bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating E. coli concentrations in irrigation pond waters with machine learning algorithms
Authors: Stocker Matthew , Pachepsky Yakov , Hill Robert
Published: March 2022

The microbial quality of irrigation water is an important factor in the field of food safety. Concentrations of the microbial contamination indicator, Escherichia coli (E. coli), are used to make microbial water quality determinations. However, relationships between the concentrations of E. coli and water quality parameters are often non-linear. Machine learning (ML) algorithms have been shown to make accurate predictions in datasets with complex relationships. The purpose of this work was to estimate E. coli concentrations in agricultural pond waters with several popular ML algorithms and observe the differences in model performances. Two ponds in mid-Atlantic U. S. were monitored biweekly during the irrigation seasons of 2016, 2017, and 2018. Samples were collected across the two ponds and E. coli concentrations were measured concurrently with 12 other water quality parameters. The resulting datasets were used to estimate E. coli concentrations using stochastic gradient boosting machines, random forest, support vector machines, and k-nearest neighbor algorithms. The performance of the algorithms was compared by treating performance metrics as statistics obtained by Monte-Carlo modeling of the algorithms. The results of repeated 10-fold cross-validation showed that the random forest model provided the lowest RMSE value for predicted E. coli concentrations in both ponds for individual years and when multi-year datasets were evaluated. However, in most cases there was no significant difference (P > 0.05) between RMSE of random forest and other ML models. For individual years, the normalized RMSE of the predicted E. coli concentrations (log10 CFU 100 mL-1) ranged from 0.071 to 0.124 and from 0.102 to 0.155 for Ponds 1 and 2, respectively. For the 3-year datasets, these values were 0.119 and 0.132 for Ponds 1 and 2, respectively.  Turbidity, dissolved organic matter content, specific conductance, chlorophyll concentration, and temperature were the most important predictors as identified by a recursive feature elimination analysis. Model predictive performance did not significantly differ when the 5 least expensive and time-consuming predictors were used as compared with the complete set of predictors. Machine learning appeared to be efficient in discerning complex relationships between E. coli and water quality parameters which describe the aquatic habitat.  
Quantifing the influence of meteorological and large-scale atmopsheric drivers on energy compound events
Authors: Otero Noelia , Martius Olivia , Allen Sam , Bloomfield Hannah , Schaefli Bettina
Published: March 2022

 The transition towards decarbonized power systems requires to account for the impacts of the climate variability and climate change on renewable energy sources. With the growing share of wind and solar power in the European power system and their strong weather dependence, balancing the energy demand and supply becomes a great challenge. In this study, we assess energy compound events, defined as periods of simultanous low renewable production of wind and solar power, and high electricity demand. Using a country-based logistic regression approach, we model the binary occurrence of energy compound events and we examine the effects of meterological and weather regimes. Then, we quantify the meteorological conditions resulting in the highest probability of occurrence of energy compound events. We found that the combination of extremely low temperatures (below the 5th percentile) and low wind speed (below the 10th percentile), along with moderate-high solar radiation (above the 50th percentile), lead to the highest probability of occurrence of energy compound events over most European countires. Furthermore, we show that blocked weather regimes lead to the weather conditions that can have a major risk in the European power system. In particular, the Greenland blocking and the European blocking were associated with widespread energy compound events that affected multiple countries at the same time. Our results highlight the importance of the weather regimes that result in spatially compounding energy events, which might a major impact within a potential fully interconnected European grid.
Understanding land cover influence on water resources in south-central Chile: A hydrological modelling with baseflow recession analysis approach 
Authors: Balocchi Francisco , Arumi José Luis , Rivera Diego , Iroumé Andrés
Published: March 2022

Land cover change and its effect on water resources has been a continuous concern in south-central Chile. In this regard, we use two methodologies to study the effect of different land covers on the hydrological processes in several experimental catchments (<100km2) located between 36°S to 39°S. These experimental catchments include native forest and commercial plantations (Monterrey Pine and Eucalyptus) land covers. The first methodology is the use of hydrological modelling to analyze the land cover influence on the water yield of a catchment. [1] compared hydrological and evapotranspiration models and selected the best which represented daily stream flow. The best results were obtained through the more complex model (i.e GR6J and Oudin PET model) which can account for groundwater interaction. The second methodology is the use of the recession coefficient (a) as a metric for baseflow recession analysis, which is a good index of the risk of flow decreasing below a threshold. This coefficient represents the rate of decrease in streamflow after a rainfall event. [2] investigated through mathematical modelling how (a) differs between land cover within the same study sites as [1] study mentioned above. This coefficient did not differ in winter, indicating a similar soil saturation, but some differences were found in summer.  It was determined that (a) was similar between land cover types. Considering both methodological approaches we can conclude that at the experimental catchment scale geology and the fractured rock system play a crucial role in surface-groundwater interactions in these ecosystems. Therefore, future investigations should be focused on subsoil processes and surface-groundwater interaction. Due to its Mediterranean climate, rainfall in Chile is concentrated during winter months, when trees are dormant, meaning that they do not significantly transpire, and a larger proportion of rainfall can infiltrate into the soil. Therefore, metrics such as (a) can help develop landscape planning strategies to increase water availability in conjunction with hydrological modelling. 

