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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multivariate Drought Monitoring, Propagation, and Projection Using Bias-Corrected General Circulation Models

Understanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological-hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought-related consequences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts.

Drought↗
DOE OSTI2024

Season of drought affects growth, but not nonstructural carbohydrates dynamics, in Pinus taeda saplings

In temperate evergreen conifers, growth occurs mostly in summer but photosynthesis proceeds year-round; thus, nonstructural carbohydrates (NSCs) increase in winter but decrease in summer. Given that mild drought reduces growth but not photosynthesis, a drought in summer should increase NSCs more than one in winter. However, the active regulation hypothesis suggests that to increase future drought resilience, plants might downregulate growth to increase NSCs after a winter drought even if NSCs do not increase during the drought. To test whether this is so, potted Pinus taeda saplings (age year) were subjected to 6-month droughts in a greenhouse with one treatment receiving drought during winter (September–March), and another during summer (March–September). Here, both treatments were compared with a control. To measure dry biomass and NSCs, we harvested plants monthly following each drought, while to assess changes in growth rates, we measured height and diameter monthly. While we observed seasonal variation and an overall increase during the study, we found no drought-related changes in NSC dynamics; however, drought did reduce growth. Furthermore, drought in winter did reduce growth during the following summer, but the reduction was less than for a drought in summer. We conclude that the effect of drought on NSCs was too small to detect in our plants. While better control of soil water would have reduced a major source of uncertainty, plants with larger NSC reserves or more intense stress would also yield easier-to-detect effects. Although not definitive, our results suggest that water stress does not lead to dramatic changes in seasonal NSC dynamics in its aftermath, despite what one might expect under the active regulation hypothesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multi‐season analysis reveals hundreds of drought‐responsive genes in sorghum

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghum's remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1500 transcriptome profiles, across a 3-year field study with replicated plots in California's Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pangene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of 726 drought-responsive genes that responded similarly in all 3 years of our field study. Functional enrichment analysis identified abiotic stress, secondary cell wall-related processes and metabolism as particularly affected under both types of drought stress. We also found that some glyoxylate cycle pathway genes, including malate synthase and isocitrate lyase, are differentially regulated particularly during post-flowering drought stress, implicating this pathway as potentially important for drought responsiveness. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

Cole, Benjamin [USDOE Joint Genome Institute (JGI)↗
DOE OSTI2025

A Greening Future Elevates Flash Drought Risk in Northern Mid‐to‐High Latitudes

Flash droughts have become a growing concern, as they can emerge rapidly and increase the risk of crop failure. Although past studies have investigated the meteorological drivers and future changes of flash drought, why flash drought is more frequent over humid and vegetated regions remains underexplored. This study delves further into the mechanism by which vegetation regulates flash drought and its future change using observations from multiple data sets and large ensemble simulations from three Earth system models. On an interannual timescale, both observations and simulations show robust increases in flash drought frequency and a higher flash-to-sub-seasonal drought ratio during spring or antecedent conditions with dense vegetation, supporting the important role of vegetation in flash drought occurrence, especially in the northern mid-to-high latitudes. In the latter regions, the large ensemble simulations show robust increases in flash drought (e.g., 67% and 46% increases in Eastern U.S. and North Asia in 2050–2100 relative to 1950–2000 under the high emission scenario), where the growing season is lengthening. Although greening might suggest reduced drought stress, it drives precipitation-soil moisture-evapotranspiration decoupling by increasing evapotranspiration partitioning to transpiration. As transpiration can access deep soil water through the plant root system, its increased portion can weaken the constraints of concurrent precipitation on evapotranspiration, thus accelerating soil moisture depletion under high evaporative demand, driving a slow-to-rapid drought transition. How vegetation regulates flash drought by regulating surface moisture budget is supported by observations and simulations. Although warming supports early planting, agriculture may increasingly be threatened by surging flash drought risk.

