Onset Of Drought Research Articles

Characteristics and driving conditions of flash drought in different grassland ecosystems

At present, flash droughts are poorly understood. Mature prevention and control measures are not available. This study aims to thoroughly explore the evolution characteristics of flash droughts in grassland ecosystems and to determine the meteorological driving conditions for inducing and relieving flash droughts.We propose the concept of the strong evapotranspiration flash drought (SEFD), a new type of flash drought in mid-temperate grasslands. The frequency of SEFDs is lower than that of heat wave flash droughts (HWFDs), but the intensity and impact of SEFDs are greater than those of HWFDs. Flash droughts in grasslands exhibit a high outbreak period from May to August, with the intensity basically above that of moderate drought. HWFDs occur most frequently in June and SEFDs in May. Meadow grasslands are the type of grassland with the highest risk of flash drought. Typical grasslands are more prone to HWFDs, while desert grasslands are more prone to SEFD outbreaks.In this study, a multifactor method was established to quantitatively evaluate the key influencing factors inducing flash droughts of different intensities in different time periods and to quantitatively predict the evolution of flash droughts into seasonal droughts. The temperature, water vapor pressure, precipitation, and wind speed were the key influencing factors of flash droughts and that the most important period in terms of inducing flash droughts is one pentad before the onset of flash drought. The outbreak rate and threshold of key influencing factors are the driving conditions for inducing flash droughts, and the recovery rate can be used as the basis for predicting whether an flash drought will evolve into a seasonal drought.The results showed that the characteristics and driving conditions of flash droughts are different in different types of grasslands and different time periods and are different for different types of flash droughts. In the future, the impact of flash droughts will become more severe.

Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence.

Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching thresholds of unusually low water content. Here, we propose a flash drought early warning approach based on spaceborne measurements of solar-induced chlorophyll fluorescence (SIF), a proxy of photosynthesis that captures plant response to multiple environmental stressors. Instead of negative SIF anomalies, we focus on the subseasonal trajectory of SIF and consider slower-than-usual increase or faster-than-usual decrease of SIF as an early warning for flash drought onset. To quantify the deviation of SIF trajectory from the climatological norm, we adopt existing formulas for a rapid change index (RCI) and apply the RCI analysis to spatially downscaled 8-d SIF data from GOME-2 during 2007-2018. Using two well-known flash drought events identified by the operational US Drought Monitor (in 2012 and 2017), we show that SIF RCI can produce strong predictive signals of flash drought onset with a lead time of 2 wk to 2 mo and can also predict drought recovery with several weeks of lead time. While SIF RCI shows great early warning potential, its magnitude diminishes after drought onset and therefore cannot reflect the current drought intensity. With its long lead time and direct relevance for agriculture, SIF RCI can support a global early warning system for flash drought and is especially useful over regions with sparse hydrometeorological data.

The anthropogenic acceleration and intensification of flash drought over the southeastern coastal region of China will continue into the future

The frequent and rapid onset of flash drought poses a serious threat to agriculture and ecosystems. Detecting human influences on flash droughts and estimating their future risks under climate change have attracted great attention. Focusing on a record-breaking flash drought event in the southeastern coastal region of China in summer 2020, the authors found that the suppression of convective precipitation and high temperature caused by the persistent high geopotential height anomalies and land–atmosphere dry coupling were important reasons for the rapid onset and strong intensity of the flash drought. Event attribution analysis with the latest CMIP6 data showed that anthropogenic climate change has not only increased the likelihood of an onset speed and intensity like those of the 2020 flash drought event, by about 93% ± 20% and 18% ± 15%, respectively, but also increased the chance of their simultaneous occurrence, by about 86% ± 38%, according to their joint probability distribution. Under a business-as-usual future scenario (SSP2-4.5), the likelihood of such an onset speed, intensity, and their simultaneous occurrence will further increase, by 85% ± 33%, 49% ± 8%, and 81% ± 48%, respectively, as compared with current climate conditions. This study highlights the importance of anthropogenic climate change for accelerating and intensifying flash drought in the southeastern coastal region of China.摘要快速爆发的骤旱对农业生产, 生态环境等造成严重威胁, 亟须量化当前及未来气候变化对骤旱爆发过程的影响. 2020年夏季, 在持续高压异常和陆气干耦合的控制下, 我国东南沿海地区出现高温少雨天气并引发极端骤旱事件. 基于第六次国际耦合模式比较计划 (CMIP6) 数据开展归因分析, 本文发现相比天然情景, 温室气体排放等人为因子导致的气候变化不仅使类似2020年骤旱爆发速度和强度的发生概率分别增加93%和18%, 还使其联合概率增加86%. 在目前排放水平下, 此类骤旱爆发速度和强度发生概率及其联合概率在21世纪末将提高85%, 49%, 和81%, 极大增加了干旱适应的挑战.

Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

South Asia is home to one of the fastest-growing populations in Asia, and human activities are leaving indelible marks on the land surface. Yet the likelihood of successive observed droughts in South Asia (SA) and its four subregions (R-1: semi-arid, R-2: arid, R-3: subtropical wet, and R-4: tropical wet and dry) remains poorly understood. Using the state-of-the-art self-calibrated Palmer Drought Severity Index (scPDSI), we examined the impact of different natural ocean variability modes on the evolution, severity, and magnitude of observed droughts across the four subregions that have distinct precipitation seasonality and cover key breadbaskets and highly vulnerable populations. The study revealed that dryness had significantly increased in R-1, R-2, and R-4 during 1981–2020. Temporal analysis revealed an increase in drought intensity for R-1 and R-4 since the 2000s, while a mixed behavior was observed in R-2 and R-3. Moreover, most of the sub-regions witnessed a substantial upsurge in annual precipitation, but a significant decrease in vapor pressure deficit (VPD) during 1981–2020. The increase in precipitation and the decline in VPD partially contributed to a significant rise in Normalized Difference Vegetation Index (NDVI) and a decrease in dryness. In contrast, a strong positive correlation was found between drought index and precipitation, and NDVI across R-1, R-2, and R-4, whereas temperature and VPD exhibited a negative correlation over these regions. No obvious link was detected with El-Niño Southern Oscillation (ENSO) events, or Indian Ocean Dipole (IOD) and drought evolution, as explored for certain regions of SA. The findings showed the possibility that the precipitation changes over these regions had an insignificant relationship with ENSO, IOD, and drought onset. Thus, the study results highlight the need for considering interactions within the longer climate system in describing observed drought risks rather than aiming at drivers from an individual perspective.

Water-Level Fluctuations and Water Temperature Effects on Young-of-Year Largemouth Bass in a Southwest Irrigation Reservoir

Abstract The effects of a warming climate will alter the hydrological cycles of arid southwestern U.S. reservoirs which primarily support agricultural needs, provide flood control, and generate hydroelectric power while secondarily supporting fish communities and sport fishing opportunities. The success of littoral spawning fishes depends on the timing and variability of water levels. The onset of drought between 2017 and 2018 provided an opportunity to evaluate the timing of hatch dates and relative abundance of young-of-year Largemouth Bass Micropterus salmoides across two water years of varying water temperatures and water levels in a southwestern U.S. reservoir. A retrospective analysis of otoliths in young-of-year Largemouth Bass revealed similar hatch dates in 2017 (14 April–29 May) and 2018 (13 April–28 May) despite differences in water temperature and water level rate of change. Median water temperature during hatch dates was greater in 2017 (median 19.0°C, range 14.3–24.4°C) than 2018 (17.6°C, range 13.5–21.7°C). Water level rate of change during hatch dates in 2017 was positive (+3.1 to +13.1 cm/d), which reflected reservoir filling. In contrast, water level rate of change during hatch dates in 2018 was negative (−8.5 to −0.6 cm/d), which reflected reservoir receding. Relative abundance of young-of-year fish was greater in 2017 (21.7 fish/h) when the reservoir was filling compared with relative abundance in 2018 (6.8 fish/h) when the reservoir was receding. The median growth rate was greater in 2017 (1.02 mm/d) when the reservoir was filling than in 2018 (0.82 mm/d) when the reservoir was receding. Despite differences in water temperature and contrasting reservoir levels between the two water years, the Largemouth Bass population in a southwest U.S. reservoir exhibited similar hatch dates reported for the species in southeastern and northeastern U.S. reservoirs. While water demand in the 21st century may exceed availability, the opportunity exists to collaborate with water managers to benefit Largemouth Bass populations in southwestern reservoirs.

