| 1. |
- Blösch, Günter, et al.
(författare)
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Twenty-three unsolved problems in hydrology (UPH) - a community perspective
- 2019
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Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 64:10, s. 1141-1158
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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. |
- Breinl, Korbinian, et al.
(författare)
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A joint modelling framework for daily extremes of river discharge and precipitation in urban areas
- 2015
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Ingår i: Journal of Flood Risk Management. - : Wiley. - 1753-318X.
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Tidskriftsartikel (refereegranskat)abstract
- Human settlements are often at risk from multiple hydro-meteorological hazards, which include fluvial floods, short-time extreme precipitation (leading to ‘pluvial’ floods) or coastal floods. In the past, considerable scientific effort has been devoted to assessing fluvial floods. Only recently have methods been developed to assess the hazard and risk originating from pluvial phenomena, whereas little effort has been dedicated to joint approaches. The aim of this study was to develop a joint modelling framework for simulating daily extremes of river discharge and precipitation in urban areas. The basic framework is based on daily observations coupled with a novel precipitation disaggregation algorithm using nearest neighbour resampling combined with the method of fragments to overcome data limitations and facilitate its transferability. The framework generates dependent time series of river discharge and urban precipitation that allow for the identification of fluvial flood days (daily peak discharge), days of extreme precipitation potentially leading to pluvial phenomena (maximum hourly precipitation) and combined fluvial–pluvial flood days (combined time series). Critical thresholds for hourly extreme precipitation were derived from insurance and fire service data.
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| 3. |
- Breinl, Korbinian, et al.
(författare)
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Can weather generation capture precipitation patterns across different climates, spatial scales and under data scarcity?
- 2017
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Stochastic weather generators can generate very long time series of weather patterns, which are indispensable in earth sciences, ecology and climate research. Yet, both their potential and limitations remain largely unclear because past research has typically focused on eclectic case studies at small spatial scales in temperate climates. In addition, stochastic multi-site algorithms are usually not publicly available, making the reproducibility of results difficult. To overcome these limitations, we investigated the performance of the reduced-complexity multi-site precipitation generator TripleM across three different climatic regions in the United States. By resampling observations, we investigated for the first time the performance of a multi-site precipitation generator as a function of the extent of the gauge network and the network density. The definition of the role of the network density provides new insights into the applicability in data-poor contexts. The performance was assessed using nine different statistical metrics with main focus on the inter-annual variability of precipitation and the lengths of dry and wet spells. Among our study regions, our results indicate a more accurate performance in wet temperate climates compared to drier climates. Performance deficits are more marked at larger spatial scales due to the increasing heterogeneity of climatic conditions.
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| 4. |
- Breinl, Korbinian
(författare)
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Driving a lumped hydrological model with precipitation output from weather generators of different complexity
- 2016
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Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 61:8, s. 1395-1414
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Tidskriftsartikel (refereegranskat)abstract
- This paper deals with the question of whether a lumped hydrological model driven with lumped daily precipitation time series from a univariate single-site weather generator can produce equally good results compared to using a multivariate multi-site weather generator, where synthetic precipitation is first generated at multiple sites and subsequently lumped. Three different weather generators were tested: a univariate “Richardson type” model, an adapted univariate Richardson type model with an improved reproduction of the autocorrelation of precipitation amounts and a semi-parametric multi-site weather generator. The three modelling systems were evaluated in two Alpine study areas by comparing the hydrological output with respect to monthly and daily statistics as well as extreme design flows. The application of a univariate Richardson type weather generator to lumped precipitation time series requires additional attention. Established parametric distribution functions for single-site precipitation turned out to be unsuitable for lumped precipitation time series and led to a large bias in the hydrological simulations. Combining a multi-site weather generator with a hydrological model produced the least bias.
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| 5. |
- Breinl, Korbinian, et al.