Drought↗
DOE OSTI2023

FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration

Water systems worldwide are experiencing climate change-induced shifts in drought properties like frequency, intensity, and duration, affecting water security and reliability. To develop and test effective drought preparedness plans, researchers often use synthetic weather generators to create hydrological scenarios that explore drought variability beyond historical records. Existing weather generators typically allow users to adjust streamflow statistics like percentiles or temporal correlation but do not directly control drought properties of frequency, intensity, and duration. To fill this gap, we propose FIND (Frequency, INtensity, and Duration) synthetic weather generator. FIND incorporates a standardized drought index to directly and in dependently control drought frequency, intensity, and duration in generated streamflow time series while preserving observed hydrological variability. Use cases for FIND include i) water systems analysis applications that seek to train and test drought strategies under historical and plausible future drought conditions, and ii) bottom-up vulnerability studies relating system vulnerability outcomes to specific changes in drought properties of frequency, intensity, and duration. Here, we demonstrate FIND’s versatility through three experiments: replicating historically observed drought properties, generating streamflow scenarios for multiple sites preserving correlation between their drought conditions, and generating a set of scenarios with direct and independent changes in drought properties. FIND source code is openly available for applications beyond the scope of this paper.

42 ENGINEERING↗
DOE OSTI2023

Evolution of global snow drought characteristics from 1850 to 2100

Abstract Seasonal snow is an integral part of the global water supply and storage system. Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an early melt. The standardized SWE index (SWEI) ranks the current status of SWE for a given location compared to a baseline condition and identifies the existence, but not the cause, of snow drought. In this work, we use estimates of SWE, temperature, and precipitation from nine coupled model intercomparison project phase 6 (CMIP6) models to quantify the frequency, severity, and type of snow droughts globally for historical and future scenarios. Compared to a historical baseline (1850–1900) total snow drought frequency more than doubles under socio-economic pathway (SSP)2-4.5 and SSP5-8.5; all of the increase in snow drought frequency comes from an increase in warm droughts. The probability distribution of future SWEI in major snowy basins around the world are likely to be centered on more negative values, which corresponds to more severe drought and, with only moderate changes in distribution spread, more frequent drought. CMIP6 simulations pinpoint snow drought as an emerging global threat to water resources and highlight the need to explore higher resolution future models that better capture complex mountain topography, wildland fires, and snow-forest interactions.

CMIP6↗
DOE OSTI2025

Projected evolution of droughts and human exposure in the contiguous United States under SSP5-8.5: a regional downscaling perspective

The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.

CMIP6↗
DOE OSTI2023

Amazon drought resilience – emerging results point to new empirical needs

Will climate change turn tropical forests from a carbon sink to a source (Pan et al., 2011)? Tropical forests cycle more carbon, water, and energy than any other biome (Bonan, 2008). The Amazon is the largest tropical forest, spanning one-third of South America, and any perturbation in its function has repercussions on the global climate. Mild and severe droughts in the Amazon are predicted to double and triple in area, respectively, by 2100, while the area under wet extremes will increase (Duffy et al., 2015). Our understanding of the role of plants' hydrological environments in determining their drought response, however, is limited (Chitra-Tarak et al., 2018, 2021). An important review by Costa et al. (2023; pp. 714–733) published in this issue of New Phytologist highlights that shallow-water table (WT) forests constitute c. 50% of the Amazon and may act as hydrological refugia during droughts, yet they have been neglected in Amazon forest research to date. Emerging results suggest that the shallow-WT forests that dominate the Amazon basin may increase in productivity under moderate droughts due to relief from hypoxia, suggesting a potential buffer from drought relative to deeper WT forests (Fig. 1). During severe droughts, however, shallow-WT forests may be vulnerable to collapse due to drought-intolerant traits. Addressing the underrepresentation of relatively drought-resilient shallow-WT forests in the Amazon's forest inventories may help resolve the much-debated incongruence in recent studies of the Amazon's drought resilience. Data from forest inventories (biased toward deep-WT forests) indicate that the Amazon's carbon sink is declining, partially because of drought impacts (Phillips et al., 2009; Brienen et al., 2015), whereas basin-wide satellite-based measures of gross primary productivity, which include shallow-WT forests, indicate varied regional responses to droughts (Saleska et al., 2007; Brando et al., 2010). Costa et al.'s (2023) descriptive insights of the intricate balance of geology, topography, hydrology, vegetation, and drought on ecosystem function, as well as their conceptual predictive framework, are useful for developing new empirical research in these understudied ecosystems and improving Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Drought Drives Spatial Variation in the Millet Root Microbiome