Analysis of flash droughts in China using machine learning

Abstract. The term “flash drought” describes a type of drought with rapid onset and strong intensity, which is co-affected by both water-limited and energy-limited conditions. It has aroused widespread attention in related research communities due to its devastating impacts on agricultural production and natural systems. Based on a global reanalysis dataset, we identify flash droughts across China during 1979–2016 by focusing on the depletion rate of weekly soil moisture percentile. The relationship between the rate of intensification (RI) and nine related climate variables is constructed using three machine learning (ML) technologies, namely, multiple linear regression (MLR), long short-term memory (LSTM), and random forest (RF) models. On this basis, the capabilities of these algorithms in estimating RI and detecting droughts (flash droughts and traditional slowly evolving droughts) were analyzed. Results showed that the RF model achieved the highest skill in terms of RI estimation and flash drought identification among the three approaches. Spatially, the RF-based RI performed best in southeastern China, with an average CC of 0.90 and average RMSE of the 2.6 percentile per week, while poor performances were found in the Xinjiang region. For drought detection, all three ML technologies presented a better performance in monitoring flash droughts than in conventional slowly evolving droughts. Particularly, the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of flash drought derived from RF were 0.93, 0.15, and 0.80, respectively, indicating that RF technology is preferable in estimating the RI and monitoring flash droughts by considering multiple meteorological variable anomalies in adjacent weeks to drought onset. In terms of the meteorological driving mechanism of flash drought, the negative precipitation (P) anomalies and positive potential evapotranspiration (PET) anomalies exhibited a stronger synergistic effect on flash droughts compared to slowly developing droughts, along with asymmetrical compound influences in different regions of China. For the Xinjiang region, P deficit played a dominant role in triggering the onset of flash droughts, while in southwestern China, the lack of precipitation and enhanced evaporative demand almost contributed equally to the occurrence of flash drought. This study is valuable to enhance the understanding of flash droughts and highlight the potential of ML technologies in flash drought monitoring.

Specific features of the water regime of the genus Chaenomeles introduced plants in the steppe zone conditions

