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Träfflista för sökning "WFRF:(Westerberg Ida K.) srt2:(2015-2019)"

Sökning: WFRF:(Westerberg Ida K.) > (2015-2019)

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1.
  • Blösch, Günter, et al. (författare)
  • Twenty-three unsolved problems in hydrology (UPH) - a community perspective
  • 2019
  • Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 64:10, s. 1141-1158
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.
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2.
  • Quesada-Montano, Beatriz, 1984- (författare)
  • Hydro-Climatic Variability and Change in Central America : Supporting Risk Reduction Through Improved Analyses and Data
  • 2017
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. For this, a key aspect is access to a dense network of long and good-quality hydro-meteorological data. Unfortunately, such ideal data are sparse or non-existent in Central America. In addition, the existing methods for hydro-climatic studies need to be revised and/or improved to find the most suitable for the region’s climate, geography and hydro-climatic data situation. This work has the ultimate goal to support the reduction of risks associated with hydro-climatic-induced disasters in Central America. This was sought by developing ways to reduce data-related uncertainties and by improving the available methods to study and understand hydro-climatic variability processes. In terms of data-uncertainty reduction, this thesis includes the development of a high resolution air temperature dataset and a methodology to reduce uncertainties in a hydrological model at ungauged basins. The dataset was able to capture the spatial patterns with a detail not available with existing datasets. The methodology significantly reduced uncertainties in an assumed-to-be ungauged catchment. In terms of methodological improvements, this thesis includes an assessment of the most suitable combination of (available) meteorological datasets and drought indices to characterise droughts in Central America. In addition, a methodology was developed to analyse drought propagation in a tropical catchment, in an automated, objective way. Results from the assessment and the drought propagation analysis contributed with improving the understanding of drought patterns and generating processes in the region. Finally, a methodology was proposed for assessing changes in both hydrological extremes in a consistent way. This contrasts with most commonly used frameworks that study each extreme individually. The method provides important characteristics (frequency, duration and magnitude), information that can be useful for decisions within risk reduction and water management. The results presented in this thesis are a contribution, in terms of hydro-climatic data and assessment methods, for supporting risk reduction of disasters related with hydro-climatic extremes in Central America.
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3.
  • Westerberg, Ida, et al. (författare)
  • Hydrological data uncertainty and its implications.
  • 2018
  • Ingår i: WIREs Water. - : Wiley. - 2049-1948. ; e1319:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Hydrologic data are at the core of our understanding of physical hydrologic processes, our simulation models and forecasts of water resources and hazards, and our monitoring of water quantity and quality. However, hydrologic data are subject to multiple sources of uncertainty that can introduce bias and error into our analyses and decision‐making if not properly accounted for. In this article, we summarize five categories of data uncertainty: measurement uncertainty, derived data uncertainty, interpolation uncertainty, scaling uncertainty, and data management uncertainty. Hydrologic data uncertainty magnitudes are typically in the range 10–40%. To quantify data uncertainty, hydrologists should first construct a perceptual model of uncertainty that itemizes uncertainty sources. The magnitude of each source can then be estimated using replicates (repeated, nested or subsampled measurements), or information from the literature (in‐depth uncertainty results from experimental catchments, colocated gauges or method comparisons). Multiple uncertainty sources can be combined using Monte Carlo methods to determine total uncertainty. Data uncertainty analysis improves hydrologic process understanding by enabling robust hypothesis testing and identification of spatial and temporal patterns that relate to true process differences rather than data uncertainty. By quantifying uncertainty in data used for input or evaluation of hydrologic models, we can prevent parameter bias, exclude disinformative data, and enhance model performance evaluation. In water management applications, quantifying data uncertainty can lead to robust risk analysis, reduced costs, and transparent results that improve the trust of the public and water managers.
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4.
  • Westerberg, Ida K., et al. (författare)
  • Observational uncertainties in hypothesis testing : investigating the hydrological functioning of a tropical catchment
  • 2015
  • Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 29:23, s. 4863-4879
  • Tidskriftsartikel (refereegranskat)abstract
    • Hypothesis testing about catchment functioning with conceptual hydrological models is affected by uncertainties in the model representation of reality as well as in the observed data used to drive and evaluate the model. We formulated a learning framework to investigate the role of observational uncertainties in hypothesis testing using conceptual models and applied it to the relatively data-scarce tropical Sarapiqui catchment in Costa Rica. Observational uncertainties were accounted for throughout the framework that incorporated different choices of model structures to test process hypotheses, analyses of parametric uncertainties and effects of likelihood choice, a posterior performance analysis and (iteratively) formulation of new hypotheses. Estimated uncertainties in precipitation and discharge were linked to likely non-linear near-surface runoff generation and the potentially important role of soils in mediating the hydrological response. Some model-structural inadequacies could be identified in the posterior analyses (supporting the need for an explicit soil-moisture routine to match streamflow dynamics), but the available information about the observational uncertainties prevented conclusions about other process representations. The importance of epistemic data errors, the difficulty in quantifying them and their effect on model simulations was illustrated by an inconsistent event with long-term effects. Finally we discuss the need for new data, new process hypotheses related to deep groundwater losses, and conclude that observational uncertainties need to be accounted for in hypothesis testing to reduce the risk of drawing incorrect conclusions.
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5.
  • Westerberg, Ida, et al. (författare)
  • Response to discussion by Ertsen on Westerberg et al. “Perceptual models of uncertainty for socio-hydrological systems".
  • 2018
  • Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; :63, s. 13–14-
  • Tidskriftsartikel (refereegranskat)abstract
    • Ertsen discusses the representation of reality and uncertainty in our paper, raising three critical points. In response to the first, we agree that discussion of different interpretations of the concept of uncertainty is important when developing perceptual models – making different uncertainty interpretations explicit was a key motivation behind our method. Secondly, we do not, as Ertsen suggests, deny anyone who is not a “certified” scientist to have relevant knowledge. The elicitation of diverse views by discussing perceptual models is a basis for open discussion and decision making. Thirdly, Ertsen suggests that it is not useful to treat socio-hydrological systems as if they exist. We argue that we act as “pragmatic realists” in most practical applications by treating socio-hydrological systems as an external reality that can be known. But the uncertainty that arises from our knowledge limitations needs to be recognized, as it may impact on practical decision making and associated costs.
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