Global food systems rely on irrigated agriculture, and most of these systems in turn depend on fresh sources of groundwater. In this study, we demonstrate that groundwater development, even without overdraft, can transform a fresh, open basin into an evaporation dominated, closed-basin system, such that most of the groundwater, rather than exiting via stream baseflow and lateral subsurface flow, exits predominantly by evapotranspiration from irrigated lands. In these newly closed hydrologic basins, just as in other closed basins, groundwater salinization is inevitable because dissolved solids cannot escape, and the basin is effectively converted into a salt sink. We first provide a conceptual model of this process, called “nthropogenic asin losure and groundwater inization” (ABCSAL). We then examine the temporal dynamics of ABCSAL using the Tulare Lake Basin, California, as a case study for a large irrigated agricultural region with Mediterranean climate, overlying an unconsolidated sedimentary aquifer system. Even with modern water management practices that arrest historic overdraft, results indicate that shallow aquifers (36 m deep) exceed maximum contaminant levels for total dissolved solids on decadal timescales. Intermediate (132 m) and deep aquifers (187 m), essential for drinking water and irrigated crops, are impacted within two to three centuries. Hence, ABCSAL resulting from groundwater development in agricultural regions worldwide constitutes a largely unrecognized constraint on groundwater sustainable yield on similar timescales to aquifer depletion, and poses a serious challenge to global groundwater quality sustainability, even where water levels are stable.

Because remote sensing (RS) data are spatially and temporally explicit and available across the globe, they have the potential to be used for predicting runoff in ungauged or poorly gauged catchments, a challenging area of research in hydrology over the last several decades. There is potential to use remotely sensed data for calibrating hydrological models in regions with limited streamflow gauges. This study conducts a comprehensive investigation on how to incorporate gridded remotely sensed-evapotranspiration (AET) and water storage data for constraining hydrological model calibration in order to predict daily and monthly runoff in 30 catchments of Yalong River basin, China. To this end, seven RS data calibration schemes are explored, compared to traditional calibration against observed runoff and traditional regionalization using spatial proximity. Our results show that using bias-corrected remotely sensed AET (bias-corrected PML-AET data) for constraining model calibration performs much better than using the non bias-corrected remotely sensed AET data (non bias-corrected AET obtained from PML model estimate). Using the bias-corrected PML-AET data in a gridded way is much better than that in a lumped way, and outperforms the traditional regionalization approach especially at upstream and large catchments. Combining the bias-corrected PML-AET and GRACE water storage data performs similarly to using the bias-corrected PML-AET data only. This study demonstrates that and there is great potential to use RS-AET based data for calibrating hydrological models in order to predict runoff in data sparse regions with complex terrain conditions.

We present an upscaled Lagrangian approach to predict the plume evolution in highly heterogeneous aquifers. The model is parameterized by transport independent characteristics such as the statistics of hydraulic conductivity and the Eulerian flow speed. It can be conditioned on the tracer properties, the conductivity data at the injection region, and is able to account for mobile-immobile mass transfer. Thus, the model is transferable to different solutes and hydraulic conditions. It captures the large scale non-Gaussian features for the evolution of the longitudinal mass distribution observed for the bromide and tritium tracer plumes at the macrodispersion experiment (MADE) site (Columbus, Ohio, USA), which are characterized by a slow moving peak and pronounced forward tailing. These large scale features are explained by advective tracer propagation due to a broad distribution of spatially persistent Eulerian flow speeds as a result of spatial variability in hydraulic conductivity.

During the late Paleozoic and Mesozoic, convergent plate boundary processes in northeastern Asia shifted from the Paleo-Asian Ocean to Paleo-Pacific Ocean, influencing the tectonic regime. To better understand this tectonic transition, we investigated the petrology, geochronology and geochemistry of igneous rocks from the Jilin area in the eastern part of the Central Asian Orogenic Belt. We identified four stages of magmatism at ~261, 253–244, 183–175 and 173–164 Ma. The ~261 Ma magmatism was generated in an active continental margin by partial melting of juvenile mafic lower crustal material. This stage of continental arc magmatism continued with the emplacement of 253–244 Ma adakitic magamas, which were generated by partial melting of subducted oceanic crustal material and metasomatized with overlying mantle wedge. The 183–175 Ma monzogranitic and dioritic magmas were generated in a continental arc environment via melting of juvenile lower continental crust and mixing of basaltic magma with crustal melt, respectively. Magmatism at 173–164 Ma was developed in an active continental margin, and were generated by melting of a juvenile lower continental crust. The integrated evidence suggests that the closure of the Paleo-Asian Ocean could occur at 244–227 Ma, whereas the timing of tectonic regime transition from the convergence of Paleo-Asian Ocean to the subduction of the Paleo-Pacific Ocean occurred at 223–185 Ma. The Changchun-Yanji Suture, which marks the easternmost closure of the Paleo-Asian Ocean, experienced multiple tectonic mode switches, and was controlled by subduction of the Paleo-Pacific Ocean since Early Jurassic.

