@misc{SchmidtFranckeRottleretal.2022, author = {Schmidt, Lena Katharina and Francke, Till and Rottler, Erwin and Blume, Theresa and Sch{\"o}ber, Johannes}, title = {Suspended sediment and discharge dynamics in a glaciated alpine environment: identifying crucial areas and time periods on several spatial and temporal scales in the {\"O}tztal, Austria}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1296}, issn = {1866-8372}, doi = {10.25932/publishup-57656}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-576564}, pages = {653 -- 669}, year = {2022}, abstract = {Glaciated high-alpine areas are fundamentally altered by climate change, with well-known implications for hydrology, e.g., due to glacier retreat, longer snow-free periods, and more frequent and intense summer rainstorms. While knowledge on how these hydrological changes will propagate to suspended sediment dynamics is still scarce, it is needed to inform mitigation and adaptation strategies. To understand the processes and source areas most relevant to sediment dynamics, we analyzed discharge and sediment dynamics in high temporal resolution as well as their patterns on several spatial scales, which to date few studies have done. We used a nested catchment setup in the Upper {\"O}tztal in Tyrol, Austria, where high-resolution (15 min) time series of discharge and suspended sediment concentrations are available for up to 15 years (2006-2020). The catchments of the gauges in Vent, S{\"o}lden and Tumpen range from 100 to almost 800 km2 with 10 \% to 30 \% glacier cover and span an elevation range of 930 to 3772 m a.s.l. We analyzed discharge and suspended sediment yields (SSY), their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. We complemented our analysis by linking the observations to satellite-based snow cover maps, glacier inventories, mass balances and precipitation data. Our results indicate that the areas above 2500 m a.s.l., characterized by glacier tongues and the most recently deglaciated areas, are crucial for sediment generation in all sub-catchments. This notion is supported by the synchronous spring onset of sediment export at the three gauges, which coincides with snowmelt above 2500 m but lags behind spring discharge onsets. This points at a limitation of suspended sediment supply as long as the areas above 2500 m are snow-covered. The positive correlation of annual SSY with glacier cover (among catchments) and glacier mass balances (within a catchment) further supports the importance of the glacier-dominated areas. The analysis of short-term events showed that summer precipitation events were associated with peak sediment concentrations and yields but on average accounted for only 21 \% of the annual SSY in the headwaters. These results indicate that under current conditions, thermally induced sediment export (through snow and glacier melt) is dominant in the study area. Our results extend the scientific knowledge on current hydro-sedimentological conditions in glaciated high-alpine areas and provide a baseline for studies on projected future changes in hydro-sedimentological system dynamics.}, language = {en} } @misc{RottlerFranckeBuergeretal.2020, author = {Rottler, Erwin and Francke, Till and B{\"u}rger, Gerd and Bronstert, Axel}, title = {Long-term changes in central European river discharge for 1869-2016}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {4}, issn = {1866-8372}, doi = {10.25932/publishup-51776}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517763}, pages = {22}, year = {2020}, abstract = {Recent climatic changes have the potential to severely alter river runoff, particularly in snow-dominated river basins. Effects of changing snow covers superimpose with changes in precipitation and anthropogenic modifications of the watershed and river network. In the attempt to identify and disentangle long-term effects of different mechanisms, we employ a set of analytical tools to extract long-term changes in river runoff at high resolution. We combine quantile sampling with moving average trend statistics and empirical mode decomposition and apply these tools to discharge data recorded along rivers with nival, pluvial and mixed flow regimes as well as temperature and precipitation data covering the time frame 1869-2016. With a focus on central Europe, we analyse the long-term impact of snow cover and precipitation changes along with their interaction with reservoir constructions. Our results show that runoff seasonality of snow-dominated rivers decreases. Runoff increases in winter and spring, while discharge decreases in summer and at the beginning of autumn. We attribute this redistribution of annual flow mainly to reservoir constructions in the Alpine ridge. During the course of the last century, large fractions of the Alpine rivers were dammed to produce hydropower. In recent decades, runoff changes induced by reservoir constructions seem to overlap with changes in snow cover. We suggest that Alpine signals propagate downstream and affect runoff far outside the Alpine area in river segments with mixed flow regimes. Furthermore, our results hint at more (intense) rain-fall in recent decades. Detected increases in high discharge can be traced back to corresponding changes in precipitation.