bluuebunny/crossref_metadata_2025 huggingface dataset:
Iron(III)-carboxylate photochemistry induces iodate reduction
Authors: Iezzi Lucia , Reza Margarita , Finkenzeller Henning , Roose Antoine , Bartels-Rausch Thorsten , Volkamer Rainer , Ammann Markus
Published: March 2022

Aerosols and clouds are complex systems containing organic and inorganic species, which play central roles in atmospheric chemistry and physics, climate, air pollution and public health. Particularly chemical reactions which occur in the aqueous phase can change the composition and oxidizing capacity of the troposphere via the production and release of trace gas species. Iron(III)-carboxylate complexes impact the chemistry of the atmospheric aqueous phase due to their photochemistry which can trigger free radical chemistry generating reactive oxygen species (ROS), such as HO2 and H2O2. Several studies have highlighted the importance of iodine chemistry due to its capability to influence both oxidative capacity and radiative balance of the atmosphere. A previous work of this group demonstrated a direct link between carbonyl compounds, ROS and iodine chemistry [1]. Furthermore, observed ratios of iodide to iodate in aerosol particles and cloud droplets of the troposphere are much higher than expected [2, 3]. This is indicative of active chemical recycling of iodine between the gas and particle phases, which may be driven by not well understood reductive processes involving iodate, which is thermodynamically the most favored iodine form in the aqueous phase under oxidizing conditions.

We performed coated wall flow tube experiments (CWFT) with aqueous films containing iodate and Iron(III)-citrate (fe-cit) using citric acid (CA) as a matrix since it is an established proxy for oxygenated atmospheric organic matter and with well characterized microphysical properties. The CWFT was coupled with a CE-DOAS instrument in order to detect I2 [4] resulting from iodate reduction. The results suggest that  photochemistry promotes efficient iodate reduction, linked to the photochemical turnover of the iron(III)-carboxylate complex and to the depletion of the iodine reservoir. We speculate that reduction of iodate is driven by H2O2 according to the Bray-Liebhafsky mechanism, where H2O2 is provided by fe-cit photochemistry. 

1. P. Corral Arroyo, et al., Atmospheric Chemistry and Physics, (2019)

2. A.R. Baker and C. Yodle, Atmos. Chem. Phys. Discuss., 2021, 1 (2021)

3. T.K. Koenig, et al., Sci Adv, 7, eabj6544 (2021)

4. R. Thalman, et al., Journal of Quantitative Spectroscopy and Radiative Transfer, 147, 171 (2014)
The 2021 Pacific Northwest heat wave and associated blocking: meteorology and the role of an upstream cyclone as a diabatic source of wave activity
Authors: Nakamura Noboru
Published: March 2022

The heat wave that enveloped the Pacific Northwest from late June through early July 2021 delivered unprecedented temperatures to the normally cool region --- 108°F (42°C) in Seattle, 116°F (47°C) in Portland --- and claimed over 1000 lives mostly in British Columbia.  We investigate the meteorological and dynamical conditions that led to this extreme heat event.  The extreme surface temperatures (29-30 June) were preceded by the formation of an upper-level atmospheric blocking that snatched a warm pool of air from lower latitudes (25-27 June).  A heat-trapping stable stratification ensued within the block, raising the surface temperatures significantly.  The block itself was initiated by an upper-tropospheric wave breaking and the concomitant surface cyclogenesis off the coast of Alaska a few days prior (22-24 June).  The regional local wave activity budget reveals that a localized diabatic source associated with this storm critically contributed to the zonal wave activity flux downstream, whose convergence over Canada drove the blocking.  A simple wave activity-based reconstruction predicts a 41 percent reduction in strength and a 10-degree eastward displacement of the block when the upstream diabatic source is reduced by just 30 percent.  Our work complements previous trajectory-based studies to gain insight on the role of diabatic heating in blocking episodes.  
Deciphering streamflow composition during drought – model simulations as benchmark for advanced hydrograph separation
Authors: Stoelzle Michael , Stahl Kerstin
Published: March 2022

Prediction of hydrological drought requires good process understanding of streamflow generation. It is known that during progressing drought the water availability in rivers is a composition of different delayed contributions from various stores in the catchments. However, the composition of delayed contributions often differs a lot across landscapes and hydrogeological settings. Solutes or isotope data sets are often limited to separate different contributions only during the campaign period in a specific catchment. Hydrological models incorporate delayed contribution typically with different soil and groundwater storages to simulate total streamflow. Here we analyzed the output from different storages of the water balance model LARSIM which is a well-established operational river forecasting model in Southern Germany. We hypothesized that the different storages' contributions can also be estimated by an advanced hydrograph separation method splitting total streamflow in four delayed contributions (i.e., storm flow, fast and slow interflow and baseflow). We used the Delayed Flow Index (DFI) for hydrograph separation as, compared to a BFI index, it estimates multiple storage-outflow components. Though not entirely similar in their results, the combined analysis of model simulations and DFI hydrograph has the potential to inform water management and forecasters about relevant time scales of different streamflow contributions and drought severity. The information of streamflow storage states and contributions may help hydrological drought prediction of time periods outside the model calibration period and also for periods when faster delayed contributions consecutively cease to sustain streamflow.
The role atmospheric water management technologies might play in Nature-based solutions (NbS)
Authors: DeFelice Thomas
Published: March 2022

