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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Near-Real-Time Statistical Analysis and Visualization of Streamflow from a Deep-Learning Rainfall-Runoff Model

Near-real-time (NRT) streamflow data are critical importance for timely water resources management. Here, we developed an open-source tool, FlowStats, for NRT streamflow analysis and visualization in Germany, based on NRT meteorological data from the German Weather Service and simulated streamflow from a long short-term memory neural network (LSTM). The LSTM model achieved very good overall performance, median NSE of 0.80 for the test period across 1,479 catchments. FlowStats provides options for deriving various streamflow statistics, from normal and abnormal streamflow detection to drought and flood analyses. An example analysis from FlowStats revealed widespread below-normal to extreme low-flow conditions across Germany from March to May 2025, which weakened from June to September 2025. Drought analysis for September 2025 highlighted severe to extreme drought conditions in northwestern Germany, while flood classifications indicated that high-flow events occurred in southwestern Germany. FlowStats can be used for various hydrological assessments to support water resources management.

Hydrological modeling↗
DOE OSTI2023

Soil management legacy interacts with wheat genotype to determine access to organic N in a dryland system

Organic nutrient management through the application of compost and/or cover crops provides mineralizable sources of nutrients for plants while often building soil organic matter (SOM) and various aspects of soil health. Variability in nutrient acquisition strategies between crop genotypes may confer advantages under different soil health contexts and could be important for crop selection and breeding, but crop response under field conditions remains unexplored. We investigated the ability of different genotypes of winter wheat (Triticum aestivum L.) to access nitrogen (N) from newly added cover crop residues in two soils with contrasting levels of SOM and biological activity. We planted three previously characterized wheat genotypes in a long-term dryland compost amendment field trial: 1) Byrd (modern, deep roots, low exudation), 2) Cheyenne (historic, drought susceptible, intermediate exudation), and 3) Snowmass (modern, drought-susceptible, high exudation). 15 N-labelled cover crop residue was added to each plot and traced into wheat tissue. In the low SOM soil, the high exudate genotype Snowmass and historic genotype Cheyenne took up the most residue-derived N (6.4–8.1 kg N ha −1 ) compared to the low-exudate genotype Byrd (4.4 kg N ha −1 ), suggesting a strong exudate effect in the more carbon-limited soil. However, in the high SOM soil, the low-exudate, deep rooted genotype, Byrd, took up the most residue N (4.6 kg N ha −1 vs. 2.8 and 3.3 hg N ha −1 for Cheyenne and Snowmass, respectively), which indicated higher native N cycling activities and greater importance of drought resistance. Enzyme activity, inorganic N, and microbial communities were not influenced by genotype, though did show strong effects of compost application legacy. Furthermore, our results show that belowground allocation strategies that favor microbial stimulation may be less successful under water limitation, especially when high native SOM and biological activity can support mineralization of residue N without added investment in root inputs. Increased soil health through SOM-building management likely enhances nutrient cycling, and may better support root strategies that invest less in microbial stimulation in favor of other limiting resources.

Compost↗
DOE OSTI2023

A coupled equilibrium boundary layer model with stable water isotopes and its application to local water recycling

The contribution of evapotranspiration (ET) to regional precipitation, known as “local water recycling”, is a key process in the water cycle that can affect water management. However, the amount of planetary boundary layer (PBL) moisture that arises from ET is highly uncertain due to complex atmosphere and land surface conditions. In this study, an idealized two-layer equilibrium boundary layer model was coupled with a stable water isotope module including HDO and H 2 18 O to constrain PBL growing season water transport processes. The model was validated using turbulent heat fluxes and isotope ratios of water vapor (δ m ) and precipitation (δ P ) measured at a cropland site and a nearby tall tower in the Upper Midwest, United States. The results show that the PBL equilibrium features of δ m and δ P are well-constrained by thermal and moisture equilibrium in the PBL. For this study region, the summer values of rain evaporation fraction (f) and local water recycling ratio (LRR) are estimated to be 0.09 and 0.29 ± 0.12, respectively. The summer LRR values for the years 2006–2010 were 0.35, 0.36, 0.17, 0.29, and 0.29, respectively. The small value of LRR in 2008 corresponded to a drought condition with the lowest precipitation and second lowest ET among the five years. The summer magnitude of the amount effect is –2.8‰ (mm day –1 ) –1 and –0.8‰ (mm day –1 ) –1 for HDO and H 2 18 O, respectively. The local water recycling is identified as a significant factor influencing the continental isotope effect. Cropland has likely changed the regional LRR by –7.6 to 19.5% under different pre-agriculture land use scenarios. In conclusion, the feedback processes revealed here indicate that local water recycling is expected to be weakened under drought conditions, but it will be enhanced if irrigation is applied more intensely with more frequent drought events as the climate continues to warm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Spatial access and resource limitations control carbon mineralization in soils

