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1.
Simulations from hydrological models are affected by potentially large uncertainties stemming from various sources, including model parameters and observational uncertainty in the input/output data. Understanding the relative importance of such sources of uncertainty is essential to support model calibration, validation and diagnostic evaluation and to prioritize efforts for uncertainty reduction. It can also support the identification of ‘disinformative data’ whose values are the consequence of measurement errors or inadequate observations. Sensitivity analysis (SA) provides the theoretical framework and the numerical tools to quantify the relative contribution of different sources of uncertainty to the variability of the model outputs. In traditional applications of global SA (GSA), model outputs are aggregations of the full set of a simulated variable. For example, many GSA applications use a performance metric (e.g. the root mean squared error) as model output that aggregates the distances of a simulated time series to available observations. This aggregation of propagated uncertainties prior to GSA may lead to a significant loss of information and may cover up local behaviour that could be of great interest. Time‐varying sensitivity analysis (TVSA), where the aggregation and SA are repeated at different time steps, is a viable option to reduce this loss of information. In this work, we use TVSA to address two questions: (1) Can we distinguish between the relative importance of parameter uncertainty versus data uncertainty in time? (2) Do these influences change in catchments with different characteristics? To our knowledge, the results present one of the first quantitative investigations on the relative importance of parameter and data uncertainty across time. We find that the approach is capable of separating influential periods across data and parameter uncertainties, while also highlighting significant differences between the catchments analysed. Copyright © 2016 The Authors. Hydrological Processes. Published by John Wiley & Sons Ltd.  相似文献   

2.
Complex hydrological models are being increasingly used nowadays for many purposes such as studying the impact of climate and land‐use change on water resources. However, building a high‐fidelity model, particularly at large scales, remains a challenging task, due to complexities in model functioning and behaviour and uncertainties in model structure, parameterization, and data. Global sensitivity analysis (GSA), which characterizes how the variation in the model response is attributed to variations in its input factors (e.g., parameters and forcing data), provides an opportunity to enhance the development and application of these complex models. In this paper, we advocate using GSA as an integral part of the modelling process by discussing its capabilities as a tool for diagnosing model structure and detecting potential defects, identifying influential factors, characterizing uncertainty, and selecting calibration parameters. Accordingly, we conduct a comprehensive GSA of a complex land surface–hydrology model, Modélisation Environmentale–Surface et Hydrologie (MESH), which combines the Canadian land surface scheme with a hydrological routing component, WATROUTE. Various GSA experiments are carried out using a new technique, called Variogram Analysis of Response Surfaces, for alternative hydroclimatic conditions in Canada using multiple criteria, various model configurations, and a full set of model parameters. Results from this study reveal that, in addition to different hydroclimatic conditions and SA criteria, model configurations can also have a major impact on the assessment of sensitivity. GSA can identify aspects of the model internal functioning that are counter‐intuitive and thus help the modeller to diagnose possible model deficiencies and make recommendations for improving development and application of the model. As a specific outcome of this work, a list of the most influential parameters for the MESH model is developed. This list, along with some specific recommendations, is expected to assist the wide community of MESH and Canadian land surface scheme users, to enhance their modelling applications.  相似文献   

3.
C. Dobler  F. Pappenberger 《水文研究》2013,27(26):3922-3940
The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models that are used within an operational real‐time forecasting chain such as HQsim. The objectives of this investigation are to (i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and (ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the (i) regional sensitivity analysis, (ii) Morris analysis and (iii) state‐dependent parameter modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity whereas most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor (meltfunc_max) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

4.
Implementation of sensitivity analysis (SA) procedures is helpful in calibration of models and also for their transposition to different watersheds. The reported studies on SA of Soil and Water Assessment Tool (SWAT) model were mostly focused on identifying parameters for pruning or modifying during the calibration process. This paper presents a sensitivity and identifiability analysis of model parameters that influence stream flow generation in SWAT. The analysis was focused on evaluating the sensitivity of the parameters in different climatic settings, temporal scales and flow regimes. The global sensitivity analysis (GSA) technique based on classical decomposition of variance, Sobol', was employed in this study. The results of the study indicate that modeled stream flow show varying sensitivity to parameters in different climatic settings. The results also suggest that the identifiability of a parameter for a given watershed is a major concern in calibrating the model for the specific watershed, as it might lead to equifinality of parameters. The SWAT model parameters show varying sensitivity in different years of simulation suggesting the requirement for dynamic updation of parameters during the simulation. The sensitivity of parameters during various flow regimes (low, medium and high flow) is also found to be uneven, which suggests the significance of a multi‐criteria approach for the calibration of models. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

