Decision support system for peatland management in the humid tropics

Large areas of globally important tropical peatland in Southeast Asia are threatened by land clearance, degradation and fire, jeopardising their natural functions as reservoirs of biodiversity, carbon stores and hydrological buffers. Many development projects on tropical peatlands have failed because of lack of understanding of the landscape functions of these ecosystems. Utilisation of these peatland resources for agriculture or other land use requires drainage which, unavoidably, leads to irreversible loss of peat through subsidence, resulting in severe disturbance of the substrate, CO2-emissions and problems for cultivation. To assist planners and managers in wise use of these tropical peatlands a decision support system (DSS) has been developed. This DSS, which is based on a GIS application, combines the Groundwater Modelling Computer Programme PMWIN with expert knowledge on subsidence, land use and water management. The DSS can be used to predict the long-term effects of different types of land use, e.g. peat swamp forest, sago or oil palm plantations, on the lifetime and associated CO2 release of these tropical peatlands. The type of land use dictates the required depth of the groundwater table, which on its turn has a significant effect on the sustainability of the peatland. Therefore, special attention should be paid when deciding which type of land use to pursuit. The Decision Support System (DSS) will help to improve the decision-making process. The groundwater model PMWIN was selected because it maintains a good balance between the complexity of the model (esp. regarding to its input data requirements) and the availability of input data. The groundwater model was calibrated using data from the Balingian Area, Central Sarawak, Malaysia. The model was used to predict, based on a given land use scenario, the ratio between surface and groundwater runoff, the depth of the groundwater table and recharge and discharge zones of the peat dome. Various land use scenarios, each with its own specific water management requirements, were developed and used to predict the long-term changes in ground level and associated CO2 release. For each scenario the following outcome was generated: time span after which the water management systems have to be deepened, time span after which gravity drainage is no longer possible, time span for peat disappearance. Final results are presented in the form of maps generated by the GIS application. These maps serve as a communication tool with stakeholders to demonstrate what the hydrological effects are on for instance a certain land use type and drainage system lay-out

Controls on the spatio-temporal patterns of induced seismicity in Groningen constrained by physics-based modelling with Ensemble-Smoother data assimilation

The induced seismicity in the Groningen gas field, The Netherlands, presents contrasted spatio-temporal patterns between the central area and the south west area. Understanding the origin of this contrast requires a thorough assessment of two factors: (1) the stress development on the Groningen faults and (2) the frictional response of the faults to induced stresses. Both factors have large uncertainties that must be honoured and then reduced with the observational constraints. Ensembles of induced stress realizations are built by varying the Poisson's ratio in a poro-elastic model incorporating the 3-D complexities of the geometries of the Groningen gas reservoir and its faults, and the historical pore pressure distribution. The a priori uncertainties in the frictional response are mapped by varying the parameters of a seismicity model based on rate-and-state friction. The uncertainties of each component of this complex physics-based model are honoured through an efficient data assimilation algorithm. By assimilating the seismicity data with an Ensemble-Smoother, the prior uncertainties of each model parameter are effectively reduced, and the posterior seismicity rate predictions are consistent with the observations. Our integrated workflow allows us to disentangle the contributions of the main two factors controlling the induced seismicity at Groningen, induced stress development and fault frictional response. Posterior distributions of the model parameters of each modelling component are contrasted between the central and south west area at Groningen. We find that, even after honouring the spatial heterogeneity in stress development across the Groningen gas field, the spatial variability of the observed induced seismicity rate still requires spatial heterogeneity in the fault frictional response. This work is enabled by the unprecedented deployment of an Ensemble-Smoother combined with physics-based modelling over a complex case of reservoir induced seismicity

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes

Controls on the spatio-temporal patterns of induced seismicity in Groningen constrained by physics-based modelling with Ensemble-Smoother data assimilation

International audienceSUMMARY The induced seismicity in the Groningen gas field, The Netherlands, presents contrasted spatio-temporal patterns between the central area and the south west area. Understanding the origin of this contrast requires a thorough assessment of two factors: (1) the stress development on the Groningen faults and (2) the frictional response of the faults to induced stresses. Both factors have large uncertainties that must be honoured and then reduced with the observational constraints. Ensembles of induced stress realizations are built by varying the Poisson's ratio in a poro-elastic model incorporating the 3-D complexities of the geometries of the Groningen gas reservoir and its faults, and the historical pore pressure distribution. The a priori uncertainties in the frictional response are mapped by varying the parameters of a seismicity model based on rate-and-state friction. The uncertainties of each component of this complex physics-based model are honoured through an efficient data assimilation algorithm. By assimilating the seismicity data with an Ensemble-Smoother, the prior uncertainties of each model parameter are effectively reduced, and the posterior seismicity rate predictions are consistent with the observations. Our integrated workflow allows us to disentangle the contributions of the main two factors controlling the induced seismicity at Groningen, induced stress development and fault frictional response. Posterior distributions of the model parameters of each modelling component are contrasted between the central and south west area at Groningen. We find that, even after honouring the spatial heterogeneity in stress development across the Groningen gas field, the spatial variability of the observed induced seismicity rate still requires spatial heterogeneity in the fault frictional response. This work is enabled by the unprecedented deployment of an Ensemble-Smoother combined with physics-based modelling over a complex case of reservoir induced seismicity

Hydrothermal and Magmatic System of a Volcanic Island Inferred From Magnetotellurics, Seismicity, Self‐potential, and Thermal Image: An Example of Miyakejima (Japan)

International audiencePhreatic and phreatomagmatic eruptions represent some of the greatest hazards occurring on volcanoes. They result from complex interactions at a depth between rock, water, and magmatic fluids. Understanding and assessing such processes remain a challenging task, notably because a large-scale characterization of volcanic edifices is often lacking. Here we focused on Miyakejima Island, an inhabited 8-km-wide stratovolcano with regular phreatomagmatic activity. We imaged its plumbing system through a combination of four geophysical techniques: magnetotellurics, seismicity, self-potential, and thermal image. We thus propose the first comprehensive interpretation of the volcanic island in terms of rock properties, temperature, fluid content, and fluid flow. We identify a shallow aquifer lying above a clay cap (<1 km depth) and reveal its relation with magmatic-tectonic features and past eruptive activity. At greater depths (2-4.5 km), we infer a seismogenic resistive region interpreted as a magmatic gas-rich reservoir (≥370°C). From this reservoir, gases rise through a fractured conduit before being released in the fumarolic area at ∼180°C. During their ascent, these hot fluids cross a ∼1.2-km-long liquid-dominated zone causing local steam explosions. Such magmatic-hydrothermal interaction elucidates (i) the origin of the long-period seismic events and (ii) the mixing mechanism between magmatic and hydrothermal fluids, which was previously observed in the geochemical signature of fumaroles. Our results demonstrate that combining multidisciplinary large-scale methods is a relevant approach to better understand volcanic systems, with implications for monitoring strategies