Atmospheric water management or cloud seeding technologies might be effectively applied to assess the impacts from changing climate on water security and renewable energy use. During said assessments it might be possible to exploit their observations to mitigate the negative impacts from climate change by enhancing the water supply as part of a water security plan, and/or by effectively removing low-level supercooled cloud decks/fogs to facilitate renewable energy use providing added sunshine during typically overcast day-time periods. Cloud seeding technologies are used to positively affect the natural hydrologic cycle, while respecting and avoiding damage to public health, safety and the environment.  This talk summarizes atmospheric water management technologies and their use, how these technologies might be applied as part of a strategy to ensure water security and how their application might provide a potential opportunity for recouping lost energy potential.
The distribution and intensity of gully erosion in different soil zones of the Hengduan Mountain area
Authors: Dong Yifan
Published: March 2022

Gully erosion was one of the key processes of soil erosion in Hengduan mountain region, which belonged to the eastern part of Qinghai-Tibet Plateau. This dramatic changes in both horizontal and vertical direction has led to a diversity soil groups within the region. The aims of this study were to investigate the gully distribution and density in different soil zones, and find out the key factors that influenced the susceptibility and intensity of gully erosion of Hengduan mountain area. Totally 2300 investigation quadrats were randomly set with the size of 1 km × 1 km to check whether the occurrence and the density by Google Earth images. The ratio of gully occurrence (GR) was 25.5%, and the average gully density (GD) and gully number (GN) was 2.22 km km-2 and 20.4 of Hengduan mountain area. The annual temperature, vegetation and slope were the key factors that influences the occurrences of gullies in the alpine (>3700 m a.s.l), middle mountain (2000-3700 m a.s.l) and low mountain (<2000 m a.s.l) soil zones, respectively. The intensity of gully erosion showed exponential decreasing relationships with soil property including soil organic matters and silt content, and the average GD in different soil zones showed the same relationships with the R2 higher than 0.7. These results indicating that the distribution of gully erosion were more related to the external environmental factors, and the intensity of gully erosion were determined by soil properties at the regional scales.
Measuring Height Difference Using Two-Way Satellite Time And Frequency Transfer
Authors: Cheng Peng , Shen WenBin , Sun Xiao , Cai Chenghui , Wu Kuangchao , Shen Ziyu
Published: March 2022

According to general relativity theory, the clock at a position with lower geopotential ticks slower than an identical one at a position with higher geopotential. Here, we provide a geopotential determination using a non-transportable hydrogen clock and a transportable hydrogen clock for altitude transmission based on the two-way satellite time and frequency transfer (TWSTFT) technique. First, we set one hydrogen clock on the fifth floor and another hydrogen clock on the ground floor of a building in Beijing, with their height difference of 22.8 m measured by tape, and compared the time difference between these two clocks by TWSTFT for 13 days. Then, we set both clocks on the ground floor and compared the time difference between the two clocks for 7 days for the purpose of the zero-baseline calibration (synchronization). Based on the measured time difference between the two clocks at different floors, we obtained the height difference 28.0±5.4 m, which coincides well with the tape-measured result. This experiment provides a method of height propagation using precise clocks based on the TWSTFT technique. This study is supported by National Natural Science Foundation of China (Grant Nos. 41721003, 42030105, 41631072, 41804012, 41874023, 41974034), Space Station Project (2020)228 and Natural Science Foundation of Hubei Province (grant No. 2019CFB611).
Predicting Heterogeneous Ice Nucleation via Short-time Molecular Dynamics Simulations and Machine Learning Approaches
Authors: Soni Abhishek
Published: March 2022