}, language = {en} } @misc{PilzFranckeBronstert2017, author = {Pilz, Tobias and Francke, Till and Bronstert, Axel}, title = {lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-402880}, pages = {23}, year = {2017}, abstract = {The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial, or depend on commercial back-end software, and allow only a limited or no workflow automation at all. Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multi-scale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows for immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option to include expert knowledge. Conversely, completely automatic operation also allows for extensive analysis of aspects related to landscape discretisation. In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hillslopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes.}, language = {en} } @misc{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 = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {702}, issn = {1866-8372}, doi = {10.25932/publishup-42795}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427950}, pages = {21}, 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} } @misc{KormannBronstertFranckeetal.2017, author = {Kormann, Christoph and Bronstert, Axel and Francke, Till and Recknagel, Thomas and Gr{\"a}ff, Thomas}, title = {Model-Based attribution of high-resolution streamflow trends in two alpine basins of Western Austria}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-400641}, pages = {21}, year = {2017}, abstract = {Several trend studies have shown that hydrological conditions are changing considerably in the Alpine region. However, the reasons for these changes are only partially understood and trend analyses alone are not able to shed much light. Hydrological modelling is one possible way to identify the trend drivers, i.e., to attribute the detected streamflow trends, given that the model captures all important processes causing the trends. We modelled the hydrological conditions for two alpine catchments in western Austria (a large, mostly lower-altitude catchment with wide valley plains and a nested high-altitude, glaciated headwater catchment) with the distributed, physically-oriented WaSiM-ETH model, which includes a dynamical glacier module. The model was calibrated in a transient mode, i.e., not only on several standard goodness measures and glacier extents, but also in such a way that the simulated streamflow trends fit with the observed ones during the investigation period 1980 to 2007. With this approach, it was possible to separate streamflow components, identify the trends of flow components, and study their relation to trends in atmospheric variables. In addition to trends in annual averages, highly resolved trends for each Julian day were derived, since they proved powerful in an earlier, data-based attribution study. We were able to show that annual and highly resolved trends can be modelled sufficiently well. The results provide a holistic, year-round picture of the drivers of alpine streamflow changes: Higher-altitude catchments are strongly affected by earlier firn melt and snowmelt in spring and increased ice melt throughout the ablation season. Changes in lower-altitude areas are mostly caused by earlier and lower snowmelt volumes. All highly resolved trends in streamflow and its components show an explicit similarity to the local temperature trends. Finally, results indicate that evapotranspiration has been increasing in the lower altitudes during the study period.}, language = {en} } @misc{KormannFranckeRenneretal.2015, author = {Kormann, C. and Francke, Till and Renner, M. and Bronstert, Axel}, title = {Attribution of high resolution streamflow trends in Western Austria}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-96560}, pages = {1225 -- 1245}, year = {2015}, abstract = {The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At midaltitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.}, language = {en} } @misc{HeistermannFranckeSchroenetal.2021, author = {Heistermann, Maik and Francke, Till and Schr{\"o}n, Martin and Oswald, Sascha}, title = {Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, issn = {1866-8372}, doi = {10.25932/publishup-52213}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-522131}, pages = {20}, year = {2021}, abstract = {Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil water content at a horizontal scale of hectometres (the "field scale") and depths of tens of centimetres ("the root zone"). This study demonstrates the potential of the CRNS technique to obtain spatio-temporal patterns of soil moisture beyond the integrated volume from isolated CRNS footprints. We use data from an observational campaign carried out between May and July 2019 that featured a dense network of more than 20 neutron detectors with partly overlapping footprints in an area that exhibits pronounced soil moisture gradients within one square kilometre. The present study is the first to combine these observations in order to represent the heterogeneity of soil