@article{CostaFoersterdeAraujoetal.2013, author = {Costa, Alexandre Cunha and F{\"o}rster, Saskia and de Araujo, Jose Carlos and Bronstert, Axel}, title = {Analysis of channel transmission losses in a dryland river reach in north-eastern Brazil using streamflow series, groundwater level series and multi-temporal satellite data}, series = {Hydrological processes}, volume = {27}, journal = {Hydrological processes}, number = {7}, publisher = {Wiley-Blackwell}, address = {Hoboken}, issn = {1099-1085}, doi = {10.1002/hyp.9243}, pages = {1046 -- 1060}, year = {2013}, abstract = {Scarcity of hydrological data, especially streamflow discharge and groundwater level series, restricts the understanding of channel transmission losses (TL) in drylands. Furthermore, the lack of information on spatial river dynamics encompasses high uncertainty on TL analysis in large rivers. The objective of this study was to combine the information from streamflow and groundwater level series with multi-temporal satellite data to derive a hydrological concept of TL for a reach of the Middle Jaguaribe River (MJR) in semi-arid north-eastern Brazil. Based on this analysis, we proposed strategies for its modelling and simulation. TL take place in an alluvium, where river and groundwater can be considered to be hydraulically connected. Most losses certainly infiltrated only through streambed and levees and not through the flood plains, as could be shown by satellite image analysis. TL events whose input river flows were smaller than a threshold did not reach the outlet of the MJR. TL events whose input flows were higher than this threshold reached the outlet losing on average 30\% of their input. During the dry seasons (DS) and at the beginning of rainy seasons (DS/BRS), no river flow is expected for pre-events, and events have vertical infiltration into the alluvium. At the middle and the end of the rainy seasons (MRS/ERS), river flow sustained by base flow occurs before/after events, and lateral infiltration into the alluvium plays a major role. Thus, the MJR shifts from being a losing river at DS/BRS to become a losing/gaining (mostly losing) river at MRS/ERS. A model of this system has to include the coupling of river and groundwater flow processes linked by a leakage approach.}, language = {en} } @article{CostaBronstertKneis2012, author = {Costa, Alexandre Cunha and Bronstert, Axel and Kneis, David}, title = {Probabilistic flood forecasting for a mountainous headwater catchment using a nonparametric stochastic dynamic approach}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {57}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {1}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2011.637043}, pages = {10 -- 25}, year = {2012}, abstract = {Hydrological models are commonly used to perform real-time runoff forecasting for flood warning. Their application requires catchment characteristics and precipitation series that are not always available. An alternative approach is nonparametric modelling based only on runoff series. However, the following questions arise: Can nonparametric models show reliable forecasting? Can they perform as reliably as hydrological models? We performed probabilistic forecasting one, two and three hours ahead for a runoff series, with the aim of ascribing a probability density function to predicted discharge using time series analysis based on stochastic dynamics theory. The derived dynamic terms were compared to a hydrological model, LARSIM. Our procedure was able to forecast within 95\% confidence interval 1-, 2- and 3-h ahead discharge probability functions with about 1.40 m(3)/s of range and relative errors (\%) in the range [-30; 30]. The LARSIM model and the best nonparametric approaches gave similar results, but the range of relative errors was larger for the nonparametric approaches.}, language = {en} } @phdthesis{CunhaCosta2012, author = {Cunha Costa, Alexandre}, title = {Analyzing and modelling of flow transmission processes in river-systems with a focus on semi-arid conditions}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-59694}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {One of the major problems for the implementation of water resources planning and management in arid and semi-arid environments is the scarcity of hydrological data and, consequently, research studies. In this thesis, the hydrology of dryland river systems was analyzed and a semi-distributed hydrological model and a forecasting approach were developed for flow transmission processes in river-systems with a focus on semi-arid conditions. Three different sources of hydrological data (streamflow series, groundwater level series and multi-temporal satellite data) were combined in order to analyze the channel transmission losses of a large reach of the Jaguaribe River in NE Brazil. A perceptual model of this reach was derived suggesting that the application of models, which were developed for sub-humid and temperate regions, may be more suitable for this reach than classical models, which were developed for arid and semi-arid regions. Summarily, it was shown that this river reach is hydraulically connected with groundwater and shifts from being a losing river at the dry and beginning of rainy seasons to become a losing/gaining (mostly losing) river at the middle and end of rainy seasons. A new semi-distributed channel transmission losses model was developed, which was based primarily on the capability of simulation in very different dryland environments and flexible model structures for testing hypotheses on the dominant hydrological processes of rivers. This model was successfully tested in a large reach of the Jaguaribe River in NE Brazil and a small stream in the Walnut Gulch Experimental Watershed in the SW USA. Hypotheses on the dominant processes of the channel transmission losses (different model structures) in the Jaguaribe river were evaluated, showing that both lateral (stream-)aquifer water fluxes and ground-water flow in the underlying alluvium parallel to the river course are necessary to predict streamflow and channel transmission losses, the former process being more relevant than the latter. This procedure not only reduced model structure uncertainties, but also