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Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of-and the interaction between-climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry C-14-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 C-14 dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity-whether driven by reduced resource abundance or increased competition-can lead to violence in subsistence societies when the outcome is lower per capita resource availability.
Fast-localized electron loss, resulting from interactions with electromagnetic ion cyclotron (EMIC) waves, can produce deepening minima in phase space density (PSD) radial profiles. Here, we perform a statistical analysis of local PSD minima to quantify how readily these are associated with radiation belt depletions. The statistics of PSD minima observed over a year are compared to the Versatile Electron Radiation Belts (VERB) simulations, both including and excluding EMIC waves. The observed minima distribution can only be achieved in the simulation including EMIC waves, indicating their importance in the dynamics of the radiation belts. By analyzing electron flux depletions in conjunction with the observed PSD minima, we show that, in the heart of the outer radiation belt (L* < 5), on average, 53% of multi-MeV electron depletions are associated with PSD minima, demonstrating that fast localized loss by interactions with EMIC waves are a common and crucial process for ultra-relativistic electron populations.
Improving nitrogen (N) status in European water bodies is a pressing issue. N levels depend not only on current but also past N inputs to the landscape, that have accumulated through time in legacy stores (e.g., soil, groundwater).
Catchment-scale N models, that are commonly used to investigate in-stream N levels, rarely examine the magnitude and dynamics of legacy components.
This study aims to gain a better understanding of the long-term fate of the N inputs and its uncertainties, using a legacy-driven N model (ELEMeNT) in Germany's largest national river basin (Weser; 38,450 km(2)) over the period 1960-2015.
We estimate the nine model parameters based on a progressive constraining strategy, to assess the value of different observational data sets.
We demonstrate that beyond in-stream N loading, soil N content and in-stream N concentration allow to reduce the equifinality in model parameterizations.
We find that more than 50% of the N surplus denitrifies (1480-2210 kg ha(-1)) and the stream export amounts to around 18% (410-640 kg ha(-1)), leaving behind as much as around 230-780 kg ha(-1) of N in the (soil) source zone and 10-105 kg ha(-1) in the subsurface.
A sensitivity analysis reveals the importance of different factors affecting the residual uncertainties in simulated N legacies, namely hydrologic travel time, denitrification rates, a coefficient characterizing the protection of organic N in source zone and N surplus input.
Our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce the equifinality in water quality modeling.
Megathrust earthquakes impose changes of differential stress and pore pressure in the lithosphere-asthenosphere system that are transiently relaxed during the postseismic period primarily due to afterslip, viscoelastic and poroelastic processes.
Especially during the early postseismic phase, however, the relative contribution of these processes to the observed surface deformation is unclear.
To investigate this, we use geodetic data collected in the first 48 days following the 2010 Maule earthquake and a poro-viscoelastic forward model combined with an afterslip inversion.
This model approach fits the geodetic data 14% better than a pure elastic model. Particularly near the region of maximum coseismic slip, the predicted surface poroelastic uplift pattern explains well the observations.
If poroelasticity is neglected, the spatial afterslip distribution is locally altered by up to +/- 40%.
Moreover, we find that shallow crustal aftershocks mostly occur in regions of increased postseismic pore-pressure changes, indicating that both processes might be mechanically coupled.
On their way from inland to the ocean, flowing water bodies, their constituents and their biotic communities are ex-posed to complex transport and transformation processes. However, detailed process knowledge as revealed by La-grangian measurements adjusted to travel time is rare in large rivers, in particular at hydrological extremes. To fill this gap, we investigated autotrophic processes, heterotrophic carbon utilization, and micropollutant concentrations applying a Lagrangian sampling design in a 600 km section of the River Elbe (Germany) at historically low discharge. Under base flow conditions, we expect the maximum intensity of instream processes and of point source impacts. Phy-toplankton biomass and photosynthesis increased from upstream to downstream sites but maximum chlorophyll con-centration was lower than at mean discharge. Concentrations of dissolved macronutrients decreased to almost complete phosphate depletion and low nitrate values. The longitudinal increase of bacterial abundance and production was less pronounced than in wetter years and bacterial community composition changed downstream. Molecular analyses revealed a longitudinal increase of many DOM components due to microbial production, whereas saturated lipid-like DOM, unsaturated aromatics and polyphenols, and some CHOS surfactants declined. In decomposition exper-iments, DOM components with high O/C ratios and high masses decreased whereas those with low O/C ratios, low masses, and high nitrogen content increased at all sites. Radiocarbon age analyses showed that DOC was relatively old (890-1870 years B.P.), whereas the mineralized fraction was much younger suggesting predominant oxidation of algal lysis products and exudates particularly at downstream sites. Micropollutants determining toxicity for algae (terbuthylazine, terbutryn, isoproturon and lenacil), hexachlorocyclohexanes and DDTs showed higher concentrations from the middle towards the downstream part but calculated toxicity was not negatively correlated to phytoplankton. Overall, autotrophic and heterotrophic process rates and micropollutant concentrations increased from up-to down-stream reaches, but their magnitudes were not distinctly different to conditions at medium discharges.
