scholarly journals Parameter sensitivity of a watershed-scale flood forecasting model as a function of modelling time-step

2012 ◽  
Vol 44 (2) ◽  
pp. 334-350 ◽  
Author(s):  
Fiachra O'Loughlin ◽  
Michael Bruen ◽  
Thorsten Wagener
Keyword(s):  
Sensitivity Analysis ◽  
Strong Dependence ◽  
Flow Regimes ◽  
Flood Forecasting ◽  
Parameter Sensitivity ◽  
Hydrograph Separation ◽  
Time Step ◽  
Soil Moisture Accounting ◽  
Distributed Modelling ◽  
Sensitivity Indices

Although ongoing technological advances have alleviated data restrictions and most of the computational barriers to distributed modelling, lumped, parsimonious, conceptual and rainfall-runoff models are still widely used for flood forecasting. However both optimum parameter values and the fluxes of water through individual model components change significantly with the time-step used. Thus, such models should be used with caution in applications such as hydrograph separation or water quality studies that require the fluxes through individual flow routes through the model or which try to relate parameters to physical features of the catchment. To demonstrate this time-scale limitation, a parameter sensitivity analysis was performed on the lumped conceptual Soil Moisture Accounting and Routing with Groundwater component (SMARG) model for a 182 km2 rural catchment in Ireland for a number of time-steps, flow regimes and evaluation metrics. A global sensitivity analysis method (Higher Dimensional Model Representation) showed that sensitivity indices vary greatly with time-step and evaluation metric. The sensitivity of parameters also varied for different flow regimes. Certain parameters' sensitivities remain fairly constant across both flow regimes and time-step, while others are very much regime or time-step dependent. Care should be taken in using internal information from conceptual models because of this strong dependence on time-step.

scholarly journals Technical note: Analytical sensitivity analysis and uncertainty estimation of baseflow index calculated by a two-component hydrograph separation method with conductivity as a tracer

2019 ◽  
Vol 23 (2) ◽  
pp. 1103-1112 ◽  
Author(s):  
Weifei Yang ◽  
Changlai Xiao ◽  
Xiujuan Liang
Keyword(s):  
Time Series ◽  
Sensitivity Analysis ◽  
Measurement Errors ◽  
Uncertainty Estimation ◽  
Separation Method ◽  
Analytical Sensitivity ◽  
Hydrograph Separation ◽  
Time Step ◽  
Sensitivity Indices ◽  
Two Component

Abstract. The two-component hydrograph separation method with conductivity as a tracer is favored by hydrologists owing to its low cost and easy application. This study analyzes the sensitivity of the baseflow index (BFI, long-term ratio of baseflow to streamflow) calculated using this method to errors or uncertainties in two parameters (BFC, the conductivity of baseflow, and ROC, the conductivity of surface runoff) and two variables (yk, streamflow, and SCk, specific conductance of streamflow, where k is the time step) and then estimates the uncertainty in BFI. The analysis shows that for time series longer than 365 days, random measurement errors in yk or SCk will cancel each other out, and their influence on BFI can be neglected. An uncertainty estimation method of BFI is derived on the basis of the sensitivity analysis. Representative sensitivity indices (the ratio of the relative error in BFI to that of BFC or ROC) and BFI′ uncertainties are determined by applying the resulting equations to 24 watersheds in the US. These dimensionless sensitivity indices can well express the propagation of errors or uncertainties in BFC or ROC into BFI. The results indicate that BFI is more sensitive to BFC, and the conductivity two-component hydrograph separation method may be more suitable for the long time series in a small watershed. When the mutual offset of the measurement errors in conductivity and streamflow is considered, the uncertainty in BFI is reduced by half.

scholarly journals Sensitivity analysis of the Chaohu Lake eutrophication model with a new index based on the Morris method

2017 ◽  
Vol 18 (4) ◽  
pp. 1375-1387 ◽  
Author(s):  
Yulin Wang ◽  
Zulin Hua ◽  
Liang Wang
Keyword(s):  
Sensitivity Analysis ◽  
Life Stage ◽  
Eastern China ◽  
Parameter Sensitivity ◽  
Chaohu Lake ◽  
Sensitivity Index ◽  
Lake Eutrophication ◽  
Multiple Model ◽  
Morris Method ◽  
Sensitivity Indices

Abstract Chaohu Lake is a large shallow lake in eastern China, and few eutrophication model studies have been conducted there. We present practical sensitivity indices based on the Morris method to compare the sensitivity of a parameter group on one model output with that of one parameter on multiple model outputs. The new sensitivity indices were employed to measure the parameter sensitivity of the Chaohu Lake eutrophication model. The results of the sensitivity analysis demonstrate that the most sensitive parameters on cyanobacteria biomass, NH4, NO3, and PO4 were BMR, KDN, Nitm, and KRP, and the most sensitive parameter groups were algae-related, nitrogen-related, and phosphorus-related, which all directly participate in their cycles. Furthermore, Nitm, KRP, KDN, KHP, BMR, KTB, KTHDR, and KTCOD were the most important for the Chaohu Lake eutrophication model. The water environment characteristics, such as the cyanobacteria life stage in the simulated period, significantly affected parameter sensitivity. The power-law relationship between the new sensitivity index and the standard deviation of model variables in the Chaohu Lake model were also determined. This finding allows us to estimate the interactions between parameters using their sensitivity index. The results provide a basis for further improvement of the Chaohu Lake eutrophication model.