Efforts to boost crop yield and meet global food demands while striving to reach sustainability goals are hindered by the increasingly severe impacts of abiotic stress, such as drought. One strategy for alleviating drought stress in crops is to utilize rootassociated bacteria, yet knowledge concerning the relationship between plant hosts and their microbiomes during drought remain under-studied. One broad pattern that has recently been reported in a variety of monocot and dicot species from both native and agricultural environments, is the enrichment of Actinobacteria within the drought-stressed root microbiome. In order to better understand the causes of this phenomenon, we performed a series of experiments in millet plants to explore the roles of drought severity, drought localization, and root development in provoking Actinobacteria enrichment within the root endosphere. Through 16S rRNA ampliconbased sequencing, we demonstrate that the degree of drought is correlated with levels of Actinobacterial enrichment in four species of millet. Additionally, we demonstrate that the observed drought-induced enrichment of Actinobacteria occurs along the length of the root, but the response is localized to portions of the root experiencing drought. Finally, we demonstrate that Actinobacteria are depleted in the dead root tissue of Japanese millet, suggesting saprophytic activity is not the main cause of observed shifts in drought-treated root microbiome structure. Collectively, these results help narrow the list of potential causes of drought-induced Actinobacterial enrichment in plant roots by showing that enrichment is dependent upon localized drought responses but not root developmental stage or root death.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Quantifying Climate and Catchment Control on Hydrological Drought in the Continental United States

The evolution of hydrological drought events is a result of complex (nonlinear) interactions between climate and catchment processes. To investigate such nonlinear relationship, we integrated a machine learning modeling framework based on the random forest (RF) algorithms with an interpretation framework to quantify the role of climate and catchment controls on hydrological drought. More particularly, our framework interprets a built RF machine-learning model to identify dominant variables and visualize their functional dependence and interaction effects on hydrological drought characteristics utilizing concepts of minimal depth, interactive depth, and partial dependence. We test our proposed modeling framework based on a set of 652 continental United States catchments with minimal human interference for a period of 1979–2010. Application of this framework indicated presence of three distinct drought regimes, which includes, Regime 1: droughts with longer duration, less frequent and lesser intensity; Regime 2: droughts with moderate duration, moderate frequency, and moderate intensity; and Regime 3: droughts with shorter duration, more frequent, and more intense. RF algorithm was able to accurately model the drought characteristics (intensity, duration, and number of events) for all the three drought regimes as a function of selected variables. It was observed that the type of dominant variables as well as their nonlinear functional relationship with hydrological droughts characteristics can vary between three selected regimes. Finally, our interpretation framework indicated that catchment characteristics have a significant role in controlling the hydrologic drought for catchments (regime 1), whereas both climate and catchment characteristics control hydrological drought in regimes 2 and 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling Isoprene Emission Response to Drought and Heatwaves Within MEGAN Using Evapotranspiration Data and by Coupling With the Community Land Model

We introduce two new drought stress algorithms designed to simulate isoprene emission with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) model. The two approaches include the representation of the impact of drought on isoprene emission with a simple empirical approach for offline MEGAN applications and a more process-based approach for online MEGAN in Community Land Model (CLM) simulations. The two versions differ in their implementation of leaf-temperature impacts of mild drought. For the online version of MEGAN that is coupled to CLM, the impact of drought on leaf temperature is simulated directly and the calculated leaf temperature is considered for the estimation of isoprene emission. For the offline version, we apply an empirical algorithm derived from whole-canopy flux measurements for simulating the impact of drought ranging from mild to severe stage. In addition, the offline approach adopts the ratio ($f$ PET ) of actual evapotranspiration to potential evapotranspiration to quantify the severity of drought instead of using soil moisture. We applied the two algorithms in the CLM-CAM-chem (the Community Atmosphere Model with Chemistry) model to simulate the impact of drought on isoprene emission and found that drought can decrease isoprene emission globally by 11% in 2012. We further compared the formaldehyde (HCHO) vertical column density simulated by CAM-chem to satellite HCHO observations. We found that the proposed drought algorithm can improve the match with the HCHO observations during droughts, but the performance of the drought algorithm is limited by the capacity of the model to capture the severity of drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗
DOE OSTI2021

Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition?

Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above –1, except for July (–1.27), August (–1.39) and September (–1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIF yield , VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIF yield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIF yield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R 2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. Finally, this study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reservoir Drought Resilience Under Future Warming Scenarios: Regional Disparities Across Heavily Regulated US Basins

