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Start Over Publication Year Range Last 10 years Journal journal of hydrology Publisher elsevier
4 results

1. Uni- and multivariate bias adjustment of climate model simulations in Nordic catchments: Effects on hydrological signatures relevant for water resources management in a changing climate

Abstract

Hydrological climate-change-impact studies depend on climatic variables simulated by climate models. Due to parametrization and numerous simplifications, however, climate-model outputs come with systematic biases compared to the observations. In the past decade, several methods of different complexity and dimensionality for adjustment of such biases were introduced, but their benefits for impact studies and accurate streamflow projections are still debated. In this paper, we evaluated the ability of two state-of-the-art, advanced multivariate bias-adjustment methods to accurately reproduce 16 hydrological signatures, and compared their performance against two parsimonious univariate bias-adjustment methods based on a multi-criteria performance evaluation. The results indicated that all bias-adjustment methods considerably reduced biases and increased the consistency of simulated hydrological signatures. The added value of multivariate methods in maintaining dependence structures between precipitation and temperature was not systematically reflected in the resulting hydrological signatures, as they were generally outperformed by univariate methods. The benefits of multivariate methods only emerged for low-flow signatures in snowmelt-driven catchments. Based on these findings, we identified the most suitable bias-adjustment methods for water-resources management in Nordic regions under a changing climate, and provided practical guidelines for the selection of bias-adjustment methods given specific research targets and hydroclimatic regimes.

Published
2023

2. Fast data assimilation for open channel hydrodynamic models using control theory approach

Abstract

Model-driven forecasting, used for flood risks or big hydropower systems management, can produce results of unsatisfying accuracy even with best-calibrated hydrodynamic models. One of the biggest uncertainty sources is the inflow data, either produced by different hydrological models or obtained using unreliable rating curves. To keep the model in the up-to-date state, data assimilation techniques are used. The aim of the assimilation is to reduce the difference between simulated and observed state of selected variables by updating hydrodynamic model state variables according to observed water levels. The widely used data assimilation method applicable for nonlinear hydrodynamic models is Ensemble Kalman Filter (EnKF). However, this method can often increase the computational time due to complexity of mathematical apparatus, making it less applicable in everyday operations. This paper presents the novel, fast, tailor-made data assimilation method, suitable for 1D open channel hydraulic models, based on control theory. Using Proportional-Integrative-Derivative (PID) controllers, the difference between measured levels and simulated levels obtained by hydrodynamic model is reduced by adding or subtracting the flows in the junctions/sections where water levels are measured. The novel PID control-based data assimilation (PID-DA) is compared to EnKF. Benchmarking shows that PID-DA can be used for data assimilation, even coupled with simplified 1D hydraulic model, without significant sacrifice of stability and accuracy, and with reduction of computational time up to 63 times.

Published
2020

3. Megacities and rivers

Author

Michaela Hordijk, Francine van den Brandeler, Joyeeta Gupta, and Governance and Inclusive Development (GID, AISSR, FMG)

Subjects
geography.geographical_feature_category, 0208 environmental biotechnology, Drainage basin, Integrated urban water management, 02 engineering and technology, 010501 environmental sciences, 01 natural sciences, Metropolitan area, 020801 environmental engineering, Water scarcity, Water resources, Geography, Megacity, Urbanization, Management system, Environmental planning, 0105 earth and related environmental sciences, Water Science and Technology
Abstract

Due to rapid urbanization, population growth and economic drivers, megacities and metropolises around the world face increasing water challenges, such as water scarcity, degradation of water resources and water-related risks such as flooding. Climate change is expected to put additional stress on already strained metropolitan water management systems. Although there is considerable research on river basin management and on urban water management, there is hardly any on metropolitan water management. Similarly, as urban water generally emerges from and returns to river basins, it is surprising how little literature there is that explicitly connects these two spheres of governance. Hence this review paper addresses the: What does a review of the literature tell us about the overlap and reconciliation between the concepts of Integrated Water Resources/River Basin Management and Metropolitan/Urban Water Management, particularly in relation to megacities? Based on an extensive literature review, this paper concludes that the key differences between the two are in relation to their overarching framework, scope, inputs and outputs of water and in relation to dealing with extreme weather events. The literature review reveals how sustainable and integrated urban water management increasingly adopt principles and rhetoric from integrated water resource management, this has yet to translate into significant changing practices on the ground. Urban water management still often occurs independently of river basin issues. Achieving coherence between river basin management and sustainable/integrated urban water management is even more difficult in metropolises and megacities, because the latter consists of multiple political-administrative units. The article concludes that the scalar mismatch between river basin management and metropolitan/megacity water governance deserves much greater attention than it currently receives in the academic and policy debates.

Published
2019

4. Optimal input experiment design and parameter estimation in core-scale pressure oscillation experiments

Author

M Mansoori, Jan Dirk Jansen, M.G. Potters, van den Pmj Paul Hof, Xja Bombois, Delft Center for Systems and Control [Delft] (DCSC), Delft University of Technology (TU Delft), Sharif University of Technology [Tehran] (SUT), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Civil Engineering and Geosciences [Delft], Department of Electrical Engineering [Eindhoven], Eindhoven University of Technology [Eindhoven] (TU/e), Control Systems, and Dynamic Networks: Data-Driven Modeling and Control

Subjects
0209 industrial biotechnology, Optimization problem, Porous media, 02 engineering and technology, 010502 geochemistry & geophysics, 01 natural sciences, law.invention, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Control theory, law, 0105 earth and related environmental sciences, Water Science and Technology, Mathematics, Estimation theory, Covariance matrix, Design of experiments, Mathematical analysis, Physics::Classical Physics, Variance constraints, Permeability (earth sciences), Pressure measurement, Experiment Design, cardiovascular system, Identifiability, Actuator, Estimation
Abstract

International audience; This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using either inlet pressure/outlet pressure measurements (Heller et al., 2002) or actuator position/outlet pressure measurements, where the latter is a novel approach. The solution to the optimization problem reveals that for both measurement methods an optimal excitation frequency, an optimal inlet volume, and an optimal outlet volume exist. We find that under the same parameter variance bounds and actuator constraints, actuator position/outlet pressure measurements result in required experiment times that are a factor fourteen smaller compared to inlet pressure/outlet pressure measurements. This result is analysed in detail and we find that the dominant effect driving this difference originates from an identifiability problem when using inlet–outlet pressure measurements for joint estimation of permeability and porosity. We illustrate our results with numerical simulations, and show excellent agreement with theoretical expectations.

Published
2016