Core-scale soil carbon fluxes are ultimately regulated by pore-scale dynamics of substrate availability and microbial access. These are constrained by physicochemical and biochemical phenomena (e.g. spatial access and hydrologic connectivity, physical occlusion, adsorption-desorption with mineral surfaces, nutrient and resource limitations). We conducted an experiment to determine how spatial access and resource limitations influence core-scale SOM mineralization, and how these are regulated by antecedent moisture conditions. Intact soil cores were incubated at field-moist vs. drought conditions, after which they were saturated from above (to simulate precipitation) or below (to simulate groundwater recharge). Soluble C (acetate) and N (nitrate) forms were added to some cores during the rewetting process to alleviate potential nutrient limitations. Respiration showed evidence of C-limitation, as C amendments increased the cumulative CO 2 evolved. Drought and rewetting increased soil respiration, and these soils also exhibited increased complex aromatic molecules in porewater. This newly available substrate appeared to alleviate nutrient limitations on respiration, because there were no further respiration increases with subsequent C and N amendments. We expected that respiration would be influenced by wetting direction, as simulated precipitation would mobilize C from the surface. However, as a main effect, this response was seen only in the C-amended soils, indicating that surface-C may not have been bioavailable. At the pore scale (porewater samples), compared to the baseline soils, drought and the C, N amendments caused a net loss of identified molecules when the soils were rewet from below, whereas wetting from above caused a net increase in identified molecules. This indicates that as soils were wet from below, the fresh inputs simulated the C-and N-limited microbial populations present deeper in the soil profile. Furthermore, our experiment highlights the complex and interactive role of antecedent moisture conditions, wetting direction, and resource limitations in driving core-scale C fluxes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Seasonal and Long‐Term Groundwater Unloading in the Central Valley Modifies Crustal Stress

Abstract Changes in terrestrial water content cause elastic deformation of the Earth's crust. This deformation is thought to play a role in modulating crustal stress and seismicity in regions where large water storage fluctuations occur. Groundwater is an important component of total water storage change in California, helping to drive annual water storage fluctuations and loss during periods of drought. Here we use direct estimates of groundwater volume loss during the 2007–2010 drought in California's Central Valley obtained from high resolution Interferometric Synthetic Aperture Radar‐based vertical land motion data to investigate the effect of groundwater volume change on the evolution of the stress field. We show that GPS‐derived elastic load models may not capture the contribution of groundwater to terrestrial water loading, resulting in an underestimation of nontectonic crustal stress change. We find that groundwater unloading during the drought causes Coulomb stress change of up to 5.5 kPa and seasonal fluctuations of up to 2.6 kPa at seismogenic depth. We find that faults near the Valley show the largest stress change and the San Andreas fault experiences only ~40 Pa of Coulomb stress change over the course of a year from groundwater storage change. Annual Coulomb stress change peaks dominantly in the fall, when the groundwater level is low; however, some faults experience peak stress in the spring when groundwater levels are higher. Additionally, we find that periods of increased stress correlate with higher than average seismic moment release but are not correlated with an increase in the number of earthquakes. This indicates groundwater loading likely contributes to nontectonic loading of faults, especially near the Valley edge, but is not a dominant factor in modulation of seismicity in California because the amplitude of stress change declines rapidly with distance from the Valley. By carefully quantifying and spatially locating groundwater fluctuations, we will improve our understanding of what drives nontectonic stress and forces that modulate seismicity in California.

