics in the YRB. Decreased propagation time from meteorological to agricultural drought and decreased duration provide evidence for the accelerated occurrence and increased impact of drought, highlighting the importance of a more comprehensive understanding of drought metric changes under rapid climate change. [ABSTRACT FROM AUTHOR]

Persistent droughts pose a threat to agricultural production, and the changing environment worsens the risk of drought exposure. Understanding the propagation of drought in changing environments and assessing possible impact factors can help in the early detection of drought, guiding agricultural production practices. The current study cannot reflect the propagation status of drought to the total terrestrial hydrological drought, so this work creatively investigated the atmospheric to hydrological drought propagation time in the Yangtze River Basin under the dynamic and static perspectives based on the Standardized Precipitation Evapotranspiration Index and the Terrestrial Water Storage Anomalous Drought Index, fine-tuned the time scale to the seasonal scale, and explored the contributing capacity of the variable interactions. The results show that: (1) under the dynamic perspective, while the propagation time is decreasing in the annual scale, the spring season shows the opposite trend; and (2) large variability exists in the timing of drought propagation at spatial scales, with elevation playing the most important influential role, and bivariate interactions contributing stronger explanations compared to single variables. This study highlights the importance of considering the impact of variable interactions and contributes to our understanding of the response of secondary droughts to upper-level droughts, providing valuable insights into the propagation of droughts to total terrestrial hydrologic drought. [ABSTRACT FROM AUTHOR]

The GRACE satellite mission provides a new approach for monitoring, tracking, and assessing drought conditions by detecting changes in Earth's gravitational fields and inversing signals of terrestrial water storage anomalies. Existing studies of terrestrial water storage anomalies related droughts paid rare attention to the behind atmospheric physical mechanisms, nor quantified the risk propagation patterns between terrestrial water storage deficits and hydrological or agricultural droughts. In this study, we first extract terrestrial water storage (TWS) droughts, hydrological droughts, and agricultural droughts by using multiple variables including TWS from the GRACE/GRACE-FO satellites, runoff and soil moisture from the ERA5-Land reanalysis dataset. We then identify key atmospheric and oceanic oscillation indices affecting water deficits by employing machine learning technologies. We characterize the joint distributions between drought duration and severity by using the Copula function and quantify the risk propagation of hydrological and agricultural droughts to TWS droughts. The results show that: (1) From 2002 to 2021, there is a significant decrasing trend of TWS in China; the WPIO group atmospheric circulation indices (sea surface temperature index within the Western Pacific and Indian Ocean) contributes the most to TWS. Specifically, the sea surface temperature anomalies within the NINO 3.4 region as well as the Western Pacific Warm Pool area index show significantly positive correlation relationships with TWS in southern China; (2) The northwestern China, the Yangtze River basin, and the downstream of the Pearl River basin are the hotspots of TWS droughts. Besides, the hotspots of hydrological droughts locate in northwestern China and the hotspots of agricultural droughts locate in South China and eastern Tibetan Plateau; (3) The elastic coefficients of hydrological droughts propagating to TWS droughts are higher than those of agricultural droughts, indicating that the TWS droughts are more sensitive to hydrological droughts than to agricultural droughts. [ABSTRACT FROM AUTHOR]

This study employs an event‐based approach to analyse drought propagation from meteorological to hydrological drought via agricultural drought in the semi‐arid Krishna River basin of India. The Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI) and Standardized Streamflow Index (SSI) representing meteorological, agricultural and hydrological drought, respectively, were estimated. Two different cases of drought propagation are analysed: meteorological‐to‐agricultural (SPEI‐to‐SSMI) and agricultural‐to‐hydrological (SSMI‐to‐SSI). The drought propagation is analysed using three‐time matrices, namely the time difference between initiation (∆ti2i$$ \Delta {t}_{i2i} $$), peak (∆tp2p$$ \Delta {t}_{p2p} $$) and termination (∆tt2t$$ \Delta {t}_{t2t} $$) at multiple timescales of 1, 3, 6, 9 and 12 months using different drought threshold values 0, −0.5, −1 and − 1.5, respectively, to delineate shifts from mild to extreme drought conditions in detail. The results indicate that the propagation time from SPEI‐to‐SSMI drought decreased for most of the tributaries using multiple timescales at different threshold values, whereas it increased significantly for SSMI‐to‐SSI drought. The drought propagation changes with respect to time as well as magnitude (intensity and severity). The propagation factor (PF), defined as the ratio of the average value of succeeding drought to preceding drought characteristics, has also been studied. For SPEI‐to‐SSMI drought, the duration PF shrinks across all tributaries using multiple timescales at different threshold values, whereas it expands for SSMI‐to‐SSI drought. On the other hand, the severity and intensity PF magnify for SPEI‐to‐SSMI drought, whereas it experiences dampening effects for SSMI‐to‐SSI drought. Thus, the proposed study provides valuable insights into drought propagation dynamics, aiding in managing and mitigating droughts in the semi‐arid river basin and elsewhere. [ABSTRACT FROM AUTHOR]

Understanding the transition from meteorological to hydrological drought is essential for accurately predicting hydrological droughts. However, the factors driving this transition are intricate, and a comprehensive understanding of how direct human activities influence this shift in drought is lacking. In this study, we initially explored the spatiotemporal correlation between the occurrence of meteorological and hydrological droughts. Subsequently, we formulated multiple hydrological replenishment scenarios using the soil and water assessment tool (SWAT) model to assess the environmental impact of the transition from meteorological to hydrological droughts. The Xijiang River Basin (XRB), the primary tributary of the Pearl River basin, was selected as the study area. Our results identified 91 meteorological droughts in the XRB, and only 66 hydrological droughts from 1978 to 2018. The transition rate from meteorological to hydrological drought demonstrated large spatial variability, with a basin‐average rate of 56% and the lowest transition rate of 45% in the headstream The transition from meteorological to hydrological drought was mostly rapid between November and December (~2 months), but can be prolonged during spring (about 3–5 months) and winter (around 7–9 months). Additionally, analysis of regeneration scenarios indicated that human activity has mitigated drought severity over recent decades. The primary driver affecting drought duration and frequency during the transition from meteorological to hydrological droughts shows conspicuous spatial disparities in densely populated areas. Although human activity significantly contributes to drought duration and severity compared to climate change during the transition in the headstream, its effects are more pronounced downstream in terms of drought duration and frequency. One plausible explanation is that increased water consumption downstream has considerably prolonged drought progression, whereas water management has counteractive effects on drought progression due to climate change in the headstream. Our findings offer valuable insights into the transition process from meteorological to hydrological droughts in the presence of extensive human activities. [ABSTRACT FROM AUTHOR]

Understanding the propagation characteristics and driving factors from meteorological drought to hydrological drought is essential for alleviating drought and for early warning systems regarding drought. This study focused on the Weihe River basin (WRB) and its two subregions (the Jinghe River (JRB) and the middle reaches of the Weihe River (MWRB)), utilizing the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) to characterize meteorological and hydrological drought, respectively. Based on Copula theory and conditional probability, a quantification model for the propagation time (PT) of meteorological–hydrological drought was constructed. The dynamic characteristics of PT on annual and seasonal scales were explored. Additionally, the influences of different seasonal meteorological factors and underlying surface factors on the dynamic changes in PT were analyzed. The main conclusions were as follows: (1) The PT of meteorological–hydrological drought was characterized by faster propagation during the hot months (June–September) and slower propagation during the cold months (December to March of the following year); (2) Under the same level of hydrological drought, as the level of meteorological drought increases, the PT of the drought shortens. The propagation thresholds of meteorological to hydrological drought in the WRB, the JRB, and the MWRB are −0.69, −0.81, and −0.78, respectively. (3) In the dynamic changes in PT, the WRB showed a non-significant decrease; however, both the JRB and the MWRB exhibited a significant increase in PT across different drought levels. (4) The influence of the water and heat status during spring, summer, and winter on PT was more pronounced, while in autumn, the impact of the basin's water storage and discharge status was more significant in the JRB and the MWRB. [ABSTRACT FROM AUTHOR]

