bluuebunny/crossref_metadata_2025 huggingface dataset:
Pluvial flood forecasting in urban data-scarce regions: Influence of rainfall spatio-temporal data (in)accuracy on decision-making
Authors: Young Adele , Bhattacharya Biswa , Zevenbergen Chris
Published: March 2020

Pluvial flooding is on the rise as more cities are challenged by a changing climate and local drivers: increased urbanisation and inadequate sewer system capacity. Flood forecasting and early warning systems have been proposed as a “low regret” measure to reduce flood risk and increase preparedness through forecast-based actions.  However there are multiple sources of uncertainty from meteorological forecast, model parameters and structure and inadequate calibration.  In data-scarce cities, there are additional challenges to produce high-quality rainfall forecast and well-calibrated flood forecast (timing, water levels, extent and impact). As a result, there is a cascading effect on the ability to make and provide good reliable decisions given the uncertainty in the forecast or inaccuracy in the input data.

Ensemble prediction systems (EPS) have been proposed as a means to quantify uncertainty in forecast and compared to deterministic forecast, facilitate a probabilistic framework in decision making. Probabilistic information has been applied to cost loss ratio approaches and Bayesian decision under uncertainty. However, to what extent inherent spatiotemporal inaccuracies of meteorological inputs influence this posterior probability and the resultant decision has not been considered in data scare regions. In this regard, this research focuses on providing understanding on how the influence of the varying degrees of input data, particularly forecast rainfall spatial and temporal distributions will ultimately affect the ability to make an optimal decision; i.e. the recommended decision given the information available at the time of the forecast.

Using a study area in the Alexandria city, Egypt, this research proposes a framework for decision making under uncertainty in an urban data-scarce city using a Weather Research Forecast (WRF) model to simulate downscaled rainfall ensemble forecast and remotely sensed rainfall products to supplement data gaps. Adopting a probabilistic approach, uncertainty in the flood forecast predictions will be represented from an urban rainfall-runoff model driven by ensemble precipitation forecast. The objective of this research is not to make forecast more accurate but rather to highlight the interdependences of the flood forecast and decision-making chain in order to address what decision can be made given the quality of forecast.

Keywords: Pluvial flood forecasting, Ensemble forecast, Decision making, Data-scarce Alexandria, Egypt
The Future of the World's Sandy Beaches Under a Changing Climate
Authors: Vousdoukas Michalis , Ranasinghe Roshanka , Mentaschi Lorenzo , Plomaritis Theocharis , Feyen Luc
Published: March 2020

The world's coastline consists of more than 30% of sandy beaches, many of which are already eroding. Climate change is expected to put more pressure on sandy shorelines, not only because of rising seas, but also from changing weather patterns, affecting the characteristics of marine storms. Here we discuss projections of coastline dynamics along the world's sandy beaches in view of climate change. Using Bruun's rule combined with new global wave projections1 and a dataset on beach slopes2, we find that sea level rise will result in median retreat around -28 m and -35 m under RCP4.5 and RCP8.5, respectively, by the year 2050. the shoreline retreat is projected to climb to around -63 m and -105 m, respectively, by the end of the century. The impact of episodic erosion during storm events will most likely become more severe as sandy beaches will shrink, however, changes in the intensity and characteristics of storms seem to leave an noticeable footprint only in few locations worldwide. Ambient change, extrapolated from historical behaviour3, is expected to contribute signicantly to future sandy beach erosion. However, ambient change can also drive accretion, as is the case along a big part of East Asia. The present findings imply that many sandy beaches worldwide will experience retreat of more than 100 m, i.e. they are very likely to vanish, especially in the absence of accommodating space. The socio-economic implications to tourism, quality of life and the economy can be devastating, especially in small, tourism dependent communities.

References:

Vousdoukas, M. I. et al. Global probabilistic projections of extreme sea levels show intensication of coastal flood hazard. Nature Communications 9, 2360, doi:10.1038/s41467- 018-04692-w (2018).

Athanasiou, P. et al. A global dataset of coastal slopes for coastal recession assessments. Earth System Science Data Discussions, 29, doi:https://doi.org/10.5194/essd-2019-71 (2019).

Mentaschi, L., Vousdoukas, M. I., Pekel, J.-F., Voukouvalas, E. & Feyen, L. Global long-term observations of coastal erosion and accretion. Scientic Reports 8, 12876, doi:10.1038/s41598-018-30904-w (2018).
Ad-hoc estimation of landslide-generated impulse waves – from the lab to the field
Authors: Evers Frederic M. , Boes Robert M.
Published: March 2020

Landslide tsunamis generated by extremely rapid subaerial mass wasting are also referred to as impulse waves and may occur both along coastal areas and in inland waters including engineered reservoirs. The hydraulic process chain comprising wave generation, propagation, and run-up needs to be comprehensively assessed to predict whether these waves represent a threat to the shore and adjacent infrastructure. Hazard assessment studies based on site-specific hydraulic laboratory models and numerical simulations may generally yield quite accurate predictions of the expected wave and run-up heights. While the former involves the availability of specialized lab infrastructure and instrumentation, the latter requires in-depth knowledge of suitable numerical methods as well as experience in their application to scenarios at prototype-scale. Therefore, both approaches are time-consuming, involve high costs, and pose substantial entry thresholds for practitioners. Especially in emergency situations, when first-order estimations need to be quickly at hand, the ad-hoc applicability of these approaches may therefore be limited.

