Kolbjørn Engeland

• Ekblom Johansson, Fanny Maria; Bakke, Jostein; Støren, Eivind Wilhelm Nagel; Paasche, Øyvind; Engeland, Kolbjørn & Arnaud, Fabien (2020). Lake sediments reveal large variations in flood frequency over the last 6,500 years in south-western Norway. Frontiers in Earth Science.  ISSN 2296-6463. . doi: 10.3389/feart.2020.00239 Vis sammendrag

  Lake sediments can retain imprints of past floods, enabling reconstructions that span well beyond instrumental time series. Time series covering thousands of years can document the natural range of flood variability, which is critical for understanding the potential causality between changing flood patterns and climate. Here, we analyzed sediments from Lake Sandvinvatnet in southwest Norway. Detailed environmental magnetic analyses of an 830cm-long sediment core covering the last 6,500 years captured decadal scale trends in local flood frequency. Magnetic susceptibility (MS) assessments were carried out both on split cores and individual samples to track variability in sedimentary influx; the ratios of MS measured at 77 K and 293 K (MS ratios) provided information on potential changes in source regions. The results suggested that sediments from the Buerdalen valley dominate the signal in the core, and the amount of ferromagnetic (high MS) carriers increases during flood events. These carriers were assumed to be transported from slope deposits in Buerdalen during rainstorm-triggered flood events. The reconstructed flood frequency, based on sediment layers with ferromagnetic carriers, showed high variability over the past 6,500 years, and the finding was validated by overlapping with known historical floods in the area. We observed periods with a high frequency of extreme floods (4100-3140 cal. yr BP) compared with intervals with a few or no extreme floods (6050-4100 cal. yr BP). Floods in this region are commonly a result of intense rain events during fall and snow and glacial melt during late spring and summer. The systematic frequency changes during the past 6,500 years suggest a certain persistency in the processes that cause floods, where mean trends in summer temperature and precipitation may have played a role.

• Engeland, Kolbjørn; Aano, Anna; Steffensen, Ida Grøndahl; Støren, Eivind Wilhelm Nagel & Paasche, Øyvind (2020). New flood frequency estimates for the largest river in Norway based on the combination of short and long time series. Hydrology and Earth System Sciences.  ISSN 1027-5606.  24(11), s 5595- 5619 . doi: 10.5194/hess-24-5595-2020 Fulltekst i vitenarkiv.
• Hegdahl, Trine J.; Engeland, Kolbjørn; Müller, Malte & Sillmann, Jana (2020). An event-based approach to explore selected present and future atmospheric river–induced floods in Western Norway. Journal of Hydrometeorology.  ISSN 1525-755X.  21(9), s 2003- 2021 . doi: 10.1175/JHM-D-19-0071.1 Fulltekst i vitenarkiv. Vis sammendrag

  The aim of this study is to investigate extreme precipitation events caused by atmospheric rivers and compare their flood impact in a warmer climate to current climate using an event-based storyline approach. The study was set up by selecting four high precipitation events from 30 years of present and future climate simulations of the high-resolution global climate model EC-Earth. The two most extreme precipitation events within the selection area for the present and future climate were identified, and EC-Earth was rerun creating 10 perturbed realizations for each event. All realizations were further downscaled with the regional weather prediction model, AROME-MetCoOp. The events were thereafter used as input to the operational Norwegian flood-forecasting model for 37 selected catchments in western Norway, and the magnitude and the spatial pattern of floods were analyzed. The role of the hydrological initial conditions, which are important for the total flooding, were analyzed with a special emphasis on snow and soil moisture excess. The results show that the selected future extreme precipitation events affected more catchments with larger floods, compared to the events from present climate. In addition, multiple realizations of the meteorological forcing and four different hydrological initial conditions, e.g. soil saturation and snow storage, were important for the estimation of the maximum flood level. The meteorological forcing (e.g. the internal variability/perturbed output) accounts for the highest contribution to the spread in flood magnitude; however, for some events and catchments the hydrological initial conditions affected the magnitudes of floods more than the meteorological forcing.

• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2020). A geostatistical two field model that combines point observations and nested areal observations, and quantifies long-term spatial variability - A case study of annual runoff predictions in the Voss area. arXiv.org.  ISSN 2331-8422.
• Hegdahl, Trine Jahr; Engeland, Kolbjørn; Steinsland, Ingelin & Tallaksen, Lena M. (2019). Streamflow forecast sensitivity to air temperature forecast calibration for 139 Norwegian catchments. Hydrology and Earth System Sciences.  ISSN 1027-5606.  23(2), s 723- 739 . doi: 10.5194/hess-23-723-2019 Fulltekst i vitenarkiv.
• Engeland, Kolbjørn; Wilson, Donna; Borsanyi, Peter; Roald, Lars & Holmqvist, Erik (2018). Use of historical data in flood frequency analysis: A case study for four catchments in Norway. Hydrology Research.  ISSN 1998-9563.  49(2), s 450- 465 . doi: 10.2166/nh.2017.069
• Kobierska-Baffie, Florian Antoine; Engeland, Kolbjørn & Thorarinsdottir, Thordis Linda (2018). Evaluation of design flood estimates - a case study for Norway. Hydrology Research.  ISSN 1998-9563.  49(2), s 450- 465 . doi: 10.2166/nh.2017.068 Fulltekst i vitenarkiv. Vis sammendrag