In this study, we propose a probabilistic metric, the formative drought rate (FDR), to quantify drought propagation. It is the probability that a meteorological drought in precipitation forms a hydrological drought in streamflow. Drought events were identified based on the standardized precipitation index and streamflow drought index, respectively, at 1‐, 3‐, 6‐ and 12‐month timescales. The method was tested in three river basins in Turkey (Kucuk Menderes, Gediz and Ergene). In each river basin, meteorological stations were coupled with streamflow gauging stations to form pairs of stations depending on their distance from each other and the length of their common record periods. The FDR was calculated across all timescales for each pair of stations. It was found capable to describe the river basin‐specific spatial and temporal variability of drought propagation. As the FDR is defined in the form of probability, it is expected to be a useful metric for quantifying propagation from meteorological to hydrological drought. Thus, it carries a potential for scientific research and practice in water resources management. [ABSTRACT FROM AUTHOR]

The advent of climate change has induced frequent occurrence of droughts in the past few decades. Identification of hydrological droughts require computation of drought indices by probabilistic standardization procedures. The existing hydrological drought indices could not answer the zero monthly streamflow condition for the ephemeral streams. This issue was resolved by developing a modified Standardized Streamflow Index to characterize the hydrological drought of Upper Kangsabati River Basin, West Bengal, India. 45 hydrological droughts were extracted for the basin and the most severe drought occurred in the year 2015–2016. The basin experienced the most severe drought of 10.67 severity and longest drought duration of 13 months. A bivariate analysis of drought characteristics was carried out using copula technique to determine different design drought events. The bivariate distribution which showed the basin experienced most severe drought of 16 years and longest duration drought of 15 years 'OR' return period. Propagation time of the drought hazard from the meteorological to the hydrological drought is extensively studied in this research using both correlation and Cross Wavelet Transform (XWT) methods. XWT was mostly used for qualitative comparison of hydrological and meteorological signal in drought propagation studies in the past. In this research, a novel quantitative approach of using XWT and the phase angles obtained between the hydrological and meteorological signals is proposed to determine the drought propagation times. It was concluded that the basin had in general a drought propagation time of 2 months. However, there were seasonal variability in the drought propagation times showing prompt response in the summer season which increased to 2 months for monsoons and stretching far to 5 months for the late winter. [ABSTRACT FROM AUTHOR]

Drought is one of the most frequent types of natural disasters in the world, and it has been classified into several different categories. Generally, meteorological drought is considered to be the beginning of a drought disaster, while socio-economic drought is the possible ultimate result. However, controversy remains around the main impact factors in the propagation from meteorological drought to socio-economic drought over the past decades. In this study, a comprehensive investigation of the 2022 drought event in the city of Lishui, China was conducted to build a model for analyzing the main impact factors in the propagation from meteorological drought to socio-economic drought. The results showed that the 2022 drought event had a great impact on the city's socio-economic activities. According to governmental reports on socio-economic drought and basic information on water sources, a random forest attribution analysis model was built. The model demonstrated a great performance in distinguishing whether a socio-economic drought had occurred, with an accuracy of 0.9935, a true positive rate of 0.9489 and a false positive rate of 0.0021. Additionally, the variables related to water sources—including drainage area, covered population and daily water supply volume—were found to be more important than the other variables related to meteorological conditions in the model, meaning that the capacity of water sources is the main impact factor in the propagation between meteorological drought and socio-economic drought. In other words, it is feasible to prevent the propagation of meteorological drought to socio-economic drought through water conservancy engineering construction. [ABSTRACT FROM AUTHOR]

The purpose of this research is to identify changes in the spatiotemporal distribution and severity of meteorological droughts in Ukraine between 1946 and 2020. In order to determine the role of precipitation and atmospheric evaporative demand on drought severity, two drought indices were applied for comparative analysis: the standardized precipitation index (SPI) and the standardized evaporation precipitation index (SPEI). Both indices were calculated on 3‐ and 12‐month timescales. The gridded dataset of monthly air temperature and atmospheric precipitation for Ukraine with high spatial resolution (0.1° × 0.1°), developed in the Ukrainian Hydrometeorological Institute, was used. Results of time series analysis of drought indices showed at least 20 episodes, in which more than 25% of the territory of Ukraine was affected by drought of varying intensity. Trends show an increase in drought severity determined mostly by a strong observed increase in the atmospheric evaporative demand. Tendencies towards an increase in the duration and intensity of droughts were observed mainly in the southwestern, central and northern regions of Ukraine. The main cause of the increase was droughts in spring and summer. The temporal analysis of the spatial distribution of areas affected by drought during the identified main drought episodes showed different patterns in drought propagation across the territory of Ukraine. [ABSTRACT FROM AUTHOR]

Study region: The Juam Dam area in Suncheon, Jeollanam-do, South Korea Study focus: This study aims to analyze drought propagation characteristics using time-lagged correlation analysis based on daily drought index, determining the lag time from meteorological drought to propagation into hydrological drought. The target period for correlation analysis is the onset date of the dry spell preceding the occurrence of hydrological drought and the termination date of the dry spell following the termination of the drought for each drought event. The Standardized Precipitation Index (SPI) at various time-scales for meteorological drought and the Standardized Reservoir Supply Index (SRSI) for hydrological drought were applied. New hydrological insights for the region: This study presents the objectivity and accuracy of drought onset and termination date for drought propagation analysis through daily lagged correlation analysis. Through ROC analysis, SPI90, SPI180, and SPI365 are shown to increase by an average of 16.0 %, 8.8 %, and 6.0 %, respectively. From 1993–2023, long-term hydrological droughts lasting 2 years occurred 5 times, with a maximum duration of 408 days, magnitude −629, and severity −1.76. The daily lag between the multi-scale SPIs and SRSI of individual drought events presents the possibility of predicting hydrological drought through multiple regression analysis. This research provides insights for improving hydrological drought monitoring, prediction, and response strategies through results of individual propagation characteristics of drought events.

Different drought types exhibit propagation phenomena and feedback through the hydrological cycle. Therefore, this study utilized the convergent cross mapping to identify the causality among meteorological drought(MD), agricultural drought(AD), hydrological drought(HD), and ecological drought(ED) in the Nenjiang River Basin from 1980 to 2020, constructing a causal relationship network. The results indicate that different types of droughts are more prone to spread and influence each other at shorter time scales. Although there exist bidirectional causality between MD and other droughts at the monthly scale, no clear causal relationship is observed between AD and ED. Contrasting the direction and strength of causality, presenting the order MD-AD-HD-ED. This finding is consistent with the hydrological cycle pattern. The intensity of drought causality varies significantly across different regions spatially. This study delves into the mechanisms and intensities of mutual influence among different types of droughts by establishing the causal relationship network, offering essential scientific basis for drought monitoring, early warning, and emergency response.

