Flash Drought Research Articles

Assessing the impacts of climate change on climatic extremes in the Congo River Basin

The Congo River Basin, located in central Africa, is the second-largest river basin in the world, after the Amazon. It has a drainage area of approximately 3.7 M km2 and is home to 75 million people. A significant part of the population is exposed to recurrent floods and droughts, and climate change is likely to worsen these events. Climate change studies of the Congo River basin have so far focused on annual and seasonal precipitation, but little attention was paid to extreme climatic events. This study aims to assess future changes in rainfall-induced flash floods and drought regimes in the Congo basin from the present day to 2100, using four selected extreme climatic indices as proxies to these two natural disasters. The indices are the total annual precipitation (PCPTOT), the number of days where rainfall is above 20 mm (PCP20), the standardized precipitation index (SPI), and the standardized precipitation-evapotranspiration index (SPEI). The indices were calculated with the statistically downscaled output of eleven Regional Climate Models (RCMs) from the Coordinated Downscaling Experiment (CORDEX-AFRICA) under two Representative Concentration Pathways: RCP 8.5 (high emissions scenario) and RCP 4.5 (moderate emissions scenario). Precipitation and temperature simulated by the RCMs were statistically downscaled using quantile mapping, while wind speed, solar radiation, and relative humidity were projected using K-nearest neighbor downscaling. The evolution of the indices was then assessed between the reference period (1976–2005) and three future periods (2011–2040, 2041–2070, and 2071–2100). Multimodel average results suggest that (i) independently of the scenario and period, PCPTOT and SPI will increase in the north, east, and western extremities of the basin and decrease in the basin’s center. (ii) The maximum increase (+ 24%) and decrease (− 6%) in PCPTOT were both projected under RCP 8.5 in the 2071–2100 period. (iii) PCP20 will increase independently of the period and scenario. Under RCP 8.5, in the 2071–2100 period, PCP20 will increase by 94% on average over the whole watershed. (iv) The SPEI results suggest that in all periods and scenarios, the rise in evapotranspiration due to higher temperatures will offset annual precipitation increases in the north, east, and western extremities of the basin. Increased evaporation will exacerbate the decrease in annual precipitation in the center, leading to increased drought frequency in the entire basin.

A Multivariate Flash Drought Indicator for Identifying Global Hotspots and Associated Climate Controls

AbstractThe significant impact of flash droughts (FDs) on society can vary based on a combination of FD characteristics (event counts, mean severity, and rate of intensification), which is largely unexplored. We employed root‐zone soil‐moisture for 1980–2018 to calculate the FD characteristics and integrated them to formulate a novel multivariate FD indicator for mapping the global FD hotspot regions. The potential influence of climate characteristics (i.e., anomalies, aridity, and evaporative fractions) and land‐climate feedbacks on the evolution of multivariate FD indicator is investigated. Our results indicate that precipitation is the primary driver of FD evolution, while the effect of temperature, vapor pressure deficit, and land‐climate interaction varies across the climate divisions after the onset of the events. The magnitude of multivariate FD indicator decreases with increased climate aridity, and it is significant in the global humid regimes, underscoring the importance of water and energy supply as limiting factors regulating FD‐risk.

Decomposing the Critical Components of Flash Drought Using the Standardized Evaporative Stress Ratio

Decomposing the Critical Components of Flash Drought Using the Standardized Evaporative Stress Ratio