Motivated by an imminent landslide hazard at Carmena reservoir, Switzerland, in 2002, the national supervisory authority for dam safety, the Swiss Federal Office of Energy, commissioned the development of a fast and readily applicable computational procedure. As a result, the first edition of the so-called ‘impulse wave manual’ was published in 2009 and provides an extensive literature review of generally applicable equations derived from lab experiments. It combines selected equations into a coherent computational framework covering all stages of an impulse wave event’s hydraulic process chain. Based on the estimation of e.g. wave and run-up heights, this manual allows to rapidly implement mitigation measures including reservoir drawdown or precautionary evacuation. In addition to an improved emergency planning, the manual proved to be an inexpensive tool to obtain an estimation of an impulse wave event’s magnitude during the preliminary design phase of new reservoirs. Back in 2009, the manual’s literature analysis already identified specific research gaps, leading to the initiation of further experimental investigations. Following these research efforts over the past ten years, a second edition of the manual was published in 2019 featuring an updated computational procedure.

This contribution provides a brief introduction to the updated computational procedure and applies it to prototype events with available survey data, e.g. Chehalis Lake, Canada, in 2007. The comparison to prototype data allows to highlight the procedure’s capabilities as well as its limitations for future ad-hoc estimations of landslide-generated impulse waves.
Cross-isentropic mixing: A DEEPWAVE case study
Authors: Lachnitt Hans-Christoph , Hoor Peter , Kunkel Daniel , Hofmann Stafan , Bramberger Martina , Rapp Markus , Dörnbrack Andreas , Schlager Hans
Published: March 2020

The tropopause acts as a transport barrier between the upper troposphere and the lower stratosphere. Non-conservative (i.e. PV changing) processes are required to overcome this barrier. Orographically generated gravity waves (i.e. mountain waves) can potentially lead to cross-isentropic fluxes of trace gases via the generation of turbulence. Thus they may alter the isentropic gradient of these trace species across the tropopause.
The specific goal of this study is to identify cross-isentropic mixing processes at the tropopause based on the distribution of trace gases (i.e. tracer-tracer correlations). Based on airborne in-situ trace gas measurements of CO and N2O during the DEEPWAVE (Deep Propagating Gravity Wave Experiment) campaign in July 2014 we identified mixing regions above the Southern Alps during periods of gravity wave activity. These in-situ data show that the composition of the air above the Southern Alps change from the upstream to the leeward side of the mountains indicating cross isentropic mixing of trace gases in the region of gravity wave activity.
We complement our analysis of the measurement data with high resolution operational analysis data from the ECMWF (European Centre for Medium-Range Weather Forecasts). Furthermore, using potential vorticity and stability parameters.
Using 3D wind fields, data form Graphical Turbulence Guidance (GTG) system and in-situ measurements of the vertical wind we identify occurrence of turbulence in the region of mixing events. Using wavelet analysis, we could identify the spatial and temporal scales of local trace gas fluxes. We also give estimates of cross-isentropic flux, i.e. we want to quantify the mixing in terms of exchange.
Defining a retracking manifold within a radargram stack to improve satellite altimetric water level over coastal seas: A feasibility study
Authors: Sneeuw Nico , Elmi Omid , Eitel Maximilian , Tourian Mohammad
Published: March 2020

Single-waveform retracking for satellite altimetry applications over coastal zones has reached its limits, obtaining decimeter-level accuracy. The existing retracking methods find a retracker offset in a waveform by analyzing the variation in backscattered power along the bin coordinate. This makes the retracking procedure strongly dependent on noise in backscattered power. Moreover, the success of such methods is only guaranteed for certain waveform types requiring cumbersome pre-processing steps including waveform classification. 

With the launch of the operational Sentinel-3 series of the European Copernicus programme, the algorithms to obtain highly precise water level estimates over inland waters and coastal seas need to become more robust, efficient and fit for automated use. Therefore, the main objective of this study is to demonstrate the potential of developing a next-level retracking algorithm and, consequently, improve altimetric water level determination over coastal regions. To this end, neighboring waveforms are collected into a (single-pass) radargram and, then, such radargrams are stacked over time. These so-called (multi-pass) radargram stacks contain, unlike single waveforms, the full information on spatio-temporal variation of backscattered power over water surfaces.

The radargram stack eases the recognition of patterns like retracking gate, shoreline, tides, etc. Instead of a retracking gate as a point in the 1D waveform, in a 3D radargram stack a surface referred to as retracking manifold is to be determined.

The potential of our new approach will be demonstrated using Sentinel 3B data, pass number 655, over the Cuxhaven tide gauge station at the Wadden Sea.

