Assignment - AWBM modeling
AWBM Familiarisation Activity - Jardine River
This activity is assessable and is included as a way for you to trial the RRL software before embarking on the full calibration exercise (See Section 3). Refer to Section 4 on the submission requirements for this part of the assignment.
Open the Jardine River project file (AWBM_Jardine.jobf) and use the RRL software to complete the following:
1. For the available data from 1974 to 1989, what is the average annual rainfall, evapotranspiration and observed runoff for the Jardine River?
2. Setup the following simulation periods: Warmup from 1 January 1974 to 31 December 1974 and a calibration period to 31 December 1986. Use the SCE-UA optimisation method and the RMSE objective function to optimise the AWBM. What are the AWBM calibrated parameter values that are generated from this optimisation? In terms of the degree of fit with the observed data, what are the RMSE, Nash-Sutcliffe E and Coefficient of Determination (Correlation) values?
3. Extract a scatter plot of monthly observed and predicted runoff. Also provide a 'zoomed in' plot of observed and calculated runoffs covering the 1976 wet season.
As well as becoming familiar with the use of RRL, you should also understand the AWBM model algorithms (see good modelling practice Module 2.4). In particular, you should gain an appreciation of how the model results change when a parameter value is adjusted (see the 'electronic control box' analogy Module 2.3). This understanding will assist you in calibrating the AWBM to measured streamflows. Complete the following:
4. The scatter plot and 1976 wet season plot generated from the above Step 3 provides a benchmark or starting point to compare how the AWBM streamflows may change in response to adjustment of the AWBM parameters. The total runoff which can be found under Data Statistics is also a useful measure of model results.
5. Taking each AWBM parameter in turn, rerun the AWBM with a higher and lower parameter value and regenerate the above outputs. Keep the values of the other parameters constant, so the effect of the selected AWBM parameter is isolated. You may need to substantially vary some parameters.
6. Describe the effect of adjusting each AWBM parameter on the plotted results. Describe, based on your knowledge of the AWBM model structure, why this effect has occurred.
Attachment:- Assignment.rar