Sufficient water supply for plants is one of the most important conditions for their vital activity, since most of the biochemical reactions that regulate the plants physiological functions take place in the water environment. The plants adaptive capacity to the influence of a complex of environmental factors in field conditions is largely determined by the ability to maintain water balance, which can be characterized by various features. Among them, the transpiration intensity and the level of water deficit are the most important indicators that are related to the mechanisms of plant resistance to water or high-temperature stress. The aim of the work was to evaluate the introduction success of plants according to the markers of water availability in a new environment. The objects of the study were plants of the genus Chaenomeles, introduced in the Botanical Garden of Oles Honchar Dnipro National University: three natural species (Ch. japonica, Ch. speciosa, and Ch. cathayensis), as well as two hybrids (Ch. × superba and Ch. × californica). Species Ch. japonica naturally grows in humid areas with moderate temperatures, while species of Chinese origin Ch. speciosa and Ch. cathayensis are adapted to mountainous terrain with sharp temperature fluctuations. Water deficiency in the leaves of introduced plants was determined by saturating leaf cuttings with water; the intensity of transpiration was studied by the method of rapid weighing. Both indicators of the water regime in the leaves of introduced plants were measured under contrasting levels of moisture supply during the growing season in the steppe zone conditions: in the wet period, the dry period, and the period of moisture restoration. It was found that during the drought, the intensity of transpiration increased significantly (P ˂ 0.05) compared to the wet period in the leaves of all introduced Chaenomeles plants, the most (by 1.6–1.7 times) in Ch. japonica, Ch. speciosa and Ch. × superba, the least (by 1.3 times) in the leaves of Ch. × californica. Water deficit in the dry growing season in the leaves of all studied Chaenomeles plants increased significantly (P ˂ 0.05), the most in the leaves of Ch. catayensis (2.8 times compared to the wet period), the least in the leaves of Ch. spesiosa (in 2.0 times compared to the wet period). The level of water deficit in the leaves of both Chinese species was lower than that of Ch. japonica (18.85%). In the leaves of Ch. japonica, Ch. speciosa and Ch. × superba was the fastest recovery of the water balance after drought, as well as the most effective regulation of the transpiration intensity level with the onset of drought and during the recovery period. Introduced plants of the species Ch. japonica, Ch. speciosa and Ch. × superba turned out to be the most adapted to vegetation in the conditions of the steppe climate, which is characterized by periods of drought.

Growth resilience of conifer species decreases with early, long‐lasting and intense droughts but cannot be explained by hydraulic traits

Abstract Drought events may reduce growth and survival of conifer trees. The effects of the intensity and timing of drought on the growth resilience, including growth reductions during drought and recovery of growth after drought, remain, however, highly uncertain. Growth resilience of 20 conifer species to 11 dry years was compared in a common garden experiment. We assessed (a) the relationships among growth resistance, recovery and resilience, (b) the impacts of different drought dimensions (intensity, onset and length) on resistance and (c) the underlying mechanisms in terms of growth potential and hydraulic traits. Droughts led to 22% reduction in stem growth for 85% of species, but most species (85%) were resilient due to high recovery. Growth resistance decreased with an early onset of drought (significant for 55% of species), and longer‐lasting (35%) and intense droughts (60%). While fast‐growing species and slow‐growing species were similar in resistance and recovery, fast‐growing species were more resilient. Unexpectedly, resilience could not be explained by hydraulic traits, possibly because the species grew on poor sandy soils and were acclimated to drought with large hydraulic safety margins. Synthesis. Our study shows that in a mild maritime climate almost all conifer species are resilient to drought, and that putative hydraulic traits may be less important here for growth resilience. It also highlights the importance of addressing multiple dimensions of drought, that is, timing, duration and severity, to predict species responses to climate change.

CHARACTERIZING THE DROUGHT DEVELOPMENT IN THE PHILIPPINES USING MULTIPLE DROUGHT INDICES DURING THE 2019 EL NIÑO

Abstract. Drought events in the Philippines have resulted in a significant loss in crop production. This study investigated the drought development during the 2019 weak El Niño using different drought indices at a country and local scale. Satellite data from MODIS were used to derive Normalized Difference Vegetation Index (NDVI) anomaly, Vegetation Health Index (VHI), and Standardized Vegetation and Temperature Ratio (SVTR), while TRMM was used for the Standardized Precipitation Index (SPI). These indices were compared with crop production data at national scale and crop damage reports at local scale. The results showed consistency in the spatiotemporal variation of drought events, where drought peak occurred during March to April in most indices and indicators. Based on the values of SPI, the areas with rainfall deficit increased from January to April (25% to almost 100%), but looking at vegetation stress, around 50% was affected, as seen by SVTR and VHI. Yield loss during the first and second quarter after the El Niño peak increased up to 20%, especially in the western region in the Philippines. Overall findings demonstrate the relevance of utilizing multiple drought indices and indicators that characterize drought evolution, from drought onset to the peak of agricultural drought, which is essential in developing a robust drought metric for the Philippines.