Rapid increasing industries and city expansions have caused severe air pollution in the Guanzhong Basin (GZB), China in recent decades. Observations reveal that, although implementation of strict mitigation measures since 2014 has considerably reduced particulate matter (PM) pollution, the ozone (O) pollution during the warm season has continuously deteriorated in the basin. Simulations in May and August 2018 have been conducted using the WRF-Chem model to examine spatial and seasonal variations of the O formation regimes as well as source attributions in the GZB. The model generally performs well in simulating meteorological parameters, O, NO, and fine PM against measurements. The identified O formation regimes in cities of the GZB are all VOCs-sensitive in May and become more NO-sensitive in August. Sensitivity studies have shown that the power plants source generally suppresses the Oformation considerably in May and enhances it slightly in August due to its high NO and low VOCs emissions. The residential, transportation and industry sources increase the O concentration in May and August. Moreover, the transportation and industry sources play an increasingly important role in August but opposite for the residential source. The variation of O formation regimes and source attributions from May to August is caused by intensification of solar radiation, which not only promotes photochemical processes, also increases temperature and further enhances biogenic emissions and vertical exchange in the planetary boundary layer. The present study can provide guidelines to devise the effective O abatement strategies suitable for local situations.

This research is intended to map potential fires using GIS in forests in Talesh, Gilan Province. Spatial data analysis methods were used for zoning fire risk. First, a digital elevation model (DEM) model was prepared using the ASTERsensor . Slope, aspect and mean sea level (MSL) were also obtained by DEM. Then, maps of vegetation type and density were classified in terms of susceptibility to fire by using GIS. The roads, rural settlements and farmlands were mapped. Polygon to Raster and Euclidian Distance were used to rasterize all information layers. Fuzzy membership functions were used to value the parameters of the study area in each layer within a 0 to 1 range, and the subclasses were weighed in AHP model by Saaty valuation table and questionnaire. The use of Dong model and AHP and fuzzy weighing methods for zoning fire risk potentials showed that of the entire study area weighed by AHP method there were zones: 4221.72 Ha very low risk, 10528367 Ha low risk, 13567.94 Ha medium risk, 1382.32 Ha high risk and 6702.43 Ha very high risk, respectively. Therefore, risk zones in terms of surface area were high, medium, low, very high and very low. In fuzzy weighing method, very low, low, medium, high and very high risk zones were 6840.42 Ha, 6605.84 Ha, 12044.46 Ha, 15922.87 Ha, 15922.87 Ha, 7416.89Ha, respectively, which high erosion classes were of the highest priority and low erosion classes were of lowest priority.

In geophysics, crowdsourcing is an emerging non-traditional environmental monitoring approach that encourages contributions of data from individual citizens. Because of their reliance on undertrained citizens and imprecise low-cost sensors, crowdsourced data applications suffer from different types of noises that can deteriorate the overall monitoring accuracy. In this study, we propose a machine learning approach for automatic Crowdsourced data Quality Control (CSQC) by detecting and removing noisy data points in spatially and temporally discrete crowdsourced observations. We design a set of features from the original and interpolated rainfall data, and apply them to train and test the CSQC models based on both supervised and non-supervised machine learning algorithms. Performances of the CSQC models under various scenarios assuming no further retraining are also tested (hereafter referred to as transferability). The results based on synthetic but realistic data show that the CSQC model can significantly reduce the overall rainfall estimation error. Under the stationary assumption, CSQC models based on both supervised and unsupervised algorithms can have decent performances in noisy data identification and overall rainfall estimation error reduction; however, if the model is transferred to other cities with different rainfall structure or noise composition (without retraining), the supervised Multi-Layer Perceptrons (MLPs) turns out to be the best performing one.