Terrestrial ecosystem response to flash droughts over India

Rapid onset droughts, termed as “flash droughts”, cause short-term but serious threats to terrestrial ecosystems and influence carbon dynamics due to insufficient warning. To date, how the regional terrestrial carbon dynamics respond to flash droughts in India remains unknown. Since, India is highly dependent on its cropland and vegetation, identifying the influence of flash droughts on terrestrial ecosystem is important. Here we use MODIS remote sensing satellite sensor based gross primary productivity (GPP) and remote sensing-based soil moisture data to compute the response of ecosystems to flash droughts in India. From the investigation, it was observed that GPP responds to more than 95% of the flash droughts across India, with the highest response frequency occurring over Ganga basin and southern India while the lowest response across northeastern India. The discrepancies in the response frequencies are mainly attributed to different vegetation resilience conditions across different parts of the country. Moreover, the mean response time is about 10 to 19 days averaged over India, with the lowest and highest response time over Indus-Ganga basins and northeastern Indian river basins (including the Brahmaputra, Minor rivers draining into Myanmar basin (MRMB), and Barak basins), respectively. Severe reduction in water use efficiency (WUE) was observed for the Ganga river basin and some parts of southern India, which highlighted the non-resilient nature of ecosystem towards rapid soil moisture variations. The study facilitates the identification of flash drought hotspots in the country including the Indus basin, Southern river basins (Cauveri, EFRPCP, and EFRSCB basins), some parts of the Ganga basin, and the ability of an ecosystem to withstand such drastic conditions. These findings highlight the need to adopt essential drought mitigation measures to safeguard the sustainability of ecosystems.

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor.

Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods to forecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.

Application of an improved spatio-temporal identification method of flash droughts

Flash droughts are regional phenomena that can manifest in large areas with rapid intensification for a period of time. Few studies have considered the spatial pathways of flash droughts or their drought period. This study uses the five criteria based on the standardized evaporative stress ratio (SESR) method to identify flash droughts, and when a SESR value recovers to the 20th percentile, the flash drought is considered to terminate. To define spatially continuous flash droughts accurately, the usual order of first calculating drought patches and then identifying flash droughts is reversed to first identify flash droughts on the grid and then determine flash drought patches. In addition, this study tracks the spatial paths of flash droughts via centroid transfers of flash drought patches. Using MOD16 data, the methodology is evaluated by analyzing the regional characteristics of flash droughts in the Huaibei Plain of China from 2001 to 2019. The flash droughts in this region most frequently tracked in the northeast and west. The average flash drought duration was 31 days, of which the rapid intensification period was 18 days and drought period was 14 days. Flash drought events in this region mostly occurred in May, August and October, and east to west transition and non-transitions, which accounted for 44% and 22%, respectively, were the main spatial track paths. Only 26% of flash drought events transitioned to long term drought events. This study expands our knowledge of the evolution process of flash droughts to space-time dimensions, which is essential for flash droughts early warning and agricultural water management.

Global distribution, trends, and drivers of flash drought occurrence

Flash drought is characterized by a period of rapid drought intensification with impacts on agriculture, water resources, ecosystems, and the human environment. Addressing these challenges requires a fundamental understanding of flash drought occurrence. This study identifies global hotspots for flash drought from 1980–2015 via anomalies in evaporative stress and the standardized evaporative stress ratio. Flash drought hotspots exist over Brazil, the Sahel, the Great Rift Valley, and India, with notable local hotspots over the central United States, southwestern Russia, and northeastern China. Six of the fifteen study regions experienced a statistically significant increase in flash drought during 1980–2015. In contrast, three study regions witnessed a significant decline in flash drought frequency. Finally, the results illustrate that multiple pathways of research are needed to further our understanding of the regional drivers of flash drought and the complex interactions between flash drought and socioeconomic impacts.

A new approach to quantify propagation time from meteorological to hydrological drought

Of particular importance in a world of increasing water scarcity is the temporal and spatial relationship between a shortage in rainfall—meteorological drought—and a shortage in available water, or hydrological drought. Propagation time from meteorological to hydrological drought should be calculated at a higher (sub-monthly) temporal resolution with considerations for spatial expansion. A new framework for propagation time calculation from one index to another is established that uses the run theory, high-resolution remote sensing data on a daily time step. The framework is demonstrated using standardized drought indices representing precipitation, runoff, evapotranspiration, and soil moisture in the Central Asian subcontinent to measure the temporal shift (propagation time) in affected drought area, bringing a new perspective to contemporary drought analysis. Several variables from the water cycle are chosen to provide hydrological context for different propagation times. Correlation analyses for propagation time are shown to be ambiguous in interpretation and precision when compared to the temporal shift, which is clearly defined and calculated on a daily time step. Moreover, the results of temporal shift analyses indicate that deficits in evapotranspiration and runoff can precede deficits in precipitation, while soil moisture deficit almost always follows, highlighting the effects of additional influencing factors aside from precipitation on types of hydrological drought. While it is limited by current understanding of drought definition techniques, availability and quality of remote sensing products, and selection of characteristics for observation, use of the temporal shift over the correlation analysis provides a sub-monthly estimate of drought propagation time that may prove useful for detailed analyses, particularly in rapidly developing flash drought events.

