Hyperspectral remote sensing is thought to be a useful technology for assessing the condition of inland waters. However, non-optically active water quality parameters are rarely explored in hyperspectral remote sensing applications, despite they are highly valued in the aquatic environment condition. This study intends to evaluate the performance of non-optically active water quality parameters using Zhuhai-1 hyperspectral imagery. Focusing on total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH3-N) and nitrate-nitrogen (NO3-N) in Taipu River, we constructed empirical models to evaluate the precision of water quality inversion from OHS by comparing with Sentinel-2, and determined the sensitive bands of different water quality parameters. The final results showed that the polynomial model based on OHS had the greatest potential in retrieving TN, TP and NH3-N concentration, and the R2 was 0.9678, 0.7924, 0.7682 respectively. The combination of R(510)/R(820) and R(700)/R(806), R(940)/R(820) and R(806)/R(926), R(709)/R(806) and R(746)/R(620) were most sensitive to TN, TP and NH3-N respectively. The OHS and Sentinel-2 both had potential in retrieving NO3-N. The R2 was 0.9791 from OHS and was 0.9513 from Sentinel-2. The sensitive bands of NO3-N were R(596)/R(665) and R(466)/R(580) from OHS, and Red Eage3/Blue and SWIR1/Blue from Sentinel-2. We also analyzed the drivers of the spatial distribution of water quality in Taipu River, the results showed negative impacts of farmland and urban land on water quality, and beneficial impacts of forest land on water quality. This study represented a promising step in hyperspectral remote sensing for retrieving inland non-optically active water quality parameters utilizing Zhuhai-1.
Interactions between atmospheric aerosols and ozone have a significant impact on air pollution and the climate. However, the relative importance of the response of surface ozone to aerosol scattering and absorption has been poorly quantified from in situ observations. Results derived from a one-year in situ observational study conducted in a semi-arid region showed that the response of ozone to aerosol absorption was more sensitive than to scattering. Specifically, the change in surface ozone from low to high absorption coefficients was approximately five times that from low to high scattering coefficients. The mass scattering and absorption efficiencies, rather than the single-scattering albedo, which are commonly applied in numerical simulations, were able to clearly distinguish surface ozone. The positive correlation between aerosol and ozone in summer showed the promotion of secondary aerosols by ozone. This study provides robust observational evidence of the response of surface ozone to aerosol scattering and absorption.
Developing actionable early detection and warning systems for agricultural stakeholders is crucial to reduce the annual \$200B USD losses and environmental impacts associated with crop diseases. Agricultural stakeholders primarily rely on labor-intensive, expensive scouting and molecular testing to detect disease. Spectroscopic imagery (SI) can improve plant disease management by offering decision-makers accurate risk maps derived from Machine Learning (ML) models. However, training and deploying ML requires significant computation and storage capabilities. This challenge will become even greater as global scale data from the forthcoming Surface Biology \& Geology (SBG) satellite becomes available. This work presents a cloud-hosted architecture to streamline plant disease detection with SI from NASA’s AVIRIS-NG platform, using grapevine leafroll associated virus complex 3 (GLRaV-3) as a model system. Here, we showcase a pipeline for processing SI to produce plant disease detection models and demonstrate that the underlying principles of a cloud-based disease detection system easily accommodate model improvements and shifting data modalities. Our goal is to make the insights derived from SI available to agricultural stakeholders via a platform designed with their needs and values in mind. The key outcome of this work is an innovative, responsive system foundation that can empower agricultural stakeholders to make data-driven plant disease management decisions, while serving as a framework for others pursuing use-inspired application development for agriculture to follow that ensures social impact and reproducibility while preserving stakeholder privacy.
