bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in flood quantiles of the Italian alpine basins: statistical testing and directions for attribution
Authors: Claps Pierluigi , Ganora Daniele , Viglione Alberto , Apostolo Alessandro
Published: March 2020

Among the hydrological impacts of global warming one of the most debated is the possible increase in extreme rainfall and floods. In sensitive environment, like the mountains, global warming directly affects the alternance of snow deposition and melting, with highly likely changes foreseen in the runoff regimes. As regards floods, recent results related to the trends in Europe have highlighted non-uniform evidence for an increase of peaks in cold regions, including high-elevation and high-latitude regions. Reasons for possible reduction of peaks against climate change are that anticipated melting can reduce the rain-on-snow phenomena in some areas. In the Alpine region, however, a closer look to the possible trends of flood peak is in order, as current knowledge indicates that the a dominant positive trend exists. 
Considering all discharge stations with historical flood peak data in Italy, a group of 140 mountain basins in the whole Alpine chain has been analysed according to the selection criteria of: i) average elevation of at least 1000 m a.s.l.; ii) absence of significant natural or man-made lakes within the basin; iii) at least 10 years of observation available in the last century. Areas of the selected basins range from 10 to about 10000 km2 and the average elevations reaches 3000 m a.s.l. The full range of observations available encompasses one century, as the oldest values dates 1911 and the most recent ones are recorded in the 2013. Half of the series available have less than 25 observations.
Among the possible techniques for trend analysis, the heterogeneous nature of this unprecedent database led us to initially consider only the quantile regression, due to the its robustness against the patchiness and the insufficient length of the time series. The same weaknesses in the data consistency suggest to complementing empirical statistical results with a subsequent attribution framework.  
Quantile regression application to all the flood peaks of a given year versus time provide marked indications of positive trends. Results were positive for quantiles 0.5, 0.75 and 0.95 even reducing the analyzed time span to 1951-2007, where at least 60 contemporaneous active stations can be considered. A specific role in the results of the elevation and of the area of the active station group over time was also investigated, by means of a multivariate quantile regression. Indeed, both the elevation and the area demonstrated to be significant covariates in the trend which, nevertheless, remained clearly positive for the same quantiles. 
A bundle application of the geomorphoclimatic attribution model of Allamano et al. (2009) on the 140 basins allowed to start the attribution exercise. Reconstruction of the dependence of the first moment of the time series on elevation provided a first confirmation to the empirical findings. 
A look inside the Panola trenched hillslope - initial results of a tracer test
Authors: van Meerveld Ilja , Seibert Jan
Published: March 2020

Trenched hilsllope studies are logistically challenging but have provided valuable information on hillslope hydrological processes. For example, they have shown that subsurface stormflow can respond very quickly to rainfall and that subsurface storm flow often varies in a non-linear and threshold-like way with total rainfall or antecedent conditions. They have also highlighted the high spatial variability in subsurface stormflow due to surface or bedrock topography or spatial variability in soil and bedrock characteristics. However, still less is known about mixing and flow velocities along hillslopes.

Here we present the initial results of a tracer test at the Panola trenched hillslope in Georgia, USA. We applied chloride to the surface of the lower half of the hillslope and bromide as a line source. We measured the concentrations in subsurface flow at 2-m sections of the trench face and for two macropores during a five-month period that included two large rainfall events that caused subsurface flow, and several sprinkling experiments on parts of the hillslope. We used 20 lysimeter pairs and more than 50 wells and piezometers across the hillslope to track the transport of the tracer through the soil to the trench. The results highlight the variability in flow pathways, the considerable difference between celerity and velocity, as well as the fast tracer transport through the weathered bedrock
Characterizing dominant hydrological processes under uncertainty: evaluating the interplay between model structure, parameter sampling, error metrics, and data information content
Authors: Khatami Sina , Peel Murray , Peterson Tim , Western Andrew
Published: March 2020

Hydrological models are conventionally evaluated in terms of their response surface or likelihood surface constructed with the model parameter space. To evaluate models as hypotheses, we developed the method of Flux Mapping to construct a hypothesis space based on model process representation. Here we defined the hypothesis space based on dominant runoff generating mechanisms, and acceptable model runs are defined as total simulated flow with similar (and minimal) model error simulated by distinct combinations of runoff components. We demonstrate that the hypothesis space in each modeling case is the result of interplay between the factors of model structure, parameter sampling, choice of error metric, and data information content. The aim of this study is to disentangle the role of each factor in this interplay. We used two model structures (SACRAMENTO and SIMHYD), two parameter sampling approaches (small samples based on guided-search and large samples based on Latin Hypercube Sampling), three widely used error metrics (NSE, KGE, and WIA — Willmott’s Index of Agreement), and hydrological data from a range of Australian catchments. First, we characterized how the three error metrics behave under different error regimes independent of any modeling. We then conducted a series of controlled experiments, i.e. a type of one-factor-at-a-time sensitivity analysis, to unpack the role of each factor in runoff simulation. We show that KGE is a more reliable error metric compared to NSE and WIA for model evaluation. We also argue that robust error metrics and sufficient parameter sampling are necessary conditions for evaluating models as hypotheses under uncertainty. We particularly argue that sampling sufficiency, regardless of the sampling strategy, should be further evaluated based on its interaction with other modeling factors determining the model response. We conclude that the interplay of these modeling factors is complex and unique to each modeling case, and hence generalizing model-based inferences should be done with caution particularly in characterizing hydrological processes in large-sample hydrology.
Implementation of soft hydraulic conservation measures: are we done with soil erosion?
Authors: Cerdan Olivier , Landemaine Valentin , Vandromme Rosalie , Grangeon Thomas
Published: March 2020

