Performance of the COSERO precipitation–runoff model under non-stationary conditions in basins with different climates

Kling, Harald; Stanzel, Philipp; Fuchs, M; Nachtnebel, Hans-Peter

doi:10.1080/02626667.2014.959956

Cited by 50 publications

(50 citation statements)

References 39 publications

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“…Originally developed for modelling discharge of the Austrian rivers Enns and Steyr (Nachtnebel et al, 1993), it has recently been used for different purposes like climate change studies (e.g. Kling et al, 2012Kling et al, , 2014bStanzel and Nachtnebel, 2010), investigating the role of evapotranspiration in high alpine regions (Herrnegger et al, 2012) and operational runoff forecasting (Stanzel et al, 2008). Potential evapotranspiration is calculated using the Thornthwaite method (Thornthwaite, 1948).…”

Section: Hydrological Model Coseromentioning

confidence: 99%

A conceptual, distributed snow redistribution model

Frey

Holzmann

2015

Hydrol. Earth Syst. Sci.

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Abstract. When applying conceptual hydrological models using a temperature index approach for snowmelt to high alpine areas often accumulation of snow during several years can be observed. Some of the reasons why these "snow towers" do not exist in nature are vertical and lateral transport processes. While snow transport models have been developed using grid cell sizes of tens to hundreds of square metres and have been applied in several catchments, no model exists using coarser cell sizes of 1 km 2 , which is a common resolution for meso-and large-scale hydrologic modelling (hundreds to thousands of square kilometres). In this paper we present an approach that uses only gravity and snow density as a proxy for the age of the snow cover and land-use information to redistribute snow in alpine basins. The results are based on the hydrological modelling of the Austrian Inn Basin in Tyrol, Austria, more specifically the Ötztaler Ache catchment, but the findings hold for other tributaries of the river Inn. This transport model is implemented in the distributed rainfall-runoff model COSERO (Continuous Semidistributed Runoff). The results of both model concepts with and without consideration of lateral snow redistribution are compared against observed discharge and snow-covered areas derived from MODIS satellite images. By means of the snow redistribution concept, snow accumulation over several years can be prevented and the snow depletion curve compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data could be improved, too. In a 7-year period the standard model would lead to snow accumulation of approximately 2900 mm SWE (snow water equivalent) in high elevated regions whereas the updated version of the model does not show accumulation and does also predict discharge with more accuracy leading to a Kling-Gupta efficiency of 0.93 instead of 0.9. A further improvement can be shown in the comparison of MODIS snow cover data and the calculated depletion curve, where the redistribution model increased the efficiency (R 2 ) from 0.70 to 0.78 (calibration) and from 0.66 to 0.74 (validation).

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Section: Hydrological Model Coseromentioning

confidence: 99%

A conceptual, distributed snow redistribution model

Frey

Holzmann

2015

Hydrol. Earth Syst. Sci.

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“…In different from the calibration period, the model performance can be expected to deteriorate, as has been shown before (e.g. Kling, 2015;Seibert, 2003), and explains the findings. Figures 6 (Schliefau) and 7 (Krems) exemplarily show the runoff simulations based on the results of Exp 2 .…”

Section: Forward Model: Parameter Calibration and Validation Of The Dmentioning

confidence: 64%

“…Also due to the larger number of model parameters describing several linked storages, accounting for a variety of different runoff components, HBV-type conceptual models offer higher degrees of freedom and flexibility in the calibration procedure. They can, in consequence, be applied to catchments with a wider range of runoff characteristics (Bergström, 1995;Kling et al, 2015;Kling, 2006;Perrin et al, 2001). Therefore, in this study, the conceptual rainfall-runoff model COSERO (COntinuous SEmi-distributed RunOff Model; Nachtnebel et al, 1993;Eder et al, 2005;Kling and Nachtnebel, 2009;Herrnegger et al, 2012;Kling et al, 2015; among others), which in its structure is similar to the HBV model, is used as a basis for the inverse model.…”

Section: Catchment Precipitation From Runoff Observations Through Invmentioning

confidence: 99%

“…They can, in consequence, be applied to catchments with a wider range of runoff characteristics (Bergström, 1995;Kling et al, 2015;Kling, 2006;Perrin et al, 2001). Therefore, in this study, the conceptual rainfall-runoff model COSERO (COntinuous SEmi-distributed RunOff Model; Nachtnebel et al, 1993;Eder et al, 2005;Kling and Nachtnebel, 2009;Herrnegger et al, 2012;Kling et al, 2015; among others), which in its structure is similar to the HBV model, is used as a basis for the inverse model. The COSERO model has been frequently applied in research studies and in engineering projects (see Kling et al, 2015 for details).…”

Section: Catchment Precipitation From Runoff Observations Through Invmentioning

confidence: 99%

“…For the application, monthly INTMAX and ETVEGCOR values were calculated as area-weighted mean values, depending on the land uses in the catchments, since a lumped setup is used. For the implementation of the evapotranspiration calculations in the model the reader is also referred to Kling et al (2015).…”

Section: Model Calibration and Simulations Experiments With Observed mentioning

confidence: 99%

See 2 more Smart Citations

From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

Herrnegger

Nachtnebel

Schulz

2015

Hydrol. Earth Syst. Sci.

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Abstract. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall-runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.

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Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models

Klotz

Herrnegger

Schulz

2017

Water Resources Research

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Current concepts for parameter regionalization of spatially distributed rainfall‐runoff models rely on the a priori definition of transfer functions that globally map land surface characteristics (such as soil texture, land use, and digital elevation) into the model parameter space. However, these transfer functions are often chosen ad hoc or derived from small‐scale experiments. This study proposes and tests an approach for inferring the structure and parametrization of possible transfer functions from runoff data to potentially circumvent these difficulties. The concept uses context‐free grammars to generate possible proposition for transfer functions. The resulting structure can then be parametrized with classical optimization techniques. Several virtual experiments are performed to examine the potential for an appropriate estimation of transfer function, all of them using a very simple conceptual rainfall‐runoff model with data from the Austrian Mur catchment. The results suggest that a priori defined transfer functions are in general well identifiable by the method. However, the deduction process might be inhibited, e.g., by noise in the runoff observation data, often leading to transfer function estimates of lower structural complexity.

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Performance of the COSERO precipitation–runoff model under non-stationary conditions in basins with different climates

Cited by 50 publications

References 39 publications

A conceptual, distributed snow redistribution model

A conceptual, distributed snow redistribution model

From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models

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