bluuebunny/crossref_metadata_2025 huggingface dataset:
Fourier-Transform Infrared Spectroscopy of Environmentally Weathered Textile Fabrics for Enhanced Microplastic Identification
Authors: Patankar Shreyas , Vassilenko Ekaterina , Watkins Mathew , Posacka Anna , Ross Peter
Published: March 2021

Microplastic pollution in oceans is among the global environmental concerns of our time. Emerging research on ocean environments indicates that microfibers, such as those originating from textiles, are some of the most commonly occurring type of microplastic contaminants. While Fourier-transform infrared spectroscopy (FTIR) is commonly used to identify and characterize pollutant samples obtained from the environment, this identification is challenging because infrared spectra of materials can be modified by exposure to the ocean, air, UV light, and other ambient conditions, in a process referred to as “weathering”. We report preliminary efforts in improving FTIR characterization of microplastics by building a library of infrared spectra of common textile fibers weathered under a selection of ambient conditions. Consumer textile materials including polyester, nylon, cotton, and other, were exposed to a selection of ambient conditions: ocean, air, and wastewater treatment stages, in a controlled weathering experiment. Infrared spectra were monitored for up to 52 weeks, with the resulting data illuminating on the environmental fate and longevity of synthetic and natural fibers. Spectral changes caused by weathering were found to depend strongly on both the composition of the material and the specific ambient conditions. This library of weathered material spectra is useful not only in easier identification of environmental microfibers, but also in helping us estimate the duration and manner of weathering that a given environmental microfiber may have experienced.
European Ground Motion Service (EGMS)
Authors: Costantini Mario , Minati Federico , Trillo Francesco , Ferretti Alessandro , Novali Fabrizio , Passera Emanuele , Dehls John , Larsen Yngvar , Marinkovic Petar , Eineder Michael , Brcic Ramon , Siegmund Robert , Kotzerke Paul , Kenyeres Ambrus , Proietti Sergio , Solari Lorenzo , Andersen Henrik
Published: March 2021

Interferometric processing of series of data acquired over time by synthetic aperture radar (SAR) satellites makes it possible to measure millimetric ground motions (typically induced by landslides, subsidence and earthquake or volcanic phenomena), and to monitor the stability of buildings and infrastructures. In this work, we present the first application of the interferometric SAR (InSAR) technology to high-resolution monitoring of ground deformations over an entire continent, based on full-resolution processing of the whole archive of past and future Sentinel-1 (S1) satellite acquisitions over most parts of Europe. The European Ground Motion Service (EGMS) is funded by the European Commission and forms an essential element of the Copernicus Land Monitoring Service (CLMS) managed by the European Environment Agency. Upscaling from existing national precursor services to pan-European scale will be challenging. Although low-resolution datasets have been recently produced at this scale, full-resolution processing is more complex, potentially revealing errors that would be disguised or suppressed otherwise at coarser scale. The project will utilise the most advanced persistent scatterer (PS) and distributed scatterer (DS) InSAR processing techniques, and a high-quality GNSS model, required to calibrate the InSAR products. To foster acceptance and a maximum/optimum use of the service by the growing Copernicus user community and the public at large, the EGMS will provide tools for visualization, exploration, analysis and download of the ground deformation measurements, as well as elements to promote best practice and user uptake.
Improved estimates of future fire emissions under CMIP6 scenarios and implications for aerosol radiative forcing
Authors: Kasoar Matthew , Hamilton Douglas , Dalmonech Daniela , Hantson Stijn , Lasslop Gitta , Voulgarakis Apostolos , Wells Christopher
Published: March 2021

The CMIP6 Shared Socioeconomic Pathway (SSP) scenarios include projections of future changes in anthropogenic biomass-burning.  Globally, they assume a decrease in total fire emissions over the next century under all scenarios.  However, fire regimes and emissions are expected to additionally change with future climate, and the methodology used to project fire emissions in the SSP scenarios is opaque.

We aim to provide a more traceable estimate of future fire emissions under CMIP6 scenarios and evaluate the impacts for aerosol radiative forcing.  We utilise interactive wildfire emissions from four independent land-surface models (CLM5, JSBACH3.2, LPJ-GUESS, and ISBA-CTRIP) used within CMIP6 ESMs, and two different machine-learning methods (a random forest, and a generalised additive model) trained on historical data, to predict year 2100 biomass-burning aerosol emissions consistent with the CMIP6-modelled climate for three different scenarios: SSP126, SSP370, and SSP585.  This multi-method approach provides future fire emissions integrating information from observations, projections of climate, socioeconomic parameters and changes in vegetation distribution and fuel loads.

Our analysis shows a robust increase in fire emissions for large areas of the extra-tropics until the end of this century for all methods.  Although this pattern was present to an extent in the original SSP projections, both the interactive fire models and machine-learning methods predict substantially higher increases in extra-tropical emissions in 2100 than the corresponding SSP datasets.  Within the tropics the signal is mixed. Increases in emissions are largely driven by the temperature changes, while in some tropical areas reductions in fire emissions are driven by human factors and changes in precipitation, with the largest reductions in Africa. The machine-learning methods show a stronger reduction in the tropics than the interactive fire models, however overall there is strong agreement between both the models and the machine-learning methods.