Numerous studies worldwide have reported a dramatic increase in soil erosion rates following the development of agriculture. In Western Europe, food security issues led to an intensification of agricultural practices after World War II. A profound modification of the landscapes was operated that translated into an increase in hydrosedimentary connectivity and a decrease in soil cover in winter. Related on-site soil degradation and off site societal and environmental detrimental effects rapidly started to call for the implementation of conservation measures. Since 2000, the French water agencies, through the European water framework directives, started to fund the implementation of soft hydraulic conservation measures, such as vegetated filter strips or linear vegetation barriers. These measures have the advantage to be easily implemented and to be visible in the landscape without compromising the intensive agriculture production system. After twenty years of funding of soft hydraulic conservation measures, soil erosion is still an issue. Are these solutions just a plaster on a wooden leg or are they really effective? Recent efforts consisting in catchment scale monitoring programs and modelling exercise tend to show that soft hydraulic conservation measures may be usefull for local mitigation actions but may have a limited impact in terms of floods and muddy floods. On the basis of simulation exercises in contrasting environments we will discuss the advantages and limitations of such measures.
Observations of Methane Emissions from California Dairies from Ground and Space: New Top-Down Constraints at Regional Scales
Authors: Dubey Manvendra K. , Heerah Sajjan , Frausto-Vicencio Isis , Jeong Seongeun , Fischer Marc , Hopkins Francesca
Published: March 2020

California has made reducing methane (CH4) from its dairy industry, which accounts for nearly 50% of its inventoried CH4 emissions, a key part of its climate change mitigation plan. However, in situ atmospheric measurement-based estimates suggest that the state-wide dairy source may be underestimated by up to a factor of 2.  Furthermore, emissions at the local scales important to mitigation policy (10’s km) are very uncertain. Ground based measurements of atmospheric column averaged methane concentrations (XCH4) can provide useful constraints on local to regional methane fluxes. Additionally, the high spatial and temporal resolution XCH4 observations by the space-based TROPOMI and GOSAT instruments provide an excellent opportunity to measure CH4 fluxes at these scales. We report field measurements of XCH4 gradients across the dairy intensive region (500 dairies, 330 Gg/yr CH4 emissions inventory) in the San Joaquin Valley (SJV) using two EM27/SUN solar spectrometers. With our EM27’s we observed several days of sustained downwind-upwind XCH4 enhancements of over 40 ppb, placing these signals well above TROPOMI and GOSAT’s precision level and among the highest reported XCH4 enhancements. We compare TROPOMI and GOSAT spatial XCH4 enhancements to our EM27 data to validate it in an area of high signal and to demonstrate its utility for observing localized sources. We also use GOSAT and TROPOMI’s data to characterize the wider SJV’s CH4 sources and to fill in temporal gaps between our field campaigns. Finally, we perform inverse optimizations using WRF-STILT simulations demonstrating that top-down observationally constrained dairy emissions are a factor of 2 larger than reported inventories.  This work illustrates how ground and space-based measurements can complement each other to improve our understanding of CH4 sources at scales relevant to mitigation policy.
Optimizing the management of complex water resources systems taking into account the long-term persistence in streamflow
Authors: Tilmant Amaury , Espanmanesh Vahid
Published: March 2020

The operation of multireservoir systems is a challenging decision-making problem due to (i) multiple, often conflicting, objectives (e.g. hydropower generation versus irrigated agriculture), (ii) stochastic variables (e.g. inflows, water demands, commodity prices), (iii) nonlinear relationships, (e.g. hydropower production function) and (iv) trade-offs between immediate and future consequences. Properly capturing the properties of the hydrologic processes responsible for the inflows is of paramount importance to enhance the performance of water resources systems. This becomes all the more relevant since low-frequency climate signals, which affect the hydrology in numerous regions around the globe, has increased in recent years. If traditional time series models generally fail to reproduce this regime-like behavior, so are the optimization models that are used to support multireservoir operation. Hidden Markov Model (HMM) is a class of hydrological models that can accommodate both overdispersion and serial dependence in historical time series, two essential hydrological properties that must be captured when modeling a system where the climate is switching between different states (e.g., dry, normal, wet). In terms of reservoir operation, Stochastic Dual Dynamic Programming (SDDP) is one of the few optimization techniques that can accomodate both system and hydrologic complexity. In SDDP, the hydrologic uncertainty is often captured by a multi-site periodic autoregressive (MPAR) model. However, MPAR models are unable to represent the long-term persistence of the streamflow process found in some regions, which may lead to suboptimal reservoir operating policies. We present an extension of the SDDP algorithm that can handle the long-term persistence and provide reservoir operating policies that explicitly capture regime shifts. To achieve this, the state-space vector now includes a climate variable whose transition is governed by a HMM. The Senegal River Basin (SRB), whose flow regime is characterized by multiyear dry/wet periods, is used as a case study.
Reconstruction of spatially continuous OMI tropospheric NO2 columns over China by combining GOME-2 products
Authors: He Qin , Qin Kai , Loyola Diego , Li Ding , Shi Jincheng , Xue Yong
Published: March 2020