Assessment of Climate and Catchment Control on Drought Propagation in the Tekeze River Basin, Ethiopia

It is crucial to understand the development of hydrological drought which is unique to a sub-basin to derive management strategies that can address the cause. In this study, relationships between climate and catchment control against hydrological drought development in the Tekeze River Basin (TRB), Ethiopia, were assessed. The Water Evaluation and Planning (WEAP) modeling tool was selected to mimic the behavior and historical characteristics of the basin which was modeled for the period 1981 to 2018. The most severe drought events and historical drought years were selected and analyzed on a monthly basis, where the classical rainfall deficit drought was identified to be the most common typology within the basin. Once modeled, both meteorological and hydrological drought analyses were performed using the Threshold Level Method (TLM) where 168 months of meteorological drought with magnitudes as high as 110 mm/month and 60 months of streamflow anomalies with magnitudes of up to 17 mm/month were observed. While the temporal resolution impacts results pertaining to hydrological drought development, the analysis showed that the basin is fast responding, where storage characteristics did not play a significant role in delaying a hydrological drought onset. Compared to naturalized streamflow, the construction of the Tekeze Dam on the main river was indicative of an over 900% increase in dry season flows but a reduction of 23% of wet season flows, showing the potential to redistribute runoff in space and time.

Subseasonal Meteorological Drought Development over the Central United States during Spring

AbstractDiagnosis of rapidly developing springtime droughts in the central United States has mostly been made via numerous individual case studies rather than in an aggregate sense. This study investigates common aspects of subseasonal “meteorological drought” evolution, here defined as persistent precipitation minus evapotranspiration (P− ET) deficits, revealed in early (1 April–15 May) and late (16 May–30 June) spring composites of 5-day running mean JRA-55 reanalysis data for three different central U.S. regions during 1958–2018. On average, these droughts are initiated by a quasi-stationary Rossby wave packet (RWP), propagating from the western North Pacific, which arises about a week prior to drought onset. The RWP is related to a persistent ridge west of the incipient drought region and strong subsidence over it. This subsidence is associated with low-level divergent flow that dries the atmosphere and suppresses precipitation for roughly 1–2 weeks, and generally has a greater impact on the local moisture budget than does reduced poleward moisture transport. The resulting “dynamically driven” evaporative demand corresponds to a rapid drying of the root-zone soil moisture, which decreases around 40 percentiles within about 10 days. Anomalous near-surface warmth develops only after theP− ET deficit onset, as does anomalously low soil moisture that then lingers a month or more, especially in late spring. The horizontal scale of the RWPs, and of the related drought anomalies, decreases from early to late spring, consistent with the climatological change in the Pacific Rossby waveguide. Finally, while this composite analysis is based upon strong, persistentP− ET deficits, it still appears to capture much of the springtime development of “flash droughts” as well.

Response of vegetation ecosystems to flash drought with solar-induced chlorophyll fluorescence over the Hai River Basin, China during 2001–2019

With global climate change, frequent flash droughts have critically impacted vegetation productivity. Based on the new definition on flash drought onset and duration, the temporal and spatial evolution patterns of the flash drought over the Hai River Basin (HRB) was analysed. Among the events, the flash drought in 2019 lasted for 40 days, from the day of the year (DOY) 120 to DOY160, which was the strongest and mainly concentrated in the south-eastern part of the basin. Solar-induced chlorophyll fluorescence (SIF) and vegetation indices were used to explore the responses of different vegetation types to this flash drought. Compared to forest and grassland, the SIF and SIFyield (SIF normalized by the absorbed photosynthetically active radiation (APAR)) values of cropland were more sensitive to water losses and replenishment. By analysing different radiation conditions which would affect SIF and photosynthesis, low radiation was found altering the linear relationship between fluorescence and photosynthesis. The flash drought event caused gross primary productivity (GPP) losses in 40% of the basin and the maximum loss reached 0.16 kg C m−2, indicating that the impact of this flash drought on vegetation productivity was quite serious. The results obtained in this work can be used to understand the mechanisms with which the vegetation photosynthetic capacity responds to flash droughts and to evaluate the impact of flash droughts on terrestrial ecosystems.