Changes in Unevenness of Wet‐Day Precipitation Over China During 1961–2020

AbstractPrecipitation falls unevenly in space and time, which has significant consequences for human society and natural ecosystems. Based on 2,134 gauged observations during 1961–2020 and historical simulations of 14 models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), we analyze precipitation unevenness over China in terms of the spatiotemporal distribution of wet days (>1 mm) and wet‐day precipitation amount throughout the year. We also explore precipitation extremes related to the unevenness. Spatially, precipitation shows medium unevenness in China. Temporally, the unevenness in distribution of wet days increases from southeast (generally humid) to northwest (generally arid). This temporal unevenness weakened in large parts of western China during 1991–2020 relative to 1961–1990. As for precipitation amount, the distribution of precipitation that falls on wet days is more uneven in water‐limited regions compared with humid regions. Associated with this unevenness, between 1961 and 2020, the top 50% of annual precipitation fell in approximately the 12 wettest days, and the maximum 1‐day precipitation for the year contributed 10% on average to annual precipitation. The period 1991–2020 shows overall greater unevenness in eastern China and less unevenness in western China relative to the first 30 years. Multimodel ensemble means of CMIP6 simulations agree with the basic spatial pattern of observations, while underestimating the magnitude of temporal unevenness of precipitation. If these regional differences in precipitation unevenness were to persist over time, this would likely create some new challenges for water resource management in these areas, e.g., flash drought.

Integrating optical and microwave satellite observations for high res-olution soil moisture estimate and applications in CONUS drought analyses

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at the same spatial resolution as the optical sensors (5km here) and applied for drought analysis in the continental United States. A new refined model is proposed to include auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed soil moisture model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns. Currently, the USDM is providing a weekly map. Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively higher spatial resolution than those traditionally derived from passive microwave sensors, thus drought maps based on soil moisture anomalies can be obtained on daily basis and made the flash drought analysis and monitoring become possible.

Agricultural and food security impacts from the 2010 Russia flash drought

The flash drought and its associated heat wave that affected western Russia in the summer of 2010 had significant cascading agricultural and socioeconomic impacts. Drought indicators sensitive to soil moisture and evapotranspiration (ET) showed that the flash drought began in June 2010, then intensified rapidly and expanded to cover much of western Russia. By early July, almost all of the major wheat producing regions of Russia were experiencing extreme water stress to the winter and spring wheat crops. The timing of the onset of the flash drought was particularly devastating as the period of most rapid intensification overlapped with the flowering stage for both the winter and spring wheat crops. As a result, wheat yields in Russia were reduced by over 70 percent in top wheat producing oblasts and total wheat production was reduced by 20 million metric tons (MT) compared to the previous seasons. In fulfillment of its recently adopted Food Security Doctrine, the Russian government banned the export of wheat in early August 2010 to preserve wheat for its own consumption. Further compounding matters on a global scale, the significant reduction in wheat production in Russia coincided with wheat production issues in places like western Australia, which led to a large drop in global wheat stocks. The sharp drop in global wheat stocks coincided with a rapid increase in wheat prices across the globe. The rapid increase in wheat prices, partly resulting from the rapid intensification of drought in Russia, led to increased prices for wheat flour and bread in many countries throughout the world. This ultimately led to an increase in poverty and civil unrest in countries like Mozambique and Egypt with a history of inequality and poverty.