scholarly journals Technical note: Analytical sensitivity analysis and uncertainty estimation of a two-component hydrograph separation method which uses conductivity as a tracer

2018 ◽  
Author(s):  
Weifei Yang ◽  
Changlai Xiao ◽  
Xiujuan Liang
Keyword(s):  
Time Series ◽  
Sensitivity Analysis ◽  
Relative Error ◽  
Measurement Errors ◽  
The United States ◽  
Uncertainty Estimation ◽  
Separation Method ◽  
Hydrograph Separation ◽  
Sensitivity Indices ◽  
Two Component

Abstract. The conductivity two-component hydrograph separation method is cheap and easy to operate and is favored by hydrologists. This paper analyzes the sensitivity of the baseflow index (BFI, the long-term ratio of baseflow to streamflow) calculated by this method to errors or uncertainties of the two parameters (BFC, the conductivity of baseflow; ROC, the conductivity of surface runoff) and of the two variables (yk, the specific streamflow; Qck, the specific conductivity of streamflow), and then estimates the uncertainty of BFI. The analysis shows that when the time series is longer than 365 days, the random measurement errors of yk or Qck will cancel each other, and the influence on BFI can be neglected. Dimensionless sensitivity indices (the ratio of the relative error of BFI to the relative error of BFC or ROC) can well express the propagation of errors or uncertainties of BFC or ROC into BFI. Based on the sensitivity analysis, the uncertainty estimation method of BFI is derived. Representative sensitivity indices and BFI' uncertainties are yielded by application of the resulting equations to 24 watersheds in the United States. The results indicate that BFI is more sensitive to BFC, and the conductivity two-component hydrograph separation method may be more suitable for the long time series in a small watershed. After considering the mutual offset of the measurement errors of conductivity and streamflow, the uncertainty of BFI is reduced by half.

scholarly journals Rainstorm Magnitude Likely Regulates Event Water Fraction and Its Transit Time in Mesoscale Mountainous Catchments: Implication for Modelling Parameterization

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1169
Author(s):  
Jun-Yi Lee ◽  
Yu-Ting Shih ◽  
Chiao-Ying Lan ◽  
Tsung-Yu Lee ◽  
Tsung-Ren Peng ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Transit Time ◽  
Preferential Flow ◽  
Mean Transit Time ◽  
Time Estimation ◽  
Parameter Sensitivity ◽  
Hydrograph Separation ◽  
Water Fraction ◽  
Mountainous Catchments ◽  
Time Invariant

Event water transit time estimation has rarely been done for violent rainstorms (e.g., typhoons) in steep and fractured mountainous catchments where the range of transit time, potential controlling factors, and the validity of time-invariant parametrization are unclear. Characterized by steep landscape and torrential typhoon rainfall, Taiwan provides great opportunities for inquiring into the above questions. In this study, the hydrometrics and δ18O in rainwater and streamwater were sampled with a ~3-h interval for six typhoon events in two mesoscale catchments. The TRANSEP (transfer function hydrograph separation) model and global sensitivity analysis were applied for estimating mean transit time (MTTew) and fraction (Few) of event water and identifying the chronosequent parameter sensitivity. Results showed that the MTTew and Few varied from 2.0 to 11.0 h and from 0.2 to 0.8, respectively. Our MTTew in the mesoscale catchments is comparable with that in microscale catchments, showing a fast rainfall-runoff transfer in our steep catchments. The average rainfall intensity is a predominant indicator, which negatively affects the MTTew and positively affects the Few, likely activating preferential flow-paths and quickly transferring event water to the stream. Sensitivity analysis among inter- and intra-events demonstrates that parameter sensitivity is event-dependent and time-variant. A quick and massive subsurface flow without distinct mixing with groundwater would be triggered during large rainstorms, suggesting that time-variant parameterization should be particularly considered when estimating the MTTew in steep and fractured catchments at rainstorm scale.

scholarly journals Characterization of event water fractions and transit times under typhoon rainstorms in fractured mountainous catchments: Implications for time-variant parameterization

2019 ◽  
Author(s):  
Jun-Yi Lee ◽  
Yu-Ting Shih ◽  
Chiao-Ying Lan ◽  
Tsung-Yu Lee ◽  
Tsung-Ren Peng ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Transfer Function ◽  
Transit Time ◽  
Preferential Flow ◽  
Stream Water ◽  
Mean Transit Time ◽  
Nonlinear Behavior ◽  
Parameter Sensitivity ◽  
Hydrograph Separation ◽  
Mountainous Catchments