5.
Ephemeral gully (EG) erosion has an important impact on agricultural soil losses and increases field surface hydrology connectivity and transport of pollutants to nearby water bodies. Watershed models including an EG component are scarce and not yet properly evaluated. The objective of this study is to evaluate the capacity of one such tool, AnnAGNPS, to simulate the evolution of two EG formed in a conservation tillage system. The dataset for model testing included runoff measurements and EG morphological characteristics during 3 years. Model evaluation focused on EG evolution of volume, width, and length model outputs, and included calibration and testing phases and a global sensitivity analysis (GSA). While the model did not fully reproduce width and length, the model efficiency to simulate EG volume was satisfactory for both calibration and testing phases, supporting the watershed management objectives of the model. GSA revealed that the most sensitive factors were EG depth, critical shear stress, headcut detachment exponent coefficient b, and headcut detachment leading coefficient a. For EG outputs the model was additive, showing low sensitivity to interactions between the inputs. Prediction of EG spatial evolution on conservation tillage systems requires improved development of gully erosion components, since many of the processes were developed originally for traditional tillage practices or larger channel systems. Our results identify the need for future research when EG form within conservation tillage systems, in particular to study gully headcut, soil erodibility, and width functions specific to these practices.  相似文献   

6.
Sloped areas calculated from a GIS raster file, such as a digital elevation model, are smaller than the true surface area, because they are projected to a planimetric plane. In mountainous regions this sloped area under‐estimation (SAUE) can have significant consequences on hydrological calculations. A sensitivity analysis is conducted, using the ACRU agro‐hydrological modelling system in a small watershed in Glacier National Park, Montana, USA, to investigate the sensitivity of the SAUE on key elements of the hydrological cycle, including precipitation depth, April snow depth, August soil moisture deficit, actual evapotranspiration depth, and runoff depth. The sensitivity analysis is based on 224 unique combinations of slope, soil and land cover types, elevation with associated precipitation depths, and north and south facing radiation regimes. Results revealed an increasing influence of the SAUE on all hydrological processes with increasing slope steepness. Distinct differences and magnitudes between different land cover types, different elevations, and, in particular, different exposition were quantified. Actual evapotranspiration increases with SAUE, while runoff decreases. April soil water is simulated to decrease with an increase in SAUE. Finally, a comparison of a streamflow simulation of a small and steep alpine watershed with and without consideration of the SAUE is carried out. The sloped area of the small watershed is under‐estimated by 20·9%, and the difference in simulated runoff is 12·3%. When the SAUE was not considered, runoff was simulated to be higher, the associated coefficient of determination was slightly lower, and the slope of the regression line was flatter. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

7.
Global sensitivity analysis is a useful tool to understand process‐based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD‐FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The analysis was carried out for multiple long‐term model predictions of hydrology, biogeochemistry, and plant growth. Results showed that long‐term mean hydrological predictions were highly sensitive to several key plant physiological parameters. Long‐term mean annual soil organic C content and mineralization rate were mainly controlled by temperature‐related parameters for soil organic matter decomposition. Mean annual forest productivity and N uptake were found to be mainly dependent upon plant production‐related parameters, including canopy quantum use efficiency and carbon use efficiency. Mean annual nitrate loss was highly sensitive to parameters controlling both hydrology and plant production, while mean annual dissolved organic nitrogen loss was controlled by parameters associated with its production and physical sorption. Parameters controlling forest production, C allocation, and specific leaf area highly affected long‐term mean annual leaf area. Results of this study could help minimize the efforts needed for calibrating DRAINMOD‐FOREST. Meanwhile, this study demonstrates the critical role of plants in regulating water, C, and N cycles in forest ecosystems and highlights the necessity of incorporating a dynamic plant growth model for comprehensively simulating hydrological and biogeochemical processes. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