References:

[1] Flores, N., Rodríguez, R., Yépez, S., Osores, V., Rau, P., Rivera, D., & Balocchi, F. (2021). Comparison of Three Daily Rainfall-Runoff Hydrological Models Using Four Evapotranspiration Models in Four Small Forested Watersheds with Different Land Cover in South-Central Chile. Water, 13(22), 3191.

[2] Balocchi, F., Flores, N., Arumí, J. L., Iroumé, A., White, D. A., Silberstein, R. P., & Ramírez de Arellano, P. (2021a). Comparison of streamflow recession between plantations and native forests in small catchments in Central‐Southern Chile. Hydrological Processes, 35(6), e14182.
Multi-proxy evidence for the denudation of Taiwan at the start of the Pliocene
Authors: Hsieh Amy I. , Dashtgard Shahin E. , Wang Pei-Ling , Horng Chorng-Shern , Su Chih-Chieh , Lin Andrew T. , Vaucher Romain , Löwemark Ludvig
Published: March 2022

Collision between the Philippine Sea Plate and the Eurasian Plate in the late Miocene-early Pliocene resulted in the uplift of Taiwan, and lithospheric flexure to the west formed the adjacent Western Foreland Basin (WFB). Petrographic studies of late Miocene to Recent sediment and sedimentary strata in the WFB indicate that Taiwan was the main sediment source to the WFB in the early- to mid-Pleistocene, and prior to this, sediments were assumed to be derived primarily from the Eurasian continent. However, uplift of Taiwan began significantly earlier, and sediment derived from the island should reflect the onset and acceleration of uplift and subsequent erosion.

To resolve the timing of changes in sediment sources in the WFB, we present clay mineralogy, carbon and nitrogen geochemistry, and magnetic susceptibility data from the late Miocene to late Pliocene Kueichulin Fm that outcrops along the Da’an River in western Taiwan. This formation is composed of the lower Kuantaoshan Member, the middle Shihliufen Shale, and the upper Yutengping Sandstone. Clay mineralogy shows an upward increase in illite and illite crystallinity, and a decrease in chlorite and kaolinite starting at the base of the Shihliufen Shale, and this suggests that rapid erosion of Taiwan became a major sediment source to the WFB between the late Miocene and early Pliocene (Shihliufen Shale). δ13Corg­­­ and C/N ratios preserve the dominance of Taiwan-derived sediment in the early Pliocene where there is a marked change from dominantly marine- to dominantly terrestrially sourced carbon at the transition from the Shihliufen Shale to the overlying Yutengping Sandstone. Finally, a rapid decrease (>50%) in magnetic susceptibility across the Shihliufen/Yutengping boundary indicates a significant dilution of magnetic minerals deposited in the WFB by the high flux of non-magnetic minerals delivered from the Taiwan orogenic belt. Together, these datasets record a major shift in sediment source to the WFB during the late Miocene to early Pliocene, and that Taiwan became the dominant source of sediment supply to the WFB by the early Pliocene, approximately two million years earlier than previously thought.
What drives increased evaporation at cloud top in polluted stratocumulus clouds?
Authors: Igel Adele , Williams Abigail
Published: March 2022

Observations and simulations show that an increase in aerosol concentration typically leads to an increase in liquid water path in precipitating stratocumulus clouds due to precipitation suppression, but once precipitation is fully suppressed, further increases in aerosol concentration typically lead to a reduction in liquid water path due to enhanced evaporation at cloud top. The increased evaporation is typically attributed directly to the presence of smaller, more numerous cloud droplets. However, observations suggest that the evaporation rate is primarily controlled by the entrainment mixing rate rather than the droplet properties at the tops of stratocumulus clouds. As such, aerosol-induced changes to droplet properties should not directly lead to faster evaporation. Our simulations suggest instead that the smaller, more numerous droplets enhance the cloud top maximum radiative cooling rate, which in turn increases the entrainment rate and speeds evaporation. Our results highlight that unlike integrated radiative cooling, maximum radiative cooling continues to increase with increasing liquid water path and remains sensitive to droplet properties at high liquid water path. As such, the role of radiation in driving aerosol-cloud interactions may need additional consideration in the future.
Machine learning and geomorphometrical objects for convex and concave geomorphological features detection
Authors: Niculiță Mihai
Published: March 2022