Study region: Sanjiang Plain, China Study focus: The characterization of groundwater drought is inadequate, particularly in terms of the differences in the drought propagation dynamics between cropland and other regions. In this study, we identified groundwater drought events and characteristics in the Sanjiang Plain, using the standardized groundwater drought index (SGDI); we also quantified the mechanism of dynamic factors influencing drought propagation characteristics based on the geodetector method and wavelet coherence analysis and discussed the correlation between the NDVI and SGDI.New Hydrological Insights for the Region: The drought propagation time was shorter during summer and longer during spring and autumn in irrigated areas than in nonirrigated areas. The groundwater system exhibited greater resistance to drought during summer, and spatially nonirrigated area was more vulnerable to meteorological drought. The factor that best explained the variation in propagation time and threshold differed across seasons. A significant correlation time-frequency domain existed between all the factors and SGDI in nonirrigated area, with the SGDI exhibiting the fastest response to soil moisture. The relationship between the SGDI and factors was characterized by a discontinuous response of less than 8 months and a continuous response of more than 30 months. The correlations between the SGDI and NDVI in irrigated and nonirrigated area exhibit different changes due to groundwater exploitation and differences in plant physiology between artificial crops and natural vegetation.

The mechanisms underlying the impacts of climate change and vegetation dynamics on hydrological drought in humid regions are still lacking. In this study, we connected the four components of meteorology-soil-vegetation-runoff to investigate the spatio-temporal response relationship between vegetation growth and different drought types. Based on the Variable Infiltration Capacity model and the Self-organizing Map Algorithm, we proposed ecological risk bundles at the grid scale to characterize the potential impacts of different types and levels of drought on vegetation. Furthermore, we quantified the driving impact of temporal and spatial changes in vegetation coverage on the propagation of meteorological-hydrological drought. The study found that the centers of gravity for the occurrence frequencies of extreme and mild drought shifted towards regions where vegetation growth was influenced by climate change. In certain regions of the watershed, vegetation exhibits significant spatial and temporal heterogeneity in its response to stress caused by different drought types. From 2004 to 2014, the stress on vegetation caused by moderate and mild meteorological droughts weakened, while soil moisture stress intensified after 2014. Simultaneously, the impacts of climate change and vegetation growth on runoff reached 48.25 % and 35.13 % respectively, and their synergistic effects triggered changes in the risk of co-concurrent return periods for hydrological drought events. Under the 100-year design return period, the co-occurrence return period of runoff shifted from its natural state of 162.9 years to 52.8 years, and the joint return period reversed its scenario, becoming shorter than the co-occurrence return period.

Abstract This study aims to quantify meteorological–hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide.

Groundwater serves as the primary source of freshwater in arid and semi-arid regions, rendering them resilient against precipitation scarcity. Various aspects of the drought phenomenon necessitate the application of multivariate analysis and composite drought indices. These composite indices afford a more comprehensive understanding of various drought types. However, few studies have considered the integration of meteorological and groundwater drought information. This research delves into determining a threshold for triggering the transition from meteorological drought to groundwater drought in an arid region (Minab plain). It introduces the Joint Deficit Meteo-Groundwater Drought Index, a result of combining two droughts based on copula function. Furthermore, trivariate drought frequency analysis (severity-duration-peak) is conducted based on three scenarios in three clusters of the Minab Plain. Drought risk is then assessed using conditional probability. The results indicate that the northern and central parts of the Minab Plain face a high risk of meteo-groundwater drought. With increasing drought duration and severity, the peak also rises, placing the entire region at risk of widespread drought. A comprehensive understanding of meteo-groundwater drought and an assessment of its characteristics provide insights into the signals of propagation from meteorological drought to groundwater, facilitating the management of groundwater and surface water resources to mitigate the effects of drought. [ABSTRACT FROM AUTHOR]

Drought produces cross-system impacts, and these interactions between multiple systems are also referred to as drought propagation. However, the complex natural processes and anthropogenic disturbances lead to the drought propagation process being non-linear and systems feedback, which is still lack of knowledge in large-scale basins. To address these challenges, we propose a hydro-economic coupled model and investigate drought propagation across meteorological-hydrological-agricultural systems. The results from the Lancang-Mekong River Basin show that drought propagates from the meteorological system to the hydrological system and is weakened by the basin buffer and storage capacity. This propagation process shows spatial heterogeneity caused by basin characteristics, highlighting that the upstream (CS location) and downstream (KR and KC locations) are more prone to hydrological drought vulnerability. As drought further propagates to the agricultural system, water abstraction behaviours can alleviate the drought situation, leading to crop yield increases ranging from 4.6% to 39.2% through irrigation pathways. Unfortunately, irrigation behaviour also worsens hydrological drought in a feedback loop, where downstream VT (annual discharge decreases by around 1346 m³/s) shows more intense variation than upstream LP (annual discharge decreases by almost 135 m³/s), illustrating the feedback among multi-systems and accumulation in spatial. Moreover, upstream hydropower and downstream agricultural water use show synergistic relationships, revealing that efficient anthropogenic interventions can positively mitigate the impact of drought on human well-being. This paper provides an in-depth understanding of the complex drought propagation process in nature-human highly coupled Lancang-Mekong, which may help policymakers and basin managers to better cope with drought. [ABSTRACT FROM AUTHOR]

A reliable understanding of linkages between meteorological, hydrological and agricultural droughts (MD, HD, and AD respectively) is crucial to building resilience and planning for future climate changes. Despite Australia being prone to severe droughts, lagtimes of propagation (and recovery), from meteorological to hydrological and agricultural droughts across its large hydroclimatic regions, are poorly understood. Therefore, we investigate the characteristics of drought propagation and recovery time lags for droughts of four timescales and a combination of drought onset and cessation criteria in 407 unregulated catchments within six major precipitation zones across the country. We find that the propagation and recovery lags depend on climatic conditions, drought criteria and timescales. The median of catchment average propagation times from MD to HD across Australia varied from 0.8 to 1.7 months for 1‐month timescales, increasing to 2.2–5.0 months for 12‐month timescales. The corresponding recovery lagtimes were 1.3–3.7 and 1.7–7.0 months respectively. Similarly, the median of catchment average propagation times from MD to AD ranged from 0.8 to 1.9 months for 1‐month timescales, increasing to 0.6–5.0 months for 12‐month. The corresponding recovery lagtimes were 0.7–2.8 and 0.3–8.7 months respectively. For droughts of smaller timescales, propagation and recovery lags are linearly correlated with recovery lagtimes consistently greater than propagation times. However, as the timescale increases, these relationships weaken suggesting effects of other catchment attributes (e.g., groundwater contributions) on lag relationships. Plain Language Summary: The primary focus of the research is to investigate the time delay between the occurrence of the lack of precipitation (meteorological droughts) and its subsequent impact on river flow (hydrological drought) and soil moisture (agricultural drought). Understanding these delays is crucial for drought planning and management. This study uses observed precipitation, river flow, and satellite‐based soil moisture data spanning over 40 years across six major precipitation zones within Australia. The delays between drought types (meteorological, hydrological, and agricultural) vary depending on the specific location within Australia. The criteria used to define the onset and end of droughts, as well as the drought duration, also influence the observed delays. The average delay from meteorological to hydrological or agricultural droughts increases with longer timescales. For example, hydrological droughts measured on 1‐month timescale have shorter delays (0.8–1.7 months), while 12‐month droughts have longer delays (2.2–5 months). Similarly, shorter droughts have shorter recovery times, while longer droughts have longer recovery times. For shorter timescale droughts, there is a clear relationship between the delays with end delays consistently greater than the start delays. However, as droughts become larger and more prolonged, the relationship weakens, suggesting the influence of other catchment attributes. Key Points: Drought propagation and recovery behaviors for a large sample of catchments under varied climatic zones within Australia are investigatedPropagation and recovery lag relationships are well‐defined for shorter droughts but are increasingly indefinable for longer droughtsPropagation (TP) and recovery lags (TR) depend on drought severity with shorter TP to milder droughts and longer TR to milder droughts [ABSTRACT FROM AUTHOR]