Measurements of nitrogen dioxide (NO2) are essential for understanding air pollution and evaluating its impacts, and satellite remote sensing is an essential approach for obtaining tropospheric NO2 columns over wide temporal and spatial ranges. However, Ozone Monitoring Instrument (OMI) onboard Aura is affected by a loss of spatial coverage (around one-third of 60 viewing positions) commonly referred to as row anomaly since June 25th, 2007, and especially after June 5th, 2011. Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A/B provides data with a maximum swath width of 1920 km, and it needs one and a half days to cover the globe. Therefore, it is challenging to obtain diurnal spatially continuous vertical column densities (VCDs) of tropospheric NO2, which is limited by the performance of the instruments. Besides, the presence of clouds generates numerous missing and abnormal values that affect the application of VCDs data. To fill data gaps due to the above two reasons, this study proposes a framework for reconstructing OMI (afternoon overpass) tropospheric NO<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAfCAYAAAAvIgcYAAAAAXNSR0IArs4c6QAAAGxlWElmTU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUAAAABAAAARgEoAAMAAAABAAIAAIdpAAQAAAABAAAATgAAAAAAAACQAAAAAQAAAJAAAAABAAKgAgAEAAAAAQAAAAWgAwAEAAAAAQAAAB8AAAAAP9B61AAAAAlwSFlzAAAWJQAAFiUBSVIk8AAAAIFJREFUKBVjZmBg+A/EIOAAxftZgIwmIG4EYjhggrOQGKOCSIEBYg7iAOEGOk8B5kRGIGMlELMB8WUg1gXiCyDH3wHicCCeB8SyQAz20R8oPRFIZ8AEQfRcIO4E4mcgDijZ6AOxGRCLAbEMEK8AmXkRiKWA2BWINYEYrLIOxEACdQB+ug+3XdyoVgAAAABJRU5ErkJggg==" width="5" height="31"> VCDs over China by combining GOME-2 (morning overpass) products. First, we investigated the ground-based hourly NO2 concentration to characterize the diurnal variations, thus deriving the underlying factors that cause the difference between morning VCDs and afternoon ones. Then, the eXtreme Gradient Boosting (XGBoost) method was applied to estimate the missing values of OMI QA4ECV tropospheric NO2 VCDs from GOME-2 GDP offline products and other ancillary variables. The spatial coverage of OMI grids (binned to 0.25°) over China from 2015 to 2018 increased from 22% to 63% averagely. Furthermore, for those grids that are null in both products, we utilized an adaptive weighted temporal fitting method to fill missing data that the previous step produced. The reconstructed data set shows spatial and temporal patterns that are coherent with the adjacent areas. Our approach has great potential for reconstructing spatially continuous tropospheric NO2 columns, which are critical for daily air quality monitoring.
Applying machine learning and differential evolution optimization for soil texture predictions at national scale (Germany)
Authors: Gebauer Anika , Sakhaee Ali , Don Axel , Ließ Mareike
Published: March 2020

In order to assess the carbon and water storage capacity of agricultural soils at national scale (Germany), spatially continuous, high-resolution soil information on the particle size distribution is an essential requirement. Machine learning models are good at computing complex, composite non-linear functions. They can be trained on point data to relate soil properties (response variable) to approximations of soil forming factors (predictors). Finally, the obtained models can be used for spatial soil property predictions.

We developed models for topsoil texture regionalization using two powerful algorithms: the boosted regression trees machine learning algorithm, and the differential evolution algorithm applied for parameter tuning. Texture data (clay, silt, sand) originated from two sources: (1) the new soil database of the German Agricultural Soil Inventory (BZE), and (2) the well-known, publicly available database of the European Land Use / Cover Land Survey (LUCAS). BZE texture data results from an eight-kilometer sampling raster (2991 sampling points). LUCAS data from soils under agricultural use (Germany) comprises 1377 sampling points. The predictor datasets included DEM-based topography variables, information on the geographic position, and legacy maps of soil systematic units. In a first step, a nested five-fold cross-validation approach was used to tune and train models on the BZE data. In a second step, the amount of training data was increased by adding two-thirds of the LUCAS data. Model performance was evaluated by (1) cross-validation (RCV²), and (2) by using the remaining LUCAS data as an independent external test set (Rexternal²).

Models trained on the BZE data were able to predict the nation-wide spatial distribution of clay, silt and sand (RCV² = 0.57 – 0.76; Rexternal² = 0.68 – 0.83). Model performance was further enhanced by adding the LUCAS data to the training dataset.
Characterisation of low oxygen extreme events in the Eastern Tropical Pacific between 1979 and 2016
Authors: Köhn Eike Eduard , Münnich Matthias , Vogt Meike , Gruber Nicolas
Published: March 2020

The oxygen minimum zones (OMZs) in the Eastern Tropical Pacific (ETP)

have expanded over the past 50 years, likely leading to more frequent and more

intense low oxygen extreme events. This has potentially far-reaching implica-

tions for e.g., the production of the climate-relevant gas nitrous oxide or the

reduction of habitat for fish and zooplankton. Yet, to date our understanding

of the distribution and characteristics of low oxygen extreme events in the ETP

remains limited.

