Overview:
The Lower Nooksack Water Budget is calculated using a numerical simulation model called Topnet-WM. This hydrologic model uses data distributed in space and time to determine the flow of water between various locations and points in time on a daily time step. The modeling of the watershed is limited by the representation of hydrologic processes built into the model, the spatial data used to parameterize the model, and the climate time series data which provides the daily water inputs to the model. To address the limits of our data and knowledge of the system, parameters are used to control the relationships among hydrologic processes and the data used to represent them. In model calibration, parameters are changed within a range of expected values so that the model representation results in modeled streamflow that closely matches observed streamflow. The calibration parameters used include: saturated soil store sensitivity, hydraulic conductivity, overland flow velocity, transmissivity, and impervious surface fraction. The saturated soil store sensitivity, or f parameter, is the most sensitive parameter in this model. It is a measure of the sensitivity of lateral groundwater flow to changes in groundwater level.

The process of model calibration is complex because of limitations in models, input and output data, mathematical structure of the models, and quantitative methods used to fit the model to the data, as well as imperfect knowledge of basin characteristics (Schaake, 2003). In a world of perfect understanding of hydrologic processes, perfect input data, and no scale discrepancy between modeled and measured data, it might be possible to avoid hydrologic model calibration. An important result from the National Weather Service Distributed Model Intercomparison Project (DMIP; Smith et al., 2004a) experiment was the acknowledgement that uncalibrated models do not have the benefit of accounting for the known biases in the rainfall archives over the calibration period. Only in the absence of precipitation and other data input biases, might uncalibrated models be able to outperform calibrated models (Reed et al., 2004). Errors in input data cannot be ignored (Gupta et al., 1998), and therefore model calibration cannot be avoided.

Past work by the Lower Nooksack Water Budget Project Team has examined ways to improve the use of streamflow data that are available within a watershed and that can be used for model calibration, especially to improve the model performance where streamflow data are not available (Bandaragoda et al., 2004; Bandaragoda, 2007; Bandaragoda and Greenberg, 2009; Bandaragoda, 2008; Bandaragoda and Nielson, 2011, Neilson et al., 2010, Tarboton, 2007). The primary calibration locations in this project focused on Fishtrap Creek, Bertrand Creek and Tenmile Creek, with verification at Nooksack River locations at Cedarville and Ferndale.

In hydrologic model calibration, streamflow prediction statistics can be used as a measure of model performance, but the calibration must also address issues relevant to understanding the heterogeneity of the hydrologic system and the unique locations that are modeled. Implemented carefully, automatic calibration techniques that employ multiple objectives and estimates of distributions of watershed parameters may be a step towards both improving models and understanding hydrologic processes.

As calibration is used to conduct diagnostic model analysis and interactive learning about watersheds, our understanding of how to best model the movement of water can increase, and lead to an improvement in our existing models. As the existing models develop, the reliance on calibration will decrease, development of new models will increase, and our predictions of streamflow will improve.

This resource is a subset of the Lower Nooksack Water Budget (LNWB) Collection Resource.