58 GEOSCIENCES↗
DOE OSTI2021

Investigating Vegetation Responses to Underground Nuclear Explosions Through Integrated Analyses

Vegetation has the potential to respond to underground nuclear explosions, yet these links have not been fully explored. Given the lack of previously described signatures, the changes in vegetation are possibly subtle. The integration of multiple different data streams is potentially a useful approach to improve signal detection. Here, we investigate whether semi-arid vegetation growth patterns responded to eight legacy underground nuclear tests at the Nevada National Security Site in southern Nevada, USA. We tested for spatial and temporal changes in vegetation cover, tree growth patterns, and tree leaf spectral properties using ground-based measurements, including those from tree-rings and hyperspectral surface vegetation reflectance, as well as space-based measurements of Normalized Difference Vegetation Index (NDVI) from Landsat. Multiple data streams suggest a localized (<1.2 km) spatial pattern whereby tree growth is enhanced closer to the source of the underground test relative to sites further away. We also observed a more regional (>1.2–9 km) pattern whereby tree growth is suppressed coincident with a drought beginning 1 year before the 1989 tests, but continuing in the 5 years following the tests, which is anomalous relative to what is expected based on the response of tree growth to previous droughts. furthermore, quantification of the relative effects of the tests on vegetation remains a challenge due to the coincident drought and the potential for other disturbances to have impacted tree growth at this time, but the integration of these data reveals a more nuanced growth response than any other one data set indicates alone.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US

Abstract Burned areas in the western US have increased ten‐fold since 1980s, which are attributable to multiple factors, including increasing heat, changing precipitation patterns, and extended drought. To better understand how these factors contribute to large fire emissions (gridded monthly fire emissions >95th percentile of all the fire emissions in the western US; 0.009 Gg/month), we build a machine learning model to predict fire emissions (PM 2.5 ) over the western US at 0.25° resolution, interpreted using explainable artificial intelligence (XAI). From the predictor contributions derived from XAI, we conduct k‐means clustering analysis to identify four clusters of predictor variables representing different drivers of large fire emissions. The four clusters feature the contributions of fuel load (Cluster 1) and different levels of dryness (Cluster 2–4), controlled by fuel moisture, drought condition, and fire‐favorable large‐scale meteorological patterns featuring high temperature, high pressure, and low relative humidity. In the past two decades, large fire emissions peak in summer. However, large fire emissions increased significantly in September and October in 2010–2020 relative to 2000–2009, extending the peak large fire emissions from summer to autumn. The larger enhancements of large fire emissions during autumn compared to summer are contributed by decreased fuel moisture, along with more frequent concurrent fire‐favorable large‐scale meteorological patterns and drought. These results highlight fuel drying as a common driver supported by multiple drivers, such as warmer temperature and more frequent synoptic patterns favorable for fires, in increasing the autumn risk of large fire emissions across the western US.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accounting for Changes in Radiation Improves the Ability of SIF to Track Water Stress-Induced Losses in Summer GPP in a Temperate Deciduous Forest

Global observations of solar-induced chlorophyll fluorescence (SIF) are available from multiple satellite platforms, and SIF is increasingly used as a proxy for photosynthetic activity and ecosystem productivity. Because the relationship between SIF and gross primary productivity (GPP) depends on a variety of factors including ecosystem type and environmental conditions, it is necessary to study SIF observations across various spatiotemporal scales and ecosystems. To explore how SIF signals relate to productivity over a temperate deciduous forest, we deployed a PhotoSpec spectrometer system at the University of Michigan Biological Station AmeriFlux site (US-UMB) in the northern Lower Peninsula of Michigan during the 2018 and 2019 growing seasons. We found that SIF correlated with GPP across diurnal and seasonal cycles (R 2 = 0.61 and 0.64 for 90-min- and daily-averaged data), but that SIF signals were more strongly related to downwelling radiation than GPP (R 2 = 0.91 for daily-averaged data). The dependence of SIF on radiation obscured the impact of intraseasonal drought in the SIF timeseries, but drought stress was apparent as a decrease in relative SIF, which exhibited a stronger correlation with GPP (R 2 = 0.56) than other remotely sensed data over the drought period. These results highlight the potential of SIF for detecting stress-induced losses in forest productivity. Additionally, we found that the red:far-red SIF ratio did not exhibit a response to water stress-induced losses in productivity, but was largely driven by seasonal and interannual changes in canopy structure, as well as by synoptic changes in downwelling radiation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Climatic Drivers for the Variation of Gross Primary Productivity Across Terrestrial Ecosystems in the United States

Abstract Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future.

