Kolbjørn Engeland

• Barna, Danielle Marie; Engeland, Kolbjørn; Kneib, Thomas; Thorarinsdottir, Thordis Linda & Xu, Chong-Yu (2026). Regional flood frequency analysis at multiple durations: A comparison of duration consistency in quantile and parameter regression techniques. Hydrology Research. ISSN 1998-9563. 57(5). doi: 10.1016/j.hydrch.2026.100002. Full text in Research Archive
• Alipour, Saba Mirza; Engeland, Kolbjørn & Leal, J B (2023). Uncertainty analysis of 100-year flood maps under climate change scenarios. Journal of Hydrology. ISSN 0022-1694. 628. doi: 10.1016/j.jhydrol.2023.130502. Full text in Research Archive
• Barna, Danielle Marie; Engeland, Kolbjørn; Thorarinsdottir, Thordis Linda & Xu, Chong-Yu (2023). Flexible and consistent Flood–Duration–Frequency modeling: A Bayesian approach. Journal of Hydrology. ISSN 0022-1694. 620. doi: 10.1016/j.jhydrol.2023.129448. Full text in Research Archive Show summary

  Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Many hydrologic applications where flood retention is important, e.g. floodplain management and reservoir design, need design flood values for different durations. Flood–Duration–Frequency (QDF) models extend the standard statistical flood frequency analysis framework to multiple flood durations and are analogous to intensity–duration–frequency models for precipitation. Implementations of QDF models commonly assume simple scaling, where only the magnitude of the index flood is assumed to change with duration, despite empirical analyses showing a more complex dependence structure. We propose a multiscaling extension to existing QDF models where the magnitude of the index flood and the slope of the growth curve may scale independently with duration. In an application to 12 locations in Norway, we assess how three different QDF models capture relationships between floods of different duration. Incorporating duration dependency independently in both the index flood and the growth curve (extended QDF model) improves modeling of both short-duration events and events with long return periods. This model extension further expands the models’ ability to simultaneously model a wide range of durations. As measured by the integrated quadratic distance, the extended QDF model performs better than the original QDF model in 83% of the out of sample subdaily durations studied. Additionally, we find that the choice of durations used to fit QDF models is a highly influential aspect of the modeling process.

• Hegdahl, Trine Jahr; Engeland, Kolbjørn; Steinsland, Ingelin & Singleton, Andrew (2023). Pre- and postprocessing flood forecasts using Bayesian model averaging. Hydrology Research. ISSN 1998-9563. 54(2), p. 116–135. doi: 10.2166/nh.2023.024. Full text in Research Archive Show summary

  In this study, pre- and postprocessing of hydrological ensemble forecasts are evaluated with a special focus on floods for 119 Norwegian catchments. Two years of ECMWF ensemble forecasts of temperature and precipitation with a lead time of up to 9 days were used to force the operational hydrological HBV model to establish streamflow forecasts. A Bayesian model averaging processing approach was applied to preprocess temperature and precipitation forecasts and for postprocessing streamflow forecasts. Ensemble streamflow forecasts were generated for eight schemes based on combinations of raw, preprocessed, and postprocessed forecasts. Two datasets were used to evaluate the forecasts: (i) all streamflow forecasts and (ii) forecasts for flood events with streamflow above mean annual flood. Evaluations based on all streamflow data showed that postprocessing improved the forecasts only up to a lead time of 2–3 days, whereas preprocessing temperature and precipitation improved the forecasts for 50–90% of the catchments beyond 3 days' lead time. We found large differences in the ability to issue warnings between spring and autumn floods. Spring floods had predictability for up to 9 days for many events and catchments, whereas the ability to predict autumn floods beyond 3 days was marginal.

• Rosbjerg, Dan; Engeland, Kolbjørn; Førland, Eirik; Haghighi, Ali Torabi; Mehr, Ali Danandeh & Olsson, Jonas (2022). Nordic contributions to stochastic methods in hydrology. Nordic Hydrology. ISSN 0029-1277. 53(6), p. 840–866. doi: 10.2166/nh.2022.137. Full text in Research Archive Show summary

  The paper presents prominent Nordic contributions to stochastic methods in hydrology and water resources during the previous 50 years. The development in methods from analysis of stationary and independent hydrological events to include non-stationarity, risk analysis, big data, operational research and climate change impacts is hereby demonstrated. The paper is divided into four main sections covering flood frequency and drought analyses, assessment of rainfall extremes, stochastic approaches to water resources management and approaches to climate change and adaptation efforts. It is intended as a review paper referring to a rich selection of internationally published papers authored by Nordic hydrologists or hydrologists from abroad working in a Nordic country or in cooperation with Nordic hydrologists. Emerging trends in needs and methodologies are highlighted in the conclusions.

• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2022). A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 26(20), p. 5391–5410. doi: 10.5194/hess-26-5391-2022. Full text in Research Archive Show summary

  We present a Bayesian geostatistical model for mean annual runoff that incorporates simulations from a process-based hydrological model. The simulations are treated as a covariate and the regression coefficient is modeled as a spatial field. This way the relationship between the covariate (simulations from a hydrological model) and the response variable (observed mean annual runoff) can vary in the study area. A preprocessing step for including short records in the modeling is also suggested. We thus obtain a model that can exploit several data sources. By using state-of-the-art statistical methods, fast inference is achieved. The geostatistical model is evaluated by estimating mean annual runoff for the period 1981–2010 for 127 catchments in Norway based on observations from 411 catchments. Simulations from the process-based HBV model on a 1×1 km grid are used as input. We found that on average the proposed approach outperformed a purely process-based approach (HBV) when predicting runoff for ungauged and partially gauged catchments. The reduction in RMSE compared to the HBV model was 20 % for ungauged catchments and 58 % for partially gauged catchments, where the latter is due to the preprocessing step. For ungauged catchments the proposed framework also outperformed a purely geostatistical method with a 10 % reduction in RMSE compared to the geostatistical method. For partially gauged catchments, however, purely geostatistical methods performed equally well or slightly better than the proposed combination approach. In general, we expect the proposed approach to outperform geostatistics in areas where the data availability is low to moderate.

• Nilsen, Irene Brox; Dyrrdal, Anita Verpe; Roksvåg, Thea; Lutz, Julia & Engeland, Kolbjørn (2022). Styrtregn og styrtflom: Hvordan kan vi unngå skader? Naturen. ISSN 0028-0887. 146(1), p. 48–55. doi: 10.18261/naturen.146.1.6. Full text in Research Archive Show summary

  Samfunnet er sårbart for ekstremnedbør og flom, som vi har sett blant annet i Tyskland sommeren 2021 og i Oslo i 2019. En spesielt kraftig regnhendelse som har fått lite oppmerksomhet fordi den ikke traff tettbygd strøk, var Fulufjället i august 1997. I denne teksten tar vi utgangspunkt i kraftige nedbørhendelser og beskriver noen av utfordringene ved å unngå skader på infrastruktur og bygninger. Vi beskriver særlig hvordan vi kan beregne riktig dimensjonerende regn og dimensjonerende flom, særlig i områder der det ikke finnes målinger av kraftig nedbør, eller der måleseriene er korte. Her beskriver vi hvordan begrensninger i datagrunnlaget slår ut på gjentaksintervallet. For en kommune eller infrastruktureier er det også av interesse å utvide perspektivet fra punktvise beregninger til å finne ut hvor ofte et areal eller en strekning vil kunne oppleve en tohundreårsflom.

• Huo, Ran; Li, Lu; Engeland, Kolbjørn; Xu, Chong-Yu; Chen, Hua & Paasche, Øyvind [Show all 7 contributors for this article] (2022). Changing flood dynamics in Norway since the last millennium and to the end of the 21st century. Journal of Hydrology. ISSN 0022-1694. 613, p. 128331–128331. doi: 10.1016/j.jhydrol.2022.128331. Full text in Research Archive Show summary

  With the recent warming trend over Europe and the Arctic, the Nordic regions have experienced more frequent and damaging extreme hydrological events which are anticipated to increase towards the end of the 21st century. Despite explicit trends, large variations have been observed across basins and regions when it comes to precipitation and floods hinting at a strong natural hydroclimatic variability that further complicates any assessment of potential future changes. In this study, we aim to better understand how climate variability links with the current extremes and future projections of floods in Norway in the context of the last millennium and the future. Specifically, we simulate over 1000 years (850–2099) daily discharge and floods at 34 catchments over five regions of Norway from the last millennium (including a warm period and a cold period; 850–1849) to the end of the 21st century by an ensemble model-chain method including four global climate models (GCMs), two bias-correction methods and two hydrological models. The modelling results show (i) all GCMs except MIROC-ESM simulate a higher mean temperature in Medieval Climate Anomaly (MCA) period than Little Ice Age (LIA) period, while simulated annual precipitation varies a lot in different GCMs and catchments, (ii) no significant change of flood characteristics during the last millennium from ensemble-mean results, (iii) in future, we will have an extraordinary shift in flood seasonality and generating processes, and flood frequency increase in most of the study catchments in Norway, and (iv) climate projections represent the largest contribution to overall uncertainty in the projected changes in hydrological extremes for most of the catchments.

• Alipour, Saba Mirza; Engeland, Kolbjørn & Leal, J B (2021). A practical methodology to perform global sensitivity analysis for 2D hydrodynamic computationally intensive simulations. Hydrology Research. ISSN 1998-9563. 52(6), p. 1309–1327. doi: 10.2166/nh.2021.243. Full text in Research Archive Show summary

  Sensitivity analysis is a commonly used technique in hydrological modeling for different purposes, including identifying the influential parameters and ranking them. This paper proposes a simplified sensitivity analysis approach by applying the Taguchi design and the ANOVA technique to 2D hydrodynamic flood simulations, which are computationally intensive. This approach offers an effective and practical way to rank the influencing parameters, quantify the contribution of each parameter to the variability of the outputs, and investigate the possible interaction between the input parameters. A number of 2D flood simulations have been carried out using the proposed combinations by Taguchi (L27 and L9 orthogonal arrays) to investigate the influence of four key input parameters, namely mesh size, runoff coefficient, roughness coefficient, and precipitation intensity. The results indicate that the methodology is adequate for sensitivity analysis, and that the precipitation intensity is the dominant parameter. Furthermore, the model calibration based on local variables (cross-sectional water level) can be inaccurate to simulate global variables (flooded area).

