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1.
This paper compares artificial neural network (ANN), fuzzy logic (FL) and linear transfer function (LTF)‐based approaches for daily rainfall‐runoff modelling. This study also investigates the potential of Takagi‐Sugeno (TS) fuzzy model and the impact of antecedent soil moisture conditions in the performance of the daily rainfall‐runoff models. Eleven different input vectors under four classes, i.e. (i) rainfall, (ii) rainfall and antecedent moisture content, (iii) rainfall and runoff and (iv) rainfall, runoff and antecedent moisture content are considered for examining the effects of input data vector on rainfall‐runoff modelling. Using the rainfall‐runoff data of the upper Narmada basin, Central India, a suitable modelling technique with appropriate model input structure is suggested on the basis of various model performance indices. The results show that the fuzzy modelling approach is uniformly outperforming the LTF and also always superior to the ANN‐based models. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

2.
For many practical reasons, the empirical black‐box models have become an increasingly popular modelling tool for river flow forecasting, especially in mountainous areas where very few meteorological observatories exist. In this article, precipitation data are used as the only input to estimate river flow. Using five empirical black‐box models—the simple linear model, the linear perturbation model, the linearly varying gain factor model, the constrained nonlinear system model and the nonlinear perturbation model–antecedent precipitation index—modelling results are compared with actual results in three catchments within the Heihe River Basin. The linearly varying gain factor model and the nonlinear perturbation model yielded excellent predictions. For better simulation accuracy, a commonly used multilayer feed‐forward neural network model (NNM) was applied to incorporate the outputs of the individual models. Comparing the performance of these models, it was found that the best results were obtained from the NNM model. The results also suggest that more reliable and precise predictions of river flow can be obtained by using the NNM model while also incorporating the combined outputs of different empirical black‐box models. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

3.
Rainfall–runoff modelling at ungauged catchments often involves the transfer of calibrated model parameters from ‘donor’ gauged catchments. However, in any rainfall–runoff model, some parameters tend to be more sensitive to the objective function, whereas others are insensitive over their entire feasible range. In this paper, we analyse the effect of selectively transferring sensitive versus insensitive parameters on streamflow predictability at ungauged catchments. We develop a simple daily time‐step rainfall–runoff model [exponential bucket hydrologic model (EXP‐HYDRO)] and calibrate it at 756 catchments within the continental USA. Nash–Sutcliffe efficiency of (NS) is used as the objective function. The model simulates satisfactorily at 323 catchments (NS > 0.6), most of which are located in the eastern part of the USA, along the Rocky Mountain Range, and near the western Pacific coast. Of the six calibration parameters, only three parameters are found to be sensitive to NS. Two of these parameters control the hydrograph recession behaviour of a catchment, and the third parameter controls the snowmelt rate. We find that when only sensitive parameters are transferred, model performance at ungauged catchments is almost at par with that of transferring all six parameters. Conversely, the transfer of only insensitive parameters results in a significant deterioration in model performance. Results suggest that streamflow predictability at ungauged catchments using rainfall–runoff models is largely dependent on the transfer of a small subset of parameters. We recommend that, in any modelling framework, such parameters should be identified and further characterized to better understand the information controlling streamflow predictability at ungauged catchments. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

4.
The nature of the water–air temperature relationship, and its moderation by discharge, were investigated for catchments ranging in size from 2·1 to 601 km2 in the Exe basin, Devon, UK and for data relating to hourly, daily and weekly time bases. The sensitivity and explanatory power of simple water–air temperature regression models based on hourly data were improved by incorporation of a lag, which increased with catchment size, although relationships became more sensitive and less scattered as the time base of data increased from hourly to weekly mean values. Significant departures from linearity in water–air temperature relationships were evident for hourly, but not for daily mean or weekly mean, data. A clear tendency for relationships between water and air temperatures to be stronger and more sensitive for flows below median levels was apparent, and multiple regression analysis also revealed water temperature to be inversely related to discharge for all catchments and time‐scales. However, discharge had a greater impact in accounting for water temperature variation at shorter time‐scales and in larger catchments. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

