In light of climate change, wildfires are concurrently becoming more frequent and devastating worldwide. Though we have a good understanding of fire frequency changes in the past using charcoal analysis, records of the characteristics of these fires, such as fire severity, are lacking. This limits our ability to model how fire severity responds to climate change. Boron isotopes in clay minerals show promise as a novel fire severity proxy, where increased 𝛿11B is correlated with higher fire severity. Through reacting boron leached from experimentally combusted plants with clays, we determine that the observed correlation with fire severity is likely caused by input of isotopically heavier boron from combusted leaves. In contrast, combusted barks lower the 𝛿11B of clays upon reaction. Despite the different results, in both experiments with barks and leaves, similar boron isotope fractionation is observed during boron adsorption onto clays, where the lighter 10B is preferentially adsorbed. Therefore, the different results are likely caused by the different boron isotope composition of leaves and barks, where leaves have a much higher 𝛿11B (~30 ‰) than bark (~9 ‰). Combustion temperature can also affect the 𝛿11B of clays: changes to the 𝛿11B of clays were observed only when reacting with bark combusted at >300 °C, or with leaves combusted at >550 °C. This could be because more boron can be leached into solution from materials combusted at higher temperatures, which in turn results in greater adsorption onto clays during reactions. Clays have higher 𝛿11B in soils affected by high severity fires that consume tree crowns, because these fires combust more leaves that then deposit their isotopically heavier boron content into the soil. This relationship could help complete our fire record and improve our ability to predict future fire characteristics.
Most studies on the impacts of extreme hydrometeorological events on hydrological processes have focused primarily on surface water systems rather than groundwater systems. This study explores and seeks to untangle the complex nature of groundwater dynamics and resilience across British Columbia (BC) in response to the 2021 heatwave-intensified drought and atmospheric rivers (ARs). Historically, there have been many episodic drought events along with substantially wet periods. However, 2021 marked an unprecedented year for the immediate co-occurrence of intense and extreme drought and deluge. This weather whiplash resulted in the lowest and highest groundwater levels on record for many wells across BC. The record meteorological drought, intensified by a 13-day heatwave in late June, affected the entire province and lasted for over 50 days in the south coast region. This was followed in November by the most intense ARs to make landfall on record in southwestern BC. Groundwater hydrograph anomalies for 2021 were computed relative to their short-term historical mean for 194 provincial observation wells across the province. The 2021 anomalies showed a limited but distinct range of responses to both the drought and ARs, and cluster into three response groups, largely associated with their respective hydroclimatic regime. Many coastal wells showed a strong response to drought; however, nearly all wells in the southern interior responded substantially, with groundwater levels significantly below their historical range by late summer. Presently, groundwater levels seem to have recovered across the province, especially on the coast. This resiliency is attributed in part to the ARs that made landfall since last year along with a particularly wet, La Niña winter. The majority of coastal wells showed a much stronger signal to the ARs compared to the interior or eastern BC wells, likely due to the more rapid and intense rainfall experienced in southwestern BC. Groundwater systems across BC were variably impacted by these hydrometeorological extremes, showcasing the need for focused and area-specific approaches to water allocation decisions in assuring sustainable withdrawal practices.
Temperature is a key physical variable in streams that controls rates of metabolic processes and oxygen availability, and therefore the suitability of aquatic ecosystems. During the summer low flow period, stream temperature can be moderated by contributions from cool water sources, such as groundwater discharge and higher elevation headwaters. However, the relative contribution of these cool water sources can be spatially and temporally varying, particularly in snowmelt-dominated, high-relief watersheds. In this study, in situ and remote sensing methods are used to measure the stream temperature along a low elevation section of the North Alouette River (British Columbia, Canada) that passes through a forested area and into an open agricultural area. The methods include temperature loggers placed at the stream surface and streambed interface, and thermal infrared images acquired using a drone and Landsat 8 and 9 satellites. The drone and in situ measurements of stream temperature show good agreement, while the satellite images show the same temperature distribution (cooler in the forested area and warmer downstream in the open agricultural area) but overall shifted temperatures. Areas of mixing of cool and warm waters are identified within the stream channel using the drone imagery. Waters samples analyzed for stable isotopes are used to identify the different source waters and estimate their relative contribution to stream temperature moderation. This fingerprinting is made possible by a precipitation isotope composition-elevation gradient in the catchment. The isotope data support the observations of mixing identified with the temperature data. Understanding of where and when cool water sources contribute to streamflow will be used to inform groundwater allocation decision-making, to ensure that groundwater pumping is minimized in areas where groundwater discharge is critical for moderating stream temperatures.