• Johansson, Fanny Maria Ekblom; 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. 8. doi: 10.3389/feart.2020.00239. Full text in Research Archive Show summary

  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 830 cm-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 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 (4,100–3,140 cal. yr BP) compared with intervals with a few or no extreme floods (6,050–4,100 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.

• 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 (HESS). ISSN 1027-5606. 23(2), p. 723–739. doi: 10.5194/hess-23-723-2019. Full text in Research Archive Show summary

  In this study, we used meteorological ensemble forecasts as input to hydrological models to quantify the uncertainty in forecasted streamflow, with a particular focus on the effect of temperature forecast calibration on the streamflow ensemble forecast skill. In catchments with seasonal snow cover, snowmelt is an important flood-generating process. Hence, high-quality air temperature data are important to accurately forecast streamflows. The sensitivity of streamflow ensemble forecasts to the calibration of temperature ensemble forecasts was investigated using ensemble forecasts of temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) covering a period of nearly 3 years, from 1 March 2013 to 31 December 2015. To improve the skill and reduce biases of the temperature ensembles, the Norwegian Meteorological Institute (MET Norway) provided parameters for ensemble calibration, derived using a standard quantile mapping method where HIRLAM, a high-resolution regional weather prediction model, was used as reference. A lumped HBV (Hydrologiska Byråns Vattenbalansavdelning) model, distributed on 10 elevation zones, was used to estimate the streamflow. The results show that temperature ensemble calibration affected both temperature and streamflow forecast skill, but differently depending on season and region. We found a close to 1:1 relationship between temperature and streamflow skill change for the spring season, whereas for autumn and winter large temperature skill improvements were not reflected in the streamflow forecasts to the same degree. This can be explained by streamflow being less affected by subzero temperature improvements, which accounted for the biggest temperature biases and corrections during autumn and winter. The skill differs between regions. In particular, there is a cold bias in the forecasted temperature during autumn and winter along the coast, enabling a large improvement by calibration. The forecast skill was partly related to elevation differences and catchment area. Overall, it is evident that temperature forecasts are important for streamflow forecasts in climates with seasonal snow cover.

• 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), p. 450–465. doi: 10.2166/nh.2017.068. Full text in Research Archive Show summary

  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.

• 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), p. 450–465. doi: 10.2166/nh.2017.069. Full text in Research Archive
• 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), p. 6929–6947. doi: 10.1029/2017WR022460. Full text in Research Archive Show summary

  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.

• 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 and Sustainable Energy Reviews. ISSN 1364-0321. 79, p. 600–617. doi: 10.1016/j.rser.2017.05.046. Full text in Research Archive Show summary

  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.

• Devoli, Graziella; Jørandli, L.; Engeland, Kolbjørn & Tallaksen, Lena M. (2017). Large-Scale Synoptic Weather Types and Precipitation Responsible for Landslides in Southern Norway. In Mikoš, Matjaž; Casagli, Nicola; Yin, Yueping & Sassa, Kyoji (Ed.), Advancing Culture of Living with Landslides: Volume 4 Diversity of Landslide Forms. Springer Publishing Company. ISSN 9783319534855. p. 159–167. doi: 10.1007/978-3-319-53485-5_17. Full text in Research Archive Show summary

  This volume contains peer-reviewed papers from the Fourth World Landslide Forum organized by the International Consortium on Landslides (ICL), the Global Promotion Committee of the International Programme on Landslides (IPL), University of Ljubljana (UL) and Geological Survey of Slovenia in Ljubljana, Slovenia from May 29 to June 2, 2017. The complete collection of papers from the Forum is published in five full-color volumes.

• 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), p. 683–700. doi: 10.2166/nh.2016.047. Full text in Research Archive
• 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, p. 241–250. doi: 10.1016/j.jclepro.2015.12.036. Full text in Research Archive Show summary

  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, p. 147–160. doi: 10.1016/j.jhydrol.2016.02.036. Full text in Research Archive Show summary

  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.

• 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), p. 6897–6915. doi: 10.1002/2015WR018516. Full text in Research Archive Show summary

  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.

• Francois, B.; Borga, M.; Anquetin, S.; Creutin, Jean Domenique; Engeland, Kolbjørn & Favre, A.C. [Show all 14 contributors for this article] (2014). Integrating hydropower and intermittent climate-related renewable energies: a call for hydrology. Hydrological Processes. ISSN 0885-6087. 28(21), p. 5465–5468. doi: 10.1002/hyp.10274. Full text in Research Archive
• 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), p. 182–197. doi: 10.1002/2012WR012757. Full text in Research Archive Show summary

  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.

• Bakken, Tor Haakon; Killingtveit, Ånund; Engeland, Kolbjørn; Alfredsen, Knut & Harby, Atle (2013). Water consumption from hydropower production: review of published estimates. In Schumann, Andreas (Eds.), Considering Hydrological Change in Reservoir Planning and Management. IAHS Press. ISSN 9781907161407. p. 155–160. Full text in Research Archive Show summary

  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.