Stable paleomagnetic information in meteoritic metal is carried by the cloudy zone ~1-10 micron wide regions containing islands of ferromagnetic tetrataenite embedded in a paramagnetic antitaenite matrix. Due to their small size and high coercivity (~2.2 T), the tetrataenite islands carry very stable magnetic remanence. However, these characteristics also make it difficult to image their magnetic state with the necessary spatial resolution and applied magnetic field. Here we describe the first application of X-ray holography to image the magnetic structure of the cloudy zone of the Tazewell IIICD meteorite with spatial resolution down to ~40 nm and in applied magnetic fields up to 1.1 T, sufficient to extract high-field hysteresis data from individual islands. Images were acquired as a function of magnetic fields applied both parallel and perpendicular to the surface of a ~100 nm thick slice of the cloudy zone. Broad distributions of coercivity are observed, including values that likely exceed the maximum applied field. Horizontal offsets in the hysteresis loops indicate an interaction field distribution with half width of ~100 mT between the islands in their room-temperature single-domain state, providing a good match to first-order reversal curve diagrams. The role of interactions during the acquisition of transformation chemical remnant magnetization as the meteorite parent body is cooled, and the implications for extracting quantitative estimates of the paleofield, are discussed

Various sources emit greenhouse gases such as CO and CH. Among the natural ecosystems, forests and wetlands emit a sizeable amount of these gases by means of autotrophic, heterotrophic respiration and bacterial activities. Additionally, a relatively new source has been detected; the emission of CH by trees and plants. Growing evidence suggests that a significant amount of CH is generated by the trees in forested ecosystems. The net ecosystem exchange (NEE), measured by an eddy covariance (EC) system, typically represents the net CO fluxes arising due to the biosphere’s photosynthetic and respirative processes. The net flux derived by this system is subsequently partitioned into two components, the respired carbon, and the assimilated carbon. However, the partitioning processes may have their shortcomings, which introduce significant errors. To reduce the uncertainty, the NEE has been constrained by measuring the isotopic values of the GHGs using a real-time analyzer in a tropical forest of north-east India, the Kaziranga National Park. The GHG analyzer provided CO and CH concentrations, as well as their carbon isotopic ratios. The isotopic data were used to partition the EC derived NEE records, which showed a good agreement with the EC measurements within the limits of experimental uncertainty. However, long-term observation is required to establish the potential of this relatively new method in this endeavor. Additionally, the isotopic data provided strong evidence of plant generated CH, which was apparently not possible to identify by the conventional means.

Overestimation of precipitation frequency and duration while underestimating intensity, i.e., the “drizzling” bias, has been a long-standing problem of global climate models. Here we explore this issue from the perspective of precipitation partitioning. We found that most models in the Climate Model Intercomparison Project phase 5 (CMIP5) have high convective-to-total precipitation (PC/PR) ratios in low latitudes. Convective precipitation has higher frequency and longer duration but lower intensity than non-convective precipitation in many models. As a result, the high PC/PR ratio contributes to the “drizzling” bias over low latitudes. The PC/PR ratio and associated “drizzling” bias increase as model resolution coarsens from 0.5o to 2.0o, but the resolution’s effect weakens as the grid spacing increases from 2.0o to 3.0o. Some of the CMIP6 models show reduced “drizzling” bias associated with decreased PC/PR ratio. Thus, more reasonable precipitation partitioning, along with finer model resolution should alleviate the “drizzling” bias within current climate models.

This study aims at understanding the impact of low-frequency climate modes on Rossby Wave Packets (RWPs) during the southern hemisphere summer. In particular, we focus on long-lived RWPs (lifespan above 8 days) and determine how El Niño-Southern Oscillation (ENSO) and Southern Annular Mode (SAM) modulate their frequency of occurrence plus the main areas of detection and dissipation. We find that the occurrence of long lived RWPs is maximum during El Niño years and negative SAM events. Years with largest numbers of long-lived RWPs are characterized by a zonally symmetric and narrow upper level jet that is shifted northward from its climatological position. Conversely, when the jet is shifted southward, as during positive SAM phases, particularly in the southwestern Pacific basin, the number of long-lived RWPs detected diminishes. El Niño sets atmospheric conditions that support the formation of long lived RWPs whereas La Niña years presents high interannual variability in the frequency of occurrence. Moreover, during El Niño events the main formation area is between 61-120ºE and its main dissipation area between 300-359ºE. During La Niña events, the main formation area moves to 241-300ºE and no main dissipation area is identified. During positive SAM two main formation areas appear at 61-120ºE and 241-300ºE and two main dissipation areas between 121-180º and 301-359º, whereas in negative SAM only one formation area at 241-300º is detected and no main dissipation area is found.