The delineation of geomorphometrical objects that can be translated to geomorphological features is one of the most practical aspects of geomorphometry. The concave (closed depressions) or convex features (mounds) are often important to be delineated from multiple points of view: theoretical approaches, planning for practical purposes, or various other aspects. In this work, I have approached sinkholes and burial mounds as representative cases of concave and convex features represented on high-resolution DEMs. Based on manual delineations, several algorithms of object-based delineation were tested for accuracy. The interest was in delineating as much as accurate possible the targeted features. Further, the segments were fed to a multilayer perceptron for the classification of the delineated segments. The results show promising accuracy in regard to both types of features.
A warming-induced rainfall heterogeneity accelerates landscape evolution
Authors: Peleg Nadav , Ramirez Jorge Alberto , Marra Francesco , Skinner Chris , Fatichi Simone , Molnar Peter
Published: March 2022

The hydro-morphological response of a catchment is highly dependent on rainfall properties, including rainfall intensity, storm duration and frequency, and the timing of those events. Furthermore, rainfall spatial variability impacts streamflow, erosion, and sediment transport, and is explored primarily in the context of heavy rainfall triggering floods and rapid morphological changes on hillslopes and in channels. In order to examine the potential effects of warming on hydro-morphological responses, we first examined how changes in air temperature are affecting the spatial structure of rainfall. We observed that heterogeneity increases as temperatures rise. Then, we investigated the sensitivity of fast hydro-morphological responses to increasing temperatures and rainfall heterogeneity scenarios by simulating an extreme rainfall event that occurred in August 2005 in the Kleine Emme stream in Switzerland. The results show that rainfall heterogeneity has a greater impact on erosion processes than simply intensifying high rainfall intensities. We also looked at how changes in rainfall patterns affect landscape evolution over hundreds of years at the catchment scale. Multiple realizations of hourly rainfall fields, each with a different spatial distribution but identical in all other respects, were simulated using a stochastic weather generator, and the impact of the storm heterogeneity on catchment morphology was assessed using a landscape evolution model (CAESAR-Lisflood). We found that erosion and deposition rates increased and net erosion and deposition areas changed (increased and decreased, respectively) when the rain became less uniform in space. Increasing temperatures and rainfall heterogeneity resulted in longer, deeper, and more branched gullies. The results of these studies indicate that heterogeneity in rainfall spatial patterns accelerates landscape development even when rainfall volumes and temporal structures are identical.
A Study of Small-Scale Brightenings using EUV Data from SPICE on board Solar Orbiter
Authors: Rodriguez Gomez Jenny Marcela , Young Peter , Kucera Therese
Published: March 2022

Recently small-scale solar dynamic features have been observed on the Sun by Solar Orbiter/EUI (Berghmans et al. 2021; Panesar et al. 2021). These events (initially referred to as “campﬁres”) are small-scale heating events observed mainly in the solar corona. The Spectral Imaging of Coronal Environment (SPICE; SPICE Consortium et al. 2020) is a high-resolution imaging spectrometer that observes the Sun in extreme ultraviolet (EUV) wavelengths. This study uses L2 SPICE data (calibrated images)  to characterize and follow the evolution of these small-scale brightenings. Additionally, we use HRIEUV 174 Å on board Solar Orbiter and Stereo A datasets to have a complementary view of small-scale brightenings during the study period.
Relationship between spatial distribution of landslides in Bhutan and geographical parameters
Authors: Tada Kazuaki , Nagai Hiroto
Published: March 2022

Landslide is a disaster which is affecting countries with high-relief topography and large-amount precipitation. A typical example is Bhutan. Major roads are sometimes blocked by landslides caused by monsoon-derived intensive precipitation events. To understand where landslide is prone to occur in Bhutan, we need geographical assessments focused on both of spatial distribution of past landslide mass movements and that of precipitation. In this study, landslide features were delineated from high-resolution satellite imagery and Digital Surface Model (DSM) collected by the Advanced Land Observing Satellite (ALOS) operated by the Japan Aerospace Exploration Agency (JAXA). We define three domains located in different river basins as our study site. They are located in the Mangde river tributary, the Wang river tributary, and the Drangme river tributary. Multiple geographical parameters were calculated from ALOS-derived DSM data; i.e. elevation, slope angle, distance from the river, curvature, topographic wetness index (TWI), stream power index (SPI), and sedimentary transport index (STI). Frequency ratio (FR) was calculated by the number of pixels in each class of parameter to evaluate the geographic conditions that are known to be associated with landslides.

The results show that the FR was greater in places with (1) lower elevation, (2) closer distance from the river relative to the entire watershed, and that landslides are more likely to occur under these conditions in all three study areas. The larger FR at lower elevations is presumably due to other factors, such as weathering, which are affected by elevation. The finding that the FR was larger in the area closer to the river is explained by a hypothesis that erosion of the lower part of the slope reduces the stability of the slope and makes landslides more likely to occur. In addition, representative values of geographical parameters in the study areas were compared with each other. The Drangme river tributary area with the smallest elevation and distance from the river has the largest percentage of landslide features. They indicate the same trend as (1) and (2). Thus, elevation and distance from river are important parameters to know landslide prone area in these districts.
Global Mean Mass Sea-Level Rise From 1993 to 2016 Derived by Tongji Monthly Gravity Field Solutions
Authors: Shen Yunzhong , Chen Qiujie , Wang Fengwei , Zhang Xingfu , Nie Yufeng
Published: March 2022