Boreal forests cover over half of the global permafrost area and protect underlying permafrost. Boreal forest development, therefore, has an impact on permafrost evolution, especially under a warming climate.
Forest disturbances and changing climate conditions cause vegetation shifts and potentially destabilize the carbon stored within the vegetation and permafrost. Disturbed permafrost-forest ecosystems can develop into a dry or swampy bush- or grasslands, shift toward broadleaf- or evergreen needleleaf-dominated forests, or recover to the pre-disturbance state.
An increase in the number and intensity of fires, as well as intensified logging activities, could lead to a partial or complete ecosystem and permafrost degradation. We study the impact of forest disturbances (logging, surface, and canopy fires) on the thermal and hydrological permafrost conditions and ecosystem resilience.
We use a dynamic multilayer canopy-permafrost model to simulate different scenarios at a study site in eastern Siberia. We implement expected mortality, defoliation, and ground surface changes and analyze the interplay between forest recovery and permafrost. We find that forest loss induces soil drying of up to 44%, leading to lower active layer thicknesses and abrupt or steady decline of a larch forest, depending on disturbance intensity.
Only after surface fires, the most common disturbances, inducing low mortality rates, forests can recover and overpass pre-disturbance leaf area index values. We find that the trajectory of larch forests after surface fires is dependent on the precipitation conditions in the years after the disturbance. Dryer years can drastically change the direction of the larch forest development within the studied period.
Measuring the variability of incoming neutrons locally would be usefull for the cosmic-ray neutron sensing (CRNS) method. As the measurement of high energy neutrons is not so easy, alternative particles can be considered for such purpose. Among them, muons are particles created from the same cascade of primary cosmic-ray fluxes that generate neutrons at the ground. In addition, they can be easily detected by small and relatively inexpensive detectors. For these reasons they could provide a suitable local alternative to incoming corrections based on remote neutron monitor data. The reported measurements demonstrated that muon detection system can detect incoming cosmic-ray variations locally. Furthermore the precision of this measurement technique is considered adequate for many CRNS applications.
A large landslide (frozen debris avalanche) occurred at Assapaat on the south coast of the Nuussuaq Peninsula in Central West Greenland on June 13, 2021, at 04:04 local time. We present a compilation of available data from field observations, photos, remote sensing, and seismic monitoring to describe the event. Analysis of these data in combination with an analysis of pre- and post-failure digital elevation models results in the first description of this type of landslide. The frozen debris avalanche initiated as a 6.9 * 10(6) m(3) failure of permafrozen talus slope and underlying colluvium and till at 600-880 m elevation. It entrained a large volume of permafrozen colluvium along its 2.4 km path in two subsequent entrainment phases accumulating a total volume between 18.3 * 10(6) and 25.9 * 10(6) m(3). About 3.9 * 10(6) m(3) is estimated to have entered the Vaigat strait; however, no tsunami was reported, or is evident in the field. This is probably because the second stage of entrainment along with a flattening of slope angle reduced the mobility of the frozen debris avalanche. We hypothesise that the initial talus slope failure is dynamically conditioned by warming of the ice matrix that binds the permafrozen talus slope. When the slope ice temperature rises to a critical level, its shear resistance is reduced, resulting in an unstable talus slope prone to failure. Likewise, we attribute the large-scale entrainment to increasing slope temperature and take the frozen debris avalanche as a strong sign that the permafrost in this region is increasingly at a critical state. Global warming is enhanced in the Arctic and frequent landslide events in the past decade in Western Greenland let us hypothesise that continued warming will lead to an increase in the frequency and magnitude of these types of landslides. Essential data for critical arctic slopes such as precipitation, snowmelt, and ground and surface temperature are still missing to further test this hypothesis. It is thus strongly required that research funds are made available to better predict the change of landslide threat in the Arctic.
A novel idea for an optimal time delay state space reconstruction from uni- and multivariate time series is presented. The entire embedding process is considered as a game, in which each move corresponds to an embedding cycle and is subject to an evaluation through an objective function. This way the embedding procedure can be modeled as a tree, in which each leaf holds a specific value of the objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path, which ends at the leaf with the lowest achieved value of the objective function. The method aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way, enabling practitioners to choose a statistic for possible delays in each embedding cycle as well as a suitable objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. As a proof of concept, we demonstrate the superiority of the proposed method over the classical time delay embedding methods using a variety of application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. Finally, we utilize state space reconstruction for the detection of causality and its strength between observables of a gas turbine type thermoacoustic combustor.