 

To fill this gap, we study low oxygen extremes in the ETP using results from

an eddy-resolution hindcast simulation with the coupled physical-biogeochemical

model ROMS-BEC for the Pacific from 1979 to 2016. Our setup permits us to

simulate oxygen variability in the ETP affected by processes on a broad range

of scales, from climate modes down to mesoscale dynamics. We detect and

track low oxygen extreme events in the upper 500 meters of the ETP, by ap-

plying temporally constant statistical thresholds to the hindcast simulation and

requiring a minimum event duration of 5 days. While most extremes last less

than 10 days and are of small volumetric extent, about 15% of the extremes

exist for over a month. The diversity of the long-lasting extremes is dominated

by westward propagating low oxygen eddies, which are mostly generated in the

near-coastal area. Superimposed inter-annual variability associated with the El

Niño-Southern Oscillation (ENSO) leads to a decrease in mesoscale extremes

during El Niño periods. Along the boundaries of the ETP OMZs transient

shoaling events of the oxycline linked to ENSO dynamics or the seasonal cycle

contribute to the generation of further pronounced low oxygen extreme events.

 

The presented detection and tracking of low oxygen extremes is an important

step towards a better understanding of extreme event occurrences and charac-

teristics and lays the groundwork for further research such as the biogeochemical

impact of such extremes.
Structural Complexity and Mechanics of a shallow crustal Seismogenic Source (Vado di Corno Fault Zone, Italy)
Authors: Fondriest Michele , Balsamo Fabrizio , Bistacchi Andrea , Clemenzi Luca , Demurtas Matteo , Storti Fabrizio , Di Toro Giulio
Published: March 2020

The mechanics and seismogenic behaviour of fault zones are strongly influenced by their internal structure, intended as three-dimensional geometry and topology of the fault/fracture network and distribution of the fault zone rocks with related physical properties.  In this perspective, the internal structure of the extensional seismically active Vado di Corno Fault Zone (Central Apennines, Italy) was quantified by combining high-resolution structural mapping with modern techniques of 3D fault network modelling over ∼2 km along fault strike. The fault zone is hosted in carbonate host rocks, was exhumed from ∼2 km depth, accommodated a normal slip of ∼1.5-2 km since Early-Pleistocene and cuts through the Pliocene Omo Morto Thrust Zone that was partially reactivated in extension.

The exceptional exposure of the Vado di Corno Fault Zone footwall block allowed us to reconstruct with extreme detail the geometry of the older Omo Morto Thrust Zone and quantify the spatial arrangement of master and subsidiary faults, and fault zone rocks within the Vado di Corno Fault Zone. The combined analysis of the structural map and of a realistic 3D fault network model with kinematic, topological and slip tendency analyses, pointed out the crucial role of the older Omo Morto Thrust Zone geometry (i.e. the occurrence and position of lateral ramps) in controlling the along-strike segmentation and slip distribution of the active Vado di Corno normal fault zone. These findings were tested with a boundary element mechanical model that highlights the effect of inherited compressional features on the Vado di Corno Fault Zone internal structure and returns distributions and particularly partitioning of slip comparable with those measured in the field.

Lastly, we discuss the exhumed Vado di Corno Fault Zone as an analogue for the shallow structure of many seismic sources in the Central Apennines. The mechanical interaction of the inherited Omo Morto Thrust Zone and the extensional Vado di Corno Fault Zone generated along-strike and down-dip geometrical asperities. Similar settings could play first-order control on the complex spatio-temporal evolution and rupture heterogeneity of earthquakes in the region (e.g. 2009 Mw 6.1 L’Aquila earthquake).
A complex dielectric sensor for measurement of water content and salinity in porous media
Authors: Castiglione Paolo , Campbell Gaylon
Published: March 2020

Soil water content and solute concentration in porous media, such as soil or soilless substrates, can be estimated from measurements of soil permittivity and electrical conductivity, respectively. The two quantities can be gauged at once by measuring the complex dielectric permittivity. Unlike traditional methods, which aim at measuring only the real part of the sample permittivity, complex dielectric measurement offers estimates uncorrupted by conductivity (EC effects). This results in improved accuracy of water content estimates, particularly in high salinity media. Once reliable estimates of permittivity and conductivity are available, it is possible to estimate the pore water conductivity, and from it the solute concentration.

In this paper we describe a novel design for an inexpensive complex dielectric sensor based on voltage amplitude measurements. The analysis of the method reveals simple criteria for maximizing sensitivity and allowed us to obtain good performance even in high conductivity samples. Experimental tests conducted in rockwool substrates also suggest that accurate estimate of solute concentration are attainable with the proposed technology.