  The aim of this study was to evaluate the predictive fit of probability distributions to annual maximum flood data, and in particular to evaluate (i) which combination of distribution and estimation method gives the best fit and (ii) whether the answer to (i) depends on record length. These aims were achieved by assessing the sensitivity to record length of the predictive performance of several probability distributions. A bootstrapping approach was used by resampling (with replacement) record lengths of 30 to 90 years (50 resamples for each record length) from the original record and fitting distributions to these subsamples. Subsequently, the fits were evaluated according to several goodness-of-fit measures and to the variability of the predicted flood quantiles. Our initial hypothesis that shorter records favor two-parameter distributions was not clearly supported. The ordinary moments method was the most stable while providing equivalent goodness-of-fit.

• Thorarinsdottir, Thordis Linda; Hellton, Kristoffer Herland; Steinbakk, Gunnhildur Högnadóttir; Schlichting, Lena & Engeland, Kolbjørn (2018). Bayesian regional flood frequency analysis for large catchments. Water Resources Research.  ISSN 0043-1397.  54(9), s 6929- 6947 . doi: 10.1029/2017WR022460 Vis sammendrag

  Regional flood frequency analysis is commonly applied in situations where there exists insufficient data at a location for a reliable estimation of flood quantiles. We develop a Bayesian hierarchical modeling framework for a regional analysis of data from 203 large catchments in Norway with the generalized extreme value distribution as the underlying model. Generalized linear models on the parameters of the generalized extreme value distribution are able to incorporate location‐specific geographic and meteorological information and thereby accommodate these effects on the flood quantiles. A Bayesian model averaging component additionally assesses model uncertainty in the effect of the proposed covariates. The resulting regional model is seen to give substantially better predictive performance than the regional model currently used in Norway.

• Devoli, Graziella; Jørandli, L.; Engeland, Kolbjørn & Tallaksen, Lena M. (2017). Large-Scale Synoptic Weather Types and Precipitation Responsible for Landslides in Southern Norway., In Matjaž Mikoš; Nicola Casagli; Yueping Yin & Kyoji Sassa (ed.),  Advancing Culture of Living with Landslides: Volume 4 Diversity of Landslide Forms.  Springer Publishing Company.  ISBN 978-3-319-53485-5.  17.  s 159 - 167
• Engeland, Kolbjørn; Borga, Marco; Cretuin, Jean-Domenique; François, Baptiste; Ramos, Maria-Helena & Vidal, Jean-Philippe (2017). Space-time variability of climate variables and intermittent renewable electricity production – A review. Renewable & Sustainable Energy Reviews.  ISSN 1364-0321.  79, s 600- 617 . doi: 10.1016/j.rser.2017.05.046 Fulltekst i vitenarkiv. Vis sammendrag

  A major part of renewable electricity production is characterized by a large degree of intermittency driven by the natural variability of climate factors such as air temperature, wind velocity, solar radiation, precipitation, evaporation, and river runoff. The main strategies to handle this intermittency include energy-storage, -transport, -diversity and -information. The three first strategies smooth out the variability of production in time and space, whereas the last one aims a better balance between production and demand. This study presents a literature review on the space-time variability of climate variables driving the intermittency of wind-, solar- and hydropower productions and their joint management in electricity systems. A vast body of studies pertains to this question bringing results covering the full spectrum of resolutions and extents, using a variety of data sources, but mostly dealing with a single source. Our synthesis highlights the consistency of these works, and, besides astronomic forcing, we identify three broad climatic regimes governing the variability of renewable production and load. At sub-daily time scales, the three considered renewables have drastically different pattern sizes in response to small scale atmospheric processes. At regional scales, large perturbation weather patterns consistently control wind and solar production, hydropower having a clearly distinct type of pattern. At continental scales, all renewable sources and load seem to display patterns of constant space characteristics and no indication of marked temporal trends.

