With temperatures rising in Arctic regions at double the global average, decomposition rates and subsequent greenhouse gas release into the atmosphere are expected to rise, potentially shifting these regions from carbon sinks to carbon sources. General circulation models predict the relationship between respiration and temperature using exponential functions, showing a temperature-independent rate of increase to decomposition rates with temperature. However, enzymes catalyzing carbon depolymerization reactions have demonstrated departures from this predicted increase between 10 and 15 °C. Organic tundra soils were incubated across this range (4 to 20 °C, 4 °C increments) and harvested consecutively after carbon losses equivalent to those after 2, 4, 8, and 12 days at 20 °C. During each harvest, β-glucosidase (BG) and β-xylosidase (BX) activities were measured at both the incubation temperature and at 20 °C to determine temperature limitations to enzyme activity and production. While enzyme activities in soils incubated at different temperatures diverged significantly when measured at different temperatures, these differences were overcome when measured at 20 °C, suggesting enzyme activities are more limited than enzyme production. Two exceptions to this trend were the first harvest of the 4 and 8 °C incubations, which had significantly higher BG and BX activities when assayed at 20 °C than soils incubated at higher temperatures, indicating larger enzyme pool sizes in soils incubated at lower temperatures. For BG activities, increased enzyme pool size offset low temperature limitations to enzyme activity, resulting in no difference in measured rates when the 4 and 8 °C soils were compared with the 12 and 16 °C soils, respectively. However, in subsequent harvests, BG and BX activities measured at 20 °C declined and activities at 4 and 8 °C were significantly lower than in assays at 12, 16, and 20 °C. Declining activities of these enzymes in the 4 and 8 °C incubations may indicate limited substrate accessibility or nutrient availability at lower temperatures due to changes in the relative rates of other decomposition reactions with temperature. Improving our understanding of the multifaceted impacts of temperature on decomposition reactions will be important to better model and predict future carbon release.

Exotic plant invasions alter ecosystem properties and threaten ecosystem functions globally. Interannual climate variability (ICV) influences both plant community composition (PCC) and soil properties, and interactions between ICV and PCC may influence nitrogen (N) and carbon (C) pools. We asked how ICV and non-native annual grass invasion covary to influence soil and plant N and C in a semiarid shrubland undergoing widespread ecosystem transformation due to invasions and altered fire regimes. We sampled four progressive stages of annual grass invasion at 20 sites across a large (25,000 km2) landscape for plant community composition, plant tissue N and C, and soil total N and C in 2013 and 2016, which followed two years of dry and two years of wet conditions, respectively. Multivariate analyses and ANOVAs showed that in invasion stages where native shrub and perennial grass and forb communities were replaced by annual grass-dominated communities, the ecosystem lost more soil N and C in wet years. Path analysis showed that high water availability led to higher herbaceous cover in all invasion stages. In stages with native shrubs and perennial grasses, higher perennial grass cover was associated with increased soil C and N, while in annual-dominated stages, higher annual grass cover was associated with losses of soil C and N. Also, soil total C and C:N ratios were more homogenous in annual-dominated invasion stages as indicated by within-site standard deviations. Loss of native shrubs and perennial grasses and forbs coupled with annual grass invasion may lead to long-term declines in soil N and C and hamper restoration efforts. Restoration strategies that use innovative techniques and novel species to address increasing temperatures and ICV and emphasize maintaining plant community structure – shrubs, grasses, and forbs – will allow sagebrush ecosystems to maintain C sequestration, soil fertility and soil heterogeneity.