(författare)
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Extreme dry and wet spells face changes in their duration and timing
- 2020
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 15:7
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Tidskriftsartikel (refereegranskat)abstract
- Dry spells are sequences of days without precipitation. They can have negative implications for societies, including water security and agriculture. For example, changes in their duration and within-year timing can pose a threat to food production and wildfire risk. Conversely, wet spells are sequences of days with precipitation above a certain threshold, and changes in their duration and within-year timing can impact agriculture, flooding or the prevalence of water-related vector-borne diseases. Here we assess changes in the duration and within-year timing of extreme dry and wet spells over 60 years (1958-2017) using a consistent global land surface precipitation dataset of 5093 rain gauge locations. The dataset allowed for detailed spatial analyses of the United States, Europe and Australia. While many locations exhibit statistically significant changes in the duration of extreme dry and wet spells, the changes in the within-year timing are less often significant. Our results show consistencies with observations and projections from state-of-the-art climate and water resources research. In addition, we provide new insights regarding trends in the timing of extreme dry and wet spells, an aspect being equally important for possible future implications of extremes in a changing climate, which has not yet received the same level of attention and is characterized by larger uncertainty.
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| 6. |
- Breinl, Korbinian, et al.
(författare)
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Simulating daily precipitation and temperature: a weather generation framework for assessing hydrometeorological hazards
- 2015
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Ingår i: Meteorological Applications. - : Wiley. - 1350-4827 .- 1469-8080. ; 22:3, s. 334-347
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Tidskriftsartikel (refereegranskat)abstract
- Stochastic weather generators simulate synthetic weather data while maintaining statistical properties of the observations. A new semi-parametric algorithm for multi-site precipitation has been published recently by Breinl et al. (2013), who used a univariate Markov process to simulate precipitation occurrence at multiple sites for two small rain gauge networks. Precipitation amounts were simulated in a two-step process by first resampling observations and then sampling and reshuffling of parametric precipitation amounts. In the present study, the precipitation model by Breinl et al. (2013, J. Hydrol. 498: 23–35) is implemented in a weather generation framework for daily precipitation and temperature. It is extended to a considerably larger gauge station network of 19 stations and further improved to reduce the duplication of historical records in the simulation. Autoregressive-moving-average models (ARMA) are used to simulate mean daily temperature at three sites. Power transformations reduce the bias of simulated temperature extremes. Precipitation amounts are simulated by means of hybrid distributions consisting of a Weibull distribution for low precipitation amounts and a generalized Pareto distribution (GPD) for moderate and extreme precipitation amounts. The proposed weather generator is particularly suitable for assessing hydrometeorological hazards such as flooding as it reproduces the spatial variability of precipitation very well and can generate unobserved extremes.
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| 7. |
- Breinl, Korbinian, et al.
(författare)
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Space-time disaggregation of precipitation and temperature across different climates and spatial scales
- 2019
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Ingår i: Journal of Hydrology. - : ELSEVIER SCIENCE BV. - 2214-5818. ; 21, s. 126-146
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Tidskriftsartikel (refereegranskat)abstract
- Study region: This study focuses on two study areas: the Province of Trento (Italy; 6200 km(2)), and entire Sweden (447000km(2)). The Province of Trento is a complex mountainous area including subarctic, humid continental and Tundra climates. Sweden, instead, is mainly dominated by a subarctic climate in the North and an oceanic climate in the South. Study focus: Hydrological predictions often require long weather time series of high temporal resolution. Daily observations typically exceed the length of sub-daily observations, and daily gauges are more widely available than sub-daily gauges. The issue can be overcome by disaggregating daily into sub-daily values. We present an open-source tool for the non-parametric space-time disaggregation of daily precipitation and temperature into hourly values called spatial method of fragments (S-MOF). A large number of comparative experiments was conducted for both S-MOF and MOF in the two study regions. New hydrological insights for the region: Our experiments demonstrate the applicability of the univariate and spatial method of fragments in the two temperate/subarctic study regions where snow processes are important. S-MOF is able to produce consistent precipitation and temperature fields at sub-daily resolution with acceptable method related bias. For precipitation, although climatologically more complex, S-MOF generally leads to better results in the Province of Trento than in Sweden, mainly due to the smaller spatial extent of the former region.