Preliminary research on seed yield and nutritional traits of desi chickpea (Cicer arietinum L.) grown in Central Italy in spring sowing

In Italy, chickpea (Cicer arietinum L.) cultivation of the kabuli type is predominant, with local landraces of the desi type, including the Apulian black chickpea, occurring almost exclusively in the south. However, increasing interest in the desi type on the part of farmers and consumers is based on the nutritional properties constituting a niche area in the market health sector. Information pertaining to both field evaluation of desi chickpea in Central Italy and the chemical composition is scarce. Therefore, the aim of this preliminary research was to evaluate the agronomic performance to the agroclimatic environment of Central Italy of thirteen lines of desi chickpea accessions of different origins, as well as the ‘Apulian Black Chickpea’ (ABC). Accessions were sown on March 21 in 2019, without the use of irrigation. The principle qualitative characteristics, namely protein content and raw fiber were determined. Yield was excellent for 57 % of the accessions, some of which exceeded 3.0 t ha-1 with the maximum value of 4.1 t ha-1 recorded for ‘PI598080’ (brown seeds of Indian origin). ‘W617611’ (black seeds of Turkish origin) was the earliest flowering line at 74 days after sowing, permitting this accession to escape the onset of drought and high temperatures. Additional early flowering lines included ‘PI533676’ (black seeds of Ukrainian origin) and ‘PI567850’ (black seeds of Pakistani origin), respectively. Plant structure relating to the average height of the plants (47.0 cm), the height of the first pod (30.8 cm) and the number of branches per plant (2.6) rendered most accessions suitable to combine harvesting, an indispensable prerequisite in the maintenance of an economically sustainable crop. The average protein content was 22.7 % with maximum values exceeding 24 % (‘PI572520’ - black seeds of Syrian origin -, ‘W617614’ - black seeds of Turkish origin - and ‘PI572850’). The fiber content was very heterogeneous ranging from 4.6 % to 12.0 %.The present study provides the basis towards the future introduction of desi chickpea in Central Italy, with the potential for sustainable yield and quality.

A multi-metric assessment of drought vulnerability across different vegetation types using high resolution remote sensing

Drought impact monitoring is of crucial importance in light of climate change. However, we lack an understanding of the concomitant responses of ecosystems to a variety of drought characteristics and the links between drought and ecosystem anomaly characteristics for a comprehensive set of vegetation types to provide needed information for water management. In response, this study presents a new framework that allows us to explore the relationship between drought and its impact on ecosystems in greater detail. Specifically, our framework focuses on estimating jointly the hydrological and ecosystem temporal evolution and anomalies around a drought event using four pairs of metrics: onset-onset, duration-duration, intensity-intensity, and severity-severity of drought and vegetation damage. Additionally, we incorporated a metric on vegetation vulnerability based on changes in damage severity along a gradient of increasing drought severity. Based on this framework, we evaluated drought vulnerability patterns of various vegetation types across the Netherlands and Belgium in 2018 at high spatiotemporal resolution. Our results reveal a differential vulnerability of vegetation between ecosystems with increasing drought severity, which could aid future drought impact predictions. In particular, mosaic grasslands and tree/shrub croplands are highly sensitive to increasing drought severity. Individual characteristics (onset, duration, intensity and severity) of drought and vegetation damage behave differently in various vegetation types. For instance, broadleaved forests respond faster than other forests, while mixed forests suffer less damage than other types. The early warning threshold to drought for most vegetation types is around a Standardized Precipitation Evapotranspiration Index (SPEI) value of −1. The characterization of a suite of drought response characteristics through our impact analysis framework can be used in a wide variety of regions to understand current and possible future responses to drought.

