TY - JOUR A1 - Jackisch, Conrad A1 - Zehe, Erwin A1 - Samaniego, Luis A1 - Singh, Anupam K. T1 - An experiment to gauge an ungauged catchment: rapid data assessment and eco-hydrological modelling in a data-scarce rural catchment JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - We conducted a PUB (predictions in ungauged basins) experiment looking at hydrology and crop dynamics in the semi-arid rural Mod catchment in India. The experiment was motivated by the aims (a) to develop a coupled eco-hydrological model capable of analysing land-use strategies concerning crop water need, erosion protection, crop yield and resistivity against droughts and floods, and (b) to assess the feasibility of a strategy for collecting the necessary data in a data-scarce region. Our experiment combines parsimonious data assessment and eco-hydrological model coupling at the lower mesoscale. Linking bottom-up sampling of functionally representative soil classes and top-down regionalization based on spectral properties of the same resulted in a comprehensive distributed data basis for the model. A clear focus on the dominating processes and the catena as the organizing landscape element in the given environmental setting enabled this. We employed the WASA (Water Availability in Semi-Arid environments) model for uncalibrated process-based water balance modelling and integrated a crop simulation subroutine based on the SWAP (Soil Water Atmosphere Plant) model to account for crop dynamics, feedbacks and yield estimation. While we found the data assessment strategy and the hydrological model application largely feasible, in terms of its accounting for scale, processes and model concepts, the simulation of feedbacks with crops was problematic. Contributing to the PUB issue, more general conclusions are drawn concerning spatially-distributed structural information and uncalibrated modelling. [GRAPHICS] Editor Z.W. Kundzewicz; Associate editor F. Hattermann KW - rural KW - model coupling KW - eco-hydrological modelling KW - semi-arid KW - Prediction in Ungauged Basins (PUB) Y1 - 2014 U6 - https://doi.org/10.1080/02626667.2013.870662 SN - 0262-6667 SN - 2150-3435 VL - 59 IS - 12 SP - 2103 EP - 2125 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - THES A1 - Knopf, Brigitte T1 - On intrinsic uncertainties in earth system modelling T1 - Intrinsische Unsicherheiten in der Erdsystem Modellierung N2 - Uncertainties are pervasive in the Earth System modelling. This is not just due to a lack of knowledge about physical processes but has its seeds in intrinsic, i.e. inevitable and irreducible, uncertainties concerning the process of modelling as well. Therefore, it is indispensable to quantify uncertainty in order to determine, which are robust results under this inherent uncertainty. The central goal of this thesis is to explore how uncertainties map on the properties of interest such as phase space topology and qualitative dynamics of the system. We will address several types of uncertainty and apply methods of dynamical systems theory on a trendsetting field of climate research, i.e. the Indian monsoon. For the systematic analysis concerning the different facets of uncertainty, a box model of the Indian monsoon is investigated, which shows a saddle node bifurcation against those parameters that influence the heat budget of the system and that goes along with a regime shift from a wet to a dry summer monsoon. As some of these parameters are crucially influenced by anthropogenic perturbations, the question is whether the occurrence of this bifurcation is robust against uncertainties in parameters and in the number of considered processes and secondly, whether the bifurcation can be reached under climate change. Results indicate, for example, the robustness of the bifurcation point against all considered parameter uncertainties. The possibility of reaching the critical point under climate change seems rather improbable. A novel method is applied for the analysis of the occurrence and the position of the bifurcation point in the monsoon model against parameter uncertainties. This method combines two standard approaches: a bifurcation analysis with multi-parameter ensemble simulations. As a model-independent and therefore universal procedure, this method allows investigating the uncertainty referring to a bifurcation in a high dimensional parameter space in many other models. With the monsoon model the uncertainty about the external influence of El Niño / Southern Oscillation (ENSO) is determined. There is evidence that