 
OClO as observed by TROPOMI on Sentinel 5P
Authors: Pukite Janis , Borger Christian , Dörner Steffen , Wagner Thomas
Published: March 2020

The TROPOspheric Monitoring Instrument (TROPOMI) is an UV-VIS-NIR-SWIR instrument on board of Sentinel-5P satellite developed for monitoring the Earth’s atmosphere. It was launched on 13 October 2017 in a near polar orbit. It measures spectrally resolved earthshine radiances at an unprecedented spatial resolution of around 3.5x7.2 km2 (3.5x5.6 km2 starting from 6 Aug 2019) (near nadir) with a total swath width of ~2600 km on the Earth's surface providing daily global coverage. From the measured spectra high resolved trace gas distributions can be retrieved by means of differential optical absorption spectroscopy (DOAS).

Chlorine dioxide (OClO) is a by-product of the ozone depleting halogen chemistry in the stratosphere. Although being rapidly photolysed at low solar zenith angles (SZAs) it plays an important role as an indicator of the chlorine activation in polar regions during polar winter and spring at twilight conditions because of the nearly linear relation of its formation to chlorine oxide (ClO).

Here we present a new DOAS retrieval algorithm of the slant column densities (SCDs) of chlorine dioxide (OClO) and correlate this TROPOMI OClO signal with meteorological data for both Antarctic and Arctic regions.
New magnetostratigraphy from the Punta Grohmann section (Dolomites, NE Italy): an improvement of the Geomagnetic Polarity Time Scale around the Ladinian/Carnian boundary
Authors: Maron Matteo , Muttoni Giovanni , Ghezzi Marica , Rigo Manuel , Gianolla Piero
Published: March 2020

The Ladinian/Carnian boundary (LCB) is defined at Prati di Stuores (GSSP of the Carnian Stage) with the First Appearance Datum (FAD) of ammonoid Daxatina canadensis and approximated by the FAD of conodont Paragondolella polygnathiformis. The age of the Carnian is currently estimated at ca. 237 Ma using the composite magnetostratigraphy of the main late Ladinian basinal sequences from literature, calibrated with a U-Pb radiometric age of 237.77±0.14 Ma from the Rio Nigra section in Alpe di Siusi (Dolomites, NE Italy). In the attempt to improve the precision of the Geomagnetic Polarity Time Scale (GPTS) around the LCB we investigated for magnetostratigraphy the Punta Grohmann section in the Dolomites. The Punta Grohmann section is calibrated with ammonoids (the FAD of Zestoceras cf. lorigae is considered a proxy of the LCB) and is chronologically constrained by two U-Pb radiometric ages from zircons (237.58±0.04 Ma; 237.68±0.05 Ma). The magnetostratigraphy of the Punta Grohmann section has been successfully correlated to other Ladinian-Carnian magnetostratigraphic sections (Prati di Stuores, Mayerling, Rio Nigra) and compared to the most recent version of the Triassic Geomagnetic Polarity Time Scale (GPTS). The LCB at Prati di Stuores is calibrated through magnetostratigraphy with the U-Pb radiometric datings of Punta Grohmann, obtaining an age of the LCB of ca. 237.4 Ma. Therefore, the Ladinian should be ca. 4 Myr long and the Carnian ca. 10.4 Myr long.
Field Survey of the 2018 Anak Krakatau Tsunami on the Islands in the Sunda Strait
Authors: Fritz Hermann M. , Solihuddin Tubagus , Synolakis Costas E. , Prasetya Gegar S. , Borrero Jose C. , Skanavis Vassilis , Husrin Semeidi , Kongko Widjo , Istiyanto Dinar C. , Daulat August , Purbani Dini , Salim Hadiwijaya , Hidayat Rahman , Asvaliantina Velly , Usman Maria , Kodijat Ardito
Published: March 2020

On December 22, 2018, an eruption and partial collapse of the Anak Krakatau volcano generated a tsunami in the Sunda Strait. The tsunami caused catastrophic damage and more than 400 deaths in coastal regions of the Sunda Strait in Lampung (Sumatra) and Banten (Java). An international tsunami survey team (ITST) was deployed 6 weeks after the event to document flow depths, runup heights, inundation distances, sediment deposition, impact on the natural environment and infrastructure. The 4 to 9 February 2019 ITST focused on islands in the Sunda Strait: Rakata, Panjang, Sertung, Sebesi and Panaitan. The survey team logged more than 500 km by small boat. The collected survey data includes almost 100 tsunami runup and flow depth measurements. The tsunami impact peaked along steep slopes facing Anak Krakatau with an 85 m runup on Rakata and an 83 m runup on Sertung. The extreme runup heights were within less than 5 km of Anak Krakatau. Flow depth reached more than 11 m above ground on Sertung where a boat landing was possible and trees remained standing. On Sebesi Island located 15 km northeast of the source tsunami runup heights remained below 10 m. In contrast, tsunami heights exceeding 10 m were observed in the Ujung Kulon National Park located 50 km southwest of Anak Krakatau. The runup distributions on the islands encircling Anak Krakatau highlight the directivity of the tsunami source with the Anak Krakatau collapse towards the southwest. Inundation and damage were mostly limited to within 400 m of the shoreline given the relatively short wavelengths of volcanic tsunamis. Significant variation in tsunami impact was observed along shorelines of the Sunda Strait with tsunami heights rapidly decreasing with distance from the point source. Field observations, drone videos, and satellite imagery are presented. The team interviewed numerous eyewitnesses based on established protocol and educated residents about tsunami hazards. The tsunami caught the locals off guard despite the history and a six-month long eruptive activity in the lead up. Community-based education and awareness programs are essential to save lives in locales at risk from locally generated tsunamis. The 500 m initial height difference between the 1883 Krakatau and 2018 Anak Krakatau collapses provides a perspective on these two tsunamis. Remaining and future tsunami hazards will be affected by volcanic edifice regrowth.
Spatiotemporal influence of permafrost thaw on anthrax diffusion
Authors: Stella Elisa , Mari Lorenzo , Barbante Carlo , Gabrieli Jacopo , Bertuzzo Enrico
Published: March 2020