Heterogeneous ice nucleation (HIN) has various applications in the fields of atmospheric science, food preservation, and nanotechnology. Pure water can be supercooled to ∼−38 °C, and homogeneous ice nucleation at temperatures warmer than ∼−20 °C has essentially zero probability, even on the time scale of the universe. Thus, much of the freezing that occurs on the Earth’s surface or in the atmosphere occurs via a heterogeneous mechanism involving an ice nucleating particle (INP). These INPs can be mineral dust, soots, pollen, or bacteria. Generally, ice nucleation experiments identify substrates that act as efficient ice nuclei but lack sufficient spatial (nm) and/or temporal (ns) resolution to address basic mechanistic questions. Recently, molecular dynamics (MD) simulations of model systems have attempted to reveal the basic mechanism of ice nucleation and the fundamental molecular features of various good INPs. However, the large amount of computational cost required to cross the nucleation barrier and observe HIN in simulations is a current concern. Here, we employ information obtained from short MD simulations of water in contact with surfaces to predict the likelihood that particular surfaces would nucleate ice, or not, in sufficiently long simulations, or possibly in experiments. For prediction, we incorporated several supervised and unsupervised machine learning (ML) models. We considered various atomistic substrates with some surfaces differing from others, only in terms of lattice parameters, surface morphology, or surface charges.  Various water features near the surface are extracted from MD simulations over a time interval where ice nucleation has not initiated. We find that the interplay of surface properties and local liquid water properties determines good/bad INPs, with the liquid water properties being dominant. The accuracy of our best ML classification model is 0.89 ± 0.05. Some of the important descriptors are interfacial icelike structures, hydrogen bonding to the surface, water density and water polarization near the surface, and the two-dimensional lattice match to ice. Taken altogether, we expect that this work will be a useful contribution in the field of HIN research and serve as a guide in the design of substrates that can promote or discourage ice nucleation.
The implementation of ecological engineering in Tibet has strengthened the local human-policy-resource connection
Authors: Wang Yijia , Liu Yanxu , Wu Xutong , Wang Xinsheng , Yao Ying , Fu Bojie
Published: March 2022

Facing the dual threats of climate and socio-economic changes, how the social-ecological systems (SES) in the Tibet Autonomous Region can seize the opportunity of ecological restoration to enhance the quality of the environment while improving the relationship between human and nature is of great significance to promote the regional sustainable development. Thus, regarding human as the key component, we used Ostrom’s SES framework as an analytical fundation to analyze the impact of the implementation of ecological engineering on local human-policy-resource connection. We distributed questionnaires for local residents, distinguished experimental groups (EG, n=325) and control groups (CG,n =165), and used a network approach to construct indicators for assessing effectiveness of ecological engineering, including overall connectivity and evenness. Meanwhile, random forest regression was used to explore the background variables of the dominant connection and accordingly proposed subsequent directions for optimal governance. We found that interviewees in areas where ecological engineering was implemented had more positive perceptions of the importance of ecosystem services, the relationship between ecological conservation and well-being, attitudes toward ecological engineering, and the impact of measures. The overall connectivity and evenness of EG were significantly higher than that of CG. The implementation of ecological engineering enhanced the connection between local people and the environment, but caused some inconvenience to local residents’ livelihoods. Besides, elevation and annual precipitation were the background variables that dominated the overall connectivity. The overall connectivity was lower in alpine steppes with elevation of around 4000 m and semi-arid areas with annual precipitation around 400-500 mm. The implementation of ecological engineering played a positive role in alleviating human-nature relationship in tensions and promoting collective governance of common pool resources, but the governance process still involved risks. Safeguarding and improving the residents’ livelihoods and enhancing the regional weak SES coupling due to geographical constraints are the future directions for optimal governance.
Probabilistic water losses estimation in water distribution networks and comparison with the top down - water balance approach: A large-scale application to the city center of Patras in western Greece
Authors: Langousis Andreas , Serafeim Athanasios , Kokosalakis George , Deidda Roberto , Karathanasi Irene
Published: March 2022

Quantification of the Water Losses (WL) components in Water Distribution Networks (WDNs) is a vital task towards their reduction. However, current WL estimation methods rely on semi-empirical approaches with high uncertainty levels, which usually lead to inaccurate estimates of the lost volume. Here, we compare the probabilistic Minimum Night Flow (MNF) estimation method introduced by Serafeim et al. (2021) to the Water Balance components analysis, introduced by the International Water Association (IWA). The strong point of the Serafeim et al. (2021) approach is that it uses statistical metrics to filter out noise effects in the flow timeseries used for MNF estimation, leading to more accurate estimation of the low flows during night hours. The effectiveness of the applied methods is tested via a large-scale, real world application to the 4 largest Pressure Management Areas (PMAs) of the WDN of the city of Patras, the third largest city in Greece (see Serafeim at al., 2022). Although methodologically different, the two approaches lead to very similar results, substantiating the robustness of the Serafeim at al. (2021) approach which allows for reliable confidence interval estimation of the observed Minimum Night Flows, making it particularly suited for engineering applications.

Acknowledgements

The research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: 1162).

References

Serafeim, A.V., Kokosalakis, G., Deidda, R., Karathanasi I. and Langousis A (2021) Probabilistic estimation of minimum night flow in water distribution networks: large-scale application to the city of Patras in western Greece, Stoch. Environ. Res. Risk. Assess., https://doi.org/10.1007/s00477-021-02042-9

Serafeim, A.V.; Kokosalakis, G.; Deidda, R.; Karathanasi, I.; Langousis, A. (2022) Probabilistic Minimum Night Flow Estimation in Water Distribution Networks and Comparison with the Water Balance Approach: Large-Scale Application to the City Center of Patras in Western Greece, Water, 14, 98, https://doi.org/10.3390/w14010098
Mapping NBS stakeholders’ perspective over Sludge Treatment Reed Bed (STRB) in Iceland
Authors: Gholipour Amir , Duarte Elizabeth , Fragoso Rita , Galvao Ana , Christian Finger David
Published: March 2022