The idea of waveform retracking by analyzing its spatio-temporal behavior in a 3D data structure opens new pathways for achieving robust and more accurate water level estimates from operational missions, e.g. Sentinel 3, and from future missions, e.g. SWOT, over inland waters and coastal seas.
Looking for changes in the upper crust associated with large magnitude earthquakes in central Italia using seismic noise autocorrelations
Authors: Stehly Laurent , Delouche Estelle , Voisin Christophe , Poli Piero
Published: March 2020

In this work, we use seismic noise autocorrelations to monitor the temporal evolution of the upper crust in Central Italia in order to look for changes that could have occured before the 2009 Mw6.3 l'Aquila and the 2016 Mw 6.2 Amatrice earthquake.

To that end, we use the Coherence of Correlated Waveforms [CCW] method, that consists in measuring changes in the waveform of autocorrelations with a temporal resolution of 5 days.

Our measurements of the CCW show that the L'Aquila Earthquake  is preceded by a 150-days oscillation whose amplitude and frequency progressively increases until the rupture. Analysing 17 years of data, we found that this signal occured only before the L'Aquila and the Amatrice earhtquake.  This suggests the existence of a unique nucleation process.

Finally, we compare the results obtained using the CCW method with the temporal evolution of the seismic waves velocity (dv/v) obtained by analysing the coda of seismic noise autocorrelations.
Obliquity favours propagation pulses during continental break-up
Authors: Jourdon Anthony , Le Pourhiet Laetitia , Mouthereau Frédéric , May Dave A.
Published: March 2020

V-shaped propagators are ubiquist and the seafloor age map is often sufficient to unravel the first order features of the timing of continental break-up at regional or more global scale. Some propagators show  pulses in the rate of continental break-up propagation highlighted by the geometry of magnetic anomalies. These pulses, which were first introduced by Courtillot (1982) in the Gulf of Aden, represent a major element of plate tectonics. Despite the well documented geological record of these changes of rate, and their implications for plate kinematic reconstructions or the thermal regime of oblique margins, the dynamics of ridge and rift propagation at long/geodynamic timescale remains poorly studied nor understood. To date, despite the large progress made in understanding lithospheric dynamics and continental break-up, no lithospheric scale dynamic models has been able to produce self consistently pulse of ridgepropagation followed by a phase of stagnation. One obvious reason for this lack of dynamic ground stands from the fact that this problem mandates 3D thermo-mechanically coupled simulation approach that is just starting to emerge. In this work we chose to adopt a numerical modelling set-up after Le Pourhiet et al. (2018) to produce V-shaped propagators. Simulations investigate the influence of both kinematic and rheology of the lithosphere on the propagation trend and rate. The tectonic evolution of these margins shows 3 different modes of continental break-up propagation and a major change of deformation regime between phases of propagations and phases of stagnation.
Ocean sensitivity to bulk formulae parameterization: a NEMO-ORCA025 model study
Authors: Bonino Giulia , Iovino Doroteaciro , Masina Simona
Published: March 2020

Surface wind stress and heat fluxes (e.g. sensible and latent) are the major driving forces that modify the ocean dynamics and thermodynamics. Therefore, in a modelling framework, realistic momentum and heat fluxes are essential for simulating the global ocean. In the NEMO ocean general circulation model, these air-sea fluxes, which are difficult to be measured directly, are derived using bulk formulas. A large set of bulk formulas exist and this work tries to quantify the ocean response to the different bulk formulations implemented in the newest version of NEMO global ocean model (version 4.0.1). A set of experiments based on the CMCC ORCA025 configuration (1/4° of horizontal resolution) is run and examined. The numerical experiments differ for the bulk formula used  to estimate air-sea fluxes (ECMWF, NCAR, COARE and COARE3.5) and they consist of 2-years simulations forced by the recent JRA55-do-v1.3 (∼ 55km resolution). Preliminary results on the ocean sensitivity in terms of sea surface temperature, sea surface salinity and ocean currents, also in comparison with available observations, will be shown.
The effects of glacial-interglacial loading on the 3D pore pressure evolution in sedimentary basins: case study from the Central European Basin System
Authors: Frick Maximilian , Cacace Mauro , Klemann Volker , Tarasov Lev , Scheck-Wenderoth Magdalena
Published: March 2020

This study deals with modelling the distribution of the subsurface pore pressure in space and the respective evolution in time in response to variations in hydromechanical surface loading during a full glacial-interglacial cycle. The aim here is to better understand (i) the feedback mechanisms between the atmosphere and solid earth components, and (ii) to which degree this coupling might be relevant for subsurface hydromechanical modelling studies. The study area is the Central European Basin System (CEBS) in northern and Central Europe and state-of-the-art ice reconstructions for the last glacial-interglacial period have been used to model the surface hydromechanical loading conditions. Thereby, investigations on how transient ice coverage influences the pore pressure distribution with depth and over time within a heterogeneous sedimentary cover were carried out. The subsurface beneath the CEBS consists of more than 10 km thick sediments, which have been heavily restructured by salt movements during the whole Mesozoic evolution. Our 3D geological model resolves all major sedimentary and crustal domains, and we relied on the GLAC1-D (1.0 degree longitude by 0.5 degree latitude spatial resolution) ice sheet chronology. Starting from ice-free initial conditions, transient simulation runs are performed (hydraulic vs hydromechanical) which cover the entire last glacial cycle, i.e. encompassing 122ka BP till present day conditions. Results are discussed in terms of pore pressure evolution over time and space. The focus will lie on quantifying subsurface conditions favourable to the establishment and maintenance of overpressure evolution and the related equilibration time within the sedimentary pile. We also investigate how these transient conditions influence the subsurface hydrodynamics, showcasing representative time steps during the evolution of the system. We will finally attempt to quantify the memory effect of such loading conditions on the basin-wide hydromechanics, a feedback mechanism that has been neglected so far in 3D subsurface studies.
What can we learn from observations of small dust grains in the interstellar space?
Authors: Czechowski Andrzej , Mann Ingrid
Published: March 2020