We then use additional nudged atmospheric simulations with two state-of-the-art composition-climate models, UKESM1 and CESM2, to diagnose the impact of these updated fire emissions on aerosol burden and radiative forcing, compared with the original SSP prescribed emissions.  We provide estimates of future fire radiative forcing, compared to modern-day, under these CMIP6 scenarios which span both the severity of climate change in 2100, and the rate of reduction of other aerosol species.
Hydro-meteorological hazard analysis for new settlements framed in the Colombian peace process
Authors: Aristizábal Giraldo Edier Vicente ,   Universidad Nacional de Colombia and Ministerio de Vivienda, Ciudad y Territorio
Published: March 2021

Colombia is a country with a recent history of an armed conflict from 1960. In 2012, a negotiation process started between the Colombian National Government and the largest left-wing guerrilla group (FARC - Fuerzas Armadas Revolucionarias de Colombia in Spanish). Finally, in 2016 a final peace agreement was signed, where several compromises were taken by both sides. For starting, one of the most important element of the agreement was to define concentration areas into the Colombia territory, where the entire FARC members should be located transitory, and posteriorly those areas must change to permanent settlements following the current regulation related to land use planning in Colombia. This study shows the hazard, vulnerability and risk assessment for 5 concentration areas, which were prioritized, of 24 total areas established. The multi-hazard assessment was analysed from a regional (10-m resolution) and detailed (0.5-m resolution) approach.

For the regional approach, landslide susceptibility was assessed through analytic hierarchy process and weight of evidence methodologies compared to logistic regression and landslide hazard was evaluated with SHALSTAB and Newmark's models for rainfall and seismic triggers. Floods hazard was analysed through a combined methodology using unit hydrograph and the morphometric descriptor HAND. Meanwhile, torrential flows hazard was analysed from a morphometric evaluation and sediment availability from SHALSTAB unstable areas joined with the flood methodology using sediment and water volumes to establish the corresponding area of impact.

For the detailed approach, through field samples and local geotechnical parameters and using TRIGRS and SCOOPS 3D models, the hazard evaluation was carried out for a deterministic result and using FOSM model results can be processed to obtain a probabilistic hazard map. Flood hazard was estimated using the bidimensional hydrodynamic model IBER and the discharge was enhanced simulating the sediment volumes from unstable areas to assess torrential flows hazard but also the mass flow simulation model r.avaflow was employed for a better simulation of the rheology of the flow using the same discharge rates.

This study shows the role of multi-hazard studies as a fundamental element in a peace process, to establish new settlements in the rural area according to the Colombian land-use planning regulation, and under very complex and mountainous terrains conditions. One of the critical points in the short and long term for the sustainability of this peace process is to provide safe areas where FARC members may start a new life.
Inverse Modeling of Earthquake Source Properties Constrained by Pseudotachylite Surface Roughness
Authors: Yang Donglai , Resor Phillip
Published: March 2021

Under high rates of coseismic slip, frictional melt may be generated at the shear zone potentially altering the dynamics and rendering classical rate-and-state friction laws ineffective. Pseudotachylytes (solidified frictional melt) created in laboratories and found in natural fault zones thus provide thermal and mechanical information critical to the study of dynamic shear zone processes, including thermal runaway, stress drop, and viscous braking. While extensive geochemical and mineralogical evidence has suggested the occurrence of disequilibrium melting during pseudotachylite generation, few studies have leveraged it to resolve the kinematics of co-seismic slip.

In this study, we optimize the kinematic parameters of the regularized Yoffe source function using the topographic relief of a pseudotachylyte/wall rock surface in combination with a one-dimensional fluid-mechanical-thermal finite element model. The model consists of solving a two-phase moving boundary problem with an internal heat source constrained by the slip kinematics of the Yoffe function in tandem with the Couette flow problem as an approximation to the shearing of the viscous melt. The topographic relief data come from a pseudotachylyte-bearing fault within the Gole Larghe fault zone, Italy measured using high-resolution X-ray tomography. On this fault surface, biotites are ~260 (±100) micron lower than the mean surface height as a result of preferential melting associated with a lower fusion temperature than quartz or feldspar. Using Monte Carlo sampling of the relief data distribution and Bayesian optimization, we optimize the kinematic parameters of the regularized Yoffe functions and resolve the statistics of shear stress evolution.