In this contribution, we estimate the global mean mass sea-level (GMMSL) rise spanning January 1993 to December 2016 by using the Tongji-Grace2018 and Tongji-LEO2021 monthly gravity field solutions. In the post-processing, Tongji-Grace2018 and Tongji-Leo2021 solutions are filtered with P4M6 decorrelation plus Gauss 300km filtering, Tongji-Leo2021 solutions are filtered with Gaussian 1000km filtering, the C20 and degree-1 coefficients are replaced with those from the GRACE technique note 13 and 14 for Tongji-Grace2018 solutions, and with those from satellite laser ranging for Tongji-LEO2021 solutions, the post-glacial isostatic adjustments are corrected with ICE6G-D model, and a 300km buffer zone is used due to leakage error. Moreover, the GMMSL is averaged with the open oceans within the latitude of ±66°, the Caspian Sea, Black Sea and the Mediterranean Sea are excluded. The derived GMMSL rise from Tongji-LEO2021 and Tongji-Grace2018 solutions is 1.67±0.08 mm/yr from 1993.01 to 2016.12, consistent with 1.73±0.08 mm/year from Altimetry minus Steric. When the same missing months as gravity field solutions are removed, the GMMSL rise from Altimetry minus Steric is 1.68±0.08 mm/yr from 1993.01 to 2016.12, much close to that from Tongji-LEO2021 and Tongji-Grace2018 solutions.
Defining a Unified Height System for Africa using Relativistic Geodetic Approaches.
Authors: Ashry Mostafa , Shen wenbin , Shen ziya , Pengfei Zhang , Ruby Abdelrahim , Abd-Elmotaal Hussein
Published: March 2022

Establishing an International Height Reference Frame (IHRF) has been a major goal of the International Association of Geodesy (IAG) for a long time. The scope of this study is to define a unified height system for Africa using the advantages of relativistic geodetic approaches via spatial time-frequency links. We propose a ground clock network connected with the ACES (Atomic clocks ensemble in Space) by frequencies transfer. The gravitational potential of the ACES will be determined using a gravity field model. The ground stations include stationary clocks as the backbone of the frame. Frequency transfer between the ACES and these stations will be simulated. The gravitational potential differences between the ACES and the ground stations will be computed using the tri-frequency combination method. Finally, the gravitational potential of the ground stations will be determined and converted to orthometric height. The TFC uses the uplink of carrier frequency 13.475 GHz (Ku band) and downlinks of carrier frequencies 14.70333 GHz (Ku band) and 2248 MHz (S-band) to transfer frequency signals. Here we present a simulation experiment. In this experiment, we use the international space station (ISS) orbit data, ionosphere and troposphere models, regional gravitational potential and geoid for Africa, solid Earth tide model, and simulated clock data by a conventionally accepted stochastic noises model. We consider various effects, including the Doppler effect, second-order Doppler effect, atmospheric frequency shift, tidal effects, refraction caused by the atmosphere, and Shapiro effect, with accuracy levels of decimetres. This study is supported by the National Natural Science Foundations of China (NSFC) under Grants 42030105, 41721003, 41804012, 41631072, 41874023, Space Station Project (2020)228, and the Natural Science Foundation of Hubei Province of China under Grant 2019CFB611.
Meridional energy transport extremes and the general circulation of NH mid-latitudes: dominant weather regimes and preferred zonal wavenumbers
Authors: Lembo Valerio , Fabiano Federico , Galfi Vera Melinda , Graversen Rune , Lucarini Valerio , Messori Gabriele
Published: March 2022

The extratropical meridional energy transport in the atmosphere is fundamentally intermittent in nature, having extremes large enough to affect the net seasonal transport. Here, we investigate how these extreme transports are associated with the dynamics of the atmosphere at multiple scales, from planetary to synoptic. We use ERA5 reanalysis data to perform a wavenumber decomposition of meridional energy transport in the Northern Hemisphere mid-latitudes during winter and summer. We then relate extreme transport events to atmospheric circulation anomalies and dominant weather regimes, identified by clustering 500 hPa geopotential height fields. In general, planetary-scale waves determine the strength and meridional position of the synoptic-scale baroclinic activity with their phase and amplitude, but important differences emerge between seasons. During winter, large wavenumbers (k = 2 − 3) are key drivers of the meridional energy transport extremes, and planetary and synoptic-scale transport extremes virtually never co-occur. In summer, extremes are associated with higher wavenumbers (k = 4 − 6), identified as synoptic-scale motions. We link these waves and the transport extremes to recent results on exceptionally strong and persistent co-occurring summertime heat waves across the Northern Hemisphere mid-latitudes. We show that these events are typical, in terms of dominant regime patterns associated with extremely strong meridional energy transports.