A fraction of the dust that is contained in the local interstellar medium around the Sun can enter the heliosphere and be observed in the solar system. The exception is the small size component of the interstellar dust spectrum, which can be directly observed only beyond the heliopause. 

The charge-to-mass ratio of the interstellar dust grains of nanometer size can be high enough to make their dynamics highly sensitive to the magnetic field and plasma flow. Based on numerical simulations and analytical models, we show how the small interstellar grains entering the transition region between the undisturbed interstellar medium and the outer boundary of the heliosphere respond to plasma and magnetic field structures (in particular the heliospheric bow shock and the heliopause) expected in this region. We also point out which dust impact measurements from a spacecraft in the interstellar space would be most desirable for imaging the structure of the transition region by means of interstellar dust.
Spatiotemporal model for benchmarking causal discovery algorithms
Authors: Tibau Xavier-Andoni , Reimers Christian , Eyring Veronika , Denzler Joachim , Reichstein Markus , Runge Jakob
Published: March 2020

We propose a spatiotemporal model system to evaluate methods of causal discovery. The use of causal discovery to improve our understanding of the spatiotemporal complex system Earth has become widespread in recent years (Runge et al., Nature Comm. 2019). A widespread application example are the complex teleconnections among major climate modes of variability. 

The challenges in estimating such causal teleconnection networks are given by (1) the requirement to reconstruct the climate modes from gridded climate fields (dimensionality reduction) and (2) by general challenges for causal discovery, for instance, high dimensionality and nonlinearity. Both challenges are currently being tackled independently. Both dimensionality reduction methods and causal discovery have made strong progress in recent years, but the interaction between the two has not yet been much tackled so far. Thanks to projects like CMIP a vast amount of climate data is available. In climate models climate modes of variability emerge as macroscale features and it is challenging to objectively benchmark both dimension reduction and causal discovery methods since there is no ground truth for such emergent properties. 

We propose a spatiotemporal model system that encodes causal relationships among well-defined modes of variability. The model can be thought of as an extension of vector-autoregressive models well-known in time series analysis. This model provides a framework for experimenting with causal discovery in large spatiotemporal models. For example, researchers can analyze how the performance of an algorithm is affected under different methods of dimensionality reduction and algorithms for causal discovery. Also challenging features such as non-stationarity and regime-dependence can be modelled and evaluated. Such a model will help the scientific community to improve methods of causal discovery for climate science.

Runge, J., S. Bathiany, E. Bollt, G. Camps-Valls, D. Coumou, E. Deyle, C. Glymour, M. Kretschmer, M. D. Mahecha, J. Muñoz-Marı́, E. H. van Nes, J. Peters, R. Quax, M. Reichstein, M. Scheffer, B. Schölkopf, P. Spirtes, G. Sugihara, J. Sun, K. Zhang, and J. Zscheischler (2019). Inferring causation from time series in earth system sciences. Nature Communications 10 (1), 2553.
Global evaluation of the nutrient enabled version of land surface model ORCHIDEE-CNP (v1.2)
Authors: Sun Yan , S Goll Daniel , Chang Jinfeng , Ciais Philippe , Guenet Betrand , Helfenstein Julian , Huang YuanYuan , Lauerwald Ronny , Maignan Fabienne , Naipal Victoria , Wang Yilong , Yang Hui , Zhang Haicheng
Published: March 2020

Future land carbon (C) uptake under climate changes and rising atmospheric CO2 is influenced by nitrogen (N) and phosphorus (P) constraints. A few existing land surface models (LSMs) account for both N and P dynamics, but lack comprehensive evaluation. This will lead to large uncertainty in estimating the P effect on terrestrial C cycles. With the increasing number of measurements and data-driven products for N- and P- related variables, comprehensive model evaluations on large scale is becoming feasible.