8.
Efficiency of hydrological models mostly depends on the quality of the calibration performed prior to use. In this paper, an automatic calibration framework for the distributed hydrological model HYDROTEL is proposed. The calibration procedure was performed for three watersheds characterized with different hydroclimatological conditions: the Sassandra located in Ivory Coast, Africa, and the Montmorency and Beaurivage watersheds located in Quebec (Canada). Results of one‐a‐time (OAT) sensitivity analysis showed that the order of the most sensitive parameters differs for each watershed. Thus, the sensitivity depends on the hydroclimatic and physiographic characteristics of the watersheds. Co‐linearity indices showed that all model parameters were identifiable, that is, none of the studied parameters could be explained by a combination of the other parameters. Following these findings, an automatic calibration was run. Results indicated there was good agreement between simulated and measured streamflows at the outlet of each watershed; Nash–Sutcliffe efficiency (NSE) ranging between 0.77 and 0.92 and R2 ranging from 0.87 to 0.97. When comparing NSE and R2 values obtained using a process‐oriented, multiple‐objective, manual calibration strategy, a slight increase in model efficiency was reached with the automatic calibration procedure (4.15% for NSE and 2.95% for R2) improving predictions of peak flows for the Montmorency and Beaurivage watersheds (temperate climate conditions) and flows beyond the rainfall season in the Sassandra watershed. The proposed automatic calibration procedure introduced in this paper may be applied to other distributed hydrological model. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

9.
Land surface schemes (LSSs) represent the interface between land surface and the atmosphere in general circulation models (GCMs). Errors in LSS‐simulated heat and moisture fluxes can result from inadequate representation of hydrological features and the derivation of effective surface parameters for large heterogeneous GCM gridboxes from small‐scale observations. Previous assessments of LSS performance have generally compared simulated heat and moisture fluxes to observations over a defined experimental domain for a limited period. A different approach has been evaluated in this study, which uses a fine‐resolution calibrated hydrological model of the study basin to provide a quasi‐observed runoff series for direct comparison with simulated runoff from a selected LSS at GCM scale. The approach is tested on two GCM gridboxes covering two contrasting regions within the Nile Basin. Performance is mixed; output from the LSS is generally compatible with that of the fine‐resolution model for one gridbox while it cannot reproduce the runoff dynamics for the other. The results also demonstrate the high sensitivity of runoff and evapotranspiration to radiation and precipitation inputs and show the importance of subtle issues such as temporal disaggregation of climatic inputs. We conclude that the use of a fine‐resolution calibrated model to evaluate a LSS has several advantages, can be generalized to other areas to improve the performance of global models and provides useful data that can be used to constrain LSS parameterizations. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

10.
Integrated dynamic water and chloride balance models with a catchment‐scale hydrological model (PRMS) are used to investigate the response of a terminal tropical lake, Lake Abiyata, to climate variability and water use practices in its catchment. The hydrological model is used to investigate the response of the catchment to different climate and land‐use change scenarios that are incorporated into the lake model. Lake depth–area–volume relationships were established from lake bathymetries. Missing data in the time series were filled using statistical regression techniques. Based on mean monthly data, the lake water balance model produced a good agreement between the simulated and observed levels of Lake Abiyata for the period 1968–83. From 1984 onwards the simulated lake level is overestimated with respect to the observed one, while the chloride concentration is largely underestimated. This discrepancy is attributed to human use of water from the influent rivers or directly from the lake. The simulated lake level and chloride concentration are in better agreement with observed values (r2 = 0·96) when human water use for irrigation and salt exploitation are included in the model. A comparison of the simulation with and without human consumption indicates that climate variability controls the interannual fluctuations and that the human water use affects the equilibrium of the system by strongly reducing the lake level. Sensitivity analysis based on a mean climatic year showed that, after prolonged mean climatic conditions, Lake Abiyata reacts more rapidly to an abrupt shift to wetter conditions than to dry conditions. This study shows the significant sensitivity of the level and salinity of the terminal Lake Abiyata to small changes in climate or land use, making it a very good ‘recorder’ of environmental changes that may occur in the catchment at different time scales. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