Link to pre-print: https://wcd.copernicus.org/preprints/wcd-2021-85/
Effects of biochar addition into intensive-olive orchard soils under deficit irrigation
Authors: Campos Paloma , Sánchez-Martín Águeda , Santa-Olalla Arturo , Miller Ana Z. , de la Rosa José María
Published: March 2022

Agriculture is facing the challenge of providing food for a growing world population in a context of climate change. The Mediterranean region is characterized for a semi-arid climate. Thus, water scarcity is coupled with the development of intensive crops that require irrigation, such as olive orchards. Recently, biochar –the solid aromatic carbonaceous product of the pyrolysis of residual biomasses– has been proposed as an amendment for reducing soil water loss [1] and increasing plant productivity [2].  The main objective of this study was to compare the effects of the application of biochar and green-compost (the organic amendment traditionally used) on soil properties and crop productivity at a super-intensive plantation of arbequina olive trees under deficit irrigation located at “La Hampa” field station (Coria del Río, Seville, Spain). Thus, soils were amended with 40 t ha-1 of olive-waste biochar, green-compost or a biochar-compost mixture (50 % w/w). Un-amended plots were used as control. On a monthly basis, soil pH, water holding capacity, humidity and penetrability resistance, as well as TC and TN contents of soils were determined. Finally, the total weight of produced-olives per tree was measured.

Results showed that biochar application was the most effective amendment in increasing soil water holding capacity and moisture. All the organic amendments reduced the soil penetrability resistance. Olive production increased about 15 % at the biochar amended plots. Thus, the application of organic amendments, especially biochar, improved soil physical properties and led to a higher crop production.

Acknowledgements: The BBVA foundation is gratefully acknowledged for funding the scholarship Leonardo to “Investigadores y Creadores Culturales 2020”, what made this project possible.

References:

[1] Campos et al., 2021. Agronomy 11, 1394. https://doi.org/10.3390/agronomy11071394

[2]De la Rosa et al., 2014. Science of the Total Environment 499, 175-184. http://dx.doi.org/10.1016/j.scitotenv.2014.08.025
Grain-resolving simulations of submerged cohesive granular collapse
Authors: Zhu Rui , He Zhiguo , Zhao Kunpeng , Vowinckel Bernhard , Meiburg Eckart
Published: March 2022

We investigate the submerged collapse of weakly polydisperse, loosely packed cohesive granular columns, as a function of aspect ratio and cohesive force strength, via grain-resolving direct numerical simulations. The cohesive forces act to prevent the detachment of individual particles from the main body of the collapsing column, reduce its front velocity, and yield a shorter and thicker final deposit. All of these effects can be accurately captured across a broad range of parameters by piecewise power-law relationships. The cohesive forces significantly reduce the amount of available potential energy released by the particles. For shallow columns, the particle and fluid kinetic energy decreases for stronger cohesion. For tall columns, on the other hand, moderate cohesive forces increase the maximum particle kinetic energy, since they accelerate the initial free-fall of the upper column section. Only for larger cohesive forces do the peak kinetic energy of the particles decrease. Computational particle tracking indicates that the cohesive forces reduce the mixing of particles within the collapsing column, and it identifies the regions of origin of those particles that travel the farthest. The simulations demonstrate that cohesion promotes aggregation and the formation of aggregates. They furthermore provide complete information on the temporally and spatially evolving network of cohesive and direct contact force bonds. While the normal contact forces are primarily aligned in the vertical direction, the cohesive bonds adjust their preferred spatial orientation throughout the collapse. They result in a net macroscopic stress that counteracts deformation and slows the spreading of the advancing particle front.
Improving the skill of sub-seasonal forecasts of wind speed and surface temperature using information from large-scale fields: a proof of concept
Authors: Goutham Naveen , Plougonven Riwal , Omrani Hiba , Parey Sylvie , Tantet Alexis , Tankov Peter , Hitchcock Peter , Drobinski Philippe
Published: March 2022

With the continuously increasing share of renewables in the electricity mix, the sub-seasonal predictions of 100 m wind speed and surface temperature, if skillful, can provide significant socio-economic value to the energy sector. In this study, we develop a novel hybrid statistical-dynamical probabilistic prediction model to improve the skill of sub-seasonal predictions of 100 m wind speed (U100) and 2 m temperature (T2m). For the statistical part, multivariate statistical analysis is carried out between the observed gridded large-scale fields such as the geopotential height at 500 hPa (Z500) and the gridded predictand (U100 or T2m) over Europe to obtain weather regimes conditioned on the targeted predictand. The relationship between the predictor and the predictand is then used to 'reconstruct' sub-seasonal predictions of U100 and T2m based on the predictions of Z500, which are more skillful than the surface variables. This is applied on sub-seasonal predictions from the European Centre for Medium-Range Weather Forecasts. The new 50 ensemble members of 'reconstructed' surface fields are combined with the original 50 members of dynamical/direct predictions. The resulting hybrid prediction ensemble is found to be generally more skillful than the dynamical predictions on sub-seasonal timescales.
Asthenospheric Flow through the Izanagi-Pacific Slab Window and its Influence in East Asia
Authors: Brown Hamish , Colli Lorenzo , Bunge Hans-Peter
Published: March 2022

