A proposed index for comparing hydrographs

McCuen, Richard H.; Snyder, Willard M.

doi:10.1029/wr011i006p01021

Cited by 67 publications

(41 citation statements)

References 4 publications

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“…3a and b show the overall Nash-Sutcliffe efficiency (Nash and Sutcliffe, 1970) for uncalibrated and calibrated models respectively for all basins while Fig. 4a and b show the overall modified correlation coefficients, r mod (McCuen and Snyder, 1975;Smith et al, 2004b). Tables 9 and 10 Note that the results labeled 'Watts4' and 'Savoy4' shown in Figs.…”

Section: Overall Statisticsmentioning

confidence: 95%

Overall distributed model intercomparison project results

Reed¹,

Koren²,

Smith³

et al. 2004

Journal of Hydrology

467

350

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Section: Overall Statisticsmentioning

confidence: 95%

Overall distributed model intercomparison project results

Reed¹,

Koren²,

Smith³

et al. 2004

Journal of Hydrology

467

350

View full text Add to dashboard Cite

“…Another measure of goodness-of-fit is the modified correlation coefficient, R m , which is equivalent to the correlation coefficient multiplied by a factor, min a, b / max a, b , that incorporates the water budget balance (McCuen and Snyder, 1975).…”

Section: Continuous Streamflow Model Calibrationmentioning

confidence: 99%

The effect of climate and land use change on flow duration in the Maryland Piedmont region

Hejazi

Moglen

2008

Hydrological Processes

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Abstract:This paper describes the use of a continuous streamflow model to examine the effects of climate and land use change on flow duration in six urbanizing watersheds in the Maryland Piedmont region. The hydrologic model is coupled with an optimization routine to achieve an agreement between observed and simulated streamflow. Future predictions are made for three scenarios: future climate change, land use change, and jointly varying climate and land use. Future climate is modelled using precipitation and temperature predictions for the Canadian Climate Centre (CCC) and Hadley climate models. Results show that a significant increase in temperature under the CCC climate predictions produces a decreasing trend in low flows. A significant increasing trend in precipitation under the Hadley climate predictions produces an increasing trend in peak flows. Land use change by itself, as simulated by an additional 10% increase in imperviousness (from 20Ð5 to 30Ð5%), produces no significant changes in the simulated flow durations. However, coupling the effects of land use change with climate change leads to more significant decreasing trends in low flows under the CCC climate predictions and more significant increasing trends in peak flows under Hadley climate predictions than when climate change alone is employed. These findings indicate that combined land use and climate change can result in more significant hydrologic change than either driver acting alone.

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“…[28] Four additional criteria were used in manual selection of a single compromise solution from the set of nondominated solutions: the percentage volume bias (PVB) (equation (7)) [Boyle et al, 2000], the modified correlation coefficient (MCC) (equation (9)) McCuen and Snyder, 1975], the cumulative sum of absolute monthly volume bias (CMVB) (equation (11)), and the difference between the observed and simulated variance (Ds 2 ):…”

Section: Methods For Multiple-criteria Optimizationmentioning

confidence: 99%

On the use of spatial regularization strategies to improve calibration of distributed watershed models

Pokhrel

Gupta

2010

Water Resources Research

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[1] Hydrologic models require the specification of unknown model parameters via calibration to historical input-output data. For spatially distributed models, the large number of unknowns makes the calibration problem poorly conditioned. Spatial regularization can help to stabilize the problem by facilitating inclusion of additional information. While a common regularization approach is to apply a scalar multiplier to the prior estimate of each parameter field, this can cause problems by simultaneously changing both the mean and the variance of the distribution. This paper explores a multiple-criteria regularization approach that facilitates adjustment of the mean, variance, and shape of the parameter distribution, using prior information to constrain the problem while providing sufficient degrees of freedom to enable model performance improvements. We also test simple squashing functions to help in maintaining conceptually reasonable parameter values throughout the spatial domain. We apply the method to three basins in the context of the Distributed Model Intercomparison Project (DMIP2), obtaining considerable performance improvements at the basin outlet. However, the prior parameter estimates are found to give much better performance at the interior points (treated as ungauged), suggesting that the spatial information has not been properly exploited. The results also suggest that basin outlet hydrographs may not be particularly sensitive to spatial parameter variability and that an overall basin mean value may be sufficient for flow forecasting at the outlet, although not at the interior points. We discuss weaknesses in our study approach and suggest diagnostically more powerful strategies to be pursued.Citation: Pokhrel, P., and H. V. Gupta (2010), On the use of spatial regularization strategies to improve calibration of distributed watershed models, Water Resour. Res., 46, W01505,

show abstract

A proposed index for comparing hydrographs

Cited by 67 publications

References 4 publications

Overall distributed model intercomparison project results

Overall distributed model intercomparison project results

The effect of climate and land use change on flow duration in the Maryland Piedmont region

On the use of spatial regularization strategies to improve calibration of distributed watershed models

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