In this study, we evaluated the performance of ORCHIDEE-CNP (v1.2) which explicitly simulates N and P cycles in plant and soil, in four aspects: 1) terrestrial C fluxes, 2) N and P fluxes and budget, 3) leaf and soil stoichiometry and 4) resource use efficiencies. We found that ORCHIDEE-CNP improves the simulation of the magnitude of gross primary productivity (GPP) due to more realistic strength of the CO2 fertilization effect of GPP than the without-nutrient-version ORCHIDEE. However, ORCHIDEE-CNP cannot capture the positive and increasing C sink in North Hemisphere over past decades, which is mainly due to that a large fraction of N and P ‘locked’ in soil organic matter cannot be re-allocated into vegetation and leads to a strong N and P limitation on plant growth. ORCHIDEE-CNP generally simulates comparable global total N and P fluxes (e.g. N biofixation, P weathering, N and P uptake etc.) for both natural and agricultural biomes. Overall, ORCHIDEE-CNP doesn’t performance worse in C fluxes than ORCHIDEE, and gives reasonable N and P cycles, which is acceptable in simulating the coupling relationships between C, N and P cycles can be used to explore the nutrient limitations on land C sink from present to the future. 
Continuous seismic reflection image of the Lithosphere-Asthenosphere Boundary (LAB) from 2-75 Ma on the African plate in the Equatorial Atlantic Ocean
Authors: Audhkhasi Pranav , Singh Satish
Published: March 2020

Lithosphere-asthenosphere boundary (LAB) has generally been estimated using surface tomography (Priestley and McKenzie, 2006; Auer et al., 2014), surface waves anisotropy (Plomerova et al, 2002; Burgos et al., 2014) and receiver function methods (Kumar and Kawakatsu, 2011; Rychert et al., 2012), indicating a change in the S-wave velocity. Recently, some limited studies have shown that LAB could be imaged using seismic reflection imaging method (Stern et al., 2015; Mehouachi and Singh, 2018), requiring a sharp P-wave velocity contrast. Here, we present a continuous seismic reflection image of the LAB from 2-to-75-Ma in the Equatorial Atlantic Ocean over the African plate along a 1400 km long profile using a 12 km long offset multi-channel multi-component (hydrophone and three component acceleration) seismic data. Optimal de-ghosting by summation of pressure (P) and vertical acceleration (Az) components has improved the bandwidth of the data by removing the notches (Vassallo et al., 2013). Further advanced processing consisted of noise removal in shot and receiver domains followed by low frequency boost-up. Trace interpolation followed by wavenumber filtering was performed in the common-midpoint domain to achieve a higher signal-to-noise ratio and flat events enhancement. Post-stack processing mainly consisted of frequency-space deconvolution, dip filtering and data-adaptive edge-preserving modified Kuwahara filter. We find two prominent reflections: The upper varies from ~12 km (3.5 s) two-way time (TWT) below the seafloor at 2 Myr to ~78 km (20 s) TWT below the seafloor at 75 Myr. For 27-to-47-Myr old lithosphere, we image a second almost flat continuous reflection from 21 s to 22 s TWT below the seafloor (~82 km). This event is not prominent for 49-to-75-Myr old lithosphere, probably due to the influence of the mantle thermal anomalies from St.Helena/Cameroon. There is also evidence of some other reflections between these two reflections, which also dip towards older age. The crust-mantle boundary or the Moho is also fairly imaged throughout the profile with crustal thickness ranging between 1.4 – 2.7 s TWT. We interpret the uppermost reflection as the base of lithosphere, the top of the LAB, and the lower reflection as the base of the LAB, while the reflections between these as sheared melt sheets. Our results provide the very first image of the whole LAB system continuously as it deepens and thins away from the ridge axis. In this presentation, we will discuss different implications of these images and provide a comprehensive model of the oceanic LAB over normal oceanic lithosphere.
A bottom up approach to quantify foliar uptake of gaseous elemental mercury by European forests during the 2018 growing season
Authors: Wohlgemuth Lena , Osterwalder Stefan , Hoch Günter , Alewell Christine , Jiskra Martin
Published: March 2020

The deposition of gaseous elemental mercury, Hg(0), from the atmosphere to terrestrial surfaces remains poorly understood mainly due to difficulties in measuring net Hg(0) fluxes on the ecosystem scale. However, there is emerging evidence that vegetation uptake of atmospheric Hg(0) represents a major deposition pathway to terrestrial surfaces. We will present a novel bottom up approach to calculate Hg(0) deposition fluxes to aboveground foliage by combining foliar Hg accumulation rates on the basis of leaf area with species-specific leaf area indices. We analyzed Hg content in 583 foliage samples from major tree species at 10 European forested research sites along a latitudinal gradient from Switzerland to Northern Finland over the course of the 2018 growing season. Foliar Hg concentrations increased over time in all tree species at all sites. We found that foliar Hg accumulation rates normalized to leaf area increased with crown height and decreased with the age of multi-year old needles. We did not detect a clear latitudinal gradient in foliar Hg accumulation rates.

On an ecosystem scale we developed a simple bottom up approach for foliar Hg(0) uptake considering the systematic variations in crown height, needle age and tree species. We calculated species-specific average foliar Hg(0) dry deposition rates for the 2018 growing season of 22 ± 4 µg Hg m-2 for beech, 16 ± 8 µg Hg m-2 for oak, 3 ± 0.4 µg Hg m-2 for birch, 18 ± 10 µg Hg m-2 for spruce and 8 ± 4 µg Hg m-2 for pine. For comparison, the average Hg wet deposition flux measured at 4 of our 10 research sites during the same time period was 2.5 ± 0.2 µg Hg m-2.