11.
Mediterranean catchments are characterized by strong nonlinearities in their hydrological behaviour. Properly simulating those nonlinearities still represents a great challenge and, at the same time, an important issue in order to improve our knowledge of their hydrological behaviour. The main aim of this work is find out diverse modelling approaches to reproduce the observed nonlinear hydrological behaviour in a small Mediterranean catchment, Can Vila (Vallcebre, NE Spain). To this end, three hydrological models were considered: two lumped models called LU3 and LU4 of increasing complexity, and a distributed model called TETIS. The structures of these different models were used as hypotheses, which could explain and reproduce the observed nonlinear behaviour at the outlet. Four analyses were carried out: (i) goodness‐of‐fit criteria analysis, (ii) residual errors analysis, (iii) sensitivity analysis and (iv) multicriteria analysis based on the concept of Pareto Optimal. These analyses showed the higher capability and robustness of the distributed model to reproduce the observed complex hydrological behaviour in this catchment. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

12.
Model diagnostic analyses help to improve the understanding of hydrological processes and their representation in hydrological models. A detailed temporal analysis detects periods of poor model performance and model components with potential for model improvements, which cannot be found by analysing the whole discharge time series. In this study, we aim to improve the understanding of hydrological processes by investigating the temporal dynamics of parameter sensitivity and of model performance for the Soil and Water Assessment Tool model applied to the Treene lowland catchment in Northern Germany. The temporal analysis shows that the parameter sensitivity varies temporally with high sensitivity for three groundwater parameters (groundwater time delay, baseflow recession constant and aquifer fraction coefficient) and one evaporation parameter (soil evaporation compensation factor). Whereas the soil evaporation compensation factor dominates in baseflow and resaturation periods, groundwater time delay, baseflow recession constant and aquifer fraction coefficient are dominant in the peak and recession phases. The temporal analysis of model performance identifies three clusters with different model performances, which can be related to different phases of the hydrograph. The lowest performance, when comparing six performance measures, is detected for the baseflow cluster. A spatially distributed analysis for six hydrological stations within the Treene catchment shows similar results for all stations. The linkage of periods with poor model performance to the dominant model components in these phases and with the related hydrological processes shows that the groundwater module has the highest potential for improvement. This temporal diagnostic analysis enhances the understanding of the Soil and Water Assessment Tool model and of the dominant hydrological processes in the lowland catchment. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

13.
Parameter calibration and sensitivity analysis (SA) are usually not straightforward tasks for distributed hydrological models, owing to the complexity of models and the large number of parameters. A two-step SA approach is proposed for analysing hydrological signatures based on the distributed hydrology–soil–vegetation model (DHSVM) in the Jinhua River Basin, East China. A preliminary SA is conducted to obtain influential parameters via analysis of variance. These parameters are further analysed through a variance-based global sensitivity analysis method to achieve robust rankings and parameter contributions. Parallel computing is designed to reduce the computational burden. The results reveal that only a few parameters are significantly sensitive and that interactions between parameters cannot be ignored. When analysing hydrological signatures, it is found that water yield is simulated very well for most samples. Small and medium floods are simulated very well, while slight underestimations happen for large floods.  相似文献   

14.
Diagnostic analyses of hydrological models intend to improve the understanding of how processes and their dynamics are represented in models. Temporal patterns of parameter dominance could be precisely characterized with a temporally resolved parameter sensitivity analysis. In this way, the discharge conditions are characterized, that lead to a parameter dominance in the model. To achieve this, the analysis of temporal dynamics in parameter sensitivity is enhanced by including additional information in a three‐tiered framework on different aggregation levels. Firstly, temporal dynamics of parameter sensitivity provide daily time series of their sensitivities to detect variations in the dominance of model parameters. Secondly, the daily sensitivities are related to the flow duration curve (FDC) to emphasize high sensitivities of model parameters in relation to specific discharge magnitudes. Thirdly, parameter sensitivities are monthly averaged separately for five segments of the FDC to detect typical patterns of parameter dominances for different discharge magnitudes. The three methodical steps are applied on two contrasting catchments (upland and lowland catchment) to demonstrate how the temporal patterns of parameter dynamics represent different hydrological regimes. The discharge dynamic in the lowland catchment is controlled by groundwater parameters for all discharge magnitudes. In contrast, different processes are relevant in the upland catchment, because the dominances of parameters from fast and slow runoff components in the upland catchment are changing over the year for the different discharge magnitudes. The joined interpretation of these three diagnostic steps provides deeper insights of how model parameters represent hydrological dynamics in models for different discharge magnitudes. Thus, this diagnostic framework leads to a better characterization of model parameters and their temporal dynamics and helps to understand the process behaviour in hydrological models. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

