Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment

Self Cite

Abstract. Many environmental systems models, such as conceptual rainfall-runoff models, rely on model calibration for parameter identification. For this, an observed output time series (such as runoff) is needed, but frequently not available (e.g., when making predictions in ungauged basins). In this study, we provide an alternative approach for parameter identification using constraints based on two types of restrictions derived from prior (or expert) knowledge. The first, called parameter constraints, restricts the solution space based on realistic relationships that must hold between the different model parameters while the second, called process constraints requires that additional realism relationships between the fluxes and state variables must be satisfied. Specifically, we propose a search algorithm for finding parameter sets that simultaneously satisfy such constraints, based on stepwise sampling of the parameter space. Such parameter sets have the desirable property of being consistent with the modeler's intuition of how the catchment functions, and can (if necessary) serve as prior information for further investigations by reducing the prior uncertainties associated with both calibration and prediction.

Section: Constraints In Environmental Modelsmentioning

confidence: 99%

A constraint-based search algorithm for parameter identification of environmental models

Gharari

Shafiei

Hrachowitz

et al. 2014

Self Cite

“…When carefully implemented, spatially distributed formulations, e.g. based on hydrological response units or related concepts (Beven and Kirkby, 1979;Knudsen et al, 1986;Flügel, 1995;Winter, 2001;Seibert et al, 2003;Uhlenbrook et al, 2004, 2010Schmocker-Fackel et al, 2007Gharari et al, 2011;Zehe et al, 2014;Haghnegahdar et al, 2015), with an equilibrated balance between process heterogeneity and information/data availability and tested and evaluated against multivariate observed response dynamics, and conceptual models have been shown to be versatile enough to identify and represent the dominant hydrological processes and their heterogeneity in a catchment (e.g. Boyle et al, 2001;Fenicia et al, 2008a, b;Winsemius et al, 2008;Kumar et al, 2013;Hrachowitz et al, 2014;Nijzink et al, 2016a) within limited uncertainty.…”

Section: Modelling Myths -Or Not?mentioning

confidence: 99%

HESS Opinions: The complementary merits of competing modelling philosophies in hydrology

Hrachowitz

Clark

2017

183

130

Abstract. In hydrology, two somewhat competing philosophies form the basis of most process-based models. At one endpoint of this continuum are detailed, high-resolution descriptions of small-scale processes that are numerically integrated to larger scales (e.g. catchments). At the other endpoint of the continuum are spatially lumped representations of the system that express the hydrological response via, in the extreme case, a single linear transfer function. Many other models, developed starting from these two contrasting endpoints, plot along this continuum with different degrees of spatial resolutions and process complexities. A better understanding of the respective basis as well as the respective shortcomings of different modelling philosophies has the potential to improve our models. In this paper we analyse several frequently communicated beliefs and assumptions to identify, discuss and emphasize the functional similarity of the seemingly competing modelling philosophies. We argue that deficiencies in model applications largely do not depend on the modelling philosophy, although some models may be more suitable for specific applications than others and vice versa, but rather on the way a model is implemented. Based on the premises that any model can be implemented at any desired degree of detail and that any type of model remains to some degree conceptual, we argue that a convergence of modelling strategies may hold some value for advancing the development of hydrological models.

“…The delineation of HRUs by combinations of these layers requires a categorization of its characteristics (soils, land-use and vegetation types, topography, and geology) to keep the number of HRUs at a manageable level, both the selection of criteria and their subdivision into classes at an acceptable degree of heterogeneity within the hydrological system. Subject to the chosen technique or purpose of HRUs, their models omit the actual spatial allocation (Lindström et al, 1997;Schumann et al, 2000) or define coherent units (Dunn and Lilly, 2001;Soulsby et al, 2006;Müller et al, 2009;Nobre et al, 2011;Gharari et al, 2011). However, some of these models try to transfer geological information (Müller et al, 2009;Soulsby et al, 2006) or topographical information (Nobre et al, 2011;Gharari et al, 2011) to hydrological processes and assume homogeneous conditions of the remaining parameters.…”

Section: Introductionmentioning

confidence: 99%

A method to employ the spatial organization of catchments into semi-distributed rainfall–runoff models

Oppel

Schumann

2017

Abstract.A distributed or semi-distributed deterministic hydrological model should consider the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject to a certain spatial organization which results in archetypes of combined characteristics. In order to reproduce the natural rainfall-runoff response the reduction of variance of catchment properties as well as the incorporation of the spatial organization of the catchment are desirable. In this study the width-function approach is utilized as a basic characteristic to analyse the succession of catchment characteristics. By applying this technique we were able to assess the context of catchment properties like soil or topology along the streamflow length and the network geomorphology, giving indications of the spatial organization of a catchment. Moreover, this information and this technique have been implemented in an algorithm for automated sub-basin ascertainment, which included the definition of zones within the newly defined sub-basins. The objective was to provide subbasins that were less heterogeneous than common separation schemes. The algorithm was applied to two parameters characterizing the topology and soil of four mid-European watersheds. Resulting partitions indicated a wide range of applicability for the method and the algorithm. Additionally, the intersection of derived zones for different catchment characteristics could give insights into sub-basin similarities. Finally, a HBV 96 case study demonstrated the potential benefits of modelling with the new subdivision technique.