Atmospheric deposition is an important source of trace metals to surface environments, but knowledge about plant bioavailability of recently deposited metals is limited. We performed a fully factorial soil and atmosphere exposure experiment with three vegetables (radish, lettuce, and soybean), which allowed to effectively distinguish impacts of recently deposited metals (<1 year) from longer-term metal exposures in soils. Results showed that recently deposited Cu, Cd, and Pb accounted for 0.5-15.2% of total soil Cu, Cd, and Pb pools near emission source, while they contributed 15-76% of Cu, Cd, and Pb concentrations in edible parts of vegetables. The soil retention of recently deposited metals (52-73%) presented as higher mobile fractions than these previously present in soils (7-42%). These findings highlight a preferential uptake and high rates of bioaccumulation of deposited metals in vegetables and implicated that quick and potentially stronger reduction can be achieved by reducing current atmospheric source loads.

Geologic carbon storage (GCS) is part of a process known as carbon capture, utilization, and storage (CCUS); being adopted to mollify extreme weather events (global warming) as a result of CO2 emissions and improve energy production. Previous studies have shown promising potentials of permanent CO2 storage in depleted shale reservoirs. In this study, we experimentally and analytically investigate the impact of microbially-altered mechanical properties on carbon storage in the Niobrara shale reservoir, using a cultured solution and shale samples from Niobrara formation. Firstly, we obtained the properties of the untreated samples. Secondly, we treated and cultivated the samples with the cultured solution at specific conditions. Further, we obtained the new properties of the treated shale rocks. Lastly, we show the impact of the altered properties on CO2 storage integrity in unconventional shale reservoirs. Our results suggest that in shale reservoirs, biogeomechanical alterations can enhance the long-term integrity of geological sequestration of atmospheric CO2, by mitigating any deep subsurface potential leakage to the atmosphere.

To advance the understanding of the tectonic processes shaping the African continent, we construct the first continental-scale shear-wave velocity (Vs) model of the crust and uppermost mantle from joint analysis of ambient seismic noise and earthquake data recorded by ~1529 broadband seismic stations located in Africa, Arabia, and Europe from 1987 to 2018. We apply the widely used ambient noise cross-correlation and earthquake two-station methods to retrieve the fundamental-mode Rayleigh-wave group and phase velocity dispersions in the period range of 5 – 50 s which are jointly inverted using the neighbourhood algorithm to build a new three-dimensional Vs model with associated uncertainties. The inclusion of relatively short-period dispersion data from ambient seismic noise allows us to achieve better resolution at shallow depth and obtain a more accurate model than previous global and continental-scale studies, revealing lithospheric structures that correlate well with known tectonic features. In sparsely instrumented regions of north-central Africa, our model provides seismic evidence for the existence of cratonic remnants beneath thick sediments within the poorly imaged Sahara Metacraton and reveals unique mantle upwelling beneath hotspots, suggesting that they may be fed by unconnected plumes. The estimated crustal thickness varies among and within tectonic provinces and shows no clear evidence for the secular variation in crustal genesis. Our new model has the potential to serve as a preliminary reference velocity model for Africa and is useful for practical applications, including monitoring of the Comprehensive Nuclear-Test-Ban Treaty, geodynamic modeling as well as seismic hazard analysis.

Our understanding of the nature of crustal formation in the Eoarchean is severely curbed by the scarcity and poor preservation of the oldest rocks, and variable and imperfect preservation of protolith magmatic signatures. These limitations hamper our ability to place quantitative constraints on thermomechanical models for early crustal genesis and hence on the operative geodynamical regimes at that time. Controls on the liquid line of descent responsible for Eoarchean crust petrogenesis could help us understand more, but these remain vague. Growth of Archean crust may have occurred dominantly via processes akin to modern oceanic crustal genesis, coupled to a vertical geodynamic regime. Equally, convergent boundary processes, including subduction, are argued to be important in the development of the crust before about 3.8 Ga. The recently discovered ca. 3.75 Ga Ukaliq supracrustal enclave (northern Québec) is mainly composed of serpentinized ultramafic rocks and amphibolitized mafic schists. Inferred protoliths to the Ukaliq serpentinites include dunites, pyroxenites, and hornblendites with compositions similar to that of arc crust cumulates, whereas the mafic rocks were probably basalts to basaltic andesites. The Ukaliq cumulates record two liquid lines of descent: (i) a tholeiitic suite, partially hydrated, resulting from the fractionation of a basaltic liquid; and (ii) a boninitic suite documenting the evolution of an initially primitive basaltic to andesitic melt at ~0.5 GPa and containing >6 wt% H2O. Together with the presence of negative μ142Nd anomalies, this information points to a deep fluid input via recycling of Hadean crust in the Eoarchean via modern-style subduction.