As droughts propagate both in time and space, their impacts increase because of changes in drought properties. Because temporal and spatial drought propagation are mostly studied separately, it is yet unknown how drought spatial extent and connectedness change as droughts propagate though the hydrological cycle from precipitation to streamflow and groundwater. Here, we use a large‐sample dataset of 70 catchments in Central Europe to study the propagation of local and spatial drought characteristics. We show that drought propagation leads to longer, later, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P‐ET, among these 20% propagate further to streamflow and 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater. Drought extent and dependence increase during drought propagation along the drought propagation pathway from precipitation to streamflow thanks to synchronizing effects of the land‐surface but decreases again for groundwater because of sub‐surface heterogeneity. Plain Language Summary: As rainfall deficits develop into discharge and groundwater deficits, the impacts of droughts increase. While we know that drought impacts and properties change during drought development, it is yet unknown how the spatial characteristics of droughts change over the duration of an event. Here, we use a large dataset of 70 watersheds in Central Europe to study the development of drought characteristics over the duration of a drought event. We show that drought development leads to longer, later, fewer, and larger droughts. 20% of the rainfall droughts develop into discharge droughts, and 10% into groundwater droughts. Of the discharge droughts, 40% develop into groundwater droughts. Drought extent increases during drought development from rainfall to discharge thanks to effects at the land‐surface but decreases again for groundwater because of sub‐surface variations. Key Points: Drought propagation affects local and regional drought characteristics and leads to longer, later, fewer, and larger droughtsOnly 20% of the precipitation deficits propagate to streamflow, while 40% of the streamflow deficits propagate to groundwaterSpatial drought connectedness increases from precipitation to streamflow but decreases again for groundwater [ABSTRACT FROM AUTHOR]

This study aims to quantify meteorological–hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide. [ABSTRACT FROM AUTHOR]

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions. [ABSTRACT FROM AUTHOR]

The Nile River Basin (NRB) has experienced a notable rise in drought episodes in recent decades. The propagation of meteorological, agricultural, and groundwater drought dynamics in the NRB was investigated in this study. The following drought indices examined the correlation and propagation among meteorological, agricultural, and groundwater droughts. These are the standardized precipitation evapotranspiration index (SPEI), soil moisture index, Gravity Recovery and Climate Experiment, and GRACE Follow-On (GRACE/GRACE-FO)-derived groundwater drought index (GGDI). These droughts were comprehensively evaluated in the NRB from 2003 to 2022. The cross-wavelet transform approach highlighted the links between droughts. The following are the key findings: (1) In the NRB, the cross-wavelet energy spectrum of wavelet coherence can indicate the internal connection between meteorological versus (vs.) agricultural and agricultural versus (vs.) groundwater drought. The time scale with the most significant correlation coefficient is the drought propagation time. (2) The El Niño–Southern Oscillation (ENSO) correlated with agricultural and groundwater drought much more than the Indian Ocean Dipole (IOD), demonstrating that ENSO has an important impact on drought advancement. (3) The R2 values were 0.68 for GGDI vs. standardized soil moisture index (SSI), 0.71 for Blue Nile Region (BNR) GGDI vs. SSI, and 0.55 for SSI vs. Standardized Precipitation Evapotranspiration Index (SPEI). Similarly, in the Lake Victoria Region (LVR), GGDI vs. SSI was 0.51 and SSI vs. SPEI was 0.55, but in the Bahr-el-Ghazal Region (BER), GGDI vs. SSI was 0.61 and SSI vs. SPEI was 0.27 during the whole research period with varied lag durations ranging from 1 to 6 months. Thus, the propagation of drought (i.e., meteorological, agricultural, and groundwater drought) dynamics has the potential to reshape our understanding of drought evolution, which could lead to early drought forecasting across the NRB and similar climatic regions. [ABSTRACT FROM AUTHOR]

Subseasonal droughts including flash droughts have occurred frequently in recent years, which are accompanied by heatwaves or wildfires that raise a wide concern on environmental risk. However, the changing characteristics of subseasonal drought propagation, and the possible climate and environmental drivers remain unknown. This study quantifies the propagation characteristics from meteorological drought to soil drought using a Copula‐based Bayesian framework, and shows that higher propagation risks mainly occur in more humid regions with denser vegetation cover. Trends in drought propagation risk vary regionally, with a global increase of 2%/decade (p < 0.01) during 1980–2022. Vegetation greening and climate warming are the key drivers over >71% of the global vegetated lands, with mean contribution rates of 39.5% and 36.5% respectively. Other climatic factors including vapor pressure deficit and precipitation also paly critical roles, which closely correlate with temperature and vegetation. These findings highlight the importance of vegetation greening on subseasonal drought propagation dynamics. Plain Language Summary: Changing characteristics of seasonal‐interannual drought propagation have been well studied at watershed scales, and they were found to be principally ruled by climate divers and moderately affected by vegetation factors. In a changing environment, subseasonal droughts have occurred frequently worldwide, showing different characteristics and environmental responses with long‐term droughts. However, how climate and environment factors affect the subseasonal drought propagation characteristics remains unknown. This study investigates the propagation risk from meteorological drought to soil drought at subseasonal timescales based on a conditional probability method. We found that higher subseasonal drought propagation risks were mainly located in more humid vegetated regions, and the propagation risk showed an overall increasing trend (p < 0.01) from a global perspective but with significant spatial variations during 1980–2022. Climatic and vegetation factors jointly affect the trends in subseasonal drought propagation risks. Among them, vegetation greening and climate warming were the most important drivers over >71% of global vegetated regions. Key Points: Higher propagation risk from subseasonal meteorological to soil drought mainly occurred in humid regions with denser vegetation coverTrends in subseasonal drought propagation risk varied regionally, with a global mean increase of 2%/decade during 1980–2022Greening and warming were the key drivers of the trends, with global mean contribution rates of 39.5% and 36.5% respectively [ABSTRACT FROM AUTHOR]

As extreme climate events become more common with global warming, groundwater is increasingly vital for combating long-term drought and ensuring socio-economic and ecological stability. Currently, the mechanism of meteorological drought propagation to groundwater drought is still not fully understood. This study focuses on the North China Plain (NCP), utilizing statistical theories, spatiotemporal kriging interpolation, and the Mann–Kendall trend test to examine the spatial and temporal distribution characteristics of groundwater from 2005 to 2021. Based on drought theory, the characteristics and propagation process of drought are further quantified. Key findings reveal the following: (1) Shallow groundwater depths in the NCP follow a zonal pattern from the western mountains to the eastern plains and coastal areas. Over two-thirds of this region showed an increase in groundwater depth at a rate of 0–0.05 m/a; (2) Groundwater drought frequency typically ranges from 3 to 6 times, with an average duration of 10 to 30 months and average severity between 10 and 35; (3) Delayed effects last between 0 to 60 months, with attenuation effects varying from 0 to 3 and prolonged effects extending from 0 to 16. Additionally, delayed effects intensify with increasing time scales, while prolonged effects weaken. Notably, both delayed and prolonged effects in the north of the NCP are more pronounced than in the south of the region. This study quantifies the process by which meteorological drought propagates to groundwater drought, offering a new perspective for understanding the interaction between groundwater and meteorological drought. It holds significant scientific importance for monitoring drought and managing water resources in the context of global climate change. [ABSTRACT FROM AUTHOR]

Drought propagation analysis is of great significance to develop reliable drought-resistant schemes. In this study, based on the construction of time-variant meteorological and agricultural drought indicators SPIt and SSMIt through Generalized Additive Models for Location, Scale and Shape (GAMLSS) method, the static and dynamic drought propagation time were defined and determined by Five-element Subtraction Set Pair Potential (FSSPP) and Copula function methods. Then, the driving factors resulted in meteorological to agricultural drought propagation were recognized through Pearson Correlation Coefficient (PCC) indicator. And finally, the application results of the proposed approach in Anhui province, China indicated that, (1) the static propagation time of meteorological to agricultural drought process varied within 1 to 4 months, and differed slightly in different seasons. And drought propagation time in spring and summer was noticeably longer than that of autumn and winter. (2) the dynamic drought propagation time presented decreasing trend in winter, spring and summer but displayed slight increasing trend in autumn in Anhui province. On the whole, the research findings are beneficial for theoretical and practical research of drought propagation system. [ABSTRACT FROM AUTHOR]

