Responding to the challenges of Water and Global Warming: Environmental Hydrogeology and Global Change Research Group (HYGLO-Lab)

[EN] The current Global Warming of planet Earth is probably the most important geological phenomenon in the last 20,000 years of its history and for human race. This process is having nowadays notable effects on the climate, ecosystems and natural resources. Possibly the most important renewable geological resource is water. One of the most strategic phases of the water cycle is groundwater. Despite its low visibility, quantitatively (and qualitatively too) it is essential for life on Planet Earth. Foreseeable consequences on groundwater due to climate change and sea level rise will be very significant. Hydrogeology can provide answers to many of the questions that are beginning to be raised in relation to these impacts and their effects. Environmental hydrogeology is a way of understanding the set of disciplines mixed in Hydrogeology as a Science of Nature. The HYGLO-Lab Research Group of the IGME-CSIC National Center attempts, through its lines of research, with a double global and local component, to provide answers to some of these questions.Peer reviewe

Comparison of inference methods for estimating semivariogram model parameters and their uncertainty: the case of small data sets

The semivariogram model is the fundamental component in all geostatistical applications and its inference is an issue of significant practical interest. The semivariogram model is defined by a mathematical function, the parameters of which are usually estimated from the experimental data. There are important application areas in which small data sets are the norm; rainfall estimation from rain gauge data and transmissivity estimation from pumping test data are two examples from, respectively, surface and subsurface hydrology. Thus a benchmark problem in geostatistics is deciding on the most appropriate method for the inference of the semivariogram model. The various methods for semivariogram inference can be classified as indirect methods, in which there is an intermediate step of calculating the experimental semivariogram, and direct approaches that obtain the model parameter values directly as the values that minimize some objective function. To avoid subjectivity in fitting models to experimental semivariograms, ordinary least squares (OLS), weighted least squares (WLS) and generalized least squares (GLS) are often used. Uncertainty evaluation in indirect methods is done using computationally intensive resampling procedures such as the bootstrap method. Direct methods include parametric methods, such as maximum likelihood (ML) and maximum likelihood cross-validation (MLCV), and non-parametric methods, such as minimization of cross-validation statistics (CV). The bases for comparing the previous methods are the sampling distribution of the various parameters and the “goodness” of the uncertainty evaluation in a sense that we define. The final questions to be answered are (1) which is the best method for estimating each of the semivariogram parameters? (2) Which is the best method for assessing the uncertainty of each of the parameters? (3) Which method best selects the functional form of the semivariogram from among a set of options? and (4) which is the best method that jointly addresses all the previous questions?Instituto Geológico y Minero de España, EspañaFaculty of Engineering, Computer & Mathematical Sciences, University of Adelaide, Australi

VARBOOT: a spatial bootstrap program for semivariogram uncertainty assessment

In applied geostatistics, the semivariogram is commonly estimated from experimental data, producing an empirical semivariogram for a specified number of discrete lags. In a second stage, a model defined by a few parameters is fitted to the empirical semivariogram. As the experimental data are usually few and sparsely located, there is considerable uncertainty about the calculated semivariogram values (uncertainty of the empirical semivariogram) and about the parameters of any model fitted to them (uncertainty of the estimated model parameters). In this paper, the uncertainty in the modeling of the empirical semivariogram is numerically assessed by the generalized bootstrap, which is an extension of the classic bootstrap procedure modified for spatially correlated data. A computer program is described and provided for the assessment of those uncertainties. In particular, the program provides for the empirical semivariogram: the standard errors, the bootstrap percentile confidence intervals, the complete variance–covariance matrix, standard deviation correlation matrix. A public domain, natural dataset is used to illustrate the performance of the program. A promising result is that, for any distance, the median of the bootstrap distribution for the empirical semivariogram approximates more closely the underlying semivariogram than the estimate derived from the empirical sampleInstituto Geológico y Minero de España, EspañaUnited States Geological Survey, Estados Unido

Geología de marte: un planeta fósil

La actividad geológica de Marte parece haberse detenido en un pasado remoto de hace miles de millones de años, de modo que Marte se puede considerar como un planeta fósil. Pero esto no significa que su geología sea simple y aburrida, sino todo lo contrario: sin océanos ni vegetación, la geología de Marte se muestra en todo su esplendor, además de estar llena de enigmas fascinantes y misterios científicos, muchos de ellos todavía no resueltos. ¿Es Marte un planeta de una única placa tectónica?, ¿por que son tan gigantescos sus volcanes?, ¿hubo alguna vez un océano?, ¿tiene actividad sísmica? Y, por supuesto, la pregunta fundamental: ¿hubo vida en Marte?, o mas excitante aun, ¿hay vida en la actualidad? Estructurado en 61 breves capítulos que pueden leerse en cualquier orden, este libro permitirá a los apasionados por la ciencia y la aventura espacial realizar un recorrido aleatorio por este planeta singular.Instituto Geológico y Minero de España, Españ

Cuevas kársticas y no kársticas: del subsuelo terráqueo a las cavidades extraterrestres

