@article{KneisKnoescheBronstert2004, author = {Kneis, David and Kn{\"o}sche, R{\"u}diger and Bronstert, Axel}, title = {Ist eine Auswaschung von N{\"a}hrstoffen aus Flussgew{\"a}ssersedimenten eine realistische Option zur Trophiesenkung?}, isbn = {3-937758-18-6}, year = {2004}, language = {de} } @article{KneisKnoescheBronstert2004, author = {Kneis, David and Kn{\"o}sche, R{\"u}diger and Bronstert, Axel}, title = {Ist ein Netto-N{\"a}hrstoffexport aus Flussgew{\"a}ssersedimenten eine realistische Option zur Trophiesenkung?}, isbn = {3-937758-18-6}, year = {2004}, language = {de} } @article{BuergerReusserKneis2009, author = {B{\"u}rger, Gerd and Reusser, Dominik and Kneis, David}, title = {Early flood warnings from empirical (expanded) downscaling of the full ECMWF Ensemble Prediction System}, issn = {0043-1397}, doi = {10.1029/2009wr007779}, year = {2009}, language = {en} } @article{BronstertKneisBogena2009, author = {Bronstert, Axel and Kneis, David and Bogena, Heye R.}, title = {Interactions and feedbacks in hydrological change : relevance and possibilities of modelling}, issn = {1439-1783}, year = {2009}, abstract = {The hydrological cycle is a dynamic system by its nature, but sometimes accelerated through anthropogenic activity. A "hydrological change" (i.e. a water cycle that is significantly changing over a longer period of time) can be very different in character, depending on the specific natural conditions and the underlying spatial and temporal scales. Such changes may affect the availability and quality of water as essential pre-requisites for human development and ecosystem stability. Hydrological extremes, such as floods and droughts, may also be affected, what is also vitally important, because of their profound economic and societal impacts. Anthropogenically induced hydrological change can be attributed to three main external causes: first, the Earth's climate is changing significantly and thus directly affecting the terrestrial hydro-systems via the exchange of energy and heat. The second major issue is the land cover and its management that has been modified fundamentally by conversion of land for agriculture, forestry, and other purposes such as industrialisation and urbanisation. Finally, water resources are being used more than ever for human development, especially for agriculture, industrial activities, and navigation. If the regional terrestrial hydrological cycle is changing and counter-measures are desirable, it is from a scientific perspective mandatory to understand the extent and nature of such changes, and, especially, to identify their possible anthropogenic origin. There are, however, fundamental gaps in our knowledge, in particular about the role of feedbacks between individual processes and compartments of the hydrological cycle or the relevance of the interactions with other sub-systems of our planet, such as the atmosphere or the vegetation. This paper mentions several examples of hydrological change and discusses their identification, interaction processes, and feedback mechanisms, along with modelling issues. The possibilities and limitations of modelling are demonstrated by means of two studies: one from the river-lake system on the Middle-Havel River and one from the catchment of the Wahnbach Reservoir. The applied model systems comprise a series of consecutively coupled individual models (so-called one-way-coupling). Model systems that are able reflect feedback effects (two-way- coupling) are still in the development stage. It became clear that the applied model systems were able to reproduce the observed dynamics of the hydrological cycle and of selected matter fluxes. However, one has to be aware that the simulated time periods and scenarios represent rather moderately transient conditions, what is the justification why the one-way-coupling seems to be applicable. Furthermore, it was shown that the modelling uncertainty is considerably large. Nevertheless, this uncertainty can be distinguished from effects of changed internal systems dynamics or from changed boundary conditions, what is a basis for the usability of such model systems for prognostic purposes.}, language = {en} } @article{KneisFoersterBronstert2009, author = {Kneis, David and F{\"o}rster, Saskia and Bronstert, Axel}, title = {Simulation of water quality in a flood detention area using models of different spatial discretization}, issn = {0304-3800}, doi = {10.1016/j.ecolmodel.2009.04.006}, year = {2009}, abstract = {Detention areas provide a means to lower peak discharges in rivers by temporarily storing excess water. In the case of extreme flood events, the storage effect reduces the risk of dike failures or extensive inundations for downstream reaches and near the site of abstraction. Due to the large amount of organic matter contained in the river water and the inundation of terrestrial vegetation in the detention area, a deterioration of water quality may occur. In particular, decay processes can cause a severe depletion of dissolved oxygen (DO) in the temporary water body. In this paper, we studied the potential of a water quality model to simulate the DO dynamics in a large but shallow detention area to be built at the Elbe River (Germany). Our focus was on examining the impact of spatial discretization on the model's performance and usability. Therefore, we used a zero-dimensional (OD) and a two-dimensional (2D) modeling approach in parallel. The two approaches solely differ in their spatial discretization, while conversion processes, parameters, and boundary conditions were kept identical. The dynamics of DO simulated by the two models are similar in the initial flooding period but diverge when the system starts to drain. The deviation can be attributed to the different spatial discretization of the two models, leading to different estimates of flow velocities and water depths. Only the 2D model can account for the impact of spatial variability on the evolution of state variables. However, its application requires high efforts for pre- and post-processing and significantly longer computation times. The 2D model is, therefore, not suitable for investigating various flood scenarios or for analyzing the impact of parameter uncertainty. For practical applications, we recommend to firstly set up a fast-running model of reduced spatial discretization, e.g. a OD model. Using this tool, the reliability of the simulation results should be checked by analyzing the parameter uncertainty of the water quality model. A particular focus may be on those parameters that are spatially variable and, therefore, believed to be better represented in a 2D approach. The benefit from the application of the more costly 2D model should be assessed, based on the analyses carried out with the OD model. A 2D model appears to be preferable only if the simulated detention area has a complex topography, flow velocities are highly variable in space, and the parameters of the water quality model are well known.