The recent 2016 outbreak of anthrax disease affecting reindeer herds in Siberia has been associated to the presence of old infected carcasses released from thawing permafrost, underlying the emerging character of such disease in the Arctic region due to climate change. Anthrax occurs in nature as a global zoonotic and epizootic disease caused by the spore-forming bacterium Bacillus anthracis. It principally affects herbivores and causes high animal mortality. Transmission occurs mainly via environmental contamination through spores which can remain viable in permafrost for many decades.

We propose and analyze a novel epidemiological model for anthrax transmission specifically tailored for the Arctic region. It conceptualizes the transmission of disease between susceptible and infected animals in the presence of environmental contamination, considering also herding practices (e.g. seasonal grazing) and the seasonal environmental forcing caused by thawing permafrost. We performed stability analyses and implemented Floquet theory for periodically forced systems, and therefore applied our model to the 17-year-long records of permafrost thawing depth available at the Lena River Delta (northern Siberia). Accordingly, in order to spatialize potential anthrax incidence and consequently the possible hazardous areas in the Arctic, we used the Maximum Entropy (Maxent) approach considering environmental variables and, in particular, accounting for current and expected permafrost thawing rates.

Results show how temporal variability of grazing and thawing may influence and favor sustained anthrax transmission.  Also, particularly warm years are associated to increased risk of anthrax incidence. Accordingly, we show that such risk could be mitigated with specific precautions involving herding practices, for example by anticipating or postponing seasonal grazing. Finally, a spatial map of the potential Arctic areas at risk is presented, providing a tool for local authorities in view of eventual targeted prevention measures.
Troposphere-Stratosphere Coupling and the Role of Critical Layer Nonlinearity
Authors: Dell Imogen
Published: March 2020

There exists a coupling mechanism between the troposphere and the stratosphere, which plays a fundamental role in weather and climate. The coupling is highly complex and rests upon radiative and chemical feedbacks, as well as dynamical coupling by Rossby waves. The troposphere acts as a source of Rossby waves which propagate upwards in to the stratosphere, affecting the zonal mean flow. Rossby waves are also likely to play a significant role in downward communication of information via reflection from the stratosphere in to the troposphere. A mechanism for this reflection could be from a so-called critical layer. A shear flow exhibits a critical layer where the phase speed equals the flow velocity, where viscous and nonlinear effects become important. A wave incident upon a critical layer may be absorbed, reflected or overreflected, whereby the amplitude of the reflected wave is larger than that of the incident wave. In the case of troposphere-stratosphere coupling, the concept of critical layer overreflection is key to understanding atmospheric instability.

Motivated by this, a mathematical framework for understanding the coupling will be presented together with an investigation in to the role of nonlinearity versus viscosity inside the critical layer.
Gully Initiation on the Quartzite Ridges of Ibadan, South West, Nigeria
Authors: Fashae Olutoyin , Obateru Rotimi , Olusola Adeyemi
Published: March 2020

Gullies are morphological evidences that reflect the impact of environmental changes on landscape. In an attempt to emphasize the importance of topography on gully initiation and development in an area of uniform geology, this study examined the morphological characteristics of hillslope and the role of topographic mechanism in gully initiation on a quartzite terrain of Ibadan, South western Nigeria. Four prominent quartzite ridges exist in Ibadan namely Mokola, Mapo, Eleyele and Ojoo, each of which except the latter is characterized with significant gully systems. Field measurement was carried out to determine the gully morphological characteristics such as length, width, depth, area and depth of gully head, width/depth ratio, gully sinuosity and gully shape while Digital Elevation model (DEM) was used to examine the slope-area relationship. The slope-drainage area threshold was established for each of the gully systems.  

The average gully density of the study area is 2.48km/km2 and the gully frequency is 9.72 gullies/km2. Although an investigation into the variation of the gully morphology and initiation show that human activities and vegetation are contributary factors to their development. However, topographic characteristics exhibit a dominant role in the gullying process. The ridges were observed to trend in NNW-SSE direction with slope angles ranging between 5o and 30o. The inverse relationship derived between the topography and gully dimension (r = 0.462), suggested that gully initiation processes are dominant on gently sloping ridges due to extensive surface area on a deeply weathered regolith that enhances fluvial processes of material detachment on the one hand and anthropogenic conditions on the other hand. Thus, further geomorphological assessment of landform units in Ibadan is necessary with a view of identifying potential geomorphic risk prone areas, an essential component of risk management for dense urban areas of the tropics.
Evaluating the Consistency of All Submicron Aerosol Mass Measurements (Total and Speciated) for the NASA Atmospheric Tomography Aircraft Mission (ATom)
Authors: Guo Hongyu , Campuzano-Jost Pedro , Nault Benjamin , Day Douglas , Williamson Christina , Kupc Agnieszka , Brock Charles , Schill Gregory , Froyd Karl , Murphy Daniel , Scheuer Eric , Dibb Jack , Katich Joseph , Jimenez Jose
Published: March 2020