Study region: The Pilica River watershed, located in central Poland, is the largest left tributary of the Vistula River basin. Study focus: The study aims to assess the impact of human activities on drought dynamics by considering the specific role of the Sulejów Reservoir. Identifying factors contributing to drought development is essential for decision-makers to implement appropriate management measures. The temporal overlap method is used to distinguish between climate and human-driven droughts. The changes in drought propagation are assessed using the time shift method at various accumulation time scales. To assess the spatial distribution of drought, we applied the Soil and Water Assessment Tool (SWAT) model to simulate soil moisture and streamflow response at a spatial scale. New hydrological insights for the region: The findings highlight that about 75% of meteorological droughts lead to soil moisture droughts, and about 70% result in hydrological droughts. The results show the contribution of human activities to soil moisture drought (∼25%) and hydrological drought (∼10%), indicating that not all droughts are driven by meteorological factors alone. The key finding suggests a shorter and longer time scale of around 3 and 12 months for soil moisture drought and hydrological drought propagation analysis, respectively. Moreover, the decrease in the duration and severity of drought during 2005–2019 compared to 1997–2004 suggests that the magnitude of the reservoir impact depends on its purpose and operational strategies.

Persistent droughts pose a threat to agricultural production, and the changing environment worsens the risk of drought exposure. Understanding the propagation of drought in changing environments and assessing possible impact factors can help in the early detection of drought, guiding agricultural production practices. The current study cannot reflect the propagation status of drought to the total terrestrial hydrological drought, so this work creatively investigated the atmospheric to hydrological drought propagation time in the Yangtze River Basin under the dynamic and static perspectives based on the Standardized Precipitation Evapotranspiration Index and the Terrestrial Water Storage Anomalous Drought Index, fine-tuned the time scale to the seasonal scale, and explored the contributing capacity of the variable interactions. The results show that: (1) under the dynamic perspective, while the propagation time is decreasing in the annual scale, the spring season shows the opposite trend; and (2) large variability exists in the timing of drought propagation at spatial scales, with elevation playing the most important influential role, and bivariate interactions contributing stronger explanations compared to single variables. This study highlights the importance of considering the impact of variable interactions and contributes to our understanding of the response of secondary droughts to upper-level droughts, providing valuable insights into the propagation of droughts to total terrestrial hydrologic drought.

This study delves into the potential impacts of climate change on meteorological and hydrological droughts in the Western Ghats region of South India, a large and humid tropical region. Utilizing three drought indices—the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Standardized Runoff Index (SRI), we assessed the historical drought patterns and projected future scenarios under different Representative Concentration Pathway (RCP) scenarios (4.5 and 8.5). This comprehensive analysis encompassed three future time segments (near: 2021–2040, mid: 2041–2070, far: 2071–2100) and compared results with a base period (1989–2018). The study demonstrated that drought propagation is notably faster (around 3 months) in wet, humid tropical regions, highlighting the urgency of understanding its dynamics. Furthermore, the findings indicate that droughts are expected to increase in count and severity (> 100%) in the Western Ghats in future, accompanied by an accelerated propagation rate (around 2 months), with recovery rates for hydrological droughts being notably swift in this region. The study emphasizes the significant influence of regional conditions on drought propagation, leading to variations in its characteristics. Additionally, it underscores the potential of Pearson correlation analysis in providing approximate results for estimating drought propagation periods in the wet, humid tropical regions. These findings are significant in formulating effective risk mitigation and adaptation strategies to address the mounting challenges posed by drought in this region. [ABSTRACT FROM AUTHOR]

Recent studies on China's arid and semi-arid regions, particularly the Tarim River Basin (TRB), have shown an increase in the intensity and frequency of extreme weather events. This research examines the link between meteorological droughts, as measured by the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts, as indicated by the Standardized Runoff Index (SRI) and the Standardized Terrestrial Water Storage Index (STI), over various time scales. Historical data indicate that SPEI drought frequency (DF) was 14.3–21.9%, with prevalent events in the northern oases. SRI DF ranged from 9.0% to 35.8%, concentrated around the Taklamakan and Kumtag Deserts, while STI DF varied between 4.4% and 32.7%, averaging 15% basin-wide. Future projections show an increased DF of SPEI in deserts and a decrease in oases; SRI DF decreased in deserts but increased in oases. STI changes were more moderate. The study also found a higher risk of drought progression from SPEI to SRI in the southwestern and northeastern oases, exceeding 50% probability, while central and eastern TRB had lower risks. The western TRB and inner Taklamakan Desert faced higher risks of SPEI to STI progression, with probabilities over 45%, in contrast to the lower risks in the eastern and central oases. The concurrence of SRI/STI with moderate to extreme SPEI droughts led to a higher probability and area of SRI/STI droughts, whereas consistent SPEI types showed a reduced induced probability and extent of SRI/STI droughts. This study enhances the understanding of drought propagation from meteorological to hydrological droughts in the TRB and contributes to the prevention of hydrological drought to a certain extent. [ABSTRACT FROM AUTHOR]

The economic and human losses caused by drought are increasing, driven by climate change, human activities, and increased exposure of livelihood activities in water‐dependent sectors. Mitigation of these impacts for socio‐ecological securit is necessary to gain a better understanding of how human activities contribute to the propagation of drought as water management further develops. The previous studies investigated the impact of human activities on a macro level, but they overlooked the specific effects caused by human water management measures. In addition, most studies focus on the propagation time (PT, the number of months from meteorological drought propagation to hydrological drought), while other drought propagation characteristics, such as duration, magnitude, and recovery time, are not yet sufficiently understood. To tackle these issues, the PCR‐GLOBWB v2.0 hydrological model simulated hydrological processes in China under natural and human‐influenced scenarios. The study assessed how human activities impact hydrological drought and its propagation. Result shows that human activities have exacerbated hydrological drought in northern China, while it is mitigated in the south. The propagation rate (PR, proportion of meteorological drought propagation to hydrological drought) ranges from 45% to 75%, and the PT is 6–23 months. The PR does not differ substantially between the north and south, while the PT is longer in the north. The PR decreases by 1%–60% due to human activities, and the PT decreases (1–13 months) in the north and increases (1–10 months) in the south. Human activities display significant variations in how they influence the propagation process of drought across different basins. The primary factors driving the spatial pattern of drought disparities are regional variations in irrigation methods and the storage capacity of reservoirs. Plain Language Summary: Under the combined impact of climate change and human activities, economic and human losses caused by drought in China have been increasing year by year. To mitigate the impact of disasters, we conducted research using PCR‐GLOBWB v2.0 model to investigate how human activities have altered hydrological drought in China. And the role of human activities in the propagation process of drought was explored. The results indicate that human activities have intensified hydrological drought in northern China, while providing some alleviation in the southern regions. Human activities disrupt the natural processes of drought propagation, resulting in a decrease in propagation rates. Furthermore, human activities have shortened the propagation lag time of drought in the north, while increasing it in the south. Additionally, smaller basins are more sensitive to human activities compared to larger basins. Our study reveals the impact of human activities on hydrological drought and drought propagation, providing valuable insights for the development of more effective drought adaptation strategies. Key Points: We used the PCR‐GLOBWB v2.0 model to study the impact of human activities on the process of drought propagationHuman activities play a varying role in the propagation process of drought in different river basinsHuman activities has led to a decrease in drought propagation rates and shortened/prolonging the drought lag time in northern/southern China [ABSTRACT FROM AUTHOR]

