A multi-objective approach to select hydrological models and constrain structural uncertainties for climate impact assessments

The assessment of climate change impacts on water resources and flood risk is typically underpinned by hydrological models calibrated and selected based on observed streamflow records. Yet, changes in climate are rarely accounted for when selecting hydrological models, which compromises their ability to robustly represent future changes in catchment hydrology. In this paper, we test a simple framework for selecting an ensemble of calibrated hydrological model structures in catchments where changing climatic conditions have been observed. We start by considering 78 model structures produced using the FUSE modular modelling framework and rely on a Pareto scheme to select model structures maximizing model efficiency in both wet and dry periods. The application of this approach in three case study basins in Peru enables the identification of structures with good robustness, but also good performance according to hydrological signatures not used for model selection. We also highlight that some model structures that perform well according to traditional efficiency metrics have low performance in contrasting climates or suspicious internal states and fluxes. Importantly, the model selection approach followed here helps to reduce the spread in precipitation elasticities and temperature sensitivities, providing a clearer picture of future hydrological changes. Overall, this work demonstrates the potential of using contrasting climatic conditions in a multi-objective framework to produce robust and credible simulations, and to constrain structural uncertainties in hydrological projections.

On tomography velocity uncertainty in relation with structural imaging

Evaluating structural uncertainties associated with seismic imaging and target horizonscan be of critical importance for decision-making related to oil and gas exploration andproduction. An important breakthrough for industrial applications has been madewith the development of industrial approaches to velocity model building. We proposean extension of these approaches, sampling an equi-probable contour of the tomographyposterior probability density function (pdf) rather than the full pdf, and usingnon-linear slope tomography. Our approach allows to assess the quality of uncertainty relatedassumptions (linearity and Gaussian hypothesis within the Bayesian theory)and estimate volumetric migration positioning uncertainties (a generalization of horizonuncertainties), in addition to the advantages in terms of computational efficiency.We derive the theoretical concepts underlying this approach and unify our derivationswith those of previous publications. As the method works in the full model space ratherthan in a preconditioned one, we split the analysis into the resolved and unresolvedtomography spaces. We argue that the resolved space uncertainties are to be used infurther steps leading to decision-making and can be related to the output of methodsthat work in a preconditioned model space. The unresolved space uncertainties representa qualitative byproduct specific to our method, strongly highlighting the mostuncertain gross areas, thus useful for QCs. These concepts are demonstrated on asynthetic dataset. In addition, the industrial viability of the method is illustrated ontwo different 3D field datasets. The first one consists of a merge of different seismic surveys in the North Sea and shows corresponding structural uncertainties. The second one consists of a marine dataset and shows the impact of structural uncertainties on gross-rock volume computation.

Separation of Structural and Measurement Uncertainties in Watershed Hydrological Models

<p>A hydrological model incurs three types of uncertainties: measurement, structural and parametric uncertainty. Measurement uncertainty exists due to errors in the measurements of rainfall and streamflow data. Structural uncertainty exists due to errors in the mathematical representation of hydrological processes. Parametric uncertainty is a consequence of limited data available to calibrate the model, and measurement and structural uncertainties.</p><p>Recently, separation of structural and measurement uncertainties was identified as one of the twenty-three unsolved problems in hydrology. The information about measurement and structural uncertainties is typically available in the form of residual time-series, that is, the difference between observed and simulated streamflow time-series. The residual time-series, however, provides only an aggregate measure of measurement and structural uncertainties. Thus, the measurement and structural uncertainties are inseparable without additional information. In this study, we used random forest (RF) algorithm to gather additional information about measurement uncertainties using hydrological data across several watersheds. Subsequently, the uncertainty bounds obtained by RF were compared against the uncertainty bounds obtained by two other methods: rating-curve analysis and recently proposed runoff-coefficient method. Rating curve analysis yields uncertainty in streamflow measurements only and the runoff-coefficient yields uncertainty in both rainfall and streamflow measurements. The results of the study are promising in terms of using data across different watersheds for the construction of measurement uncertainty bounds. The preliminary results of this study will be presented in the meeting.</p>

CONTROL SYSTEM FOR STRUCTURURALLY AND PARAMETRICALLY UNDEFINED NON-AFFINE PLANT WITH NEUTRAL TYPE DELAY AND CONTROL DELAY

The article deals with the synthesis of a controller for non-affine in input plant with neutral type delay and control delay, whose state variables are not available for direct measurement. The controller constructed on the basis of the hyperstability criterion compensates for the effects of delays, interference, parametric and structural uncertainties in the system.

A MULTICONNECTED COMBINED SYSTEM FOR A FUNCTIONALLY PARAMETRIC IN-DEFINITE PLANT WITH NONАFFINITY AND CONTROL DELAY

The paper proposes a solution to the problem of synthesizing a multi-coupled combined control system for a non-affine plant with a delay in the input variable with gradually changing dynamics. The plant functions under conditions of a priori parametric and structural uncertainties in the presence of external interference when only the regulated variable is measured. The structure of a multiconnected control system includes an implicit reference model, a preceding-compensator and filter-correctors.