Environmental Sciences & Ecology↗
DOE OSTI2023

No carbon storage in growth-limited trees in a semi-arid woodland

Plant survival depends on a balance between carbon supply and demand. When carbon supply becomes limited, plants buffer demand by using stored carbohydrates (sugar and starch). During drought, NSCs (non-structural carbohydrates) may accumulate if growth stops before photosynthesis. This expectation is pervasive, yet few studies have combined simultaneous measurements of drought, photosynthesis, growth, and carbon storage to test this. Using a field experiment with mature trees in a semi-arid woodland, we show that growth and photosynthesis slow in parallel as ψ pd declines, preventing carbon storage in two species of conifer (J. monosperma and P. edulis). During experimental drought, growth and photosynthesis were frequently co-limited. Our results point to an alternative perspective on how plants use carbon that views growth and photosynthesis as independent processes both regulated by water availability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The time since land-use transition drives changes in fire activity in the Amazon-Cerrado region

Abstract Deforestation and climate change are expected to alter fire regimes along the Cerrado-Amazon transition, one of the world’s most active agricultural frontiers. Here we tested the hypothesis that the time since land-use transition (age of frontier) and agricultural intensification also drive changes in the region’s fire regimes by reducing fire probability in both drought and non-drought years. We modeled fire probability as a function of the time since land-use transitions based on MapBiomas Project datasets from 1986 to 2020. We find that, while burned area declined as pasturelands aged and croplands advanced, deforestation abruptly increased fire activity before (Amazon: 4 years; Cerrado: 3 years) and after (Amazon: 8 years; Cerrado: 7 years) land clearing for pasture, especially in the Amazon. Additionally, the combination of ignition risk, drought, and air-dryness increased the likelihood of large extents of burned areas associated with deforestation. Incorporating frontier age as a proxy for governance in fire modeling is crucial, given the ecological implications of changing fire regimes despite declining rates of fire probability. Most importantly, protecting against deforestation and preserving native vegetation are vital.

Environmental Sciences & Ecology↗
DOE OSTI2024

Preserving isohydricity: vertical environmental variability explains Amazon forest water-use strategies

Abstract Increases in hydrological extremes, including drought, are expected for Amazon forests. A fundamental challenge for predicting forest responses lies in identifying ecological strategies which underlie such responses. Characterization of species-specific hydraulic strategies for regulating water-use, thought to be arrayed along an ‘isohydric–anisohydric’ spectrum, is a widely used approach. However, recent studies have questioned the usefulness of this classification scheme, because its metrics are strongly influenced by environments, and hence can lead to divergent classifications even within the same species. Here, we propose an alternative approach positing that individual hydraulic regulation strategies emerge from the interaction of environments with traits. Specifically, we hypothesize that the vertical forest profile represents a key gradient in drought-related environments (atmospheric vapor pressure deficit, soil water availability) that drives divergent tree water-use strategies for coordinated regulation of stomatal conductance (gs) and leaf water potentials (ΨL) with tree rooting depth, a proxy for water availability. Testing this hypothesis in a seasonal eastern Amazon forest in Brazil, we found that hydraulic strategies indeed depend on height-associated environments. Upper canopy trees, experiencing high vapor pressure deficit (VPD), but stable soil water access through deep rooting, exhibited isohydric strategies, defined by little seasonal change in the diurnal pattern of gs and steady seasonal minimum ΨL. In contrast, understory trees, exposed to less variable VPD but highly variable soil water availability, exhibited anisohydric strategies, with fluctuations in diurnal gs that increased in the dry season along with increasing variation in ΨL. Our finding that canopy height structures the coordination between drought-related environmental stressors and hydraulic traits provides a basis for preserving the applicability of the isohydric-to-anisohydric spectrum, which we show here may consistently emerge from environmental context. Our work highlights the importance of understanding how environmental heterogeneity structures forest responses to climate change, providing a mechanistic basis for improving models of tropical ecosystems.

