HiPerBorea aims to enable quantitative and predictive modeling of the thermo-hydrological evolution of cold environments covered by permafrost (25% of lands of northern hemisphere) under climate change. Permafrost thaw is associated with major feed-backs on greenhouse gases cycles (e.g.: thawing of previously frozen organic carbon pools). Its dynamics is a key factor for climatic evolution. The involved physics are highly coupled and non-linear, and simulating them at the scale of long-term monitored watersheds requires the development of spatially distributed and process oriented high performance computing tools. The fields of applications are numerous, from the hydro-bio-geochemistry of cold areas to engineering applications such as infrastructure stability in cold environments or site scale cryo-barriers in polluted industrial areas. The approach that we aim to apply in order to reach this goal is to develop an OpenFOAM® framework for parallel computing modeling of thermo-hydrodynamics of cold continental surfaces. The team of the project already recently produced a validated and high performance simulation tool for coupled thermo-hydrological transfers in the ground with freeze/thaw of the pore water, the so-called permaFoam solver (Orgogozo et al., 2019), with a good scalability tested on tier-2 and tier-1 supercomputers up to 4000 cores, and enabling to deal with large problems such as a 1.2 billion cells mesh problems (Orgogozo et al., 2015). In this project we would like to further develop the high performance computing capabilities of permaFoam and to apply them to perform highly challenging, watershed scale, centennial simulations of thermo-hydrologic transfers in long term environmental monitoring stations of arctic and sub-arctic regions. The goal is to give a proof of concept of the benefit that can be expected from the use of modern high performance computing techniques for cold regions sciences and engineering. In order to relevantly use this computational power, the permaFoam solver will be further developed to cope with all the determinant processes for water catchment hydrology and hydrogeology in boreal areas. As such it will: 1) integrates in a numerically efficient way the main external processes that control permafrost hydrology, such as bryophytic layer (i.e. moss and lichen cover) dynamics, solar radiation penetration and snow cover thermal insulation; 2) be validated for watershed scale modeling according to the current international standards, and parameterized based on field data sets from sites of long term monitoring of permafrost (eu-interact.org, IRN CAR WET SIB); 3) be used to perform 3D, watershed scale modeling of arctic and sub-arctic permafrost dynamics in response to climate change, thanks to its good parallel performances, which will be optimised for current supercomputers along the project (from the Tier-2 regional meso-centre to the Tier-0 PRACE european computing infrastructures). HiPerBorea will proceed in three main steps: 1) developing, testing and validating the needed numerical tool, 2) applying this tool to the already numerically studied Kulingdakan experimental watershed (Orgogozo et al., 2019) in order to establish an efficient, consolidated methodology for 3D watershed scale, centennial cryohydrologic modeling and finally 3) simulating the responses of four reference long term monitoring boreal catchments to various IPCC scenarios of climate change (CMIP5 projections). Technically speaking the goal is to test the limit size of the applications that can be dealt with the present performances of permaFoam (ability to deal with billion cells mesh, with up to 4000 cores on Tier-1 supercomputers), and to go beyond these limits along the project – towards 10 billions cells mesh, and tens of thousands of used cores on Tier-0 supercomputers.

