@article{SunyerHundechaLawrenceetal.2015, author = {Sunyer, M. A. and Hundecha, Y. and Lawrence, D. and Madsen, H. and Willems, Patrick and Martinkova, M. and Vormoor, Klaus Josef and B{\"u}rger, Gerd and Hanel, M. and Kriauciuniene, J. and Loukas, A. and Osuch, M. and Yucel, I.}, title = {Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe}, series = {Hydrology and earth system sciences : HESS}, volume = {19}, journal = {Hydrology and earth system sciences : HESS}, number = {4}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-19-1827-2015}, pages = {1827 -- 1847}, year = {2015}, abstract = {Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30\% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.}, language = {en} } @article{VormoorLawrenceHeistermannetal.2015, author = {Vormoor, Klaus Josef and Lawrence, D. and Heistermann, Maik and Bronstert, Axel}, title = {Climate change impacts on the seasonality and generation processes of floods}, series = {Hydrology and earth system sciences : HESS}, volume = {19}, journal = {Hydrology and earth system sciences : HESS}, number = {2}, publisher = {Copernicus Publications}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-19-913-2015}, pages = {913 -- 931}, year = {2015}, abstract = {Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961-1990) and a future (2071-2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.}, language = {en} } @article{HundechaSunyerLawrenceetal.2016, author = {Hundecha, Yeshewatesfa and Sunyer, Maria A. and Lawrence, Deborah and Madsen, Henrik and Willems, Patrick and B{\"u}rger, Gerd and Kriauciuniene, Jurate and Loukas, Athanasios and Martinkova, Marta and Osuch, Marzena and Vasiliades, Lampros and von Christierson, Birgitte and Vormoor, Klaus Josef and Yuecel, Ismail}, title = {Inter-comparison of statistical downscaling methods for projection of extreme flow indices across Europe}, series = {Journal of hydrology}, volume = {541}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2016.08.033}, pages = {1273 -- 1286}, year = {2016}, abstract = {The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km(2) in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model ensemble, although the statistical downscaling methods contribute 35-60\% of the total variance. (C) 2016 Elsevier B.V. All rights reserved.}, language = {en} } @article{VormoorLawrenceSchlichtingetal.2016, author = {Vormoor, Klaus Josef and Lawrence, Deborah and Schlichting, Lena and Wilson, Donna and Wong, Wai Kwok}, title = {Evidence for changes in the magnitude and frequency of observed rainfall vs. snowmelt driven floods in Norway}, series = {Journal of hydrology}, volume = {538}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2016.03.066}, pages = {33 -- 48}, year = {2016}, abstract = {There is increasing evidence for recent changes in the intensity and frequency of heavy precipitation and in the number of days with snow cover in many parts of Norway. The question arises as to whether these changes are also discernable with respect to their impacts on the magnitude and frequency of flooding and on the processes producing high flows. In this study, we tested up to 211 catchments for trends in peak flow discharge series by applying the Mann-Kendall test and Poisson regression for three different time periods (1962-2012, 1972-2012, 1982-2012). Field-significance was tested using a bootstrap approach. Over threshold discharge events were classified into rainfall vs. snowmelt dominated floods, based on a simple water balance approach utilizing a nationwide 1 x 1 km(2) gridded data set with daily observed rainfall and simulated snowmelt data. Results suggest that trends in flood frequency are more pronounced than trends in flood magnitude and are more spatially consistent with observed changes in the hydrometeorological drivers. Increasing flood frequencies in southern and western Norway are mainly due to positive trends in the frequency of rainfall dominated events, while decreasing flood frequencies in northern Norway are mainly the result of negative trends in the frequency of snowmelt dominated floods. Negative trends in flood magnitude are found more often than positive trends, and the regional patterns of significant trends reflect differences in the flood generating processes (FGPs). The results illustrate the benefit of distinguishing FGPs rather than simply applying seasonal analyses. The results further suggest that rainfall has generally gained an increasing importance for the generation of floods in Norway, while the role of snowmelt has been decreasing and the timing of snowmelt dominated floods has become earlier. (C) 2016 Elsevier B.V. All rights reserved.