The tectonics of East and Southeast Asia are notoriously complex. Consisting of an intricate patchwork of microplates and accreted terrains, even the recent (i.e Cenozoic) tectonic history of the region remains controversial; and many differing reconstructions have been proposed. While the exact kinematics remain poorly constrained, it is generally accepted that the region has been characterised by a long history of subduction and downwelling. However, numerous geological and geophysical observations, at a first glance, appear to lie in stark contrast to this history. For example, regions of present-day dynamic uplift inferred from residual topography studies, the observation of seismically slow anomalies in numerous tomography models, and the widespread intraplate volcanism in East Asia since the latest Paleogene are all at odds with the expected cold upper mantle and downwelling associated with a history of subduction. Here, we propose a solution to this problem, in which hot asthenospheric material flows from the Pacific domain into East Asia—passing through the slab window opened by the subduction of the Izanagi-Pacific ridge during the early Cenozoic. To investigate this hypothesis, we compare several independent geological observations to the asthenospheric flow predicted by a suite of recently published 3D global mantle convection models.  Firstly, we compare observations linked to uplift and erosion to the changes in dynamic topography induced by this influx of hot material. These include the widespread late Eocene–Oligocene sedimentary hiatus in far eastern China and the regional erosion of southeastern China since the Miocene inferred from Apatite Fission Track Thermochronology (AFT) studies. Secondly, the timing and location of intraplate volcanism is compared with the predicted distribution of hot material through time. We find the westward influx of asthenospheric material to be a robust feature in the models, being predicted under all considered tectonic reconstructions.  Nevertheless, the influence of this material is significantly affected by differing implementations of the Philippine Sea Plate (PSP) history, which allows us to distinguish between these reconstructions based on their correlations with the evidence considered. A larger PSP is found to predict dynamic subsidence in regions where uplift and erosion is present, such as the East China Sea Shelf Basin and the Cathaysia Block, while also predicting large-scale mantle downwelling in regions where intraplate OIB-type magmatism has been recorded. A smaller PSP and the consequent existence of the hypothesised 'East Asian Sea' slabs instead allows the hot asthenospheric material to predominate over a larger region, providing a better fit to the spatial distribution of regional-scale erosional episodes and OIB-type magmatism.
Observed Effects of Vertical wind shear on the intensities of Mesoscale Convective Systems in West Africa.
Authors: Baidu Michael , Schwendike Juliane , Marsham John , Bain Caroline
Published: March 2022

Vertical wind shear plays a key role in the organisation and intensification of Mesoscale Convective Systems (MCSs). In West Africa, the meridional temperature gradient between the hot Sahel and the humid Gulf of Guinea results in a strong easterly wind at mid-levels and south-westerlies at low-levels leading to a strong vertical wind shear. A decadal increase in vertical wind shear has recently been linked to a decadal increase in intense MCSs over the Sahel. Here, the effects of vertical wind shear on MCSs over West Africa have been investigated using a 10-year (1998 - 2007) MCS dataset. The results show that, a strong vertical wind shear is associated with long-lived, fast moving, large and cold (deep) storms with high rain-rates.  The observed cloud-top heights of storms over the oceans are closer to their level of neutral buoyancies (LNBs) compared to their land counterparts. We hypothesise that this is due to greater entrainment dilution over land compared to storms over the ocean. The difference between the observed cloud-top heights and the LNBs of land MCSs is minimised over regions of high vertical wind shear. Strong vertical wind shear results in colder brightness temperatures relative to the temperature at their LNBs. This is consistent with recent modelling work showing that shear reduces  entrainment dilution of squall-line updrafts. We conclude that, modelling the impacts of vertical shear, which are normally missed in convection parameterisations, are not only important for predictions of high impact weather, but also important for modelling the climatology of anvil heights.
Built cultural heritage of Ouro Preto, Brazil: an architectural legacy edified in quartzite stone
Authors: Costa Antônio , Boas Paola
Published: March 2022

