ALBERT

Description: In this study we propose an uspcaling approach to derive time series of (a) REW scale state variables, and (b) effective REW scale soil hydraulic functions to test and parameterise models based on the REW approach. To this end we employed a physically based hydrological model, that represents the typical patterns and structures in the study catchment, and has previously been shown to reproduce observed runoff response and state dynamics well. This landscape- and process-compatible model is used to simulate numerical drainage and wetting experiments. The effective soil water retention curve and soil hydraulic conductivity curve are derived using the spatially averaged saturation and capillary pressure as well as averaged fluxes. When driven with observed boundary conditions during a one year simulation the model is used to estimate how the spatial pattern of soil moisture evolved during this period in the catchment. The time series of the volume integrated soil moisture is deemed as best estimate for the average catchment scale soil moisture. The approach is applied to the extensively monitored Weiherbach catchment in Germany. A sensitivity analysis showed that catchment scale model structures different from the landscape- and process compatible one yielded different times series of average catchment scale soil moisture and where not able to reproduce the observed rainfall runoff response. Hence, subscale typical heterogeneity leaves a clear fingerprint in the time series of average catchment scale saturation. In case of the Weiherbach catchment local scale heterogeneity of ks could be neglected and a simple representation of the typical hillslope scale patterns of soil types and macroporosity was sufficient for obtaining effective REW scale soil hydraulic functions. Both the effective soil hydraulic functions and time series of catchment scale saturation turned out to be useful to parameterise and test the CREW model, which is based on the REW approach and was applied to the Weiherbach catchment in a companion study Lee et al. (2006, this issue).

Description: Within the present study we shed light on the question whether objective circulation patterns (CP) classified from either the 500 HPa or the 700 HPa level may serve as predictors to explain the spatio-temporal variability of monsoon rainfall in the Anas catchment in North West India. To this end we employ a fuzzy ruled based classification approach in combination with a novel objective function as originally proposed by (Stehlik and BᲤossy, 2002). After the optimisation we compare the obtained circulation classification schemes for the two pressure levels with respect to their conditional rainfall probabilities and amounts. The classification scheme for the 500 HPa level turns out to be much more suitable to separate dry from wet meteorological conditions during the monsoon season. As is shown during a bootstrap test, the CP conditional rainfall probabilities for the wet and the dry CPs for both pressure levels are highly significant at levels ranging from 95 to 99%. Furthermore, the monthly CP frequencies of the wettest CPs show a significant positive correlation with the variation of the total number of rainy days at the monthly scale. Consistently, the monthly frequencies of the dry CPs exhibit a negative correlation with the number of rainy days at the monthly scale. The present results give clear evidence that the circulation patterns from the 500 HPa level are suitable predictors for explaining spatio- temporal Monsoon variability. A companion paper shows that the CP time series obtained within this study are suitable input into a stochastical rainfall model.

Description: This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights the frequencies that are not well reproduced by the model, which gives specific indications about how to improve the model structure.

Description: Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Description: The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physics-based model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.

Description: The present study tests whether an explicit treatment of worm burrows and tile drains as connected structures is feasible for simulating water flow, bromide and pesticide transport in structured heterogeneous soils at hillslope scale. The essence is to represent worm burrows as morphologically connected paths of low flow resistance in a hillslope model. A recent Monte Carlo study (Klaus and Zehe, 2010, Hydrological Processes, 24, p. 1595–1609) revealed that this approach allowed successful reproduction of tile drain event discharge recorded during an irrigation experiment at a tile drained field site. However, several "hillslope architectures" that were all consistent with the available extensive data base allowed a good reproduction of tile drain flow response. Our second objective was thus to find out whether this "equifinality" in spatial model setups may be reduced when including bromide tracer data in the model falsification process. We thus simulated transport of bromide for the 13 spatial model setups that performed best with respect to reproduce tile drain event discharge, without any further calibration. All model setups allowed a very good prediction of the temporal dynamics of cumulated bromide leaching into the tile drain, while only four of them matched the accumulated water balance and accumulated bromide loss into the tile drain. The number of behavioural model architectures could thus be reduced to four. One of those setups was used for simulating transport of Isoproturon, using different parameter combinations to characterise adsorption according to the Footprint data base. Simulations could, however, only reproduce the observed leaching behaviour, when we allowed for retardation coefficients that were very close to one.