Nature-Based Solutions (NBSs) like Sludge Treatment Reed Beds (STRBs) can address resource recovery from sewage sludge in urban and rural areas to boost circular economy and to mitigate climate change. To ensure successful implementation of STRBs, an evaluation of stakeholders’ perceptions can be helpful to identify relevant barriers and opportunities. In this study, semi-structured interviews were conducted with relevant stakeholders, which were categorized in 5 interest groups including academics, state and governments, NGOs, water companies and local communities across Iceland. The interviews were then transcribed and effective elements influencing STRB technology in Iceland were identified through an open-coded method on the transcriptions. The elements were categorized as independent elements (NBS actors, on-going projects, feasibility, legal, economic, sociological, and natural criteria), which were grouped into 7 classifications impacting dependent elements (relevant aspects of STRB, STRB services and system cost). Through Causal Diagrams (CDs), the impact of the independent elements was visualized on the dependent elements. The result of the study is exposed in 8 causal networks and 4 aggregated CDs for sustainability, climate change, biodiversity and circular economy together with mediators interpreting the impacts. The complexity of multi-sequenced causalities of a heterogeneous nature is depicted in CDs implying by stakeholders’ reports and expectations. The study exposes information on the compatible aspects, where further research is required to facilitate the use of STRB for the resource recovery of sewage sludge in Iceland. Therefore, our findings can enable decision makers with intracommunity information to identify elements impacting STRB application, in which the influence of the multiple groups of interests is regarded. 

 

Keywords: Nature-Based Solutions; Sludge Treatment Reed Beds, Resource Recovery, Causal Diagram, climate change, circular economy, sustainability
Extensional tectonics at oceanic transform plate boundaries: evidence from seafloor morphology
Authors: Ren Yu , Geersen Jacob , Grevemeyer Ingo
Published: March 2022

Oceanic transform faults are among the most prominent morphologic features in ocean basins, offsetting mid-ocean ridges by tens to hundreds of kilometers. Since the inception of plate tectonics, transform faults have been assumed to be simple, two-dimensional strike-slip, conservative plate boundaries, where lithosphere is neither created nor destroyed. This concept nurtured an over-simplified understanding of oceanic transform faults for many decades. New advances in seafloor mapping revealed that the morphology of oceanic transform faults is difficult to explain exclusively by strike-slip faulting and differential thermal subsidence. We compiled ship-based bathymetric data of 94 oceanic transform faults, and parameterized their morphological characteristics (e.g., length, width, depth, etc.) using quantitative geomorphologic methods. A prominent feature of most oceanic transform plate boundaries is a deep valley extending along the active transform fault. Our statistical analysis indicates that these valleys are generally deeper and wider at slow- and ultraslow-slipping rates than at faster slipping rates. However, the key feature that governs structural variability, seems to be age-offset across a transform fault rather than spreading rate. While the correlation between transform morphology and spreading rate turns out to be rather weak, our statistical results consistently show that transform valleys get deeper and wider with increasing age-offset. The surface deformation pattern observed therefore supports the tectonic extension scaling with age-offset predicted by recent geodynamic simulations (Grevemeyer et al., 2021). Furthermore, at small age-offsets (< 5 Myr), scatters especially in the depth of transform valley increase, indicating that small-age-offset transforms corresponding to weak lithospheric strength are easily affected by secondary tectonic processes, such as nearby hotspots and changes in plate motion. Now, five decades after Wilson (1965) published his seminal paper on transform faults, our quantitative submarine geomorphologic study emphasizes that oceanic transform faults are not simple conservative strike-slip plate boundaries, but that tectonic extension is an integral process affecting their morphology. The larger age-offset causes greater extension at OTFs and hence wider and deeper valleys as evidenced by our statistics on transform morphology.

References

Wilson, J. T. (1965), A new class of faults and their bearing on continental drift. Nature, 207, 343–347. doi: 10.1038/207343a0

Grevemeyer, I., Rüpke, L. H., Morgan, J. P., Iyer, K., & Devey, C. W. (2021), Extensional tectonics and two-stage crustal accretion at oceanic transform faults. Nature, 591, 402–407. doi: 10.1038/s41586-021-03278-9
First analysis of landslides triggered by the August 14, 2021, Nippes (Haiti) earthquake, compared with the 2010 event
Authors: Havenith Hans-Balder , Guerrier Kelly , Schlögel Romy , Mreyen Anne-Sophie , Ulysse Sophia , Braun Anika , Victor Karl-Henry , Saint-Fleur Newdeskarl , Cauchie Lena , Boisson Dominique , Prépetit Claude
Published: March 2022