The Aerodyne Aerosol Mass Spectrometer (AMS) is a widely used instrument to quantify the composition of non-refractory submicron aerosol, in particular, organic aerosol (OA). Past comparisons, particularly of aircraft data in continental areas, have shown good overall agreement with other chemical and optical sensors. Recently, theoretically-based concerns have been raised regarding the overall AMS calibration uncertainties (particularly for OA), although there is no evidence that those apply to aircraft datasets.

The ATom mission sampled the remote marine troposphere from 87S to 82N and from 0 to 12.5 km over the course of four aircraft deployments over the space of 2 years, carrying an advanced aerosol payload that included particle sizing instruments operated by NOAA ESRL, as well as several chemical sensors: UNH Mist Chamber and Filters for inorganic aerosol, NOAA SP2 for black carbon measurements, NOAA PALMS instrument for single particle composition and the CU aircraft high-resolution AMS for non-refractory submicron mass. This provides a unique opportunity to explore the agreement of the different instruments over a very large range of conditions and calibration regimes, and improve our understanding of the various instrumental uncertainties in field data.

Special attention was paid to characterize the AMS size-dependent transmission with in-field calibrations; this provided crucial context when comparing with instruments with very different size cuts. Excellent agreement was found between the AMS calculated volume (including black carbon from the SP2) and the PM1 volume derived from the NOAA particle sizing measurements over three orders of magnitude (slope 0.94). The comparisons for sulfate, OA, and seasalt (the three main components of the remote PM1 aerosol) measured by AMS with the PALMS instrument showed similar consistency once differences in particle detection at different sizes were accounted for. Similarly, comparisons with sulfate from filters showed good consistency once episodes with large supermicron mass were filtered out. Comparisons of the AMS with the mist chamber sulfate were affected by the variable time response of the latter instrument but were overall consistent. Overall, no evidence for AMS calibration artifacts or unknown sources of error was found for these datasets. A comprehensive evaluation of the different sources of uncertainty and their impact on the comparisons was performed, and factors to be considered for performing such intercomparisons and improving the reliability of submicron mass quantification in the future are discussed.
Mapping landslides from EO data using deep-learning methods
Authors: Prakash Nikhil , Manconi Andrea , Loew Simon
Published: March 2020

Landslide hazard has always been a significant source of economic losses and fatalities in the mountainous regions. Knowledge of the spatial extent of the past and present landslide activity, compiled in the form of a landslide inventory map, is essential for effective risk management. High-resolution data acquired by Earth observation (EO) satellites are often used to map landslides by identifying morphological expressions that can be associated with past and/or recent deformation. This is a slow and difficult process as it requires extensive manual efforts. As a result, such maps are not readily available for all the landslide hazard affected regions. Fully automated methods are required to exploit the exponentially increasing amount of EO data available for landslide hazard assessments. In this context, conventional methods like pixel-based and object-based machine learning strategies have been studied extensively in the last decade. Recent advances in convolutional neural network (CNN), a type of deep-learning method, has outperformed other conventional learning methods in similar image interpretation tasks. In this work, we present a deep-learning based method for semantic segmentation of landslides from EO images. We present the results from a study area in the south of Portland in Oregon, USA. The landslide inventory for training and ground truth was extracted from the Statewide Landslide Information Database of Oregon (SLIDO). We were able to achieve a probability of detection (POD) greater than 0.70. This method can also be extended to be used for rapid mapping of landslides after a major triggering event (like earthquake or extreme metrological event) has occurred.

This work is done in the framework of European Commission's Horizon 2020 project "BETTER”. More information is available on the website https://www.ec-better.eu/.
Ecohydrology of CAM plants: environmental co-benefits for agroecosystems
Authors: Porporato Amilcare , Hartzell Samantha
Published: March 2020

In spite of their potential as low input crops in arid and semi-arid regions, limitations in CAM (Crassulacean Acid Metabolism) modeling have made it difficult to compare the productivity and water use of CAM crops with their C3 and C4 counterparts on a consistent basis. Using the Photo3 model, which adds a malic acid storage and circadian rhythm to the widely accepted Farquhar et al. model for C3 photosynthesis, we analyze the coupling of CAM carbon assimilation and transpiration with the soil-plant-atmosphere continuum at an hourly timescale to explore the potential of prickly pear and agave in several semiarid locations. Model results are compared with experimental data and contrasted with results generated using the widely used and empirically based Environmental Productivity Index introduced by Park Nobel in 1980. Using model results for CAM as well as C3 and C4 species, we explore how agricultural productivity in these locations may be optimized by diversifying planting strategies among the three photosynthetic pathways. This work aims to assist in better understanding the potential of CAM for food and biofuel production in arid and semiarid regions of the world accounting also for environmental co-benefits related to enhanced carbon sequestration and reduced water demand in semi-arid, marginal lands.

