Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

BPM software and process modelling languages in practice

IT has turned out to be a key factor for the purposes of gaining maturity in Business Process Management (BPM). This book presents a worldwide investigation that was conducted among companies from the ‘Forbes Global 2000’ list to explore the current usage of software throughout the BPM life cycle and to identify the companies’ requirements concerning process modelling. The responses from 130 companies indicate that, at the present time, it is mainly software for process description and analysis that is required, while process execution is supported by general software such as databases, ERP systems and office tools. The resulting complex system landscapes give rise to distinct requirements for BPM software, while the process modelling requirements can be equally satisfied by the most common languages (BPMN, UML, EPC).

Productive Diversification and Sustainable Use of Complex Social-Ecological Systems: A Comparative Study of Indigenous and Settler Communities in the Bolivian Amazon

Agricultural and forest productive diversification depends on multiple socioeconomic drivers—like knowledge, migration, productive capacity, and market—that shape productive strategies and influence their ecological impacts. Our comparison of indigenous and settlers allows a better understanding of how societies develop different diversification strategies in similar ecological contexts and how the related socioeconomic aspects of diversification are associated with land cover change. Our results suggest that although indigenous people cause less deforestation and diversify more, diversification is not a direct driver of deforestation reduction. A multidimensional approach linking sociocognitive, economic, and ecological patterns of diversification helps explain this contradiction.

Discussion: Food security and sustainable food systems: The role of soil

There is a general consensus that healthy soils are pivotal for food security. Food production is one of the main ecosystem services provided by and thus dependent on well-functioning soils. There are also intrinsic connections between the four pillars of food security: food availability, access, utilization, and stability; with how soils are managed, accessed and secured, in particular by food insecure and vulnerable populations. On the other hand, socio-political and economic processes that precipitate inequalities and heighten vulnerabilities among poor populations often increase pressure on soils due to unsustainable forms of land use and poor agricultural practises. This has often led to scenarios that can be described as: ‘poor soils, empty stomachs (hungry people) and poor livelihoods.' In 2015, in particular, as we head towards approval of the ‘Sustainable Development Goals' (SDGs), the role of Financing for Development is debated and agreed upon and a new climate pact is signed – these three political dimensions define how a new post-2015 agenda needs to be people-smart as well as resource-smart. For proposed SDG 2 (Food Security and Hunger), there can be so resolution without addressing people, policies and institutions.

Predictive modelling of mineral scaling, corrosion and the performance of solute geothermometers in a granitoid-hosted, enhanced geothermal system

Experience is lacking with mineral scaling and corrosion in enhanced geothermal systems (EGS) in which surface water is circulated through hydraulically stimulated crystalline rocks. As an aid in designing EGS projects we have conducted multicomponent reactive-transport simulations to predict the likely characteristics of scales and corrosion that may form when exploiting heat from granitoid reservoir rocks at ∼200 °C and 5 km depth. The specifications of an EGS project at Basel, Switzerland, are used to constrain the model. The main water–rock reactions in the reservoir during hydraulic stimulation and the subsequent doublet operation were identified in a separate paper (Alt-Epping et al., 2013b). Here we use the computed composition of the reservoir fluid to (1) predict mineral scaling in the injection and production wells, (2) evaluate methods of chemical geothermometry and (3) identify geochemical indicators of incipient corrosion. The envisaged heat extraction scheme ensures that even if the reservoir fluid is in equilibrium with quartz, cooling of the fluid will not induce saturation with respect to amorphous silica, thus eliminating the risk of silica scaling. However, the ascending fluid attains saturation with respect to crystalline aluminosilicates such as albite, microcline and chlorite, and possibly with respect to amorphous aluminosilicates. If no silica-bearing minerals precipitate upon ascent, reservoir temperatures can be predicted by classical formulations of silica geothermometry. In contrast, Na/K concentration ratios in the production fluid reflect steady-state conditions in the reservoir rather than albite–microcline equilibrium. Thus, even though igneous orthoclase is abundant in the reservoir and albite precipitates as a secondary phase, Na/K geothermometers fail to yield accurate temperatures. Anhydrite, which is present in fractures in the Basel reservoir, is predicted to dissolve during operation. This may lead to precipitation of pyrite and, at high exposure of anhydrite to the circulating fluid, of hematite scaling in the geothermal installation. In general, incipient corrosion of the casing can be detected at the production wellhead through an increase in H2(aq) and the enhanced precipitation of Fe-bearing aluminosilicates. The appearance of magnetite in scales indicates high corrosion rates.

Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

Invited Abstract: Issues with State-based Energy Consumption Modelling

Energy consumption modelling by state based approaches often assume constant energy consumption values in each state. However, it happens in certain situations that during state transitions or even during a state the energy consumption is not constant and does fluctuate. This paper discusses those issues by presenting some examples from wireless sensor and wireless local area networks for such cases and possible solutions.

Computational fluid dynamics modelling in cardiovascular medicine.

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.