In the ocean, temperature extremes have adverse effects on precipitation patterns, sea level change, and migration/damage of ecosystems. It has been found that most species are more sensitive to extreme events like marine heatwaves (MHWs), implying the severe impacts of MHWs on ecology. These events are driven by various atmospheric and oceanic processes. In recent years, these extreme events are more frequent and intense globally and their increasing trend is expected to continue in the upcoming decades. They have the potential to devastate marine habitats, and ecosystems together with ensuing socioeconomic consequences. It recently attracted public interest and scientific researchers, which motivates us to analyze the recent MHW events in the Bay of Bengal region. we have isolated 107 MHW events (above the 90th percentile threshold) in this region of the Indian Ocean and investigated the variation in duration, intensity, and frequency of MHW events during our test period (1982-2021). Our study reveals that the average of three MHW events per year in the study region with an increasing linear trend of 1.11 MHW events per decade. In the analysis, we found the most intense event has a maximum intensity was 5.29°C (above the climatology mean), while the mean intensity was 2.03°C. In addition, we observed net heat flux accompanied by anticyclonic eddies to be the primary cause of these events. Also, an effort has been made to understand the relationship between climate modes, sea surface height, and the difference between evaporation and precipitation with the occurrence of MHW events.
The West African Monsoon (WAM) strongly drives precipitation variability and seasonality across continental West Africa and the tropical Eastern Atlantic. However, the evolution of the WAM in the late Cenozoic, in response to changes in vegetation, atmospheric CO 2 , orbital forcings, paleogeography, and orography as well as its teleconnections such as the mean location of the African Easterly Jet (AEJ), Tropical Easterly Jet (TEJ), SubTropical Jet (STJ), Inter-Tropical Discontinuity (ITD) and low-level westerly flow is not well constrained. We contribute to understanding past WAM dynamics by performing high-resolution, time-specific paleoclimate simulation using General Circulation Model ECHAM5. We focus our analysis on the migration and intensification of the WAM and its associated atmospheric thermodynamic structure which influence the rainfall seasonality and patterns across the Sahel, Guinea Coast, and Sahara regions.
The Government of India announced its commitment to reach net-zero greenhouse gas emissions by 2070 at the recent COP 26 summit. Modeling projections suggest that meeting this target would likely require substantial amounts of CO2 capture and storage (CCS) from large-point sources (LPS). Our analysis first reveals the key co-benefits for India in the adoption of CCS, viz. energy security, lower aggregate costs of carbon mitigation, higher resilience and lower stranded assets. For instance, we estimate that stranding of >100 GW and >70 GW of coal- and gas-fired power capacity could be avoided with the presence of CCS in the power sector mix.This analysis is further supplemented by our recent estimates on CO2 storage potential estimates in Indian geologic formations. Our results indicate that the storage capacity via enhanced oil recovery (EOR) is 1.2 GtCO2 after incorporating engineering and geologic constraints. Similarly, the storage capacity in unminable coal fields is estimated to be 3.5-6.3 GtCO2. Even though the combined storage potential in these formations is constrained, they should be actively considered within policy-making as they predominantly lie within areas of dense areas of LPS, thus creating possibilities of CCS hubs and clusters. In addition, 291 GtCO2 could be sequestered in saline aquifers and 97-316 GtCO2 in basalts; though, these values are subject to higher uncertainties. A number of saline aquifers may be characterized as having storage potential equivalent to several years of LPS emissions (>10 GtCO2) along with high storage feasibility.Our ongoing analysis attempts a more evolved approach towards source-sink mapping in India by combining the storage potential estimates with geospatial layers of LPS. Large power plants, which emit >20 MtCO2 annually, and high-purity CO2 sources such as refineries, are of particular interest. Preliminary source-sink mapping results show substantial clustering opportunities in eastern India, which has active coalbed methane extraction undertaken by five companies, and western India, with large industrial sources interspersed with EOR sites. The results of this analysis will also inform decision-makers on future LPS siting opportunities if a policy thrust on CCS is undertaken for meeting net-zero targets over the next two decades.