In the past several decades, drought events have occurred frequently around the world. However, research on the propagation of drought events has not been adequately explored. This study investigated the drought propagation process from meteorological drought to agricultural drought (PMAD) and from meteorological drought to hydrological drought (PMHD) using a 72-year reanalysis dataset in the tropical Lancang–Mekong River Basin. Firstly, we used a new method—Standardized Drought Analysis Toolbox—to construct drought indices. Then, a linear method (Pearson correlation analysis) and a nonlinear method (mutual information) were used to investigate the drought propagation process. Cross-wavelet analysis and wavelet coherence analysis were employed to explore the statistical relationship among the three drought types. Finally, the random forest method was applied to quantify the major factors in drought response time (DRT). The results revealed the following: (1) both linear and nonlinear methods exhibited strong temporal and spatial consistency for both PMAD and PMHD, with linear relationships being stronger than nonlinear ones. (2) The DRTs of PMAD and PMHD were around 1–2 months and 3–5 months, respectively. Significant differences existed in the DRT between the dry season and the rainy season. (3) A divergent spatial pattern of the proportion of DRT was observed between PMAD and PMHD. (4) Significant statistical correlations between meteorological drought and agricultural drought and between meteorological drought and hydrological drought were observed in specific periods for each sub-region; (5) Hydrometeorological factors contributed the most to DRT, followed by terrain factors and the land cover types. The findings of this study deepened our understanding of the spatial–temporal relationship of multiple drought propagation types in this transboundary river basin. [ABSTRACT FROM AUTHOR]

Revealing the mechanism of hydrological and agricultural drought has been challenging and vital in the environment under extreme weather and water resource shortages. To explore the evolution process from meteorological to hydrological and agricultural drought further, multi-source remote sensing data, including the Gravity Recovery and Climate Experiment (GRACE) product, were collected in the Huaihe River basin of China during 2002–2020. Three machine learning methods, including long short-term memory neural network (LSTM), convolutional neural network (CNN), and categorical boosting (CatBoost), were constructed for hydrological and agricultural drought forecasting. The propagation time from meteorological drought to surface water storage and terrestrial water storage drought, evaluated by the standardized precipitation evapotranspiration index, was 8 and 11 months with Pearson correlation coefficients (R) of 0.68 and 0.48, respectively. Groundwater storage drought was correlated with evapotranspiration and vegetation growth with a 12-month lag time, respectively. In addition, vegetation growth was affected by the drought of soil moisture at depths ranging from 100 to 200 cm with an 8-month lag time with an R of −0.39. Although the forecasting performances of terrestrial water storage drought were better than those of groundwater storage drought and agricultural drought, CNN always performed better than LSTM and CatBoost models, with Nash–Sutclife efficiency values during testing ranging from 0.28 to 0.70, 0.26 to 0.33, and −0.10 to −0.40 for terrestrial water storage drought, groundwater storage drought, and agricultural drought at lead times of 0–3 months, respectively. Furthermore, splitting training and testing data at random significantly improved the performances of CNN and CatBoost methods for drought forecasting rather than in chronological order splitting for non-stationary data. [ABSTRACT FROM AUTHOR]

Investigating systematic meteorological–agricultural–hydrological drought propagation within an integrated watershed framework is crucial yet challenging for advancing robust early warning systems and targeted resilience strategies. To address this gap, this study employs the standardized precipitation evapotranspiration index (SPEI), standardized soil moisture index (SSMI), and nonlinear joint hydrological drought index (NJHDI) to characterize meteorological, agricultural, and hydrological drought, respectively. Utilizing the strongest correlation method, variations in the propagation time along moisture movement pathways within the system are quantified using the Soil and Water Assessment Tool (SWAT) model. The Yellow River basin (YRB) is selected as the case study area. Key results reveal distinct seasonal patterns in meteorological–agricultural propagation across the basin, with escalated spring and summer timescales. However, weaker correlations and limited seasonality emerge for agricultural–hydrological linkages due to sustaining baseflow buffers. Specifically, the arid and semiarid region exhibited shorter propagation time with 1–5 months, while the semiarid and semihumid region displayed longer timescales with 7–12 months. These findings provide valuable scientific references for enhancing real-time early warning systems tailored to coupled watershed systems. The integrated methodology underscores the importance of unraveling fine-scale spatiotemporal propagation variability for localized drought resilience. [ABSTRACT FROM AUTHOR]

Understanding the full propagation process of drought, from meteorological drought (MD) to vegetation drought (VD), could promote drought monitoring and early warning in the ecosystems. This study characterized MD, soil moisture drought (SD), and VD and their propagations using the Standardized Precipitation Evapotranspiration Index (SPEI), the Soil Moisture Anomaly Percentage Index (SMAPI), and the Vegetation Health Index (VHI) to enhance understanding of the drought hazard in the Yellow River Basin (YRB), China. Drought events, duration, magnitude, intensity, and interval were identified from these time series via the run theory and percentile thresholds. The relationships between MD, SD, and VD were examined by cross-correlating the SPEI, SMAPI, and VHI. Finally, the effects of climate and grid properties on drought characteristics and propagations were investigated. The results showed that the upland had a low risk for all droughts, while the midland had a low risk for MD and a high risk for SD, and the lowland had a high risk for MD in the YRB. For the full-time data, the lowland had the strongest correlations and shortest time lags, while the upland had the weakest correlations and longest time lags for full propagation from MD to SD to VD. However, seasonality and multi-threshold characteristics in extreme drought dominated the propagation process of VD. For monthly data, midland showed the strongest correlations and shortest time lags in summer, while lowland showed the strongest correlations and shortest time lags in other seasons for full propagation of VD. For multi-threshold data, the 0–30th percentile had stronger correlations and shorter time lags for full propagation of VD. Meteorology showed a stronger correlation with all drought characteristics and drought propagation than soil properties and land use. These findings provide valuable insights for enhancing the vegetation aspects of drought monitoring and early warning in the YRB.

Abstract A reliable understanding of linkages between meteorological, hydrological and agricultural droughts (MD, HD, and AD respectively) is crucial to building resilience and planning for future climate changes. Despite Australia being prone to severe droughts, lagtimes of propagation (and recovery), from meteorological to hydrological and agricultural droughts across its large hydroclimatic regions, are poorly understood. Therefore, we investigate the characteristics of drought propagation and recovery time lags for droughts of four timescales and a combination of drought onset and cessation criteria in 407 unregulated catchments within six major precipitation zones across the country. We find that the propagation and recovery lags depend on climatic conditions, drought criteria and timescales. The median of catchment average propagation times from MD to HD across Australia varied from 0.8 to 1.7 months for 1‐month timescales, increasing to 2.2–5.0 months for 12‐month timescales. The corresponding recovery lagtimes were 1.3–3.7 and 1.7–7.0 months respectively. Similarly, the median of catchment average propagation times from MD to AD ranged from 0.8 to 1.9 months for 1‐month timescales, increasing to 0.6–5.0 months for 12‐month. The corresponding recovery lagtimes were 0.7–2.8 and 0.3–8.7 months respectively. For droughts of smaller timescales, propagation and recovery lags are linearly correlated with recovery lagtimes consistently greater than propagation times. However, as the timescale increases, these relationships weaken suggesting effects of other catchment attributes (e.g., groundwater contributions) on lag relationships.