A specialized ground-based system has been developed for simultaneous observations of pulsating aurora (PsA) and related magnetospheric phenomena with the Arase satellite. The instrument suite is composed of 1) six 100-Hz sampling high-speed all-sky imagers (ASIs), 2) two 10-Hz sampling monochromatic ASIs observing 427.8 and 844.6 nm auroral emissions, 3) Watec Monochromatic Imagers, 4) a 20-Hz sampling magnetometer and 5) a 5-wavelength photometer. The 100-Hz ASIs were deployed in four stations in Scandinavia and two stations in Alaska, which have been used for capturing the main pulsations and quasi 3 Hz internal modulations of PsA at the same time. The 10-Hz sampling monochromatic ASIs have been operative in Tromsø, Norway with the 20-Hz magnetometer and the 5-wavelength photometer. Combination of these multiple instruments with the European Incoherent SCATter (EISCAT) radar enables us to reveal the energetics/electrodynamics behind PsA and further to detect the low-altitude ionization due to energetic electron precipitation during PsA. In particular, we intend to derive the characteristic energy of precipitating electrons during PsA by comparing the 427.8 and 844.6 nm emissions from the two monochromatic ASIs. Since the launch of the Arase satellite, the data from these instruments have been examined in comparison with the wave and particle data from the satellite in the magnetosphere. In the future, the system will be utilized not only for studies of PsA but also for other categories of aurora in close collaboration with the planned EISCAT_3D project.

Starting in January 2020, the novel coronavirus, now known as acute respiratory syndrome coronavirus (SARS-CoV-2) and the disease that it causes (COVID-19) has had significant impacts on human health, the environment and the economy globally. The rapid lockdown that occurred as well as its well documented timing in various locations allows for an unprecedented opportunity to examine the impact of air pollution from densely populated regions has on adjacent and pristine environments. Here we use in-situ and satellite observations to show that there was a step function decrease in two key indicators of air quality, nitrogen dioxide and airborne particulates, in locations within the Indo-Gangetic Plan (IGP) as a result of the Spring 2020 lockdown. Based on anomaly patterns, we find a dipole response with a statistically significant reduction in air pollution along the western IGP and Himalaya and an increase in air pollution in the eastern IGP and Himalaya. We show that spatial variability in the reductions in economic activity across northern India and the adjoining countries of Nepal, Pakistan and Bangladesh contributed to this dipole as did a persistent atmospheric circulation anomaly across the region during the lockdown.

Abstract The key to evaluating the formation history and evolution of the Moon lies in understanding the current state of its interior. We used a multidisciplinary approach to explore the current day lunar structure and composition with the aim of identifying signatures of formation and early evolution. We constructed a large number of 1D lunar interior models to explore a wide range of potential structures and identified those models that match the present day mass, moment of inertia, and bulk silicate composition of the Moon. In an advance on previous studies, we explicitly calculate the physical and elastic properties of the varying mineral assemblages in the lunar interior using multicomponent equations of state. We considered models with either a compositionally homogeneous mantle or a stratified mantle that preserved remnants of magma ocean crystallization, and tested thermal profiles that span the range of proposed selenotherms. For the models that reproduced the observed mass and moment of inertia, we found a narrow range of possible metallic (iron) core radii (269-387 km) consistent with previous determinations. We explored the possibility of an ilmenite bearing layer both below the crust and at the core-mantle boundary as a potential tracer of magma ocean solidification and overturn. We observed a trade-off between the mass of the upper and lower ilmenite-bearing layers and structures that have undergone mantle overturn are both consistent with present observations. Plain Language Summary In order to understand how the Moon formed, along with the following history including the processes that change and shape it, the current state of the lunar interior offers a lot of valuable information or clues. We used several different computer simulation tools from different disciplines to calculate the Moon’s interior structure. We then compared our calculations with observations of the Moon’s mass and moment of inertia (a measure of how its weight is distributed through the interior) and the average composition and chemistry of the Moon. We considered a Moon that is well mixed and one that has preserved layers from its early history and tried different temperature structures. We find that the Moon has to have a small dense iron core and that it may have a hot soft layer just above the core that can dampen moonquakes.