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Thorsten Wagener

Bio: Thorsten Wagener is an academic researcher from University of Bristol. The author has contributed to research in topics: Hydrological modelling & Climate change. The author has an hindex of 67, co-authored 260 publications receiving 18933 citations. Previous affiliations of Thorsten Wagener include Queen's University & Pennsylvania State University.


Papers
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Journal ArticleDOI
TL;DR: This paper presents an overview of SA and its link to uncertainty analysis, model calibration and evaluation, robust decision-making, and provides practical guidelines by developing a workflow for the application of SA.
Abstract: Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be attributed to variations of its input factors. SA is increasingly being used in environmental modelling for a variety of purposes, including uncertainty assessment, model calibration and diagnostic evaluation, dominant control analysis and robust decision-making. In this paper we review the SA literature with the goal of providing: (i) a comprehensive view of SA approaches also in relation to other methodologies for model identification and application; (ii) a systematic classification of the most commonly used SA methods; (iii) practical guidelines for the application of SA. The paper aims at delivering an introduction to SA for non-specialist readers, as well as practical advice with best practice examples from the literature; and at stimulating the discussion within the community of SA developers and users regarding the setting of good practices and on defining priorities for future research. We present an overview of SA and its link to uncertainty analysis, model calibration and evaluation, robust decision-making.We provide a systematic review of existing approaches, which can support users in the choice of an SA method.We provide practical guidelines by developing a workflow for the application of SA and discuss critical choices.We give best practice examples from the literature and highlight trends and gaps for future research.

888 citations

Journal ArticleDOI
TL;DR: In this paper, a catchment classification framework is proposed to provide a mapping of landscape form and hydro-climatic conditions on catchment function (including partition, storage, and release of water), while explicitly accounting for uncertainty and for variability at multiple temporal and spatial scales.
Abstract: Hydrology does not yet possess a generally agreed upon catchment classification system. Such a classification framework should provide a mapping of landscape form and hydro-climatic conditions on catchment function (including partition, storage, and release of water), while explicitly accounting for uncertainty and for variability at multiple temporal and spatial scales. This framework would provide an organizing principle, create a common language, guide modeling and measurement efforts, and provide constraints on predictions in ungauged basins, as well as on estimates of environmental change impacts. In this article, we (i) review existing approaches to define hydrologic similarity and to catchment classification; (ii) discuss outstanding components or characteristics that should be included in a classification scheme; and (iii) provide a basic framework for catchment classification as a starting point for further analysis. Possible metrics to describe form, hydro-climate, and function are suggested and discussed. We close the discussion with a list of requirements for the classification framework and open questions that require addressing in order to fully implement it. Open questions include: How can we best represent characteristics of form and hydro-climatic conditions? How does this representation change with spatial and temporal scale? What functions (partition, storage, and release) are relevant at what spatial and temporal scale? At what scale do internal structure and heterogeneity become important and need to be considered?

693 citations

Journal ArticleDOI
TL;DR: This paper presents the concept of a diagnostic evaluation approach rooted in information theory and employing the notion of signature indices that measure theoretically relevant system process behaviours that addresses the issue of degree of system complexity resolvable by a model.
Abstract: This paper discusses the need for a well-considered approach to reconciling environmental theory with observations that has clear and compelling diagnostic power. This need is well recognized by the scientific community in the context of the ‘Predictions in Ungaged Basins’ initiative and the National Science Foundation sponsored ‘Environmental Observatories’ initiative, among others. It is suggested that many current strategies for confronting environmental process models with observational data are inadequate in the face of the highly complex and high order models becoming central to modern environmental science, and steps are proposed towards the development of a robust and powerful ‘Theory of Evaluation’. This paper presents the concept of a diagnostic evaluation approach rooted in information theory and employing the notion of signature indices that measure theoretically relevant system process behaviours. The signature-based approach addresses the issue of degree of system complexity resolvable by a model. Further, it can be placed in the context of Bayesian inference to facilitate uncertainty analysis, and can be readily applied to the problem of process evaluation leading to improved predictions in ungaged basins. Copyright  2008 John Wiley & Sons, Ltd.

576 citations

Journal ArticleDOI
TL;DR: For a long-term initiative to address the regional implications of environmental change, hydrologists must become both synthesists and analysts, understanding the functioning of individual system components, while operating firmly within a well-designed hypothesis testing framework.
Abstract: Human activities exert global-scale impacts on our environment with significant implications for freshwater-driven services and hazards for humans and nature. Our approach to the science of hydrology needs to significantly change so that we can understand and predict these implications. Such an adjustment is a necessary prerequisite for the development of sustainable water resource management strategies and to achieve long-term water security for people and the environment. Hydrology requires a paradigm shift in which predictions of system behavior that are beyond the range of previously observed variability or that result from significant alterations of physical (structural) system characteristics become the new norm. To achieve this shift, hydrologists must become both synthesists, observing and analyzing the system as a holistic entity, and analysts, understanding the functioning of individual system components, while operating firmly within a well-designed hypothesis testing framework. Cross-disciplinary integration must become a primary characteristic of hydrologic research, catalyzing new research and nurturing new educational models. The test of our quantitative understanding across atmosphere, hydrosphere, lithosphere, biosphere, and anthroposphere will necessarily lie in new approaches to benchmark our ability to predict the regional hydrologic and connected implications of environmental change. To address these challenges and to serve as a catalyst to bring about the necessary changes to hydrologic science, we call for a long-term initiative to address the regional implications of environmental change.

575 citations

Journal ArticleDOI
TL;DR: The impact of climate change on karst aquifers has been studied in this article, where the authors explore different conceptual models and how they can be translated into numerical models of varying complexity and therefore varying data requirements.
Abstract: Karst regions represent 7–12% of the Earth's continental area, and about one quarter of the global population is completely or partially dependent on drinking water from karst aquifers. Climate simulations project a strong increase in temperature and a decrease of precipitation in many karst regions in the world over the next decades. Despite this potentially bleak future, few studies specifically quantify the impact of climate change on karst water resources. This review provides an introduction to karst, its evolution, and its particular hydrological processes. We explore different conceptual models of karst systems and how they can be translated into numerical models of varying complexity and therefore varying data requirements and depths of process representation. We discuss limitations of current karst models and show that at the present state, we face a challenge in terms of data availability and information content of the available data. We conclude by providing new research directions to develop and evaluate better prediction models to address the most challenging problems of karst water resources management, including opportunities for data collection and for karst model applications at so far unprecedented scales.

556 citations


Cited by
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Journal ArticleDOI

6,278 citations

Journal ArticleDOI
TL;DR: A diagnostically interesting decomposition of NSE is presented, which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and it is shown how model calibration problems can arise due to interactions among these components.

3,147 citations

01 Mar 1987
TL;DR: The variable-order Adams method (SIVA/DIVA) package as discussed by the authors is a collection of subroutines for solution of non-stiff ODEs.
Abstract: Initial-value ordinary differential equation solution via variable order Adams method (SIVA/DIVA) package is collection of subroutines for solution of nonstiff ordinary differential equations. There are versions for single-precision and double-precision arithmetic. Requires fewer evaluations of derivatives than other variable-order Adams predictor/ corrector methods. Option for direct integration of second-order equations makes integration of trajectory problems significantly more efficient. Written in FORTRAN 77.

1,955 citations

01 Jan 2016

1,907 citations

Book ChapterDOI
11 Dec 2012

1,704 citations