TY - GEN A1 - Guse, Björn A1 - Pfannerstill, Matthias A1 - Gafurov, Abror A1 - Kiesel, Jens A1 - Lehr, Christian A1 - Fohrer, Nicola T1 - Identifying the connective strength between model parameters and performance criteria T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria.& para;& para;To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE) and its three components (alpha, beta and r) as well as RSR (the ratio of the root mean square error to the standard deviation) for different segments of the flow duration curve (FDC) are calculated.& para;& para;With a joint analysis of two regression tree (RT) approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter.& para;& para;In this study, a high bijective connective strength between model parameters and performance criteria is found for low- and mid-flow conditions. Moreover, the RT analyses emphasise the benefit of an individual analysis of the three components of KGE and of the FDC segments. Furthermore, the RT analyses highlight under which conditions these performance criteria provide insights into precise parameter identification. Our results show that separate performance criteria are required to identify dominant parameters on low- and mid-flow conditions, whilst the number of required performance criteria for high flows increases with increasing process complexity in the catchment. Overall, the analysis of the connective strength between model parameters and performance criteria using RTs contribute to a more realistic handling of parameters and performance criteria in hydrological modelling. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 657 KW - flow-duration curves KW - hydrological models KW - multiobjective calibration KW - sensitivity-analysis KW - landscape controls KW - lowland catchment KW - regional patterns KW - physical controls KW - water-balance KW - part 1 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419142 SN - 1866-8372 IS - 657 ER - TY - JOUR A1 - Guse, Björn A1 - Pfannerstill, Matthias A1 - Gafurov, Abror A1 - Kiesel, Jens A1 - Lehr, Christian A1 - Fohrer, Nicola T1 - Identifying the connective strength between model parameters and performance criteria JF - Hydrology and earth system sciences : HESS N2 - In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria.& para;& para;To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE) and its three components (alpha, beta and r) as well as RSR (the ratio of the root mean square error to the standard deviation) for different segments of the flow duration curve (FDC) are calculated.& para;& para;With a joint analysis of two regression tree (RT) approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter.& para;& para;In this study, a high bijective connective strength between model parameters and performance criteria is found for low- and mid-flow conditions. Moreover, the RT analyses emphasise the benefit of an individual analysis of the three components of KGE and of the FDC segments. Furthermore, the RT analyses highlight under which conditions these performance criteria provide insights into precise parameter identification. Our results show that separate performance criteria are required to identify dominant parameters on low- and mid-flow conditions, whilst the number of required performance criteria for high flows increases with increasing process complexity in the catchment. Overall, the analysis of the connective strength between model parameters and performance criteria using RTs contribute to a more realistic handling of parameters and performance criteria in hydrological modelling. Y1 - 2017 U6 - https://doi.org/10.5194/hess-21-5663-2017 SN - 1027-5606 SN - 1607-7938 VL - 21 SP - 5663 EP - 5679 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Müller, Eva Nora A1 - van Schaik, Loes A1 - Blume, Theresa A1 - Bronstert, Axel A1 - Carus, Jana A1 - Fleckenstein, Jan H. A1 - Fohrer, Nicola A1 - Geissler, Katja A1 - Gerke, Horst H. A1 - Gräff, Thomas A1 - Hesse, Cornelia A1 - Hildebrandt, Anke A1 - Hölker, Franz A1 - Hunke, Philip A1 - Körner, Katrin A1 - Lewandowski, Jörg A1 - Lohmann, Dirk A1 - Meinikmann, Karin A1 - Schibalski, Anett A1 - Schmalz, Britta A1 - Schröder-Esselbach, Boris A1 - Tietjen, Britta T1 - Scales, key aspects, feedbacks and challenges of ecohydrological research in Germany JF - Hydrologie und Wasserbewirtschaftung N2 - Ecohydrology analyses the interactions of biotic and abiotic aspects of our ecosystems and landscapes. It is a highly diverse discipline in terms of its thematic and methodical research foci. This article gives an overview of current German ecohydrological research approaches within plant-animal-soil-systems, meso-scale catchments and their river networks, lake systems, coastal areas and tidal rivers. It discusses their relevant spatial and temporal process scales and different types of interactions and feedback dynamics between hydrological and biotic processes and patterns. The following topics are considered key challenges: innovative analysis of the interdisciplinary scale continuum, development of dynamically coupled model systems, integrated monitoring of coupled processes at the interface and transition from basic to applied ecohydrological science to develop sustainable water and land resource management strategies under regional and global change. KW - Coastal regions KW - drylands KW - ecohydrological modelling KW - feedback KW - hyporheic zone KW - meso-scale ecosystems KW - plant-animal-soil-system KW - river networks Y1 - 2014 U6 - https://doi.org/10.5675/HyWa_2014,4_2 SN - 1439-1783 VL - 58 IS - 4 SP - 221 EP - 240 PB - Bundesanst. für Gewässerkunde CY - Koblenz ER -