Forestry↗
DOE OSTI2021

Root traits reveal safety and efficiency differences in grasses and shrubs exposed to different fire regimes

Plant roots are important components of terrestrial ecosystems, but little is known about how root traits differ between plant species or vary across space in natural ecosystems. In this study, we investigated how root traits vary across grasses and woody shrubs in a tallgrass prairie located in Manhattan, KS, USA. Specifically, were interested in understanding how anatomical traits vary across these different plant groups, across different depths in the soil, and also across multiple areas of tallgrass prairie that are burned at different frequencies. We compared traits that allow roots to use soil water efficiently and those that help roots persist through extended periods of drought. We found that woody roots exhibited traits that allow them to use water efficiently in shallow soils but persist through drought in deeper soil. Here, these traits may allow shrubs to transport water from shallow soils to deeper soil after large rain events and resist extended periods without rain when soils become dry, which may allow woody plants to successfully compete for water in less frequently burned, more diverse plant communities. Grasses had traits that allow them to use water efficiently but also tolerate drought in shallow soils, regardless of fire treatment. This unique trait combination likely gives grasses a competitive advantage over other tallgrass prairie plants across different fire regimes. Together, these results show that anatomical root traits can be used to enhance mechanistic understanding of plant functioning in dynamic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Engineering quantitative stomatal trait variation and local adaptation potential by cis‐regulatory editing

Summary Cis‐regulatory element editing can generate quantitative trait variation that mitigates extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed CRISPR/Cas9 approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter ofOsSTOMAGEN, a positive regulator of rice stomatal density. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild‐type stomatal density. This panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation and intrinsic water use efficiency in steady‐state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought‐responsive stomatal density reprogramming instomagenand two cis‐regulatory edited alleles was reduced. Collectively our data demonstrate that cis‐regulatory element editing can generate near‐isogenic trait variation that can be leveraged for establishing relationships between anatomy and physiology, providing a basis for optimizing traits across diverse environments.

Biotechnology & Applied Microbiology↗
DOE OSTI2024

Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths <8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Pantropical Tree Leaf Hydraulic Properties, 1986 - 2015

This data package contains leaf pressure-volume parameters (osmotic potential at full turgor, turgor loss point, bulk elastic modulus, and others). Data was obtained by combining new data I gleaned from original publications not already in the following compilations (after removing the extratropical data): Bartlett, M. K., Zhang, Y., Kreidler, N., Sun, S., Ardy, R., Cao, K., and Sack, L.: Global analysis of plasticity in turgor loss point, a key drought tolerance trait, Ecol Lett, 17, 1580-1590, 2014. Bartlett, M. K., Scoffoni, C., and Sack, L.: The determinants of leaf turgor loss point and prediction of drought tolerance of species and biomes: a global meta-analysis, Ecology Letters, 15, 393-405, 2012. Maréchaux, I., Bartlett, M. K., Sack, L., Baraloto, C., Engel, J., Joetzjer, E., Chave, J., and Kitajima, K.: Drought tolerance as predicted by leaf water potential at turgor loss point varies strongly across species within an Amazonian forest, Functional Ecology, 29, 1268-1277, 2015. Data are from natural tropical and subtropical forests or savannas and span rainfall gradients from deciduous dry tropical forests to everwet tropical forests, and come from countries all throughout the pantropics. The attached zip file contains data organized into three CSV files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Response Of Salt Intrusion In A Tidal Estuary To Regional Climatic Forcing (FVCOM Output for the baseline scenario)

Salinity distribution in a large tidal estuary is subject to estuarine adjustment under the influences of multiple physical drivers such as freshwater pulses and sea level rise, and is crucial to upstream water quality, aquaculture, and ecosystem functions of the estuary. To better understand the estuarine salinity response to climate change, the unstructured-grid Finite Volume Community Ocean Model was implemented to simulate the salt intrusion in the Delaware Bay Estuary. The model was first validated by multiple observational data sets and subsequently applied in an idealized setting to examine the response of salt front to freshwater pulses in high flow conditions, followed by a long-term drought condition supported by a multi-decadal streamflow drought analysis in the estuary. The model results showed that after the freshwater pulses the salt front location moved further upstream with sea level rise. Under the simulated long-term drought condition, the adjustment timescale of salt intrusion varies nonlinearly with sea level rise. With a significant increase in sea level rise, the adjustment timescale starts to decrease. This shift suggests a transition into a different regime where the estuary becomes more stratified, as indicated by an increasing bulk Simpson number with rising sea levels. These findings have been summarized into a journal manuscript. The data included in this information release request are FVCOM model output associated with the numerical simulations described in the journal manuscript.

Liu, Jinliang↗