Description: Topography exerts influence on the spatial precipitation distribution over different scales, known typically at the large scale as the orographic effect, and at the small scale as the wind-drift rainfall (WDR) effect. At the intermediate scale (1~10 km), which is characterized by secondary mountain valleys, topography also demonstrates some effect on the precipitation pattern. This paper investigates such intermediate-scale topographic effects on precipitation patterns, focusing on narrow-steep valleys in the complex terrain of southern Germany, based on the daily observations over a 48 yr period (1960~2007) from a high-density rain-gauge network covering two sub-areas, Baden-Wuerttemberg (BW) and Bavaria (BY). Precipitation data at the valley and non-valley stations are compared under consideration of the daily general circulation patterns (CPs) classified by a fuzzy rule-based algorithm. Scatter plots of precipitation against elevation demonstrate a different behavior of valley stations comparing to non-valley stations. A detailed study of the precipitation time series for selected station triplets, each consisting of a valley station, a mountain station and an open station have been investigated by statistical analysis with the Kolmogorov–Smirnov (KS) test supplemented by the One-way analysis of variance (One-way ANOVA) and a graphical comparison of the mean precipitation amounts. The results show an interaction of valley orientation and the direction of the CPs at the intermediate scale, i.e. when the valley is shielded from the CP which carries the precipitation, the precipitation amount within the valley is comparable to that on the mountain crest, and both larger than the precipitation at the open station. When the valley is open to the CP, the precipitation within the valley is similar to the open station but much less than that on the mountain. Such phenomenon where the precipitation is "blind" to the valleys at the intermediate scale conditioned on CPs is defined as the "narrow-valley effect" in this work. Such an effect cannot be captured by the widely used elevation–precipitation relationship, which implies that the traditional geostatistical interpolation schemes, e.g. ordinary kriging (OK) or external drift kriging (EDK) applying digital elevation model (DEM) as external information, are not sufficient. An interpolation experiment applying EDK with orographic surrogate elevation defined in this paper as auxiliary information to account for the valley effects shows improvement for the cross-validation.

Description: Applying metrics to quantify the similarity or dissimilarity of hydrographs is a central task in hydrological modelling, used both in model calibration and the evaluation of simulations or forecasts. Motivated by the shortcomings of standard objective metrics such as the Root Mean Square Error (RMSE) or the Mean Absolute Peak Time Error (MAPTE) and the advantages of visual inspection as a powerful tool for simultaneous, case-specific and multi-criteria (yet subjective) evaluation, we propose a new objective metric termed Series Distance, which is in close accordance with visual evaluation. The Series Distance quantifies the similarity of two hydrographs neither in a time-aggregated nor in a point-by-point manner, but on the scale of hydrological events. It consists of three parts, namely a Threat Score which evaluates overall agreement of event occurrence, and the overall distance of matching observed and simulated events with respect to amplitude and timing. The novelty of the latter two is the way in which matching point pairs on the observed and simulated hydrographs are identified: not by equality in time (as is the case with the RMSE), but by the same relative position in matching segments (rise or recession) of the event, indicating the same underlying hydrological process. Thus, amplitude and timing errors are calculated simultaneously but separately, from point pairs that also match visually, considering complete events rather than only individual points (as is the case with MAPTE). Relative weights can freely be assigned to each component of the Series Distance, which allows (subjective) customization of the metric to various fields of application, but in a traceable way. Each of the three components of the Series Distance can be used in an aggregated or non-aggregated way, which makes the Series Distance a suitable tool for differentiated, process-based model diagnostics. After discussing the applicability of established time series metrics for hydrographs, we present the Series Distance theory, discuss its properties and compare it to those of standard metrics used in Hydrology, both at the example of simple, artificial hydrographs and an ensemble of realistic forecasts. The results suggest that the Series Distance quantifies the degree of similarity of two hydrographs in a way comparable to visual inspection, but in an objective, reproducible way.