Volcano eruption forecast remains a challenging and controversial problem despite the fact that data from volcano monitoring significantly increased in quantity and quality during the last decades. ...This study uses pattern recognition techniques to quantify the predictability of the 15 Piton de la Fournaise (PdlF) eruptions in the 1988–2001 period using increase of the daily seismicity rate as a precursor. Lead time of this prediction is a few days to weeks. We formulate a simple prediction rule, use it for retrospective prediction of the 15 eruptions, and test the prediction quality with error diagrams. The best prediction performance corresponds to averaging the daily seismicity rate over 5 days and issuing a prediction alarm for 5 days. 65% of the eruptions are predicted for an alarm duration less than 20% of the time considered. Even though this result is concomitant of a large number of false alarms, it is obtained with a crude counting of daily events that are available from most volcano observatories.
Entropy and optimality in river deltas Tejedor, Alejandro; Longjas, Anthony; Edmonds, Douglas A. ...
Proceedings of the National Academy of Sciences,
10/2017, Letnik:
114, Številka:
44
Journal Article
Recenzirano
Odprti dostop
The form and function of river deltas is intricately linked to the evolving structure of their channel networks, which controls how effectively deltas are nourished with sediments and nutrients. ...Understanding the coevolution of deltaic channels and their flux organization is crucial for guiding maintenance strategies of these highly stressed systems from a range of anthropogenic activities. To date, however, a unified theory explaining how deltas self-organize to distribute water and sediment up to the shoreline remains elusive. Here, we provide evidence for an optimality principle underlying the self-organized partition of fluxes in delta channel networks. By introducing a suitable nonlocal entropy rate (nER) and by analyzing field and simulated deltas, we suggest that delta networks achieve configurations that maximize the diversity of water and sediment flux delivery to the shoreline. We thus suggest that prograding deltas attain dynamically accessible optima of flux distributions on their channel network topologies, thus effectively decoupling evolutionary time scales of geomorphology and hydrology. When interpreted in terms of delta resilience, high nER configurations reflect an increased ability to withstand perturbations. However, the distributive mechanism responsible for both diversifying flux delivery to the shoreline and dampening possible perturbations might lead to catastrophic events when those perturbations exceed certain intensity thresholds.
Quantifying regional earthquake cluster style is essential for providing a context for studies of seismicity patterns and earthquake interactions. Here, we identify clusters of seismicity in the Sea ...of Marmara region of the North Anatolian Fault, NW Turkey, using a recently derived high-resolution seismicity catalog and the nearest-neighbor earthquake cluster approach. The detected earthquake clusters are utilized for (1) determining spatial distribution of mainshock and aftershock rates and estimating the proximity to failure on different fault segments, (2) identifying fault sections having earthquake repeaters, and (3) finding areas with enhanced foreshock activity. About 6%, 70% and 24% of the events are identified as foreshocks, mainshocks and aftershocks, respectively, with the largest concentration of aftershocks and foreshocks located along the Western High and the Cinarcik Fault, respectively. The method successfully identifies regions where previous studies reported earthquake repeaters as indicator for fault creep and suggests additional repeater areas in the Gulf of Gemlik. The largest proportion of mainshocks with associated foreshocks and aftershocks are along the Western High and Cinarcik Fault segments, potentially indicating that these segments are closer to failure and have increased susceptibility to seismic triggering. Continuing studies can contribute to monitoring possible preparation phase of a large (M > 7) earthquake in the Marmara region near the Istanbul Metropolitan region.