reported modelling failures rejecting model structure hypotheses, namely streamflow without river-aquifer interaction and stream-aquifer flow without groundwater flow parallel to the river course. The application of the model to different dryland environments enabled learning about the model itself from differences in channel reach responses. For example, the parameters related to the unsaturated part of the model, which were active for the small reach in the USA, presented a much greater variation in the sensitivity coefficients than those which drove the saturated part of the model, which were active for the large reach in Brazil. Moreover, a nonparametric approach, which dealt with both deterministic evolution and inherent fluctuations in river discharge data, was developed based on a qualitative dynamical system-based criterion, which involved a learning process about the structure of the time series, instead of a fitting procedure only. This approach, which was based only on the discharge time series itself, was applied to a headwater catchment in Germany, in which runoff are induced by either convective rainfall during the summer or snow melt in the spring. The application showed the following important features: • the differences between runoff measurements were more suitable than the actual runoff measurements when using regression models; • the catchment runoff system shifted from being a possible dynamical system contaminated with noise to a linear random process when the interval time of the discharge time series increased; • and runoff underestimation can be expected for rising limbs and overestimation for falling limbs. This nonparametric approach was compared with a distributed hydrological model designed for real-time flood forecasting, with both presenting similar results on average. Finally, a benchmark for hydrological research using semi-distributed modelling was proposed, based on the aforementioned analysis, modelling and forecasting of flow transmission processes. The aim of this benchmark was not to describe a blue-print for hydrological modelling design, but rather to propose a scientific method to improve hydrological knowledge using semi-distributed hydrological modelling. Following the application of the proposed benchmark to a case study, the actual state of its hydrological knowledge and its predictive uncertainty can be determined, primarily through rejected hypotheses on the dominant hydrological processes and differences in catchment/variables responses.}, 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} } @article{BronstertdeAraujoBatallaVillanuevaetal.2014, author = {Bronstert, Axel and de Araujo, Jose-Carlos and Batalla Villanueva, Ramon J. and Costa, Alexandre Cunha and Delgado, Jos{\´e} Miguel Martins and Francke, Till and F{\"o}rster, Saskia and Guentner, Andreas and Lopez-Tarazon, Jos{\´e} Andr{\´e}s and Mamede, George Leite and Medeiros, Pedro Henrique Augusto and Mueller, Eva and Vericat, Damia}, title = {Process-based modelling of erosion, sediment transport and reservoir siltation in mesoscale semi-arid catchments}, series = {Journal of soils and sediments : protection, risk assessment and remediation}, volume = {14}, journal = {Journal of soils and sediments : protection, risk assessment and remediation}, number = {12}, publisher = {Springer}, address = {Heidelberg}, issn = {1439-0108}, doi = {10.1007/s11368-014-0994-1}, pages = {2001 -- 2018}, year = {2014}, abstract = {To support scientifically sound water management in dryland environments a modelling system has been developed for the quantitative assessment of water and sediment fluxes in catchments, transport in the river system, and retention in reservoirs. The spatial scale of interest is the mesoscale because this is the scale most relevant for management of water and land resources. This modelling system comprises process-oriented hydrological components tailored for dryland characteristics coupled with components comprising hillslope erosion, sediment transport and reservoir deposition processes. The spatial discretization is hierarchically designed according to a multi-scale concept to account for particular relevant process scales. The non-linear and partly intermittent run-off generation and sediment dynamics are dealt with by accounting for connectivity phenomena at the intersections of landscape compartments. The modelling system has been developed by means of data from nested research catchments in NE-Spain and in NE-Brazil. In the semi-arid NE of Brazil sediment retention along the topography is the main process for sediment retention at all scales, i.e. the sediment delivery is transport limited. This kind of deposition retains roughly 50 to 60 \% of eroded sediment, maintaining a similar deposition proportion in all spatial scales investigated. On the other hand, the sediment retained in reservoirs is clearly related to the scale, increasing with catchment area. With increasing area, there are more reservoirs, increasing the possibility of deposition. Furthermore, the area increase also promotes an increase in flow volume, favouring the construction of larger reservoirs, which generally overflow less frequently and retain higher sediment fractions. The second example comprises a highly dynamic Mediterranean catchment in NE-Spain with nested sub-catchments and reveals the full dynamics of hydrological, erosion and deposition features. The run-off modelling performed well with only some overestimation during low-flow periods due to the neglect of water losses along the river. The simulated peaks in sediment flux are reproduced well, while low-flow sediment transport is less well captured, due to the disregard of sediment remobilization in the riverbed during low flow. This combined observation and modelling study deepened the understanding of hydro-sedimentological systems characterized by flashy run-off generation and by erosion and sediment transport pulses through the different landscape compartments. The connectivity between the different landscape compartments plays a very relevant role, regarding both the total mass of water and sediment transport and the transport time through the catchment.}, 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} }