water content at the sub-footprint scale as well as between the CRNS stations. First, we apply a state-of-the-art procedure to correct the observed neutron count rates for static effects (heterogeneity in space, e.g. soil organic matter) and dynamic effects (heterogeneity in time, e.g. barometric pressure). Based on the homogenized neutron data, we investigate the robustness of a calibration approach that uses a single calibration parameter across all CRNS stations. Finally, we benchmark two different interpolation techniques for obtaining spatio-temporal representations of soil moisture: first, ordinary Kriging with a fixed range; second, spatial interpolation complemented by geophysical inversion ("constrained interpolation"). To that end, we optimize the parameters of a geostatistical interpolation model so that the error in the forward-simulated neutron count rates is minimized, and suggest a heuristic forward operator to make the optimization problem computationally feasible. Comparison with independent measurements from a cluster of soil moisture sensors (SoilNet) shows that the constrained interpolation approach is superior for representing horizontal soil moisture gradients at the hectometre scale. The study demonstrates how a CRNS network can be used to generate coherent, consistent, and continuous soil moisture patterns that could be used to validate hydrological models or remote sensing products.}, language = {en} } @misc{HeistermannBogenaFranckeetal.2022, author = {Heistermann, Maik and Bogena, Heye and Francke, Till and G{\"u}ntner, Andreas and Jakobi, Jannis and Rasche, Daniel and Schr{\"o}n, Martin and D{\"o}pper, Veronika and Fersch, Benjamin and Groh, Jannis and Patil, Amol and P{\"u}tz, Thomas and Reich, Marvin and Zacharias, Steffen and Zengerle, Carmen and Oswald, Sascha}, title = {Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site W{\"u}stebach}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1272}, issn = {1866-8372}, doi = {10.25932/publishup-56775}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-567756}, pages = {2501 -- 2519}, year = {2022}, abstract = {Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 W{\"u}stebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land-atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms.}, language = {en} } @misc{FranckeHeistermannKoehlietal.2022, author = {Francke, Till and Heistermann, Maik and K{\"o}hli, Markus and Budach, Christian and Schr{\"o}n, Martin and Oswald, Sascha}, title = {Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, issn = {1866-8372}, doi = {10.25932/publishup-54422}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-544229}, pages = {75 -- 92}, year = {2022}, abstract = {Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use. This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution. Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time. The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.}, language = {en} } @misc{FranckeFoersterBrosinskyetal.2018, author = {Francke, Till and F{\"o}rster, Saskia and Brosinsky, Arlena and Sommerer, Erik and Lopez-Tarazon, Jose Andres and G{\"u}ntner, Andreas and Batalla Villanueva, Ramon J. and Bronstert, Axel}, title = {Water and sediment fluxes in Mediterranean mountainous regions}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {547}, issn = {1866-8372}, doi = {10.25932/publishup-41915}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419150}, pages = {13}, year = {2018}, abstract = {A comprehensive hydro-sedimentological dataset for the Is{\´a}bena catchment, northeastern (NE) Spain, for the period 2010-2018 is presented to analyse water and sediment fluxes in a Mediterranean mesoscale catchment. The dataset includes rainfall data from 12 rain gauges distributed within the study area complemented by meteorological data of 12 official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSCs) at six gauging stations of the River Is{\´a}bena and its sub-catchments. Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses. The Is{\´a}bena catchment (445 km 2 ) is located in the southern central Pyrenees ranging from 450 m to 2720 m a.s.l.; together with a pronounced topography, this leads to distinct temperature and precipitation gradients. The River Is{\´a}bena shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona Reservoir. The main sediment source is badland areas located on Eocene marls that are well connected to the river network. The dataset features a comprehensive set of variables in a high spatial and temporal resolution suitable for the advanced process understanding of water and sediment fluxes, their origin and connectivity and sediment budgeting and for the evaluation and further development of hydro-sedimentological models in Mediterranean mesoscale mountainous catchments.