Assessment of Water Availability in a Central-European River Basin (Elbe) Under Climate Change

 The Elbe region is representative of humid to semi-humid landscapes in Central Europe, where water availability during the summer season is the limiting factor for plant growth and crop yields, especially in the loess areas with high crop productivity having annual precipitation lower than 500 mm. This paper summarizes the results of the first phase of the GLOWA (GLObal WAter)-Elbe project and tries to assess the reliability of water supply in the German part of the Elbe river basin for the next 50 years, a time scale relevant for the implementation of water and land use management plans. One focus of the study was developing scenarios which are consistent with climate and land use changes considering possible uncertainties. The concluding result of the study is that nature and communities in parts of Central Europe will have to deal with considerably lower water resources under scenario conditions.     

Continuous Hidden Markov Models: Application to automatic earthquake detection and classification at Las Canãdas caldera,Tenerife

A possible interaction of (volcano-) tectonic earthquakes with the continuous seismic noise recorded in the volcanic island of Tenerife was recently suggested. Also recently the zone close to Las Canadas caldera shows unusual high number of near (< 25 km), possibly volcano-tectonic, earthquakes indicating signs of reawakening of the volcano putting high pressure on the risk analyst. Certainly for both tasks consistent earthquake catalogues provide valuable information and thus there is a strong demand for automatic detection and classification methodologies generating such catalogues. Therefore we adopt methodologies of speech recognition where statistical models, called Hidden Markov Models (HMMs), are widely used for spotting words in continuous audio data. In this study HMMs are used to detect and classify volcano-tectonic and/or tectonic earthquakes in continuous seismic data. Further the HMM detection and classification is evaluated and discussed for a one month period of continuous seismic data at a single seismic station. Being a stochastic process, HMMs provide the possibility to add a confidence measure to each classification made, basically evaluating how “sure” the algorithm is when classifying a certain earthquake. Moreover, this provides helpful information for the seismological analyst when cataloguing earthquakes. Combined with the confidence measure the HMM detection and classification can provide precise enough earthquake statistics, both for further evidence on the interaction between seismic noise and (volcano-) tectonic earthquakes as well as for incorporation in an automatic early warning system.     

Numerical Modeling of Methane Leakage from a Faulty Natural Gas Well into Fractured Tight Formations

Horizontal drilling and hydraulic fracturing have enabled hydrocarbon recovery from unconventional reservoirs, but led to natural gas contamination of shallow groundwaters. We describe and apply numerical models of gas‐phase migration associated with leaking natural gas wells. Three leakage scenarios are simulated: (1) high‐pressure natural gas pulse released into a fractured aquifer; (2) continuous slow leakage into a tilted fractured formation; and (3) continuous slow leakage into an unfractured aquifer with fluvial channels, to facilitate a generalized evaluation of natural gas transport from faulty natural gas wells. High‐pressure pulses of gas leakage into sparsely fractured media are needed to produce the extensive and rapid lateral spreading of free gas previously observed in field studies. Transport in fractures explains how methane can travel vastly different distances and directions laterally away from a leaking well, which leads to variable levels of methane contamination in nearby groundwater wells. Lower rates of methane leakage (≤1 Mcf/day) produce shorter length scales of gas transport than determined by the high‐pressure scenario or field studies, unless aquifers have low vertical permeabilities (≤1 millidarcy) and fractures and bedding planes have sufficient tilt (～10°) to allow a lateral buoyancy component. Similarly, in fractured rock aquifers or where permeability is controlled by channelized fluvial deposits, lateral flow is not sufficiently developed to explain fast‐developing gas contamination (0‐3 months) or large length scales (～1 km) documented in field studies. Thus, current efforts to evaluate the frequency, mechanism, and impacts of natural gas leakage from faulty natural gas wells likely underestimate contributions from small‐volume, low‐pressure leakage events.     

Locating wind farms by seismic interferometry and migration

We present a case study on the detection and quantification of seismic signals induced by operating wind turbines (WTs). We spatially locate the sources of such signals in data which were recorded at 11 seismic stations in 2011 and 2012 during the TIMO project (Deep Structure of the Central Upper Rhine Graben). During this time period, four wind farms with altogether 12 WTs were in operation near the town of Landau, Southwest Germany. We locate WTs as sources of continuous seismic signals by application of seismic interferometry and migration of the energy found in cross-correlograms. A clear increase of emitted seismic energy with rotor speed confirms that the observed signal is induced by WTs. We can clearly distinguish wind farms consisting of different types of WTs (different hub height and rotor diameter) corresponding to different stable frequency bands (1.3–1.6 Hz, 1.75–1.95 Hz and 2.0–2.2 Hz) which do not depend on wind speed. The peak frequency apparently is controlled by the elastic eigenmodes of the structure rather than the passing of blades at the tower. From this we conclude that vibrations are coupled into the ground at the foundation and propagate as Rayleigh waves (and not as infrasound). The migration velocity of 320 m/s corresponds to their group velocity. The applied migration method can contribute to the assessment of local sources of seismic noise. This topic gets growing attention in the seismological community. In particular, the recent boost of newly installed wind farms is a threat to seismological observatories such as the Black Forest Observatory (BFO) and the Gräfenberg array (GRF) or gravitational wave observatories (e.g. LIGO, VIRGO) in terms of a sensitivity degradation of such observatories.