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- Akner, Gunnar, 1953-, et al.
(författare)
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Vi står gärna bakom en utfallsbaserad vård
- 2017
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Ingår i: Dagens Samhälle. - 1652-6511.
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Tidskriftsartikel (populärvet., debatt m.m.)abstract
- Jörgen Nordenström försöker få det till att vår kritik av värdebaserad vård egentligen handlar om att vi vill ha mer resurser. Han har helt missuppfattat oss, skriver 26 specialistläkare i en replik.
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| 2. |
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| 4. |
- Fuentes-Andino, Diana, 1984-, et al.
(författare)
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Event and model dependent rainfall adjustments to improve discharge predictions
- 2017
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Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 62:2, s. 232-245
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Tidskriftsartikel (refereegranskat)abstract
- Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it was hypothesised that a simple spatially and temporally averaged event-dependent rainfall multiplier can account for errors in the rainfall input. The potentials and limitations of this lumped multiplier approach were explored by evaluating the effects of multipliers on the accuracy and precision of the predictive distributions. Parameter sets found to be behavioural across a range of different flood events were assumed to be a good representation of the catchment dynamics and were used to identify rainfall multipliers for each of the individual events. An effect of the parameter sets on identified multipliers was found; however, it was small compared to the differences between events. Accounting for event-dependent multipliers improved the reliability of the predictions. At the cost of a small decrease in precision, the distribution of identified multipliers for past events can be used to account for possible rainfall errors when predicting future events. By using behavioural parameter sets to identify rainfall multipliers, the method offers a simple and computationally efficient way to address rainfall errors in hydrological modelling.
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| 5. |
- Fuentes-Andino, Diana, 1984-
(författare)
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Flood Hazard Assessment in Data-Scarce Basins : Use of alternative data and modelling techniques
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Flooding is of great concern world-wide, causing damage to infrastructure, property and loss of life. Low-income countries, in particular, can be negatively affected by flood events due to their inherent vulnerabilities. Moreover, data to perform studies for flood risk management in low-income regions are often scarce or lacking sufficient quality.This thesis proposes new methodologies and explores the use of unconventional sources of information in flood hazard assessment in areas where the quantity or sufficient quality of traditional hydrometrical data are lacking. One method was developed to account for errors in spatially averaged rainfall, from a sparse rain-gauge network, used as input to a rainfall-runoff model. A spatially-averaged and event-dependent rainfall depth multiplier led to improvements of the hydrographs at calibration. And by using a distribution of the multiplier, identified from previous events in the catchment, improvement in predictions could also be obtained.A second method explored the possibility of reproducing an unmeasured extreme flood event using a combination of models, post-event data, precipitation and an uncertainty-analysis framework. This combination allowed the identification of likelihood-associated parameter sets from which the flood hazard map for the extreme event could be obtained.A third and fourth study made at the regional scale explored the value of catchment similarities, and the effects of climate on the hydrological response of catchments.Flood frequency curves were estimated for 36 basins, assumed ungauged, using regional information of short flow records, and local information about the frequency of the storm. In the second regional study, hydro-climatic information provided great value to constrain predictions of series of daily flow from a hydrological model.Previously described methods, used in combination with unconventional information within an uncertainty analysis, proven to be useful for flood hazard assessment at basins with data limitations. The explored data included: post-event measurements of an extreme flood event, hydro-climate regional information and local precipitation data. The methods presented in this thesis are expected to support development of hydrological studies underpinning flood-risk reduction in data-poor areas.
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| 7. |
- Fuentes–Andino, Diana, 1984-, et al.