• Bakken, Tor Haakon; Modahl, Ingunn Saur; Engeland, Kolbjørn; Raadal, Hanne Lerche & Arnøy, Silje (2016). The life-cycle water footprint of two hydropower projects in Norway. Journal of Cleaner Production.  ISSN 0959-6526.  113, s 241- 250 . doi: 10.1016/j.jclepro.2015.12.036 Vis sammendrag

  The life-cycle water consumption is calculated for two Norwegian hydropower plants, one is a typical run-of-river plant located in southern Norway (Embretsfoss 4) and the second a reservoir-based plant located in mid-Norway (Trollheim). Applying the net evaporation approach, the water consumption values are 0.15 l/kWh for Embretsfoss 4 and 0.19 l/kWh for Trollheim, which are very low compared to earlier published studies. Dividing the life-cycle phases, the water consumption originating from the operational phase constitutes of 37.9% for Embretsfoss 4 and 84.5% for Trollheim of the total net water consumption. The net water consumption rates are very low compared to the gross rates for the two projects, i.e. only 0.2% for Embretsfoss 4 and 4.2% for Trollheim and much lower than similar comparative studies. The water consumption is further regionalized and the impact calculated by use of five different characterizations ('water-scarcity') methods, lowering the water consumption rates further due to the low characterization factors of Norway. Three of the five applied methods and the life-cycle inventory (LCI) provide a consistent picture with respect to the relative contribution of water consumption from the various elements of the life-cycle phases. The spatial boundaries of the study are set wider than most similar studies, by including a larger part of the regulated system than only the power plant and the reservoir located in the immediate vicinity of the plant. According the authors' knowledge, this is also the first well-documented study comparing the water consumption from the various lifecycle phases. Copyright © 2015 Elsevier Ltd. All rights reserved.

• Engeland, Kolbjørn; Steinsland, Ingelin; Johansen, Stig; Petersen-Øverleir, Asgeir & Kolberg, Sjur (2016). Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway. Journal of Hydrology.  ISSN 0022-1694.  536, s 147- 160 . doi: 10.1016/j.jhydrol.2016.02.036 Vis sammendrag

  In this study, we explore the effect of uncertainty and poor observation quality on hydrological model calibration and predictions. The Osali catchment in Western Norway was selected as case study and an elevation distributed HBV-model was used. We systematically evaluated the effect of accounting for uncertainty in parameters, precipitation input, temperature input and streamflow observations. For precipitation and temperature we accounted for the interpolation uncertainty, and for streamflow we accounted for rating curve uncertainty. Further, the effects of poorer quality of precipitation input and streamflow observations were explored. Less information about precipitation was obtained by excluding the nearest precipitation station from the analysis, while reduced information about the streamflow was obtained by omitting the highest and lowest streamflow observations when estimating the rating curve. The results showed that including uncertainty in the precipitation and temperature inputs has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Less information in precipitation input resulted in a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions, giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using streamflow observations based on different rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions, the best evaluation scores were not achieved for the rating curve used for calibration, but for rating curves giving smoother streamflow observations. Less information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores by giving both better and worse scores. © 2016 Elsevier B.V.

• Hegdahl, Trine Jahr; Tallaksen, Lena M.; Engeland, Kolbjørn; Burkhart, John & Xu, Chong-Yu (2016). Discharge sensitivity to snowmelt parameterization: A case study for Upper Beas basin in Himachal Pradesh, India. Hydrology Research.  ISSN 1998-9563.  47(4), s 683- 700 . doi: 10.2166/nh.2016.047
• Steinbakk, Gunnhildur Högnadóttir; Thorarinsdottir, Thordis Linda; Reitan, Trond; Schlichting, Lena; Hølleland, Sondre & Engeland, Kolbjørn (2016). Propagation of rating curve uncertainty in design flood estimation. Water Resources Research.  ISSN 0043-1397.  52(9), s 6897- 6915 . doi: 10.1002/2015WR018516 Vis sammendrag

  Statistical flood frequency analysis is commonly performed based on a set of annual maximumdischarge values which are derived from stage measurements via a stage-discharge rating curve model.Such design flood estimation techniques often ignore the uncertainty in the underlying rating curve model.Using data from eight gauging stations in Norway, we investigate the effect of curve and sample uncertain-ty on design flood estimation by combining results from a Bayesian multisegment rating curve model and aBayesian flood frequency analysis. We find that sample uncertainty is the main contributor to the designflood estimation uncertainty. However, under extrapolation of the rating curve, the uncertainty bounds forboth the rating curve model and the flood frequency analysis are highly skewed and ignoring these featuresmay underestimate the potential risk of flooding. We expect this effect to be even more pronounced in aridand semiarid climates with a higher variability in floods.

