Seasonal drought predictability in Portugal using statistical–dynamical techniques

Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical–dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R² and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.     

A numerical predicting method on monthly seismic tendency

IntroductionEarthquakepredictionisanundertakingofpublicwelfare,butearthquakecannotbesuccessfullypredictedatthepresentstageduetotechnologicalreasons.Howtoadaptthepresentsituationofearthquakepredictiontotheneedofsocietyisasubjectthatshouldbestudiedearnestly.Logicallyspeaking,themostimportantproblemindisasterpreventionisthemagnitudeofthecomingearthquake(becauseitconcernstherangeandinvestmentforprevention);Thesecondproblemisthemostdangerousseismiczone(becauseitconcernstheconcretearrangementforprev…     

A new method for precursory information extraction: Slope-difference information method

IntroductionSignificant progress has been made in the application of crustal deformation data to the intermediate and long-term earthquake prediction, seismicity situation judgment and the intermediate-term prediction, but the application to the intermediate and short-term earthquake prediction and research is difficult. This is because the crustal deformation data are not stable and contain strong intermediate and long-term deformational and disturbing signals, annual deformation signals and …     

A Bayesian method for missing rainfall estimation using a conceptual rainfall–runoff model

The estimation of missing rainfall data is an important problem for data analysis and modelling studies in hydrology. This paper develops a Bayesian method to address missing rainfall estimation from runoff measurements based on a pre-calibrated conceptual rainfall–runoff model. The Bayesian method assigns posterior probability of rainfall estimates proportional to the likelihood function of measured runoff flows and prior rainfall information, which is presented by uniform distributions in the absence of rainfall data. The likelihood function of measured runoff can be determined via the test of different residual error models in the calibration phase. The application of this method to a French urban catchment indicates that the proposed Bayesian method is able to assess missing rainfall and its uncertainty based only on runoff measurements, which provides an alternative to the reverse model for missing rainfall estimates.     

P–PINI: A cosmogenic nuclide burial dating method for landscapes undergoing non-steady erosion

Existing methods of cosmogenic nuclide burial dating perform well provided that sediment sources undergo steady rates of erosion and the samples experience continuous exposure to cosmic rays. These premises exert important limitations on the applicability of the methods. And yet, high mountain sediment sources are rife with transient processes, such as non-steady erosion by glacial quarrying and/or landsliding, or temporary cosmic-ray shielding beneath glaciers and/or sediment. As well as breaching the premises of existing burial dating methods, such processes yield samples with low nuclide abundances and variable ²⁶Al/¹⁰Be ratios that may foil both isochron and simple burial-age solutions. P–PINI (Particle-Pathway Inversion of Nuclide Inventories) is a new dating tool designed for dating the burial of sediments sourced from landscapes characterized by abrupt, non-steady erosion, discontinuous exposure, and catchments with elevation-dependent ²⁶Al/¹⁰Be production ratios. P–PINI merges a Monte Carlo simulator with established cosmogenic nuclide production equations to simulate millions of samples (¹⁰Be–²⁶Al inventories). The simulated samples are compared statistically with ¹⁰Be–²⁶Al measured in field samples to define the most probable burial age. Here, we target three published ¹⁰Be–²⁶Al datasets to demonstrate the versatility of the P–PINI model for dating fluvial and glacial sediments. (1) The first case serves as a robust validation of P–PINI. For the Pulu fluvial gravels (China), we obtain a burial age of 1.27 ± 0.10 Ma (1σ), which accords with the isochron burial age and two independent chronometers reported in Zhao et al. (2016) Quaternary Geochronology 34, 75–80. The second and third cases, however, reveal marked divergence between P–PINI and isochron-derived ages. (2) For the fluvial Nenana Gravel (USA), we obtain a minimum-limiting burial age of 4.5 ± 0.7 Ma (1σ), which is compatible with unroofing of the Alaska Range starting ∼ 6 Ma, while calling into question the Early Pleistocene isochron burial age presented in Sortor et al. (2021) Geology 49, 1473–1477. (3) For the Bünten Till (Switzerland), we obtain a limiting burial age of <204 ka (95th percentile range), which conforms with the classical notion of the most extensive glaciation in the northern Alpine Foreland assigned to the Riss glaciation (sensu marine isotope stage 6) contrary to the isochron burial age presented in Dieleman et al. (2022) Geosciences, 12, 39. Discrepancies between P–PINI and the isochron ages are rooted in the challenges posed by the diverse pre-burial ²⁶Al/¹⁰Be ratios produced under conditions characteristic of high mountain landscapes; i.e., non-steady erosion, discontinuous cosmic-ray exposure, and elevation-dependent ²⁶Al/¹⁰Be production ratios in the source region, which are incompatible with the isochron method, but easily accommodated by the stochastic design of P–PINI.     