Scaling up site-specific deposition rates to the forested area of Europe (EU28) resulted in a total aboveground Hg(0) deposition to foliage of approximately 20 Mg during the 2018 growing season. Our results confirm that vegetation uptake of atmospheric Hg(0) represents a major deposition pathway to terrestrial surfaces. The bottom up approach we used is a promising method to quantify Hg(0) deposition fluxes based on easy-to-do Hg concentration measurements in foliage.
Effects of microplastic particles on vertical water flow in soil columns
Authors: Laermanns Hannes , Müller Katharina Luise , Löder Martin , Ehl Ramona , Möller Julia , Bogner Christina
Published: March 2020

Since the introduction of synthetic polymers into the global material cycle, increasing amounts of microplastics have been deposited in soils. In contrast to their impact on marine environments, only little is known about the influence of these long-term contaminants on terrestrial ecosystems in general and on physical and chemical soil properties in particular. First studies highlight that microplastic particles might attach to and clog especially smaller than 30 µm pores which are crucial for the hydraulic conductivity and therefore the water flow of soils (Zhang et al., 2019, doi:10.1016/j.scitotenv.2019.03.149).In our study, we analyse the effects of microplastic particles on vertical water flow in soil columns. In infiltration-drainage experiments, we contrast water flow in soil columns with and without microplastic particles. A bromide tracer is used to compare the arrival times of the wetting fronts and the tracer fronts, and water flow is characterized using the viscous flow approach (e.g. Bogner & Germann, 2019, doi:10.2136/vzj2018.09.0168). We show first results on how microplastic particles may affect the vertical water flow in soils and the breakthrough of the tracer.
Impact of salt marsh and seagrass beds on the sediemnt buget and resilience of coatsal areas
Authors: Leonardi Nicoletta , Donatelli Carmine , Zhang Xiahoe , Ganju Neil , Fagherazzi Sergio
Published: March 2020

Salt marshes and seagrass beds can offer sustainable coastal protection solutions and several ecosystem co-benefits. The delicate balance regulating salt marsh stability depends on several factors including the sediment added to and removed from the coastal system (Donatelli et al., 2018, 2019; Zhang et al., 2019).  Despite the importance of these sediment budget dynamics, many feedbacks between salt marsh presence and sediment availability are still unclear. Here, we use numerical models to simulate changes in depositional patterns of six estuaries along the U.S. coastline to investigate how salt marsh and seagrass beds removal and restoration can alter the sediment budget and resilience of coastal environments. 

Donatelli, C., Ganju, N.K., Kalra, T.S., Fagherazzi, S. and Leonardi, N., 2019. Changes in hydrodynamics and wave energy as a result of seagrass decline along the shoreline of a microtidal back-barrier estuary. Advances in Water Resources, 128, pp.183-192.

Zhang, X., Leonardi, N., Donatelli, C. and Fagherazzi, S., 2019. Fate of cohesive sediments in a marsh-dominated estuary. Advances in water resources, 125, pp.32-40.

Donatelli, C., Ganju, N.K., Fagherazzi, S. and Leonardi, N., 2018. Seagrass impact on sediment exchange between tidal flats and salt marsh, and the sediment budget of shallow bays. Geophysical Research Letters, 45(10), pp.4933-4943.
Drivers of methane variability in Arctic ponds
Authors: Rehder Zoé , Zaplavnova Anna , Kutzbach Lars
Published: March 2020

Arctic ponds are significant sources of methane, but their overall contribution to pan-Arctic methane emissions is still uncertain. Ponds come in different sizes and shapes, which are associated with different stages of permafrost degradation. Methane concentrations and fluxes show large spatiotemporal variability. To better understand this variability, as a first step towards upscaling pond methane emissions, we studied 41 ponds in the Lena River Delta, northeast Siberia. We collected water samples at different locations and depths in each pond and determined methane concentrations using gas chromatography. Additionally, we collected information on the geomorphology, vegetation cover as well as on key physical and chemical properties of the ponds and combined them with meteorological data.

The ponds are divided into three geomorphological types with distinct differences in methane concentrations: water-filled degraded polygon centers, water-filled interpolygonal troughs and larger collapsed and merged polygons. These ponds exhibit mean surface methane concentrations (with standard deviation) of 1.2 ± 1.3 μmol L-1, 4.3 ± 4.9 μmol L-1 and 0.9 ± 0.7 μmol L-1 respectively, while mean bottom methane concentrations amount to 102.6 ± 145.4 μmol L-1, 263.3 ± 275.6 μmol L-1 and 17.0 ± 34.1 μmol L-1. Using principle components and multiple linear regressions, we show that a large portion of spatial variability can be explained by the ponds’ shape and vegetation. Merged ponds have the least relative vegetation cover, and they also tend to be better mixed, both of which explains the lowest methane concentrations and the lowest variability in these ponds. Vegetation covers larger fractions in polygon centers and troughs, leading to a larger methane variability. Finally, troughs, as they are underlain by ice wedges, exhibit more pronounced stratification and the highest methane concentrations. More results will be presented at the conference.
Water quality policies in the Brantas River Basin, Indonesia
Authors: Ertsen Maurits
Published: March 2020