• Engeland, Kolbjørn & Steinsland, Ingelin (2014). Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times. Water Resources Research.  ISSN 0043-1397.  50(1), s 182- 197 . doi: 10.1002/2012WR012757 Vis sammendrag

  This paper introduces a methodology for the construction of probabilistic inflow forecasts for multiple catchments and lead times. A postprocessing approach is used, and a Gaussian model is applied for transformed variables. In operational situations, it is a straightforward task to use the models to sample inflow ensembles which inherit the dependencies between catchments and lead times. The methodology was tested and demonstrated in the river systems linked to the Ulla-Førre hydropower complex in southern Norway, where simultaneous probabilistic forecasts for five catchments and ten lead times were constructed. The methodology exhibits sufficient flexibility to utilize deterministic flow forecasts from a numerical hydrological model as well as statistical forecasts such as persistent forecasts and sliding window climatology forecasts. It also deals with variation in the relative weights of these forecasts with both catchment and lead time. When evaluating predictive performance in original space using cross-validation, the case study found that it is important to include the persistent forecast for the initial lead times and the hydrological forecast for medium-term lead times. Sliding window climatology forecasts become more important for the latest lead times. Furthermore, operationally important features in this case study such as heteroscedasticity, lead time varying between lead time dependency and lead time varying between catchment dependency are captured. ©2013. American Geophysical Union. All Rights Reserved.

• Francois, B.; Borga, M.; Anquetin, S.; Creutin, Jean Domenique; Engeland, Kolbjørn; Favre, A.C.; Hingray, B.; Ramos, M.H.; Raynaud, D.; Renard, Benjamin; Sauquet, E.; Sauterleute, Julian; Vidal, J.P. & Warland, Geir (2014). Integrating hydropower and intermittent climate-related renewable energies: a call for hydrology. Hydrological Processes.  ISSN 0885-6087.  28(21), s 5465- 5468 . doi: 10.1002/hyp.10274
• Abdella, Yisak Sultan & Engeland, Kolbjørn (2013). Bruk av værradardata for beregning av gjentaksintervallkart for ekstreme nedbørshendelser. Vann.  ISSN 0042-2592.  48(2), s 162- 174
• Bakken, Tor Haakon; Killingtveit, Ånund; Engeland, Kolbjørn; Alfredsen, Knut & Harby, Atle (2013). Water consumption from hydropower plants – review of published estimates and an assessment of the concept. Hydrology and Earth System Sciences.  ISSN 1027-5606.  17, s 3983- 4000 . doi: 10.5194/hess-17-3983-2013 Fulltekst i vitenarkiv.
• Bakken, Tor Haakon; Killingtveit, Ånund; Engeland, Kolbjørn; Alfredsen, Knut & Harby, Atle (2013). Water consumption from hydropower plants – review of published estimates and an assessment of the concept. Hydrology and Earth System Sciences Discussions.  ISSN 1812-2108.  10, s 8071- 8115 . doi: 10.5194/hessd-10-8071-2013 Fulltekst i vitenarkiv.
• Bakken, Tor Haakon; Killingtveit, Ånund; Engeland, Kolbjørn; Alfredsen, Knut & Harby, Atle (2013). Water consumption from hydropower production: review of published estimates, In Andreas Schumann (ed.),  Considering Hydrological Change in Reservoir Planning and Management.  IAHS Press.  ISBN 978-1-907161-40-7.  Paper.  s 155 - 160 Vis sammendrag

  This paper presents an extensive review of all known published literature on water consumption from hydropower plants. The paper documents that the estimates show a large variation, from close to zero m3/MWh to more than 3500 m3/MWh, where the maximum values are far beyond the published values by IPCC (2011). The highest values are from irrigation reservoirs with very limited hydropower production. The review reveals that there is no consistent methodological approach in place, which is a major obstacle in making a fair comparison between hydropower projects, and ultimately between technologies.

• Li, Lu; Xu, Chong-Yu & Engeland, Kolbjørn (2013). Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling. Journal of Hydrology.  ISSN 0022-1694.  486, s 384- 394 . doi: 10.1016/j.jhydrol.2013.02.002 Vis sammendrag

  With respect to model calibration, parameter estimation and analysis of uncertainty sources, various regression and probabilistic approaches are used in hydrological modeling. A family of Bayesian methods, which incorporates different sources of information into a single analysis through Bayes' theorem, is widely used for uncertainty assessment. However, none of these approaches can well treat the impact of high flows in hydrological modeling. This study proposes a Bayesian modularization uncertainty assessment approach in which the highest streamflow observations are treated as suspect information that should not influence the inference of the main bulk of the model parameters. This study includes a comprehensive comparison and evaluation of uncertainty assessments by our new Bayesian modularization method and standard Bayesian methods using the Metropolis-Hastings (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions were used in combination with standard Bayesian method: the AR(1) plus Normal model independent of time (Model 1), the AR(1) plus Normal model dependent on time (Model 2) and the AR(1) plus Multi-normal model (Model 3). The results reveal that the Bayesian modularization method provides the most accurate streamflow estimates measured by the Nash-Sutcliffe efficiency and provide the best in uncertainty estimates for low, medium and entire flows compared to standard Bayesian methods. The study thus provides a new approach for reducing the impact of high flows on the discharge uncertainty assessment of hydrological models via Bayesian method. © 2013 Elsevier B.V