}, language = {en} } @phdthesis{Francke2009, author = {Francke, Till}, title = {Measurement and modelling of water and sediment fluxes in meso-scale dryland catchments}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-31525}, school = {Universit{\"a}t Potsdam}, year = {2009}, abstract = {Water shortage is a serious threat for many societies worldwide. In drylands, water management measures like the construction of reservoirs are affected by eroded sediments transported in the rivers. Thus, the capability of assessing water and sediment fluxes at the river basin scale is of vital importance to support management decisions and policy making. This subject was addressed by the DFG-funded SESAM-project (Sediment Export from large Semi-Arid catchments: Measurements and Modelling). As a part of this project, this thesis focuses on (1) the development and implementation of an erosion module for a meso-scale catchment model, (2) the development of upscaling and generalization methods for the parameterization of such model, (3) the execution of measurements to obtain data required for the modelling and (4) the application of the model to different study areas and its evaluation. The research was carried out in two meso-scale dryland catchments in NE-Spain: Ribera Salada (200 km²) and Is{\´a}bena (450 km²). Adressing objective 1, WASA-SED, a spatially semi-distributed model for water and sediment transport at the meso-scale was developed. The model simulates runoff and erosion processes at the hillslope scale, transport processes of suspended and bedload fluxes in the river reaches, and retention and remobilisation processes of sediments in reservoirs. This thesis introduces the model concept, presents current model applications and discusses its capabilities and limitations. Modelling at larger scales faces the dilemma of describing relevant processes while maintaining a manageable demand for input data and computation time. WASA-SED addresses this challenge by employing an innovative catena-based upscaling approach: the landscape is represented by characteristic toposequences. For deriving these toposequences with regard to multiple attributes (eg. topography, soils, vegetation) the LUMP-algorithm (Landscape Unit Mapping Program) was developed and related to objective 2. It incorporates an algorithm to retrieve representative catenas and their attributes, based on a Digital Elevation Model and supplemental spatial data. These catenas are classified to provide the discretization for the WASA-SED model. For objective 3, water and sediment fluxes were monitored at the catchment outlet of the Is{\´a}bena and some of its sub-catchments. For sediment yield estimation, the intermittent measurements of suspended sediment concentration (SSC) had to be interpolated. This thesis presents a comparison of traditional sediment rating curves (SRCs), generalized linear models (GLMs) and non-parametric regression using Random Forests (RF) and Quantile Regression Forests (QRF). The observed SSCs are highly variable and range over six orders of magnitude. For these data, traditional SRCs performed poorly, as did GLMs, despite including other relevant process variables (e.g. rainfall intensities, discharge characteristics). RF and QRF proved to be very robust and performed favourably for reproducing sediment dynamics. QRF additionally excels in providing estimates on the accuracy of the predictions. Subsequent analysis showed that most of the sediment was exported during intense storms of late summer. Later floods yielded successively less sediment. Comparing sediment generation to yield at the outlet suggested considerable storage effects within the river channel. Addressing objective 4, the WASA-SED model was parameterized for the two study areas in NE Spain and applied with different foci. For Ribera Salada, the uncalibrated model yielded reasonable results for runoff and sediment. It provided quantitative measures of the change in runoff and sediment yield for different land-uses. Additional land management scenarios were presented and compared to impacts caused by climate change projections. In contrast, the application for the Is{\´a}bena focussed on exploring the full potential of the model's predictive capabilities. The calibrated model achieved an acceptable performance for the validation period in terms of water and sediment fluxes. The inadequate representation of the lower sub-catchments inflicted considerable reductions on model performance, while results for the headwater catchments showed good agreement despite stark contrasts in sediment yield. In summary, the application of WASA-SED to three catchments proved the model framework to be a practicable multi-scale approach. It successfully links the hillslope to the catchment scale and integrates the three components hillslope, river and reservoir in one model. Thus, it provides a feasible approach for tackling issues of water and sediment yield at the meso-scale. The crucial role of processes like transmission losses and sediment storage in the river has been identified. Further advances can be expected when the representation of connectivity of water and sediment fluxes (intra-hillslope, hillslope-river, intra-river) is refined and input data improves.}, language = {en} } @misc{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}, journal = {Hydrology and Earth System Sciences}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418461}, pages = {16}, 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} }