Over the past 20 years, river water quality in Indonesia has deteriorated enormously. Water quality deterioration continues to increase socio-economic inequality, as it are the most poor communities who live on and along the river. Women are comparatively highly impacted by failing water resources management, but their involvement in decision making processes is limited. As such, the uneven water quality related disease burden in Brantas River Basin widens the socio-economic gap between societal groups. In the Brantas region, cooperation and intention between stakeholders to tackle these issues is growing, but is fragile as well due to overlapping institutional mandates, poor status of water quality monitoring networks, and limited commitment of industries to treat their waste water streams. Currently, an Indonesian-Dutch consortium develops a project which is built on the premise that water problems of our world do not necessarily have to be only a cause of tension, but can also be a catalyst for cooperation. Cooperation is a process that needs active input from all concerned. As such, this project seeks to support a twinned learning process in which science is used to build a trusted information system for policy and decision making in Brantas river basin management. The project focuses on the close links between research processes of data gathering and monitoring and its relevance for societal and institutional actors within river basin management organizations. This twinning between policies and science aims to facilitate learning processes of basin authorities, societal stakeholders, companies and knowledge institutions, as they can profit from each other’s achievements, knowledge and experiences. One of the important issues for this new cooperative partnership is how to develop procedures and routines to monitor water quality in the Brantas river. Participatory data monitoring is among the prime requirements for sustainable river management. An additional dimension of the already challenging issue of data gathering in river management is how to deal with transdisciplinary issues in monitoring, measurements and measures, including research procedures and institutional setup.
Glacier evolution modelling with deep learning: challenges and opportunities
Authors: Bolibar Jordi , Rabatel Antoine , Gouttevin Isabelle , Galiez Clovis , Condom Thomas , Sauquet Eric
Published: March 2020

Glacier surface mass balance (SMB) and glacier evolution modelling have traditionally been tackled with physical/empirical methods, and despite some statistical studies very few efforts have been made towards machine learning approaches. With the end of this past decade, we have witnessed an impressive increase in the available amount of data, mostly coming from remote sensing products and reanalyses, as well as an extensive list of open-source tools and libraries for data science. Here we introduce a first effort to use deep learning (i.e. a deep artificial neural network) to simulate glacier-wide surface mass balance at a regional scale, based on direct and remote sensing SMB data, climate reanalysis and multitemporal glacier inventories. Coupled with a parameterized glacier-specific ice dynamics function, this allows us to simulate the evolution of glaciers for a whole region. This has been developed as the ALpine Parameterized Glacier Model (ALPGM), an open-source Python glacier evolution model. To illustrate this data science approach, we present the results of a glacier-wide surface mass balance reconstruction of all the glaciers in the French Alps from 1967-2015. These results were analysed and compared with all the available observations in the region as well as another physical/empirical SMB reconstruction study. We observe some interesting differences between the two SMB reconstructions, which further highlight the interest of using alternative methods in glacier modelling. Due to (relatively) recent advances in data availability and open tools (e.g. Tensorflow, Keras, Pangeo) this research field is ripe for progress, with many interesting challenges and opportunities lying ahead. To conclude, some perspectives on data science glacier modelling are discussed, based on the limitations of our current approach and on upcoming tools and methods, such as convolutional and physics-informed neural networks. 
Assessment of the interannual evolution of water resources with an ensemble of fully coupled terrestrial model simulations
Authors: Hartick Carl , Furusho-Percot Carina , Goergen Klaus , Kollet Stefan
Published: March 2020

In 2018, a severe drought occurred in Central and Northern Europe and water security concerns rose in regions where previously water was considered an abundant resource. Followed by another extremely dry year 2019, the meteorological drought developed into a hydrological drought and estimates on the probable evolution of water stores at an interannual time scale over Europe seem required that have the potential to provide informed options for adaptation. Utilizing the Terrestrial Systems Modeling Platform (TSMP) regional Earth system model over the 12km resolution pan-European CORDEX model domain, a probabilistic assessment methodology is proposed based on fully coupled groundwater-to-atmosphere simulations, which provide subsurface water resources anomalies for a water year defined from September to August. For the assessment, the TSMP ensemble is initialized with the surface and subsurface states at the end of a previous water year that is part of a spun up climatology run (here: 1989 to 2019). In an ensuing step, an ensemble of forward simulations is performed, driven by past ERA-Interim reanalysis meteorological boundary conditions until the end of August of the following year. The memory effect of groundwater, which is well-captured in TSMP, in combination with the different, plausible atmospheric states and evolution of the atmospheric forcing from the reanalysis, allows for a probabilistic assessment of the development of water resources in the upcoming year. The novelty is the use of the past meteorological conditions in a fully coupled model to account for the uncertainty of unknown weather conditions at the interannual forecasting time scale. We show that the method provides good results in a hindcast approach of 2018/19 and present the results of the upcoming water year 2019/20.
Early warning and risk perception of landslide hazard chain in the Wu Gorge, Yangtze River, China
Authors: Liang Xin , Yin Kunlong , Chen Lixia , Du Juan , Xiao Ting , Zhang Yiyue
Published: March 2020