• Gudmundsson, Lukas; Wagener, Thorsten; Tallaksen, Lena M. & Engeland, Kolbjørn (2012). Evaluation of nine large-scale hydrological models with respect to the seasonal runoff climatology in Europe. Water Resources Research.  ISSN 0043-1397.  48(11) . doi: 10.1029/2011WR010911 Vis sammendrag

  Large-scale hydrological models, simulating the terrestrial water cycle on continental and global scales, are fundamental for many studies in earth system sciences. However, due to imperfect knowledge of real world systems, the models cannot be expected to capture all aspects of large-scale hydrology equally well. To gain insights in the strengths and shortcomings of nine large-scale hydrological models, we assessed their ability to capture the mean annual runoff cycle. Unlike most other studies that rely on discharge observations from continental scale river basins, our study is based on observed runoff from a large number of small, near-natural catchments in Europe. We evaluated the models’ ability to capture the average magnitude, the amplitude, as well as the timing of the mean annual runoff cycle. Our study revealed large uncertainties when modeling runoff from these small catchments. We identified large differences in model performance, however, the ensemble mean (mean of all model simulations) yielded rather robust predictions. Model performance varied systematically with climatic conditions and was best in regions with little influence of snow. In cold regions, many models exhibited low correlations between observed and simulated mean annual cycles, which can be associated with shortcomings in simulating the timing of snow accumulation and melt. Local (grid cell) scale differences between observed and simulated runoff can be large and local biases often exceeded 100%. These local uncertainties are contrasted by a relatively good regional average performance, ultimately reflecting the purpose of the models, i.e., to capture regional hydroclimatology.

• Li, Lu; Xu, Chong-Yu; Xia, Juan; Engeland, Kolbjørn & Reggiani, Paolo (2011). Uncertainty estimates by Bayesian method with likelihood of AR (1) plus Normal model and AR (1) plus Multi-Normal model in different time-scales hydrological models. Journal of Hydrology.  ISSN 0022-1694.  406(1-2), s 54- 65 . doi: 10.1016/j.jhydrol.2011.05.052
• Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin & Kolberg, Sjur (2010). Evaluation of statistical models for forecast errors from the HBV model. Journal of Hydrology.  ISSN 0022-1694.  384(1-2), s 142- 155 . doi: 10.1016/j.jhydrol.2010.01.018
• Engeland, Kolbjørn & Hisdal, Hege (2009). A Comparison of Low Flow Estimates in Ungauged Catchments Using Regional Regression and the HBV-Model. Water resources management.  ISSN 0920-4741.  23(12), s 2567- 2586 . doi: 10.1007/s11269-008-9397-7 Fulltekst i vitenarkiv.
• Engeland, Kolbjørn; Braud, Isabel; Gottschalk, Lars & Leblois, Etienne (2006). Multi-objective regional modelling. Journal of Hydrology.  ISSN 0022-1694.  327, s 339- 351
• Engeland, Kolbjørn; Xu, Chong-yu & Gottschalk, Lars (2005). Assessing uncertainties in a conceptual water balance model using Bayesian methodology. Hydrological Sciences Journal.  ISSN 0262-6667.  50(1), s 45- 63
• Engeland, Kolbjørn; Hisdal, Hege & Frigessi, Arnoldo (2004). Practical Extreme value Modelling of Hydrological Floods and Droughts: a case study. Extremes.  ISSN 1386-1999.  7, s 5- 30

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• Engeland, Kolbjørn & Alfredsen, Knut (ed.) (2020). Hydrology and Water Resources Management in a Changing World. IWA Publishing.  ISBN 9781789062168.  240 s.
• Alfredsen, Knut; Xu, Chong-Yu & Engeland, Kolbjørn (ed.) (2018). Nordic Hydrological Conference 2018. Hydrology and Water Resources Management in a Changing World. Norges vassdrags- og energidirektorat.  ISBN 978-82-410-1724-7.  130 s.