5.
In this paper fuzzy models are used as an alternative to describe groundwater flow in the unsaturated zone. The core of these models consists of a fuzzy rule-based model of the Takagi–Sugeno type. Various fuzzy clustering algorithms are compared in the data-driven identification of these Takagi–Sugeno models. The performance of the resulting fuzzy models is evaluated on the training surface on which they were identified, and on time series measurements of water content values obtained through an experiment carried out by the non-vegetated terrain (NVT) workgroup of the European Microwave Signature Laboratory (EMSL) (see [Mancini M, Hoeben R, Troch PA. Multifrequency radar observations of bare surface soil moisture content: a laboratory experiment. Water Resour Res 1999;35(6):1827–38] and [Hoeben R, Troch PA. Assimilation of active microwave observation data for soil moisture profile estimation. Water Resour Res 2000;36(10):2805–19]). Despite higher errors at the borders of high water content values in the training surface, good results are obtained on the simulation of the time series.  相似文献   

6.
The rainfall–runoff modelling being a stochastic process in nature is dependent on various climatological variables and catchment characteristics and therefore numerous hydrological models have been developed to simulate this complex process. One approach to modelling this complex non-linear rainfall–runoff process is to combine the outputs of various models to get more accurate and reliable results. This multi-model combination approach relies on the fact that various models capture different features of the data, and hence combination of these features would yield better result. This study for the first time presented a novel wavelet based combination approach for estimating combined runoff The simulated daily output (Runoff) of five selected conventional rainfall–runoff models from seven different catchments located in different parts of the world was used in current study for estimating combined runoff for each time period. Five selected rainfall–runoff models used in this study included four data driven models, namely, the simple linear model, the linear perturbation model, the linearly varying variable gain factor model, the constrained linear systems with a single threshold and one conceptual model, namely, the soil moisture accounting and routing model. The multilayer perceptron neural network method was used to develop combined wavelet coupled models to evaluate the effect of wavelet transformation (WT). The performance of the developed wavelet coupled combination models was compared with their counterpart simple combination models developed without WT. It was concluded that the presented wavelet coupled combination approach outperformed the existing approaches of combining different models without applying input WT. The study also recommended that different models in a combination approach should be selected on the basis of their individual performance.  相似文献   

7.
Abstract

Application of the concept of combining the estimated forecast output of different rainfall-runoff models to yield an overall combined estimated output in the context of real-time river flow forecasting is explored. A Real-Time Model Output Combination Method (RTMOCM) is developed, based on the structure of the Linear Transfer Function Model (LTFM) and utilizing the concept of the Weighted Average Method (WAM) for model output combination. A multiple-input single-output form of the LTFM is utilized in the RTMOCM. This form of the LTFM model uses synchronously the daily simulation-mode model-estimated discharge time series of the rainfall-runoff models selected for combination, its inherent updating structure being used for providing updated combined discharge forecasts. The RTMOCM is applied to the daily data of five catchments, using the simulation-mode estimated discharges of three selected rainfall-runoff models, comprising one conceptual model (Soil Moisture Accounting and Routing Procedure—SMAR) and two black-box models (Linear Perturbation Model—LPM and Linearly-Varying Variable Gain Factor Model—LVGFM). In order to get an indication of the accuracy of the updated combined discharge forecasts relative to the updated discharge forecasts of the individual models, the LTFM is also used for updating the simulation-mode discharge time series of each of the three individual models. The results reveal that the updated combined discharge forecasts provided by the RTMOCM, with parameters obtained by linear regression, can improve on the updated discharge forecasts of the individual rainfall-runoff models.  相似文献   

8.
S. Riad  J. Mania  L. Bouchaou  Y. Najjar 《水文研究》2004,18(13):2387-2393
A model of rainfall–runoff relationships is an essential tool in the process of evaluation of water resources projects. In this paper, we applied an artificial neural network (ANN) based model for flow prediction using the data for a catchment in a semi‐arid region in Morocco. Use of this method for non‐linear modelling has been demonstrated in several scientific fields such as biology, geology, chemistry and physics. The performance of the developed neural network‐based model was compared against multiple linear regression‐based model using the same observed data. It was found that the neural network model consistently gives superior predictions. Based on the results of this study, artificial neural network modelling appears to be a promising technique for the prediction of flow for catchments in semi‐arid regions. Accordingly, the neural network method can be applied to various hydrological systems where other models may be inappropriate. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