Our preliminary results show that the displacement-averaged shear stress in frictional melt ranges from 2 to 7 MPa with a mean value of 5.5 MPa. This is much smaller than estimates based on pseudotachylyte thickness and laboratory experiments, indicating a more complete stress drop than previously thought. The optimal Yoffe source functions have a mean total rise time of ~4 seconds, which is longer than that inferred from scaling laws. Simulations are ongoing and we look forward to interpreting the results in the context of source properties, source models, and energy partitioning for pseudotachylyte-bearing faults.
Tensile Crack Speed in Brittle Rocks
Authors: Serati Mehdi
Published: March 2021

An important issue in rapid brittle fracture is the limiting speed of crack propagation. It is widely believed that brittle mode I crack cannot propagate faster than the Rayleigh wave speed, or the speed of sound on a solid surface. Mode II cracks are also limited by longitudinal speed wave. The origin for this belief stems from the predictions of continuum mechanics. Once the crack speed reaches a theoretical upper limit in a material, which is most often larger than one fifth of the Rayleigh wave velocity, branching of a propagating crack occurs. To verify this hypothesis, this paper presents the results of an experimental program aimed at disclosing the size effect on the crack velocity in the Splitting Tensile Strength indirect test (i.e. the Brazilian Test) using high-speed photography techniques. Over 100 Brazilian tests with more than 10 different rock types at various diameters were prepared and tested according to the ASTM standard recommendations using either a servo hydraulic machine or an electromechanical load frame at a wide ranges of load/displacement rates. By adopting a high frame rate of above 100,000 frames per second (fps), crack initiation, propagation, and coalescence were captured to study the size effect on the crack speed and failure mode on the Brazilian test results.
Mid-Pliocene mesic subtropical hydroclimate over continents driven by land surface changes
Authors: Feng Ran , Bhattacharya Tripti , Otto-bliesner Bette , Brady Esther ,   PlioMIP2
Published: March 2021

Earth System Models (ESMs) project drying of the northern subtropics by the end of the 21st century. However, geologic evidence from intervals with elevated concentrations of atmospheric carbon dioxide (pCO2), like the mid-Pliocene, suggest mesic subtropical conditions. Several hypotheses, including an El Niño-like SST pattern and weaker Hadley circulation, have been proposed to explain this mismatch. Here, we show that PlioMIP2 ensemble broadly capture the pattern of proxy reconstructed Pliocene hydroclimate, notably a wetter Sahel and southeast Asia. Sensitivity simulations reveal that this pattern is driven by summertime rainfall increases as a result of lowered albedo and a distinct surface warming pattern, generated by prescribed vegetation and ice sheet changes. The resultant tropospheric moistening and stationary wave pattern enhance moisture convergence into the northern subtropics. Our results suggest that mid-Pliocene hydroclimate is part of the Earth system feedback to sustained CO2 concentrations similar to today.
Mineral and Trace Element Identification in Jezero Crater, Mars, with SuperCam’s Time-Resolved Raman (TRR) and Luminescence (TRL) Techniques
Authors: Ollila Ann , Beyssac Olivier , Arana Gorka , Angel Stanley Mike , Benzerara Karim , Bernard Sylvain , Bernardi Pernelle , Bousquet Bruno , Castro Kepa , Clave Elise , Clegg Sam , Sharma Shiv , Cousin Agnes , Forni Olivier , Gasnault Olivier , Willis Peter , Lopez-Reyes Guillermo , Madariaga Juan Manuel , Manrique Jose , Martinez-Frias Jesus ,   SuperCam Raman Working Group
Published: March 2021

In February 2021, NASA’s Perseverance rover will begin its exploration of Jezero crater near a putative ancient delta. Orbital mineralogy indicates the presence of carbonates and clay minerals in the landing site, which will be key targets for study. The SuperCam instrument provides an important tool for remotely surveying for these and other minerals using multiple techniques: Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman (TRR) and Luminescence (TRL) spectroscopies, Visible-Near Infrared (VisIR) spectroscopy, micro-imaging, and acoustics. TRR and TRL use a pulsed 532 nm laser with an adjustable gate width, from 100 ns to several ms. The time at which the gate opens is also adjustable, from coincident with the laser pulse to obtain Raman and fast luminescence out to 10 ms or more to capture the lifetimes of luminescence signals. These techniques will operate at distances up to 7 m from the rover mast and will be most effective if LIBS first removes dust from the targets and chemistry is subsequently obtained at the same location. Early lab results show that TRR is effective for detecting certain carbonates (magnesite, hydromagnesite, siderite, ankerite, calcite, and dolomite), sulfates (gypsum, anhydrite, barite, epsomite, and coquimbite), phosphates (apatite), and silicates (e.g., quartz, feldspar, forsteritic olivine, topaz, and diopside). Many of these minerals are high-priority targets for astrobiology studies because they represent habitable environments and have high biosignature preservation potential in terrestrial rocks. Raman signal strength is significantly decreased in fine-grained materials, however, and clay minerals will be a challenge to detect, as will opaque minerals such as Fe-oxides. TRL will be useful for identifying rare earth elements in phosphates and zircon, Fe3+ in silicates such as feldspar, Mn2+ in carbonates, and Cr3+ in Al-oxides and some silicates. TRL may also be able to identify fast (<100 ns) fluorescence that may indicate the presence of organic materials, which could then be analyzed more closely with the rover’s other instruments. Early results from the Jezero crater will be presented, if available.   
Magnetic Field Line Random Walk and Solar Energetic Particle Path Lengths
Authors: Matthaeus William , Chhiber Rohit , Cohen Christina M. S. , Ruffolo David , Sonsrettee Wirin , Tooprakai Paisan , Seripienlert Achara , Chuychai Piyanate , Usmanov Arcadi V. , Goldstein Melvyn . L. , McComas David J. ,   PSP/ISOIS Team
Published: March 2021