The mid-ocean ridge system comprises a series of spreading ridges, transform faults, propagating ridges, and other non-transform offsets. Transform faults remain stable for millions of years leaving long linear scars, or fracture zones, on older seafloor. Propagating ridges migrate in the ridge parallel direction leaving V-shaped or W-shaped scars on older seafloor. Vertical gravity gradient (VGG) maps can now resolve the details of the ridge segmentation. For slow- and intermediate-spreading ridges, there appears to be an offset length threshold above which adjacent ridges do not propagate so remain as stable transform faults. We propose this threshold is due to the yield strength of the lithosphere, and we develop a model framework based on a force balance wherein forces driving propagation must exceed the integrated shear strength of the offset zone. We apply this model framework to 4 major propagating ridges, 55 seesaw propagating ridges, and 70 transform faults. The model correctly predicts the migration of major propagating ridges and the stability of transform faults, but the results for SSPs are less accurate. Model predictions for direction of ridge propagation are mixed as well. This model framework simplifies deformation in the shear zone, but can possibly explain why non-transform deformation is preferred at short offsets.
The interaction of the northern Nazca and southwestern Caribbean oceanic plates with South America, and the collision of the Panama-Choco arc have significant implications on the evolution of the northern Andes. We integrate an alternative interpretation of the Nazca and Caribbean kinematics with the magmatic and deformation history in the region. The northeastward migration of the Caribbean plate caused a progressive change in the geometry of the subducting Farallon plate, causing flat-slab subduction throughout the late Eocene-late Oligocene, inhibition of magmatism and eastward migration of the Andean deformation. Meanwhile, the Paleocene-Eocene highly oblique convergence of the Caribbean plate against South America changed by the mid-Eocene, when the Caribbean plate began to migrate in an easterly direction. These events and the late Oligocene breakup of the Farallon plate, prompted a Miocene plate reorganization, with further plate fragmentation, changes in convergence obliquity, steepening of the subducting slabs and renewal of magmatism. This tectonics was complicated by the accretion of the Panama-Choco arc to South America, which was characterized by early Miocene subduction erosion of the forearc and trench advance, followed by breakoff of the subducting slab east of Panama and collisional tectonics from the middle Miocene. By 9 Ma the Coiba and Malpelo microplates were attached to the Nazca plate, resulting in an abrupt change in convergence directions, that correlates with the main pulse of Andean orogeny. During the late Pliocene, the Nazca slab broke, triggering the modern volcanism south of 5.5º N. Seismicity data and tomography support the proposed reconstruction.
The Indian plate underthrusting the Himalaya is considered to be segmented along the collision belt arc and seismic images of the Indian mantle lithosphere (IML) suggest along-arc variations in the angle of underthrusting and its northern limit beneath Tibet. The pre-existing transverse tectonic structures of the Indian plate mapped in the Ganga foreland basin have been related to these segmentation boundaries. These segmentations imply changes in mechanical properties of adjoining blocks which should manifest in the form of spatial variations in topography build-up. We have analysed a geomorphic index, normalized channel steepness (ksn), along the Himalayan arc using the ALOS elevation dataset to test whether there is any correlation between the and these segmentation boundaries. Our results bring out spatial variability in the along the arc. Based on these results, the arc can be segmented into five blocks, similar to the ones delineated based on correlation between the width of the Ganga foreland basin and the disposition of major Himalayan thrusts from the foothills. Thus, the can be used as a proxy to demarcate different tectonic blocks along the Himalayan arc. Further, we have found a good correlation between the basin width and the northern limit of the IML for all block except the Uttarakhand block. We infer that transverse crustal heterogeneities in this block due to the continuation of different litho-units of the Aravalli-Delhi Fold Belt could be a plausible cause for this anti-correlation.
Zagros Orogeny System resulted due to collision of the Arabian with Eurasia. The region has the ocean-continent subduction and continent-continent collision; and convergence velocity shows variation from east to west. Therefore, this region shows the complex tectonic stress and a wide range of diffuse or localized deformation between both plates. The in-situ stress and GPS data are very limited in this region, therefore, we performed a numerical simulation of the stresses causing deformation in the Zagros-Iran region. The deviatoric stresses resulting from the variations in lithospheric density and thickness; and those from shear tractions at the base of lithosphere due to mantle convection were computed using thin-sheet approximation. Surface observations of strain rates, SHmax, plate velocities etc. are explained using the joint models of lithosphere and mantle, suggesting a good coupling between lithosphere and mantle in most parts of Zagros and Iran. However, the deformation in east of Iran is caused primarily by lithospheric stresses. Plate motion of Arabian plate is found to vary along the Zagros belt from north-northeast in south-east of Zagros, north in central Zagros to slight northwest in northwestern Zagros. The output of this study can be used in seismic hazards estimations.