In the framework of EGS, using hydraulic stimulation increases pore pressure into the existing fracture networks and can be responsible for slip reactivations. In order to predict the seismic or aseismic character of these slips, it is important to determine the influence of the gouge characteristics on the slip behaviour. Lab or in-situ testing can be very helpful, but experience has shown that it is complicated to install local sensors inside a mechanical contact and that some data remains impossible to obtain. In this study, we are focusing on the physics of the contact inside a granular gouge to understand the mechanisms of slip triggering by using numerical modelling. We implement a 2D granular fault gouge with Discrete Element Modelling (DEM). The model involves two rough surfaces representing the rock walls separated by a granular gouge with realistic angular particles created by the wear of previous slips. A displacement-driven model with dry contact is primarily studied to observe the peak of static friction (shape, slope or duration). In order to spotlight the aseismic and seismic patterns, a second model is carried out to add the stiffness of the rocks (or loading apparatus). Dedicated post processing tools are also used in order to analyse the spatial distribution of the solid fraction and the force chains patterns bringing a new understanding of physics from a granular point of view. Representing realistic morphology of particles (angular shapes) brings an additional level of control with respect to most of the simulations reported in the literature using circular grains. Angular grains lead to higher friction coefficients with different global behaviours. The initial solid fraction of the gouge appears to be a good indicator of the friction peak we have at a slip triggering (Fig.). The more compacted the gouge is, the more effort is needed to disturb the initial grains assembly and to reach a steady state regime. With fractal size distribution, we have also studied the mechanical contribution of small particles in the media. Friction coefficient results let us conclude that the presence or not of very small particles is not as influent as the initial solid fraction of the gouge. Finally, adding a stiffness on the upper rock wall provides information on the transition from stable sliding to slow-slip/stick-slip behaviour.

Accurately estimating the net seasonal snow accumulation (or “winter balance”) on glaciers is central to assessing glacier health and predicting glacier runoff. However, measuring and modeling snow distribution is inherently difficult in mountainous terrain, resulting in high uncertainties in estimates of winter balance. Our work focuses on uncertainty attribution within the process of converting direct measurements of snow depth and density to estimates of winter balance. We collected more than 9000 direct measurements of snow depth across three glaciers in the St. Elias Mountains, Yukon, Canada in May 2016. Linear regression (LR) and simple kriging (SK), combined with cross correlation and Bayesian model averaging, are used to interpolate estimates of snow water equivalent (SWE) from snow depth and density measurements. Snow distribution patterns are found to differ considerably between glaciers, highlighting strong inter- and intra-basin variability. Elevation is found to be the dominant control of the spatial distribution of SWE, but the relationship varies considerably between glaciers. A simple parameterization of wind redistribution is also a small but statistically significant predictor of SWE. The SWE estimated for one study glacier has a short range parameter (90 m) and both LR and SK estimate a winter balance of ~0.6 m w.e. but are poor predictors of SWE at measurement locations. The other two glaciers have longer SWE range parameters (~450 m) and due to differences in extrapolation, SK estimates are more than 0.1 m w.e. (up to 40%) lower than LR estimates. By using a Monte Carlo method to quantify the effects of various sources of uncertainty, we find that the interpolation of estimated values of SWE is a larger source of uncertainty than the assignment of snow density or than the representation of the SWE value within a terrain model grid cell. For our study glaciers, the total winter balance uncertainty ranges from 0.03 (8%) to 0.15 (54%) m w.e. depending primarily on the interpolation method. Despite the challenges associated with accurately and precisely estimating winter balance, our results are consistent with the previously reported regional accumulation gradient.

Brittleness index (BI) has been considered as a key geomechanical parameter in evaluating fracturability of the shale formation for optimal extraction of hydrocarbon. BI is commonly used to quantitatively classify the brittle-ductile zones in thick shale reservoir and is considered as completion quality index. There are different methods for determining BI. In the present study, mineralogy based BI estimation method has been followed to identify brittle zones of Cambay Shale of Jambusar-Broach block, Cambay basin, India. Mineralogical composition is having a very significant role in controlling brittleness of a rock. Advanced geochemical logs like the Elemental Capture Spectroscopy (ECS) / Litho Scanner were utilized to get the continuous estimation of mineralogical composition of the Cambay Shale formation. XRD and SEM-EDS techniques are also used for mineralogical analysis of selected core samples taken from different depths. Analysis from XRD and SEM-EDS techniques reveals that the shale is composed of kaolinite, chlorite, quartz, siderite, pyrite and other minerals. Good match has been observed between the BI estimated using mineralogical composition from geochemical log and XRD analysis of core samples. Along with BI, another parameter namely fracability index (FI) has been also used for hydro-fracture evaluation. FI has been estimated continuously, combining normalized brittleness index and normalized Young’s modulus. In addition to BI and FI, type of clay minerals present has some controlling role during hydro-fracture. Mineralogical analysis reveals that for hydro-fracture operation, Cambay Shale has the advantage of having kaolinite and chlorite as dominant clay minerals which are comparatively less susceptible to swelling and plastic behaviour than other clay minerals like illite. An integrated analysis of BI, FI, mineralogy, petrophysical and geochemical properties will be helpful for identification of potential target zones within thick shale. Acknowledgement The authors would like to thank Oil and Natural Gas Corporation Limited, India for providing the requisite dataset and core samples to carry out the present study.