In 2020 May-June, six solar energetic ion events were observed by the Parker Solar Probe/ISoIS instrument suite at ~0.35 AU from the Sun.  From standard velocity-dispersion analysis, the apparent ion path length is ~0.625 AU at the onset of each event. We develop a formalism for estimating the path length of random-walking magnetic field lines, to explain why the apparent ion path length at event onset greatly exceeds the radial distance from the Sun for these events. We developed analytical estimates of the average increase in path length of random-walking magnetic field lines, relative to the unperturbed mean field. Both a simple estimate and a rigorous theoretical formulation are obtained for field-lines' path length increase as a function of path length along the large-scale field. Monte Carlo simulations of field line and particle trajectories in a model of solar wind turbulence are used to validate the formalism and study the path lengths of particle guiding-center and full-orbital trajectories. From these simulated trajectories, we find that particle guiding centers can have path lengths somewhat shorter than the average field line path length, while particle orbits can have substantially larger path lengths due to their gyromotion with a nonzero effective pitch angle. The formalism is also implemented in a global solar wind model, and results are compared with ion path lengths inferred from ISoIS observations. The long apparent pathlength during these solar energetic ion events can be explained by 1) a magnetic field line path length increase due to the field line random walk, and 2) particle transport about the guiding center with nonzero effective pitch angle due to pitch angle scattering. This research partially supported by the PSP /ISOIS project.
Study of Thermal Activity in The Mixing Layer During First Generated Single Cloud by Using Combined Observation From Boundary Layer Radar, Doppler Lidar and Time Lapse Camera 
Authors: Nugroho Ginaldi Ari , Yamaguchi Kosei , Nakakita Eiichi , Yamamoto Masayuki K. , Kawamura Seiji , Iwai Hironori
Published: March 2021

Detailed observation of small scale perturbation in the atmospheric boundary layer during the first generated cumulus cloud are conducted. Our target is to study this small scale perturbation, especially related to the thermal activity at the first generated cumulus cloud. The observation is performed during the daytime on August 17, 2018, and September 03, 2018. Location is focused in the urban area of Kobe, Japan. High-resolution instruments such as Boundary Layer Radar, Doppler Lidar, and Time Lapse camera are used in this observation. Boundary Layer Radar, and Doppler Lidar are used for clear air observation. Meanwhile Time Lapse Camera are used for cloud existence observation. The atmospheric boundary layer structure is analyzed based on vertical velocity profile, variance, skewness, and estimated atmospheric boundary layer height. Wavelet are used to observe more of the period of the thermal activity. Furthermore, time correlation between vertical velocity time series from height 0.3 to 2 km and image pixel of generated cloud time series are also discussed in this study.
Impact assessment of structural barriers and flow regulation on the Ganga River morphology and ecology
Authors: Sonkar Gaurav Kailash , Gaurav Kumar
Published: March 2021

The Ganga-Brahmaputra river system in the Himalayan Foreland supports diverse aquatic fauna. Decades of flow regulation through dams and barrages have affected their habitat suitability. To evaluate the impacts of large barrages on the morphology and habitat ecology we studied two different reaches (middle and lower) of the Ganga River. These reaches are the habitat of the endangered Ganga River dolphin (Platanista gangetica). In a reach in the middle Ganga between Bijnor and Narora barrage, a reported rise in dolphin population has been documented. In contrast, near the Farakka barrage in the lower reach of the Ganga River, a significant decline in the dolphin population has been observed.

We use Corona and time-series Landsat satellite images along with flow discharge data to assess the morphological and ecological impact of the barrages. In middle Ganga, the dolphin habitat is isolated between the Bijnor and Narora barrage where the minimum flow is available throughout the year for the dolphins to thrive.  On the other hand, in the lower Ganga, contrasting impacts are observed in the proximity (upstream/downstream) of the Farakka barrage. In the downstream, reduction in water (by one-third in the pre-monsoon discharge) and sediment discharge has decoupled the channel belt to its floodplain resulting in a loss of lateral connectivity. The presence of minimum flow between the Bijnor and Narora barrage has aided the dolphin population rise while the loss of lateral connectivity and excess siltation at the Farakka barrage has made the river reach unsuitable for habitation.   
Data assimilation, sensitivity analysis and uncertainty quantification in a semi-arid terminal catchment subject to rainfall decline
Authors: De Sousa Eduardo , Hipsey Matthew , Vogwill Ryan
Published: March 2021