A new method of migration imaging for MT data

Introduction The migrationof electromagnetic field is like that of elastic wave in seismic prospecting, butthere are some differences between them (Lee et al, 1989). The elastic wave field satisfies thegeneral wave equation, while the electromagnetic field in our study satisfies the diffusion equation.Both the electromagnetic field and the elastic wave field have a similar mechanism. The imagingfunction named map can characterize the interface of different mediums (MA, 1989), that is …     

A new method for dynamic inversion of anisotropic equations

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A new method for spatio-temporal prediction of rainfall-induced landslide

1 Introduction The landslides influences on the human society have become an environment difficult problem not able to be neglected, and according to the priority of harms, harms of landslides are only smaller than those from earthquakes in all sorts of natural hazards[1]. Landslide is part of rock mass, soil mass or their compound mass slides downward along a certain slid- ing surface under the actions of inner and external dy- namics, and it is one severe instability phenomenon of rock and s…     

A new method for earthquake prediction by earth-resistivity measurements

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A process-based,distributed hydrologic model based on a large-scale method for surface–subsurface coupling

Process-based watershed models are useful tools for understanding the impacts of natural and anthropogenic influences on water resources and for predicting water and solute fluxes exported from watersheds to receiving water bodies. The applicability of process-based hydrologic models has been previously limited to small catchments and short time frames. Computational demands, especially the solution to the three-dimensional subsurface flow domain, continue to pose significant constraints. This paper documents the mathematical development, numerical testing and the initial application of a new distributed hydrologic model PAWS (Process-based Adaptive Watershed Simulator). The model solves the governing equations for the major hydrologic processes efficiently so that large scale applications become relevant. PAWS evaluates the integrated hydrologic response of the surface–subsurface system using a novel non-iterative method that couples runoff and groundwater flow to vadose zone processes approximating the 3D Richards equation. The method is computationally efficient and produces physically consistent solutions. All flow components have been independently verified using analytical solutions and experimental data where applicable. The model is applied to a medium-sized watershed in Michigan (1169 km²) achieving high performance metrics in terms of streamflow prediction at two gages during the calibration and verification periods. PAWS uses public databases as input and possesses full capability to interact with GIS datasets. Future papers will describe applications to other watersheds and the development and application of fate and transport modules.     

Geostatistical radar–raingauge merging: A novel method for the quantification of rain estimation accuracy

Compared to other estimation techniques, one advantage of geostatistical techniques is that they provide an index of the estimation accuracy of the variable of interest with the kriging estimation standard deviation (ESD). In the context of radar–raingauge quantitative precipitation estimation (QPE), we address in this article the question of how the kriging ESD can be transformed into a local spread of error by using the dependency of radar errors to the rain amount analyzed in previous work. The proposed approach is implemented for the most significant rain events observed in 2008 in the Cévennes-Vivarais region, France, by considering both the kriging with external drift (KED) and the ordinary kriging (OK) methods. A two-step procedure is implemented for estimating the rain estimation accuracy: (i) first kriging normalized ESDs are computed by using normalized variograms (sill equal to 1) to account for the observation system configuration and the spatial structure of the variable of interest (rainfall amount, residuals to the drift); (ii) based on the assumption of a linear relationship between the standard deviation and the mean of the variable of interest, a denormalization of the kriging ESDs is performed globally for a given rain event by using a cross-validation procedure. Despite the fact that the KED normalized ESDs are usually greater than the OK ones (due to an additional constraint in the kriging system and a weaker spatial structure of the residuals to the drift), the KED denormalized ESDs are generally smaller the OK ones, a result consistent with the better performance observed for the KED technique. The evolution of the mean and the standard deviation of the rainfall-scaled ESDs over a range of spatial (5–300 km²) and temporal (1–6 h) scales demonstrates that there is clear added value of the radar with respect to the raingauge network for the shortest scales, which are those of interest for flash-flood prediction in the considered region.     