 
MUFITS: A Universal Reservoir Simulator for Numerical Modelling, History Matching and Optimization of Multicomponent Flows in Porous Media
Authors: Afanasyev Andrey , Vedeneeva Elena , Gorokhova Natalia
Published: March 2020

The recent development of the academic reservoir simulator MUFITS aims its transformation to a universal software package that allows for (a) numerical modelling of non-isothermal multicomponent flows in porous media under wide range of pressures and temperatures, including under critical thermodynamic conditions, (b) history matching of non-isothermal reservoir models, and (c) optimization of thermohydrodynamic processes in porous media.

The extended simulator capabilities for modelling of multicomponent flows includes a new fluid properties module for compositional and thermal reservoir simulations using different cubic equations of state (e.g. Peng-Robinson EoS). An extended library of hydrocarbons, carbon dioxide, nitrogen, water, and other components is built into the simulator, and additional components can be characterized and loaded into the library. An arbitrary number of components can be used in particular simulation. In order to simplify the module usage, the corresponding input data are made compatible with the petroleum industry standards. Unlike many other codes, MUFITS allows for compositional modelling of non-isothermal flows of fluids which properties are predicted with a cubic EoS.

For improved history matching and optimization the simulator is supplied with an external Simulation Control Unit (SCU), which automatically changes certain parameters of the digital reservoir model and reads back the results of the simulations. An external control loop is implemented in SCU. At each iteration of the loop non-isothermal flow in a porous medium is simulated, and the simulation results are used for calculation of the objective function being minimized. In order to accelerate the history matching and optimization, the SCU can simultaneously (in parallel) run several reservoir simulations. The simulator is supplied with the build-in capabilities for the calculation of gravity changes and surface uplift/subsidence which measurements can also be automatically used in history matching.

We complement the new developments with several application examples related to gas condensate fields exploration, carbon dioxide injection in depleted oil reservoirs and gas storages, and natural flows in deep geothermal systems.

We acknowledge the funding from Russian Science Foundation under grant # 19-71-10051.
Interaction between air filled hollow particles and surface in water
Authors: Shen Chongyang
Published: March 2020

A thorough knowledge of the interaction energy between a hollow particle (HP) and a surface or between two HPs is critical to the optimization of HP-based products and assessing the environmental risks of HPs and HP-associated pollutants. The van der Waals (vdW) energy between a HP and a surface is often calculated by subtracting the vdW energies of the inner and outer HP geometries. In this study, we show that this subtraction method is only valid when the interior and exterior fluids are the same, for example, for water-filled HPs (WHPs) dispersed in an aqueous solution. Expressions were developed to calculate the vdW energies for HPs whose interiors were filled with air (AHPs). The vdW energies were then calculated between a planar surface and a spherical or cylindrical WHP and AHP, and between WHPs or AHPs. The vdW attraction between a surface and a WHP was decreased at large separation distances compared to solid particles, and this reduced the depth of the secondary minimum. In contrast, the vdW attraction for AHPs and a surface was significantly reduced at all separation distances, and even became repulsive for thin shells, and this inhibited both primary and secondary minimum interactions. The vdW attraction between WHPs decreased with increasing shell thicknesses, and this reduced aggregation in both primary and secondary minima. In contrast, aggregation of AHPs was increased in both minima with decreasing shell thicknesses because of an increase in vdW attraction. Our theoretical calculations show the evolution of vdW and total interaction energies for HPs with different interior fluids and shell thicknesses. These results help explain various experimental observations such as inhibited attachment and favorable aggregation for AHPs (e.g., carbon nanotubes) and favorable bubble coalescence.
Tectonic Deformation and Surface Processes of the Tibetan Plateau Constrained by Time Series Analysis of Sentinel-1 InSAR Data
Authors: Zinke Robert , Peltzer Gilles , Fielding Eric , Sangha Simran , Bekaert David , Owen Susan
Published: March 2020

We quantify deformation patterns resulting from tectonic motions and surface processes across the central Tibetan Plateau (29–45ºN, 83–92ºE) since late 2014 using ascending and descending passes of the Sentinel-1A and -1B radar satellites. The broad spatial extent of these data (> 106 km2), fine spatial resolution (originally 90 m pixels, resampled to 270 m pixels), and high rate of temporal sampling (12–24-day orbit repeat time) offer unprecedented resolution of surface deformation in space and time. To process such an extensive data set – including more than 100 dates and 300 interferograms per track thus far – we leverage the Advanced Rapid Imaging and Analysis (ARIA) standardized interferometric synthetic aperture radar (InSAR) products and toolbox. We construct time series of surface deformation constrained from our Sentinel-1 interferograms using the small baseline subset approach implemented by the Miami InSAR time series software in Python (MintPy). Our preliminary results from three Sentinel-1 orbits (two descending and one ascending; each comprising 10 frames along track) allow us to quantify deformation in the satellite lines of sight. Combinations of ascending and descending track measurements are used to approximate east-west and vertical ground velocities. The resulting velocity fields will provide a more complete and accurate picture of interseismic strain accumulation rates across active faults in the region such as the Altyn Tagh and Kunlun faults, and allow us to study surface processes such as permafrost active layer dynamics and isostatic adjustment due to lake level changes in unparalleled scope and detail.