Assessing Winter Storm Flow Generation by Means Of

Hydrol. Earth Syst. Sci., 11, 1673–1682, 2007 www.hydrol-earth-syst-sci.net/11/1673/2007/ Hydrology and © Author(s) 2007. This work is licensed Earth System under a Creative Commons License. Sciences Assessing winter storm flow generation by means of permeability of the lithology and dominating runoff production processes H. Hellebrand, L. Hoffmann, J. Juilleret, and L. Pfister Public Research Center-Gabriel Lippmann, Belvaux, Grand Duchy of Luxembourg Received: 11 June 2007 – Published in Hydrol. Earth Syst. Sci. Discuss.: 26 June 2007 Revised: 11 September 2007 – Accepted: 4 October 2007 – Published: 17 October 2007 Abstract. In this study two approaches are used to predict 1 Introduction winter storm flow coefficients in meso-scale basins (10 km2 2 to 1000 km ) with a view to regionalization. The winter Regionalization is a widely used procedure in hydrology storm flow coefficient corresponds to the ratio between direct (Burn, 1997; Post and Jakeman, 1999; Kokkonen et al., 2003; discharge and rainfall. It is basin specific and supposed to Croke and Norton, 2004; Merz and Bloschl,¨ 2004; Parajka give an integrated response to rainfall. The two approaches, et al., 2005; Merz et al., 2006), regionalization being de- which used the permeability of the substratum and dom- fined as the transfer of information from one basin to an- inating runoff generation processes as basin attributes are other (Bloschl¨ and Sivapalan, 1995). Regression analysis is compared. The study area is the Rhineland Palatinate and the most widely used regionalization technique, although al- the Grand Duchy of Luxembourg and the study focuses on ternative techniques are also used (Kokkonen et al., 2003). the Nahe basin and its 16 sub-basins (Rhineland Palatinate). Since a regression needs a dependent and at least one in- For the comparison, three statistical models were derived by dependent variable, the choice of the variables is usually means of regression analysis. The models used the winter a hydrological variable as dependent and one or several storm flow coefficient as the dependent variable; the inde- physiographic basin characteristics as independent variables. pendent variables were the permeability of the substratum, Mazvimavi (2003) listed the most commonly used physio- preliminary derived dominating runoff generation processes graphic basin characteristics in regression analyses, which and a combination of both. It is demonstrated that the perme- are: land use, geology, drainage density and basin area. Pfis- ability and the preliminary derived processes carry different ter et al. (2002) developed a methodology that determines layers of information. Cross-validation and statistical tests the qualitative behavior of gauged basins with short histor- were used to determine and evaluate model differences. The ical data series with a view to regionalization, using the cross-validation resulted in a best model performance for the winter storm flow coefficient, or C-value, as the dependent model that used both parameters, followed by the model that parameter in a regression analysis. The previously named used the dominant runoff generation processes. From the basin characteristics served as independent parameters. The statistical tests it was concluded that the models come from C-value is defined as the ratio between storm flow and rain- different populations, carrying different information layers. fall, is supposed to be basin specific and to have a strong Analysis of the residuals of the models indicated that the per- seasonal variability, and should be more or less constant dur- meability and runoff generation processes did provide com- ing winter, expressing the saturated state of the basin (Pfister plementary information. Simple linear models appeared to et al., 2002). Uhlenbrook et al. (2004) pointed out that in perform well in describing the winter storm flow coefficient meso-scale basins processes combine into a more complex at the meso-scale when a combination of the permeability of way, producing an integrated runoff response to rainfall. In the substratum and dominating runoff generation processes this study, the C-value is supposed to represent this response served as independent parameters. of meso-scale basins (i.e. basins ranging in size from 10 km2 to 103 km2; Bloschl,¨ 1996) to rainfall during winter. The permeability of the substratum was found to be an impor- tant basin characteristic in describing the C-value of basins Correspondence to: H. Hellebrand in the Grand Duchy of Luxembourg (Pfister et al., 2002) and ([email protected]) it will serve in this study as a single independent parameter Published by Copernicus Publications on behalf of the European Geosciences Union. 