• Abdella, Yisak Sultan & Engeland, Kolbjørn (2013). Bruk av værradardata for beregning av gjentaksintervallkart for ekstreme nedbørshendelser. VANN. ISSN 0042-2592. 48(2), p. 162–174. Full text in Research Archive
• 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 (HESSD). ISSN 1812-2116. 10, p. 8071–8115. doi: 10.5194/hessd-10-8071-2013. Full text in Research Archive Show summary

  Since the report from IPCC on renewable energy (IPCC, 2012) was published; more studies on water consumption from hydropower have become available. The newly published studies do not, however, contribute to a more consistent picture on what the "true" water consumption from hydropower plants is. The dominant calculation method is the gross evaporation from the reservoirs divided by the annual power production, which appears to be an over-simplistic calculation method that possibly produces a biased picture of the water consumption of hydropower plants. This review paper shows that the water footprint of hydropower is used synonymously with water consumption, based on gross evaporation rates.

• 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, p. 384–394. doi: 10.1016/j.jhydrol.2013.02.002. Full text in Research Archive Show summary

  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

• 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 (HESS). ISSN 1027-5606. 17, p. 3983–4000. doi: 10.5194/hess-17-3983-2013. Full text in Research Archive Show summary

  Since the report from IPCC on renewable energy (IPCC, 2012) was published; more studies on water consumption from hydropower have become available. The newly published studies do not, however, contribute to a more consistent picture on what the “true” water consumption from hydropower plants is. The dominant calculation method is the gross evaporation from the reservoirs divided by the annual power production, which appears to be an oversimplistic calculation method that possibly produces a biased picture of the water consumption of hydropower plants. This review paper shows that the water footprint of hydropower is used synonymously with water consumption, based on gross evaporation rates. This paper also documents and discusses several methodological problems when applying this simplified approach (gross evaporation divided by annual power production) for the estimation of water consumption from hydropower projects. A number of short-comings are identified, including the lack of clarity regarding the setting of proper system boundaries in space and time. The methodology of attributing the water losses to the various uses in multi-purpose reservoirs is not developed. Furthermore, a correct and fair methodology for handling water consumption in reservoirs based on natural lakes is needed, as it appears meaningless that all the evaporation losses from a close-to-natural lake should be attributed to the hydropower production. It also appears problematic that the concept is not related to the impact the water consumption will have on the local water resources, as high water consumption values might not be problematic per se. Finally, it appears to be a paradox that a reservoir might be accorded a very high water consumption/footprint and still be the most feasible measure to improve the availability of water in a region. We argue that reservoirs are not always the problem; rather they may contribute to the solution of the problems of water scarcity. The authors consider that an improved conceptual framework is needed in order to calculate the water footprint from hydropower projects in a more reasonable way.

• 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. Full text in Research Archive Show summary

  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), p. 54–65. doi: 10.1016/j.jhydrol.2011.05.052. Full text in Research Archive
• 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), p. 142–155. doi: 10.1016/j.jhydrol.2010.01.018. Full text in Research Archive
• 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), p. 2567–2586. doi: 10.1007/s11269-008-9397-7. Full text in Research Archive

View all works in NVA

• Engeland, Kolbjørn & Alfredsen, Knut (2020). Hydrology and Water Resources Management in a Changing World. IWA Publishing. ISBN 9781789062168. 240 p. Full text in Research Archive
• Alfredsen, Knut; Xu, Chong-Yu & Engeland, Kolbjørn (2018). Nordic Hydrological Conference 2018. Hydrology and Water Resources Management in a Changing World. Norges vassdrags- og energidirektorat. ISBN 9788241017247. 130 p. Full text in Research Archive

View all works in NVA

• Huang, Shaochun; Silantyeva, Olga; Gelati, Emiliano; Yilmaz, Yeliz A.; Engeland, Kolbjørn & Tallaksen, Lena M. (2025). Quantifying the uncertainty of evapotranspiration estimates for unregulated Norwegian catchments using multiple hydrological models and remote sensing products. doi: 10.5194/egusphere-egu25-14913. Full text in Research Archive Show summary

  Previous studies show high uncertainty of evapotranspiration (ET) estimates for Norway, ranging from about 200 to more than 500 mm/year. It is partly due to sparce ET measurements in Norway to constrain the ET process in the hydrological modelling, and partly due to the uncertainty of precipitation (P) observations, especially in high mountainous regions with complex topography. In this study, we aim to quantify the uncertainty of ET estimates for 66 Norwegian catchments based on three hydrological models and four global remote sensing products. All the selected catchments are small (< 1000 km2), non-regulated and non-glacierized, with long-term discharge (Q) observations and runoff coefficient less than one (i.e. P>Q). These catchments differ substantially in climatic and hydrological characteristics and span the five hydrological regimes commonly used in Norway (Atlantic, Mountain, Inland, Baltic, and Transition). The three hydrological models (HBV, LISFLOOD and Shyft) are calibrated against daily discharge between 1981 and 2000 using three objective functions (KGE, KGE+LKGE, and KGE+BoxcoxKGE) and validated between 2001 and 2020 using six criteria (KGE, LKGE, BoxcoxKGE, percent Bias (PBias), and KGE &#160;and PBias in the snow free period). The latter two criteria are specifically selected to evaluate the model performance in simulating ET given the absence of direct ET measurements. The snow free period is identified for each catchment and year based on a daily fractional snow-covered area data at 500 m spatial resolution produced from a combined MODIS dataset (MOD10A1 and MYD10A1). The four global remote sensing estimates of ET are obtained from BESSV2, ETMonitor, PML_V2 and SSEBop_V2 datasets and they are available at fine spatial resolution (&#8804;0.05&#176;) and monthly time steps. The calibration and validation results show that the three hydrological models perform best using different objective functions for each hydrological regime and target variable (discharge and ET). The uncertainty ranges of annual mean ET are up to 177 mm based on all hydrological model results and remote sensing products. Using the best performing hydrological model results as the benchmark, all remote sensing products overestimate ET for the mountain regime and PML_V2 gives the best estimate for the other four hydrological regimes.