Flash Drought Characteristics by Different Severities in Humid Subtropical Basins: A Case Study in the Gan River Basin, China

AbstractIt is essential to assess flash drought risk based on a reliable flash drought intensity (severity) index incorporating comprehensive information of the rapid decline (“flash”) in soil moisture toward drought conditions and soil moisture thresholds belonging to the “drought” category. In this study, we used the Gan River basin as an example to define a flash drought intensity index that can be calculated for individual time steps (pentads) during a flash drought period over a given grid (or station). The severity of a complete flash drought event is the sum of the intensity values during the flash drought. We explored the spatial and temporal characteristics of flash droughts with different grades based on their respective severities. The results show that decreases in total cloud cover, precipitation, and relative humidity, as well as increases in 500-hPa geopotential height, convective inhibition, temperature, vapor pressure deficit, and wind speed can create favorable conditions for the occurrence of flash droughts. Although flash droughts are relatively frequent in the central and southern parts of the basin, the severity is relatively high in the northern part of the basin due to longer duration. Flash drought severity shows a slightly downward trend due to decreases in frequency, duration, and intensity from 1961 to 2018. Extreme and exceptional flash droughts decrease significantly while moderate and severe flash droughts trend slightly upward. Flash drought severity appears to be more affected by the interaction between duration and intensity as the grade increases from mild to severe. The frequency and duration of flash droughts are higher in July–October. The southern part of the basin is more prone to moderate and severe flash droughts, while the northern parts of the basin are more vulnerable to extreme and exceptional flash droughts due to longer durations and greater severities than other parts. Moderate, severe, extreme, and exceptional flash droughts occurred at approximately 3–6-, 5–15-, 10–50-, and 30–200-yr intervals, respectively, based on the copula analysis.

Global Flash Drought Monitoring Using Surface Soil Moisture

AbstractAbrupt onset and swift intensification characterize flash droughts. Global surface soil moisture (θRS) from NASA's Soil Moisture Active Passive (SMAP) satellite can facilitate a near‐real‐time assessment of emerging flash droughts at a 36‐km footprint. However, a robust flash drought monitoring using θRS must account for the (a) short observation record of SMAP, (b) nonlinear geophysical controls over θRS dynamics, and (c) emergent meteorological drivers of flash droughts. We propose a new method for near‐real‐time characterization of droughts using Soil Moisture Stress (SMS, drought stress) and Relative Rate of Drydown (RRD, drought stress intensification rate)—developed using SMAP θRS (March 2015–May 2021), footprint‐scale seasonal soil water retention parameters and land‐atmospheric coupling strength. SMS and RRD are nonlinearly combined to develop Flash Drought Stress Index (FDSI) to characterize emerging flash droughts (FDSI ≥ 0.71 for moderate to high RRD and SMS). Globally, FDSI shows a high correlation with concurrent meteorological anomalies. A mechanistic evaluation of flash droughts is presented for the Northern Great Plains, Central South Africa, and Eastern Australia using FDSI, SMS, and RRD. About 5.6% of the earth's landmass experienced flash droughts of varying intensity and duration during 2015–2021 (FDSI ≥ 0.71 for >30 consecutive days), majorly in global drylands. FDSI shows high skill in forecasting vegetation health with a lead of 0–2 weeks, with exceptions in irrigated croplands and mixed forests. With readily available parameters, low data latency, and no dependence on model simulations, we provide a robust tool for global near‐real‐time flash drought monitoring using SMAP.

Drought Early Warning in Agri-Food Systems

Droughts will increase in frequency, intensity, duration, and spread under climate change. Drought affects numerous sectors in society and the natural environment, including short-term reduced crop production, social conflict over water allocation, severe outmigration, and eventual famine. Early action can prevent escalation of impacts, requiring drought early warning systems (DEWSs) that give current assessments and sufficient notice for active risk management. While most droughts are relatively slow in onset, often resulting in late responses, flash droughts are becoming more frequent, and their sudden onset poses challenging demands on DEWSs for timely communication. We examine several DEWSs at global, regional, and national scales, with a special emphasis on agri-food systems. Many of these have been successful, such as some of the responses to 2015–2017 droughts in Africa and Latin America. Successful examples show that early involvement of stakeholders, from DEWS development to implementation, is crucial. In addition, regional and global cooperation can cross-fertilize with new ideas, reduce reaction time, and raise efficiency. Broadening partnerships also includes recruiting citizen science and including seemingly subjective indigenous knowledge that can improve monitoring, data collection, and uptake of response measures. More precise and more useful DEWSs in agri-food systems will prove even more cost-effective in averting the need for emergency responses, improving global food security.