9.
Integrated watershed models can be used to calculate streamflow generation in snow‐dominated mountainous catchments. Parameterization of water flow is often complicated by the lack of information on subsurface hydraulic properties. In this study, bulk density optimization was used to determine hydraulic parameters for the upper and lower regolith in the GEOtop model. The methodology was tested in two small catchments in the Dry Creek Watershed in Idaho and the Libby Creek Watershed in Wyoming. Modelling efficiencies for profile‐average soil–water content for the two catchments were between 0.52 and 0.64. Modelling efficiencies for stream discharge (cumulative stream discharge) were 0.45 (0.91) and 0.54 (0.94) for the Idaho and Wyoming catchments, respectively. The calculated hydraulic properties suggest that lateral flow across the upper–lower regolith interface is an important driver of streamflow in both the Idaho and Wyoming watersheds. The overall calibration procedure is computationally efficient because only two bulk density values are optimized. The two‐parameter calibration procedure was complicated by uncertainty in hydraulic conductivity anisotropy. Different upper regolith hydraulic conductivity anisotropy factors had to be tested in order to describe streamflow in both catchments.  相似文献   

10.
Solute concentrations in streamflow typically vary systematically with stream discharge, and the resulting concentration–discharge relationships are important signatures of catchment biogeochemical processes. Solutes derived from mineral weathering often exhibit decreasing concentrations with increasing flows, suggesting dilution of a kinetically limited weathering flux by a variable flux of water. However, previous work showed that concentration–discharge relationships of weathering‐derived solutes in 59 headwater catchments were much weaker than this simple dilution model would predict. Instead, catchments behaved as chemostats, with rates of solute production and/or mobilization that were nearly proportional to water fluxes, on both event and interannual timescales. Here, we re‐examine these findings using data for a wider range of solutes from 2,186 catchments, ranging from ~10 to >1,000,000 km2 in drainage area and spanning a wide range of lithologic and climatic settings. Concentration–discharge relationships among this much larger set of larger catchments are broadly consistent with the previously described chemostatic behaviour, at least on event and interannual timescales for weathering‐derived solutes. Among these same catchments, however, site‐to‐site variations in mean concentrations of weathering‐derived solutes exhibit strong negative correlations with long‐term average precipitation and discharge, reflecting strong climatic control on long‐term leaching of the critical zone. We use multiple regression of site characteristics including discharge to identify potential controls on long‐term mean concentrations and find that lithologic and land cover controls are significant predictors for many analytes. The picture that emerges is one in which, on event and interannual timescales, weathering‐derived stream solute concentrations are chemostatically buffered by groundwater storage and fast chemical reactions, but each catchment's chemostatic “set point” reflects site‐to‐site differences in climatically driven evolution of the critical zone. In contrast to these weathering products, some nutrients and particulates are often near‐chemostatic across all timescales, and their long‐term mean concentrations correlate more strongly with land use than climatic characteristics.  相似文献   

11.
Australian arid zone ephemeral rivers are typically unregulated and maintain a high level of biodiversity and ecological health. Understanding the ecosystem functions of these rivers requires an understanding of their hydrology. These rivers are typified by highly variable hydrological regimes and a paucity, often a complete absence, of hydrological data to describe these flow regimes. A daily time‐step, grid‐based, conceptual rainfall–runoff model was developed for the previously uninstrumented Neales River in the arid zone of northern South Australia. Hourly, logged stage data provided a record of stream‐flow events in the river system. In conjunction with opportunistic gaugings of stream‐flow events, these data were used in the calibration of the model. The poorly constrained spatial variability of rainfall distribution and catchment characteristics (e.g. storage depths) limited the accuracy of the model in replicating the absolute magnitudes and volumes of stream‐flow events. In particular, small but ecologically important flow events were poorly modelled. Model performance was improved by the application of catchment‐wide processes replicating quick runoff from high intensity rainfall and improving the area inundated versus discharge relationship in the channel sections of the model. Representing areas of high and low soil moisture storage depths in the hillslope areas of the catchment also improved the model performance. The need for some explicit representation of the spatial variability of catchment characteristics (e.g. channel/floodplain, low storage hillslope and high storage hillslope) to effectively model the range of stream‐flow events makes the development of relatively complex rainfall–runoff models necessary for multisite ecological studies in large, ungauged arid zone catchments. Grid‐based conceptual models provide a good balance between providing the capacity to easily define land types with differing rainfall–runoff responses, flexibility in defining data output points and a parsimonious water‐balance–routing model. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