• Silantyeva, Olga; Ahlbäck, Malin; Yilmaz, Yeliz A.; Tallaksen, Lena M.; Lappegard, Gaute & Erlandsen, Helene B. [Show all 11 contributors for this article] (2024). SnowSub: Assessing snow sublimation for hydropower production in Norway. Project results at Snow Bridges workshop. Full text in Research Archive
• Gelati, Emiliano; Bakke, Sigrid Jørgensen; Engeland, Kolbjørn & Tallaksen, Lena Merete (2023). River discharge extremes in Norwegian regulated catchments: hydrologic model simulations including human interventions. Full text in Research Archive Show summary

  Slides: https://www.hydrologiraadet.no/wp-content/uploads/2023/10/1_Gelati.pdf In the coming years and decades, Norway will likely be affected by more frequent and severe extreme weather events, including both intense precipitation and drought. Predicting how these hazards will result in extreme high and low river discharge in a changing climate requires robust hydrologic models representing all relevant physical and human processes. While hydrologic modelling in catchments affected by human activities is more challenging than in pristine environments, it is mainly in the former that water-related natural hazards have the largest societal impacts. Therefore it is crucial to test and refine hydrologic predictions in human influenced catchments. We apply the spatially distributed hydrologic and water resources model LISFLOOD to regulated Norwegian catchments, aiming to evaluate, and possibly improve, the simulation of high and low discharge conditions under the influence of human interventions. LISFLOOD simulates hydrologic processes on several sub-grid land use and cover classes, routing discharge along river networks. It can also simulate lakes and reservoir regulation, as well as human water abstractions, consumption and return flows. We focus primarily on the Drammen catchment, which is heavily regulated and serves several water users, with the possibility to extend the analysis to other catchments in Norway. Land use, vegetation, soil and river data are derived from the LISFLOOD setup at 5 km resolution used in the European Flood Awareness System. The model is forced with daily SeNorge_2018 and European Meteorological Observations atmospheric data at, respectively, 1 km and 1 arcminute spatial resolution. Detailed information for the Drammen catchment, in particular regarding human water use and regulation, is available through collaboration with the STARS4Water research project, which focuses on how climate change affects water resources availability at catchment scale and the potential impacts on ecosystems and society. Model evaluation is based on observed river discharge and reservoir water storage time series obtained from the Norwegian Water Resources and Energy Directorate. We aim to assess the ability of the model to reproduce extreme high and low discharge conditions, and whether representing human interventions improves model performance.

• Engeland, Kolbjørn; Erlandsen, Helene B.; Gelati, Emiliano; Huang, Shaochun; Narayanappa, Devaraju & Pirk, Norbert [Show all 10 contributors for this article] (2023). Intercomparison of local evapotranspiration estimates at high latitudes. Full text in Research Archive
• Thorarinsdottir, Thordis Linda; Roksvåg, Thea; Engeland, Kolbjørn; Barna, Danielle Marie; Xu, Chong-Yu & Lutz, Julia [Show all 8 contributors for this article] (2022). Consistent estimation of extreme precipitation and flooding across multiple durations. Full text in Research Archive
• Thorarinsdottir, Thordis Linda; Barna, Danielle Marie; Roksvåg, Thea; Engeland, Kolbjørn; Xu, Chong-Yu & Lutz, Julia [Show all 8 contributors for this article] (2022). Consistent estimation of extreme precipitation and flooding across multiple durations. Full text in Research Archive
• Barna, Danielle Marie; Engeland, Kolbjørn; Thorarinsdottir, Thordis Linda & Xu, Chong-Yu (2022). Regional flood-Duration-Frequency (QDF) Models for Norway. Full text in Research Archive
• Barna, Danielle Marie; Engeland, Kolbjørn; Thorarinsdottir, Thordis Linda & Xu, Chong-Yu (2022). New Flood-Duration-Frequency Models with a Focus on Estimation of Sub-daily Floods. Full text in Research Archive
• Barna, Danielle Marie; Engeland, Kolbjørn; Thorarinsdottir, Thordis Linda & Xu, Chong-Yu (2022). Flood-duration-frequency (QDF) Modeling: Updates and Current Status. Full text in Research Archive
• Nilsen, Irene Brox; Kleivane, Ingeborg & Engeland, Kolbjørn (2022). Jernbanen må klargjøres for å takle framtidas flommer. Full text in Research Archive Show summary

  Etter flommene i 2011, 2013, og igjen i 2018, registrerte Bane NOR tre hundre skadepunkter langs Dovrebanen, med en beregnet kostnad på 300 millioner kroner. Det er et stort behov for bedre flomberegninger.

