Model Calibration Criteria for Estimating Ecological Flow Characteristics

Water

Marc Vis¹  Rodney Knight²  Sandra Pool¹  William Wolfe²  Jan Seibert¹ 

[1] Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; E-Mails:;U.S. Geological Survey Lower Mississippi—Gulf Water Science Center, 640 Grassmere Park, Suite 100, Nashville, TN 37211, USA; E-Mails:

关键词: hydrological modeling;    ecological flow characteristics;    objective functions;    model calibration;    parameter uncertainty;    catchments;   

DOI  :  10.3390/w7052358

来源: mdpi

【 摘 要 】

Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those envisioned by the modelers. While the estimation of model parameters for ungauged catchments is a challenging research task in itself, it is important to evaluate whether simulated time series preserve critical aspects of the streamflow hydrograph. To address this question, seven calibration objective functions were evaluated for their ability to preserve ecologically relevant streamflow characteristics of the average annual hydrograph using a runoff model, HBV-light, at 27 catchments in the southeastern United States. Calibration trials were repeated 100 times to reduce parameter uncertainty effects on the results, and 12 ecological flow characteristics were computed for comparison. Our results showed that the most suitable calibration strategy varied according to streamflow characteristic. Combined objective functions generally gave the best results, though a clear underprediction bias was observed. The occurrence of low prediction errors for certain combinations of objective function and flow characteristic suggests that (1) incorporating multiple ecological flow characteristics into a single objective function would increase model accuracy, potentially benefitting decision-making processes; and (2) there may be a need to have different objective functions available to address specific applications of the predicted time series.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.