Aeolian processes on Mars form a distinct class of meter-scale ripples, whose mechanisms of formation are debated. We present a global morphometric survey of bedforms on Mars, adding relevant observational constraints to the ongoing debate. We show that the bedforms located in the Tharsis region form a distinct group, not akin to the large dark-toned ripples which cover dune fields elsewhere on the planet. The relation between wavelength and atmospheric density derived from the new data is consistent with the predictions of a wind-drag mechanism, favoring the model that uses a saltation saturation length. Regardless of the mechanism that limits the size of bedforms, these results confirm the existence of a robust relationship between the wavelength of large ripples and atmospheric density (ripples spacings increases with decreasing atmospheric density). This provides further support to the interpretation of paleoatmospheric conditions on Mars through the analysis of its aeolian sedimentary record.
Entrainment of dry moat air with low equivalent potential temperature laterally into the eyewall and rainbands is a unique turbulent process in the inner-core region of a tropical cyclone (TC). By analyzing in-situ aircraft measurements collected by the reconnaissance flights that penetrated the eyewalls and rainbands of Hurricanes Rita (2005), Patricia (2015), Harvey (2017), and Michael (2018), as well as numerical simulations of Hurricanes Patricia (2015) and Michael (2018), we show that the moat air entrained into the eyewall and rainbands meets the instability criterion, and therefore, sinks unstably as a convective downdraft. The resultant positive buoyancy fluxes are an important source for the turbulent kinetic energy (TKE) in the eyewall and rainband clouds. This mechanism of TKE generation via lateral entrainment instability should be included in the TKE-type turbulent mixing schemes for a better representation of turbulent transport processes in numerical forecasts of TCs.
A budget approach is used to disentangle drivers of the seasonal mixed layer carbon cycle at Station ALOHA (A Long-term Oligotrophic Habitat Assessment) in the North Pacific Subtropical Gyre (NPSG). The budget utilizes data from the WHOTS (Woods Hole - Hawaii Ocean Time-series Site) mooring, and the ship-based Hawai‘i Ocean Time-series (HOT) in the North Pacific Subtropical Gyre (NPSG), a region of significant oceanic carbon uptake. Parsing the carbon variations into process components allows an assessment of both the proportional contributions of mixed layer carbon drivers, and the seasonal interplay of drawdown and supply from different processes. Annual net community production reported here is at the lower end of previously published data, while net community calcification estimates are 4- to 7-fold higher than available sediment trap data, the only other estimate of calcium carbonate export at this location. Although the observed seasonal cycle in dissolved inorganic carbon (DIC) in the NPSG has a relatively small amplitude, larger fluxes offset each other over an average year, with major supply from physical transport, especially lateral eddy transport throughout the year and entrainment in the winter, and biological carbon uptake in the spring. Gas exchange plays a smaller role, supplying carbon to the surface ocean between Dec-May, and outgassing in Jul-Oct. Evaporation-precipitation (E–P) is variable with precipitation prevailing in the first- and evaporation in the second half of the year. The observed total alkalinity signal is largely governed by E–P, with a somewhat stronger net calcification signal in the wintertime.
We studied atmospheric methane observations from November 2016 to October 2017 from one rural and two urban towers in the Baltimore-Washington region (BWR). Methane observations at these three towers display distinct seasonal and diurnal cycles with maxima at night and in the early morning, reflecting local emissions and boundary layer dynamics. Peaks in winter concentrations and vertical gradients indicate strong local anthropogenic wintertime methane sources in urban regions. In contrast, our analysis shows larger local emissions in summer at the rural site, suggesting a dominant influence of wetland emissions. We compared observed enhancements (mole fractions above the 5th percentile) to simulated methane enhancements using the WRF-STILT model driven by two EDGAR inventories. When run with EDGAR 5.0, the low bias of modeled versus measured methane was greater (ratio of 1.9) than the bias found when using the EDGAR 4.2 emission inventory (ratio of 1.3). However, the correlation of modeled versus measured methane was stronger (~1.2 times higher) for EDGAR 5.0 compared to results found using EDGAR 4.2. In winter, the inclusion of wetland emissions using WETCHARTs had little impact on the mean bias, but during summer, the low bias for all hours using EDGAR 5.0 improved by from 63 to 23 nanomoles per mole of dry air or parts per billion (ppb) at the rural site. We conclude that both versions of EDGAR underestimate the regional anthropogenic emissions of methane, but version 5.0 has a more accurate spatial representation.