•Proportions of foreshocks, mainshocks and aftershocks along the Sea of Marmara region are about 6%, 70% and 24%, respectively•Selected cluster statistics successfully identifies creeping regions where earthquake repeaters have been observed•Western High and Cinarcik segments display largest proportion of families, suggesting higher susceptibility of triggering
Understanding how thermokarst lakes on arctic river deltas will respond to rapid warming is critical for projecting how carbon storage and fluxes will change in those vulnerable environments. Yet, ...this understanding is currently limited partly due to the complexity of disentangling significant interannual variability from the longer‐term surface water signatures on the landscape, using the short summertime window of optical spaceborne observations. Here, we rigorously separate perennial lakes from ephemeral wetlands on 12 arctic deltas and report distinct size distributions and climate trends for the two waterbodies. Namely, we find a lognormal distribution for lakes and a power‐law distribution for wetlands, consistent with a simple proportionate growth model and inundated topography, respectively. Furthermore, while no trend with temperature is found for wetlands, a statistically significant decreasing trend of mean lake size with warmer temperatures is found, attributed to colder deltas having deeper and thicker permafrost preserving larger lakes.
Plain Language Summary
Arctic river deltas are landscapes facing significant risk from climate change, in part due to their unique permafrost features. In particular, thermokarst lakes in ice‐rich permafrost are expected to both expand and drain under warming‐induced permafrost thaw, reconfiguring deltaic hydrology and impacting the arctic carbon cycle. A limitation in understanding how thermokarst lake cover might be changing is the significant interannual variability in water cover in flat regions such as deltas, which makes it difficult to distinguish between perennially inundated, thermally relevant waterbodies, and ephemerally inundated waterbodies. Here, we present a pan‐Arctic study of 12 arctic deltas wherein we classify observed waterbodies into perennial lakes and ephemeral wetlands capitalizing on the historical record of remote sensing data. We provide evidence that thermokarst lake sizes are universally lognormally distributed and that historical temperature trends are encoded in lake sizes, while wetland sizes are power law distributed and have no temperature trend. These findings pave the way for quantitative insight into lake cover changes on arctic deltas and associated carbon and hydrologic cycle impacts under future climate change.
Key Points
Lake areas in arctic deltas exhibit a lognormal distribution associated with a simple mechanistic growth process
Wetland areas exhibit a power law distribution consistent with inundated topography
Colder arctic deltas have larger average lake sizes, likely due to thicker permafrost restricting sub‐lake hydrologic connectivity
Deltas contain complex self‐organizing channel networks that nourish the surface with sediment and nutrients. Developing a quantitative understanding of how controlling physical mechanisms of delta ...formation relate to the channel networks they imprint on the landscape remains an open problem, hindering further progress on quantitative delta classification and understanding process from form. Here we isolate the effect of sediment composition on network structure by analyzing Delft3D river‐dominated deltas within the recently introduced graph‐theoretic framework for quantifying complexity of delta channel networks. We demonstrate that deltas with coarser incoming sediment tend to be more complex topologically (increased number of pathways) but simpler dynamically (reduced flux exchange between subnetworks) and that once a morphodynamic steady state is reached, complexity also achieves a steady state. By positioning simulated deltas on the so‐called TopoDynamic complexity space and comparing with field deltas, we propose a quantitative framework for exploring complexity toward systematic inference and classification.
Key Points
Sediment composition leaves a distinct signature on delta channel network complexity
As deltas evolve and reach steady state, complexity also achieves steady state
A TopoDynamic complexity space offers potential for process inference and delta classification
Boolean Delay Equations (BDEs) are semi-discrete dynamical models with Boolean-valued variables that evolve in continuous time. Systems of BDEs can be classified into
conservative or
dissipative, in ...a manner that parallels the classification of ordinary or partial differential equations. Solutions to certain conservative BDEs exhibit growth of complexity in time; such BDEs can be seen therefore as metaphors for biological evolution or human history. Dissipative BDEs are structurally stable and exhibit multiple equilibria and limit cycles, as well as more complex, fractal solution sets, such as Devil’s staircases and “fractal sunbursts.” All known solutions of dissipative BDEs have stationary variance. BDE systems of this type, both free and forced, have been used as highly idealized models of climate change on interannual, interdecadal and paleoclimatic time scales. BDEs are also being used as flexible, highly efficient models of colliding cascades of loading and failure in earthquake modeling and prediction, as well as in genetics. In this paper we review the theory of systems of BDEs and illustrate their applications to climatic and solid-earth problems. The former have used small systems of BDEs, while the latter have used large hierarchical networks of BDEs. We moreover introduce BDEs with an infinite number of variables distributed in space (“partial BDEs”) and discuss connections with other types of discrete dynamical systems, including cellular automata and Boolean networks. This research-and-review paper concludes with a set of open questions.