More than 2500 landslides in the Three Gorge Reservoir (TGR) region are affected by reservoir impoundment and seasonal water fluctuation since 2003, accounting for huge property loss and remaining a great threat to the local residents. In order to detect these landslides with potential threat, a series of early warning systems (EWS) at different scales of analysis were installed in this area, and have gained significant consequences in issuing alarm information. However, some catastrophic landslide, e.g., Hongyangzi landslide and Gongjiafang landslide, indicating that landslides in the TGR area should be considered as disaster chains, as the landslide-induced waves may have more serious influences. Therefore, it is necessary to carry out a prospective risk perception about landslide-induced wave based on the existing early warning. This paper aims to assess the risk of impulsive wave in the TGR with a quantitative method, and a new perspective about risk mitigation is proposed with the purpose of controlling the size of the surge. The risk assessment method mentioned is applied to Ganjingzi landslide, a typical colluvial landslide in the Wu Gorge, activating by reservoir impoundment and fluctuation. The EWS installed indicates that the landslide undergoes a retrogressive evolution, and local failure of the strong-deformation area will decrease the stability of the landslide and induce the movement. By preforming Tsunami Squares method, potential waves generate by Ganjingzi landslide with different failure situations are simulated. The quantitative risk analysis is carried out with the consideration of both sailing and moored vessels in the Yangtze River. The result reveals that impulse wave induced by the strong-deformation area causes the maximum economic loss, of about 0.59 million USD. Moreover, a new risk mitigation measure is designed to lower the speed of landslide intrusion into the reservoir. Compared with the traditional control measure that only use anti-sliding piles (about 21.4 million USD), reducing the load around the trailing edge of landslide and settling anti-sliding piles in the strong-deformation area (about 3.5 million USD) is more economical and effective. Overall, the proposed method for risk assessment and mitigation may provide a basis for the risk management of geological hazards and early warning in the other reservoir areas with similar geological conditions and environmental backgrounds.
Global patterns of plant diversity and their evolutionary drivers
Authors: Tietje Melanie , Baker William J. , Govaerts Rafaël , Smith Stephen A. , Sun Miao , Eiserhardt Wolf L.
Published: March 2020

Spatial patterns of plant diversity follow the well-known global latitudinal biodiversity gradient, however there is little consensus about the underlying causes for this pattern. Here we present a spatial analysis of a complete checklist of the world’s seed plants, integrated with a comprehensive plant Tree of Life. This combination allows insights into the evolutionary drivers of plant species richness patterns, specifically current plant biodiversity patterns, and the diversification processes that shaped them. Our study provides a comprehensive global species richness map and relates the observed species richness pattern to speciation rates derived from phylogeny, and with environmental variables, which are hypothesized to impact speciation rates. Initial results show that tropical rain forest regions, although being areas that contain among the highest numbers of species, are regions with comparatively low speciation rates, contradicting the widespread notion that rainforests are “cradles” of biodiversity. This finding seems further supported by contrasting association of environmental variables, like precipitation and temperature, with speciation rates and species richness.
Classification of Seismic Events with Deep Learning Strategies: Insights from the Moosfluh Landslide
Authors: Dazzi Nadir , Manconi Andrea , Prakash Nikhil , Bickel Valentin
Published: March 2020

Rockfalls affect steep slopes in several geographic regions. Different systems from remote to in-situ instruments are used for their detection and study. In this scenario, seismic signals produced by the detachment, bouncing, and rolling of rockfalls are being increasingly used for the detection and classification of such events. This is typically done by using different manual, semi-automatic and/or automatic signal processing strategies. In this work, we applied a new Deep Learning (DL) algorithm in order to test the performance on the automatic classification of seismic signals. We applied the method to seismic data acquired by a low-cost Raspberry Shake 1D seismometer (sampling rate 50Hz) in order to discriminate rockfall from not-rockfall events occurred at the Moosfluh active slope region in Wallis (CH). Here we present the methodology and show the results obtained on a continuous record of more than 2-years of seismic data. The performance accuracy of the DL approach reached values larger than 90%. Our results show that the application of DL strategies in this context can be very useful and save time on seismic data classification.
One Million Years of Human-Landscape Interaction in the Ethiopian and Kenyan Rift-System
Authors: Junginger Annett , Kuebler Simon
Published: March 2020

Landscapes form the basis for the development of human habitats. Studying human-landscape interactions thus requires an understanding of the character and evolution of landscapes on different temporal and spatial scales. In Africa, key anthropological sites are often associated with the tectonically active sectors of the East African Rift. But the landscapes inhabited by our ancestors have undergone massive changes over time, changes driven by climatic variability as well as long-term geomorphological and tectonic processes. River courses have changed, lakes expanded and then disappeared, and volcanic and tectonic activity formed steep fault scarps and barriers. Here we present a review of archaeological, paleo-climatological, paleo-limnological, tectonic and soil nutrients data sets of the southern Ethiopian and Kenyan Rift System in Eastern Africa of the past 1 Million years. Results suggest that tectonic processes and climatic change created a unique suite of landscape features potentially advantageous for human inhabitance. The combined analysis thus allows the quantification of styles and rates of surface modification, which in turn can be used for reconstructing ancient landscapes.