A statistical study of nightside inverted-V events using Freja electron data: implications for the current–voltage relationship

We study a set of 47 nightside inverted-V events using the Freja F7 (Two-dimensional Electron Spectrometer; TESP) electron detector. For each data point, we determine the peak potential, the source plasma density and temperature, and the field-aligned current density. We show that the temperature and peak potential are correlated, which is in line with previous studies: the temperature is on the average 3.3 times smaller than eV, where V is the peak potential. On the contrary, the current density is statistically quite independent of the potential. Thus, based on Freja F7 data, the observational current–voltage relationship is that the current is constant with respect to the voltage in an average sense. The formation of a parallel electric field, represented by the voltage, is more related to the source plasma density and temperature and density than the current. Our results concern energies up to 8.7 keV.     

A statistical study of magnetosphere–ionosphere coupling in the Lyon–Fedder–Mobarry global MHD model

The statistics of magnetosphere–ionosphere (MI) coupling derived from a two-month long run of the Lyon–Fedder–Mobarry (LFM) global simulation model are investigated. MI coupling characteristics such as polar cap potential and field-aligned current (FAC), downward Poynting flux and vorticity of ionospheric convection are compared with observed statistical averages and with results from the Weimer 05 empirical model. The comparisons for eight different IMF clock-angle orientations show that the LFM model produces reasonably accurate average distributions of the Region I and Region II currents. Both current systems have average amplitudes similar to those observed by the Iridium satellite constellation; however, the average LFM amplitudes are smaller by a factor of two compared with the values from the Weimer 05 model. The comparisons of polar cap potential show that the LFM model produces reasonable patterns of ionospheric convection, but the average cross polar cap potential (CPCP) is greater than the observed results by a factor of approximately 2 and greater than Weimer 05 by a factor of 1.5. The differences in convection in LFM results relative to the Weimer 05 model accounts for much of the difference in the Poynting flux patterns and integrated power produced by the two models. The comparisons of average ionospheric field-aligned vorticity show good agreement on the dayside; however, the LFM model gives higher nightside vorticity which may imply that the ionospheric conductance on the nightside is too small in the simulation.     

A method for visualizing sound propagation in solids and liquids

Introduction When seismic waves propagate in a medium of complex geometry,such as a dam,it pro-duces stress concentration area at some spots of the dam because of the interface reflection and refraction of the waves,resulting in serious safety risk.Understanding seismic wave propagation in complex mediums becomes very important.In order to reduce the damage from natural earth-quakes,precaution measures should be designed on the basis of the seismic propagation charac-teristics.Experimental geo…     

A flux-limiting wetting–drying method for finite-element shallow-water models,with application to the Scheldt Estuary

We present a flux-limiting wetting–drying approach for finite-element discretizations of the shallow-water equations using discontinuous linear elements for the elevation. The key ingredient of the method is the use of limiters for generalized nodal fluxes. This method is implemented into the Second-generation Louvain-la-Neuve Ice-ocean Model (SLIM), and is verified against standard test cases. The method is further applied to the wetting and drying of sand banks in the Scheldt Estuary, which is located in northern Belgium and the southern Netherlands. The results obtained for both the benchmarks and the realistic problem illustrate the accuracy of the method in describing the hydrodynamics in the vicinity of dry areas. In particular, the method strictly conserves mass, and there is no transport through dry areas.     