First-ever measurements of the turbulent kinetic energy (TKE) dissipation rate in the northeastern Strait of Magellan (Segunda Angostura region) taken in March 2019 are reported here. At the time of microstructure measurements, the magnitude of the reversing tidal current ranged between 0.8 and 1.2 ms-1. The probability distribution of the TKE dissipation rate in the water interior above the bottom boundary layer was lognormal with a high median value εmed =1.2x10-6 Wkg-1. Strong vertical shear, (1-2)x10-2 s-1 in the weakly stratified water interior ensued a sub-critical gradient Richardson number, Ri<10-1-10-2. In the bottom boundary layer (BBL), the vertical shear and the TKE dissipation rate both decreased exponentially with the distance from the seafloor ζ, leading to a turbulent regime with the eddy viscosity KM~10-3 m2/s, which varied with the time and location, while being independent of the vertical coordinate in the upper part of BBL (for ζ>~2 meters above the bottom).
Typical mining operations can induce microseismicity and in some cases can result in the occurrence of moderate to large events, which is an expected but not always fully understood phenomenon. To assess the safety and efficiency of mining operations, operators must quantitatively discern between normal and abnormal seismic activity. In this work, statistical aspects and clustering of induced microseismicity from a potash mine in Saskatchewan, Canada, are analyzed and quantified. Specifically, the frequency-magnitude statistics display a rich behavior that deviates from the standard Gutenberg-Richter scaling for small magnitudes. To model the magnitude distribution, we consider two additional models, i.e. the tapered Pareto distribution and a mixture of the tapered Pareto and Pareto distributions to fit the bi-modal catalog data. We also observe deviations from the Poisson statistics on short-time scales that are primarily driven by mining operations. To study the clustering aspects of the observed microseismicity, the nearest-neighbor distance (NND) method is applied. This allowed us to identify characteristics of the clusters of micro-events and to analyze their structure in space, time and magnitude domains. The implemented modeling approaches and obtained results can be used to further advance strategies and protocols for the safe and efficient operation of potash mines.
Injection or production of fluids from subsurface reservoirs lead to stress changes affecting both reservoir and surrounding rocks. For low-permeable caprocks overlying such reservoirs, the movement of pore fluids to or from the formation is restricted and the immediate and short-term response to changes in the stress field will be undrained. Consequently, stress changes transfer partly into pore pressure changes. The aim of the current study is to investigate theoretical means of forecasting the undrained pore pressure generation in the Draupne Formation shale and to compare predictions with experimental results. Predictions are based on measurements from a single undrained triaxial test on a sample with known orientation, and a combination of Skempton's classical formulation and anisotropic poroelastic theory. The predicted pore pressures are compared to measured pore pressures from a series of triaxial tests on samples with various orientations exposed to different total stress paths. First, it is confirmed that the normalized undrained pore pressure measured is linearly connected to the total stress path. Then it is demonstrated that a tensorial pore pressure parameter can be used to accurately predict the influence of stress orientation on generated pore pressure. Lastly, it is experimentally confirmed that the two predictions can be combined to predict the pore pressure arising from stress changes along any compressional stress path and orientation. The observations herein may contribute significantly to the understanding of induced pore pressure in low-permeable materials and provide valuable input to geomechanical modeling of various field operations.