Quantification of long-term hydrologic change in groundwater often requires the comparison of states pre- and post- change. The assessment of these changes in ungauged catchments is particularly difficult from a conceptual point of view and due to parameter non-uniqueness and associated uncertainty of quantitative frameworks. In these contexts, the use of data assimilation, sensitivity analysis and uncertainty quantification techniques are critical to maximise the use of available data both in terms of conceptualisation and quantification. This paper summarises findings of a study undertaken in the Lake Muir-Unicup Natural Diversity Recovery Catchment (MUNDRC), where a number of techniques were applied to inform both conceptual and numerical models. The MUNDRC is and small-scale endorheic basin located in southwestern Australia listed under the Ramsar Convention as a Wetland of International Importance and have been subject to a systematic decline in rainfall rates since 1970. Conceptual and numerical frameworks have been development to understand and quantify impacts of rainfall decline on the catchment using a variety of metrics involving groundwater and lake levels, as well as fluxes between these compartments and mass balance components. Conceptualisation was facilitated with the use a novel data-driven method relating rainfall and groundwater response running backwards in time, allowing the establishment of baseline conditions prior to rainfall decline, estimation of net recharge rates and providing initial heads for the forward numerical modelling. Parameter and predictive uncertainties associated with data gaps have been minimised and quantified utilising an Iterative Ensemble Smoother (White, 2018), while further refinement of conceptual model was undertaken following results from sensitivity analysis, where major parameter controls groundwater levels and other predictions of interest were quantified.
Short-wavelength Bouguer anomaly and active faults in the northeastern Japan arc from the viewpoint of differential geometry
Authors: Hirano Mitsuhiro , Nagahama Hiroyuki , Muto Jun
Published: March 2021

In the northeastern Japan arc with the active compressive stress field since ~3 Ma, it is reported that active faults have a characteristic distribution on the short-wavelength (< 160 km) Bouguer anomalies: Active faults tend to be located in negative regions. It suggests that they do not simply correspond to geologic distributions, and also reflect active crustal deformation in the northeastern Japan arc. Although previous studies proposed that cracks and volumetric strain caused by faulting contribute to negative gravity anomalies, the quantitative effect of active faults on the short-wavelength Bouguer anomalies in the northeastern Japan arc has been unclear in previous studies because of the low resolution of the gravity map. So, we evaluated the quantitative effect of active faults in the northeastern Japan arc using the latest digital datasets for gravity measurements. First, we created a new short-wavelength (< 160 km) Bouguer anomaly map with high spatial resolution and redrew the geologic map to the mass-density distribution map. On our map, active faults are accompanied by negative regions or grooves. The negative regions or grooves with active faults cannot be only explained by the existence of a low mass-density layer (e.g., sedimentary layer) based on the mass distribution map and cylinder's model with a mass-density depending on the depth. We then showed that gravity anomalies due to accumulated cracks and volumetric strain caused by faulting over the past three million years, which is estimated at around -10 mGal, should also be taken into account. Our result indicates accumulated crustal deformation can generate negative gravity anomaly zones along the strain concentration zones, impacting the pattern of short-wavelength Bouguer anomalies throughout in the entire northeastern Japan arc. Moreover, the earthquakes occur near the crustal bending regions in Niigata-Kobe Tectonic zone, which is a strain concentration field. Since active crustal deformation with large dislocation is associated with the curvature of crustal bending, gravity anomalies can be related to the crustal geometry including the curvature. Finally, we would reveal that the relationship between gravity anomaly and crustal deformation originates from the correspondence among differential geometric objects in space-time and material space, and the short-wavelength Bouguer anomalies are the result of its projection.
Paleoaltitudinal histories for the northern and southern margins of the Tibetan Plateau during the Late Cenozoic: revealed by GDGTs
Authors: Chen Chihao , Bai Yan , Fang Xiaomin , Guo Haichao , Zhang Weilin , Meng Qingquan , Xu Qiang , Zhang Tao , Deng Tao , He Jiankun , Chen Qinghu
Published: March 2021

As an important driver of global climate change during the Cenozoic, the uplift of the Tibetan Plateau (TP) has strongly influenced the origination and evolution of the Asian monsoon system, and therefore the aridification of central Asia. Over the last two decades, the application of stable isotope paleoaltimeters and the discoveries of mammal and plant fossils have greatly promoted the understanding of the uplift history of the TP. However, paleoaltitudinal reconstructions based on different paleoaltimeters have suggested differing outcomes and therefore remain controversial. Novel paleoaltimeters have therefore needed to be developed and applied to constrain the uplift history of the TP more accurately and effectively by comparing and verifying multi-proxies. Paleothermometers based on glyceryl dialkyl glycerol tetraethers (GDGTs) are widely used in terrestrial and ocean temperature reconstructions. In this study, GDGT-based paleothermometers were tentatively applied to the Gyirong Basin on the southern TP, and the Xining Basins on the northern TP, in an attempt to quantitatively reconstruct their paleoaltitudes.

Both soil and aquatic-typed branched GDGTs have been identified from Late Miocene to Mid-Pliocene (7.0-3.2 Ma) samples taken from the Gyirong Basin; their reconstructed paleotemperatures were 7.5±3.3°C and 14.2±4.5°C, respectively. The former temperature may represent the mean temperature of the terrestrial organic matter input area, while the latter may represent the lake surface temperature. The results would suggest that the lake surface of the Gyirong Basin during the Late Miocene to Mid-Pliocene was 2.5±0.8 km and that the surrounding mountains exceeded 3.6±0.6 km, implying that the central Himalayas underwent a rapid uplift of ~1.5 km after the Mid-Pliocene.