First analyses of landslide distribution and triggering factors are presented for the region affected by the August, 14, Nippes, earthquake (Mw=7.2) in Haiti. Landslide mapping was mainly carried out by comparing pre- and post-event remote imagery (~0.5-1 m resolution) available on Google Earth® and with Sentinel 2 (10 m) satellite images. The first cover about 50% of the affected region (for post-event imagery), the latter were selected to cover the entire potentially affected zone. On the basis of the completed landslide inventory, comparisons are made with a catalogue compiled by the USGS for the January, 12, 2010 seismic event (Mw=7.0); additionally, we also analyzed the pre-2021 earthquake slope stability conditions. These comparisons show that the  total number of landslides mapped for the 2021 earthquake (=7091) is smaller than the one observed for the 2010 (=23567). However, these fewer landslides triggered in 2021 cover a much wider area of slopes (>80 km2) than those induced by the 2010 event (~25 km2). A simple statistical analysis indicates that the lower number of 2021-landslides can be explained by the ‘under-mapping’ of smallest landslides triggered in 2021, partly due to the lower resolution imagery available for most of the areas affected by the recent earthquake; this is also confirmed by an inventory completeness analysis based on size-frequency statistics. The much larger total area of landslides triggered in 2021, compared to the 2010 earthquake, can be related to different physical reasons: a) the larger earthquake magnitude in 2021; b) the more central location of the fault segment that ruptured in 2021 with respect to coastal zones; c) and possible climatic pre-conditioning of slope stability in the 2021-affected area. These observations are supported by (1) a new pre-2021 earthquake landslide map, (2) rainfall distribution maps presented for different periods (including October 2016 - when Hurricane Matthew had crossed the western part of Haiti), covering a region including both 2010- and 2021 affected zones, as well as (3) the shaking intensity prediction and related simplified Newmark Displacement maps.
Globally consistent tropical cyclones impact forecast system for population displacement
Authors: Kam Pui Man , Fairless Christopher , Bresch David N.
Published: March 2022

Tropical cyclones (TCs) displace millions of people every year. Displaced people are subject to heightened risks to their physical and mental well-being. We present the first results of a TC impact forecast system for population displacement, aiding the decision-making process for planning early prevention and mitigation actions. For example, planning precautionary evacuations and the allocation of humanitarian aid. We work closely with the Internal Displacement Monitoring Centre (IDMC) to develop a global TC impact forecast system that predicts the number of people potentially affected or displaced.

We build the impact forecast system using a python-based, open-source, globally consistent platform called CLIMADA (CLIMate ADAptation). The platform integrates probabilistic hazard, exposure, and vulnerability information to compute the potential impacts from TC events. The first prototype of the forecast system extracts information from ECMWF ensemble TC forecast tracks, a global population layer at ~1km resolution, and vulnerability functions that relate the exposed people to the intensity of TC wind speed. We show case studies of recent TC events to reveal the potential of the displacement forecast system, the uncertainties of the forecast results

The displacement forecast system will provide richer information for decision-makers and help improve warnings. The open-source data and codes of this implementation are also transferable to other users, hazards, and impact types. 
Dynamical dependencies at monthly and interannual time scales in the Climate system: Study of the North Pacific and Atlantic regions
Authors: Vannitsem Stéphane , Liang X. San
Published: March 2022

The directional dependencies of different climate indices are explored using the Liang-Kleeman information flow in order to disentangle the influence of certain regions over the globe on the development of low-frequency variability of others. Seven key indices (the sea-surface temperature in El-Niño 3.4 region, the Atlantic Multidecadal Oscillation, the North Atlantic Oscillation, the North Pacific America pattern, the Arctic Oscillation, the Pacifid Decadal Oscillation, the Tropical North Atlantic index), together with three local time series located in Western Europe (Belgium), are selected. The analysis is performed on time scales from a month to 5 years by using a sliding window as filtering procedure.

A few key new results on the remote influence emerge: (i) The Arctic Oscillation plays a key role at short time (monthly) scales on the dynamics of the North Pacific and North Atlantic; (ii) the North Atlantic Oscillation is playing a global role at long time scales (several years); (iii) the Pacific Decadal Oscillation is indeed slaved to other influences; (iv) the local observables over Western Europe influence the variability on the ocean basins on long time scales. These results further illustrate the power of the Liang-Kleeman information flow in disentangling the dynamical dependencies.
DTVT: a GIS tool for the automatic validation of Physically Based Landslide Models and the identification of the optimal warning criterium
Authors: Segoni Samuele , Pappafico Giulio , Masi Elena Benedetta , Rossi Guglielmo , Tofani Veronica
Published: March 2022

Distributed physically based slope stability models represent the most advanced and scientifically sound method to forecast landslide triggering conditions. However, their operational application in regional warning systems is still hindered by some limitations. Among these, the problem of a robust validation (a task that is time consuming and not standardized) and the difficulty to manage a model output that (especially in the most advanced applications) is constituted by a raster of small pixels expressing the probability of landslide triggering: to activate an operational response an evaluation is usually performed on the overall conditions of larger spatial units and not on a pixel basis.