Onsite wastewater treatment systems (OWTSs), or septic tank systems, are commonly used throughout the United States and are generally effective at remediating wastewater. However, malfunctioning OWTSs can introduce excess nutrients (i.e., nitrogen and phosphorous) and pathogens (i.e., E. coli) into the environment. There is increasing evidence that OWTSs can be a significant, and potentially underestimated, nonpoint source (NPS) of pollution. Thus, the objectives of this research were to (1) develop a model to assess the pollution potential from OWTSs using GIS-based multi-criteria decision analyses (MCDA) and (2) evaluate the relationship between the pollution potential from OWTSs and water pollutants. This study was completed in the Choccolocco Creek watershed, Alabama. The main tributary in this watershed, the Choccolocco Creek, is an impaired waterbody due to elevated E. coli concentrations. An MCDA was developed to model the pollution potential from OWTSs using environmental and OWTS variables. Similarly, an OWTS site unsuitability analysis, that only included environmental variables, was used to predict where OWTS may poorly perform, if OWTS data are not accessible in other areas. Water samples were taken along Choccolocco Creek to measure nitrogen, phosphorous, and E. coli concentrations. Pollutant concentrations were correlated to modeled pollution potential from OWTSs and OWTS site unsuitability, to compare how the exclusion of OWTS data changes the results. Additionally, land cover distribution was correlated to pollutant concentrations to account for other potential NPSs of water pollution. All water pollutants were significantly, positively correlated to OWTS count. Additionally, E. coli and nitrogen concentrations were significantly, positively correlated to pollution potential from OWTSs. This suggests that OWTSs may contribute to water pollution within the watershed. Furthermore, the location of areas most probable to have OWTS pollution varied between models, highlighting the importance of accounting for OWTSs as a NPS of water pollution. The methods presented could be adapted for other watersheds and used to guide best watershed management practices.
The current contribution presents wintertime climatology from 2012 to 2020 of mixed-phase clouds and their radiative effects when coupled to the sea ice states. Measurements from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) at the North Slope Alaska (NSA) site in Utqiagvik, Alaska are being analyzed.Classification of cloud hydrometeors in the liquid, ice or mixed-phase states was primary determined by the Cloudnet algorithm, developed by the Finish Meteorological Institute, and applied to a set of ground-based remote sensing instruments from NSA . To evaluate the influence by sea ice, which plays an important role on the Arctic surface-atmosphere interaction, the statistics are separated into cases when clouds are coupled or decoupled to specific sea ice conditions, like presence of leads or polynyas in the vicinity of NSA .We found that clouds coupled to sea ice with presence of leads have shown distinguished features like the increase of total liquid content, lower cloud base heights and less ice content when compared to decoupled cases. Nevertheless, these results rely on Cloudnet accurately detecting cloud droplets within mixed-phase clouds. Arctic cloud radiative effects (CRE) have already been studied from short expeditions like the SHEBA campaign (Shupe et al., 2004) and middle-term ground observations in Barrow (Shupe et al., 2015) and Ny-Ålesund, Svalbard (Ebell et al., 2020). We extend similar CRE studies for 8 years during wintertime, where longwave up- and down-welling flux measurements from NSA are used to estimate surface net fuxes and other cloud radiative features for cases when clouds are coupled or decoupled to sea ice conditions and their sensitivity to different gradients of air-surface temperature when leads or polynyas are present.
