@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{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} } @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} } @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{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{SkalevagVormoor2021, author = {Sk{\aa}lev{\aa}g, Amalie and Vormoor, Klaus Josef}, title = {Daily streamflow trends in Western versus Eastern Norway and their attribution to hydro-meteorological drivers}, series = {Hydrological processes : an international journal}, volume = {35}, journal = {Hydrological processes : an international journal}, number = {8}, publisher = {Wiley}, address = {New York}, issn = {0885-6087}, doi = {10.1002/hyp.14329}, pages = {17}, year = {2021}, abstract = {Regional warming and modifications in precipitation regimes has large impacts on streamflow in Norway, where both rainfall and snowmelt are important runoff generating processes. Hydrological impacts of recent changes in climate are usually investigated by trend analyses applied on annual, seasonal, or monthly time series. None of these detect sub-seasonal changes and their underlying causes. This study investigated sub-seasonal changes in streamflow, rainfall, and snowmelt in 61 and 51 catchments respectively in Western (Vestlandet) and Eastern (ostlandet) Norway by applying the Mann-Kendall test and Theil-Sen estimator on 10-day moving averaged daily time series over a 30-year period (1983-2012). The relative contribution of rainfall versus snowmelt to daily streamflow and the changes therein have also been estimated to identify the changing relevance of these driving processes over the same period. Detected changes in 10-day moving averaged daily streamflow were finally attributed to changes in the most important hydro-meteorological drivers using multiple-regression models with increasing complexity. Earlier spring flow timing in both regions occur due to earlier snowmelt. ostlandet shows increased summer streamflow in catchments up to 1100 m a.s.l. and slightly increased winter streamflow in about 50\% of the catchments. Trend patterns in Vestlandet are less coherent. The importance of rainfall has increased in both regions. Attribution of trends reveals that changes in rainfall and snowmelt can explain some streamflow changes where they are dominant processes (e.g., spring snowmelt in ostlandet and autumn rainfall in Vestlandet). Overall, the detected streamflow changes can be best explained by adding temperature trends as an additional predictor, indicating the relevance of additional driving processes such as increased glacier melt and evapotranspiration.}, language = {en} } @article{RottlerVormoorFranckeetal.2021, author = {Rottler, Erwin and Vormoor, Klaus Josef and Francke, Till and Warscher, Michael and Strasser, Ulrich and Bronstert, Axel}, title = {Elevation-dependent compensation effects in snowmelt in the Rhine River Basin upstream gauge Basel}, series = {Hydrology research : an international journal / Nordic Association of Hydrology ; British Hydrological Society}, volume = {52}, journal = {Hydrology research : an international journal / Nordic Association of Hydrology ; British Hydrological Society}, number = {2}, publisher = {IWA Publ.}, address = {London}, issn = {2224-7955}, doi = {10.2166/nh.2021.092}, pages = {536 -- 557}, year = {2021}, abstract = {In snow-dominated river basins, floods often occur during early summer, when snowmelt-induced runoff superimposes with rainfall-induced runoff. An earlier onset of seasonal snowmelt as a consequence of a warming climate is often expected to shift snowmelt contribution to river runoff and potential flooding to an earlier date. Against this background, we assess the impact of rising temperatures on seasonal snowpacks and quantify changes in timing, magnitude and elevation of snowmelt. We analyse in situ snow measurements, conduct snow simulations and examine changes in river runoff at key gauging stations. With regard to snowmelt, we detect a threefold effect of rising temperatures: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Due to the wide range of elevations in the catchment, snowmelt does not occur simultaneously at all elevations. Results indicate that elevation bands melt together in blocks. We hypothesise that in a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevation. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier, although the timing of the snowmelt-induced runoff stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below.}, language = {en} } @article{RottlerVormoorFranckeetal.2021, author = {Rottler, Erwin and Vormoor, Klaus Josef and Francke, Till and Bronstert, Axel}, title = {Hydro Explorer}, series = {River research and applications}, volume = {37}, journal = {River research and applications}, number = {4}, publisher = {Wiley}, address = {New York}, issn = {1535-1459}, doi = {10.1002/rra.3772}, pages = {544 -- 554}, year = {2021}, abstract = {Climatic changes and anthropogenic modifications of the river basin or river network have the potential to fundamentally alter river runoff. In the framework of this study, we aim to analyze and present historic changes in runoff timing and runoff seasonality observed at river gauges all over the world. In this regard, we develop the Hydro Explorer, an interactive web app, which enables the investigation of >7,000 daily resolution discharge time series from the Global Runoff Data Centre (GRDC). The interactive nature of the developed web app allows for a quick comparison of gauges, regions, methods, and time frames. We illustrate the available analytical tools by investigating changes in runoff timing and runoff seasonality in the Rhine River Basin. Since we provide the source code of the application, existing analytical approaches can be modified, new methods added, and the tool framework can be re-used to visualize other data sets.}, 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{MtilatilaBronstertVormoor2022, author = {Mtilatila, Lucy Mphatso Ng'ombe and Bronstert, Axel and Vormoor, Klaus Josef}, title = {Temporal evaluation and projections of meteorological droughts in the Greater Lake Malawi Basin, Southeast Africa}, series = {Frontiers in Water}, journal = {Frontiers in Water}, publisher = {Frontiers Media S.A.}, address = {Lausanne, Schweiz}, issn = {2624-9375}, doi = {10.3389/frwa.2022.1041452}, pages = {1 -- 16}, year = {2022}, abstract = {The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50\% during 2021-2050 and between +131 and +388\% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.}, language = {en} } @article{MtilatilaBronstertVormoor2022, author = {Mtilatila, Lucy Mphatso Ng'ombe and Bronstert, Axel and Vormoor, Klaus Josef}, title = {Temporal evaluation and projections of meteorological droughts in the Greater Lake Malawi Basin, Southeast Africa}, series = {Frontiers in water}, volume = {4}, journal = {Frontiers in water}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2624-9375}, doi = {10.3389/frwa.2022.1041452}, pages = {16}, year = {2022}, abstract = {The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50\% during 2021-2050 and between +131 and +388\% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.}, 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} } @article{MtilatilaBronstertBuergeretal.2020, author = {Mtilatila, Lucy Mphatso Ng'ombe and Bronstert, Axel and B{\"u}rger, Gerd and Vormoor, Klaus Josef}, title = {Meteorological and hydrological drought assessment in Lake Malawi and Shire River basins (1970-2013)}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {65}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {16}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2020.1837384}, pages = {2750 -- 2764}, year = {2020}, abstract = {The study assesses the variability and trends of both meteorological and hydrological droughts from 1970 to 2013 in Lake Malawi and Shire River basins using the standardized precipitation index (SPI) and standardized precipitation and evaporation index (SPEI) for meteorological droughts and the lake level change index (LLCI) for hydrological droughts. Trends and slopes in droughts and drought drivers are estimated using Mann-Kendall test and Sen's slope, respectively. Results suggest that meteorological droughts are increasing due to a decrease in precipitation which is exacerbated by an increase in temperature (potential evapotranspiration). The hydrological system of Lake Malawi seems to have a >24-month memory towards meteorological conditions, since the 36-month SPEI can predict hydrological droughts 10 months in advance. The study has found the critical lake level that would trigger hydrological drought to be 474.1 m a.s.l. The increase in drought is a concern as this will have serious impacts on water resources and hydropower supply in Malawi.}, 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{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} }