DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.

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.