The winter Arctic Oscillation (AO) is important for understanding the Northern Hemisphere climate variability and predictability. However, ENSEMBLES models produce inconsistent predictions when applied to the interannual variability of the 1962–2006 winter AO. In this study, the interannual increment of the winter AO index (DY_AOI) during 1962–2006 is first improved by a dynamical‐statistical model with two predictors: the preceding autumn Arctic sea ice and the concurrent winter ENSEMBLES‐predicted sea surface temperature over the North Pacific. Next, the improved final AOI is obtained by adding the improved DY_AOI to the preceding observed AOI. Because the interannual increment approach can amplify prediction signals and takes advantage from the previous observed AOI, this method shows promise for significantly improving the interannual variability prediction capabilities of the winter AO during 1962–2006 in the ENSEMBLES models. Therefore, this study offers important insights for AO predictions, even other climate variables predictions.

The Thermal And Near infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT) was launched in Jan. 2009 to monitor global CO2 and CH4 distribution from space. The wide-spectral-range data by FTS can measure the partial-column density of the lower troposphere using sun-light reflected from the surface and thermal emission from the atmosphere. In addition to nominal global grid-observation, TANSO-FTS has an agile pointing system to target various CH4 point-sources as well as reference points every three days over years, and can capture the entire flux emitted vertically and horizontally from the source. We demonstrated the monitoring capability by using the natural-gas blowout event at Aliso Canyon, CA and tried to estimate the CH4 flux from a dairy farm in Chino, CA with the Weather Research and Forecasting model. The GOSAT footprint, which is much larger than the point-source area, reduces the enhancement of the retrieved column density close to the detection level. As the single-pixel data and acquisition time of 4 s by FTS limits the number of sampling points near the emission source, careful screening with wind speed and direction is required to acquire reference and source dataset for analysis. The largely fluctuated single data requires to be averaged to improve the precision, but the GOSAT data is spatially too sparse. We calculated the local CH4 flux from Chino using the correlation between wind speed and density, but the lack of a proper reference result in large errors. To solve the above-mentioned issues, we manufactured airborne imaging-spectrometer suites comprising two bands to measure CH4 and CO2 at 1.6 μm and O2 at 0.76 μm. They have 4,000 times more data than GOSAT, increase enhancement with higher spatial resolution, and select proper upwind reference with imaging capability. In Feb. 2018, we flew over greater Nagoya with the mixture of possible emission sources such as energy production, waste water, dairy farm, and agriculture. The spectral image of spatial resolution <100 m has clearly detected enhancement from individual local sources of CH4 and CO2. We add one more spectrometer to measure short-lived NO2 to detect plume orientation. Our goal is to individually estimate city-level CH4 flux from different source sectors.

not-yet-known not-yet-known not-yet-known unknown Vegetation serves as a critical indicator of environmental health, reflecting soil, water and air quality. Monitoring changes in vegetation distribution and extent is essential, especially in regions prone to climatic extremes. Traditional vegetation monitoring methods are labor-intensive, costly, and time-consuming. Remote sensing offers a powerful alternative, providing extensive spatial coverage and enabling efficient analysis. This study examines the impact of rainfall on vegetation growth in Latur, a drought-prone district in Maharashtra, India, utilizing Sentinel-2 satellite data and the Vegetation Condition Index (VCI) from 2017 to 2023. The 10-meter spatial resolution annual maps from ESRI, covering the years 2017 to 2023, were utilized to assess changes in land use and land cover (LULC). The LULC data were classified into seven classes: Water, Trees, Flooded Vegetation, Agricultural Land, Built Area, Bare Ground, and Rangeland. In 2017, Agricultural Land constituted 92% of the total area, decreasing to 90.28% by 2023, while the built-up area rose from 2.81% to 3.41%. Additionally, the annual mean VCI decreased from 36.28 in 2017 to 15.29 in 2023. The study assessed land use changes from 2017 to 2023, revealing a strong correlation between rainfall and vegetative growth. Spatial maps show significant seasonal variations in vegetation, emphasizing the need for continuous monitoring. This research highlights the effectiveness of Sentinel-2 data and Google Earth Engine for large-scale vegetation monitoring in drought-prone areas. Keywords: Vegetation dynamics, Sentinel-2, VCI, Google Earth Engine, rainfall impact, drought-prone regions.