The 4 per mil initiative promotes soil organic carbon (SOC) sequestration to improve soil fertility, adapt to climate change and reduce greenhouse gas emissions. It targets agricultural soils in priority. Rendering soils « climate smart » requires however an understanding and assessment of the SOC storage potential of different soils. SOC is very heterogeneous with residences times ranging from hours to millennia so that the durability of the stored C needs assesment. Hence, the sustained mitigation of climate change by SOC management requires reliable routine methodologies forecasting SOC stocks evolution. The SOC storage potential of a soil may be defined as the maximum gain in SOC stock attainable under a given climate, a given land use and a given timeline (e.g. time to attain a new equilibrium or IPCC time period: 20y). To date, the different available methods (e.g. Tier 1 to 3) have seldom been compared on a variety of soils, nor with the C saturation approach. Furthermore, SOC dynamics models are limited by the lack of calibration of the different SOC kinetic pools, for which indicators are needed. The project aims to : • Investigate the ability of different methods to determine the size of SOC kinetic pools and test how their routine use to initialize models of SOC dynamics may improve their predictions • Develop and compare different methods to estimate the C storage potential of agricultural soils • Determine the persistence of stored C, particularly in relation to its interaction with soil minerals. The project associates 6 partners, with high and complementary expertise from process level understanding and biogeochemistry, pedology, chemistry, SOC modelling, agronomy, databases and monitoring networks, to spatial statistics and mapping (Ecosys, Grignon, Laboratoire de Géologie Paris, Infosol Orléans LSCE Gif sur Yvette, Institut de Géologie Paris and AgroImpact Laon. The project combines measurements, experiments and modelling. It takes advantage of well-documented Long Term Experiments (LTE) with agroecological cropping practices (conservation agriculture, application of organic wastes, temporary grasslands) and considers the diversity of agricultural soils in a small territory (Versailles plain), in the Region Centre as well as in a series of sites from the French soils monitoring network (RMQS). To identify indicators of SOC kinetic pool sizes Rock Eval pyrolysis will be compared to physical fractionation methods, and these indicators tested against 13C and 14C measurements of the turnover rate of SOC in LTEs. SOC stocks will be modelled with RothC and Century models and with AMG, a simpler one extensively calibrated for temperate agricultural soils. Several approaches will be compared to estimate the SOC storage potential: (i) a statistical approach (identifying in a territory soils with highest SOC stocks per soil type); (ii) a Tier 2 approach (applying literature-based emission factors for practices changes); (iii) a modelling approach (modelling the effect of changes in practices) and (iv) a C saturation approach (quantifying SOC stabilized by its association with < 20 µm soil particles). The project will propose a methodological framework for estimating the SOC storage potential of agricultural soils, to be used also in other pedoclimatic contexts and will compare the ability of several agricultural practices to increase SOC stocks and stabilize organic matter. A strong attention will be dedicated in to promoting international cooperation (e.g. by organizing dedicated workshops) and to dissemination to the scientific community, to stakeholders (i.e. agricultural extension services, small companies, managers in charge of implementing GHG policies at the territorial scale) and to students.

Megathrust earthquakes can induce metric-scale sudden subsidence or uplift, and destabilize shelf sediments, instigating turbiditic flows and landslides. They can also generate tsunamis that can transport huge quantities of marine and coastal sediments and debris inland. Such dramatic events can cause many casualties, destroy infrastructure, and have longer-term impacts on the environment. They may considerably modify the landscape, affecting human settlement over millennia. Between large earthquakes, due to strain accumulation, land deformation induces relative sea level changes at rates much faster than those due to climate change. These events represent a major threat and must be accounted for in regional planning. Missing information on such extreme and rare events, necessary to better constrain the seismic hazard, is a major limitation. The largest earthquakes may recur only every 500 or 1000 yrs and the historical catalogs are too short to allow an estimation of earthquake recurrence intervals and of their magnitude. Existing models based on short historical records have not been successful at predicting earthquake recurrence. Paleoseismological and paleotsunami studies of the geological record are thus needed to address this issue and establish time series over thousands of years. The Lesser Antilles arc is a densely populated and highly touristic zone exposed to megathrust earthquakes. The largest historical event that occurred on 8 February 1843t destroyed the city of Pointe-à-Pitre on Guadeloupe, killing more than 1500 people. Today, a comparable earthquake might cause tens of thousands of casualties. The objective of the CARQUAKES project is to improve the catalog of large earthquakes and tsunamis in the Lesser Antilles and characterize the related hazards by applying an innovative and novel multidisciplinary approach combining several state-of-art methods