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| 8. |
- Breinl, Korbinian, et al.
(författare)
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Stochastic generation of multi-site daily precipitation for applications in risk management
- 2013
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Ingår i: Journal of Hydrology. - : Elsevier BV. - 0022-1694 .- 1879-2707. ; 498, s. 23-35
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Tidskriftsartikel (refereegranskat)abstract
- Unlike single-site precipitation generators, multi-site precipitation generators make it possible to reproduce the space–time variation of precipitation at several sites. The extension of single-site approaches to multiple sites is a challenging task, and has led to a large variety of different model philosophies for multi-site models. This paper presents an alternative semi-parametric multi-site model for daily precipitation that is straightforward and easy to implement. Multi-site precipitation occurrences are simulated with a univariate Markov process, removing the need for individual Markov models at each site. Precipitation amounts are generated by first resampling observed values, followed by sampling synthetic precipitation amounts from parametric distribution functions. These synthetic precipitation amounts are subsequently reshuffled according to the ranks of the resampled observations in order to maintain important statistical properties of the observation network. The proposed method successfully combines the advantages of non-parametric bootstrapping and parametric modeling techniques. It is applied to two small rain gauge networks in France (Ubaye catchment) and Austria/Germany (Salzach catchment) and is shown to well reproduce the observations. Limitations of the model relate to the bias of the reproduced seasonal standard deviation of precipitation and the underestimation of maximum dry spells. While the lag-1 autocorrelation is well reproduced for precipitation occurrences, it tends to be underestimated for precipitation amounts. The model can generate daily precipitation amounts exceeding the ones in the observations, which can be crucial for risk management related applications. Moreover, the model deals particularly well with the spatial variability of precipitation. Despite its straightforwardness, the new concept makes a good alternative for risk management related studies concerned with producing daily synthetic multi-site precipitation time series.
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| 9. |
- Di Baldassarre, Giuliano, et al.
(författare)
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An integrative research framework to unravel the interplay of natural hazards and vulnerabilities
- 2018
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Ingår i: Earth's Future. - : John Wiley & Sons. - 2328-4277. ; 6:3, s. 305-310
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Tidskriftsartikel (refereegranskat)abstract
- Climate change, globalization, urbanization, social isolation, and increased interconnectednessbetween physical, human, and technological systems pose major challenges to disaster risk reduction(DRR). Subsequently, economic losses caused by natural hazards are increasing in many regions of theworld, despite scientific progress, persistent policy action, and international cooperation. We argue thatthese dramatic figures call for novel scientific approaches and new types of data collection to integratethe two main approaches that still dominate the science underpinning DRR: the hazard paradigm and thevulnerability paradigm. Building from these two approaches, here we propose a research framework thatspecifies the scope of enquiry, concepts, and general relations among phenomena. We then discuss theessential steps to advance systematic empirical research and evidence-based DRR policy action.
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| 10. |
- Di Baldassarre, Giuliano, et al.
(författare)
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Water shortages worsened by reservoir effects
- 2018
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Ingår i: Nature Sustainability. - London : Nature Publishing Group. - 2398-9629 .- 2398-9629. ; 1, s. 617-622
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Tidskriftsartikel (refereegranskat)abstract
- The expansion of reservoirs to cope with droughts and water shortages is hotly debated in many places around the world. We argue that there are two counterintuitive dynamics that should be considered in this debate: supply–demand cycles and reservoir effects. Supply–demand cycles describe instances where increasing water supply enables higher water demand, which can quickly offset the initial benefits of reservoirs. Reservoir effects refer to cases where over-reliance on reservoirs increases vulnerability, and therefore increases the potential damage caused by droughts. Here we illustrate these counterintuitive dynamics with global and local examples, and discuss policy and research implications.
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