GDGT-based paleotemperature reconstructions using MBT'5ME values show that the Xining Basin dropped in temperature by ~10°C during the ~10.5-8 Ma period, exceeding that in sea surface temperatures and low-altitude terrestrial temperatures during these periods. By combining these results with contemporaneous tectonic and sedimentary records, we infer that these cooling events signaled the regional uplift with the amplitude of ~1 km of the Xining basins. Our results support that the TP was still growing and uplifting substantially since the Late Miocene, which may provide new evidence for understanding the growth, expansion and uplift patterns of the TP.
Analyzing the occurrence of environmental indicator minerals using clustering techniques and mineral networks
Authors: Williams Jason , Potter-McIntyre Sally , Filiberto Justin , Morrison Shaunna , Hummer Daniel
Published: March 2021

Indicator minerals have special physical and chemical properties that can be analyzed to glean information concerning the composition of host rocks and formational (or altering) fluids. Clay, zeolite, and tourmaline mineral groups are all ubiquitous at the Earth’s surface and shallow crust and distributed through a wide variety of sedimentary, igneous, metamorphic, and hydrothermal systems. Traditional studies of indicator mineral-bearing deposits have provided a wealth of data that could be integral to discovering new insights into the formation and evolution of naturally occurring systems. This study evaluates the relationships that exist between different environmental indicator mineral groups through the implementation of machine learning algorithms and network diagrams. Mineral occurrence data for thousands of localities hosting clay, zeolite, and tourmaline minerals were retrieved from mineral databases. Clustering techniques (e.g., agglomerative hierarchical clustering and density based spatial clustering of applications with noise) combined with network analyses were used to analyze the compiled dataset in an effort to characterize and identify geological processes operating at different localities across the United States. Ultimately, this study evaluates the ability of machine learning algorithms to act as supplementary diagnostic and interpretive tools in geoscientific studies.
Overview of the Airborne Phased Array Radar Observing Simulator
Authors: Lee Wen-Chau , Vivekanandan Jothiram , Ellis Scott , Manning Kevin , Bryan George , Lussier Lou , Grubišić Vanda , Klotz Bradley
Published: March 2021

The proposed airborne phased array radar (APAR) system consists of four removable, dual-polarized, C-band AESAs (Active Electronic Scanning Array) strategically located on the fuselage of the NSF/NCAR C-130. Conceptually, the radar system is divided into the front-end, the backend, and aircraft-specific section with the front-end primarily consisting of AESAs and the signal processor is in the backend. The aircraft specific section includes a power system and a GPS antenna.

As part of the risk reduction of the APAR development, the APAR Observing Simulator (AOS) system has been developed to provide simulated APAR data collection sampled from a C-130 flying by/through realistic numerical weather simulations of high-impact weather events. Given that APAR is designed to extend beyond capabilities of the existing airborne tail Doppler radars (e.g., NOAA TDRs and the retired NSF/NCAR ELDORA), a verification of signal processing software and algorithms is needed before the radar is physically built to ensure that the signal processing software infrastructure can handle high data rates and complicated, multiplex scanning that will be part of normal APAR operations.  Furthermore, several algorithms that will need to ingest large amounts of APAR data at very high rates are under development, including dual-Doppler wind synthesis, radar reflectivity attenuation correction, rain rate estimation, and hydrometeor classification. These algorithms need to be tested and verified before the implementation. 

The AOS will also serve as a planning tool for future Principal Investigators (PIs) who will use it to design and test different flight and scanning strategies based on simulated storms to yield the best scientific outcomes before their field deployment takes place. This will enable better understanding of trade-offs among various sampling regimes/strategies during the planning and enhance future field programs' efficiency and effectiveness.
Comparison of 1D and 3D hydrodynamic models on the assessement of climate change scenarios impact over a small tropical lake
Authors: Duarte Barbara , Amorim Lais , Martins José Rodolfo , Bernardino José Carlos
Published: March 2021

Lakes and reservoirs are standing surface water bodies that provide several environmental services and anthropic uses. As driving forces, climate conditions, sediment loads and pollutants influence the hydrodynamic behaviour of lakes, affecting the thermal stratification and mixing regime patterns that play expressive roles in the water quality condition. Therefore, the analysis of climate change scenarios allows the planning and implementation of preventive and mitigative actions. Mathematical modelling can simulate the thermal regime of lakes and reservoirs, considering different boundary conditions. Three-dimensions models are often used to better assess the changes on these environments, however, the extensive set of information required, along with its elevated processing parameters, can determine the selection of simpler models for long periods simulations, provided that the results accuracy remains appropriated. This paper intends to evaluate the differences and similarities between a one-dimension (GLM) and a three-dimensions (DELFT3D) transport models, used to assess the impacts of different climate scenarios on the thermal regime of a small lake. The case study was conducted on the Hedberg Dam, located about 90 km from Sao Paulo city, Brazil. It is a 0,2 km²-4.5m depth pond, built in the beginnings of the 19th century. Its hydrological catchment area is partially protected, with some sparse urban occupations. Both models used morphology characteristics, atmospheric variables and flow as input data. The calibration and validation were performed using water thermal profiles from high-frequency sensor data, observed from 2016 to 2018. Two climate change scenarios, optimistic and pessimistic, based on Eta Regional Climate Model, were simulated considering changes in radiation, air temperature, wind, precipitation and flow. Both results indicate changes in the thermal profiles regime, with increasing occurrence of mixing events and variations on the stratification patterns. However, differences can be noted in the water balance and in the thermal profiles results.
Machine learning to estimate surface roughness from satellite images
Authors: Singh Abhilash , Gaurav Kumar
Published: March 2021