}, language = {en} } @phdthesis{Vormoor2016, author = {Vormoor, Klaus Josef}, title = {The changing role of snowmelt- and rainfall dominated floods in Norway under climate change}, school = {Universit{\"a}t Potsdam}, pages = {115}, year = {2016}, language = {en} } @article{VormoorRosslerBuergeretal.2017, author = {Vormoor, Klaus Josef and Rossler, Ole and B{\"u}rger, Gerd and Bronstert, Axel and Weingartner, Rolf}, title = {When timing matters-considering changing temporal structures in runoff response surfaces}, series = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change}, volume = {142}, journal = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change}, publisher = {Springer}, address = {Dordrecht}, issn = {0165-0009}, doi = {10.1007/s10584-017-1940-1}, pages = {213 -- 226}, year = {2017}, abstract = {Scenario-neutral response surfaces illustrate the sensitivity of a simulated natural system, represented by a specific impact variable, to systematic perturbations of climatic parameters. This type of approach has recently been developed as an alternative to top-down approaches for the assessment of climate change impacts. A major limitation of this approach is the underrepresentation of changes in the temporal structure of the climate input data (i.e., the seasonal and day-to-day variability) since this is not altered by the perturbation. This paper presents a framework that aims to examine this limitation by perturbing both observed and projected climate data time series for a future period, which both serve as input into a hydrological model (the HBV model). The resulting multiple response surfaces are compared at a common domain, the standardized runoff response surface (SRRS). We apply this approach in a case study catchment in Norway to (i) analyze possible changes in mean and extreme runoff and (ii) quantify the influence of changes in the temporal structure represented by 17 different climate input sets using linear mixed-effect models. Results suggest that climate change induced increases in mean and peak flow runoff and only small changes in low flow. They further suggest that the effect of the different temporal structures of the climate input data considerably affects low flows and floods (at least 21\% influence), while it is negligible for mean runoff.}, language = {en} } @article{DelgadoVossBuergeretal.2018, author = {Delgado, Jos{\´e} Miguel Martins and Voss, Sebastian and B{\"u}rger, Gerd and Vormoor, Klaus Josef and Murawski, Aline and Rodrigues Pereira, Jos{\´e} Marcelo and Martins, Eduardo and Vasconcelos J{\´u}nior, Francisco and Francke, Till}, title = {Seasonal drought prediction for semiarid northeastern Brazil}, series = {Hydrology and Earth System Sciences}, volume = {22}, journal = {Hydrology and Earth System Sciences}, number = {9}, publisher = {Copernicus Publ.}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-22-5041-2018}, pages = {5041 -- 5056}, year = {2018}, abstract = {A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Cear{\´a}'s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.}, language = {en} } @article{VormoorHeistermannBronstertetal.2018, author = {Vormoor, Klaus Josef and Heistermann, Maik and Bronstert, Axel and Lawrence, Deborah}, title = {Hydrological model parameter (in)stability}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {63}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {7}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2018.1466056}, pages = {991 -- 1007}, year = {2018}, abstract = {This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of -5 to -17\%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa.}, language = {en} } @article{PilzDelgadoVossetal.2019, author = {Pilz, Tobias and Delgado, Jos{\´e} Miguel Martins and Voss, Sebastian and Vormoor, Klaus Josef and Francke, Till and Cunha Costa, Alexandre and Martins, Eduardo and Bronstert, Axel}, title = {Seasonal drought prediction for semiarid northeast Brazil}, series = {Hydrology and Earth System Sciences}, volume = {23}, journal = {Hydrology and Earth System Sciences}, publisher = {Copernicus Publications}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-23-1951-2019}, pages = {1951 -- 1971}, year = {2019}, abstract = {The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach. Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality. Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.}, language = {en} } @article{MtilatilaBronstertShresthaetal.2020, author = {Mtilatila, Lucy Mphatso Ng'ombe and Bronstert, Axel and Shrestha, Pallav and Kadewere, Peter and Vormoor, Klaus Josef}, title = {Susceptibility of water resources and hydropower production to climate change in the tropics}, series = {Hydrology : open access journal}, volume = {7}, journal = {Hydrology : open access journal}, number = {3}, publisher = {MDPI}, address = {Basel}, issn = {2306-5338}, doi = {10.3390/hydrology7030054}, pages = {26}, year = {2020}, abstract = {The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17\%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5\% (-5\%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20\% (-15\%). The study further projects a reduction in annual hydropower production between 1\% (RCP8.5) and 2.5\% (RCP4.5) during 2021-2050 and between 5\% (RCP4.5) and 24\% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.}, language = {en} }