Study region: The Yellow River Basin in China Study focus: Agricultural drought (AD) poses a serious threat to national food security, however, responses to AD to meteorological drought (MD), factoring in influences of climate change and human activity, are not well understood. This study employed the Standardized Precipitation Evapotranspiration Index and the Standardized Soil Moisture Index to characterize the evolution of MD and AD. The drought propagation time (PT) was calculated with maximum correlation coefficients under full-crop-cycle, seasonal, and multi-threshold modes for spring and winter wheat in the Yellow River Basin (YRB; China). New hydrological insights for the region: Both spring and winter wheat faced increasing magnitude agricultural drought events (ADEM), with winter wheat being affected more severely from 1950–2021. Increasing temperature enhanced ADEM, while human activities had a more uncertain. The PT was generally prolonged for all propagation modes, with spring wheat having a longer PT except for in multi-threshold mode. The full-crop-cycle mode showed the entire period of crop growth propagation characteristics, the seasonal mode showed different propagation characteristics by month, and the multi-threshold mode showed the propagation characteristics at different degrees of AD. Sunspot Index had the highest influence on PT among all teleconnection factors, and human activities had increasing impact. The results of this study provide a basis for better understanding the agricultural drought propagation.

Abstract As droughts propagate both in time and space, their impacts increase because of changes in drought properties. Because temporal and spatial drought propagation are mostly studied separately, it is yet unknown how drought spatial extent and connectedness change as droughts propagate though the hydrological cycle from precipitation to streamflow and groundwater. Here, we use a large‐sample dataset of 70 catchments in Central Europe to study the propagation of local and spatial drought characteristics. We show that drought propagation leads to longer, later, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P‐ET, among these 20% propagate further to streamflow and 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater. Drought extent and dependence increase during drought propagation along the drought propagation pathway from precipitation to streamflow thanks to synchronizing effects of the land‐surface but decreases again for groundwater because of sub‐surface heterogeneity.

Meteorological drought precedes the agricultural drought and studying the propagation time from meteorological to agricultural drought can substantially reduce agricultural losses. To find this propagation time between the meteorological and agricultural drought, this study analyzed the copula-based conditional probability between the Standardized Precipitation Index at 12 timescales (SPI-1 to12, meteorological drought) and Standardized Soil Moisture Index at 1 month timescale (SSI-1, agricultural drought), over the fifteen Agro-Climatic Zones (ACZs) of India. SSI is computed using a total column Soil Moisture (SM) derived from ESACCI SM using the Statistical Soil Moisture Profile (SSMP) model. The SSMP-based ESACCI SM is positively correlated (Correlation Coefficient of 0.871) with ERA5 Land SM. To compute the conditional probability, three copulas namely Frank, Clayton, and Gumbel copulas are fitted between SPI-1 to 12 and SSI-1. The Goodness of Fit analysis showed the dominance of the Gumbel copula among the Clayton, Frank, and Gumbel copulas. Gumbel copula completely dominated the SPI timescales of 1–3 and 11–12 whereas Clayton copula was relatively favored for SPI timescales of 4–10. The propagation time results revealed that the monsoon season (JAS) consistently exhibits the highest propagation time, averaging around 10 months followed by summer (AMJ, 7 months), spring (JFM, 4 months), and winter (OND, 2–3 months) seasons. The Mann-Kendall trend test revealed that the same season can have different trends in different ACZs and vice versa, underlining the localized and season-specific strategies for drought management, considering each ACZ's unique environmental, agricultural, and socio-economic conditions in each zone. Overall, this study showcases the capability of remote sensing and copula-based statistical models, in understanding meteorological to agricultural drought propagation. It also highlights the efficiency of statistical models in deriving total column SM from surface SM.

Abstract Subseasonal droughts including flash droughts have occurred frequently in recent years, which are accompanied by heatwaves or wildfires that raise a wide concern on environmental risk. However, the changing characteristics of subseasonal drought propagation, and the possible climate and environmental drivers remain unknown. This study quantifies the propagation characteristics from meteorological drought to soil drought using a Copula‐based Bayesian framework, and shows that higher propagation risks mainly occur in more humid regions with denser vegetation cover. Trends in drought propagation risk vary regionally, with a global increase of 2%/decade (p 71% of the global vegetated lands, with mean contribution rates of 39.5% and 36.5% respectively. Other climatic factors including vapor pressure deficit and precipitation also paly critical roles, which closely correlate with temperature and vegetation. These findings highlight the importance of vegetation greening on subseasonal drought propagation dynamics.

Study region: Guangdong, China Study focus: Droughts have resulted in significant crop failure in Guangdong province, where annual crop yield exceed 12 million tons. However, there is a lack of a comprehensive assessment of both meteorological drought and agricultural drought in Guangdong, particularly regarding the influencing factors and drought propagation. This study aims to address this gap by utilizing the standardized precipitation evapotranspiration index (SPEI) and soil water deficit index (SWDI) to represent meteorological drought and agricultural drought, respectively. To examine the characteristics of drought in the past 50 years (1973–2022), the year is divided into flood and non-flood season based on the temporal distribution of precipitation. New hydrological insights for the region: Over the last five decades, the number of meteorological and agricultural drought days decreases from coastal to inland areas. Notably, agricultural droughts have become more pronounced in the last two decades. More agricultural drought days appears during the non-flood season than the flood season. Precipitation emerges as the most influential factor for meteorological drought, while potential evapotranspiration, actual evapotranspiration and temperature are identified as the primary factors for agricultural drought. The drought propagation time ranges from 10 to 45 days which is shorter in central Guangdong than other regions, and it is longer in non-flood season than in flood season.

Study region: The Yiluo River Basin (YLRB), China Study focus: Understanding the alterations in drought propagation under evolving environmental conditions is crucial for the efficient management of water resources. In this study, the 'simulation-observation' comparison method was employed to analyze the drought propagation in distinct periods: baseline, simulated, and disturbed periods. This facilitated the quantification of the impact of climate change and human activities on drought propagation characteristics, such as the response time of the Standardized Streamflow Index (SSI) to the Standardized Precipitation Index (SPI) and the propagation threshold. New hydrological insights for the region: The response times of the SSI to the SPI has been prolonged at monthly and seasonal scales due to climate change, while it has been reduced at the annual scale. The impact of human activities on the lengthening of response time is only evident at longer temporal scales. Human activities have contributed to higher thresholds for severe and extreme droughts on monthly and annual scales, increasing the probability of extreme droughts. Meanwhile, climate change has partially offset the negative impacts of human activities. However, at the seasonal scale, climate change is the main cause of the increasing propagation thresholds. The conclusions drawn from this research provide valuable insights for the development of policies aimed at managing drought in a changing environment.

Study region: Three subbasins with different karstification degrees in Southwest China. Study focus: To investigate the mechanism of karst influence on drought propagation, this paper used a daily-scale threshold level method to identify drought events and comparatively analyzed the differences in drought propagation characteristics among three subbasins. New hydrological insights for the region: (i) The karstification degree is appreciably correlated with the drought propagation from meteorological to hydrological droughts, and the stronger the karstification, the closer the relationship. (ii) Daily-scale drought events performed better in identifying drought characteristics; of all drought events, 55% were meteorological and 24% were hydrological and lasted

Understanding the propagation characteristics and driving factors from meteorological drought to hydrological drought is essential for alleviating drought and for early warning systems regarding drought. This study focused on the Weihe River basin (WRB) and its two subregions (the Jinghe River (JRB) and the middle reaches of the Weihe River (MWRB)), utilizing the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) to characterize meteorological and hydrological drought, respectively. Based on Copula theory and conditional probability, a quantification model for the propagation time (PT) of meteorological–hydrological drought was constructed. The dynamic characteristics of PT on annual and seasonal scales were explored. Additionally, the influences of different seasonal meteorological factors and underlying surface factors on the dynamic changes in PT were analyzed. The main conclusions were as follows: (1) The PT of meteorological–hydrological drought was characterized by faster propagation during the hot months (June–September) and slower propagation during the cold months (December to March of the following year); (2) Under the same level of hydrological drought, as the level of meteorological drought increases, the PT of the drought shortens. The propagation thresholds of meteorological to hydrological drought in the WRB, the JRB, and the MWRB are −0.69, −0.81, and −0.78, respectively. (3) In the dynamic changes in PT, the WRB showed a non-significant decrease; however, both the JRB and the MWRB exhibited a significant increase in PT across different drought levels. (4) The influence of the water and heat status during spring, summer, and winter on PT was more pronounced, while in autumn, the impact of the basin’s water storage and discharge status was more significant in the JRB and the MWRB.