The diagnosis about spatio-temporal characteristics and driving factors of flash drought and its prediction over typical humid and semi-arid basins in China

AbstractFlash drought is a rapid-onset drought, which has greatly threatened the agricultural production and economic development. However, the unclear development mechanism of flash droughts brings challenges for its monitoring, forecasting and mitigation. This study investigates the spatio-temporal characteristics, driving factors and the prediction of flash drought over typical humid and semi-arid basins. The main objectives and findings are as follows: (1) The patterns of flash drought are compared under different climate types. The results show that flash drought is more serious in the chosen humid basin than that in the semiarid basin, with more events, longer duration, larger frequency of occurrence (FOC). (2) The development mechanisms of flash drought are explored by analyzing the anomalies of seven meteorological variables in the evolution of flash drought. The results indicate that the main driving factors are the negative anomalies of precipitation and the positive anomalies of temperature, which usually occur at two pentads before the onset of flash drought. (3) The prediction of soil moisture as a key variable in flash droughts developing process is conducted using support vector machine (SVM), with meteorological variables and a remote sensing soil moisture, namely Soil Moisture Active and Passive (SMAP), as inputs. In this study, about 65%-70% of flash droughts can be captured by the prediction. However, some events are missed, and false alarms also exist in most stations in both basins. This study can provide some references for monitoring and early warning of flash drought, which is important to reduce the losses and risks in agriculture production.

Water use strategies of different aged moso bamboo culms under summer drought

Moso bamboo (Phyllostachys edulis (Carriere) J. Houzeau) is distributed widely over the subtropical regions of China, but it encounters a chronic summer reduced rainfall and elevated temperatures induced by subtropical high pressure. In some flash droughts characterized by rapid development speed and high intensity, the newly sprouted culms have much higher mortality than established culms, even though they have the advantage of resource integration. To determine the impact of flash drought on the water use of culms of different ages and the potential relation to differential mortality, we conducted a manipulated throughfall exclusion experiment in the field to simulate a summer flash drought. Under the manipulated summer drought, we found that newly sprouted culms still had higher sap flux densities than the established culms. However, their normalized daily water use had a similar positive response to meteorological factors (radiation and vapor pressure deficit) and soil moisture. Under the summer drought, the established culms significantly decreased water use and relied more on nighttime sap flow. In contrast, the continuously higher water use rates of the newly sprouted culms under drought stress may be attributed to the additional support from the rhizomes via physiological integration. The results indicated that the established and newly sprouted adopted drought-avoidance and drought-tolerance strategies, respectively. However, this drought-tolerance strategy might hurt the hydraulic system of the newly sprouted culms and even lead to hydraulic failure. Our findings provide some initial insight into the integrated responses of moso bamboo to summer drought. Further study on the network integration of bamboo culms will provide more insight into the natural response to drought and corresponding management.

Precedent meteorological driving forces of flash drought and their feasibility for flash drought simulation

Flash droughts are extreme events characterized by a short duration, strong intensity, and rapid onset. Owing to their unusually rapid occurrence, the use of current drought monitoring tools to capture them is still challenging. In this study, using ERA-Interim soil moisture reanalysis products from the European Center for Medium-Range Weather Forecast, an approach that considers the rate of decrease in soil moisture content during the onset stage of flash droughts was proposed for the identification of the flash droughts that occurred during the 1979-2018 period. Further, the anomalies associated with meteorological variables during the drought onset stage of these events were analyzed, and the feasibility of using precedent meteorological driving forces to realize flash drought simulation based on a multivariate linear regression model was investigated. The results obtained showed that the rate of soil moisture intensification during the onset state of flash droughts showed significant spatial discrepancy. Specifically, during this stage, soil moisture content declined much faster in the south of the Yangtze River than in Northwestern China. Additionally, the mean, peak, and variation ranges of the anomalies of the different meteorological variables exhibited more significant spatial discrepancies during this stage. Particularly, the peak values showed the most significant variation, and were half the standard deviation higher than the slowly-evolving drought. Furthermore, by integrating the anomalies associated with multiple meteorological variables during the early and onset stages of the flash drought events, the regression model provided satisfying simulations of the soil moisture intensification rate, suggesting that it is possible to simulate flash droughts from a meteorological perspective.

