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Moradkhani, H. and Sorooshian, S. (2008) General Review of Rainfall-Runoff Modeling: Model Calibration, Data Assimilation, and Uncertainty Analysis. In: Sorooshian, S., Hsu, K.-L., Coppola, E., Tomassetti, B., Verdecchia, M. and Visconti, G., Eds., Hydrological Modelling and the Water Cycle: Coupling the Atmospheric and Hydrological Models, Water Science and Technology Library, Springer, Berlin, Heidelberg, 1-24.
https://doi.org/10.1007/978-3-540-77843-1_1

has been cited by the following article:

• TITLE: Verification of the MIKE11-NAM Model for Simulating Streamflow

  AUTHORS: Fitsum T. Teshome, Haimanote K. Bayabil, L. N. Thakural, Fikadu G. Welidehanna

  KEYWORDS: Lumped Conceptual Model, MIKE 11-NAM, Sensitivity Analysis, Rainfall-Runoff Modeling

  JOURNAL NAME: Journal of Environmental Protection, Vol.11 No.2, February 28, 2020

  ABSTRACT: Modeling watershed hydrological processes are important for water resources planning, development, and management. In this study, the MIKE 11-NAM (Nedbor-Afstromings Model model) was evaluated for simulation of streamflow from the Bina basin located in the Madhya Pradesh State of India. The model was calibrated and validated on a daily basis using five years (1994-1998) observed hydrological data. In addition, a model sensitivity analysis was performed on nine MIKE 11-NAM parameters to identify sensitive model parameters. Statistical and graphical approaches were used to assess the performance of the model in simulating the streamflow of the basin. Results show that during daily model calibration, the model performed very well with a coefficient of determination (R2) and the percentage of water balance error (WBL) values 0.87% and -8.63%, respectively. In addition, the model performed good during the validation period with R2 and WBL values of 0.68% and -6.72%, respectively. Model sensitivity analysis results showed that Overland flow runoff coefficient (CQOF), Time constant for routing overland flow (CK1,2) and Maximum water content in root zone storage (Lmax) were found as the most influential and sensitive model parameters for simulating streamflow. Overall, the model’s performance was satisfactory based on R2 and EI metrics.