To overcome these shortcomings, we developed a GIS tool that can be fed with the results of slope stability models (raster maps representing the probability of landslide occurrence) and landslide inventory maps. The tool automatically performs a long series of operations traditionally performed by GIS operators to validate their models: the raw instability maps are reaggregated from pixels to watershed; warning maps are drawn; they are compared with the landslide inventory; a contingency matrix (with true positives, true negatives, false positive, and false negatives) is built; the validation results are drawn in a map. The warning criterium is defined based on two threshold values:  the probability of failure above which a pixel should be considered stable and the percentage of unstable pixels that a watershed needs to consider the hazard level widespread enough to justify the issuing of an alert. The tool was named Double Threshold Validation Tool (DTVT) and after some tests in three different test sites it was verified that: (i) DTVT can be used to carry out a standardized validation procedure in a very shorter time than traditional methods (ii) a reiterated application of the tool (by varying the values of the thresholds) can be used to identify the best warning criterion for each test site (e.g. which double threshold maximizes correct predictions while minimizing missed alarms). It is important to stress that DTVT does not improve the results obtained with the slope stability model; instead, this newly proposed tool that can be used to shift form a triggering model to a warning model, the latter being aimed at identifying when larger spatial units need the activation of operational procedures.
Spatial distribution of urea induced ammonia loss potentials of German cropland soils 
Authors: Ohnemus Thomas , Spott Oliver , Thiel Enrico
Published: March 2022

Urea is currently the most distributed nitrogen fertilizer in the world. Its application to soil is accompanied by loss of ammonia (NH3), which contributes to eutrophication, soil acidification, formation of particulate matter and results in economic losses for farmers. Predicting susceptibility of cropland soils to release NH3 after urea fertilization is therefore of high interest for both society and farmers. 
The present study aimed at (i) developing a process-driven model that estimates susceptibility of cropland soils to release NH3 after urea application based on the most relevant processes occurring within the soil and (ii) to use this model to derive the spatial distribution of urea induced NH3 loss potentials of German cropland soils. Therefore, urea induced NH3 loss potential was studied in the lab for 26 German cropland soils and CEC, initial 
soil pH (pHi), texture and SOC were determined. For a subset of these soils (n = 12) soil buffer capacity and pH dynamic after urea application were also analysed. 
Ammonia loss potential of cropland soils was found to be primarily dependent on CEC, but is superimposed by pHi as well as SOC as they directly affect maximum soil pH during urea hydrolysis. Two process-driven models for estimation of Potential Ammonia Loss (PAL) were developed using either CEC and pHi (PAL 1; r² = 0.82) or CEC, pHi and SOC (PAL 2; r² = 0.88) as input variables. Due to limited availability of suitable spatial SOC data only PAL 1 could be applied for evaluating NH3 loss potentials of German cropland soils. The spatial distribution revealed a strong heterogeneity. Cropland soils susceptible to NH3 release due to urea fertilization are primarily located in northern and eastern Germany. Therefore, future large-scale estimations of NH3 loss due to urea fertilization need to consider regional soil characteristics identified here as most relevant for soil NH3 loss. 
Assessment of soil erosion induced by different tillage practices through multi-temporal geomorphometric analyses
Authors: Cucchiaro Sara , Carretta Laura , Nasta Paolo , Cazorzi Federico , Masin Roberta , Romano Nunzio , Tarolli Paolo
Published: March 2022

One of the main environmental threats to sustainability and crop productivity in the agricultural sector is soil erosion. For the mitigation of this problem in agricultural fields, no-till management is considered a key approach. The measurement of soil erosion is particularly challenging, especially when surficial morphological changes are relatively small. Conventional experiments are commonly time-consuming and labour-intensive in terms of both field surveys and laboratory methods. However, the Structure from Motion (SfM) photogrammetry technique has enhanced the experimental activities by enabling the temporal evolution of soil erosion to be assessed through detailed micro-topography. This work presents a multitemporal quantification of soil erosion, using SfM through Uncrewed Aerial Vehicles (UAV) survey for understanding the evolution of no-till (NT) and conventional tillage (CT) in experimental plots. Considering that plot-scale soil surface (mm grid size) by several orders of magnitude, it was necessary to minimise SfM errors (e.g., co-registration and interpolation) in volumetric estimates to reduce noise as much as possible. Therefore, a methodological workflow was developed to analyse and identify the effectiveness of multi-temporal SfM-derived products, e.g. the conventional Difference of Digital Terrain Models (DoDs) and the less used Differences of Meshes (DoMs), for soil volume computations. To recognise the most suitable estimation method, the research validated the erosion volumetric changes calculated from the SfM outputs with the amount of soil directly collected through conventional runoff and sediment measurements in the field. This study presents a novel approach for using DoMs instead of DoDs to accurately describe the micro-topography changes and sediment dynamics. Another key and innovative aspect of this research, often overlooked in soil erosion studies, was to identify the contributing sediment surface, by delineating the channels potentially routing runoff directly to water collectors. The sediment paths and connected areas inside the plots were identified using a multi-temporal analysis of the sediment connectivity index for achieving the volumetric estimates. The DoM volume estimates showed better results with respect to DoDs and a mild overestimation compared to in-situ measurements. This difference was attributable to other factors (e.g., the soil compaction processes) or variables rather than to photogrammetric or geometric ones. The developed workflow enabled a very detailed quantification of soil erosion dynamics for assessing the mitigation effects of no-till management that can also be extended in the future to different scales with low-costs, based on SfM and UAV technologies.
Soil texture and plant diversity are important abiotic and biotic factors regulating ecosystem multifunctionality across grasslands of northern China
Authors: Wang Congwen , Yu Wanying , Ye Xuehua , Ma Linna , Wang Renzhong , Huang Zhenying , Liu Guofang
Published: March 2022