ENSO influences the variability of the Indian monsoon, but the underlying physical mechanism is discussed controversially. As a contribution to the debate three different hypotheses are tested of how ENSO and the Indian summer monsoon are linked. In this thesis the coupling through the trade winds is identified as key in linking these two key climate constituents. On the basis of this physical mechanism the observed monsoon rainfall data can be reproduced to a great extent. Moreover, this mechanism can be identified in two general circulation models (GCMs) for the present day situation and for future projections under climate change. Furthermore, uncertainties in the process of coupling models are investigated, where the focus is on a comparison of forced dynamics as opposed to fully coupled dynamics. The former describes a particular type of coupling, where the dynamics from one sub-module is substituted by data. Intrinsic uncertainties and constraints are identified that prevent the consistency of a forced model with its fully coupled counterpart. Qualitative discrepancies between the two modelling approaches are highlighted, which lead to an overestimation of predictability and produce artificial predictability in the forced system. The results suggest that bistability and intermittent predictability, when found in a forced model set-up, should always be cross-validated with alternative coupling designs before being taken for granted. All in this, this thesis contributes to the fundamental issue of dealing with uncertainties the climate modelling community is confronted with. Although some uncertainties allow for including them in the interpretation of the model results, intrinsic uncertainties could be identified, which are inevitable within a certain modelling paradigm and are provoked by the specific modelling approach. N2 - Die vorliegende Arbeit untersucht, auf welche Weise Unsicherheiten, wie sie in der integrierten Klima(folgen)forschung allgegenwärtig sind, die Stabilität und die Struktur dynamischer Systeme beeinflussen. Im Rahmen der Erdsystemmodellierung wird der Unsicherheitsanalyse zunehmend eine zentrale Bedeutung beigemessen. Einerseits können mit ihrer Hilfe disziplinäre Qualitäts-standards verbessert werden, andererseits ergibt sich die Chance, im Zuge von "Integrated Assessment" robuste entscheidungsrelevante Aussagen abzuleiten. Zur systematischen Untersuchung verschiedener Arten von Unsicherheit wird ein konzeptionelles Modell des Indischen Monsuns eingesetzt, das einen übergang von einem feuchten in ein trockenes Regime aufgrund einer Sattel-Knoten-Bifurkation in Abhängigkeit derjenigen Parameter zeigt, die die Wärmebilanz des Systems beeinflussen. Da einige dieser Parameter anthropogenen Einflüssen und Veränderungen unterworfen sind, werden zwei zentrale Punkte untersucht: zum einen, ob der Bifurkationspunkt robust gegenüber Unsicherheiten in Parametern und in Bezug auf die Anzahl und die Art der im Modell implementierten Prozesse ist und zum anderen, ob durch anthropogenen Einfluss der Bifurkationspunkt erreicht werden kann. Es zeigt sich unter anderem, dass das Auftreten der Bifurkation überaus robust, die Lage des Bifurkationspunktes im Phasenraum ist hingegen sehr sensitiv gegenüber Parameterunsicherheiten ist. Für diese Untersuchung wird eine neuartige Methode zur Untersuchung des Auftretens und der Lage einer Bifurkation gegenüber Unsicherheiten im hochdimensionalen Parameterraum entwickelt, die auf der Kombination einer Bifurkationsanalyse mit einer multi parametrischen Ensemble Simulation basiert. Mit dem Monsunmodell wird des weiteren die Unsicherheit bezüglich des externen Einflusses von El Niño / Southern Oscillation (ENSO) untersucht. Es ist bekannt, dass durch ENSO die Variabilität des Indischen Monsun beeinflußt wird, wohingegen der zu Grunde liegende Mechanismus kontrovers diskutiert wird. In dieser Arbeit werden drei verschiedene Hypothesen zur Kopplung zwischen diesen beiden Phänomenen untersucht. Es kann gezeigt werden, dass die Passat Winde einen Schlüsselmechanismus für den Einfluß von ENSO auf den Indischen Monsun darstellen. Mit Hilfe dieses Mechanismus können die beobachteten Niederschlagsdaten des Monsuns zu einem großen Anteil reproduziert werden. Zudem kann dieser Mechanismus kann auch in zwei globalen Zirkulationsmodellen (GCMs) für den heutigen Zustand und für ein Emissionsszenario unter Klimawandel identifiziert werden. Im weiteren Teil der Arbeit werden intrinsische Unsicherheiten identifiziert, die den Unterschied zwischen der