The city of Ouro Preto, located in Minas Gerais, Brazil, a cultural heritage of humanity since 1980, has still preserved within its listed urban site, buildings built from the 18th century, when Brazil was still a Portuguese colony. In a geological context, it is certain that the city grew in the middle and is surrounded by mountain ranges formed by quartzite crests with some occurrence of schist and steatites in the regions of its valleys. Based on comparisons with other regions of the country, it can be stated that due to this particular geodiversity, the city stands out even from others in Minas Gerais, due to the volume and diversity of quartzite material used in its buildings. The architectural ensemble that served as the basis for the granting of the title by Unesco includes buildings and monuments with public, religious and private purposes, which make up a legacy of importance for the history of Minas Gerais and Brazil. The set built using quartzite material, however, inspires attention, since the artisanal process of extracting and processing the pieces did not take into account properties suitable for applications, which until then were little known. Taken from known areas around the city and located in the mountains known as Ouro Preto and Itacolomy, it appears that the process did not involve steps and procedures that are typical of quarries, especially those we know today. These rocks were, for the most part, collected both in the form of blocks and plates, later undergoing some kind of processing. The blocks were widely used as structuring elements, such as pillars and columns, door and window frames and the plates, used in external and internal coatings. With some frequency, blocks were also used in decorative elements in masonry, such as portals on church facades and even in sculptural art, with the production of elements that make up various building facades such as, for example, the former Chamber and Prison House, currently headquarters of the Museum of the Inconfidence. With a greater or lesser degree of detail, these works can also be seen in the nineteen churches and chapels inserted in the listed perimeter. Sculptural elements are also present in a good part of the various fountains built in different parts of the old city, among them, six individually listed and whose objective was to facilitate the supply of water to the city. With some rarity, compositions involving the use of schists and steatite in decorative arrangements with quartzites are observed. It is understood that the survey of information on the former extraction areas of these rocks, on the various types of applications and on the buildings that are part of this architectural set, as well as on their deterioration processes, will be of importance to support conservation actions of this cultural heritage.
Updated global reference models of broadband infrasound signals for atmospheric studies and civilian applications
Authors: Kristoffersen Samuel , Le Pichon Alexis , Hupe Patrick , Matoza Robin
Published: March 2022

The International Monitoring System (IMS) was established to monitor for nuclear explosions, and is capable of detecting many different signals of interest (e.g. volcanoes, earthquakes, atmospheric convection etc.) embedded in the station specific ambient noise. The ambient noise can be separated into coherent noise (e.g. microbaroms) and incoherent noise (e.g. wind turbulence). The analysis of the coherent ambient noise was expanded through the use of updated IMS data-sets up to the end of 2020 for all 53 currently certified IMS stations. Monthly reference curves will be presented, which provide a means to determine the deviation from nominal monthly behavior. An example of this use is through the Ambient Noise Stationarity (ANS) factor created for this paper, which provides quick references to the data quality compared to the nominal situations allowing for the identification of either poor data quality, or instances of strong abnormal signals of interest. Further investigation, through use of information about the number of detections can be used to distinguish between poor data quality and strong abnormal signals of interest.
Cultural Layers and Buried Soil of the Tula Kremlin (Russia) Tell About Palaeoenvironments and Landscape Transformation by Human Activity in the Late Middle Age
Authors: Khokhlova Olga , Myakshina Tatyana
Published: March 2022

Properties of the buried soil and cultural layers studied at the Tula Kremlin excavation (Central Russian Upland) allows us to carry out paleoenvironmental reconstruction of the stages of landscape transformation, characterize the early stages of human activity in this area, and also explain the location of a large cultural and economic center of the Late Middle Ages at a low hypsometric level in the immediate vicinity of the edge of the Upa River. The morphological and physicochemical characteristics of the cultural layers, buried and surface soils were studied, as well as micromorphological and micro biomorphic analyzes were carried out.

It is ascertained that the site where the fortress is located has never been flooded with a river. The buried soil developed on the mantle (loess-like) sediments is characterized by a typical profile for the surrounding watersheds. The signs of gleying (waterlogging) are weakly expressed or not expressed at all. Before the building of the fortifications, there was arable land or a kitchen garden on this site for a short time (5-7 years). In the cultural layers, due to the introduction of various building materials, there is an accumulation of substances and elements that are not characteristic of the surrounding soils. Pedogenic features preserved in the cultural layers made it possible to reconstruct the dynamics of paleoclimatic conditions in different periods of the Kremlin's construction or rebuilding. Cultural layer 1 (the 17-18th centuries) was formed in relatively humid climatic conditions, and during the formation of cultural layer 2 (the 16-17th centuries), it was slightly drier, but also colder. The soil buried under the cultural layers in the Kremlin at the beginning of the 16th century is characterized by a dark-colored humus horizon and an almost absence of eluvial horizon with bleached sandy-silty material, which was especially clearly revealed when compared with the surface soil. If the paleosol is classified as Luvic Phaeozem (Anthric, Loamic, Aric), the surface soil – as Folic Retisol (Loamic, Cutanic). The paleosol developed during the warm time of the Medieval Climate Anomaly. This work was supported within the framework of Goszadanie no. 0191-2019-0046 and by RFBR, project N 19-29-05024 mk.
Quantifying space-time patterns of precipitation importance for flood generation via interpretability of deep-learning models
Authors: Morin Efrat , Rojas Ronen , Wiesel Ami
Published: March 2022

This study proposes a new approach for quantitively assessing the importance of precipitation features in space and time to predict streamflow discharge (and, hence, sensitivity). For this, we combine well-performing deep-learning (DL) models with interpretability tools.