(författare)
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Reproducing an extreme flood with uncertain post-event information
- 2017
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Ingår i: Hydrology and Earth System Sciences Discussions. - : Copernicus GmbH. - 1812-2108 .- 1812-2116 .- 1607-7938. ; 21:7, s. 3597-3618
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Tidskriftsartikel (refereegranskat)abstract
- Studies for the prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa, the capital of Honduras, when Hurricane Mitch struck the city. In this study we hypothesized that it is possible to estimate, in a trustworthy way considering large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed from a combination of models and post-event measured data. Postevent data collected in 2000 and 2001 were used to estimate discharge peaks, times of peak, and high-water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well-known modelling tools: TOPMODEL, Muskingum-Cunge-Todini routing, and the LISFLOOD-FP hydraulic model. Simulations were performed within the generalized likelihood uncertainty estimation (GLUE) uncertainty-analysis framework. The model combination predicted peak discharge, times of peaks, and more than 90% of the observed highwater marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high-water marks could not be reproduced at a few locations on the floodplain. Identifications of these locations are useful to improve model set-up, model structure, or post-event data-estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e. g. from radar data or a denser rain-gauge net-work. Our study demonstrated that it was possible, considering the uncertainty in the post-event data, to reasonably reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event. The method proposed here can be part of a Bayesian framework in which more events can be added into the analysis as they become available.
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| 8. |
- Gebrehiwot, Solomon Gebreyohannis, et al.
(författare)
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Is observation uncertainty masking the signal of land use change impacts on hydrology?
- 2019
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Ingår i: Journal of Hydrology. - : Elsevier. - 0022-1694 .- 1879-2707. ; 570, s. 393-400
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of hydrological impacts of land use change raises questions about whether, and how much, such impacts are misrepresented because of errors in river flow observations. In this paper, land use change impacts (represented by changes in watershed storage) and different ranges of discharge measurement error are compared to assess how errors in discharge measurement can potentially mask a land use change impact. Using a watershed from the Ethiopian highlands to exemplify this, we simulated five different levels of land use change impacts with five levels of watershed storage reductions (from 10% to 50% change) and the associated time series of runoff. Different levels of observation error were then introduced into these artificial time series. Comparison was made between every pair, i.e. a time series derived from a certain level of land use change (storage reduction) versus a time series corresponding to a given level of observation error, using a step-change t-test. Significant step-changes between pairs define the detectability of land use change impact. The analysis was made for the entire 30-year time series as well as for the most extreme annual weather conditions. The results showed that for the average year and wettest year, 75% or more error in observed discharge masks the maximum simulated land use change impact on hydrology. In dry years, a 50% error in discharge is enough to mask the same impact. Knowing (and improving) the level of data quality contributes to a better understanding of hydrological uncertainties and improves the precision in assessing land use change impacts. Both of these are essential elements in water resources development planning.
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| 9. |
- Girons Lopez, Marc, 1986-
(författare)
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Information Needs for Water Resource and Risk Management : Hydro-Meteorological Data Value and Non-Traditional Information
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Data availability is extremely important for water management. Without data it would not be possible to know how much water is available or how often extreme events are likely to occur. The usually available hydro-meteorological data often have a limited representativeness and are affected by errors and uncertainties. Additionally, their collection is resource-intensive and, thus, many areas of the world are severely under-monitored. Other areas are seeing an unprecedented – yet local – wealth of data in the last decades. Additionally, the spread of new technologies together with the integration of different approaches to water management science and practice have uncovered a large amount of soft information that can potentially complement and expand the possibilities of water management.This thesis presents a series of studies that address data opportunities for water management. Firstly, the hydro-meteorological data needs for correctly estimating key processes for water resource management such as precipitation and discharge were evaluated. Secondly, the use of non-traditional sources of information such as social media and human behaviour to improve the efficiency of flood mitigation actions were explored. The results obtained provide guidelines for determining basic hydro-meteorological data needs. For instance, an upper density of 24 rain gauges per 1000 km2 for spatial precipitation estimation beyond which improvements are negligible was found. Additionally, a larger relative value of discharge data respect to precipitation data for calibrating hydrological models was observed. Regarding non-traditional sources of information, social memory of past flooding events was found to be a relevant factor determining the efficiency of flood early warning systems and therefore their damage mitigation potential. Finally, a new methodology to use social media data for probabilistic estimates of flood extent was put forward and shown to achieve results comparable to traditional approaches.This thesis significantly contributes to integrated water management by improving the understanding of data needs and opportunities of new sources of information thus making water management more efficient and useful for society.
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