United States Federal Emergency Management Agency provides model-output localized flood grids that are useful in characterizing flood hazards for properties located in the Special Flood Hazard Area (SFHA ─ areas expected to experience a 1% or greater annual chance of flooding). But these flood grids are often unavailable or fail to include return periods for particular applications, such as understanding flood risk of properties during the 70-year useful building life cycle. Furthermore, due to the unavailability of higher-return-period flood grids, the flood risk of properties located outside the SFHA cannot be quantified. Here, we present a method to estimate the flood hazard for U.S. properties that are located both inside and outside the SFHA. The flood hazard is characterized by the Gumbel extreme value distribution to project flood elevations to extreme flood events for which an entire area is assumed to be submerged. Spatial interpolation techniques impute elevation values in the extreme flood elevation surfaces and therefore can estimate the flood hazard for areas outside the SFHA. The proposed method can improve the assessment of flood risk for properties located in both inside and outside the SFHA and therefore, the decision-making process regarding flood insurance purchases, mitigation strategies, and long-term planning for enhanced resilience to one of the world’s most ubiquitous natural hazards.
ORCiD: https://orcid.org/0000-0003-4699-3733 Rootstocks are gaining importance in viticulture as a strategy to combat abiotic challenges, as well as enhancing scion physiology and attributes. Therefore, understanding how the rootstock affects photosynthesis is insightful for genetic improvement of either genotype in the grafted grapevines. Photosynthetic parameters such as maximum rate of carboxylation of RuBP (Vcmax) and the maximum rate of electron transport driving RuBP regeneration (Jmax) has been identified as ideal targets for breeding and genetic studies. However, techniques used to measure these photosynthetic parameters are time consuming and subjective to leaf level which is complex to implement at field scale. Hyperspectral remote sensing uses the optical properties of the entire vine to predict photosynthetic capacity at canopy level. In this study, estimates of Vcmax and Jmax were assessed using different machine learning models: PLS (Partial least Squares), LR (Least Angle Regression), LASSO (Least Absolute Shrinkage and Selection Operator), PCR (Principle Component Regression) based on leaf reflectance metrics obtained with hyperspectral wavelength ranging from 400 to 1000nm. Prediction models were developed for six different rootstock genotypes with common scion Marquette considering three different sampling dates carried out in Brookings, South Dakota in 2021. Preliminary results indicate that each rootstock has distinctly different Vcmax and Jmax profiles across the season. From the model assessment, PLS was found to have robust prediction of Vcmax with R2 of 0.53 and for Jmax with R2 of 0.63. Multiple year trials will be used to validate precise and rapid quantification of photosynthesis using hyperspectral remote sensing.
Root exudation refers to the processes by which plants release compounds called root exudates into the soil. These exudates are primarily carbon-containing compounds that interact with microbial communities in the rhizosphere. Microbial consumption of exudates reduces the concentration of the exudated compounds in the soil, causing the plant to exude more of those compounds. Currently, there is limited understanding of the interaction between plant-root exudation mechanisms and the surrounding microbial communities. Among the Sorghum Association Panel (SAP), an established and genetically characterized sorghum diversity panel, we observed a spectrum of root colors (tan, yellow, red, purple-brown, black) identical to the range of observed sorghum seed colors. Previous studies examining differentially expressed metabolites between colorful seeds showed that flavonoids and anthocyanins were higher in dark seeds than white seeds. Root color is genotype-dependent and consistent over time. We hypothesized that the observed color diversity of sorghum roots was due to differential metabolite profiles in the root exudates across genotypes. We designed an experiment to collect exudates from 15 genotypes (n=60). After three weeks of growth, sorghum roots were washed and submerged in ultrapure water for 24 hours. The hydroponic solution was filtered and incubated with methanol. The whole root system was also ground after exudation. The root exudate solutions and the ground-up roots underwent either HILIC and RPLC analysis to separate and detect polar and hydrophobic metabolites. Through metabolite profiling of root exudates, we aim to identify sorghum genotypes that more efficiently allocate carbon below ground via their root systems.