The DL models are composed of convolutional neural networks (CNNs) and long-short term memory (LSTM) networks. Their input is precipitation data distributed over the watershed and taken back in time (other inputs, meteorological and watershed properties, can also be included). Its output is streamflow discharge at a present or future time. Interpretability tools allow learning about the modeled system. We used the Integrated Gradients method that provides a level of importance (IG value) for each space-time precipitation feature for a given streamflow prediction. We applied the models and interpretability tools to several watersheds in the US and India.

To understand the importance of precipitation features for flood generation, we compared spatial and temporal patterns of IG for high flows vs. low and medium flows. Our results so far indicate some similar patterns for the two categories of flows, but others are distinctly different. For example, common IG mods exist at short times before the discharge, but mods are substantially different when considered further back in time. Similarly, some spatial cores of high IG appear in both flow categories, but other watershed cores are featured only for high flows. These IG time and space pattern differences are presumably associated with slow and fast flow paths and threshold-runoff mechanisms.

There are several advantages to the proposed approach: 1) recent studies have shown DL models to outperform standard process-based hydrological models, 2) given data availability and quality, DL models are much easier to train and validate, compared to process-based hydrological models, and therefore many watersheds can be included in the analysis, 3) DL models do not explicitly represent hydrological processes, and thus sensitivities derived in this approach are assured to represent patterns arise from the data. The main disadvantage of the proposed approach is its limitation to gauged watersheds only; however, large data sets are publicly available to exploit sensitivities of gauged streamflow.

It should be stressed out that learning about hydrological sensitivities with DL models is proposed here as a complementary approach to analyzing process-based hydrological models. Even though DL is considered black-box models, together with interpretability tools, they can highlight hard or impossible sensitivities to resolve with standard models.
Variable Runoff Generation Layer distributed hydrological model of hilly regions
Authors: Zhao JianFei , Liang ZhongMin , Liu JinTao , Li BinQuan , Duan YaNan
Published: March 2022

The variable runoff generation layer concept is proposed based on the new understanding of hillslope hydrological experiments to address the problem of flash flood forecasting in hilly regions. This concept has expanded the depiction of interflow from soil horizon to soil-weathering bedrock interface and provided a unified description of the infiltration excess and the saturation excess runoff and their conversion mechanism by meticulously depicting the formation and development process of interflow. Based on the concept of variable generation layer and the theory of kinematic wave model, the calculation formulas of infiltration excess (Horton), saturation excess (Dunne) surface runoff, and interflow of the unit grid are derived. The nonlinear reservoir method, 2-d diffusion wave equation, and 1-d diffusion wave equation are applied to calculate the groundwater flow, the surface runoff routing, and channel flow routing separately, based on which established the variable runoff generation layer distributed hydrological model (VRGL). The VRGL model is applied to the Tunxi watershed, a typical humid watershed of the hilly region. 24 flood events ranging from 2010 to 2019 were studied, and the results showed that the relative error of the flood peak and the flood volume were both within ±20%, and the Nash-Sutcliffe efficiency (NSE) was around 0.84. It is indicated that the accuracy of the VRGL model is high enough for flash flood forecasting in hilly regions.
Enhancing the modeling of dissolved oxygen concentration using machine learning, a case study in the Greek Mediterranean Sea. 
Authors: Spinosa Anna , El Serafy Ghada
Published: March 2022

In recent years, artificial intelligence (AI) tools have gained popularity as forecasting and predictive tools able to approximate with high accuracy trends and outcomes in many fields such as robotics, climatology, and hydrology, including water resources. AI models have shown remarkable performances handling big data and dealing with their nonlinearity and nonstationary features in monitoring and forecasting water quality, complementing the traditional numerical water quality models that provide precise parametrizations of near-shore and off-shore processes and their complex interactions.

In this research, we examine the accuracy of different machine learning techniques in estimating and predicting dissolved oxygen concentration (DO) in water bodies. DO is a crucial water quality variable that influences the living conditions of all aquatic organisms requiring oxygen. Low DO concentration, when persistent, can cause eutrophic conditions, thus altering the normal nutrient cycle, favoring the formation of algal blooms and furtherly reducing water quality and affecting the entire ecosystems, also causing fish mortality.

The Random Forest (RF) and the generalized regression neural network (GRNN) are explored and compared. The two models are developed using high frequency in situ data collected from Andromeda Group, a leading company in the aquaculture sector in Greece, at four different stations in the Greek Mediterranean Sea. The input variables used for the two models are temperature and currents. The performances of the models are evaluated using root mean square errors (RMSE) and mean absolute error (MAE). The RF and GRNN showed similar performances, with the best fit obtained using the GRNN model. Results are also compared with a traditional numerical model developed with the DELFT3D-WAQ modeling suite. The AI models show better performances in estimating daily changes of the DO concentration and by being less computationally expensive than the numerical model, enhance the water quality monitoring and provide aquaculture and farmers managers with a forecasting tool.

Acknowledgments:

The work has been conducted within the framework of the HiSea project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821934 and of the Water Harmony project, an ERA-NET WATERJPI Co-fund Action. Funding received via the Dutch Research Council - NWO Project number ENWWW.2018.1