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• Engeland, Kolbjørn & Støren, Eivind Wilhelm Nagel (2021). Trollet under broen. Dagens næringsliv.  ISSN 0803-9372.
• Kjørstad, Elise; Paasche, Øyvind & Engeland, Kolbjørn (2021). Varmere klima kan bety færre storflommer i Glomma. Forskning.no.  ISSN 1891-635X.
• Engeland, Kolbjørn & Alfredsen, Knut (2020). Hydrology and water resources management in a changing world. Hydrology Research.  ISSN 1998-9563.  51(2), s 143- 145 . doi: 10.2166/nh.2020.000
• Engeland, Kolbjørn; Støren, Eivind Wilhelm Nagel; Aano, Anna & Paasche, Øyvind (2020). New flood frequency estimates for the largest river in Norway based on a novel combination of streamflow-, historical- and paleo-data.
• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2020). Using Bayesian geostatistical models to correct gridded hydrological products relative to the actually observed streamflow.
• Steinsland, Ingelin; Roksvåg, Thea & Engeland, Kolbjørn (2020). A new Bayesian hierarchical geostatistical model based on two spatial fields with case studies with short records of annual runoff in Norway.
• Engeland, Kolbjørn; Støren, Eivind Wilhelm Nagel & Aano, Anna (2019). Combining streamflow time series, historical information and paleodata in statistical flood frequency analysis – a case study from the Glomma river in Norway.
• Paasche, Øyvind; Øksnes, Monika; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Lu, Li; Engeland, Kolbjørn & Hirt, Ann M. (2019). Centennial shifts in flood frequency and magnitude over the last thousand years in Western Norway.
• Paasche, Øyvind; Øksnes, Monika; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Lu, Li; Engeland, Kolbjørn & Hirt, Ann Marie (2019). Adopting to new flood regimes: how the past can inform present day decision making.
• Paasche, Øyvind; Øksnes, Monika; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Lu, Li; Engeland, Kolbjørn & Hirt, Ann Marie (2019). Centennial shifts in flood frequency and magnitude over the last thousend years in Western Norway.
• Alfredsen, Knut; Xu, Chong-Yu & Engeland, Kolbjørn (ed.) (2018). Nordic Hydrological Conference 2018. Rapport (Norges vassdrags- og energidirektorat). 66-2018.
• Engeland, Kolbjørn & Holmqvist, Erik (2018). Flood frequency analysis including historical data: A case study for catchments in Norway.
• Engeland, Kolbjørn & Steinsland, Ingelin (2018). Flood frequency analysis - assessment of uncertainties in flood data, plotting positions and fitted distributions.
• Hegdahl, Trine Jahr; Engeland, Kolbjørn; Mueller, Malte & Sillmann, Jana (2018). Atmospheric River (AR) induced floods in western Norway under current and future climate. Geophysical Research Abstracts.  ISSN 1029-7006.  20
• Li, Lu; Pontoppidan, Marie Louise Nielsen; Engeland, Kolbjørn & Kolstad, Erik Wilhelm (2018). ASSESSMENT OF THE REGIONAL FUTURE PROJECTIONS OF FLOOD IN NORWAY BY PALEOCLIMATE DATA.
• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2018). Prediction of annual runoff by using a Bayesian geostatistical model for combining precipitation gauge observations and runoff observations.
• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2018). Prediction of annual runoff by using a Bayesian geostatistical model for combining precipitation gauge observations and runoff observations.
• Støren, Eivind Wilhelm Nagel; Engeland, Kolbjørn & Paasche, Øyvind (2018). Nye metoder gir økt kunnskap om flom. Naturen.  ISSN 0028-0887.  (6), s 267- 274 . doi: 10.18261/ISSN.1504-3118-2018-06-07
• Thorarinsdottir, Thordis Linda; Engeland, Kolbjørn; Lawrence, Deborah; Pedersen, Øyvind; Tveito, Ole Einar; Hellton, Kristoffer Herland; Dyrrdal, Anita Verpe; Eide, Vidar; Førland, Eirik; Holmqvist, Erik; Kobierska, Florian; Jørgensen, Sigrid; Midttømme, Grethe Holm; Moore, Richard; Nordtun, Kristian Strand; Orthe, Nils Kristian; Randen, Frode; Reitan, Trond; Ruther, Nils; Schlichting, Lena; Skaugen, Thomas; Steinbakk, Gunnhildur Högnadóttir; Voksø, Astrid; Væringstad, Thomas; Wang, Thea; Wilson, Donna & Ødemark, Karianne (2018). Nytt rammeverk for flomestimering i Norge: Sluttrapport fra forskningsprosjektet FlomQ.
• Thorarinsdottir, Thordis Linda; Hellton, Kristoffer Herland; Steinbakk, Gunnhildur Högnadóttir; Schlichting, Lena & Engeland, Kolbjørn (2018). Statistical estimation of extreme floods.
• Thorarinsdottir, Thordis Linda; Lenkoski, Alex; Hellton, Kristoffer Herland; Steinbakk, Gunnhildur Högnadóttir; Dyrrdal, Anita Verpe; Stordal, Frode; Schlichting, Lena & Engeland, Kolbjørn (2018). On developing general and efficient inference algorithms for complicated hierarchical models.
• Engeland, Kolbjørn & Holmqvist, Erik (2017). Lærdom fra flomhistorien. Forskning.no.  ISSN 1891-635X.
• Lawrence, Deborah; Thorarinsdottir, Thordis Linda; Paquet, Eric R.; Skaugen, Thomas & Engeland, Kolbjørn (2017). FlomQ: Improving flood estimation methods for dam safety in Norway.
• Roksvåg, Thea; Engeland, Kolbjørn & Steinsland, Ingelin (2017). A Bayesian spatial model for utilising precipitation gauge observations and runoff observations for annual runoff predictions.
• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2017). A Bayesian spatial model for utilising precipitation gauge observations and runoff observations for annual runoff predictions.
• Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Engeland, Kolbjørn; Kolstad, Erik Wilhelm; Paasche, Øyvind & Aano, Anna (2017). Integrating lake sediment paleoflood reconstructions in Norwegian flood frequency scenarios.
• Engeland, Kolbjørn (2016). Forbedret informasjonsgrunnlag for flomfrekvensanalyse of flomberegninger i NEVINA-plattformen.
• Kobierska, Florian & Engeland, Kolbjørn (2016). Evaluation of design flood estimates with respect to sample size.
• Engeland, Kolbjørn (2015). FLOMQ, siste nytt fra prosjektet.
• Engeland, Kolbjørn (2015). Flood frequency analysis – the challenge of using historical data.
• Engeland, Kolbjørn; Tallaksen, Lena M.; Bakken, Tor Haakon & Killingtveit, Ånund (2015). Water footprint of hydro power in Norway. Vis sammendrag