12.
Concentration–discharge relationships have been widely used as clues to the hydrochemical processes that control runoff chemistry. Here we examine concentration–discharge relationships for solutes produced primarily by mineral weathering in 59 geochemically diverse US catchments. We show that these catchments exhibit nearly chemostatic behaviour; their stream concentrations of weathering products such as Ca, Mg, Na, and Si typically vary by factors of only 3 to 20 while discharge varies by several orders of magnitude. Similar patterns are observed at the inter‐annual time scale. This behaviour implies that solute concentrations in stream water are not determined by simple dilution of a fixed solute flux by a variable flux of water, and that rates of solute production and/or mobilization must be nearly proportional to water fluxes, both on storm and inter‐annual timescales. We compared these catchments' concentration–discharge relationships to the predictions of several simple hydrological and geochemical models. Most of these models can be forced to approximately fit the observed concentration–discharge relationships, but often only by assuming unrealistic or internally inconsistent parameter values. We propose a new model that also fits the data and may be more robust. We suggest possible tests of the new model for future studies. The relative stability of concentration under widely varying discharge may help make aquatic environments habitable. It also implies that fluxes of weathering solutes in streams, and thus fluxes of alkalinity to the oceans, are determined primarily by water fluxes. Thus, hydrology may be a major driver of the ocean‐alkalinity feedback regulating climate change. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

13.
The measurement of discharge is fundamental in nutrient load estimation. Because of our ability to monitor discharge routinely, it is generally assumed that the associated uncertainty is low. This paper challenges this preconception, arguing that discharge uncertainty should be explicitly taken into account to produce robust statistical analyses. In many studies, paired discharge and chemical datasets are used to calculate ‘true’ loads and used as the benchmark to compare with other load estimates. This paper uses two years of high frequency (daily and sub‐hourly) discharge and nutrient concentration data (nitrate‐N and total phosphorus (TP)) collected at four field sites as part of the Hampshire Avon Demonstration Test Catchment (DTC) programme. A framework for estimating observational nutrient load uncertainty was used which combined a flexible non‐parametric approach to characterising discharge uncertainty, with error modelling that allowed the incorporation of errors which were heteroscedastic and temporally correlated. The results showed that the stage–discharge relationships were non‐stationary, and observational uncertainties from ±2 to 25% were recorded when the velocity–area method was used. The variability in nutrient load estimates ranged from 1.1 to 9.9% for nitrate‐N and from 3.3 to 10% for TP when daily laboratory data were used, rising to a maximum of 9% for nitrate‐N and 83% for TP when the sensor data were used. However, the sensor data provided a better representation of the ‘true’ load as storm events are better represented temporally, posing the question: is it more beneficial to have high frequency, lower precision data or lower frequency but higher precision data streams to estimate nutrient flux responses in headwater catchments? Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

14.
Abstract

Modelling of the rainfall–runoff transformation process and routing of river flows in the Kilombero River basin and its five sub-catchments within the Rufiji River basin in Tanzania was undertaken using three system (black-box) models—a simple linear model, a linear perturbation model and a linear varying gain factor model—in their linear transfer function forms. A lumped conceptual model—the soil moisture accounting and routing model—was also applied to the sub-catchments and the basin. The HEC-HMS model, which is a distributed model, was applied only to the entire Kilombero River basin. River discharge, rainfall and potential evaporation data were used as inputs to the appropriate models and it was observed that sometimes the system models performed better than complex hydrological models, especially in large catchments, illustrating the usefulness of using simple black-box models in datascarce situations.  相似文献   