Drought is one of the most frequent types of natural disasters in the world, and it has been classified into several different categories. Generally, meteorological drought is considered to be the beginning of a drought disaster, while socio-economic drought is the possible ultimate result. However, controversy remains around the main impact factors in the propagation from meteorological drought to socio-economic drought over the past decades. In this study, a comprehensive investigation of the 2022 drought event in the city of Lishui, China was conducted to build a model for analyzing the main impact factors in the propagation from meteorological drought to socio-economic drought. The results showed that the 2022 drought event had a great impact on the city’s socio-economic activities. According to governmental reports on socio-economic drought and basic information on water sources, a random forest attribution analysis model was built. The model demonstrated a great performance in distinguishing whether a socio-economic drought had occurred, with an accuracy of 0.9935, a true positive rate of 0.9489 and a false positive rate of 0.0021. Additionally, the variables related to water sources—including drainage area, covered population and daily water supply volume—were found to be more important than the other variables related to meteorological conditions in the model, meaning that the capacity of water sources is the main impact factor in the propagation between meteorological drought and socio-economic drought. In other words, it is feasible to prevent the propagation of meteorological drought to socio-economic drought through water conservancy engineering construction.

As a natural hazard, drought is a complex multivariate phenomenon that requires more comprehensive analysis. In this study, we studied meteorological, agricultural, and hydrological drought events with precipitation, soil moisture, and stream flow data for the study area. The risk analysis for drought duration and severity of three kinds of drought events were analyzed with univariate and three kinds of bivariate return periods based on the copula. Furthermore, the propagation of three kinds of drought was studied. From the investigation, it is observed that agricultural drought events are longer and more severe, besides the risk associated with agricultural drought is high compared to other kinds of drought. Moreover, the average time taken for meteorological drought to propagate into agricultural drought is 4.3 months and for the hydrological drought is 3.8 months for the river basin. The comprehensive study of three kinds of drought is helpful to adopt suitable drought management plans in the region. HIGHLIGHTS Studied characteristics of meteorological, agricultural, and hydrological drought events in the river basin.; Found out that agricultural drought events have a long duration and high severity.; Meteorological drought has less risk compared to the other two kinds of drought.; The propagation time to agricultural drought from meteorological drought is long compared to the time taken for hydrological drought events.;

The propagation from meteorological to hydrological drought is critical for better understanding hydrological drought. However, how climate change would affect the drought propagation has not been well studied, especially over regions mixed with massive human interventions. The study attempts to explore changes in the characteristics of meteorological and hydrological droughts, and the corresponding drought propagation under different climate change scenarios across six watersheds over the Yangtze River basin (YZB). Seasonal meteorological and hydrological droughts were characterized by using standardized precipitation and streamflow index at 3‐month scales (SPI‐3 and SSI‐3), which were calculated using precipitation simulations from 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models and streamflow simulations from PCR‐GLOBWB 2.0 hydrological model driven by CMIP6 outputs. Drought propagation characteristics, including propagation ratio, lag and lengthening, were then determined. Both meteorological and hydrological drought durations would shorten, while their drought severity would increase excluding a downstream watershed. About 40%–50% of meteorological droughts could develop into hydrological droughts, with lag time less than 1.4 months and lengthening time less than 1.8 months, respectively. Under climate warming, the drought propagation ratio would increase over two watersheds, while decrease and then increase over three watersheds. The drought propagation lag time is expected to prolong over the regions above Cuntan under moderate emission scenario, while prolong first and then shorten over most watersheds under high‐emission scenario. The drought propagation lengthening time would shorten over most watersheds excluding a downstream watershed, where drought conditions would further worsen during drought propagation. This study calls for climate mitigation efforts to suppress drought aggravation in the propagation particularly for the downstream YZB. [ABSTRACT FROM AUTHOR]

The meteorological drought (MD) is the precursor of the hydrological drought (HD), and understanding the propagation process from MD to HD is of great significance for the early warning of HD. Based on the theory of run and Bayesian networks, this study uses the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) and standardized streamflow index (SSI) to explore the characteristics and propagation of MD and HD in the regions of eastern Gansu, China. The results indicate that: (1) The region was mainly wet (dry) and the wetness (dryness) was stronger before (after) 2000 when reflected by SSI. The frequency is higher based on SPI and SPEI than that based on SSI, while the duration and magnitude are lower than those based on SSI. (2) The propagation time from MD to HD is generally within 1–10 months. After the occurrence of a certain level of MD, it is most likely to propagate to HD events that are relatively weaker than the MD. Besides, the higher the intensity level of MD, the shorter the propagation time to HD, and the shorter for cumulative occurrence probability of HD to approach 1.0. (3) The increase in temperature and decrease in precipitation, runoff and runoff coefficient may contribute to the dryness after 2000. Moreover, the weakened propagation from MD to HD may be due to the rapid increase of water resource consumption caused by intensive anthropogenic activities in the study area. From the above results, this study found some propagation characteristics from MD to HD in a semi‐arid and semi‐humid watershed, which can provide a supplement for revealing the drought mechanism and can assist in the management and planning of water resources in China. [ABSTRACT FROM AUTHOR]

Persistent deficits in meteorological, hydrological and ecological variables define different types of drought that are often linked together in a cascade. The drought cascade is an emergent phenomenon in the climatic system. A quantitative evaluation of the drought cascade based on observations is both a rigorous test of how different components of numerical Earth System models interact with one‐another and a useful tool for practitioners concerned with drought impacts on water resource and ecosystem services. In this study the drought cascade is characterized over the continental US using remote sensing data and in situ observations. Remote sensing fields of coincident vegetation photosynthesis and above‐ground biomass anomalies are introduced into the cascade to assess the role of the terrestrial biosphere within the cascade. The propagation of the diverse drought types, in terms of amplitude‐dampening and phase‐delays, are quantified. It is shown that woody and herbaceous vegetation have contrasting responses to prolonged soil moisture deficit that is traceable to access and storage of water as well as the dual effects of water‐ and light‐limitation. The observations also show that prolonged precipitation deficit in itself is not adequate to trigger the intense soil moisture and vegetation stress responses and that excessive atmospheric evaporative demand needs to be coincident with the precipitation anomalies. Plain Language Summary: The elements of the water cycle such as precipitation, soil moisture, streamflow and groundwater storage occasionally experience extended periods of below‐average conditions. Such conditions for each of the elements defines different drought types. In applications, different users of water resources are sensitive to different types of drought. The drought types are often linked together in a cascade. This study offers an observation‐based characterization of the drought cascade that allows quantitative evaluation of the dampening and delay among the different drought types. The study is largely based on remote sensing observations and adds measurements of photosynthesis and above‐ground biomass anomalies as additional elements of ecological drought within the cascade. Key Points: Persistent deficits in meteorological, hydrological and ecological variables define different types of droughtDrought types are often linked within a cascade and propagate from one to another, sometime with delays and amplitude changesDifferent drought types and their role in the cascade are quantified using observational data across the continental USA [ABSTRACT FROM AUTHOR]