This study is motivated by problems related to environmental transport on river networks. We establish statistical properties of a flow along a directed branching network and suggest its compact ...parameterization. The downstream network transport is treated as a particular case of nearest neighbor hierarchical aggregation with respect to the metric induced by the branching structure of the river network. We describe the static geometric structure of a drainage network by a tree, referred to as the static tree, and introduce an associated dynamic tree that describes the transport along the static tree. It is well known that the static branching structure of river networks can be described by self‐similar trees; we demonstrate that the corresponding dynamic trees are also self‐similar, albeit with different self‐similarity parameters. We report an unexpected phase transition in the dynamics of three river networks (one from California and two from Italy), demonstrate the universal features of this transition, and seek to interpret it in hydrological terms.
We use GPS data to show synchronization between the 2011 and 2016 drought cycle in California, accelerated uplift of the Sierra Nevada Mountains, and enhanced magmatic inflation of the Long Valley ...Caldera (LVC) magmatic system. The drought period coincided with faster uplift rate, changes in gravity seen in the Gravity Recovery and Climate Experiment (GRACE), and changes in standardized relative climate dryness index. These observations together suggest that the Sierra Nevada elevation is sensitive to changes in hydrological loading conditions, which subsequently influences the LVC magmatic system. We use robust imaging of horizontal GPS velocities to derive time‐variable shear and dilatational strain rates in a region with highly variable station distribution. The results show that the highest strain rates are near the eastern margin of the Sierra Nevada and western edge of the Central Walker Lane (CWL) passing directly through LVC. The drought period saw geographic shifts in the distribution in active shear strain in the CWL more than 60 km from the LVC, delineating the minimum extent over which the active magmatic system affects the CWL tectonic environment. We analyze declustered seismicity data to show that locations with higher seismicity rates tend to be (1) areas with higher strain rates and (2) areas in which strain rates increased during drought‐enhanced inflation. We hypothesize that drought conditions reduce vertical surface mass loading, which decreases pressure at depth in the LVC system, in turn enhances magmatic inflation, and drives horizontal elastic stress changes that redistribute active CWL strain and modulate seismicity.
Plain Language Summary
We show that there were connections between the recent drought in California to changes in uplift rate of the Sierra Nevada, magmatic inflation at the Long Valley Caldera near Mammoth, CA, and earthquakes in the region. We use GPS, seismic, gravity, and climate data to show that the speed of uplift of the Sierra Nevada is sensitive to big changes in surface and groundwater (e.g., in snow, streams, lakes, and aquifers) and that these changes correlate with movements within the large volcano. A plausible explanation is that the weight of snow and water loads the surface and changes pressures deep in the Earth. As the Sierra Nevada was unloaded during recent drought, there was less pressure on the magmatic system, allowing fluids to rise or expand more easily. When that occurred, it provided an outward horizontal push on the crust, influencing small‐ to moderate‐sized earthquakes up to 60 km away. We show where and when these changes occurred and specific examples of earthquakes that may have been triggered by this inflation.
Key Points
Faster Sierra Nevada uplift during the 2011–2016 drought in California coincided with faster magmatic inflation at the Long Valley Caldera
Faster magmatic inflation changed the rate and distribution of crustal strain in the Central Walker Lane, >60 km from Long Valley
Seismicity patterns in the Central Walker Lane suggest that long‐term crustal strain may be driven in part by Long Valley magmatic inflation
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