15.
Lihua Xiong  Shenglian Guo 《水文研究》2004,18(10):1823-1836
Effects of the catchment runoff coefficient on the performance of TOPMODEL in simulating catchment rainfall–runoff relationships are investigated in this paper, with an aim to improve TOPMODEL's simulation efficiency in catchments with a low runoff coefficient. Application of TOPMODEL in the semi‐arid Yihe catchment, with an area of 2623 km2 in the Yellow River basin of China, produced a Nash–Sutcliffe model efficiency of about 80%. To investigate how the catchment runoff coefficient affects the performance of TOPMODEL, the whole observed discharge series of the Yihe catchment is multiplied with a larger‐than‐unity scale factor to obtain an amplified discharge series. Then TOPMODEL is used to simulate the amplified discharge series given the original rainfall and evaporation data. For a set of different scale factors, TOPMODEL efficiency is plotted against the corresponding catchment runoff coefficient and it is found that the efficiency of TOPMODEL increases with the increasing catchment runoff coefficient before reaching a peak (e.g. about 90%); after the peak, however, the efficiency of TOPMODEL decreases with the increasing catchment runoff coefficient. Based on this finding, an approach called the discharge amplification method is proposed to enhance the simulation efficiency of TOPMODEL in rainfall–runoff modelling in catchments with a low runoff coefficient. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

16.
Fuzzy theory appears to be extremely effective at handling dynamic, non‐linear and noisy data, especially when the underlying physical relationships are not fully understood. Since hydrologists are still uncertain about many of the aspects of the physical processes in the watershed, fuzzy theory has proved to be a very attractive tool enabling them to investigate such problems. The effectiveness of the fuzzy model lies in the identification of the antecedent membership function (MF), which is generally addressed through a fuzzy clustering approach. Most of the applications of fuzzy computing in hydrology seem to have selected the clustering algorithm quite arbitrarily. However, it is apparent that, as the antecedent parameters are based solely on the identified clusters, the method used for clustering should certainly have an impact on the overall performance of the model. This paper presents the results of a study conducted to investigate the impact of choice of clustering algorithm on the overall performance of a fuzzy‐based hydrologic model. The research is illustrated through a case study of developing a Takagi–Sugeno fuzzy model for reservoir inflow forecasting in the Narmada basin, India. The model was developed using two popular clustering techniques, namely Gustafson–Kessel (GK) and subtractive clustering (SC), and was extensively evaluated for performance based on various statistical indices. The results show that the model performance is comparable at a 1 h lead forecast. However, it is observed that the GK approach results in a better performance than the SC approach in computing forecasts at higher lead times. The analysis suggest that the GK method clusters the input space based on the actual pattern, since it uses a membership‐grade weighted‐distance measure as the measure of closeness, whereas the SC method classifies the input space more logically according to the magnitude of flow available in the data set. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

17.
C. Soulsby  C. Birkel  D. Tetzlaff 《水文研究》2016,30(14):2482-2497
The importance of conceptualizing the dynamics of storage‐driven saturation area connectivity in runoff generation has been central to the development of TOPMODEL and similar low parameterized rainfall–runoff models. In this contribution, we show how we developed a 40‐year hydrometric data base to simulate storage–discharge relationships in the Girnock catchment in the Scottish Highlands using a simple conceptual model. The catchment is a unique fisheries reference site where Atlantic salmon populations have been monitored since 1966. The modelling allowed us to track storage dynamics in hillslopes, the riparian zone and groundwater, and explicitly link non‐linear changes of streamflows to landscape storage and connectivity dynamics. This provides a fundamental basis for understanding how the landscape and riverscape are hydrologically connected and how this regulates in‐stream hydraulic conditions that directly influence salmonids. We use the model to simulate storage and discharge dynamics over the 40‐year period of fisheries records. The modelled storage‐driven connectivity provides an ecohydological context for understanding the dynamics in stream flow generation which determine habitat hydraulics for different life stages of salmon population. This new, long‐term modelling now sets this variability in the riverscape in a more fundamental context of the inter‐relationships between storage in the landscape and stream flow generation. This provides a simple, robust framework for future ecohydrological modelling at this site, which is an alternative to more increasingly popular but highly parameterized and uncertain commercial ecohydrological models. It also provides a wider, novel context that is a prerequisite for any model‐based scenario assessment of likely impacts resulting from climate or land use change. Copyright © 2016 The Authors Hydrological Processes Published by John Wiley & Sons Ltd. Copyright © 2016 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.  相似文献   