The Icelandic mantle contains a range of lithologies associated with the depleted upper mantle, a mantle plume, and recycled oceanic lithosphere but the precise nature of depleted and enriched components in the mantle and their relative contributions to melt production remain poorly constrained. In this study, we collect new olivine- and plagioclase-hosted melt inclusion data and compile this with existing literature data to investigate the relative contributions from different mantle lithologies to basaltic magmas erupted in Icelandic flank zones and neovolcanic zones by modelling the melting of a heterogeneous mantle and subsequent mixing of derived melts. We find that observed melt inclusion compositions from off-axis flank zones are best explained as homogenized mixtures of pyroxenite- and lherzolite-derived melts produced at depths around 80-93 km, by which point lherzolite has only experienced a low degree of melting whereas the pyroxenite lithology has melted extensively. These melts represent the onset of channelization in the mantle and are transported rapidly to the surface without input from shallower melts. Melt compositions from the on-axis neovolcanic zones and off-axis Öræfajökull, are produced by mixing this deep melt component with higher degree lherzolite melts produced at shallower depths, between 57-93 km. Proportions of shallow lherzolite-derived melts and deep homogenized melt vary, but the lowest contribution from the deep homogenized melt is seen in the Northern Volcanic Zone. Ourresults support a model whereby deep melts mix until melt channelization starts in the mantle, after which binary mixing between the homogenized deep melt and shallower fractional melts occurs.
The total meridional heat transport (MHT) is relatively stable across different climates. Nevertheless, the strength of individual processes contributing to the total transport are not stable. Here we investigate the MHT and its main components especially in the atmosphere, in five coupled climate model simulations from the Deep-Time Model Intercomparison Project (DeepMIP). These simulations target the Early Eocene Climatic Optimum (EECO), a geological time period with high CO2 concentrations, analogous to the upper range of end-of-century CO2 projections. Preindustrial and early Eocene simulations at a range of CO2 levels (1x, 3x and 6x preindustrial values) are used to quantify the MHT changes in response to both CO2 and non-CO2 related forcings. We found that atmospheric poleward heat transport increases with CO2, while the effect of non-CO2 boundary conditions (e.g., paleogeography, land ice, vegetation) is causing more poleward atmospheric heat transport on the Northern and less on the Southern Hemisphere. The changes in paleogeography increase the heat transport via transient eddies at the mid-latitudes in the Eocene. The Hadley cells have an asymmetric response to both the CO2 and non-CO2 constraints. The poleward latent heat transport of monsoon systems increases with rising CO2 concentrations, but this effect is offset by the Eocene topography. Our results show that the changes in the monsoon systems’ latent heat transport is a robust feature of CO2 warming, which is in line with the currently observed precipitation increase of present day monsoon systems.
Light-absorbing impurities such as mineral dust can play a major role in reducing the albedo of snow surfaces. Particularly in spring, deposited dust particles lead to increased snow melt and trigger further feedbacks at the land surface and in the atmosphere. Quantifying the extent of dust-induced variations is difficult due to the high variability in the spatial distribution of mineral dust and snow. We present an extension of a fully coupled atmospheric and land surface model system to address the impact of mineral dust on the snow albedo across Eurasia. We evaluated the short-term effects of Saharan dust in a case study. To obtain robust results, we performed an ensemble simulation followed by statistical analysis. Mountainous regions showed a strong impact of dust deposition on snow depth. We found a mean significant reduction of -1.4 cm in the Caucasus Mountains after one week. However, areas with flat terrain near the snow line also showed strong effects despite lower dust concentrations. Here, the feedback to dust deposition was more pronounced as increase in surface temperature and air temperature. In the region surrounding the snow line, we found an average significant surface warming of 0.9 K after one week. This study shows that the impact of mineral dust deposition depends on several factors. Primarily, these are altitude, slope, snow depth, and snow cover fraction. Especially in complex terrain, it is therefore necessary to use fully coupled models to investigate the effects of mineral dust on snow pack and the atmosphere.
The present study focuses on quantifying the impact of the choice of spatio-temporal resolution and hydrology models on the projection of extreme flow and their link to the catchment size. We use two process-based distributed hydrology models forced with a large-ensemble regional climate model (50-member ClimEx dataset) over the 1990-2100 period at different spatio-temporal scales. The extreme summer-fall flow corresponding with each spatio-temporal resolution was extracted by pooling the members together and computing the empirical cumulative distribution function. The results show that by refining the time-step from daily to sub-daily, the summer-fall extreme flow projected over the future period exceeds that of the reference period for the small but not large catchments. By increasing the catchment size, the hydrology model’s contribution to the variability of extreme flow increases. Moreover, the choice of spatial resolution affects the extreme flow’s trend in terms of magnitude, significance, and direction. But no pattern regarding the catchment size and spatial discretization variations exists.