1674 H. Hellebrand et al.: Storm flow generation by permeability and soil processes in a first model, which is based on linear regression, to de- action. The “detailedness” of these processes is supposed scribe the C-value with. Since soils form the first medium to be larger compared to the permeability assessment of the between precipitation and runoff generating processes after substratum due to a larger scale. Furthermore the dominat- the vegetation cover, they will serve in this study as indepen- ing runoff generation processes are more heterogeneously dent parameters for a second model. distributed compared to the permeability of the substratum. The impermeability of the substratum, which is used Both the permeability of the substratum and the dominating in this study, is based on a methodology of Zumstein et runoff generation processes will be derived as percentages of al. (1989), who classified the infiltration permeability of the total basin areas in a GIS. substratum with respect to its lithology and geohydrologi- The objective of the study is to compare the information cal characteristics such as fractures and porosity, obtaining carried by the simplified permeability of the substratum, the eight different permeability classes. This classification was dominating runoff generating processes and a combination adapted and simplified into only three classes: permeable, of both with respect to the winter storm flow coefficient. For semi-permeable and impermeable. The determination of the this purpose three models that are based on regression anal- three classes in this study was based on the available dig- ysis will be used. Model results will be assessed with cross- itized geological map (Geologische Ubersichtskarte,¨ scale validation, two non-parametric statistical tests and a compar- 1:300 000 (GUK¨ 300)). Due to this simplification and due ison of their residuals. The use of the permeability of the to the coarse scale of the geological map, the thus assessed substratum as a parameter in a regression model may open permeability should be regarded as an indicator for runoff possibilities for predictions in un-gauged basins concerning production only. their runoff coefficient. Scherrer and Naef (2003) developed an approach to determine runoff processes at the plot scale. It uses soil data, geology, topography and vegetation for the process identification. 2 Study area Scherrer (1997) and Faeh (1997) conducted sprinkling exper- iments in Switzerland on grassland hill slopes with varying The study area comprises 71 basins located throughout the slopes, geology and soils and recorded the soil-water levels, Grand Duchy of Luxembourg and the Rhineland Palatinate soil-water content and soil-water tension. The outcome of (Germany) and it focuses on the Nahe basin (4011 km2, lo- this research formed the basis for developing process deci- cated in the Rhineland Palatinate) and its 16 sub-basins, sion schemes, which reflect the complex nature of runoff for- which are listed in Table 1. The study focuses on the Nahe mation to eventually determine the dominating runoff gen- basin and its sub-basins, which were chosen for the avail- eration process on a soil profile (Scherrer and Naef, 2003). ability of a preliminary GIS-based map that provided domi- Since several runoff processes can occur at the same site, the nating runoff generating processes as derived by Steinrucken¨ one process that contributes most is called the dominating et al. (2006). All basins have daily discharge measure- runoff generation process. Schmocker-Fackel et al. (2007) ments for a period of 30 years (1972–2002). Altitudes used this approach for identifying runoff processes at the plot range from 84 m a.s.l. at the lowest point of the Rhine val- as well as at catchment scale and illustrated the potential of ley to 817 m a.s.l. on the Hunsruck¨ middle mountain re- the use of dominating runoff generation processes for defin- gion. The study area has an oceanic temperate climate in ing the infiltration parameters used in rainfall-runoff mod- the West transforming to a semi-oceanic climate to the East. els. However, the approach of Scherrer and Naef (2003) is The temperate humid climate is influenced by the Atlantic time consuming and often, detailed soil data is lacking to ap- Ocean. The macro relief influences rainfall patterns as well. ply it on a smaller scale. The approach has been up-scaled The average annual precipitation ranges from approximately using an artificial neural network (ANN) model developed 540 mm/y in the middle part of the study area (Rhine val- by Steinrucken¨ et al. (2006). This model was applied to the ley) to approximately 1100 mm/y on the higher ridges, with Nahe basin, resulting in a digitized map that provides the pre- an average annual precipitation of 820 mm/y for the entire liminary modelled dominating runoff generation processes study area. The study area is located mainly in the Rhen- for this basin. The results of Steinrucken¨ et al. (2006) formed ish Massif and consists largely of schist, siltstone, sandstone the basis for the derivation of the processes that are used in and quartzite of Devonian age. The northeastern part is char- this study. acterized by tectonic dissections of geological strata, hence The dominating runoff generation processes obtained from displaying a heterogeneous geology in comparison to the re- Steinrucken¨ et al.

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