The California Council on Science and Technology (CCST) is a non-partisan, nonprofit, boundary organization with the mission of bringing science to decisionmakers. We focus on building and strengthening relationships with California’s decisionmakers—who need information to craft fact-based policy—and the scientists and experts who generate knowledge. We connect science and policy through a variety of programs, including 1) rapid-response expert briefings for the California capitol community on emerging issues, such as wildfires or disease outbreaks; 2) peer-reviewed, independent studies commissioned by State entities to provide decisionmakers with comprehensive analyses of the state of science on politically relevant, technically complex topics; and 3) a Science Fellowship program that for the past 10 years has placed PhD scientists and engineers as staff in State legislative offices for a year of public service. We will share specific examples from our programs that highlight best practices for facilitating the transfer of knowledge between scientists and decisionmakers and lessons learned from navigating the barriers that commonly arise when working at the boundary of science and policy.

The response of atmospheric variability to the Tibetan Plateau (TP) snow cover (TPSC) at interannual to decadal time-scales has been extensively investigated. However, the response of the atmosphere to the subseasonal variability of the TPSC has been largely ignored. Here, we found that the subseasonal variability of the TPSC revealed by daily data can serve as an indicator of East Asian atmospheric circulation on medium-range time-scales (approximately 3–7 days in advance). The subseasonal variability of the TPSC influences the upper-level regional atmospheric circulations, especially the East Asia upper-level westerly jet stream (EAJS), during wintertime. The variability of the TPSC modulates the land surface thermal conditions over the TP, which acts as an elevated cooling source in the middle troposphere during wintertime. The upper-level geopotential height is affected by the TPSC and then the zonal wind. As a result, the EAJS is influenced.

Open data, data that anyone can access, use, and share have found its place in the current research landscape. Yet, there are many waters to navigate for open access data. Repositories such as BCO-DMO are here to make that journey easier; juggling data principles and policies, funding requirements, publication specifications, research specifics, archiving and discovery through online search engines. BCO-DMO is a domain-specific repository serving highly heterogeneous biological and chemical oceanographic data. The scale of our data ranges from atmospheric aerosols to the bottom of the seafloor, microbes to megafauna. We assist investigators supported through NSF and private funders throughout the Data Life Cycle. We not only have in-house data managers that extensively curate the data and assist submitters in complying with the F.A.I.R Data Principles, but we also develop resources and architecture to tackle technology hurdles associated with these principles to ease data sharing on the behalf of researchers: Designing and implementing ontologies to increase discovery of the data Developing systems to track provenance Creating and improving standard operating procedures to ensure consistent data processing Providing APIs for improved interoperability Developing an automated submission system to ease data sharing burden To make sure that everything we develop addresses community needs, we continue to seek feedback on our processes (i.e what hurdles does the community have with their data and how can we help to overcome them) through a strategic planning committee and continued communication with submitters. We take part in several broader data community initiatives to improve data interoperability and reuse and demonstrate trustworthiness by obtaining CoreTrustSeal certification. How do you determine an appropriate repository to openly share your data? Is BCO-DMO on your list of choices? Let’s hear about it.