18.
Processes controlling streamflow generation were determined using geochemical tracers for water years 2004–2007 at eight headwater catchments at the Kings River Experimental Watersheds in southern Sierra Nevada. Four catchments are snow‐dominated, and four receive a mix of rain and snow. Results of diagnostic tools of mixing models indicate that Ca2+, Mg2+, K+ and Cl? behaved conservatively in the streamflow at all catchments, reflecting mixing of three endmembers. Using endmember mixing analysis, the endmembers were determined to be snowmelt runoff (including rain on snow), subsurface flow and fall storm runoff. In seven of the eight catchments, streamflow was dominated by subsurface flow, with an average relative contribution (% of streamflow discharge) greater than 60%. Snowmelt runoff contributed less than 40%, and fall storm runoff less than 7% on average. Streamflow peaked 2–4 weeks earlier at mixed rain–snow than snow‐dominated catchments, but relative endmember contributions were not significantly different between the two groups of catchments. Both soil water in the unsaturated zone and regional groundwater were not significant contributors to streamflow. The contributions of snowmelt runoff and subsurface flow, when expressed as discharge, were linearly correlated with streamflow discharge (R2 of 0.85–0.99). These results suggest that subsurface flow is generated from the soil–bedrock interface through preferential pathways and is not very sensitive to snow–rain proportions. Thus, a declining of the snow–rain ratio under a warming climate should not systematically affect the processes controlling the streamflow generation at these catchments. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

19.
Heavy rainfall events during the fall season are causing extended damages in Mediterranean catchments. A peaks‐over‐threshold model is developed for the extreme daily areal rainfall occurrence and magnitude in fall over six catchments in Southern France. The main driver of the heavy rainfall events observed in this region is the humidity flux (FHUM) from the Mediterranean Sea. Reanalysis data are used to compute the daily FHUM during the period 1958–2008, to be included as a covariate in the model parameters. Results indicate that the introduction of FHUM as a covariate can improve the modelling of extreme areal precipitation. The seasonal average of FHUM can improve the modelling of the seasonal occurrences of heavy rainfall events, whereas daily FHUM values can improve the modelling of the events magnitudes. In addition, an ensemble of simulations produced by five different general circulation models are considered to compute FHUM in future climate with the emission scenario A1B and hence to evaluate the effect of climate change on the heavy rainfall distribution in the selected catchments. This ensemble of climate models allows the evaluation of the uncertainties in climate projections. By comparison to the reference period 1960–1990, all models project an amplification of the mean seasonal FHUM from the Mediterranean Sea for the projection period 2070–2099, on average by +22%. This increase in FHUM leads to an increase in the number of heavy rainfall events, from an average of 2.55 events during the fall season in present climate to 3.57 events projected for the period 2070–2099. However, the projected changes have limited effects on the magnitude of extreme events, with only a 5% increase in the median of the 100‐year quantiles. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

20.
Bettina Schaefli 《水文研究》2016,30(22):4019-4035
Discharge simulation from snow‐dominated catchments seems to be an easy task. Any spatially explicit precipitation–runoff model coupled to a temperature‐index snow model generally yields simulations that mimic well the observed daily discharges. The robustness of such models is, however, questionable: in the presence of strong annual discharge cycles, small model residuals do not guarantee high explanatory power of the underlying model. This paper proposes a methodology for snow hydrological model identification within a limits‐of‐acceptability framework, where acceptable model simulations are the ones that reproduce a set of signatures within an a priori specified range. The signatures proposed here namely include the relationship between the air temperature regime and the discharge regime, a new snow hydrology signature that can be readily transferred to other Alpine settings. The discriminatory power of all analysed signatures is assessed with a new measure of their discriminatory power in the model prediction domain. The value of the proposed snow hydrology signatures and of the limits‐of‐acceptability approach is demonstrated for the Dischma river in Switzerland, whose discharge shows a strong temporal variability of hydrologic forcing conditions over the last 30 years. The signature‐based model identification for this case study leads to the surprising conclusion that the observed discharge data contains a multi‐year period that cannot be reproduced with the model at hand. This model‐data mismatch might well result from a yet to be identified problem with the discharge observations, which would have been difficult to detect in a classical residual‐based model identification approach. Overall, the detailed results for this case study underline the robustness of the limits‐of‐acceptability approach in the presence of error‐prone observations if it is applied in combination with relatively robust signatures. Future work will show whether snow hydrology signatures and their limits‐of‐acceptability can be regionalized to ungauged catchments, which would make this model selection approach particularly powerful for Alpine environments. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

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