Assessing the Impact of Extreme Droughts on Dryland Vegetation by Multi-Satellite Solar-Induced Chlorophyll Fluorescence

Satellite-estimated solar-induced chlorophyll fluorescence (SIF) is proven to be an effective indicator for dynamic drought monitoring, while the capability of SIF to assess the variability of dryland vegetation under water and heat stress remains challenging. This study presents an analysis of the responses of dryland vegetation to the worst extreme drought over the past two decades in Australia, using multi-source spaceborne SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) and TROPOspheric Monitoring Instrument (TROPOMI). Vegetation functioning was substantially constrained by this extreme event, especially in the interior of Australia, in which there was hardly seasonal growth detected by neither satellite-based observations nor tower-based flux measurements. At a 16-day interval, both SIF and enhanced vegetation index (EVI) can timely capture the reduction at the onset of drought over dryland ecosystems. The results demonstrate that satellite-observed SIF has the potential for characterizing and monitoring the spatiotemporal dynamics of drought over water-limited ecosystems, despite coarse spatial resolution coupled with high-retrieval noise as compared with EVI. Furthermore, our study highlights that SIF retrieved from TROPOMI featuring substantially enhanced spatiotemporal resolution has the promising capability for accurately tracking the drought-induced variation of heterogeneous dryland vegetation.

Assessing the Potential of Downscaled Far Red Solar-Induced Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought Monitoring in Winter Wheat

Solar-induced chlorophyll fluorescence (SIF) from ground, airborne, and satellite-based observations has been increasingly used in drought monitoring recently due to its close relationship with photosynthesis. SIF emissions respond rapidly to droughts, relative to the widely used vegetation indices (VIs), thus indicating their potential for early drought monitoring. The response of SIF to droughts can be attributed to the confounding effects of both the physiology and canopy structure. In order to reduce the reabsorption and scattering effects, the total emitted SIF (SIFtot) was proposed and served as a better tool to estimate GPP compared with the top-of-canopy SIF (SIFtoc). However, the response time and response magnitude of SIFtot to droughts and its relationships with the environmental parameters and soil moisture (SM) (i.e., the knowledge of drought monitoring using SIFtot) remains unclear. Here, the continuous ground data of F760toc (SIFtoc at 760 nm) from a nadir view that was downscaled to F760tot (SIFtot at 760 nm), NIRv, and the NDVI, SM, meteorological, and crop growth parameters were measured from four winter wheat plots with different intensities of drought (well-watered, moderate drought, severe drought, and extreme drought) over 2 months. The results indicated that F760tot was more closely correlated with the SM than the VIs at short time lags but weaker at longer time lags. The daily mean values of F760tot and NIRv were able to distinguish the differences between different drought levels, and F760tot responded quickly to the onset of drought, especially for the moderate drought intensity. These findings demonstrated that F760tot has potential for early drought monitoring and may contribute to mitigating the risk of agricultural drought.

Accelerating flash droughts induced by the joint influence of soil moisture depletion and atmospheric aridity

The emergence of flash drought has attracted widespread attention due to its rapid onset. However, little is known about the recent evolution of flash droughts in terms of the speed of onset and the causes of such a rapid onset phase of flash droughts. Here, we present a comprehensive assessment of the onset development of flash droughts and the underlying mechanisms on a global scale. We find that 33.64−46.18% of flash droughts with 5-day onset of drying, and there is a significant increasing trend in the proportion of flash droughts with the 1-pentad onset time globally during the period 2000−2020. Flash droughts do not appear to be occurring more frequently in most global regions, just coming on faster. In addition, atmospheric aridity is likely to create a flash drought-prone environment, and the joint influence of soil moisture depletion and atmospheric aridity further accelerates the rapid onset of flash droughts.