15.
The process of tillage translocation is well studied and can be described adequately by different existing models. Nevertheless, in complex environments with numerous obstacles, such as olive orchards, the application of conventional tillage erosion models is not straightforward. However, such obstacles have important effects on the spatial pattern of soil redistribution and on resulting soil properties. Cellular automata could provide a valuable alternative here. This study aims at developing a cellular automata model for tillage translocation (CATT) that can take into account such obstacles, exploring its possibilities and limitations. Firstly, model outcome was tested on a traditional field with rolling topography, for which caesium‐137 (137Cs) inventories are available. The observed spatial soil redistribution patterns could be adequately represented by the CATT model. Secondly, a global sensitivity analysis was performed to explore the effect of input parameter uncertainty on several selected model outputs. The variance‐based extended Fourier Amplitude Sensitivity Test (FAST) method was used to determine first‐ and total‐order sensitivity indices. Tillage depth was identified as the input parameter that determined most of the output variance, followed respectively by tillage direction and speed. The high difference between the total‐ and first‐order sensitivity indices indicated that, in spite of the simple model structure, the model behaves non‐linearly with respect to some of the model output variables. Higher order interactions were especially important for determining the proportion of eroding and deposition cells. Finally, simulations were performed to analyse the model behaviour in complex landscapes, applying it to a field with protruding obstacles (representing olive trees). The model adequately represented some morphological features observed in actual olive orchards, such as mounds around the olive trees. The results show that cellular automata are an appropriate tool to describe long‐term tillage soil redistribution. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

16.
Changes in climate and land use can significantly influence the hydrological cycle and hence affect water resources. Understanding the impacts of climate and land‐use changes on streamflow can facilitate development of sustainable water resources strategies. This study investigates the flow variation of the Zamu River, an inland river in the arid area of northwest China, using the Soil and Water Assessment Tool distributed hydrological model. Three different land‐use and climate‐change scenarios were considered on the basis of measured climate data and land‐use cover, and then these data were input into the hydrological model. Based on the sensitivity analysis, model calibration and verification, the hydrological response to different land‐use and climate‐change scenarios was simulated. The results indicate that the runoff varied with different land‐use type, and the runoff of the mountain reaches of the catchment increased when grassland area increased and forestland decreased. The simulated runoff increased with increased precipitation, but the mean temperature increase decreased the runoff under the same precipitation condition. Application of grey correlation analysis showed that precipitation and temperature play a critical role in the runoff of the Zamu River basin. Sensitivity analysis of runoff to precipitation and temperature by considering the 1990s land use and climate conditions was also undertaken. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

17.
This study develops a novel approach for modelling and examining the impacts of time–space land‐use changes on hydrological components. The approach uses an empirical land‐use change allocation model (CLUE‐s) and a distributed hydrological model (DHSVM) to examine various land‐use change scenarios in the Wu‐Tu watershed in northern Taiwan. The study also uses a generalized likelihood uncertainty estimation approach to quantify the parameter uncertainty of the distributed hydrological model. The results indicate that various land‐use policies—such as no change, dynamic change and simultaneous change—have different levels of impact on simulating the spatial distributions of hydrological components in the watershed study. Peak flow rates under simultaneous and dynamic land‐use changes are 5·71% and 2·77%, respectively, greater than the rate under the no land‐use change scenario. Using dynamic land‐use changes to assess the effect of land‐use changes on hydrological components is more practical and feasible than using simultaneous land‐use change and no land‐use change scenarios. Furthermore, land‐use change is a spatial dynamic process that can lead to significant changes in the distributions of ground water and soil moisture. The spatial distributions of land‐use changes influence hydrological processes, such as the ground water level of whole areas, particularly in the downstream watershed. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

