A non-stationary bias adjustment method for improving the inter-annual variability and persistence of projected precipitation

Hydrological studies depend heavily on environmental variables, such as precipitation and resulting runoff, which exhibit highly seasonal and intermittent behaviour in semiarid basins. In these basins, the use of traditional methods to adjust biases in time series projections can lead to inaccurate results regarding the impacts of climate change. This study introduces a non-stationary bias adjustment methodology (NS) specifically designed for environmental variables characterized by sporadic events and substantial intensity variability, such as precipitation. The methodology involves establishing a probability threshold to adapt the occurrence of precipitation events and utilizes a quantile mapping method based on a non-stationary theoretical and parametric distribution to adjust biases associated with precipitation intensity. The NS method is applied to daily precipitation projections from seven regional climatic models under the RCP 8.5 scenario spanning 2006-2100, alongside historical concurrent data from 1970 to 2005. The present method is compared to the widely used quantile delta mapping approach (QDM), revealing significant differences in performance related to the distribution of precipitation events throughout the year and the behaviour of mean and extreme intensity values. Both approaches show reliable performance, with root mean square errors between the empirical distribution functions of the corrected hindcast time series and the observations being lower than or close to 1 mm for the percentiles smaller than 50th. The error increases with the percentiles, particularly at stations located at higher altitudes. In these locations, QDM doubles or triples the error obtained with the non-stationary approach for percentiles higher than 75th, reaching up to 34 mm. The proposed methodology demonstrates promising potential in reducing uncertainties associated with systematic errors in inter-annual precipitation variability. It is a first step to jointly apply a similar approach to all involved driving variables. Such methods are key to assessing hydrological responses and associated impacts in semi-arid mountainous basins all around the Globe.

Do Rock Design Formulas Based on Wave Flume Experiments Reliably Model Their Performance at Sea?

The mean sea level rising predicted for this century and the following centuries will make necessary to protect most of the human properties located on the coast. One of the alternatives is the construction of slope breakwaters along hundreds of kilometers of coastline. For coastal engineering this task is a social/environmental and economic/financial challenge, in particular the optimization of the total costs of the structure during its useful life. It is common to design these structures with the Van der Meer stability formula, assuming that the uncertainty of the project is due to maritime agents. Today, this approach is no longer valid and must be reconsidered to adapt to the social and environmental demands. The main source of uncertainty of the Van der Meer formula is epistemic, associated with its ability to predict the progression of failure modes of the structure. This study analyses the actual formula of design coastal structures and discusses the limitations for predicting damage progression, which directly affects designing strategies and total lifetime conservation and repair costs of the structure. It is shown that these limitations derive from: (1) design and experimental technique of the wave flume to propose the formula; (2) non-dimensional variables and parameters included in the formula; and (3) the method of application. It seems desirable and urgent to review and update the state of knowledge and tools for slope breakwater design to meet the demand for protection of human properties on the coast.

Analysis of the Parametric Correlation in Mathematical Modeling of In Vitro Glioblastoma Evolution Using Copulas

Modeling and simulation are essential tools for better understanding complex biological processes, such as cancer evolution. However, the resulting mathematical models are often highly non-linear and include many parameters, which, in many cases, are difficult to estimate and present strong correlations. Therefore, a proper parametric analysis is mandatory. Following a previous work in which we modeled the in vitro evolution of Glioblastoma Multiforme (GBM) under hypoxic conditions, we analyze and solve here the problem found of parametric correlation. With this aim, we develop a methodology based on copulas to approximate the multidimensional probability density function of the correlated parameters. Once the model is defined, we analyze the experimental setting to optimize the utility of each configuration in terms of gathered information. We prove that experimental configurations with oxygen gradient and high cell concentration have the highest utility when we want to separate correlated effects in our experimental design. We demonstrate that copulas are an adequate tool to analyze highly-correlated multiparametric mathematical models such as those appearing in Biology, with the added value of providing key information for the optimal design of experiments, reducing time and cost in in vivo and in vitro experimental campaigns, like those required in microfluidic models of GBM evolution.

High-resolution time-dependent probabilistic assessment of the hydraulic performance for historic coastal structures: application to Luarca Breakwater

Historic coastal structures have played a key role in small- to medium-size ports, being the driving force for the local development of coastal communities. Because coastal managers require reliable risk-based analysis of the whole life cycle of these coastal structures, previous lifetimes should be studied. This is a differentiating factor with respect to the newly built breakwaters. For this reason, in this work, a methodology for assessing how the hydraulic performance of an expired lifetime has evolved over the years is presented. It is performed following a probabilistic approach due to the uncertainty related to both the involved variables (wave climate, geometrical and structural breakwater variables) and the hydraulic response of the structure. The first ones are characterized by reliable probability distribution functions. The second ones are characterized by reliable formulae for the analysis of the hydraulic response. However, their non-conventional designs located in shallow-water locations require site-dependent formulae. To overcome this problem, a novel methodology to apply CFD numerical models is presented. Finally, it is integrated in a high-resolution time-dependent probabilistic methodology which takes into account the stochastic behaviour of all the involved variables, coastal and structural processes with a good uncertainty level. This article is part of the theme issue 'Environmental loading of heritage structures'.