• Paasche, Øyvind; Engeland, Kolbjørn & Støren, Eivind Wilhelm Nagel (2021). Trollet under broen. Dagens næringsliv. ISSN 0803-9372. Full text in Research Archive
• Kjørstad, Elise; Paasche, Øyvind & Engeland, Kolbjørn (2021). Varmere klima kan bety færre storflommer i Glomma. [Journal]. Forskning.no. Full text in Research Archive
• Paasche, Øyvind & Engeland, Kolbjørn (2021). Vår tids flommer. Full text in Research Archive
• Barna, Danielle; Engeland, Kolbjørn; Thorarinsdottir, Thordis Linda & Xu, Chong-Yu (2021). A Bayesian approach to Flood-Duration-Analysis. Full text in Research Archive
• Glad, Per; Stenius, Seija; Engeland, Kolbjørn; Holmqvist, Erik; Ejigo, Demissew Kebede & Væringstad, Thomas (2021). Flomberegninger i regulerte felt — hvordan vassdragsreguleringer og flomforløp påvirker flomforholdene. Full text in Research Archive Show summary

  Rapporten beskriver hvordan ulike tilnærminger for beregning av flommer i et regulert vassdrag, så som ulike vassdragsreguleringer og flomforløp, påvirker flomforholdene. Det er også utført en litteraturstudie og utarbeidet en rutinebeskrivelse for beregning av tilsigsserier. Analysene er utført vha. vassdragsmodeller der tilsigsserier, observerte vannføringsserier og tidsserier for vanntilførsel (summen av regn- og snøsmelting) fra seNorge er brukt som inngangsdata. Det er utført en romlig statistisk analyse på vanntilførsel-data for å utarbeide IVF-kurver som igjen er brukt til å konstruere dimensjonerende hendelser for nedbørfeltene. Dette er så brukt for å undersøke hvor følsomme flomstørrelsene er for fordeling av vanntilførselen i tid og rom.

• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2020). Using Bayesian geostatistical models to correct gridded hydrological products relative to the actually observed streamflow. Full text in Research Archive
• 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. Full text in Research Archive
• Engeland, Kolbjørn & Alfredsen, Knut (2020). Hydrology and water resources management in a changing world. Hydrology Research. ISSN 1998-9563. 51(2), p. 143–145. doi: 10.2166/nh.2020.000. Full text in Research Archive
• 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. Full text in Research Archive
• 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), p. 2003–2021. doi: 10.1175/JHM-D-19-0071.1. Full text in Research Archive Show summary

  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, for example, 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.

• 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 (HESS). ISSN 1027-5606. 24, p. 5595–5619. doi: 10.5194/hess-24-5595-2020. Full text in Research Archive Show summary

  The Glomma River is the largest in Norway, with a catchment area of 154 450 km2. People living near the shores of this river are frequently exposed to destructive floods that impair local cities and communities. Unfortunately, design flood predictions are hampered by uncertainty since the standard flood records are much shorter than the requested return period and the climate is also expected to change in the coming decades. Here we combine systematic historical and paleo information in an effort to improve flood frequency analysis and better understand potential linkages to both climate and non-climatic forcing. Specifically, we (i) compile historical flood data from the existing literature, (ii) produce high-resolution X-ray fluorescence (XRF), magnetic susceptibility (MS), and computed tomography (CT) scanning data from a sediment core covering the last 10 300 years, and (iii) integrate these data sets in order to better estimate design floods and assess non-stationarities. Based on observations from Lake Flyginnsjøen, receiving sediments from Glomma only when it reaches a certain threshold, we can estimate flood frequency in a moving window of 50 years across millennia revealing that past flood frequency is non-stationary on different timescales. We observe that periods with increased flood activity (4000–2000 years ago and <1000 years ago) correspond broadly to intervals with lower than average summer temperatures and glacier growth, whereas intervals with higher than average summer temperatures and receding glaciers overlap with periods of reduced numbers of floods (10 000 to 4000 years ago and 2200 to 1000 years ago). The flood frequency shows significant non-stationarities within periods with increased flood activity, as was the case for the 18th century, including the 1789 CE (“Stor-Ofsen”) flood, the largest on record for the last 10 300 years at this site. Using the identified non-stationarities in the paleoflood record allowed us to estimate non-stationary design floods. In particular, we found that the design flood was 23 % higher during the 18th century than today and that long-term trends in flood variability are intrinsically linked to the availability of snow in late spring linking climate change to adjustments in flood frequency.