  The IPCC Special Report on Renewable Energy (IPCC, 2012) assesses the potential for renewable energy sources to replace fossil-based fuels and benchmarks the technologies with respect to a set of criteria, including their water footprint measured as m3/MWh. While most of the renewable technologies show a typical range of 1-5 m3/MWh, the very sparse data on hydropower range from a minimum of 0.04 to a maximum of 209 m3/MWh. More recent studies on water footprint from hydropower indicate that the water consumption rates could go even far beyond the numbers published by IPCC (2012). The methodological approach behind these numbers are, however, criticized as it appears over-simplistic and several issues need to be defined and clarified in order to present the ’true picture’ of the water footprint of hydropower. Despite this, the rather high numbers for hydropower may imply a reputational risk for the sector and also be a direct investment risk in new projects if hydropower is considered a "large-scale water consumer". Estimation of water footprint has two important components (i) definition of water footprint (including system boundaries), and (ii) estimation of evaporation, which is assumed to constitute the main water loss from hydropower. Here we will mainly address the second topic and have chosen to use a water footprint definition based on net evapotranspiration from reservoirs. Thus, we need estimates of evapotranspiration from the land surface prior to inundation and the evaporation from the reservoir after it has been filled up. The primary objective of the study is to estimate water footprint of hydropower in Norway and in particular to answer the following questions: (i) How does different environmental variables influence water footprint estimation in Norway?, and in particular (ii) What is the total/specific water footprint from Norwegian hydropower production? To answer these questions we tested how environmental variables like climate and vegetation characteristics influence the estimated net evaporation and water footprint estimates by systematically varying their values. The water footprint was estimated for a subset of hydropower complex for which GIS data sets with land use prior to construction of reservoirs were available. The presentation will focus on the differences in evaporation from reservoirs and evapotranspiration from various land surfaces.

• Engeland, Kolbjørn; Warland, Geir; Borga, Marco; Creutin, Jean-Dominique & Ramos, Maria-Helena (2015). Space-time dependence between energy sources and climate related energy production.
• Modahl, Ingunn Saur; Raadal, Hanne Lerche; Bakken, Tor Haakon & Engeland, Kolbjørn (2015). Regionalisation of water consumption and the effect on water footprint results for hydropower.
• Schlichting, Lena; Vormoor, Klaus & Engeland, Kolbjørn (2015). Estimation of flood generating processes in gauged catchments.
• Bakken, Tor Haakon; Engeland, Kolbjørn & Killingtveit, Ånund (2014). Review of water consumption estimates and the importance of evaporation.
• Engeland, Kolbjørn (2014). Vannforbruk og fordampningsberegninger.
• Engeland, Kolbjørn; Tøfte, Lena S; Warland, Geir; Borga, Marco; Jean-Dominique, Creutin & Ramos, Maria-Helena (2014). Space-time dependence between energy sources and climate related energy production.
• Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S & Bruland, Oddbjørn (2013). Parameter identifiability and regional calibration for reservoir inflow prediction.
• Steinsland, Ingelin & Engeland, Kolbjørn (2013). Temporal-spatial post processing models for probabilistic inflow forecasts combining hydrological and persistent forecasts with inflow climatology.
• Bruland, Oddbjørn; Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S; Gragne, Ashenafi Seifu; Alfredsen, Knut & Liston, Glen (2012). Updating of states in operational hydrological models.
• Bruland, Oddbjørn; Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S; Gragne, Ashenafi Seifu; Liston, Glen; Sand, Knut & Alfredsen, Knut (2012). Updating of states in operational hydrological models. Geophysical Research Abstracts.  ISSN 1029-7006.  14 Vis sammendrag