Quantifying Spatial Drought Propagation Potential in North America Using Complex Network Theory

AbstractDroughts have a dominant three‐dimensional (3‐D) spatiotemporal structure typically spanning hundreds of kilometers and often lasting for months to years. Here, we introduced a novel framework to explore the 3‐D structure of the evolution of droughts based on network theory concepts. The proposed framework is applied to identify critical source regions responsible for large‐scale drought onsets during 1901–2014 for the North American continent using the Standardized Precipitation Evaporation Index (SPEI). We built a spatial network connecting the drought onset timings for the North American continent. Using a spatially weighted network partitioning algorithm, the whole continent is then classified into regional spatial drought networks (RSN), where droughts are more likely to propagate within these regional systems. Finally, a customized network metric was applied to identify locations (source regions) where the drought onsets further propagate to other areas within the regional spatial network. Our results indicated that the West coast, Texas coastal region, and Southeastern Arkansas as major source regions through which atmospheric drought propagates to Western, South Central, and Eastern North America. The formation of drought source regions are due to presence of high pressure ridges and anomalous wind patterns. Furthermore, our results indicate that the drought propagation from these source regions may be due to inadequate moisture transport. The proposed framework can help to develop an early warning detection system for droughts and other spatially extensive extreme events such as heatwaves and floods.

Reconstructing butterfly-pollen interaction networks through periods of anthropogenic drought in the Great Basin (USA) over the past century

Interactions between plants and insects dominate terrestrial biomes and are altered in response to global human-environmental change. Documenting such changes in complex interactions is challenging, however, because traditional methods for describing plant-insect interactions at community scales are often based on relatively short sampling periods. This paper investigates quantitative networks of pollen-insect interactions gleaned from adult Lepidoptera from long-term museum collections that helped to overcome the challenge of limited temporal resolution. The paper reports how richness and frequency of butterfly-pollen associations have changed over a 100-year time series (1910–2020) in the Great Basin of Nevada and California, USA. First, we examined changes in pollen richness for 19 butterfly species over five consecutive 20-year time periods. We pooled interaction networks associated with specimens captured before and after the onset of drought in 2000. In doing so, we estimated variation in pollen-pollinator interactions under anthropogenic drought periods in the Great Basin in the last two decades. Overall, pollen richness associated with butterflies declined slightly over the study period. The details depend on the species, however, where a few species experienced moderate declines in richness and two species exhibited small increases in pollen richness. Butterfly-pollen networks indicated specialization in most pollen-butterfly species interactions. They are apparently more reticulate than observational networks. Interaction networks associated with specimens captured before and after the year 2000 revealed that, compared to previous decades, butterfly-pollen networks over the past 20 years had higher connectivity and diversity of interactions. • Plant-pollinator interactions contribute substantially to biodiversity. • Moderately generalized networks are likely to provide ecosystem stability in the face of anthropogenic global change. • Pollen-butterfly interactions are changing in response to global change, especially more generalized interactions. • Most pollen-butterfly interaction networks are specialized, which could make them more susceptible to anthropogenic change. • Pollen diversity on Great Basin butterflies has declined over the past 100 years, concurrent with drought in the region.

Multivariate drought analysis for the temperature homogeneous regions of India: Lessons from the Gomati River basin

AbstractDroughts inflict significant loss on agricultural economies. Gomati River basin, the area of the present study, is located within the Ganga River floodplains, which approximately coincide with the north central temperature homogeneous region (NCTHR) of India. Gomati basin is a non‐perennial one supporting water intensive agricultural crops. To ascertain the occurrence of droughts (if any) from 1986 to 2015 within Gomati River basin, in terms of inter‐dependencies of drought causing variables through study of multivariate drought indices, is the main objective of the present study. Soil Water Assessment Tool (SWAT) was used in combination with the Copula approach to construct multivariate standardized drought indices (MSDIs) for drought onset detection through simulation in the face of data scarcity. Although MSDI based assessment of the basin as a whole did not detect any droughts, in the upper basin, MSDIs indicated the possibilities of impending agricultural droughts marked by their consistent variability aroundnear‐normalconditions. This methodology can be used to detect drought situations in data scarce non‐perennial river basins within the Ganga River floodplains including the NCTHR of India.