• Paasche, Øyvind; Øksnes, Monika; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Lu, Li & Engeland, Kolbjørn [Show all 7 contributors for this article] (2019). Centennial shifts in flood frequency and magnitude over the last thousand years in Western Norway. Full text in Research Archive
• 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. Full text in Research Archive
• Paasche, Øyvind; Øksnes, Monika; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Lu, Li & Engeland, Kolbjørn [Show all 7 contributors for this article] (2019). Centennial shifts in flood frequency and magnitude over the last thousend years in Western Norway. Full text in Research Archive
• Paasche, Øyvind; Øksnes, Monika; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Lu, Li & Engeland, Kolbjørn [Show all 7 contributors for this article] (2019). Adopting to new flood regimes: how the past can inform present day decision making. Full text in Research Archive
• Ruan, Gusong; Borsányi, Péter; Engeland, Kolbjørn; Holmqvist, Erik; Devoli, Graziella & Langsholt, Elin [Show all 12 contributors for this article] (2019). Treffsikkerhet og presisjon i hydrologiske prognoser. Full text in Research Archive Show summary

  Denne sluttrapporten oppsummerer resultater og leveranser fra det interne FoU-prosjektet 80103, Treffsikkerhet og presisjon i hydrologiske prognoser, som ble gjennomført i perioden 2015 til 2018. Målsettingen med prosjektet var å forbedre våre operasjonelle metoder med hensyn til metodikk og tilgjengelige data, for å forbedre treffsikkerhet og presisjon i våre hydrologiske prognoser

• 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. Full text in Research Archive
• 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. Full text in Research Archive
• Støren, Eivind Wilhelm Nagel; Engeland, Kolbjørn & Paasche, Øyvind (2018). Nye metoder gir økt kunnskap om flom. Naturen. ISSN 0028-0887. p. 267–274. doi: 10.18261/ISSN.1504-3118-2018-06-07. Full text in Research Archive
• 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. Full text in Research Archive
• Thorarinsdottir, Thordis Linda; Hellton, Kristoffer Herland; Steinbakk, Gunnhildur Högnadóttir; Schlichting, Lena & Engeland, Kolbjørn (2018). Statistical estimation of extreme floods. Full text in Research Archive
• Thorarinsdottir, Thordis Linda; Lenkoski, Alex; Hellton, Kristoffer Herland; Steinbakk, Gunnhildur Högnadóttir; Dyrrdal, Anita Verpe & Stordal, Frode [Show all 8 contributors for this article] (2018). On developing general and efficient inference algorithms for complicated hierarchical models. Full text in Research Archive
• Engeland, Kolbjørn & Holmqvist, Erik (2018). Flood frequency analysis including historical data: A case study for catchments in Norway. Full text in Research Archive
• Engeland, Kolbjørn & Steinsland, Ingelin (2018). Flood frequency analysis - assessment of uncertainties in flood data, plotting positions and fitted distributions. Full text in Research Archive
• 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. Full text in Research Archive
• 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. Full text in Research Archive
• Engeland, Kolbjørn & Holmqvist, Erik (2017). Lærdom fra flomhistorien. Forskning.no. ISSN 1891-635X. Full text in Research Archive
• Roksvåg, Thea; Engeland, Kolbjørn & Steinsland, Ingelin (2017). A Bayesian spatial model for utilising precipitation gauge observations and runoff observations for annual runoff predictions. Full text in Research Archive
• Roksvåg, Thea; Steinsland, Ingelin & Engeland, Kolbjørn (2017). A Bayesian spatial model for utilising precipitation gauge observations and runoff observations for annual runoff predictions. Full text in Research Archive
• Lawrence, Deborah; Thorarinsdottir, Thordis Linda; Paquet, Eric R.; Skaugen, Thomas & Engeland, Kolbjørn (2017). FlomQ: Improving flood estimation methods for dam safety in Norway. Full text in Research Archive
• Kobierska, Florian & Engeland, Kolbjørn (2016). Evaluation of design flood estimates with respect to sample size. Full text in Research Archive
• Engeland, Kolbjørn (2016). Forbedret informasjonsgrunnlag for flomfrekvensanalyse of flomberegninger i NEVINA-plattformen. Full text in Research Archive
• Engeland, Kolbjørn; Warland, Geir; Borga, Marco; Creutin, Jean-Dominique & Ramos, Maria-Helena (2015). Space-time dependence between energy sources and climate related energy production. Full text in Research Archive
• 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. Full text in Research Archive
• Engeland, Kolbjørn; Tallaksen, Lena M.; Bakken, Tor Haakon & Killingtveit, Ånund (2015). Water footprint of hydro power in Norway. Full text in Research Archive Show summary

  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.

• Schlichting, Lena; Vormoor, Klaus & Engeland, Kolbjørn (2015). Estimation of flood generating processes in gauged catchments. Full text in Research Archive
• Engeland, Kolbjørn (2015). FLOMQ, siste nytt fra prosjektet. Full text in Research Archive
• Engeland, Kolbjørn (2015). Flood frequency analysis – the challenge of using historical data. Full text in Research Archive
• 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. Full text in Research Archive
• Engeland, Kolbjørn (2014). Vannforbruk og fordampningsberegninger. Full text in Research Archive
• Bakken, Tor Haakon; Engeland, Kolbjørn & Killingtveit, Ånund (2014). Review of water consumption estimates and the importance of evaporation. Full text in Research Archive
• Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S & Bruland, Oddbjørn (2013). Parameter identifiability and regional calibration for reservoir inflow prediction. Full text in Research Archive
• Steinsland, Ingelin & Engeland, Kolbjørn (2013). Temporal-spatial post processing models for probabilistic inflow forecasts combining hydrological and persistent forecasts with inflow climatology. Full text in Research Archive
• Engeland, Kolbjørn; Killingtveit, Ånund; Bakken, Tor Haakon; Alfredsen, Knut & Harby, Atle (2012). Water use in Hydropower Reservoirs - a Review. Full text in Research Archive
• Bruland, Oddbjørn; Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S; Gragne, Ashenafi Seifu & Liston, Glen [Show all 8 contributors for this article] (2012). Updating of states in operational hydrological models. Geophysical Research Abstracts. ISSN 1029-7006. 14. Full text in Research Archive Show summary

  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.