  Operationally the main purpose of hydrological models is to provide runoff forecasts. The quality of the model state and the accuracy of the weather forecast together with the model quality define the runoff forecast quality. Input and model errors accumulate over time and may leave the model in a poor state. Usually model states can be related to observable conditions in the catchment. Updating of these states, knowing their relation to observable catchment conditions, influence directly the forecast quality. Norway is internationally in the forefront in hydropower scheduling both on short and long terms. The inflow forecasts are fundamental to this scheduling. Their quality directly influence the producers profit as they optimize hydropower production to market demand and at the same time minimize spill of water and maximize available hydraulic head. The quality of the inflow forecasts strongly depends on the quality of the models applied and the quality of the information they use. In this project the focus has been to improve the quality of the model states which the forecast is based upon. Runoff and snow storage are two observable quantities that reflect the model state and are used in this project for updating. Generally the methods used can be divided in three groups: The first re-estimates the forcing data in the updating period; the second alters the weights in the forecast ensemble; and the third directly changes the model states. The uncertainty related to the forcing data through the updating period is due to both uncertainty in the actual observation and to how well the gauging stations represent the catchment both in respect to temperatures and precipitation. The project looks at methodologies that automatically re-estimates the forcing data and tests the result against observed response. Model uncertainty is reflected in a joint distribution of model parameters estimated using the Dream algorithm.

• Engeland, Kolbjørn; Abdella, Yisak Sultan; Lepioufle, Jean-Marie & Grønsleth, Martin (2012). Sluttrapport for værradarprosjektet. SINTEF Energi. Rapport. TR A7185.
• Engeland, Kolbjørn; Killingtveit, Ånund; Bakken, Tor Haakon; Alfredsen, Knut & Harby, Atle (2012). Water use in Hydropower Reservoirs - a Review.
• Engeland, Kolbjørn & Lepioufle, Jean-Marie (2012). Evaluation of radar-derived precipitation estimates using runoff simulation. SINTEF Energi. Rapport. TR A7184.
• Bruland, Oddbjørn; Sand, Knut; Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S & Liston, Glen (2011). Development and testing of model updating techniques for the Hydropower industry in Norway.
• Tøfte, Lena S & Engeland, Kolbjørn (2010). Hydrological modeling for environmental studies -challenges and examples from Norway.
• Bruland, Oddbjørn; Tøfte, Lena S; Engeland, Kolbjørn & Kolberg, Sjur (2009). ENKI – Operational hydrological forecasting system.
• Engeland, Kolbjørn (2008). Flomsikring av boligområder i Oppdal kommune. Vis sammendrag

  Forslag til ny løsning for drenering og bortleding av overvann i Oppdal gjennomgås. Dimensjonerende flom beregnes for kritiske kulverter og bekker, og det anbefales dimensjoner på kulverter og nye bekkeløp. Denne rapporten er ikke en detaljert prosjektering av en eventuell utbygging. Skal tiltakene gjennomføres bør det søkes assistanse fra konsulentbyrå med kompetanse innenfor detaljprosjektering av bygg- og anlegg og landskapsarkitektur. Følgende konklusjoner og anbefalinger gis:• Ekstrem regnnedbør antas å bestemme størrelsen på 200-års flommen.• Arealet som dreneres gjennom Oppdal sentrum reduseres med 77 %. Mens arealet som drenerer gjennom bekkeinntaket ved BOAS reduseres med 31 %. Ønsker man at mer flomvann skal ledes utenom BOAS kan man enten overføre vann vestover fra 2.4 til 1.2 eller forlenge vannvegen ved 2.1 vestover slik at en større del drenerer via østlige vannveg.• I beregningene er det ikke tatt hensyn til alternative flomveger eller eventuelle flomreduserende tiltak som fordrøyningsbasseng. Det bør vurderes å bygge forsinkelsesbasseng som flomreduserende tiltak. I østre vannveg kan dette gjøres oppstrøms punkt 2.0 og oppstrøms E6 og i vestre vannveg kan det vurderes mellom 1.3 og 1.1.• Det er gitt anbefalinger for dimensjoner, utforming av innløp og erosjonssikring av utløp for kulvertene. Kulvertene bør sikres med rister og rekkverk. Flere av kulvertene bør detaljprosjekteres.• Det er gitt anbefalinger for dimensjonering og materialbruk ved utforming av nye vannveger. Flere av strekkene, spesielt de bratteste partiene, bør detaljprosjekteres.• Det bør planlegges for alternative flomveier.• Ved nybygging bør lokal behandling av overvann tas med i reguleringsplaner slik at flommer reduseres betraktelig.

• Tøfte, Lena S; Engeland, Kolbjørn; Bruaset, Stian & Hafskjold, Leif Sigurd (2008). Flomsikring av boligområder i Oppdal kommune.
• Tøfte, Lena S; Kolberg, Sjur & Engeland, Kolbjørn (2008). En fordelt hydrologisk modell til Statkraft. Utvikling og simuleringer.
• Engeland, Kolbjørn; Braud, Isabel; Gottschalk, Lars & Leblois, Etienne (2004). Regionalisation of streamflow statistics using a rainfall-runoff model.

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