of offshore and onshore paleoseismology and tsunami modeling. Offshore, we will use the marine sediments (i.e. turbidites/homogenites) as proxies for earthquake recurrence in the Lesser Antilles (Task 1). During the CASEIS marine cruise in Spring 2016, we collected 42 sedimentary cores in the eastern part of the Lesser Antilles arc, above the megathrust zone. The CARQUAKES project is in part conceived to permit the exploitation of this large dataset. Onshore, we will combine several approaches to retrieve the traces of extreme events: 1) paleoseismological and paleotsunami studies in coastal lagoons and ponds that may have preserved the evidence of earthquakes and tsunamis (Task 2); 2) Coral paleogeodesy along the reefs, where coral microatolls may record earthquakes in their skeletal growth (Task 3); and 3) Archaeology and history comprising analysis of historical descriptions of earthquakes and tsunamis in archives and investigations of several coastal archeological sites on Guadeloupe (Task 4). Tsunami and strain modeling will be performed to calculate the impact of earthquake cycle and tsunamis on the littoral zone (wave height, inundation and coastline variations) (Task 5). The CARQUAKES project brings together experts in tectonics, geomorphology, paleoseismology and paleotsunamis, sedimentology, paleo-environment, tsunami modeling, botany, palynology, archaeology, and history. Six partners are involved in the project. The project will benefit society because it will provide information essential to reduce the vulnerability of coastal populations in the Lesser Antilles islands. This will improve our knowledge of earthquake and tsunami hazards and their impact on coastline evolution, ecosystems (destruction and resilience) and human settlement.

TRAJECTOIRE aims to establish past and predictive trajectories of contaminants at the outlets of the major French watersheds (Rhône, Loire, Seine, Garonne, Rhine, Meuse, Moselle) for substances brought about by human activities in these environments during the technological, industrial and environmental development that punctuated the 20th century: radionuclides, microplastics and their additives, and critical metals. These non-legacy substances are currently at the heart of reflections on the energy transition. By considering these three families of contaminants we expect to draw lessons learned based on the differentiated and successive time scales of their inputs, which were governed by institutions and public policies according to distinct management modes. By considering them, we expect to draw general lessons on the environmental resiliency regarding contaminants, and then to positioning or repositioning current environmental concerns face to new and future technologies. In other words, it will be a question of evaluating how society can be an actor of the resilience of the environment following anthropic disturbances from economic choices, political decisions and collective actions. In river systems, sediments convey and store most of contaminants introduced in the catchment. Therefore, sedimentary archives in perennial storage areas, such as riverbanks or alluvial margins, give testimonials on previous contaminations and anthropic pressures. Feedbacks on the ability of large rivers to absorb or remove anthropogenic pressures will be established by reconstructing time-series of: 1) contamination levels based on sedimentary records and 2) pressures exerted on environments and responses provided by institution and society, based on analyses of documentary archives. The difficulties of such retrospective exercise, requiring to cross multiple and complex information, are all the greater as the statistical sources concerning contaminants are rare or confidential. The causal links between the observed contamination levels in sedimentary archives (quantitative data sets) and the anthropic pressures determined from documented archives (qualitative and semi-quantitative data sets) will be assessed using neural network analyses for time series prediction. Time series models are purely dependent on the idea that past behavior and patterns can be used to predict future behavior and trends. By using these models on data sets acquired at the outlets of major French rivers, various anthropic pressures will be considered and their consequences on the concentration of contaminants over time will be identified. Socio-historical events, acquired from documented archive analyses, will be characterized regarding their impact on concentrations, the time-lag between their occurrence and the environmental impact, and the duration of the environmental perturbation. The values of these three parameters associated to the best fittings between the data and times series models will define key pressures to be implemented in a predictive model based on scenario in order to forecast the levels of contaminants in river systems and estimate trajectories and resiliencies for the short, medium and long terms. Our results will put forth the environmental changes that succeeded over the last industrial era, and will help to predict those expected depending on our future conduct. We consider that society needs such feedbacks as well as predictive vision in order to reinforce environmental awareness and future decision making related to the sustainability of ecosystems. Our project aims to give quantitative feed backs and predictive models based on scenarios in order to inform stakeholders on environmental impacts of their past and future decisions, over short and longer term time periods. It aims to demonstrate that society can act on environmental resiliency.