Droughts across the U.S. have imposed substantial challenges to the management of water resources. Reservoir drought, one type of hydrological drought, is characterized by abnormally low reservoir storage levels, reflecting combined impacts of natural water shortages and water management practices. We investigate how reservoir drought signatures, particularly onset, severity, duration, recovery and frequency, may shift under rising temperatures, and how these shifts vary by reservoir typology and degree of regulation. By coupling atmosphere-land-river models with reservoir operations at ~12-km resolution, we simulated reservoir storage and characterized reservoir droughts across five heavily regulated U.S. basins. Our findings reveal significant regional and functional disparities in reservoir drought resilience under the scenario of rising temperatures. Reservoirs in the Texas-Gulf region are projected to become more resilient, while systems in the Upper Colorado and South Atlantic-Gulf regions face increased risk due to prolonged drought durations and slower recovery. With respect to primary function, reservoirs used for irrigation and hydropower, particularly those with smaller storage capacity and lower degrees of regulation, are most susceptible to future drought stress. These results are valuable in understanding water availability in highly regulated environments, and the influence of hydrometeorological conditions on storage dynamics. Overall, this study provides the first of its kind benchmark for reservoir droughts at a continental scale to support evolving multi-sectoral drought mitigation efforts. Future research is needed to link reservoir drought conditions to actual supply shortages across competing water uses, while leveraging existing adaptive management strategies and coordinated reservoir operations.

reservoir↗
DOE OSTI2025

Elucidating the drought-responsive changes in Poplar cuticular waxes: A GWAS analysis of genes involved in fatty acid biosynthesis

Drought and episodic drought events are major impending impacts of climate change, limiting the productivity of plants and especially trees due to their inherent high transpiration rates. One common mechanism used by plants to cope with drought stress is to change the composition of their leaf cuticular waxes. Cuticular waxes are essential for controlling non-stomatal water loss and are typically composed of a homologous series of very-long-chain fatty acid-derived compounds, as well as flavonoids, tocopherols, triterpenoids, and phytosterols. In this study, we compared the cuticular waxes of 339 natural accessions of Populus trichocarpa (black cottonwood) grown under control and drought conditions in a common garden. A Genome-Wide Association Study (GWAS) was then used to identify candidate genes associated with cuticular wax biosynthesis and/or its regulation. Although no major differences were observed in total wax load when subject to drought conditions, the amounts of the individual wax constituents were indeed responsive to drought. Specifically, changes in alkenes, alcohols, esters, and aldehydes were evident, and suggest that they contribute to the drought response/tolerance in poplar. GWAS uncovered several genes linked to fatty acid biosynthesis, including CER1, CER3, CER4, FATB, FAB1, FAR3, FAR4, KCS, and a homolog of SOH1, as well as other candidate genes that may be involved in coordinating the drought responses in poplar trees. Our findings provide new evidence that genotype-specific shifts in wax composition, rather than total wax accumulation, contribute to drought adaptation in poplar. Additionally, we show that genetic variation in key wax biosynthetic genes drives cuticular wax plasticity in P. trichocarpa under drought, identifying putative molecular targets for improving stress resilience in trees. This study expands our understanding of the adaptative mechanisms of the cuticle and their potential for enhancing drought tolerance in poplar species.

Alkanes↗
DOE OSTI2022

Comparative transcriptomics and metabolomics reveal specialized metabolite drought stress responses in switchgrass ( Panicum virgatum )

Summary Switchgrass ( Panicum virgatum ) is a bioenergy model crop valued for its energy efficiency and drought tolerance. The related monocot species rice ( Oryza sativa ) and maize ( Zea mays ) deploy species‐specific, specialized metabolites as core stress defenses. By contrast, specialized chemical defenses in switchgrass are largely unknown. To investigate specialized metabolic drought responses in switchgrass, we integrated tissue‐specific transcriptome and metabolite analyses of the genotypes Alamo and Cave‐in‐Rock that feature different drought tolerance. The more drought‐susceptible Cave‐in‐Rock featured an earlier onset of transcriptomic changes and significantly more differentially expressed genes in response to drought compared to Alamo. Specialized pathways showed moderate differential expression compared to pronounced transcriptomic alterations in carbohydrate and amino acid metabolism. However, diterpenoid‐biosynthetic genes showed drought‐inducible expression in Alamo roots, contrasting largely unaltered triterpenoid and phenylpropanoid pathways. Metabolomic analyses identified common and genotype‐specific flavonoids and terpenoids. Consistent with transcriptomic alterations, several root diterpenoids showed significant drought‐induced accumulation, whereas triterpenoid abundance remained predominantly unchanged. Structural analysis verified select drought‐responsive diterpenoids as oxygenated furanoditerpenoids. Drought‐dependent transcriptome and metabolite profiles provide the foundation to understand the molecular mechanisms underlying switchgrass drought responses. Accumulation of specialized root diterpenoids and corresponding pathway transcripts supports a role in drought stress tolerance.

transcriptomics↗