Development of a Flash Drought Intensity Index

Flash droughts are characterized by a period of rapid intensification over sub-seasonal time scales that culminates in the rapid emergence of new or worsening drought impacts. This study presents a new flash drought intensity index (FDII) that accounts for both the unusually rapid rate of drought intensification and its resultant severity. The FDII framework advances our ability to characterize flash drought because it provides a more complete measure of flash drought intensity than existing classification methods that only consider the rate of intensification. The FDII is computed using two terms measuring the maximum rate of intensification (FD_INT) and average drought severity (DRO_SEV). A climatological analysis using soil moisture data from the Noah land surface model from 1979–2017 revealed large regional and interannual variability in the spatial extent and intensity of soil moisture flash drought across the US. Overall, DRO_SEV is slightly larger over the western and central US where droughts tend to last longer and FD_INT is ~75% larger across the eastern US where soil moisture variability is greater. Comparison of the FD_INT and DRO_SEV terms showed that they are strongly correlated (r = 0.82 to 0.90) at regional scales, which indicates that the subsequent drought severity is closely related to the magnitude of the rapid intensification preceding it. Analysis of the 2012 US flash drought showed that the FDII depiction of severe drought conditions aligned more closely with regions containing poor crop conditions and large yield losses than that captured by the intensification rate component (FD_INT) alone.

Flash drought in Australia and its relationship to evaporative demand

Flash droughts can be distinguished by rapid intensification from near-normal soil moisture to drought conditions in a matter of weeks. Here, we provide the first characterisation of a climatology of flash drought across Australia using a suite of indices. The experiment is designed to capture a range of conditions related to drought: evaporative demand describes the atmospheric demand for moisture from the surface; precipitation, the supply of moisture from the atmosphere to the surface; and evaporative stress, the supply of moisture from the surface relative to the demand from the atmosphere. We show that regardless of the definition, flash droughts occur in all seasons. They can terminate as rapidly as they start, but in some cases can last many months, resulting in a seasonal-scale drought. We show that flash-drought variability and its prevalence can be related to phases of the El Niño–Southern Oscillation, highlighting scope for seasonal-scale prediction. Using a case study in southeast Australia, we show that monitoring precipitation is less useful for capturing the onset of flash drought as it occurs. Instead, indices like the Evaporative Demand Drought Index and Evaporative Stress Index are more useful for monitoring flash-drought development.

A new framework for the identification of flash drought: Multivariable and probabilistic statistic perspectives

AbstractFlash drought is distinguished with seasonal drought by its characteristics of sudden onset and rapid intensification, and has attracted increasing concern due to the severe negative impacts on socioeconomic development and ecosystems. To accurate identify the onset time and propagation of flash drought is still a big challenge, as it is influenced by many factors (e.g., deficit in precipitation, increase in evapotranspiration and temperature, shortage in soil moisture, and etc.). This study aims to develop a probabilistic and multivariable flash drought identification method (PMFDI) from the perspective of considering the interaction effects from different driving factors on flash drought occurrence and propagation with a multivariable statistical tool. The PMFDI uses the weekly standardized precipitation evapotranspiration index and the standardized soil moisture index to describe the abnormally changes in multiple hydrometeorological variables over a short duration. The linearly multivariable index (LMI) is employed to describe the correlation relationship between multiple hydrometeorological variables and to identify flash droughts from the aspects of sudden onset and rapid intensification. We select the Loess Plateau (LP) in China to verify the efficiency of the developed PMFDI with the comparison to the other two recently proposed flash drought identification methods. The results indicate that PMFDI can identify high‐ and low‐ frequency regions similar to those identified by the other two methods and can generally recognize actual flash droughts. In addition, the PMFDI can capture the comprehensive impact of multiple hydrometeorological variables as well as their interaction on flash drought occurrence, which provides a useful perspective to understand the propagation processes of the actual flash droughts in the LP.