}, language = {en} } @article{BronstertKneisBogena2009, author = {Bronstert, Axel and Kneis, David and Bogena, Heye R.}, title = {Interaktionen und R{\"u}ckkopplungen beim hydrologischen Wandel : Relevanz und M{\"o}glichkeiten der Modellierung}, issn = {1439-1783}, year = {2009}, language = {de} } @article{KneisHeistermann2009, author = {Kneis, David and Heistermann, Maik}, title = {Bewertung der G{\"u}te einer Radar-basierten Niederschlagssch{\"a}tzung am Beispiel eines kleinen Einzugsgebiets}, issn = {1439-1783}, year = {2009}, language = {de} } @article{HeistermannKneis2011, author = {Heistermann, Maik and Kneis, David}, title = {Benchmarking quantitative precipitation estimation by conceptual rainfall-runoff modeling}, series = {Water resources research}, volume = {47}, journal = {Water resources research}, number = {23}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2010WR009153}, pages = {23}, year = {2011}, abstract = {Hydrologic modelers often need to know which method of quantitative precipitation estimation (QPE) is best suited for a particular catchment. Traditionally, QPE methods are verified and benchmarked against independent rain gauge observations. However, the lack of spatial representativeness limits the value of such a procedure. Alternatively, one could drive a hydrological model with different QPE products and choose the one which best reproduces observed runoff. Unfortunately, the calibration of conceptual model parameters might conceal actual differences between the QPEs. To avoid such effects, we abandoned the idea of determining optimum parameter sets for all QPE being compared. Instead, we carry out a large number of runoff simulations, confronting each QPE with a common set of random parameters. By evaluating the goodness-of-fit of all simulations, we obtain information on whether the quality of competing QPE methods is significantly different. This knowledge is inferred exactly at the scale of interest-the catchment scale. We use synthetic data to investigate the ability of this procedure to distinguish a truly superior QPE from an inferior one. We find that the procedure is prone to failure in the case of linear systems. However, we show evidence that in realistic (nonlinear) settings, the method can provide useful results even in the presence of moderate errors in model structure and streamflow observations. In a real-world case study on a small mountainous catchment, we demonstrate the ability of the verification procedure to reveal additional insights as compared to a conventional cross validation approach.}, language = {en} } @article{KneisChatterjeeSingh2014, author = {Kneis, David and Chatterjee, C. and Singh, R.}, title = {Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)}, series = {Hydrology and earth system sciences : HESS}, volume = {18}, journal = {Hydrology and earth system sciences : HESS}, number = {7}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-18-2493-2014}, pages = {2493 -- 2502}, year = {2014}, abstract = {The paper examines the quality of satellite-abased precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-aadjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-astep procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the subbasin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-arunoff simulation. At sub-abasin level (4000 to 16 000 km(2)) the satellite-abased areal precipitation estimates were found to be moderately correlated with the gauge-abased counterparts (R-2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-aintensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate < 0.6 for ground-abased intensities > 80 mm day(-1)). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-abased equivalents (false alarm ratios of 0.2-0.6). In addition, the real-atime product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-arunoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by reservoir operation). This compares to the values of 0.71-0.78 for the gauge-djusted TRMM 3B42 data and 0.65-0.77 for the 3B42-RT real-atime data. Whether the 3B42-RT data are useful in the context of operational runoff prediction in spite of the identified problems remains a question for further research.}, language = {en} } @article{Kneis2015, author = {Kneis, David}, title = {A lightweight framework for rapid development of object-based hydrological model engines}, series = {Environmental modelling \& software with environment data news}, volume = {68}, journal = {Environmental modelling \& software with environment data news}, publisher = {Elsevier}, address = {Oxford}, issn = {1364-8152}, doi = {10.1016/j.envsoft.2015.02.009}, pages = {110 -- 121}, year = {2015}, abstract = {Computer-based simulation models are frequently used in hydrological research and engineering but also in other fields of environmental sciences. New case studies often require existing model concepts to be adapted. Extensions may be necessary due to the peculiarities of the studied natural system or subtleties of anthropogenic control. In other cases, simplifications must be made in response to scarce data, incomplete knowledge, or restrictions set by the spatio-temporal scale of application. This paper introduces an open-source modeling framework called ECHSE designed to cope with the above-mentioned challenges. It provides a lightweight infrastructure for the rapid development of new, reusable simulation tools and, more importantly, the safe modification of existing formulations. ECHSE-based models treat the simulated system as a collection of interacting objects. Although feedbacks are generally supported, the majority of the objects' interactions is expected to be of the feed-forward type. Therefore, the ECHSE software is particularly useful in the context of hydrological catchment modeling. Conversely, it is unsuitable, e.g., for fully hydrodynamic simulations and groundwater flow modeling. The focus of the paper is put on a comprehensible outline of the ECHSE's fundamental concepts and limitations. For the purpose of illustration, a specific, ECHSE-based solution for hydrological catchment modeling is presented which has undergone testing in a number of river basins. (C) 2015 Elsevier Ltd. All rights reserved.}, language = {en} }