An improved understanding of the mechanisms and factors affecting glacial flow is crucial to better predict sea level rise. Glacial ice often contains impurities such as the presence of small insoluble particles. Mixtures of ice and dust can be found in many places throughout the world, specifically in areas of high latitude and altitude (Moore, 2014). This study aims to understand the effect of entrained insoluble debris on processes of glacial motion. Glaciers move through a combination of internal ice deformation and basal sliding. Internal ice deformation, the flow of individual ice grains, has been found to be grain-size dependent in both field and laboratory studies (Goldsby and Kohlstedt, 2001). In an attempt to better understand ice grain size, this study considers the effect of debris on grain growth. Samples of pure ice and ice with debris were fabricated with a standard protocol and maintained at -5°C for controlled annealing. Microstructural characterization was preformed using a light microscope to image the samples, and calculating the average grain sizes using a linear-intercept method. The ice with debris was found to have smaller grain sizes, thought to be associated with grain-boundary pinning. Extrapolated values were used with a flow law, projecting that ice with debris will have lower viscosity, thus flow faster. To address basal sliding, the other form of glacial movement, we conducted a second phase of study. Basal sliding, the process of a glacier sliding over the bedrock, is influenced by the presence of meltwater at the base of the glacier (Hoffman et al., 2011). Frictional heating, from ice-on-rock friction, was studied as a factor affecting meltwater production. We conducted a simple 1D computer model using laboratory friction measurements of ice with entrained debris (Zoet et al., 2013). We find that debris content and frictional heating are directly proportional. Trials run at faster glacial velocities also show larger amounts of frictional heating. As frictional heating may increase meltwater, glaciers with debris may slide faster over bedrock. Overall, by better understanding the motion of debris-rich glaciers, we can focus our attention to areas around the world at risk, and better predict/prepare for sea level rise.

Due to the effects of climate change, the USA Southwest is expected to experience increased temperatures and decreased water availability. Extended droughts will likely have important consequences for riparian trees whose growth and habitat are strongly limited by water availability. One consequence of extended water table declines on riparian trees is the development of wood anatomical anomalies. Using techniques developed for quantitative wood anatomy (QWA) it may be possible to quantify these anomalies and reconstruct water table variability through time. We explore this possibility using tree rings from netleaf hackberry (Celtis laevigata var. reticulata) collected along the Upper Santa Cruz River, Arizona. We suggest hackberry has the potential to be used 1) as an indicator of riparian ecosystem health, and 2) to provide improved reconstructions of water availability. Understanding how hackberry responds to periods of low and high flows can provide insight into how to better manage these ecosystems into the future.

Some aspects of the dynamics of aeolian transport over a flat sediment bed have been thoroughly investigated and are relatively well understood. The interactions between grains in transport and the wind give rise to well-known dynamical scaling laws for the fluxes and concentrations of grains in most of the transport layer. However, recent work has revealed a sudden shift in these scaling laws near the granular surface and below. While the vertical flux of grains in the transport layer scale linearly with excess wind shear stress, the vertical flux near the granular surface—the ‘erosion rate’—scales linearly with wind speed. Analysis of numerical modeling results reveal that near-surface horizontal and vertical fluxes are important for the instability that leads to wind ripple growth and stabilization as well as ripple propagation. A few main open questions are: What are the physical mechanisms behind the scaling of the erosion rate with wind speed? Could they arise from the small subpopulation of high-energy grains, who’s characteristics scale differently than the average grain in transport? As these grains move downward from the free-wind layer, do they tend to retain their properties as they pass through the feedback layer, delivering their energy, momentum and scaling directly to the bed? Do collisions between grains near and within the bed, which redistribute energy and momentum from high-energy impacts, play a key role in determining the scaling of near-bed fluxes? How important are potential collective effects that can occur when impacts with sufficient energy to excite the bed occur close together in time and space? An answer to these questions would help complete our understanding of the physics of aeolian transport, with repercussions that shed light onto the emergence and propagation of wind ripples. Using a detailed grain scale numerical model, we are investigating the dynamics of grains near the granular bed, and what saltation properties drive these dynamics. Preliminary results, including velocity distributions near the bed, indicate that the signal from high-energy grains that traverse the feedback layer from above reaches the bed surface, consistent with the hypothesis that the surface erosion rate is related to this small population of grains who’s characteristics scale with the free-wind speed.

The conservation of historic cultural heritage sites is an endeavor that often brings together a diverse group of methods and interests. Castelul Corvinilor, also called Corvin’s Castle or Hunedoara Castle, in central Transylvania (Hunedoara county, Romania) is no exception. The first stone fortification of the medieval castle can be dated to the 14th century and has undergone significant expansion since the original structure was completed. The main building campaigns started in 1440 with the conversion of the fortress into a castle, followed by two more major campaigns during the 17th and 19th centuries, including restoration and remodeling of the original areas. The castle’s historical significance and touristic value make conservation an important goal for the site. This area has been the subject of limited and opportunistic (salvage) archaeological investigations, hoping to understand earlier phases of an administrative complex in the courtyard. However, the excavations did not establish a complete stratigraphy. A ground penetrating radar survey over most of the courtyard was conducted with a 500 MHz antenna, including the main courtyard area. This GPR survey of the courtyard was able to confirm some results of the archaeological excavation and located additional structures which were previously unknown. This presentation included analysis and interpretation of the data in both radargrams and depth slices. They reveal further horizons which indicate bedrock and possible reflections from structures dating to even earlier phases of the site.