Ecosystem functions play crucial role in maintaining human well-being. In recent years, more studies have focused on multiple ecosystem functions (ecosystem multifunctionality, EMF) in terrestrial ecosystems. Biotic and abiotic factors mediated by climate change and human activities have important influence on regulating EMF. However, their relative roles are unclear in grassland ecosystems. We conducted a transect survey across grassland ecosystems of northern China to illustrate the relative effects of biotic (including plant diversity, plant traits, and soil microbial diversity) and abiotic (including climatic and soil variables) factors on EMF (including 9 functions, i.e. aboveground biomass, aboveground litter biomass, soil organic carbon, total carbon, total nitrogen, total microbial biomass, bacterial biomass, fungal biomass, and arbuscular mycorrhizal fungi biomass) in 2018. Structural equation modeling indicated that soil sand content and plant diversity had direct effects on EMF, and soil fungal diversity (including main functional guild diversity) indirectly affected EMF through regulating plant diversity. Functional richness of leaf dry matter content had direct effects on EMF, while functional richness of stem density indirectly regulated EMF through affecting functional richness of leaf dry matter content. Variance partitioning analysis showed that biotic and abiotic factors together explained 85% of the variance in EMF, and biotic and abiotic factors explained 77% and 34%, respectively, and combined explained 26%. The random forest algorithm detected that soil sand content and plant diversity were the important abiotic and biotic variables in predicting EMF. These findings have contributed to comprehensive unraveling the effects of biotic and abiotic factors on EMF, highlighting particularly the importance of soil texture and plant diversity in regulating EMF. Land degradation (increased soil sand content) and biodiversity loss induced by on-going climate change and human activities will cause detrimental effects on grassland ecosystem functions. Our findings suggest that integrated management of aboveground and belowground ecosystems contributes to better restoration of degraded grassland ecosystem functions and services.
Climate warming enhances rockfall activity from permafrost environments - but rockfall risk increases primarily due to larger exposure and vulnerability
Authors: Stoffel Markus , Corona Christophe , Ballesteros Juan
Published: March 2022

Rockfall in high mountains is perceived to change more than other mass-wasting processes, presumably as a result of ongoing climate warming and the related, increasing degradation of permafrost. However, the systematic lack of longer-term observational records of rockfall largely hampers any in-depth assessment of how process activity may have been altered by a warming climate and its variability since pre-industrial times. Here, we present evidence that the ongoing climate warming in the Swiss Alps indeed controls rockfall activity from degrading permafrost, and that changes in rockfall frequency correlate significantly with warming air temperature since the 1880s. Using this dataset, we then look into rockfall risk by combining changes in process activity with socio-deconomic developments at the study site. We illustrate how rockfall risk has changed over the past 140 years and how it might change over the course of the 21st century. hile more rockfall and larger volumes occur nowadays as compared to the early 20th century, rockfall risk has increased mostly due to changes in exposure and vulberability and only partly due to changes in process activity itself.
InSAR-Deep learning approach for simulation and prediction of land subsidence in arid regions
Authors: Zhang Yixin , Hashemi Hossein
Published: March 2022

Massive groundwater pumping for agricultural and industrial activities results in significant land subsidence in the arid world. In an acute water crisis, monitoring land subsidence and its key drivers is essential to assist groundwater depletion mitigation strategy. Physical models for aquifer simulation related to land deformation are computationally expensive. The interferometric synthetic aperture radar (InSAR) technique provides precise deformation mapping yet is affected by tropospheric and ionospheric errors. This study explores the capabilities of the deep learning approach coupled with satellite-derived variables in modeling subsidence, spatially and temporally, from 2016 to 2020 and predicting subsidence in the near future by using a recurrent neural network (RNN) in the Shabestar basin, Iran. The basin is part of the Urmia Lake River Basin, embracing 6.4 million people, yet has been primarily desiccated due to the over-usage of water resources in the basin. The deep learning model incorporates InSAR-derived land subsidence and its satellite-based key drivers such as actual evapotranspiration, Normalized Difference Vegetation Index (NDVI), land surface temperature, precipitation to yield the importance of critical drivers to inform groundwater governance. The land deformation in the area varied between -93.2 mm/year to 16 mm/year on average in 2016-2020. Our findings reveal that precipitation, evapotranspiration, and vegetation coverage primarily affected land subsidence; furthermore, the subsidence rate is predicted to increase rapidly. The phenomenon has the same trend with the variation of the Urmia Lake level. This study demonstrates the potential of artificial intelligence incorporating satellite-based ancillary data in land subsidence monitoring and prediction and contributes to future groundwater management.
Monitoring crustal vertical deformation by optical clocks network
Authors: Hoang Anh The , Shen WenBin
Published: March 2022