Abstract. Transit time with its indicative significance in regulating rainfall-runoff mechanism is a key factor for understanding many biogeochemical processes, but is rarely investigated in steep and fractured mountainous catchments. Mountainous catchments in Taiwan are characterized by active endogenic tectonics and exogenic typhoons and thus provide opportunities to explore the hydrodynamic systems over time. In this study, the hydrometrics and δ18O in rain and stream water were sampled by ~ 3-hour interval for six typhoon events in two mesoscale catchments. The TRANSEP (transfer function hydrograph separation model) and global sensitivity analysis was applied for estimating mean transit time (MTTew) and fraction (Few) of event water and identifying the chronosequent parameter sensitivity. Results show that TRANSEP could satisfactorily simulate the streamflow and δ18O change with the efficiency coefficients of from 0.85 to 0.97 and from 0.61 to 0.99, respectively. The MTTew and Few varied from 2 to 11 h and from 0.2 to 0.8, respectively. Our MTTew in the meso-scale catchments is similar with that in micro-scale catchments, showing a fast transfer in our steep catchments. The mean rainfall intensity which negatively controls on the MTTew and positively on the Few is a predominant indicator which likely activates preferential flow paths and quickly transfers event water to the stream. Sensitivity analysis among inter- and intra-events suggested that parameter sensitivity is event-depend and time-variant, affirming a nonlinear behavior in event water transfer function and time-variant parameterization should be particularly considered when estimating the MTTew in steep and fractured catchments.

scholarly journals Sensitivity Analysis for Microscopic Crowd Simulation

Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 162
Author(s):  
Marion Gödel ◽  
Rainer Fischer ◽  
Gerta Köster
Keyword(s):  
Sensitivity Analysis ◽  
Low Cost ◽  
Input Parameter ◽  
Dimensional Subspace ◽  
Crowd Simulation ◽  
Pedestrian Dynamics ◽  
Sensitivity Indices ◽  
Expensive Problems ◽  
Influential Parameters ◽  
Typical Scenario

Microscopic crowd simulation can help to enhance the safety of pedestrians in situations that range from museum visits to music festivals. To obtain a useful prediction, the input parameters must be chosen carefully. In many cases, a lack of knowledge or limited measurement accuracy add uncertainty to the input. In addition, for meaningful parameter studies, we first need to identify the most influential parameters of our parametric computer models. The field of uncertainty quantification offers standardized and fully automatized methods that we believe to be beneficial for pedestrian dynamics. In addition, many methods come at a comparatively low cost, even for computationally expensive problems. This allows for their application to larger scenarios. We aim to identify and adapt fitting methods to microscopic crowd simulation in order to explore their potential in pedestrian dynamics. In this work, we first perform a variance-based sensitivity analysis using Sobol’ indices and then crosscheck the results by a derivative-based measure, the activity scores. We apply both methods to a typical scenario in crowd simulation, a bottleneck. Because constrictions can lead to high crowd densities and delays in evacuations, several experiments and simulation studies have been conducted for this setting. We show qualitative agreement between the results of both methods. Additionally, we identify a one-dimensional subspace in the input parameter space and discuss its impact on the simulation. Moreover, we analyze and interpret the sensitivity indices with respect to the bottleneck scenario.

scholarly journals Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation

2007 ◽  
Vol 11 (2) ◽  
pp. 793-817 ◽  
Author(s):  
Y. Tang ◽  
P. Reed ◽  
T. Wagener ◽  
K. van Werkhoven
Keyword(s):  
Sensitivity Analysis ◽  
Model Identification ◽  
Local Analysis ◽  
Time Interval ◽  
Watershed Model ◽  
Soil Moisture Accounting ◽  
Analysis Methods ◽  
Accounting Model ◽  
Sobol’S Method ◽  
Comparative Results

Abstract. This study seeks to identify sensitivity tools that will advance our understanding of lumped hydrologic models for the purposes of model improvement, calibration efficiency and improved measurement schemes. Four sensitivity analysis methods were tested: (1) local analysis using parameter estimation software (PEST), (2) regional sensitivity analysis (RSA), (3) analysis of variance (ANOVA), and (4) Sobol's method. The methods' relative efficiencies and effectiveness have been analyzed and compared. These four sensitivity methods were applied to the lumped Sacramento soil moisture accounting model (SAC-SMA) coupled with SNOW-17. Results from this study characterize model sensitivities for two medium sized watersheds within the Juniata River Basin in Pennsylvania, USA. Comparative results for the 4 sensitivity methods are presented for a 3-year time series with 1 h, 6 h, and 24 h time intervals. The results of this study show that model parameter sensitivities are heavily impacted by the choice of analysis method as well as the model time interval. Differences between the two adjacent watersheds also suggest strong influences of local physical characteristics on the sensitivity methods' results. This study also contributes a comprehensive assessment of the repeatability, robustness, efficiency, and ease-of-implementation of the four sensitivity methods. Overall ANOVA and Sobol's method were shown to be superior to RSA and PEST. Relative to one another, ANOVA has reduced computational requirements and Sobol's method yielded more robust sensitivity rankings.

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