The boreal forests of Alaska have been experiencing a changing fire regime which threatens human lives and vulnerable ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition could provide guidance for decision support. Such insight may be especially useful in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium, or large fires with 50.4 ± 5.2% accuracy in cross-validation. This was accomplished using two variables: vapor pressure deficit (VPD) and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, which accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires. The overprediction is explained by (1) suppression of those fires and (2) the fact that ignitions in more human-influenced areas occurred during periods of higher VPD on average. Overall, this type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.

Clear air turbulence (CAT) is a serious threat for civil aviation flights. In the years 2009 through 2015, with the support of the European Commission, as a part of the 7th Framework Program, the DELICAT project (DEmonstration of LIdar based Clear Air Turbulence detection) was implemented. In this project, an air-borne lidar was developed and built for an early detection of CAT. In August 2013, flight tests of the lidar were carried out. During the experiments, a large unique data set was collected; a copy of the data set is in the possession of the Obukhov Institute of Atmospheric Physics of Russian Academy of Sciences (IAP RAS). In the proposed project, we propose solving the following problems. We will develop a numerical model of the laser sounding of CAT, considering the effect of the laser beam propagation in a random medium, as well as the aerosol (Mie) and molecular (Rayleigh) scattering. The analysis of the existing observations indicates that, in most cases, the multiple scattering effects are negligible. The will allow us to develop the model on the basis of the multiple phase screen method. This model will produce realizations of the random signal for specific realization of the random refractivity and aerosol distribution fields. A modification of the multiple phase screen method will allow modeling a diverging laser beam. This will also allow modeling of the back-scattering enhancement (BSE). By varying the aerosol composition, it will be possible to model different degree of correlation and intensity ratio in co- and cross-polarization channels. The model of the laser sounding of CAT will help answering the question, whether aerosol is an impeding factor when using the BSE effect. We will develop a realistic model of the observation geometry variations. We will perform the primary processing of the whole available data set of the DELICAT observations. This will allow us to estimate the statistical properties of the measurement noise. We will analyze the DELICAT observations. We will fit the model parameters in order to reproduce, as close as possible, the statistical properties of the observations. This will help answering the questions, how accurately and timely it is possible to detect CAT parameters using two types of lidar systems: 1) system with two polarization channels, and 2) system based on the BSE effect.

In the call of 2015, the European Geosciences Union funded the workshop “Water as hazard and water as heritage”, to take place in Rome in the consecutive year. The frame for the workshop was given by the “Spazi aperti” (=open spaces) event at the Accademia di Romania a Roma, where the convener (Maria Bostenaru Dan) was a fellow that time on a topic related to water and architecture. Spazi aperti XIV, the edition of 2016, was curated by Roxana Mihaly, former fellow of Accademia di Romania a Roma. The integration reached over the day of oral presentations, as posters of the workshop were displayed in frame of the exhibition in a creative way. Accademia di Romania a Roma opens in frame of Spazi aperti all its spaces, not only the conference room, and the posters were displayed in an underground corridor ending in spaces with related artistic works (for example the convener participated with an installation). The artists invited come from other foreign accademies in Rome, Rome being a city to be visited by scientists from humanities and artists since a number of centuries (“all ways lead to Rome”). This ensured international participation from Europe and beyond. The geosciences were also well represented, which enabled the dialogue between science and the arts. After the talks guided tours were organised to related exhibitions on water in related museums which emphasized the archaeology dimension. Apart of this event there were a number of scientific and musical events accompanying the exhibition, strenghening the dialogue. The event was part of the “month of international culture” in Rome, highly mediatised, and different of the exhibitions of just own fellows in other foreign academies. In 2018 the book was published and is subject of a poster in another session (EGU2019-2000) which all attendees are invited to see. More about the event can be followed on the webpage https://sites.google.com/site/egutopicalevent/