Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

Post-Nonlinear Mixtures and Beyond

Although sources in general nonlinear mixturm arc not separable iising only statistical independence, a special and realistic case of nonlinear mixtnres, the post nonlinear (PNL) mixture is separable choosing a suited separating system. Then, a natural approach is based on the estimation of tho separating Bystem parameters by minimizing an indcpendence criterion, like estimated mwce mutual information. This class of methods requires higher (than 2) order statistics, and cannot separate Gaarsian sources. However, use of [weak) prior, like source temporal correlation or nonstationarity, leads to other source separation Jgw rithms, which are able to separate Gaussian sourra, and can even, for a few of them, works with second-order statistics. Recently, modeling time correlated s011rces by Markov models, we propose vcry efficient algorithms hmed on minimization of the conditional mutual information. Currently, using the prior of temporally correlated sources, we investigate the fesihility of inverting PNL mixtures with non-bijectiw non-liacarities, like quadratic functions. In this paper, we review the main ICA and BSS results for riunlinear mixtures, present PNL models and algorithms, and finish with advanced resutts using temporally correlated snu~sm

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Stable isotopes in arid and semi-arid forest systems

El empleo de isótopos estables en el ámbito de la ecología forestal ha ido creciendo progresivamente en las últimas dos décadas. Cabe esperar que esta tendencia se mantenga en el futuro, ya que éstos aportan una visión integradora de cómo las plantas, hoy y en el pasado, han interaccionado con el medio así como con otros organismos. Su implementación es particularmente relevante en climas secos debido a la fuerte limitación de recursos que en ellos acontece. Tras una breve introducción sobre las bases teóricas de los isótopos estables en fisiología vegetal, esta revisión destaca, sobre diferentes escalas espaciales y temporales, los últimos avances en ecología forestal empleando esta metodología y con un énfasis especial en los sistemas áridos y semiáridos.

Disentangling the formation of contrasting tree line physiognomies combining model selection and Bayesian parameterization for simulation models.

Alpine tree-line ecotones are characterized by marked changes at small spatial scales that may result in a variety of physiognomies. A set of alternative individual-based models was tested with data from four contrasting Pinus uncinata ecotones in the central Spanish Pyrenees to reveal the minimal subset of processes required for tree-line formation. A Bayesian approach combined with Markov chain Monte Carlo methods was employed to obtain the posterior distribution of model parameters, allowing the use of model selection procedures. The main features of real tree lines emerged only in models considering nonlinear responses in individual rates of growth or mortality with respect to the altitudinal gradient. Variation in tree-line physiognomy reflected mainly changes in the relative importance of these nonlinear responses, while other processes, such as dispersal limitation and facilitation, played a secondary role. Different nonlinear responses also determined the presence or absence of krummholz, in agreement with recent findings highlighting a different response of diffuse and abrupt or krummholz tree lines to climate change. The method presented here can be widely applied in individual-based simulation models and will turn model selection and evaluation in this type of models into a more transparent, effective, and efficient exercise.

Secondhand tobacco smoke exposure in open and semi-open settings: a systematic review

Background: Some countries have recently extended smoke-free policies to particular outdoor settings; however, there is controversy regarding whether this is scientifically and ethically justifiable. Objectives: The objective of the present study was to review research on secondhand smoke (SHS) exposure in outdoor settings. Data sources: We conducted different searches in PubMed for the period prior to September 2012. We checked the references of the identified papers, and conducted a similar search in Google Scholar. Study selection: Our search terms included combinations of"secondhand smoke,""environmental tobacco smoke,""passive smoking" OR"tobacco smoke pollution" AND"outdoors" AND"PM" (particulate matter),"PM2.5" (PM with diameter ≤ 2.5 µm),"respirable suspended particles,""particulate matter,""nicotine,""CO" (carbon monoxide),"cotinine,""marker,""biomarker" OR"airborne marker." In total, 18 articles and reports met the inclusion criteria. Results: Almost all studies used PM2.5 concentration as an SHS marker. Mean PM2.5 concentrations reported for outdoor smoking areas when smokers were present ranged from 8.32 to 124 µg/m3 at hospitality venues, and 4.60 to 17.80 µg/m3 at other locations. Mean PM2.5 concentrations in smoke-free indoor settings near outdoor smoking areas ranged from 4 to 120.51 µg/m3. SHS levels increased when smokers were present, and outdoor and indoor SHS levels were related. Most studies reported a positive association between SHS measures and smoker density, enclosure of outdoor locations, wind conditions, and proximity to smokers. Conclusions: The available evidence indicates high SHS levels at some outdoor smoking areas and at adjacent smoke-free indoor areas. Further research and standardization of methodology is needed to determine whether smoke-free legislation should be extended to outdoor settings.

Cost-effectiveness analysis of cardiac resynchronization therapy in patients with NYHA I and NYHA II heart failure in Spain

Objectives: The aim of the study was to combine clinical results from the European Cohort of the REVERSE study and costs associated with the addition of cardiac resynchronization therapy (CRT) to optimal medical therapy (OMT) in patients with mild symptomatic (NYHA I-II) or asymptomatic left ventricular dysfunction and markers of cardiac dyssynchrony in Spain. Methods: A Markov model was developed with CRT + OMT (CRT-ON) versus OMT only (CRT-OFF) based on a retrospective cost-effectiveness analysis. Raw data was derived from literature and expert opinion, reflecting clinical and economic consequences of patient"s management in Spain. Time horizon was 10 years. Both costs (euro 2010) and effects were discounted at 3 percent per annum. Results: CRT-ON showed higher total costs than CRT-OFF; however, CRT reduced the length of hospitalization in ICU by 94 percent (0.006 versus 0.091 days) and general ward in by 34 percent (0.705 versus 1.076 days). Surviving CRT-ON patients (88.2 percent versus 77.5 percent) remained in better functional class longer, and they achieved an improvement of 0.9 life years (LYGs) and 0.77 years quality-adjusted life years (QALYs). CRT-ON proved to be cost-effective after 6 years, except for the 7th year due to battery depletion. At 10 years, the results were 18,431 per LYG and 21,500 per QALY gained. Probabilistic sensitivity analysis showed CRT-ON was cost-effective in 75.4 percent of the cases at 10 years. Conclusions: The use of CRT added to OMT represents an efficient use of resources in patients suffering from heart failure in NYHA functional classes I and II.