Soil surface attributes (mainly surface roughness and soil moisture) play a critical role in land-atmosphere interaction and have several applications in agriculture, hydrology, meteorology, and climate change studies. This study explores the potential of different machine learning algorithms (Support Vector Regression (SVR), Gaussian Process Regression (GPR), Generalised Regression Neural Network (GRNN), Binary Decision Tree (BDT), Bragging Ensemble Learning, and Boosting Ensemble Learning) to estimate the surface soil roughness from Synthetic Aperture Radar (SAR) and optical satellite images in an alluvial megafan of the Kosi River in northern India. In a field campaign during 10-21 December 2019, we measured the surface soil roughness at 78 different locations using a mechanical pin-meter. The average value of the in-situ surface roughness is 1.8 cm. Further, at these locations, we extract the multiple features (backscattering coefficients, incidence angle, Normalised Difference Vegetation Index, and surface elevation) from Sentinel-1 A/B, LANDSAT-8 and SRTM data. We then trained and evaluated (in 60:40 ratio) the performance of all the regression-based machine learning techniques. 

We found that SVR method performs exceptionally well over other methods with (R= 0.74, RMSE=0.16 cm, and MSE=0.025 cm2). To ensure a fair selection of machine learning techniques, we have calculated some additional criteria that include Akaike’s Information Criterion (AIC), corrected AIC and Bayesian Information Criterion (BIC). On comparing, we observed that SVR exhibits the lowest values of AIC, corrected AIC and BIC amongst all other methods, indicating best goodness-of-fit.
Spatial heterogeneity of debris-flow watershed
Authors: Yao Yingjie
Published: March 2021

The intermittent surge is the basic manifestation of viscous debris flow, which emerges universally over the world, especially exemplified by those in Jiangjia Gully (JJG), a valley famous for its high frequency and variety of debris flow surges. It has been found that the surges originate from various sources in the watershed, thus identifying the source areas plays a fundamental role in studying the mechanism and process of surge developing. Advancement of GIS provides an apparent convenience in geospatial analysis of the watershed, which is used as a dominate tool in this paper.

In this study the JJG is divided into 97 tributaries (sub-watershed) and the hypsometric analysis is performed for each, from which derive the height of inflection points and the gravitational potential energy, coupled with the fitted parameters of specific power function. Then the morphology parameters, including slope, roundness, vegetation and soil, are revealed in tributaries. Besides, spatial autocorrelation among tributaries is quantified both globally and locally through Moran’s I and Getis-Ord Gi*, so that the HI spatial distributions are quantified and visualized. In particular, hot spots are conspicuously visible and highlight the geologic meaning of the HI when exploratory spatial data analysis is applied to the data distributions through local indices of spatial autocorrelation.

The results show that H-curves approximately present as S-shaped, and the integral values (HI) range from 0.18 to 0.69 and show positive relationship with both gravitational potential energy and the height of the inflection points. By the HI value, the tributaries are identified as in 5 phases of evolution. The younger tributaries (HI>0.49) make up the majority, which are expected to be the main possible sources for debris flows. Additionally, the slope distribution of tributaries all conform to the extreme distribution while the curves for the upstream, where the HI of tributaries generally manifest higher coupled with larger roundness, tends to skew to the right.

Finally the correlation between possible sources are explored through geospatial analysis. The spatial association in JJG provides an explanation of the debris flow source areas. Global spatial autocorrelation manifests significantly clustered (Moran’s I shows 0.449, passing the significance test) while tributaries with high HI value concentrate mainly in the Menqian Valley. Moreover, the drainage form of Menqian Valley represents a large possibility of debris flow source area with the respect of that being in Duozhao Valley.

Keywords: debris flow source area; hypsometric analysis; topographical characteristics; spatial autocorrelation; evolutionary phases
Spatial and temporal evaluation of multiple gridded precipitation datasets over complex topography and variable climate of Turkey
Authors: Uysal Gokcen , Hafizi Hamed , Sorman Ali Arda
Published: March 2021