18.
In this paper, we assess the performance of the catchment model SIMulated CATchment model (SIMCAT), to predict nitrate and soluble reactive phosphorus concentrations against four monitoring regimes with different spatial and temporal sampling frequencies. The Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty framework is used, along with a general sensitivity analysis to understand relative parameter sensitivity. Improvements to model calibration are explored by introducing more detailed process representation using the Integrated Catchments model (INCA) water quality model, driven by the European hydrological predictions for the environment model. The results show how targeted sampling of headwater watercourses upstream of point discharges is essential for calibrating diffuse loads and can exert a strong influence on the whole‐catchment model performance. Further downstream, if the point discharges and loads are accurately represented, then the improvement in the catchment‐scale model performance is relatively small as more calibration points are added or frequency is increased. The higher‐order, dynamic model integrated catchments model of phosphorus dynamics, which incorporates sediment and biotic interaction, resulted in improved whole‐catchment performance over SIMCAT, although there are still large epistemic uncertainties from land‐phase export coefficients and runoff. However, the very large sampling errors in routine monitoring make it difficult to invest confidence in the modelling, especially because we know phosphorous transport to be very episodic and driven by high flow conditions for which there are few samples. The environmental modelling community seems to have been stuck in this position for some time, and whilst it is useful to use an uncertainty framework to highlight these issues, it has not widely been adopted, perhaps because there is no clear mechanism to allow uncertainties to influence investment decisions. This raises the question as to whether it might better place a cost on uncertainty and use this to drive more data collection or improved models, before making investment decisions concerning, for example, mitigation strategies. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

19.
Hongyan Li  Miao Xie  Shan Jiang 《水文研究》2012,26(18):2827-2837
Mid‐ to long‐term runoff forecasting is important to China. Forecasting based on physical causes has become the trend of this field, and recognition of key factors is central to recent development. Here, global sensitivity analysis based on back‐propagation arithmetic was used to calculate the sensitivity of up to 24 factors that affect runoff in the Nenjiang River Basin. The following five indices were found to be key factors for mid‐ to long‐term runoff forecasting during flood season: Tibetan Plateau B, index of the strength of the East Asian trough, index of the area of the northern hemisphere polar vortex, zonal circulation index over the Eurasian continent and index of the strength of the subtropical high over the western Pacific. The hydrological climate of the study area and the rainfall–runoff laws were then analysed in conjunction with its geographical position and topographic condition. The rationality of the results can be demonstrated from the positive analysis point of view. The results of this study provide a general method for selection of mid‐ to long‐term runoff forecasting factors based on physical causes. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

20.
In this paper, we analyse the uncertainty and parameter sensitivity of a conceptual water quality model, based on a travel time distribution (TTD) approach, simulating electrical conductivity (EC) in the Duck River, Northwest Tasmania, Australia for a 2-year period. Dynamic TTDs of stream water were estimated using the StorAge Selection (SAS) approach, which was coupled with two alternate methods to model stream water EC: (1) a solute-balance approach and (2) a water age-based approach. Uncertainty analysis using the Differential Evaluation Adoptive Metropolis (DREAM) algorithm showed that: 1. parameter uncertainty was a small contribution to the overall uncertainty; 2. most uncertainty was related to input data uncertainty and model structure; 3. slightly lower total error was obtained in the water age-based model than the solute-balance model; 4. using time-variant SAS functions reduced the model uncertainty markedly, which likely reflects the effect of dynamic hydrological conditions over the year affecting the relative importance of different flow pathways over time. Model parameter sensitivity analysis using the Variogram Analysis of Response Surfaces (VARS-TOOL) framework found that parameters directly related to the EC concentration were most sensitive. In the solute-balance model, the rainfall concentration Crain and in the age-based model, the parameter controlling the rate of change of EC with age (λ) were the most sensitive parameter. Model parameters controlling the age mixes of both evapotranspiration and streamflow water fluxes (i.e., the SAS function parameters) were influential for the solute-balance model. Little change in parameter sensitivity over time was found for the age-based concentration relationship; however, the parameter sensitivity was quite dynamic over time for the solute-balance approach. The overarching outcomes provide water quality modellers, engineers and managers greater insight into catchment functioning and its dependence on hydrological conditions.  相似文献   

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