• Bruland, Oddbjørn; Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S; Gragne, Ashenafi Seifu & Alfredsen, Knut [Show all 7 contributors for this article] (2012). Updating of states in operational hydrological models. Full text in Research Archive
• 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. Full text in Research Archive
• Tøfte, Lena S & Engeland, Kolbjørn (2010). Hydrological modeling for environmental studies -challenges and examples from Norway. Full text in Research Archive
• Bruland, Oddbjørn; Tøfte, Lena S; Engeland, Kolbjørn & Kolberg, Sjur (2009). ENKI – Operational hydrological forecasting system. Full text in Research Archive
• Dyrrdal, Anita Verpe; Bakke, Sigrid Jørgensen; Hanssen-Bauer, Inger; Mayer, Stephanie; Nilsen, Irene Brox & Nilsen, Jan Even Øie [Show all 71 contributors for this article] (2025). Klima i Norge – kunnskapsgrunnlag for klimatilpasning oppdatert i 2025. Meteorologisk institutt. Full text in Research Archive Show summary

  I kjølvannet av FNs klimapanels sjette hovedrapport, og nedskalerte europeiske klimaframskrivninger, har Norsk klimaservicesenter fått i oppdrag å oppdatere rapporten Klima i Norge – Kunnskapsgrunnlag for klimatilpasning oppdatert i 2025. Dette er den tredje utgaven av ”Klima i Norge”-rapporten. Klima i Norge beskriver hvordan klimaendringer påvirker Norge, basert på målinger og klimaframskrivninger. Rapporten omhandler primært nasjonale forhold og definerer klimaendringer som endringer i atmosfære, kryosfære, hydrologi, skred og hav. Denne kunnskapen danner grunnlaget for klimatilpasning i Norge

• Beldring, Stein; Engeland, Kolbjørn; Holmqvist, Erik; Pedersen, Anja Iselin; Ruan, Gusong & Veie, Carl Andreas [Show all 7 contributors for this article] (2022). Avrenningskart for Norge 1991-2020. Norges vassdrags- og energidirektorat. ISSN 9788241022777. Full text in Research Archive Show summary

  NVE har beregnet normalverdier for årlig avrenning for perioden 1991-2020. Det er utført et omfattende arbeid med kvalitetskontroll og homogenisering av observerte hydrologiske data fra NVEs stasjonsnett og innhenting av hydrologiske data fra institusjoner i Norge, Sverige og Finland. Arbeidet er utført med en hydrologisk modell som beregner vannbalansen for 1 km2 grid-ruter som dekker fastlandet i Norge og vassdrag i Sverige og Finland som renner til Norge. Den modellerte årlige middelavrenningen er korrigert ved hjelp av en geostatistisk interpolasjonsmetode som benytter observerte data.

• Paasche, Øyvind; Engeland, Kolbjørn; Støren, Eivind Wilhelm Nagel; Bakke, Jostein; Neby, Simon & Li, Lu [Show all 10 contributors for this article] (2021). Hordaflom rapporten – Klima og flom. NORCE Research AS. Full text in Research Archive
• Alfredsen, Knut; Xu, Chong-Yu & Engeland, Kolbjørn (2018). Nordic Hydrological Conference 2018. Norges vassdrags- og energidirektorat. Full text in Research Archive
• Thorarinsdottir, Thordis Linda; Engeland, Kolbjørn; Lawrence, Deborah; Pedersen, Øyvind; Tveito, Ole Einar & Hellton, Kristoffer Herland [Show all 27 contributors for this article] (2018). Nytt rammeverk for flomestimering i Norge: Sluttrapport fra forskningsprosjektet FlomQ. Energi Norge. ISSN 9788243610484. Full text in Research Archive
• Engeland, Kolbjørn; Abdella, Yisak Sultan; Lepioufle, Jean-Marie & Grønsleth, Martin (2012). Sluttrapport for værradarprosjektet. SINTEF Energi AS. ISSN 9788259435118. Full text in Research Archive
• Engeland, Kolbjørn & Lepioufle, Jean-Marie (2012). Evaluation of radar-derived precipitation estimates using runoff simulation. SINTEF Energi AS. ISSN 9788259435101. Full text in Research Archive
• Tøfte, Lena S; Kolberg, Sjur & Engeland, Kolbjørn (2008). En fordelt hydrologisk modell til Statkraft. Utvikling og simuleringer. Teknisk rapport (SINTEF Energiforskning) serienr TR F6643. Full text in Research Archive

View all works in NVA