En este trabajo nos hacemos eco de una interesante paradoja; las cuevas, que en el pasado dieron cobijo a los seres humanos en la prehistoria y que tanta importancia tienen en nuestro planeta por muy variados motivos, son también de gran importancia y actualidad en geología planetaria e investigación espacial como posible habitáculo para las futuras misiones tripuladas a Marte. Adicionalmente, las cuevas serán candidatas excepcionales para buscar indicios de vida actual o pasada, en dicho planeta. En este trabajo se repasan los tipos de cuevas naturales que podemos encontrar en la Tierra de acuerdo al mecanismo que las origina y la litología donde se desarrollan. Esto nos permite extrapolar, por analogía, qué tipo de cuevas es posible encontrar en otros cuerpos del sistema solar, esto es, qué tipo de cuevas extraterrestres cabe esperar descubrir en el futuro. Concluimos este trabajo examinando la situación actual del estado de nuestro conocimiento en tal sentido.Instituto Geológico y Minero de España, EspañaUnidad de Baleares, Instituto Geológico y Minero de España, Españ

Cuevas kársticas y no kársticas: del subsuelo terráqueo a las cavidades extraterrestres

En este trabajo nos hacemos eco de una interesante paradoja; las cuevas, que en el pasado dieron cobijo a los seres humanos en la prehistoria y que tanta importancia tienen en nuestro planeta por muy variados motivos, son también de gran importancia y actualidad en geología planetaria e investigación espacial como posible habitáculo para las futuras misiones tripuladas a Marte. Adicionalmente, las cuevas serán candidatas excepcionales para buscar indicios de vida actual o pasada, en dicho planeta. En este trabajo se repasan los tipos de cuevas naturales que podemos encontrar en la Tierra de acuerdo al mecanismo que las origina y la litología donde se desarrollan. Esto nos permite extrapolar, por analogía, qué tipo de cuevas es posible encontrar en otros cuerpos del sistema solar, esto es, qué tipo de cuevas extraterrestres cabe esperar descubrir en el futuro. Concluimos este trabajo examinando la situación actual del estado de nuestro conocimiento en tal sentido.Instituto Geológico y Minero de España, EspañaUnidad de Baleares, Instituto Geológico y Minero de España, Españ

Spectral and cross-spectral analysis of uneven time series with the smoothed Lomb–Scargle periodogram and Monte Carlo evaluation of statistical significance

Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis,…) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb–Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb–Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb–Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and real data) are described in this paper to corroborate the methodology and the implementation of these two new programsInstituto Geológico y Minero de España, EspañaDepartamento de Estratigrafía y Paleontología, Universidad de Granada, Españ

Análisis espectral de series temporales de variables geológicas con muestreo irregular

En geociencias el muestreo más frecuente para las series temporales de variables geológicas es el muestreo irregular. Esto sucede bien porque el muestreo es aleatorio, por la ausencia parcial de datos (datos perdidos, hiatos,…), o por la transformación de la escala espacial a la escala temporal cuando la tasa de sedimentación no es constante. En todos estos casos la interpolación no es una estrategia aconsejable y es más correcto utilizar un método que trate directamente con los datos irregulares. En este trabajo se muestra cómo el periodograma de Lomb-Scargle suavizado es una elección apropiada. Se examinan los efectos del tipo de muestreo, la interpolación y la presencia de una deriva. Se propone el test de permutación como el método para calcular niveles de confianza estadística. A través de la aplicación del peridograma de Lomb-Scargle a una serie sintética se concluye la robustez del método ante los efectos anteriormente mencionados. Se ilustra la aplicación a una serie real con hiatos y que representa el espesor del bandeado anual de una estalagmita. El estudio de estos ejemplos pretende ayudar al investigador a la aplicación del periodograma de Lomb-Scargle a sus propios datos.Instituto Geológico y Minero de España, EspañaDepartamento de Estratigrafía y Paleontología, Universidad de Granada, Españ

Comparison of Trend Detection Approaches in Time Series and Their Application to Identify Temperature Changes in the Valencia Region (Eastern Spain)

International Geostatistical Congress (10º. 2016. Valencia)The identification of systematic small- and intermediate-scale temperature changes (trends) in a time series is of significant importance in the analysis of climate data. This is particularly so in the analysis of local climate change trends and their potential impact on local hydrological cycles. Although many statistical tests have been proposed for detecting these trends their effectiveness is often affected by the presence of serial correlation in the time series. Hence, it is of both interest and necessity to compare the performances of these tests by applying them under a representative range of conditions. In this study, we use Monte Carlo experiments to compare and explore six commonly used tests for detecting trend. For this purpose, we use the confidence level and power to assess the ability to detect trend in two groups of simulated time series with and without serial correlation. The statistical tests are also applied to mean annual temperature measured at 13 weather stations located in the Valencia region (Eastern Spain).School of Resources and GeosciencesChina University of Mining and Technology, ChinaInstituto Geológico y Minero de España, EspañaUniversity of Adelaide, AustraliaPeer reviewe