A new method for establishing hydrologic fidelity of snow depth measurements based on snowmelt–runoff hydrographs

For snowmelt-driven flood studies, snow water equivalent (SWE) is frequently estimated using snow depth data. Accurate measurements of snow depth are important in providing data for continuous hydrologic simulations of such watersheds. A new hydrologic fidelity metric is proposed in this study to evaluate the potential contribution of particular snow depth datasets to flow characteristics using observed data and hydrologic modeling using the Variable Infiltration Capacity (VIC) model. Data-based hydrologic fidelity of snow depth measurements is defined as a categorical skill score between the snow depth in the watershed and the hydrograph peak or volume at the watershed outlet. Similarly, model-based hydrologic fidelity is defined as a categorical skill score between the model-simulated snow depth and the model-simulated hydrograph peak or volume. The proposed framework is illustrated using the Pecatonica River watershed in the USA, indicating which sites have a higher hydrologic fidelity, which is preferred in hydrologic studies.     

Homotopy perturbation method for solving the space–time fractional advection–dispersion equation

In this paper we present a reliable algorithm, the homotopy perturbation method, to construct numerical solutions of the space–time fractional advection–dispersion equation in the form of a rapidly convergent series with easily computable components. Fractional advection–dispersion equations are used in groundwater hydrology to model the transport of passive tracers carried by fluid flow in a porous medium. The fractional derivatives are described in the Caputo sense. Some examples are given. Numerical results show that the homotopy perturbation method is easy to implement and accurate when applied to space–time fractional advection–dispersion equations.     

A method for evaluating the longitudinal functional connectivity of a river–lake–marsh system and its application in China

The longitudinal functional connectivity of a river–lake–marsh system (RLMS) refers to the actual water-mediated transport of material from upstream to downstream areas along a spatial gradient and is fundamental to understand hydrological and biogeochemical cycles. However, due to a lack of consensus on appropriate data and methods, the quantification of connectivity is still a challenge, especially at the catchment scale. We developed a new method to evaluate longitudinal functional connectivity based on fluxes of materials (water, sediment, and chemicals) along a RLMS. The calculation of fluxes is based on the longitudinal pattern of terrain gradient, which influences transport efficiency, and on contributions from hillslopes, which set the initial spatial template of material loading to the RLMS. We evaluate the contributions from hillslopes to RLMS based on a new modified version of the index of sediment connectivity (IC) proposed by Borselli et al. (2008) and revised by Chartin et al. (2017).We applied this method to the Baiyangdian Basin covering an area of 3.4 × 10⁴ km² in China and quantified longitudinal functional connectivity during normal, wet, and dry periods(April, July and December) in year 2016. We found that areas with good structural connectivity exhibited poor functional connectivity during the normal and dry periods. Modelling testing with discharge data from hydrological stations and measured chemicals from Baiyangdian Lake was satisfactory in test periods. We conclude that public data and Digital Elevation Model-derived information can be used to reliably map the longitudinal functional connectivity of RLMSs. The proposed method provides a useful tool for monitoring and restoring the longitudinal functional connectivity of RLMSs and our results indicate that efforts aimed at restoring functional connectivity in RLMSs should take into account landscape patterns that can greatly influence fluxes in the watershed.     

A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface tem-perature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM,the difference of different frequen-cies can eliminate the influence of water in soil and atmosphere,and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately,the land surface should be at least classified into three types:water covered surface,snow covered surface,and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm,we built different equations for different ranges of temperature. The average land surface temperature er-ror is about 2―3℃ relative to the MODIS LST product.     

A comprehensive study method for lifeline system interaction under seismic conditions

Introduction The lifeline interaction is the mutual effect between a lifeline system and other lifelinesystems in the same district under seismic conditions. In other words, the reliability of a lifelinesystem, in addition to system oneself earthquake resistant performance, still depends on the reliability of other lifeline system which have functional connections or physical proximity with the lifeline system. For example, the function of water supply system also relies on the function of pow…