Optical clocks with increasingly high accuracy have broadened scopes of applications of atomic clocks in scientific community as well as in life. One of the applications of optical clocks is based on the Einstein’s general relativity theory (GRT) to determine geopotential as well as orthometric height. The GRT concludes that a clock at a higher position (with a lower geopotential) will run faster than a clock at a lower position (with a higher geopotential). Therefore, relativistic geodesy has studied and come to the conclusion: using a clock with a stability of 10-18, the height difference will be determined with an accuracy of 1 cm. Currently, optical clocks with a stability of 10-19 have been created in the laboratory, which help scientists investigate prospective applications of the clocks in geodesy. One of the issues that scientists are interested in is monitoring the vertical deformation of the Earth's crust such as slow sliding events, earthquakes, volcanoes, etc. Here, we propose an optical clock network model for monitoring the vertical deformation of the Earth's crust. The optical clocks will be located at the fault layers and connected by fiber optic cables. The advantage of using a clock network over other classical methods (spirit leveling, GNSS) is that it is not only convenient and accurate (centimeter level or higher) but also not restricted by measurement time and geographic conditions. This study is supported by National Natural Science Foundation of China (NSFC) (grant Nos. 42030105, 41721003, 41631072, 41874023, 41804012), and Space Station Project (2020)228.

Key words: GRT, optical clocks network, orthometric height, crustal vertical deformation.
Comparing uncertainty quantification methods based on distributions or statistical moments in thermal design calculations
Authors: Bjorge Merle , Chaudhry Aqeel Afzal , Rühaak Wolfram , Nagel Thomas
Published: March 2022

The presented work investigates aspects of uncertainty quantification in thermal design calculations of deep geological repositories for nuclear waste. The expected evolution of thermal conditions is a key element in the design process of the repository layout. Due to the radioactive decay and the associated emission of heat, temperatures increase in the repository system, potentially affecting processes relevant to the repository negatively. In order to quantify the temperature evolution and assess its effects on the various barriers, such as the host rock, models are set up and thermal calculations are conducted. Often specific distributions are assigned to model parameters, which are not known precisely.

To achieve a robust understanding and design despite this limited knowledge, it is necessary to assess the uncertainties associated with both parameters and models as part of these calculations. However, an uncertainty quantification, which includes calculations based on full distributions is expensive. To compare different uncertainty quantification methods applied to thermal design calculations, a benchmark is created. This benchmark is based on an analytical solution for a 1-D, thermal heat conduction problem using Python. Results of uncertainty quantification calculations based on full distributions, utilizing statistical moments or employing series expansion such as the first-order-second-moment method are compared.

This benchmark can help assess methods of uncertainty quantification in context of thermal design calculations.
Saltmarsh vegetation biomass distribution from drones: a case study
Authors: Silvestri Sonia , Cuenca Portillo Ruth Pamela , Rufo Olinda , Assiri Marco , Avendaño Sofia , Murray A. Brad , Marani Marco
Published: March 2022

Coastal salt marshes are unique and complex geomorphological systems, which must accrete to keep pace with sea-level rise. Even though we know the importance of vegetation and organic matter accumulation in the marsh accretion process, we lack an understanding of spatially-distributed saltmarsh dynamics that include feedbacks with vegetation, especially for sites characterized by high species diversity. Remote sensing retrievals of wetland topography, spatial distribution of species, and vegetation biomass and productivity provide an ideal solution, providing observations over the wide range of scales of interest. Here we present the results obtained using LiDAR and hyperspectral data collected via Unmanned Aerial Vehicles (UAVs) on the San Felice saltmarsh (Venice lagoon, Italy). The selected study site hosts at least twelve species of halophytes grouped into five main associations. UAVs data were collected in September 2021, while a simultaneous field survey provided spatially-distributed georeferenced data and samples on the distribution of vegetation associations, above- and below-ground biomass, vegetation height, bulk density and organic carbon content of the soil. Results suggest that, for different plant associations, LiDAR data can be used to retrieve the aboveground biomass and estimate the belowground biomass (through allometric relations), hence providing a spatially-distributed assessment of the vegetation biomass across the marsh. Combining this information with the organic carbon content obtained by soil analyses, we estimate the combined above- and below-ground carbon stock of the salt marsh. The results obtained using hyperspectral data suggest that vegetation indexes defined on appropriate spectral bands correlate with the LiDAR biomass information and ground truth data. Using these results, observations from UAVs and satellites can be combined to bridge data from the plant to the wetland scale and beyond.