Kopplung von Teilmodulen und dem Vorschreiben von einzelnen dieser Module durch Daten betreffen. Untersucht werden dazu ein getriebenes GCM-Ensemble und ein konzeptionelles Ozean-Atmosphären-Modell, das eine strukturierte Analyse anhand von Methoden der Theorie dynamischer Systeme ermöglicht. In den meisten Fällen kann die getriebene Version, in der ein Teil der Dynamik als externer Antrieb vorschrieben wird, das voll gekoppelte Pendant nachbilden. Es wird gezeigt, dass es jedoch auch Regionen im Phasen- und Parameterraum gibt, in dem sich die zwei Modellierungsansätze signifikant unterscheiden und unter anderem zu einer überschätzung der Vorhersagbarkeit und zu künstlichen Zuständen im getriebenen System führen. Die Ergebnisse legen den Schluss nahe, dass immer auch alternative Kopplungsmechanismen getestet werden müssen bevor das getriebene System als adäquate Beschreibung des gekoppelten Gesamtsystems betrachtet werden kann. Anhand der verschiedenen Anwendungen der Unsicherheitsanalyse macht die Arbeit deutlich, dass zum einen Unsicherheiten intrinsisch durch bestimmte Arten der Modellierung entstehen und somit unvermeidbar innerhalb eines Modellierungsansatzes sind, dass es zum anderen aber auch geeignete Methoden gibt, Unsicherheiten in die Modellierung und in die Bewertung von Modellergebnissen einzubeziehen. KW - Unsicherheit KW - Monsun KW - Klimatologie KW - Nichtlineare Dynamik KW - Unsicherheitsanalyse KW - Bifurkationsanalyse KW - Indischer Monsun KW - Modellkopplung KW - nonlinear dynamics KW - uncertainty analysis KW - bifurcation analysis KW - Indian Monsoon KW - model coupling Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-10949 ER - TY - JOUR A1 - Schibalski, Anett A1 - Körner, Katrin A1 - Maier, Martin A1 - Jeltsch, Florian A1 - Schröder, Boris T1 - Novel model coupling approach for resilience analysis of coastal plant communities JF - Ecological applications : a publication of the Ecological Society of America N2 - Resilience is a major research focus covering a wide range of topics from biodiversity conservation to ecosystem (service) management. Model simulations can assess the resilience of, for example, plant species, measured as the return time to conditions prior to a disturbance. This requires process-based models (PBM) that implement relevant processes such as regeneration and reproduction and thus successfully reproduce transient dynamics after disturbances. Such models are often complex and thus limited to either short-term or small-scale applications, whereas many research questions require species predictions across larger spatial and temporal scales. We suggest a framework to couple a PBM and a statistical species distribution model (SDM), which transfers the results of a resilience analysis by the PBM to SDM predictions. The resulting hybrid model combines the advantages of both approaches: the convenient applicability of SDMs and the relevant process detail of PBMs in abrupt environmental change situations. First, we simulate dynamic responses of species communities to a disturbance event with a PBM. We aggregate the response behavior in two resilience metrics: return time and amplitude of the response peak. These metrics are then used to complement long-term SDM projections with dynamic short-term responses to disturbance. To illustrate our framework, we investigate the effect of abrupt short-term groundwater level and salinity changes on coastal vegetation at the German Baltic Sea. We found two example species to be largely resilient, and, consequently, modifications of SDM predictions consisted mostly of smoothing out peaks in the occurrence probability that were not confirmed by the PBM. Discrepancies between SDM- and PBM-predicted species responses were caused by community dynamics simulated in the PBM and absent from the SDM. Although demonstrated with boosted regression trees (SDM) and an existing individual-based model, IBC-grass (PBM), our flexible framework can easily be applied to other PBM and SDM types, as well as other definitions of short-term disturbances or long-term trends of environmental change. Thus, our framework allows accounting for biological feedbacks in the response to short- and long-term environmental changes as a major advancement in predictive vegetation modeling. KW - Baltic Sea KW - hybrid model KW - Lolium perenne KW - model coupling KW - Scirpus maritimus KW - transient dynamics Y1 - 2018 U6 - https://doi.org/10.1002/eap.1758 SN - 1051-0761 SN - 1939-5582 VL - 28 IS - 6 SP - 1640 EP - 1654 PB - Wiley CY - Hoboken ER -