Evaluation of problems related to water resources development and management require accurate precipitation estimates. Although ground-based stations provide direct physical measurement of precipitation, the accuracy of gauge-based precipitation data in terms of quality and spatial pattern may still be controversial. On the other hand, Gridded Precipitation Datasets (GPDs) provide high spatial and temporal precipitation estimates. GPDs are continuously changing with the improving technology and updating of retrospective algorithms, but they still need to be assessed over different regions both in space and time before being used for hydro-climatic studies. This study attempts to evaluate the spatio-temporal consistency of 13 different GPDs (CPCv1, MSWEPv2.2, ERA5, CHIRPSv2.0, CHIRPv2.0, IMERGHHFv06, IMERGHHEv06, IMERGHHLv06, TMPA-3b42v07, TMPA-3b42RTv07, PERSIANN-CDR, PERSIANN-CCS and PERSIANN) over Turkey which is a country characterized by diverse climate and complex terrain. The evaluation is performed for daily and monthly time scales considering the entire period of 2015-2019 as well as seasonal (spring, summer, autumn and winter) variability. Precipitation data from 130 stations are provided as reference data for point-to-grid comparison of GPDs. The modified Kling Gupta Efficiency (KGE) is selected for qualitative analysis whereas the Hanssen–Kuipers Score (HKS) is used to identify the ability of GPDs for capturing various precipitation events. The Probability Density Function (PDF) is selected to evaluate the intensity frequency of 13 GPDs for individual daily-based precipitation events. The results indicate that all GPDs have a median KGE performance ranging between -0.11 and 0.53 for daily precipitation while their performance increases in the monthly case (median KGE from 0.16 to 0.82). Gauge-corrected GPDs exhibit slightly better results over the uncorrected datasets in comparison with ground observations. GPDs from multi-source merging perform better than only satellite-based and reanalysis precipitation datasets. Among uncorrected GPDs, ERA5 and CHIRPv2.0 perform better while PERSIANN perform worse in all conditions. MSWEPv2.2 suffers from high-altitude conditions during winter and CHIRPSv2.0 shows poor performance during dry seasons. On the overall, MSWEPv2.2 performs better than CHIRPSv2.0 during daily/monthly, while CHIRPv2.0 performs better than CHIRPSv2.0 for daily time scale.
The flood resilience dashboard: community resilience
Authors: McCallum Ian , Velev Stefan , Laurien Finn , Mechler Reinhard , Keating Adriana , Hochrainer-Stigler Stefan , Szoenyi Michael
Published: March 2021

Communities around the world in flood-prone regions are increasingly aware of the benefits of using spatial data to better understand their predicament. With the advent of web mapping, free and open satellite data and the proliferation of mobile technologies, the possibilities for both understanding and improving community resilience are on the rise.

Here we present the “Flood Resilience Dashboard”, which is designed to put geo-spatial flood resilience data into the hands of practitioners. The objective is to provide a platform for practitioners in the Zurich Flood Resilience Alliance which gives access to both community resilience data and freely available, peer reviewed flood risk data, which can be used for decision support at scale. This data will include among others the Zurich Flood Resilience Measurement for Communities (FRMC) data, Vulnerability Capacity Assessment (VCA) maps, remote sensing derived information on flooding and other biophysical datasets (e.g. forest cover, water extent), modelled risk information, satellite imagery (e.g. night-time lights), crowdsourced data and more. Using two case studies, we illustrate how the above-mentioned datasets help to better understand community resilience. When co-developed with communities, these examples could potentially be scaled up and applied to similar regions around the world.
Accuracy and completeness of a near real-time citizen science-based multi-disaster inventory in the Rwenzori Mountains, Uganda
Authors: Sekajugo John , Kagoro Grace R , Jacobs Liesbet , Kabaseke Clovis , Namara Esther , Dewitte Olivier , Kervyn Matthieu
Published: March 2021

Accurate and complete inventory of natural hazard occurrence and their level of impact is a key first step to risk assessment, but it remains a challenge, especially for high frequency low impact events that rarely makes it to the news media. This challenge is even greater in rural areas of developing countries such as Uganda, where limited IT facilities prevent dissemination of information through social media. Here we report on a citizen-science initiative to monitor small-scale disasters (landslides and floods) occurring in the Rwenzori Mountains. A network of citizen (geo-)observers was established in February 2017 to collect temporally explicit geo-referenced information on eight different hazards and their impact using smartphone technology. Since then, over 500 hazard occurrences have been reported. However, such dataset needs to be assessed for its accuracy and potential biases before being used for scientific analysis. In this study, we evaluate the accuracy and completeness of the geo-observer-based disaster reports. First, systematic errors are reduced by peer reviewing the reports and implementing automatic tests to assess potential errors in detection and biases. Then, we compare the geo-observer-based records with two independent inventories collected through systematic field mapping and  satellite imagery mapping, focusing on landslide and flood events for the period between May 2019 and May 2020.  Results show over 95% of the geo-observer reports validated in the field were correctly identified and recorded less than 5 days after the occurrence (60% true positives, 1% false positives and 39% false negatives). For the satellite imagery mapping, 29% were true positives, 43% false positives and 28% false negatives. Geo-observers provide near real time disaster information on the location and level of impact, something difficult to achieve with systematic field and satellite imagery mapping. Depending on the topography of the area and the weather conditions, it can take several days to weeks before a cloud-free satellite image of a place can be obtained. The false negatives in the Geo-observer data are due to the tendency to report mainly occurrences along roads and rural foot paths since such occurrences are easily seen and accessed. Isolated small and inaccessible landslides are often not seen or reported to the Geo-observers. While satellite imagery mapping provides an opportunity to record disaster occurrences even in extremely inaccessible places, small landslides are often missed while shallow ones can easily be confused with freshly cleared vegetation for crop planting. Citizen science-based disaster reporting therefore not only provide the spatial occurrence of disasters but also the temporal and weather-related information, necessary for disaster risk analysis.